An Energy-Efficient Spectrum-Aware Reinforcement Learning-Based Clustering Algorithm for Cognitive Radio Sensor Networks

PubMed Central

Mustapha, Ibrahim; Ali, Borhanuddin Mohd; Rasid, Mohd Fadlee A.; Sali, Aduwati; Mohamad, Hafizal

2015-01-01

It is well-known that clustering partitions network into logical groups of nodes in order to achieve energy efficiency and to enhance dynamic channel access in cognitive radio through cooperative sensing. While the topic of energy efficiency has been well investigated in conventional wireless sensor networks, the latter has not been extensively explored. In this paper, we propose a reinforcement learning-based spectrum-aware clustering algorithm that allows a member node to learn the energy and cooperative sensing costs for neighboring clusters to achieve an optimal solution. Each member node selects an optimal cluster that satisfies pairwise constraints, minimizes network energy consumption and enhances channel sensing performance through an exploration technique. We first model the network energy consumption and then determine the optimal number of clusters for the network. The problem of selecting an optimal cluster is formulated as a Markov Decision Process (MDP) in the algorithm and the obtained simulation results show convergence, learning and adaptability of the algorithm to dynamic environment towards achieving an optimal solution. Performance comparisons of our algorithm with the Groupwise Spectrum Aware (GWSA)-based algorithm in terms of Sum of Square Error (SSE), complexity, network energy consumption and probability of detection indicate improved performance from the proposed approach. The results further reveal that an energy savings of 9% and a significant Primary User (PU) detection improvement can be achieved with the proposed approach. PMID:26287191

An Energy-Efficient Spectrum-Aware Reinforcement Learning-Based Clustering Algorithm for Cognitive Radio Sensor Networks.

PubMed

Mustapha, Ibrahim; Mohd Ali, Borhanuddin; Rasid, Mohd Fadlee A; Sali, Aduwati; Mohamad, Hafizal

2015-08-13

It is well-known that clustering partitions network into logical groups of nodes in order to achieve energy efficiency and to enhance dynamic channel access in cognitive radio through cooperative sensing. While the topic of energy efficiency has been well investigated in conventional wireless sensor networks, the latter has not been extensively explored. In this paper, we propose a reinforcement learning-based spectrum-aware clustering algorithm that allows a member node to learn the energy and cooperative sensing costs for neighboring clusters to achieve an optimal solution. Each member node selects an optimal cluster that satisfies pairwise constraints, minimizes network energy consumption and enhances channel sensing performance through an exploration technique. We first model the network energy consumption and then determine the optimal number of clusters for the network. The problem of selecting an optimal cluster is formulated as a Markov Decision Process (MDP) in the algorithm and the obtained simulation results show convergence, learning and adaptability of the algorithm to dynamic environment towards achieving an optimal solution. Performance comparisons of our algorithm with the Groupwise Spectrum Aware (GWSA)-based algorithm in terms of Sum of Square Error (SSE), complexity, network energy consumption and probability of detection indicate improved performance from the proposed approach. The results further reveal that an energy savings of 9% and a significant Primary User (PU) detection improvement can be achieved with the proposed approach.

Optimization and performance improvement of an electromagnetic-type energy harvester with consideration of human walking vibration

NASA Astrophysics Data System (ADS)

Seo, Jongho; Kim, Jin-Su; Jeong, Un-Chang; Kim, Yong-Dae; Kim, Young-Cheol; Lee, Hanmin; Oh, Jae-Eung

2016-02-01

In this study, we derived an equation of motion for an electromechanical system in view of the components and working mechanism of an electromagnetic-type energy harvester (ETEH). An electromechanical transduction factor (ETF) was calculated using a finite-element analysis (FEA) based on Maxwell's theory. The experimental ETF of the ETEH measured by means of sine wave excitation was compared with and FEA data. Design parameters for the stationary part of the energy harvester were optimized in terms of the power performance by using a response surface method (RSM). With optimized design parameters, the ETEH showed an improvement in performance. We experimented with the optimized ETEH (OETEH) with respect to changes in the external excitation frequency and the load resistance by taking human body vibration in to account. The OETEH achieved a performance improvement of about 30% compared to the initial model.

Optimization for energy efficiency of underground building envelope thermal performance in different climate zones of China

NASA Astrophysics Data System (ADS)

Shi, Luyang; Liu, Jing; Zhang, Huibo

2017-11-01

The object of this article is to investigate the influence of thermal performance of envelopes in shallow-buried buildings on energy consumption for different climate zones of China. For the purpose of this study, an effective building energy simulation tool (DeST) developed by Tsinghua University was chosen to model the heat transfer in underground buildings. Based on the simulative results, energy consumption for heating and cooling for the whole year was obtained. The results showed that the relationship between energy consumption and U-value of envelopes for underground buildings is different compared with above-ground buildings: improving thermal performance of exterior walls cannot reduce energy consumption, on the contrary, may result in more energy cost. Besides, it is can be derived that optimized U-values of underground building envelopes vary with climate zones of China in this study. For severe cold climate zone, the optimized U-value of underground building envelopes is 0.8W/(m2·K); for cold climate zone, the optimized U-value is 1.5W/(m2·K); for warm climate zone, the U-value is 2.0W/(m2·K).

Control strategy optimization of HVAC plants

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

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

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

Staircase Quantum Dots Configuration in Nanowires for Optimized Thermoelectric Power

PubMed Central

Li, Lijie; Jiang, Jian-Hua

2016-01-01

The performance of thermoelectric energy harvesters can be improved by nanostructures that exploit inelastic transport processes. One prototype is the three-terminal hopping thermoelectric device where electron hopping between quantum-dots are driven by hot phonons. Such three-terminal hopping thermoelectric devices have potential in achieving high efficiency or power via inelastic transport and without relying on heavy-elements or toxic compounds. We show in this work how output power of the device can be optimized via tuning the number and energy configuration of the quantum-dots embedded in parallel nanowires. We find that the staircase energy configuration with constant energy-step can improve the power factor over a serial connection of a single pair of quantum-dots. Moreover, for a fixed energy-step, there is an optimal length for the nanowire. Similarly for a fixed number of quantum-dots there is an optimal energy-step for the output power. Our results are important for future developments of high-performance nanostructured thermoelectric devices. PMID:27550093

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

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

Spatio-temporal modeling and optimization of a deformable-grating compressor for short high-energy laser pulses

DOE PAGES

Qiao, Jie; Papa, J.; Liu, X.

2015-09-24

Monolithic large-scale diffraction gratings are desired to improve the performance of high-energy laser systems and scale them to higher energy, but the surface deformation of these diffraction gratings induce spatio-temporal coupling that is detrimental to the focusability and compressibility of the output pulse. A new deformable-grating-based pulse compressor architecture with optimized actuator positions has been designed to correct the spatial and temporal aberrations induced by grating wavefront errors. An integrated optical model has been built to analyze the effect of grating wavefront errors on the spatio-temporal performance of a compressor based on four deformable gratings. Moreover, a 1.5-meter deformable gratingmore » has been optimized using an integrated finite-element-analysis and genetic-optimization model, leading to spatio-temporal performance similar to the baseline design with ideal gratings.« less

Rapid Deployment of Optimal Control for Building HVAC Systems using Innovative Software Tools and a Hybrid Heuristic/Model Based Control Approach

DTIC Science & Technology

2017-03-21

Energy and Water Projects March 21, 2017 REPORT DOCUMENTATION PAGE Form Approved OMB No. 0704-0188 Public reporting burden for this collection of...included reduced system energy use and cost as well as improved performance driven by autonomous commissioning and optimized system control. In the end...improve system performance and reduce energy use and cost. However, implementing these solutions into the extremely heterogeneous and often

Optimal control of 2-wheeled mobile robot at energy performance index

NASA Astrophysics Data System (ADS)

Kaliński, Krzysztof J.; Mazur, Michał

2016-03-01

The paper presents the application of the optimal control method at the energy performance index towards motion control of the 2-wheeled mobile robot. With the use of the proposed method of control the 2-wheeled mobile robot can realise effectively the desired trajectory. The problem of motion control of mobile robots is usually neglected and thus performance of the realisation of the high level control tasks is limited.

An Enhanced PSO-Based Clustering Energy Optimization Algorithm for Wireless Sensor Network.

PubMed

Vimalarani, C; Subramanian, R; Sivanandam, S N

2016-01-01

Wireless Sensor Network (WSN) is a network which formed with a maximum number of sensor nodes which are positioned in an application environment to monitor the physical entities in a target area, for example, temperature monitoring environment, water level, monitoring pressure, and health care, and various military applications. Mostly sensor nodes are equipped with self-supported battery power through which they can perform adequate operations and communication among neighboring nodes. Maximizing the lifetime of the Wireless Sensor networks, energy conservation measures are essential for improving the performance of WSNs. This paper proposes an Enhanced PSO-Based Clustering Energy Optimization (EPSO-CEO) algorithm for Wireless Sensor Network in which clustering and clustering head selection are done by using Particle Swarm Optimization (PSO) algorithm with respect to minimizing the power consumption in WSN. The performance metrics are evaluated and results are compared with competitive clustering algorithm to validate the reduction in energy consumption.

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

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

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

2014-08-01

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

Exploring performance and energy tradeoffs for irregular applications: A case study on the Tilera many-core architecture

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

Panyala, Ajay; Chavarría-Miranda, Daniel; Manzano, Joseph B.

High performance, parallel applications with irregular data accesses are becoming a critical workload class for modern systems. In particular, the execution of such workloads on emerging many-core systems is expected to be a significant component of applications in data mining, machine learning, scientific computing and graph analytics. However, power and energy constraints limit the capabilities of individual cores, memory hierarchy and on-chip interconnect of such systems, thus leading to architectural and software trade-os that must be understood in the context of the intended application’s behavior. Irregular applications are notoriously hard to optimize given their data-dependent access patterns, lack of structuredmore » locality and complex data structures and code patterns. We have ported two irregular applications, graph community detection using the Louvain method (Grappolo) and high-performance conjugate gradient (HPCCG), to the Tilera many-core system and have conducted a detailed study of platform-independent and platform-specific optimizations that improve their performance as well as reduce their overall energy consumption. To conduct this study, we employ an auto-tuning based approach that explores the optimization design space along three dimensions - memory layout schemes, GCC compiler flag choices and OpenMP loop scheduling options. We leverage MIT’s OpenTuner auto-tuning framework to explore and recommend energy optimal choices for different combinations of parameters. We then conduct an in-depth architectural characterization to understand the memory behavior of the selected workloads. Finally, we perform a correlation study to demonstrate the interplay between the hardware behavior and application characteristics. Using auto-tuning, we demonstrate whole-node energy savings and performance improvements of up to 49:6% and 60% relative to a baseline instantiation, and up to 31% and 45:4% relative to manually optimized variants.« less

Optimizing physical energy functions for protein folding.

PubMed

Fujitsuka, Yoshimi; Takada, Shoji; Luthey-Schulten, Zaida A; Wolynes, Peter G

2004-01-01

We optimize a physical energy function for proteins with the use of the available structural database and perform three benchmark tests of the performance: (1) recognition of native structures in the background of predefined decoy sets of Levitt, (2) de novo structure prediction using fragment assembly sampling, and (3) molecular dynamics simulations. The energy parameter optimization is based on the energy landscape theory and uses a Monte Carlo search to find a set of parameters that seeks the largest ratio deltaE(s)/DeltaE for all proteins in a training set simultaneously. Here, deltaE(s) is the stability gap between the native and the average in the denatured states and DeltaE is the energy fluctuation among these states. Some of the energy parameters optimized are found to show significant correlation with experimentally observed quantities: (1) In the recognition test, the optimized function assigns the lowest energy to either the native or a near-native structure among many decoy structures for all the proteins studied. (2) Structure prediction with the fragment assembly sampling gives structure models with root mean square deviation less than 6 A in one of the top five cluster centers for five of six proteins studied. (3) Structure prediction using molecular dynamics simulation gives poorer performance, implying the importance of having a more precise description of local structures. The physical energy function solely inferred from a structural database neither utilizes sequence information from the family of the target nor the outcome of the secondary structure prediction but can produce the correct native fold for many small proteins. Copyright 2003 Wiley-Liss, Inc.

Optimizing lighting, thermal performance, and energy production of building facades by using automated blinds and PV cells

NASA Astrophysics Data System (ADS)

Alzoubi, Hussain Hendi

Energy consumption in buildings has recently become a major concern for environmental designers. Within this field, daylighting and solar energy design are attractive strategies for saving energy. This study seeks the integrity and the optimality of building envelopes' performance. It focuses on the transparent parts of building facades, specifically, the windows and their shading devices. It suggests a new automated method of utilizing solar energy while keeping optimal solutions for indoor daylighting. The method utilizes a statistical approach to produce mathematical equations based on physical experimentation. A full-scale mock-up representing an actual office was built. Heat gain and lighting levels were measured empirically and correlated with blind angles. Computational methods were used to estimate the power production from photovoltaic cells. Mathematical formulas were derived from the results of the experiments; these formulas were utilized to construct curves as well as mathematical equations for the purpose of optimization. The mathematical equations resulting from the optimization process were coded using Java programming language to enable future users to deal with generic locations of buildings with a broader context of various climatic conditions. For the purpose of optimization by automation under different climatic conditions, a blind control system was developed based on the findings of this study. This system calibrates the blind angles instantaneously based upon the sun position, the indoor daylight, and the power production from the photovoltaic cells. The functions of this system guarantee full control of the projected solar energy on buildings' facades for indoor lighting and heat gain. In winter, the system automatically blows heat into the space, whereas it expels heat from the space during the summer season. The study showed that the optimality of building facades' performance is achievable for integrated thermal, energy, and lighting models in buildings. There are blind angles that produce maximum energy from the photovoltaic cells while keeping indoor light within the acceptable limits that prevent undesired heat gain in summer.

Energy Optimal Path Planning: Integrating Coastal Ocean Modelling with Optimal Control

NASA Astrophysics Data System (ADS)

Subramani, D. N.; Haley, P. J., Jr.; Lermusiaux, P. F. J.

2016-02-01

A stochastic optimization methodology is formulated for computing energy-optimal paths from among time-optimal paths of autonomous vehicles navigating in a dynamic flow field. To set up the energy optimization, the relative vehicle speed and headings are considered to be stochastic, and new stochastic Dynamically Orthogonal (DO) level-set equations that govern their stochastic time-optimal reachability fronts are derived. Their solution provides the distribution of time-optimal reachability fronts and corresponding distribution of time-optimal paths. An optimization is then performed on the vehicle's energy-time joint distribution to select the energy-optimal paths for each arrival time, among all stochastic time-optimal paths for that arrival time. The accuracy and efficiency of the DO level-set equations for solving the governing stochastic level-set reachability fronts are quantitatively assessed, including comparisons with independent semi-analytical solutions. Energy-optimal missions are studied in wind-driven barotropic quasi-geostrophic double-gyre circulations, and in realistic data-assimilative re-analyses of multiscale coastal ocean flows. The latter re-analyses are obtained from multi-resolution 2-way nested primitive-equation simulations of tidal-to-mesoscale dynamics in the Middle Atlantic Bight and Shelbreak Front region. The effects of tidal currents, strong wind events, coastal jets, and shelfbreak fronts on the energy-optimal paths are illustrated and quantified. Results showcase the opportunities for longer-duration missions that intelligently utilize the ocean environment to save energy, rigorously integrating ocean forecasting with optimal control of autonomous vehicles.

Optimal Force Control of Vibro-Impact Systems for Autonomous Drilling Applications

NASA Technical Reports Server (NTRS)

Aldrich, Jack B.; Okon, Avi B.

2012-01-01

The need to maintain optimal energy efficiency is critical during the drilling operations performed on future and current planetary rover missions (see figure). Specifically, this innovation seeks to solve the following problem. Given a spring-loaded percussive drill driven by a voice-coil motor, one needs to determine the optimal input voltage waveform (periodic function) and the optimal hammering period that minimizes the dissipated energy, while ensuring that the hammer-to-rock impacts are made with sufficient (user-defined) impact velocity (or impact energy). To solve this problem, it was first observed that when voice-coil-actuated percussive drills are driven at high power, it is of paramount importance to ensure that the electrical current of the device remains in phase with the velocity of the hammer. Otherwise, negative work is performed and the drill experiences a loss of performance (i.e., reduced impact energy) and an increase in Joule heating (i.e., reduction in energy efficiency). This observation has motivated many drilling products to incorporate the standard bang-bang control approach for driving their percussive drills. However, the bang-bang control approach is significantly less efficient than the optimal energy-efficient control approach solved herein. To obtain this solution, the standard tools of classical optimal control theory were applied. It is worth noting that these tools inherently require the solution of a two-point boundary value problem (TPBVP), i.e., a system of differential equations where half the equations have unknown boundary conditions. Typically, the TPBVP is impossible to solve analytically for high-dimensional dynamic systems. However, for the case of the spring-loaded vibro-impactor, this approach yields the exact optimal control solution as the sum of four analytic functions whose coefficients are determined using a simple, easy-to-implement algorithm. Once the optimal control waveform is determined, it can be used optimally in the context of both open-loop and closed-loop control modes (using standard realtime control hardware).

Investigation of Cost and Energy Optimization of Drinking Water Distribution Systems.

PubMed

Cherchi, Carla; Badruzzaman, Mohammad; Gordon, Matthew; Bunn, Simon; Jacangelo, Joseph G

2015-11-17

Holistic management of water and energy resources through energy and water quality management systems (EWQMSs) have traditionally aimed at energy cost reduction with limited or no emphasis on energy efficiency or greenhouse gas minimization. This study expanded the existing EWQMS framework and determined the impact of different management strategies for energy cost and energy consumption (e.g., carbon footprint) reduction on system performance at two drinking water utilities in California (United States). The results showed that optimizing for cost led to cost reductions of 4% (Utility B, summer) to 48% (Utility A, winter). The energy optimization strategy was successfully able to find the lowest energy use operation and achieved energy usage reductions of 3% (Utility B, summer) to 10% (Utility A, winter). The findings of this study revealed that there may be a trade-off between cost optimization (dollars) and energy use (kilowatt-hours), particularly in the summer, when optimizing the system for the reduction of energy use to a minimum incurred cost increases of 64% and 184% compared with the cost optimization scenario. Water age simulations through hydraulic modeling did not reveal any adverse effects on the water quality in the distribution system or in tanks from pump schedule optimization targeting either cost or energy minimization.

Optimal Energy Management for Microgrids

NASA Astrophysics Data System (ADS)

Zhao, Zheng

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

Economic Evaluation of Dual-Level-Residence Solar-Energy System

NASA Technical Reports Server (NTRS)

1982-01-01

105-page report is one in a series of economic evaluations of different solar-energy installations. Using study results, an optimal collector area is chosen that minimizes life-cycle costs. From this optimal size thermal and economic performance is evaluated.

The assessment of global thermo-energy performances of existing district heating systems optimized by harnessing renewable energy sources

NASA Astrophysics Data System (ADS)

Şoimoşan, Teodora M.; Danku, Gelu; Felseghi, Raluca A.

2017-12-01

Within the thermo-energy optimization process of an existing heating system, the increase of the system's energy efficiency and speeding-up the transition to green energy use are pursued. The concept of multi-energy district heating system, with high harnessing levels of the renewable energy sources (RES) in order to produce heat, is expected to be the key-element in the future urban energy infrastructure, due to the important role it can have in the strategies of optimizing and decarbonizing the existing district heating systems. The issues that arise are related to the efficient integration of different technologies of harnessing renewable energy sources in the energy mix and to the increase of the participation levels of RES, respectively. For the holistic modeling of the district heating system, the concept of the energy hub was used, where the synergy of different primary forms of entered energy provides the system a high degree energy security and flexibility in operation. The optimization of energy flows within the energy hub allows the optimization of the thermo-energy district system in order to approach the dual concept of smart city & smart energy.

Facilities | Integrated Energy Solutions | NREL

Science.gov Websites

strategies needed to optimize our entire energy system. A photo of the high-performance computer at NREL . High-Performance Computing Data Center High-performance computing facilities at NREL provide high-speed

Evaluation of solar thermal power plants using economic and performance simulations

NASA Technical Reports Server (NTRS)

El-Gabawali, N.

1980-01-01

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

Exploiting variability for energy optimization of parallel programs

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

Lavrijsen, Wim; Iancu, Costin; de Jong, Wibe

2016-04-18

Here in this paper we present optimizations that use DVFS mechanisms to reduce the total energy usage in scientific applications. Our main insight is that noise is intrinsic to large scale parallel executions and it appears whenever shared resources are contended. The presence of noise allows us to identify and manipulate any program regions amenable to DVFS. When compared to previous energy optimizations that make per core decisions using predictions of the running time, our scheme uses a qualitative approach to recognize the signature of executions amenable to DVFS. By recognizing the "shape of variability" we can optimize codes withmore » highly dynamic behavior, which pose challenges to all existing DVFS techniques. We validate our approach using offline and online analyses for one-sided and two-sided communication paradigms. We have applied our methods to NWChem, and we show best case improvements in energy use of 12% at no loss in performance when using online optimizations running on 720 Haswell cores with one-sided communication. With NWChem on MPI two-sided and offline analysis, capturing the initialization, we find energy savings of up to 20%, with less than 1% performance cost.« less

Simulation and optimization of a dc SQUID with finite capacitance

NASA Astrophysics Data System (ADS)

de Waal, V. J.; Schrijner, P.; Llurba, R.

1984-02-01

This paper deals with the calculations of the noise and the optimization of the energy resolution of a dc SQUID with finite junction capacitance. Up to now noise calculations of dc SQUIDs were performed using a model without parasitic capacitances across the Josephson junctions. As the capacitances limit the performance of the SQUID, for a good optimization one must take them into account. The model consists of two coupled nonlinear second-order differential equations. The equations are very suitable for simulation with an analog circuit. We implemented the model on a hybrid computer. The noise spectrum from the model is calculated with a fast Fourier transform. A calculation of the energy resolution for one set of parameters takes about 6 min of computer time. Detailed results of the optimization are given for products of inductance and temperature of LT=1.2 and 5 nH K. Within a range of β and β c between 1 and 2, which is optimum, the energy resolution is nearly independent of these variables. In this region the energy resolution is near the value calculated without parasitic capacitances. Results of the optimized energy resolution are given as a function of LT between 1.2 and 10 mH K.

Design optimization of a fuzzy distributed generation (DG) system with multiple renewable energy sources

NASA Astrophysics Data System (ADS)

Ganesan, T.; Elamvazuthi, I.; Shaari, Ku Zilati Ku; Vasant, P.

2012-09-01

The global rise in energy demands brings major obstacles to many energy organizations in providing adequate energy supply. Hence, many techniques to generate cost effective, reliable and environmentally friendly alternative energy source are being explored. One such method is the integration of photovoltaic cells, wind turbine generators and fuel-based generators, included with storage batteries. This sort of power systems are known as distributed generation (DG) power system. However, the application of DG power systems raise certain issues such as cost effectiveness, environmental impact and reliability. The modelling as well as the optimization of this DG power system was successfully performed in the previous work using Particle Swarm Optimization (PSO). The central idea of that work was to minimize cost, minimize emissions and maximize reliability (multi-objective (MO) setting) with respect to the power balance and design requirements. In this work, we introduce a fuzzy model that takes into account the uncertain nature of certain variables in the DG system which are dependent on the weather conditions (such as; the insolation and wind speed profiles). The MO optimization in a fuzzy environment was performed by applying the Hopfield Recurrent Neural Network (HNN). Analysis on the optimized results was then carried out.

CPAC: Energy-Efficient Data Collection through Adaptive Selection of Compression Algorithms for Sensor Networks

PubMed Central

Lee, HyungJune; Kim, HyunSeok; Chang, Ik Joon

2014-01-01

We propose a technique to optimize the energy efficiency of data collection in sensor networks by exploiting a selective data compression. To achieve such an aim, we need to make optimal decisions regarding two aspects: (1) which sensor nodes should execute compression; and (2) which compression algorithm should be used by the selected sensor nodes. We formulate this problem into binary integer programs, which provide an energy-optimal solution under the given latency constraint. Our simulation results show that the optimization algorithm significantly reduces the overall network-wide energy consumption for data collection. In the environment having a stationary sink from stationary sensor nodes, the optimized data collection shows 47% energy savings compared to the state-of-the-art collection protocol (CTP). More importantly, we demonstrate that our optimized data collection provides the best performance in an intermittent network under high interference. In such networks, we found that the selective compression for frequent packet retransmissions saves up to 55% energy compared to the best known protocol. PMID:24721763

Design of a Conceptual Bumper Energy Absorber Coupling Pedestrian Safety and Low-Speed Impact Requirements

PubMed Central

Mo, Fuhao; Zhao, Siqi; Yu, Chuanhui; Duan, Shuyong

2018-01-01

The car front bumper system needs to meet the requirements of both pedestrian safety and low-speed impact which are somewhat contradicting. This study aims to design a new kind of modular self-adaptive energy absorber of the front bumper system which can balance the two performances. The X-shaped energy-absorbing structure was proposed which can enhance the energy absorption capacity during impact by changing its deformation mode based on the amount of external collision energy. Then, finite element simulations with a realistic vehicle bumper system are performed to demonstrate its crashworthiness in comparison with the traditional foam energy absorber, which presents a significant improvement of the two performances. Furthermore, the structural parameters of the X-shaped energy-absorbing structure including thickness (t u), side arc radius (R), and clamping boost beam thickness (t b) are analyzed using a full factorial method, and a multiobjective optimization is implemented regarding evaluation indexes of both pedestrian safety and low-speed impact. The optimal parameters are then verified, and the feasibility of the optimal results is confirmed. In conclusion, the new X-shaped energy absorber can meet both pedestrian safety and low-speed impact requirements well by altering the main deformation modes according to different impact energy levels. PMID:29581728

Design of a Conceptual Bumper Energy Absorber Coupling Pedestrian Safety and Low-Speed Impact Requirements.

PubMed

Mo, Fuhao; Zhao, Siqi; Yu, Chuanhui; Xiao, Zhi; Duan, Shuyong

2018-01-01

The car front bumper system needs to meet the requirements of both pedestrian safety and low-speed impact which are somewhat contradicting. This study aims to design a new kind of modular self-adaptive energy absorber of the front bumper system which can balance the two performances. The X-shaped energy-absorbing structure was proposed which can enhance the energy absorption capacity during impact by changing its deformation mode based on the amount of external collision energy. Then, finite element simulations with a realistic vehicle bumper system are performed to demonstrate its crashworthiness in comparison with the traditional foam energy absorber, which presents a significant improvement of the two performances. Furthermore, the structural parameters of the X-shaped energy-absorbing structure including thickness ( t u ), side arc radius ( R ), and clamping boost beam thickness ( t b ) are analyzed using a full factorial method, and a multiobjective optimization is implemented regarding evaluation indexes of both pedestrian safety and low-speed impact. The optimal parameters are then verified, and the feasibility of the optimal results is confirmed. In conclusion, the new X-shaped energy absorber can meet both pedestrian safety and low-speed impact requirements well by altering the main deformation modes according to different impact energy levels.

Using particle swarm optimization to enhance PI controller performances for active and reactive power control in wind energy conversion systems

NASA Astrophysics Data System (ADS)

Taleb, M.; Cherkaoui, M.; Hbib, M.

2018-05-01

Recently, renewable energy sources are impacting seriously power quality of the grids in term of frequency and voltage stability, due to their intermittence and less forecasting accuracy. Among these sources, wind energy conversion systems (WECS) received a great interest and especially the configuration with Doubly Fed Induction Generator. However, WECS strongly nonlinear, are making their control not easy by classical approaches such as a PI. In this paper, we continue deepen study of PI controller used in active and reactive power control of this kind of WECS. Particle Swarm Optimization (PSO) is suggested to improve its dynamic performances and its robustness against parameters variations. This work highlights the performances of PSO optimized PI control against classical PI tuned with poles compensation strategy. Simulations are carried out on MATLAB-SIMULINK software.

Energy-efficient approach to minimizing the energy consumption in an extended job-shop scheduling problem

NASA Astrophysics Data System (ADS)

Tang, Dunbing; Dai, Min

2015-09-01

The traditional production planning and scheduling problems consider performance indicators like time, cost and quality as optimization objectives in manufacturing processes. However, environmentally-friendly factors like energy consumption of production have not been completely taken into consideration. Against this background, this paper addresses an approach to modify a given schedule generated by a production planning and scheduling system in a job shop floor, where machine tools can work at different cutting speeds. It can adjust the cutting speeds of the operations while keeping the original assignment and processing sequence of operations of each job fixed in order to obtain energy savings. First, the proposed approach, based on a mixed integer programming mathematical model, changes the total idle time of the given schedule to minimize energy consumption in the job shop floor while accepting the optimal solution of the scheduling objective, makespan. Then, a genetic-simulated annealing algorithm is used to explore the optimal solution due to the fact that the problem is strongly NP-hard. Finally, the effectiveness of the approach is performed smalland large-size instances, respectively. The experimental results show that the approach can save 5%-10% of the average energy consumption while accepting the optimal solution of the makespan in small-size instances. In addition, the average maximum energy saving ratio can reach to 13%. And it can save approximately 1%-4% of the average energy consumption and approximately 2.4% of the average maximum energy while accepting the near-optimal solution of the makespan in large-size instances. The proposed research provides an interesting point to explore an energy-aware schedule optimization for a traditional production planning and scheduling problem.

Optimal Operation of a Thermal Energy Storage Tank Using Linear Optimization

NASA Astrophysics Data System (ADS)

Civit Sabate, Carles

In this thesis, an optimization procedure for minimizing the operating costs of a Thermal Energy Storage (TES) tank is presented. The facility in which the optimization is based is the combined cooling, heating, and power (CCHP) plant at the University of California, Irvine. TES tanks provide the ability of decoupling the demand of chilled water from its generation, over the course of a day, from the refrigeration and air-conditioning plants. They can be used to perform demand-side management, and optimization techniques can help to approach their optimal use. The proposed optimization approach provides a fast and reliable methodology of finding the optimal use of the TES tank to reduce energy costs and provides a tool for future implementation of optimal control laws on the system. Advantages of the proposed methodology are studied using simulation with historical data.

A systematic optimization for graphene-based supercapacitors

NASA Astrophysics Data System (ADS)

Deuk Lee, Sung; Lee, Han Sung; Kim, Jin Young; Jeong, Jaesik; Kahng, Yung Ho

2017-08-01

Increasing the energy-storage density for supercapacitors is critical for their applications. Many researchers have attempted to identify optimal candidate component materials to achieve this goal, but investigations into systematically optimizing their mixing rate for maximizing the performance of each candidate material have been insufficient, which hinders the progress in their technology. In this study, we employ a statistically systematic method to determine the optimum mixing ratio of three components that constitute graphene-based supercapacitor electrodes: reduced graphene oxide (rGO), acetylene black (AB), and polyvinylidene fluoride (PVDF). By using the extreme-vertices design, the optimized proportion is determined to be (rGO: AB: PVDF  =  0.95: 0.00: 0.05). The corresponding energy-storage density increases by a factor of 2 compared with that of non-optimized electrodes. Electrochemical and microscopic analyses are performed to determine the reason for the performance improvements.

Optimizing Instruction Scheduling and Register Allocation for Register-File-Connected Clustered VLIW Architectures

PubMed Central

Tang, Haijing; Wang, Siye; Zhang, Yanjun

2013-01-01

Clustering has become a common trend in very long instruction words (VLIW) architecture to solve the problem of area, energy consumption, and design complexity. Register-file-connected clustered (RFCC) VLIW architecture uses the mechanism of global register file to accomplish the inter-cluster data communications, thus eliminating the performance and energy consumption penalty caused by explicit inter-cluster data move operations in traditional bus-connected clustered (BCC) VLIW architecture. However, the limit number of access ports to the global register file has become an issue which must be well addressed; otherwise the performance and energy consumption would be harmed. In this paper, we presented compiler optimization techniques for an RFCC VLIW architecture called Lily, which is designed for encryption systems. These techniques aim at optimizing performance and energy consumption for Lily architecture, through appropriate manipulation of the code generation process to maintain a better management of the accesses to the global register file. All the techniques have been implemented and evaluated. The result shows that our techniques can significantly reduce the penalty of performance and energy consumption due to access port limitation of global register file. PMID:23970841

Optimal design and control of an electromechanical transfemoral prosthesis with energy regeneration.

PubMed

Rohani, Farbod; Richter, Hanz; van den Bogert, Antonie J

2017-01-01

In this paper, we present the design of an electromechanical above-knee active prosthesis with energy storage and regeneration. The system consists of geared knee and ankle motors, parallel springs for each motor, an ultracapacitor, and controllable four-quadrant power converters. The goal is to maximize the performance of the system by finding optimal controls and design parameters. A model of the system dynamics was developed, and used to solve a combined trajectory and design optimization problem. The objectives of the optimization were to minimize tracking error relative to human joint motions, as well as energy use. The optimization problem was solved by the method of direct collocation, based on joint torque and joint angle data from ten subjects walking at three speeds. After optimization of controls and design parameters, the simulated system could operate at zero energy cost while still closely emulating able-bodied gait. This was achieved by controlled energy transfer between knee and ankle, and by controlled storage and release of energy throughout the gait cycle. Optimal gear ratios and spring parameters were similar across subjects and walking speeds.

An approach to optimal semi-active control of vibration energy harvesting based on MEMS

NASA Astrophysics Data System (ADS)

Rojas, Rafael A.; Carcaterra, Antonio

2018-07-01

In this paper the energy harvesting problem involving typical MEMS technology is reduced to an optimal control problem, where the objective function is the absorption of the maximum amount of energy in a given time interval from a vibrating environment. The interest here is to identify a physical upper bound for this energy storage. The mathematical tool is a new optimal control called Krotov's method, that has not yet been applied to engineering problems, except in quantum dynamics. This approach leads to identify new maximum bounds to the energy harvesting performance. Novel MEMS-based device control configurations for vibration energy harvesting are proposed with particular emphasis to piezoelectric, electromagnetic and capacitive circuits.

Utilization of Renewable Energy to Meet New National Challenges in Energy and Climate Change

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

Momoh, James A.

The project aims to design a microgrid system to promote utilization of renewable energy resources such as wind and solar to address the national challenges in energy and climate change. Different optimization techniques and simulation software are used to study the performance of the renewable energy system under study. A series of research works performed under the grant Department of Energy (DOE) is presented. This grant opportunity affords Howard faculty, students, graduates, undergraduates, K-12, postdocs and visiting scholars to benefit state of the art research work. The research work has led to improve or advance understanding of new hardware technologies,more » software development and engineering optimization methods necessary and sufficient for handling probabilistic models and real-time computation and functions necessary for development of microgrid system. Consistent with State of Project Objective Howard University has partitioned the task into the following integrated activities: 1. Stochastic Model for RER and Load • Development of modeling Renewable Energy Resources (RER) and load which is used to perform distribution power flow study which leads to publication in refereed journals and conferences. The work was also published at the IEEE conference. 2. Stochastic optimization for voltage/Var • The development of voltage VAr optimization based on a review of existing knowledge in optimization led to the use of stochastic program and evolution of programming optimization method for V/VAr optimization. Papers were presented at the North America Power Systems Conference and the IEEE PES general meeting. 3. Modeling RER and Storage • Extending the concept of optimization method an RER with storage, such as the development of microgrid V/VAr and storage is performed. Several papers were published at the North America Power Systems Conference and the IEEE PES general meeting. 4. Power Game • Development of power game experiment using Labvolt to allow for hands on understanding of design and development of microgrid functions is performed. Publication were done by students at the end of their summer program. 5. Designing Microgrid Testbed • Example microgrid test bed is developed. In addition, function of the test bed are developed. The papers were presented at the North America Power Systems Conference and the IEEE general meeting. 6. Outreach Program • From the outreach program, topics from the project have been included in the revision of courses at Howard University, new book called Energy Processing and Smartgrid has being developed. • Hosted masters students from University of Denver to complete their projects with us. • Hosted high school students for early exposure for careers in STEM • Representations made in IEEE conferences to share the lessons learned in the use of micro grid to expose students to STEM education and research.« less

Energy-Aware Multipath Routing Scheme Based on Particle Swarm Optimization in Mobile Ad Hoc Networks

PubMed Central

Robinson, Y. Harold; Rajaram, M.

2015-01-01

Mobile ad hoc network (MANET) is a collection of autonomous mobile nodes forming an ad hoc network without fixed infrastructure. Dynamic topology property of MANET may degrade the performance of the network. However, multipath selection is a great challenging task to improve the network lifetime. We proposed an energy-aware multipath routing scheme based on particle swarm optimization (EMPSO) that uses continuous time recurrent neural network (CTRNN) to solve optimization problems. CTRNN finds the optimal loop-free paths to solve link disjoint paths in a MANET. The CTRNN is used as an optimum path selection technique that produces a set of optimal paths between source and destination. In CTRNN, particle swarm optimization (PSO) method is primly used for training the RNN. The proposed scheme uses the reliability measures such as transmission cost, energy factor, and the optimal traffic ratio between source and destination to increase routing performance. In this scheme, optimal loop-free paths can be found using PSO to seek better link quality nodes in route discovery phase. PSO optimizes a problem by iteratively trying to get a better solution with regard to a measure of quality. The proposed scheme discovers multiple loop-free paths by using PSO technique. PMID:26819966

Energy extraction from atmospheric turbulence to improve flight vehicle performance

NASA Astrophysics Data System (ADS)

Patel, Chinmay Karsandas

Small 'bird-sized' Unmanned Aerial Vehicles (UAVs) have now become practical due to technological advances in embedded electronics, miniature sensors and actuators, and propulsion systems. Birds are known to take advantage of wind currents to conserve energy and fly long distances without flapping their wings. This dissertation explores the possibility of improving the performance of small UAVs by extracting the energy available in atmospheric turbulence. An aircraft can gain energy from vertical gusts by increasing its lift in regions of updraft and reducing its lift in downdrafts - a concept that has been known for decades. Starting with a simple model of a glider flying through a sinusoidal gust, a parametric optimization approach is used to compute the minimum gust amplitude and optimal control input required for the glider to sustain flight without losing energy. For small UAVs using optimal control inputs, sinusoidal gusts with amplitude of 10--15% of the cruise speed are sufficient to keep the aircraft aloft. The method is then modified and extended to include random gusts that are representative of natural turbulence. A procedure to design optimal control laws for energy extraction from realistic gust profiles is developed using a Genetic Algorithm (GA). A feedback control law is designed to perform well over a variety of random gusts, and not be tailored for one particular gust. A small UAV flying in vertical turbulence is shown to obtain average energy savings of 35--40% with the use of a simple control law. The design procedure is also extended to determine optimal control laws for sinusoidal as well as turbulent lateral gusts. The theoretical work is complemented by experimental validation using a small autonomous UAV. The development of a lightweight autopilot and UAV platform is presented. Flight test results show that active control of the lift of an autonomous glider resulted in approximately 46% average energy savings compared to glides with fixed control surfaces. Statistical analysis of test samples shows that 19% of the active control test runs resulted in no energy loss, thus demonstrating the potential of the 'gust soaring' concept to dramatically improve the performance of small UAVs.

Optimal throughput for cognitive radio with energy harvesting in fading wireless channel.

PubMed

Vu-Van, Hiep; Koo, Insoo

2014-01-01

Energy resource management is a crucial problem of a device with a finite capacity battery. In this paper, cognitive radio is considered to be a device with an energy harvester that can harvest energy from a non-RF energy resource while performing other actions of cognitive radio. Harvested energy will be stored in a finite capacity battery. At the start of the time slot of cognitive radio, the radio needs to determine if it should remain silent or carry out spectrum sensing based on the idle probability of the primary user and the remaining energy in order to maximize the throughput of the cognitive radio system. In addition, optimal sensing energy and adaptive transmission power control are also investigated in this paper to effectively utilize the limited energy of cognitive radio. Finding an optimal approach is formulated as a partially observable Markov decision process. The simulation results show that the proposed optimal decision scheme outperforms the myopic scheme in which current throughput is only considered when making a decision.

Foraging on the potential energy surface: a swarm intelligence-based optimizer for molecular geometry.

PubMed

Wehmeyer, Christoph; Falk von Rudorff, Guido; Wolf, Sebastian; Kabbe, Gabriel; Schärf, Daniel; Kühne, Thomas D; Sebastiani, Daniel

2012-11-21

We present a stochastic, swarm intelligence-based optimization algorithm for the prediction of global minima on potential energy surfaces of molecular cluster structures. Our optimization approach is a modification of the artificial bee colony (ABC) algorithm which is inspired by the foraging behavior of honey bees. We apply our modified ABC algorithm to the problem of global geometry optimization of molecular cluster structures and show its performance for clusters with 2-57 particles and different interatomic interaction potentials.

Foraging on the potential energy surface: A swarm intelligence-based optimizer for molecular geometry

NASA Astrophysics Data System (ADS)

Wehmeyer, Christoph; Falk von Rudorff, Guido; Wolf, Sebastian; Kabbe, Gabriel; Schärf, Daniel; Kühne, Thomas D.; Sebastiani, Daniel

2012-11-01

We present a stochastic, swarm intelligence-based optimization algorithm for the prediction of global minima on potential energy surfaces of molecular cluster structures. Our optimization approach is a modification of the artificial bee colony (ABC) algorithm which is inspired by the foraging behavior of honey bees. We apply our modified ABC algorithm to the problem of global geometry optimization of molecular cluster structures and show its performance for clusters with 2-57 particles and different interatomic interaction potentials.

Measurement of damping and temperature: Precision bounds in Gaussian dissipative channels

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

Monras, Alex; Illuminati, Fabrizio

2011-01-15

We present a comprehensive analysis of the performance of different classes of Gaussian states in the estimation of Gaussian phase-insensitive dissipative channels. In particular, we investigate the optimal estimation of the damping constant and reservoir temperature. We show that, for two-mode squeezed vacuum probe states, the quantum-limited accuracy of both parameters can be achieved simultaneously. Moreover, we show that for both parameters two-mode squeezed vacuum states are more efficient than coherent, thermal, or single-mode squeezed states. This suggests that at high-energy regimes, two-mode squeezed vacuum states are optimal within the Gaussian setup. This optimality result indicates a stronger form ofmore » compatibility for the estimation of the two parameters. Indeed, not only the minimum variance can be achieved at fixed probe states, but also the optimal state is common to both parameters. Additionally, we explore numerically the performance of non-Gaussian states for particular parameter values to find that maximally entangled states within d-dimensional cutoff subspaces (d{<=}6) perform better than any randomly sampled states with similar energy. However, we also find that states with very similar performance and energy exist with much less entanglement than the maximally entangled ones.« less

On the Optimization of a Probabilistic Data Aggregation Framework for Energy Efficiency in Wireless Sensor Networks.

PubMed

Kafetzoglou, Stella; Aristomenopoulos, Giorgos; Papavassiliou, Symeon

2015-08-11

Among the key aspects of the Internet of Things (IoT) is the integration of heterogeneous sensors in a distributed system that performs actions on the physical world based on environmental information gathered by sensors and application-related constraints and requirements. Numerous applications of Wireless Sensor Networks (WSNs) have appeared in various fields, from environmental monitoring, to tactical fields, and healthcare at home, promising to change our quality of life and facilitating the vision of sensor network enabled smart cities. Given the enormous requirements that emerge in such a setting-both in terms of data and energy-data aggregation appears as a key element in reducing the amount of traffic in wireless sensor networks and achieving energy conservation. Probabilistic frameworks have been introduced as operational efficient and performance effective solutions for data aggregation in distributed sensor networks. In this work, we introduce an overall optimization approach that improves and complements such frameworks towards identifying the optimal probability for a node to aggregate packets as well as the optimal aggregation period that a node should wait for performing aggregation, so as to minimize the overall energy consumption, while satisfying certain imposed delay constraints. Primal dual decomposition is employed to solve the corresponding optimization problem while simulation results demonstrate the operational efficiency of the proposed approach under different traffic and topology scenarios.

Design and Analysis of Optimal Ascent Trajectories for Stratospheric Airships

NASA Astrophysics Data System (ADS)

Mueller, Joseph Bernard

Stratospheric airships are lighter-than-air vehicles that have the potential to provide a long-duration airborne presence at altitudes of 18-22 km. Designed to operate on solar power in the calm portion of the lower stratosphere and above all regulated air traffic and cloud cover, these vehicles represent an emerging platform that resides between conventional aircraft and satellites. A particular challenge for airship operation is the planning of ascent trajectories, as the slow moving vehicle must traverse the high wind region of the jet stream. Due to large changes in wind speed and direction across altitude and the susceptibility of airship motion to wind, the trajectory must be carefully planned, preferably optimized, in order to ensure that the desired station be reached within acceptable performance bounds of flight time and energy consumption. This thesis develops optimal ascent trajectories for stratospheric airships, examines the structure and sensitivity of these solutions, and presents a strategy for onboard guidance. Optimal ascent trajectories are developed that utilize wind energy to achieve minimum-time and minimum-energy flights. The airship is represented by a three-dimensional point mass model, and the equations of motion include aerodynamic lift and drag, vectored thrust, added mass effects, and accelerations due to mass flow rate, wind rates, and Earth rotation. A representative wind profile is developed based on historical meteorological data and measurements. Trajectory optimization is performed by first defining an optimal control problem with both terminal and path constraints, then using direct transcription to develop an approximate nonlinear parameter optimization problem of finite dimension. Optimal ascent trajectories are determined using SNOPT for a variety of upwind, downwind, and crosswind launch locations. Results of extensive optimization solutions illustrate definitive patterns in the ascent path for minimum time flights across varying launch locations, and show that significant energy savings can be realized with minimum-energy flights, compared to minimum-time time flights, given small increases in flight time. The performance of the optimal trajectories are then studied with respect to solar energy production during ascent, as well as sensitivity of the solutions to small changes in drag coefficient and wind model parameters. Results of solar power model simulations indicate that solar energy is sufficient to power ascent flights, but that significant energy loss can occur for certain types of trajectories. Sensitivity to the drag and wind model is approximated through numerical simulations, showing that optimal solutions change gradually with respect to changing wind and drag parameters and providing deeper insight into the characteristics of optimal airship flights. Finally, alternative methods are developed to generate near-optimal ascent trajectories in a manner suitable for onboard implementation. The structures and characteristics of previously developed minimum-time and minimum-energy ascent trajectories are used to construct simplified trajectory models, which are efficiently solved in a smaller numerical optimization problem. Comparison of these alternative solutions to the original SNOPT solutions show excellent agreement, suggesting the alternate formulations are an effective means to develop near-optimal solutions in an onboard setting.

Building Energy Modeling and Control Methods for Optimization and Renewables Integration

NASA Astrophysics Data System (ADS)

Burger, Eric M.

This dissertation presents techniques for the numerical modeling and control of building systems, with an emphasis on thermostatically controlled loads. The primary objective of this work is to address technical challenges related to the management of energy use in commercial and residential buildings. This work is motivated by the need to enhance the performance of building systems and by the potential for aggregated loads to perform load following and regulation ancillary services, thereby enabling the further adoption of intermittent renewable energy generation technologies. To increase the generalizability of the techniques, an emphasis is placed on recursive and adaptive methods which minimize the need for customization to specific buildings and applications. The techniques presented in this dissertation can be divided into two general categories: modeling and control. Modeling techniques encompass the processing of data streams from sensors and the training of numerical models. These models enable us to predict the energy use of a building and of sub-systems, such as a heating, ventilation, and air conditioning (HVAC) unit. Specifically, we first present an ensemble learning method for the short-term forecasting of total electricity demand in buildings. As the deployment of intermittent renewable energy resources continues to rise, the generation of accurate building-level electricity demand forecasts will be valuable to both grid operators and building energy management systems. Second, we present a recursive parameter estimation technique for identifying a thermostatically controlled load (TCL) model that is non-linear in the parameters. For TCLs to perform demand response services in real-time markets, online methods for parameter estimation are needed. Third, we develop a piecewise linear thermal model of a residential building and train the model using data collected from a custom-built thermostat. This model is capable of approximating unmodeled dynamics within a building by learning from sensor data. Control techniques encompass the application of optimal control theory, model predictive control, and convex distributed optimization to TCLs. First, we present the alternative control trajectory (ACT) representation, a novel method for the approximate optimization of non-convex discrete systems. This approach enables the optimal control of a population of non-convex agents using distributed convex optimization techniques. Second, we present a distributed convex optimization algorithm for the control of a TCL population. Experimental results demonstrate the application of this algorithm to the problem of renewable energy generation following. This dissertation contributes to the development of intelligent energy management systems for buildings by presenting a suite of novel and adaptable modeling and control techniques. Applications focus on optimizing the performance of building operations and on facilitating the integration of renewable energy resources.

Joint Resource Optimization for Cognitive Sensor Networks with SWIPT-Enabled Relay.

PubMed

Lu, Weidang; Lin, Yuanrong; Peng, Hong; Nan, Tian; Liu, Xin

2017-09-13

Energy-constrained wireless networks, such as wireless sensor networks (WSNs), are usually powered by fixed energy supplies (e.g., batteries), which limits the operation time of networks. Simultaneous wireless information and power transfer (SWIPT) is a promising technique to prolong the lifetime of energy-constrained wireless networks. This paper investigates the performance of an underlay cognitive sensor network (CSN) with SWIPT-enabled relay node. In the CSN, the amplify-and-forward (AF) relay sensor node harvests energy from the ambient radio-frequency (RF) signals using power splitting-based relaying (PSR) protocol. Then, it helps forward the signal of source sensor node (SSN) to the destination sensor node (DSN) by using the harvested energy. We study the joint resource optimization including the transmit power and power splitting ratio to maximize CSN's achievable rate with the constraint that the interference caused by the CSN to the primary users (PUs) is within the permissible threshold. Simulation results show that the performance of our proposed joint resource optimization can be significantly improved.

Energy aware swarm optimization with intercluster search for wireless sensor network.

PubMed

Thilagavathi, Shanmugasundaram; Geetha, Bhavani Gnanasambandan

2015-01-01

Wireless sensor networks (WSNs) are emerging as a low cost popular solution for many real-world challenges. The low cost ensures deployment of large sensor arrays to perform military and civilian tasks. Generally, WSNs are power constrained due to their unique deployment method which makes replacement of battery source difficult. Challenges in WSN include a well-organized communication platform for the network with negligible power utilization. In this work, an improved binary particle swarm optimization (PSO) algorithm with modified connected dominating set (CDS) based on residual energy is proposed for discovery of optimal number of clusters and cluster head (CH). Simulations show that the proposed BPSO-T and BPSO-EADS perform better than LEACH- and PSO-based system in terms of energy savings and QOS.

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

PubMed Central

Zhao, Xiuli; Yiranbon, Ethel

2014-01-01

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

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

PubMed

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

2014-01-01

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

A Framework for Daylighting Optimization in Whole Buildings with OpenStudio

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

None

2016-08-12

We present a toolkit and workflow for leveraging the OpenStudio (Guglielmetti et al. 2010) platform to perform daylighting analysis and optimization in a whole building energy modeling (BEM) context. We have re-implemented OpenStudio's integrated Radiance and EnergyPlus functionality as an OpenStudio Measure. The OpenStudio Radiance Measure works within the OpenStudio Application and Parametric Analysis Tool, as well as the OpenStudio Server large scale analysis framework, allowing a rigorous daylighting simulation to be performed on a single building model or potentially an entire population of programmatically generated models. The Radiance simulation results can automatically inform the broader building energy model, andmore » provide dynamic daylight metrics as a basis for decision. Through introduction and example, this paper illustrates the utility of the OpenStudio building energy modeling platform to leverage existing simulation tools for integrated building energy performance simulation, daylighting analysis, and reportage.« less

Optimal Time-Resource Allocation for Energy-Efficient Physical Activity Detection

PubMed Central

Thatte, Gautam; Li, Ming; Lee, Sangwon; Emken, B. Adar; Annavaram, Murali; Narayanan, Shrikanth; Spruijt-Metz, Donna; Mitra, Urbashi

2011-01-01

The optimal allocation of samples for physical activity detection in a wireless body area network for health-monitoring is considered. The number of biometric samples collected at the mobile device fusion center, from both device-internal and external Bluetooth heterogeneous sensors, is optimized to minimize the transmission power for a fixed number of samples, and to meet a performance requirement defined using the probability of misclassification between multiple hypotheses. A filter-based feature selection method determines an optimal feature set for classification, and a correlated Gaussian model is considered. Using experimental data from overweight adolescent subjects, it is found that allocating a greater proportion of samples to sensors which better discriminate between certain activity levels can result in either a lower probability of error or energy-savings ranging from 18% to 22%, in comparison to equal allocation of samples. The current activity of the subjects and the performance requirements do not significantly affect the optimal allocation, but employing personalized models results in improved energy-efficiency. As the number of samples is an integer, an exhaustive search to determine the optimal allocation is typical, but computationally expensive. To this end, an alternate, continuous-valued vector optimization is derived which yields approximately optimal allocations and can be implemented on the mobile fusion center due to its significantly lower complexity. PMID:21796237

Dual-energy contrast enhanced digital breast tomosynthesis: concept, method, and evaluation on phantoms

NASA Astrophysics Data System (ADS)

Puong, Sylvie; Patoureaux, Fanny; Iordache, Razvan; Bouchevreau, Xavier; Muller, Serge

2007-03-01

In this paper, we present the development of dual-energy Contrast-Enhanced Digital Breast Tomosynthesis (CEDBT). A method to produce background clutter-free slices from a set of low and high-energy projections is introduced, along with a scheme for the determination of the optimal low and high-energy techniques. Our approach consists of a dual-energy recombination of the projections, with an algorithm that has proven its performance in Contrast-Enhanced Digital Mammography1 (CEDM), followed by an iterative volume reconstruction. The aim is to eliminate the anatomical background clutter and to reconstruct slices where the gray level is proportional to the local iodine volumetric concentration. Optimization of the low and high-energy techniques is performed by minimizing the total glandular dose to reach a target iodine Signal Difference to Noise Ratio (SDNR) in the slices. In this study, we proved that this optimization could be done on the projections, by consideration of the SDNR in the projections instead of the SDNR in the slices, and verified this with phantom measurements. We also discuss some limitations of dual-energy CEDBT, due to the restricted angular range for the projection views, and to the presence of scattered radiation. Experiments on textured phantoms with iodine inserts were conducted to assess the performance of dual-energy CEDBT. Texture contrast was nearly completely removed and the iodine signal was enhanced in the slices.

Multi-parameter geometrical scaledown study for energy optimization of MTJ and related spintronics nanodevices

NASA Astrophysics Data System (ADS)

Farhat, I. A. H.; Alpha, C.; Gale, E.; Atia, D. Y.; Stein, A.; Isakovic, A. F.

The scaledown of magnetic tunnel junctions (MTJ) and related nanoscale spintronics devices poses unique challenges for energy optimization of their performance. We demonstrate the dependence of the switching current on the scaledown variable, while considering the influence of geometric parameters of MTJ, such as the free layer thickness, tfree, lateral size of the MTJ, w, and the anisotropy parameter of the MTJ. At the same time, we point out which values of the saturation magnetization, Ms, and anisotropy field, Hk, can lead to lowering the switching current and overall decrease of the energy needed to operate an MTJ. It is demonstrated that scaledown via decreasing the lateral size of the MTJ, while allowing some other parameters to be unconstrained, can improve energy performance by a measurable factor, shown to be the function of both geometric and physical parameters above. Given the complex interdependencies among both families of parameters, we developed a particle swarm optimization (PSO) algorithm that can simultaneously lower energy of operation and the switching current density. Results we obtained in scaledown study and via PSO optimization are compared to experimental results. Support by Mubadala-SRC 2012-VJ-2335 is acknowledged, as are staff at Cornell-CNF and BNL-CFN.

Stochastic control of smart home energy management with plug-in electric vehicle battery energy storage and photovoltaic array

NASA Astrophysics Data System (ADS)

Wu, Xiaohua; Hu, Xiaosong; Moura, Scott; Yin, Xiaofeng; Pickert, Volker

2016-11-01

Energy management strategies are instrumental in the performance and economy of smart homes integrating renewable energy and energy storage. This article focuses on stochastic energy management of a smart home with PEV (plug-in electric vehicle) energy storage and photovoltaic (PV) array. It is motivated by the challenges associated with sustainable energy supplies and the local energy storage opportunity provided by vehicle electrification. This paper seeks to minimize a consumer's energy charges under a time-of-use tariff, while satisfying home power demand and PEV charging requirements, and accommodating the variability of solar power. First, the random-variable models are developed, including Markov Chain model of PEV mobility, as well as predictive models of home power demand and PV power supply. Second, a stochastic optimal control problem is mathematically formulated for managing the power flow among energy sources in the smart home. Finally, based on time-varying electricity price, we systematically examine the performance of the proposed control strategy. As a result, the electric cost is 493.6% less for a Tesla Model S with optimal stochastic dynamic programming (SDP) control relative to the no optimal control case, and it is by 175.89% for a Nissan Leaf.

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

DOE PAGES

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

2017-07-25

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

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

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

Luo, Na; Hong, Tianzhen; Li, Hui

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

The value of compressed air energy storage in energy and reserve markets

DOE PAGES

Drury, Easan; Denholm, Paul; Sioshansi, Ramteen

2011-06-28

Storage devices can provide several grid services, however it is challenging to quantify the value of providing several services and to optimally allocate storage resources to maximize value. We develop a co-optimized Compressed Air Energy Storage (CAES) dispatch model to characterize the value of providing operating reserves in addition to energy arbitrage in several U.S. markets. We use the model to: (1) quantify the added value of providing operating reserves in addition to energy arbitrage; (2) evaluate the dynamic nature of optimally allocating storage resources into energy and reserve markets; and (3) quantify the sensitivity of CAES net revenues tomore » several design and performance parameters. We find that conventional CAES systems could earn an additional 23 ± 10/kW-yr by providing operating reserves, and adiabatic CAES systems could earn an additional 28 ± 13/kW-yr. We find that arbitrage-only revenues are unlikely to support a CAES investment in most market locations, but the addition of reserve revenues could support a conventional CAES investment in several markets. Adiabatic CAES revenues are not likely to support an investment in most regions studied. As a result, modifying CAES design and performance parameters primarily impacts arbitrage revenues, and optimizing CAES design will be nearly independent of dispatch strategy.« less

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

PubMed

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

2018-02-01

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

Optimal symmetric flight studies

NASA Technical Reports Server (NTRS)

Weston, A. R.; Menon, P. K. A.; Bilimoria, K. D.; Cliff, E. M.; Kelley, H. J.

1985-01-01

Several topics in optimal symmetric flight of airbreathing vehicles are examined. In one study, an approximation scheme designed for onboard real-time energy management of climb-dash is developed and calculations for a high-performance aircraft presented. In another, a vehicle model intermediate in complexity between energy and point-mass models is explored and some quirks in optimal flight characteristics peculiar to the model uncovered. In yet another study, energy-modelling procedures are re-examined with a view to stretching the range of validity of zeroth-order approximation by special choice of state variables. In a final study, time-fuel tradeoffs in cruise-dash are examined for the consequences of nonconvexities appearing in the classical steady cruise-dash model. Two appendices provide retrospective looks at two early publications on energy modelling and related optimal control theory.

Observer model optimization of a spectral mammography system

NASA Astrophysics Data System (ADS)

Fredenberg, Erik; Åslund, Magnus; Cederström, Björn; Lundqvist, Mats; Danielsson, Mats

2010-04-01

Spectral imaging is a method in medical x-ray imaging to extract information about the object constituents by the material-specific energy dependence of x-ray attenuation. Contrast-enhanced spectral imaging has been thoroughly investigated, but unenhanced imaging may be more useful because it comes as a bonus to the conventional non-energy-resolved absorption image at screening; there is no additional radiation dose and no need for contrast medium. We have used a previously developed theoretical framework and system model that include quantum and anatomical noise to characterize the performance of a photon-counting spectral mammography system with two energy bins for unenhanced imaging. The theoretical framework was validated with synthesized images. Optimal combination of the energy-resolved images for detecting large unenhanced tumors corresponded closely, but not exactly, to minimization of the anatomical noise, which is commonly referred to as energy subtraction. In that case, an ideal-observer detectability index could be improved close to 50% compared to absorption imaging. Optimization with respect to the signal-to-quantum-noise ratio, commonly referred to as energy weighting, deteriorated detectability. For small microcalcifications or tumors on uniform backgrounds, however, energy subtraction was suboptimal whereas energy weighting provided a minute improvement. The performance was largely independent of beam quality, detector energy resolution, and bin count fraction. It is clear that inclusion of anatomical noise and imaging task in spectral optimization may yield completely different results than an analysis based solely on quantum noise.

Integrating prediction, provenance, and optimization into high energy workflows

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

Schram, M.; Bansal, V.; Friese, R. D.

We propose a novel approach for efficient execution of workflows on distributed resources. The key components of this framework include: performance modeling to quantitatively predict workflow component behavior; optimization-based scheduling such as choosing an optimal subset of resources to meet demand and assignment of tasks to resources; distributed I/O optimizations such as prefetching; and provenance methods for collecting performance data. In preliminary results, these techniques improve throughput on a small Belle II workflow by 20%.

Optimization of HTS superconducting magnetic energy storage magnet volume

NASA Astrophysics Data System (ADS)

Korpela, Aki; Lehtonen, Jorma; Mikkonen, Risto

2003-08-01

Nonlinear optimization problems in the field of electromagnetics have been successfully solved by means of sequential quadratic programming (SQP) and the finite element method (FEM). For example, the combination of SQP and FEM has been proven to be an efficient tool in the optimization of low temperature superconductors (LTS) superconducting magnetic energy storage (SMES) magnets. The procedure can also be applied for the optimization of HTS magnets. However, due to a strongly anisotropic material and a slanted electric field, current density characteristic high temperature superconductors HTS optimization is quite different from that of the LTS. In this paper the volumes of solenoidal conduction-cooled Bi-2223/Ag SMES magnets have been optimized at the operation temperature of 20 K. In addition to the electromagnetic constraints the stress caused by the tape bending has also been taken into account. Several optimization runs with different initial geometries were performed in order to find the best possible solution for a certain energy requirement. The optimization constraints describe the steady-state operation, thus the presented coil geometries are designed for slow ramping rates. Different energy requirements were investigated in order to find the energy dependence of the design parameters of optimized solenoidal HTS coils. According to the results, these dependences can be described with polynomial expressions.

Kosol Kiatreungwattana | NREL

Science.gov Websites

Kosol Kiatreungwattana Kosol Kiatreungwattana Senior Engineer - Building and Renewable Energy experience in building energy systems and renewable technologies, building energy codes, LEED certified projects, sustainable high performance building design, building energy simulation analysis/optimization

The trust-region self-consistent field method in Kohn-Sham density-functional theory.

PubMed

Thøgersen, Lea; Olsen, Jeppe; Köhn, Andreas; Jørgensen, Poul; Sałek, Paweł; Helgaker, Trygve

2005-08-15

The trust-region self-consistent field (TRSCF) method is extended to the optimization of the Kohn-Sham energy. In the TRSCF method, both the Roothaan-Hall step and the density-subspace minimization step are replaced by trust-region optimizations of local approximations to the Kohn-Sham energy, leading to a controlled, monotonic convergence towards the optimized energy. Previously the TRSCF method has been developed for optimization of the Hartree-Fock energy, which is a simple quadratic function in the density matrix. However, since the Kohn-Sham energy is a nonquadratic function of the density matrix, the local energy functions must be generalized for use with the Kohn-Sham model. Such a generalization, which contains the Hartree-Fock model as a special case, is presented here. For comparison, a rederivation of the popular direct inversion in the iterative subspace (DIIS) algorithm is performed, demonstrating that the DIIS method may be viewed as a quasi-Newton method, explaining its fast local convergence. In the global region the convergence behavior of DIIS is less predictable. The related energy DIIS technique is also discussed and shown to be inappropriate for the optimization of the Kohn-Sham energy.

Crush Can Behaviour as an Energy Absorber in a Frontal Impact

NASA Astrophysics Data System (ADS)

Bhuyan, Atanu; Ganilova, Olga

2012-08-01

The work presented is devoted to the investigation of a state-of-the-art technological solution for the design of a crush-can characterized by optimal energy absorbing properties. The work is focused on the theoretical background of the square tubes, circular tubes and inverbucktube performance under impact with the purpose of design of a novel optimized structure. The main system under consideration is based on the patent US 2008/0185851 A1 and includes a base flange with elongated crush boxes and back straps for stabilization of the crush boxes with the purpose of improvement of the energy-absorbing functionality. The modelling of this system is carried out applying both a theoretical approach and finite element analysis concentrating on the energy absorbing abilities of the crumple zones. The optimization process is validated under dynamic and quasi-static loading conditions whilst considering various modes of deformation and stress distribution along the tubular components. Energy absorbing behaviour of the crush-cans is studied concentrating on their geometrical properties and their diamond or concertina modes of deformation. Moreover, structures made of different materials, steel, aluminium and polymer composites are considered for the material effect analysis and optimization through their combination. Optimization of the crush-can behaviour is done within the limits of the frontal impact scenario with the purpose of improvement of the structural performance in the Euro NCAP tests.

Basic aspects and contributions to the optimization of energy systems exploitation of a super tanker ship

NASA Astrophysics Data System (ADS)

Faitar, C.; Novac, I.

2017-08-01

Today, the concept of energy efficiency or energy optimization in ships has become one of the main problems of engineers in the whole world. To increase the fiability of a crude oil super tanker ship it means, among other things, to improve the energy performance and optimize the fuel consumption of ship through the development of engines and propulsion system or using alternative energies. Also, the importance of having an effective and reliable Power Management System (PMS) in a vessel operating system means to reduce operational costs and maintain power system of machine parts working in minimum stress in all operating conditions. Studying the Energy Efficiency Design Index and Energy Efficiency Operational Indicator for a crude oil super tanker ship, it allows us to study the reconfiguration of ship power system introducing new generation systems.

Design Studies and Optimization of High-Field Nb$$_3$$Sn Dipole Magnets for a Future Very High Energy PP Collider

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

Kashikhin, V. V.; Novitski, I.; Zlobin, A. V.

2017-05-01

High filed accelerator magnets with operating fields of 15-16 T based on themore » $$Nb_3Sn$$ superconductor are being considered for the LHC energy upgrade or a future Very High Energy pp Collider. Magnet design studies are being conducted in the U.S., Europe and Asia to explore the limits of the $$Nb_3Sn$$ accelerator magnet technology while optimizing the magnet design and performance parame-ters, and reducing magnet cost. The first results of these studies performed at Fermilab in the framework of the US-MDP are reported in this paper.« less

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

Multi-objective robust design of energy-absorbing components using coupled process-performance simulations

NASA Astrophysics Data System (ADS)

Najafi, Ali; Acar, Erdem; Rais-Rohani, Masoud

2014-02-01

The stochastic uncertainties associated with the material, process and product are represented and propagated to process and performance responses. A finite element-based sequential coupled process-performance framework is used to simulate the forming and energy absorption responses of a thin-walled tube in a manner that both material properties and component geometry can evolve from one stage to the next for better prediction of the structural performance measures. Metamodelling techniques are used to develop surrogate models for manufacturing and performance responses. One set of metamodels relates the responses to the random variables whereas the other relates the mean and standard deviation of the responses to the selected design variables. A multi-objective robust design optimization problem is formulated and solved to illustrate the methodology and the influence of uncertainties on manufacturability and energy absorption of a metallic double-hat tube. The results are compared with those of deterministic and augmented robust optimization problems.

Optimization of CW Fiber Lasers With Strong Nonlinear Cavity Dynamics

NASA Astrophysics Data System (ADS)

Shtyrina, O. V.; Efremov, S. A.; Yarutkina, I. A.; Skidin, A. S.; Fedoruk, M. P.

2018-04-01

In present work the equation for the saturated gain is derived from one-level gain equations describing the energy evolution inside the laser cavity. It is shown how to derive the parameters of the mathematical model from the experimental results. The numerically-estimated energy and spectrum of the signal are in good agreement with the experiment. Also, the optimization of the output energy is performed for a given set of model parameters.

Exergy Based Analysis for the Environmental Control and Life Support Systems of the International Space Station

NASA Technical Reports Server (NTRS)

Clem, Kirk A.; Nelson, George J.; Mesmer, Bryan L.; Watson, Michael D.; Perry, Jay L.

2016-01-01

When optimizing the performance of complex systems, a logical area for concern is improving the efficiency of useful energy. The energy available for a system to perform work is defined as a system's energy content. Interactions between a system's subsystems and the surrounding environment can be accounted for by understanding various subsystem energy efficiencies. Energy balance of reactants and products, and enthalpies and entropies, can be used to represent a chemical process. Heat transfer energy represents heat loads, and flow energy represents system flows and filters. These elements allow for a system level energy balance. The energy balance equations are developed for the subsystems of the Environmental Control and Life Support (ECLS) system aboard the International Space Station (ISS). The use of these equations with system information would allow for the calculation of the energy efficiency of the system, enabling comparisons of the ISS ECLS system to other systems as well as allows for an integrated systems analysis for system optimization.

Intelligent and robust optimization frameworks for smart grids

NASA Astrophysics Data System (ADS)

Dhansri, Naren Reddy

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

Parameter Selection and Performance Comparison of Particle Swarm Optimization in Sensor Networks Localization.

PubMed

Cui, Huanqing; Shu, Minglei; Song, Min; Wang, Yinglong

2017-03-01

Localization is a key technology in wireless sensor networks. Faced with the challenges of the sensors' memory, computational constraints, and limited energy, particle swarm optimization has been widely applied in the localization of wireless sensor networks, demonstrating better performance than other optimization methods. In particle swarm optimization-based localization algorithms, the variants and parameters should be chosen elaborately to achieve the best performance. However, there is a lack of guidance on how to choose these variants and parameters. Further, there is no comprehensive performance comparison among particle swarm optimization algorithms. The main contribution of this paper is three-fold. First, it surveys the popular particle swarm optimization variants and particle swarm optimization-based localization algorithms for wireless sensor networks. Secondly, it presents parameter selection of nine particle swarm optimization variants and six types of swarm topologies by extensive simulations. Thirdly, it comprehensively compares the performance of these algorithms. The results show that the particle swarm optimization with constriction coefficient using ring topology outperforms other variants and swarm topologies, and it performs better than the second-order cone programming algorithm.

Parameter Selection and Performance Comparison of Particle Swarm Optimization in Sensor Networks Localization

PubMed Central

Cui, Huanqing; Shu, Minglei; Song, Min; Wang, Yinglong

2017-01-01

Localization is a key technology in wireless sensor networks. Faced with the challenges of the sensors’ memory, computational constraints, and limited energy, particle swarm optimization has been widely applied in the localization of wireless sensor networks, demonstrating better performance than other optimization methods. In particle swarm optimization-based localization algorithms, the variants and parameters should be chosen elaborately to achieve the best performance. However, there is a lack of guidance on how to choose these variants and parameters. Further, there is no comprehensive performance comparison among particle swarm optimization algorithms. The main contribution of this paper is three-fold. First, it surveys the popular particle swarm optimization variants and particle swarm optimization-based localization algorithms for wireless sensor networks. Secondly, it presents parameter selection of nine particle swarm optimization variants and six types of swarm topologies by extensive simulations. Thirdly, it comprehensively compares the performance of these algorithms. The results show that the particle swarm optimization with constriction coefficient using ring topology outperforms other variants and swarm topologies, and it performs better than the second-order cone programming algorithm. PMID:28257060

Study on key technologies of optimization of big data for thermal power plant performance

NASA Astrophysics Data System (ADS)

Mao, Mingyang; Xiao, Hong

2018-06-01

Thermal power generation accounts for 70% of China's power generation, the pollutants accounted for 40% of the same kind of emissions, thermal power efficiency optimization needs to monitor and understand the whole process of coal combustion and pollutant migration, power system performance data show explosive growth trend, The purpose is to study the integration of numerical simulation of big data technology, the development of thermal power plant efficiency data optimization platform and nitrogen oxide emission reduction system for the thermal power plant to improve efficiency, energy saving and emission reduction to provide reliable technical support. The method is big data technology represented by "multi-source heterogeneous data integration", "large data distributed storage" and "high-performance real-time and off-line computing", can greatly enhance the energy consumption capacity of thermal power plants and the level of intelligent decision-making, and then use the data mining algorithm to establish the boiler combustion mathematical model, mining power plant boiler efficiency data, combined with numerical simulation technology to find the boiler combustion and pollutant generation rules and combustion parameters of boiler combustion and pollutant generation Influence. The result is to optimize the boiler combustion parameters, which can achieve energy saving.

Optimization Under Uncertainty of Site-Specific Turbine Configurations

NASA Astrophysics Data System (ADS)

Quick, J.; Dykes, K.; Graf, P.; Zahle, F.

2016-09-01

Uncertainty affects many aspects of wind energy plant performance and cost. In this study, we explore opportunities for site-specific turbine configuration optimization that accounts for uncertainty in the wind resource. As a demonstration, a simple empirical model for wind plant cost of energy is used in an optimization under uncertainty to examine how different risk appetites affect the optimal selection of a turbine configuration for sites of different wind resource profiles. If there is unusually high uncertainty in the site wind resource, the optimal turbine configuration diverges from the deterministic case and a generally more conservative design is obtained with increasing risk aversion on the part of the designer.

A self-optimizing scheme for energy balanced routing in Wireless Sensor Networks using SensorAnt.

PubMed

Shamsan Saleh, Ahmed M; Ali, Borhanuddin Mohd; Rasid, Mohd Fadlee A; Ismail, Alyani

2012-01-01

Planning of energy-efficient protocols is critical for Wireless Sensor Networks (WSNs) because of the constraints on the sensor nodes' energy. The routing protocol should be able to provide uniform power dissipation during transmission to the sink node. In this paper, we present a self-optimization scheme for WSNs which is able to utilize and optimize the sensor nodes' resources, especially the batteries, to achieve balanced energy consumption across all sensor nodes. This method is based on the Ant Colony Optimization (ACO) metaheuristic which is adopted to enhance the paths with the best quality function. The assessment of this function depends on multi-criteria metrics such as the minimum residual battery power, hop count and average energy of both route and network. This method also distributes the traffic load of sensor nodes throughout the WSN leading to reduced energy usage, extended network life time and reduced packet loss. Simulation results show that our scheme performs much better than the Energy Efficient Ant-Based Routing (EEABR) in terms of energy consumption, balancing and efficiency.

Efficient Convex Optimization for Energy-Based Acoustic Sensor Self-Localization and Source Localization in Sensor Networks.

PubMed

Yan, Yongsheng; Wang, Haiyan; Shen, Xiaohong; Leng, Bing; Li, Shuangquan

2018-05-21

The energy reading has been an efficient and attractive measure for collaborative acoustic source localization in practical application due to its cost saving in both energy and computation capability. The maximum likelihood problems by fusing received acoustic energy readings transmitted from local sensors are derived. Aiming to efficiently solve the nonconvex objective of the optimization problem, we present an approximate estimator of the original problem. Then, a direct norm relaxation and semidefinite relaxation, respectively, are utilized to derive the second-order cone programming, semidefinite programming or mixture of them for both cases of sensor self-location and source localization. Furthermore, by taking the colored energy reading noise into account, several minimax optimization problems are formulated, which are also relaxed via the direct norm relaxation and semidefinite relaxation respectively into convex optimization problems. Performance comparison with the existing acoustic energy-based source localization methods is given, where the results show the validity of our proposed methods.

Efficient Convex Optimization for Energy-Based Acoustic Sensor Self-Localization and Source Localization in Sensor Networks

PubMed Central

Yan, Yongsheng; Wang, Haiyan; Shen, Xiaohong; Leng, Bing; Li, Shuangquan

2018-01-01

The energy reading has been an efficient and attractive measure for collaborative acoustic source localization in practical application due to its cost saving in both energy and computation capability. The maximum likelihood problems by fusing received acoustic energy readings transmitted from local sensors are derived. Aiming to efficiently solve the nonconvex objective of the optimization problem, we present an approximate estimator of the original problem. Then, a direct norm relaxation and semidefinite relaxation, respectively, are utilized to derive the second-order cone programming, semidefinite programming or mixture of them for both cases of sensor self-location and source localization. Furthermore, by taking the colored energy reading noise into account, several minimax optimization problems are formulated, which are also relaxed via the direct norm relaxation and semidefinite relaxation respectively into convex optimization problems. Performance comparison with the existing acoustic energy-based source localization methods is given, where the results show the validity of our proposed methods. PMID:29883410

Multi-Objective Approach for Energy-Aware Workflow Scheduling in Cloud Computing Environments

PubMed Central

Kadima, Hubert; Granado, Bertrand

2013-01-01

We address the problem of scheduling workflow applications on heterogeneous computing systems like cloud computing infrastructures. In general, the cloud workflow scheduling is a complex optimization problem which requires considering different criteria so as to meet a large number of QoS (Quality of Service) requirements. Traditional research in workflow scheduling mainly focuses on the optimization constrained by time or cost without paying attention to energy consumption. The main contribution of this study is to propose a new approach for multi-objective workflow scheduling in clouds, and present the hybrid PSO algorithm to optimize the scheduling performance. Our method is based on the Dynamic Voltage and Frequency Scaling (DVFS) technique to minimize energy consumption. This technique allows processors to operate in different voltage supply levels by sacrificing clock frequencies. This multiple voltage involves a compromise between the quality of schedules and energy. Simulation results on synthetic and real-world scientific applications highlight the robust performance of the proposed approach. PMID:24319361

Multi-objective approach for energy-aware workflow scheduling in cloud computing environments.

PubMed

Yassa, Sonia; Chelouah, Rachid; Kadima, Hubert; Granado, Bertrand

2013-01-01

We address the problem of scheduling workflow applications on heterogeneous computing systems like cloud computing infrastructures. In general, the cloud workflow scheduling is a complex optimization problem which requires considering different criteria so as to meet a large number of QoS (Quality of Service) requirements. Traditional research in workflow scheduling mainly focuses on the optimization constrained by time or cost without paying attention to energy consumption. The main contribution of this study is to propose a new approach for multi-objective workflow scheduling in clouds, and present the hybrid PSO algorithm to optimize the scheduling performance. Our method is based on the Dynamic Voltage and Frequency Scaling (DVFS) technique to minimize energy consumption. This technique allows processors to operate in different voltage supply levels by sacrificing clock frequencies. This multiple voltage involves a compromise between the quality of schedules and energy. Simulation results on synthetic and real-world scientific applications highlight the robust performance of the proposed approach.

Integrated solar energy system optimization

NASA Astrophysics Data System (ADS)

Young, S. K.

1982-11-01

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

Solar thermal collectors using planar reflector

NASA Technical Reports Server (NTRS)

Espy, P. N.

1978-01-01

Specular reflectors have been used successfully with flat-plate collectors to achieve exceptionally high operating temperatures and high delivered energy per unit collector area. Optimal orientation of collectors and reflectors can result in even higher performance with an improved relationship between energy demand and supply. This paper reports on a study providing first order optimization of collector-reflector arrays in which single- and multiple-faceted reflectors in fixed or singly adjustable configurations provide delivered energy maxima in either summer or winter.

Dynamic Energy Management System for a Smart Microgrid.

PubMed

Venayagamoorthy, Ganesh Kumar; Sharma, Ratnesh K; Gautam, Prajwal K; Ahmadi, Afshin

2016-08-01

This paper presents the development of an intelligent dynamic energy management system (I-DEMS) for a smart microgrid. An evolutionary adaptive dynamic programming and reinforcement learning framework is introduced for evolving the I-DEMS online. The I-DEMS is an optimal or near-optimal DEMS capable of performing grid-connected and islanded microgrid operations. The primary sources of energy are sustainable, green, and environmentally friendly renewable energy systems (RESs), e.g., wind and solar; however, these forms of energy are uncertain and nondispatchable. Backup battery energy storage and thermal generation were used to overcome these challenges. Using the I-DEMS to schedule dispatches allowed the RESs and energy storage devices to be utilized to their maximum in order to supply the critical load at all times. Based on the microgrid's system states, the I-DEMS generates energy dispatch control signals, while a forward-looking network evaluates the dispatched control signals over time. Typical results are presented for varying generation and load profiles, and the performance of I-DEMS is compared with that of a decision tree approach-based DEMS (D-DEMS). The robust performance of the I-DEMS was illustrated by examining microgrid operations under different battery energy storage conditions.

Vibroacoustic optimization using a statistical energy analysis model

NASA Astrophysics Data System (ADS)

Culla, Antonio; D`Ambrogio, Walter; Fregolent, Annalisa; Milana, Silvia

2016-08-01

In this paper, an optimization technique for medium-high frequency dynamic problems based on Statistical Energy Analysis (SEA) method is presented. Using a SEA model, the subsystem energies are controlled by internal loss factors (ILF) and coupling loss factors (CLF), which in turn depend on the physical parameters of the subsystems. A preliminary sensitivity analysis of subsystem energy to CLF's is performed to select CLF's that are most effective on subsystem energies. Since the injected power depends not only on the external loads but on the physical parameters of the subsystems as well, it must be taken into account under certain conditions. This is accomplished in the optimization procedure, where approximate relationships between CLF's, injected power and physical parameters are derived. The approach is applied on a typical aeronautical structure: the cabin of a helicopter.

Nozzle Mounting Method Optimization Based on Robot Kinematic Analysis

NASA Astrophysics Data System (ADS)

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

2016-08-01

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

Optimizing energy functions for protein-protein interface design.

PubMed

Sharabi, Oz; Yanover, Chen; Dekel, Ayelet; Shifman, Julia M

2011-01-15

Protein design methods have been originally developed for the design of monomeric proteins. When applied to the more challenging task of protein–protein complex design, these methods yield suboptimal results. In particular, they often fail to recapitulate favorable hydrogen bonds and electrostatic interactions across the interface. In this work, we aim to improve the energy function of the protein design program ORBIT to better account for binding interactions between proteins. By using the advanced machine learning framework of conditional random fields, we optimize the relative importance of all the terms in the energy function, attempting to reproduce the native side-chain conformations in protein–protein interfaces. We evaluate the performance of several optimized energy functions, each describes the van der Waals interactions using a different potential. In comparison with the original energy function, our best energy function (a) incorporates a much “softer” repulsive van der Waals potential, suitable for the discrete rotameric representation of amino acid side chains; (b) does not penalize burial of polar atoms, reflecting the frequent occurrence of polar buried residues in protein–protein interfaces; and (c) significantly up-weights the electrostatic term, attesting to the high importance of these interactions for protein–protein complex formation. Using this energy function considerably improves side chain placement accuracy for interface residues in a large test set of protein–protein complexes. Moreover, the optimized energy function recovers the native sequences of protein–protein interface at a higher rate than the default function and performs substantially better in predicting changes in free energy of binding due to mutations.

Wind Turbine Optimization with WISDEM

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

Dykes, Katherine L; Damiani, Rick R; Graf, Peter A

This presentation for the Fourth Wind Energy Systems Engineering Workshop explains the NREL wind energy systems engineering initiative-developed analysis platform and research capability to capture important system interactions to achieve a better understanding of how to improve system-level performance and achieve system-level cost reductions. Topics include Wind-Plant Integrated System Design and Engineering Model (WISDEM) and multidisciplinary design analysis and optimization.

Optimized Free Energies from Bidirectional Single-Molecule Force Spectroscopy

NASA Astrophysics Data System (ADS)

Minh, David D. L.; Adib, Artur B.

2008-05-01

An optimized method for estimating path-ensemble averages using data from processes driven in opposite directions is presented. Based on this estimator, bidirectional expressions for reconstructing free energies and potentials of mean force from single-molecule force spectroscopy—valid for biasing potentials of arbitrary stiffness—are developed. Numerical simulations on a model potential indicate that these methods perform better than unidirectional strategies.

Screening reservoir systems by considering the efficient trade-offs—informing infrastructure investment decisions on the Blue Nile

NASA Astrophysics Data System (ADS)

Geressu, Robel T.; Harou, Julien J.

2015-12-01

Multi-reservoir system planners should consider how new dams impact downstream reservoirs and the potential contribution of each component to coordinated management. We propose an optimized multi-criteria screening approach to identify best performing designs, i.e., the selection, size and operating rules of new reservoirs within multi-reservoir systems. Reservoir release operating rules and storage sizes are optimized concurrently for each separate infrastructure design under consideration. Outputs reveal system trade-offs using multi-dimensional scatter plots where each point represents an approximately Pareto-optimal design. The method is applied to proposed Blue Nile River reservoirs in Ethiopia, where trade-offs between total and firm energy output, aggregate storage and downstream irrigation and energy provision for the best performing designs are evaluated. This proof-of concept study shows that recommended Blue Nile system designs would depend on whether monthly firm energy or annual energy is prioritized. 39 TWh/yr of energy potential is available from the proposed Blue Nile reservoirs. The results show that depending on the amount of energy deemed sufficient, the current maximum capacities of the planned reservoirs could be larger than they need to be. The method can also be used to inform which of the proposed reservoir type and their storage sizes would allow for the highest downstream benefits to Sudan in different objectives of upstream operating objectives (i.e., operated to maximize either average annual energy or firm energy). The proposed approach identifies the most promising system designs, reveals how they imply different trade-offs between metrics of system performance, and helps system planners asses the sensitivity of overall performance to the design parameters of component reservoirs.

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

Krueger, Jens; Micikevicius, Paulius; Williams, Samuel

Reverse Time Migration (RTM) is one of the main approaches in the seismic processing industry for imaging the subsurface structure of the Earth. While RTM provides qualitative advantages over its predecessors, it has a high computational cost warranting implementation on HPC architectures. We focus on three progressively more complex kernels extracted from RTM: for isotropic (ISO), vertical transverse isotropic (VTI) and tilted transverse isotropic (TTI) media. In this work, we examine performance optimization of forward wave modeling, which describes the computational kernels used in RTM, on emerging multi- and manycore processors and introduce a novel common subexpression elimination optimization formore » TTI kernels. We compare attained performance and energy efficiency in both the single-node and distributed memory environments in order to satisfy industry’s demands for fidelity, performance, and energy efficiency. Moreover, we discuss the interplay between architecture (chip and system) and optimizations (both on-node computation) highlighting the importance of NUMA-aware approaches to MPI communication. Ultimately, our results show we can improve CPU energy efficiency by more than 10× on Magny Cours nodes while acceleration via multiple GPUs can surpass the energy-efficient Intel Sandy Bridge by as much as 3.6×.« less

Automatic threshold optimization in nonlinear energy operator based spike detection.

PubMed

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

2016-08-01

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

Box-Behnken statistical design to optimize thermal performance of energy storage systems

NASA Astrophysics Data System (ADS)

Jalalian, Iman Joz; Mohammadiun, Mohammad; Moqadam, Hamid Hashemi; Mohammadiun, Hamid

2018-05-01

Latent heat thermal storage (LHTS) is a technology that can help to reduce energy consumption for cooling applications, where the cold is stored in phase change materials (PCMs). In the present study a comprehensive theoretical and experimental investigation is performed on a LHTES system containing RT25 as phase change material (PCM). Process optimization of the experimental conditions (inlet air temperature and velocity and number of slabs) was carried out by means of Box-Behnken design (BBD) of Response surface methodology (RSM). Two parameters (cooling time and COP value) were chosen to be the responses. Both of the responses were significantly influenced by combined effect of inlet air temperature with velocity and number of slabs. Simultaneous optimization was performed on the basis of the desirability function to determine the optimal conditions for the cooling time and COP value. Maximum cooling time (186 min) and COP value (6.04) were found at optimum process conditions i.e. inlet temperature of (32.5), air velocity of (1.98) and slab number of (7).

Performance investigation on dissipative dielectric elastomer generators with a triangular energy harvesting scheme

NASA Astrophysics Data System (ADS)

Fan, Peng; Chen, Hualing; Li, Bo; Wang, Yongquan

2017-11-01

In this letter, a theoretical framework describing an energy harvesting cycle including the loss of tension (LT) process is proposed to investigate the energy harvesting performance of a dielectric elastomer generator (DEG) with a triangular energy harvesting scheme by considering material viscosity and leakage current. As the external force that is applied to the membrane decreases, the membrane is relaxed. When the external force decreases to zero, the condition is known as LT. Then the membrane undergoing LT can further relax, which is referred to as the LT process. The LT process is usually ignored in theoretical analysis but observed from energy harvesting experiments of DEGs. It is also studied how shrinking time and transfer capacitor affect the energy conversion of a DEG. The results indicate that energy density and conversion efficiency can be simultaneously improved by choosing appropriate shrinking time and transfer capacitor to optimize the energy harvesting cycle. The results and methods are expected to provide guidelines for the optimal design and assessment of DEGs.

Relay Selection for Cooperative Relaying in Wireless Energy Harvesting Networks

NASA Astrophysics Data System (ADS)

Zhu, Kaiyan; Wang, Fei; Li, Songsong; Jiang, Fengjiao; Cao, Lijie

2018-01-01

Energy harvesting from the surroundings is a promising solution to provide energy supply and extend the life of wireless sensor networks. Recently, energy harvesting has been shown as an attractive solution to prolong the operation of cooperative networks. In this paper, we propose a relay selection scheme to optimize the amplify-and-forward (AF) cooperative transmission in wireless energy harvesting cooperative networks. The harvesting energy and channel conditions are considered to select the optimal relay as cooperative relay to minimize the outage probability of the system. Simulation results show that our proposed relay selection scheme achieves better outage performance than other strategies.

Fuel consumption optimization for smart hybrid electric vehicle during a car-following process

NASA Astrophysics Data System (ADS)

Li, Liang; Wang, Xiangyu; Song, Jian

2017-03-01

Hybrid electric vehicles (HEVs) provide large potential to save energy and reduce emission, and smart vehicles bring out great convenience and safety for drivers. By combining these two technologies, vehicles may achieve excellent performances in terms of dynamic, economy, environmental friendliness, safety, and comfort. Hence, a smart hybrid electric vehicle (s-HEV) is selected as a platform in this paper to study a car-following process with optimizing the fuel consumption. The whole process is a multi-objective optimal problem, whose optimal solution is not just adding an energy management strategy (EMS) to an adaptive cruise control (ACC), but a deep fusion of these two methods. The problem has more restricted conditions, optimal objectives, and system states, which may result in larger computing burden. Therefore, a novel fuel consumption optimization algorithm based on model predictive control (MPC) is proposed and some search skills are adopted in receding horizon optimization to reduce computing burden. Simulations are carried out and the results indicate that the fuel consumption of proposed method is lower than that of the ACC+EMS method on the condition of ensuring car-following performances.

Energy Efficiency Maximization for WSNs with Simultaneous Wireless Information and Power Transfer

PubMed Central

Yu, Hongyan; Zhang, Yongqiang; Yang, Yuanyuan; Ji, Luyue

2017-01-01

Recently, the simultaneous wireless information and power transfer (SWIPT) technique has been regarded as a promising approach to enhance performance of wireless sensor networks with limited energy supply. However, from a green communication perspective, energy efficiency optimization for SWIPT system design has not been investigated in Wireless Rechargeable Sensor Networks (WRSNs). In this paper, we consider the tradeoffs between energy efficiency and three factors including spectral efficiency, the transmit power and outage target rate for two different modes, i.e., power splitting (PS) and time switching modes (TS), at the receiver. Moreover, we formulate the energy efficiency maximization problem subject to the constraints of minimum Quality of Service (QoS), minimum harvested energy and maximum transmission power as non-convex optimization problem. In particular, we focus on optimizing power control and power allocation policy in PS and TS modes to maximize energy efficiency of data transmission. For PS and TS modes, we propose the corresponding algorithm to characterize a non-convex optimization problem that takes into account the circuit power consumption and the harvested energy. By exploiting nonlinear fractional programming and Lagrangian dual decomposition, we propose suboptimal iterative algorithms to obtain the solutions of non-convex optimization problems. Furthermore, we derive the outage probability and effective throughput from the scenarios that the transmitter does not or partially know the channel state information (CSI) of the receiver. Simulation results illustrate that the proposed optimal iterative algorithm can achieve optimal solutions within a small number of iterations and various tradeoffs between energy efficiency and spectral efficiency, transmit power and outage target rate, respectively. PMID:28820496

Energy Efficiency Maximization for WSNs with Simultaneous Wireless Information and Power Transfer.

PubMed

Yu, Hongyan; Zhang, Yongqiang; Guo, Songtao; Yang, Yuanyuan; Ji, Luyue

2017-08-18

Recently, the simultaneous wireless information and power transfer (SWIPT) technique has been regarded as a promising approach to enhance performance of wireless sensor networks with limited energy supply. However, from a green communication perspective, energy efficiency optimization for SWIPT system design has not been investigated in Wireless Rechargeable Sensor Networks (WRSNs). In this paper, we consider the tradeoffs between energy efficiency and three factors including spectral efficiency, the transmit power and outage target rate for two different modes, i.e., power splitting (PS) and time switching modes (TS), at the receiver. Moreover, we formulate the energy efficiency maximization problem subject to the constraints of minimum Quality of Service (QoS), minimum harvested energy and maximum transmission power as non-convex optimization problem. In particular, we focus on optimizing power control and power allocation policy in PS and TS modes to maximize energy efficiency of data transmission. For PS and TS modes, we propose the corresponding algorithm to characterize a non-convex optimization problem that takes into account the circuit power consumption and the harvested energy. By exploiting nonlinear fractional programming and Lagrangian dual decomposition, we propose suboptimal iterative algorithms to obtain the solutions of non-convex optimization problems. Furthermore, we derive the outage probability and effective throughput from the scenarios that the transmitter does not or partially know the channel state information (CSI) of the receiver. Simulation results illustrate that the proposed optimal iterative algorithm can achieve optimal solutions within a small number of iterations and various tradeoffs between energy efficiency and spectral efficiency, transmit power and outage target rate, respectively.

Optimization design of energy deposition on single expansion ramp nozzle

NASA Astrophysics Data System (ADS)

Ju, Shengjun; Yan, Chao; Wang, Xiaoyong; Qin, Yupei; Ye, Zhifei

2017-11-01

Optimization design has been widely used in the aerodynamic design process of scramjets. The single expansion ramp nozzle is an important component for scramjets to produces most of thrust force. A new concept of increasing the aerodynamics of the scramjet nozzle with energy deposition is presented. The essence of the method is to create a heated region in the inner flow field of the scramjet nozzle. In the current study, the two-dimensional coupled implicit compressible Reynolds Averaged Navier-Stokes and Menter's shear stress transport turbulence model have been applied to numerically simulate the flow fields of the single expansion ramp nozzle with and without energy deposition. The numerical results show that the proposal of energy deposition can be an effective method to increase force characteristics of the scramjet nozzle, the thrust coefficient CT increase by 6.94% and lift coefficient CN decrease by 26.89%. Further, the non-dominated sorting genetic algorithm coupled with the Radial Basis Function neural network surrogate model has been employed to determine optimum location and density of the energy deposition. The thrust coefficient CT and lift coefficient CN are selected as objective functions, and the sampling points are obtained numerically by using a Latin hypercube design method. The optimized thrust coefficient CT further increase by 1.94%, meanwhile, the optimized lift coefficient CN further decrease by 15.02% respectively. At the same time, the optimized performances are in good and reasonable agreement with the numerical predictions. The findings suggest that scramjet nozzle design and performance can benefit from the application of energy deposition.

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

NASA Astrophysics Data System (ADS)

Latief, Y.; Berawi, M. A.; Koesalamwardi, A. B.; Supriadi, L. S. R.

2018-03-01

Near Zero Energy House (NZEH) is a housing building that provides energy efficiency by using renewable energy technologies and passive house design. Currently, the costs for NZEH are quite expensive due to the high costs of the equipment and materials for solar panel, insulation, fenestration and other renewable energy technology. Therefore, a study to obtain the optimum design of a NZEH is necessary. The aim of the optimum design is achieving an economical life cycle cost performance of the NZEH. One of the optimization methods that could be utilized is Genetic Algorithm. It provides the method to obtain the optimum design based on the combinations of NZEH variable designs. This paper discusses the study to identify the optimum design of a NZEH that provides an optimum life cycle cost performance using Genetic Algorithm. In this study, an experiment through extensive design simulations of a one-level house model was conducted. As a result, the study provide the optimum design from combinations of NZEH variable designs, which are building orientation, window to wall ratio, and glazing types that would maximize the energy generated by photovoltaic panel. Hence, the design would support an optimum life cycle cost performance of the house.

Relay selection in energy harvesting cooperative networks with rateless codes

NASA Astrophysics Data System (ADS)

Zhu, Kaiyan; Wang, Fei

2018-04-01

This paper investigates the relay selection in energy harvesting cooperative networks, where the relays harvests energy from the radio frequency (RF) signals transmitted by a source, and the optimal relay is selected and uses the harvested energy to assist the information transmission from the source to its destination. Both source and the selected relay transmit information using rateless code, which allows the destination recover original information after collecting codes bits marginally surpass the entropy of original information. In order to improve transmission performance and efficiently utilize the harvested power, the optimal relay is selected. The optimization problem are formulated to maximize the achievable information rates of the system. Simulation results demonstrate that our proposed relay selection scheme outperform other strategies.

Energy Minimization of Discrete Protein Titration State Models Using Graph Theory.

PubMed

Purvine, Emilie; Monson, Kyle; Jurrus, Elizabeth; Star, Keith; Baker, Nathan A

2016-08-25

There are several applications in computational biophysics that require the optimization of discrete interacting states, for example, amino acid titration states, ligand oxidation states, or discrete rotamer angles. Such optimization can be very time-consuming as it scales exponentially in the number of sites to be optimized. In this paper, we describe a new polynomial time algorithm for optimization of discrete states in macromolecular systems. This algorithm was adapted from image processing and uses techniques from discrete mathematics and graph theory to restate the optimization problem in terms of "maximum flow-minimum cut" graph analysis. The interaction energy graph, a graph in which vertices (amino acids) and edges (interactions) are weighted with their respective energies, is transformed into a flow network in which the value of the minimum cut in the network equals the minimum free energy of the protein and the cut itself encodes the state that achieves the minimum free energy. Because of its deterministic nature and polynomial time performance, this algorithm has the potential to allow for the ionization state of larger proteins to be discovered.

Energy Minimization of Discrete Protein Titration State Models Using Graph Theory

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

Purvine, Emilie AH; Monson, Kyle E.; Jurrus, Elizabeth R.

There are several applications in computational biophysics which require the optimization of discrete interacting states; e.g., amino acid titration states, ligand oxidation states, or discrete rotamer angles. Such optimization can be very time-consuming as it scales exponentially in the number of sites to be optimized. In this paper, we describe a new polynomial-time algorithm for optimization of discrete states in macromolecular systems. This algorithm was adapted from image processing and uses techniques from discrete mathematics and graph theory to restate the optimization problem in terms of maximum flow-minimum cut graph analysis. The interaction energy graph, a graph in which verticesmore » (amino acids) and edges (interactions) are weighted with their respective energies, is transformed into a flow network in which the value of the minimum cut in the network equals the minimum free energy of the protein, and the cut itself encodes the state that achieves the minimum free energy. Because of its deterministic nature and polynomial-time performance, this algorithm has the potential to allow for the ionization state of larger proteins to be discovered.« less

Energy Minimization of Discrete Protein Titration State Models Using Graph Theory

PubMed Central

Purvine, Emilie; Monson, Kyle; Jurrus, Elizabeth; Star, Keith; Baker, Nathan A.

2016-01-01

There are several applications in computational biophysics which require the optimization of discrete interacting states; e.g., amino acid titration states, ligand oxidation states, or discrete rotamer angles. Such optimization can be very time-consuming as it scales exponentially in the number of sites to be optimized. In this paper, we describe a new polynomial-time algorithm for optimization of discrete states in macromolecular systems. This algorithm was adapted from image processing and uses techniques from discrete mathematics and graph theory to restate the optimization problem in terms of “maximum flow-minimum cut” graph analysis. The interaction energy graph, a graph in which vertices (amino acids) and edges (interactions) are weighted with their respective energies, is transformed into a flow network in which the value of the minimum cut in the network equals the minimum free energy of the protein, and the cut itself encodes the state that achieves the minimum free energy. Because of its deterministic nature and polynomial-time performance, this algorithm has the potential to allow for the ionization state of larger proteins to be discovered. PMID:27089174

Optimisation structurelle des systemes energetiques

NASA Astrophysics Data System (ADS)

Saloux, Etienne

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

Multi-parameter optimization of piezoelectric actuators for multi-mode active vibration control of cylindrical shells

NASA Astrophysics Data System (ADS)

Hu, K. M.; Li, Hua

2018-07-01

A novel technique for the multi-parameter optimization of distributed piezoelectric actuators is presented in this paper. The proposed method is designed to improve the performance of multi-mode vibration control in cylindrical shells. The optimization parameters of actuator patch configuration include position, size, and tilt angle. The modal control force of tilted orthotropic piezoelectric actuators is derived and the multi-parameter cylindrical shell optimization model is established. The linear quadratic energy index is employed as the optimization criterion. A geometric constraint is proposed to prevent overlap between tilted actuators, which is plugged into a genetic algorithm to search the optimal configuration parameters. A simply-supported closed cylindrical shell with two actuators serves as a case study. The vibration control efficiencies of various parameter sets are evaluated via frequency response and transient response simulations. The results show that the linear quadratic energy indexes of position and size optimization decreased by 14.0% compared to position optimization; those of position and tilt angle optimization decreased by 16.8%; and those of position, size, and tilt angle optimization decreased by 25.9%. It indicates that, adding configuration optimization parameters is an efficient approach to improving the vibration control performance of piezoelectric actuators on shells.

Optimization under Uncertainty of a Biomass-integrated Renewable Energy Microgrid with Energy Storage

NASA Astrophysics Data System (ADS)

Zheng, Yingying

The growing energy demands and needs for reducing carbon emissions call more and more attention to the development of renewable energy technologies and management strategies. Microgrids have been developed around the world as a means to address the high penetration level of renewable generation and reduce greenhouse gas emissions while attempting to address supply-demand balancing at a more local level. This dissertation presents a model developed to optimize the design of a biomass-integrated renewable energy microgrid employing combined heat and power with energy storage. A receding horizon optimization with Monte Carlo simulation were used to evaluate optimal microgrid design and dispatch under uncertainties in the renewable energy and utility grid energy supplies, the energy demands, and the economic assumptions so as to generate a probability density function for the cost of energy. Case studies were examined for a conceptual utility grid-connected microgrid application in Davis, California. The results provide the most cost effective design based on the assumed energy load profile, local climate data, utility tariff structure, and technical and financial performance of the various components of the microgrid. Sensitivity and uncertainty analyses are carried out to illuminate the key parameters that influence the energy costs. The model application provides a means to determine major risk factors associated with alternative design integration and operating strategies.

An Optimal Free Energy Dissipation Strategy of the MinCDE Oscillator in Regulating Symmetric Bacterial Cell Division

PubMed Central

Xiong, Liping; Lan, Ganhui

2015-01-01

Sustained molecular oscillations are ubiquitous in biology. The obtained oscillatory patterns provide vital functions as timekeepers, pacemakers and spacemarkers. Models based on control theory have been introduced to explain how specific oscillatory behaviors stem from protein interaction feedbacks, whereas the energy dissipation through the oscillating processes and its role in the regulatory function remain unexplored. Here we developed a general framework to assess an oscillator’s regulation performance at different dissipation levels. Using the Escherichia coli MinCDE oscillator as a model system, we showed that a sufficient amount of energy dissipation is needed to switch on the oscillation, which is tightly coupled to the system’s regulatory performance. Once the dissipation level is beyond this threshold, unlike stationary regulators’ monotonic performance-to-cost relation, excess dissipation at certain steps in the oscillating process damages the oscillator’s regulatory performance. We further discovered that the chemical free energy from ATP hydrolysis has to be strategically assigned to the MinE-aided MinD release and the MinD immobilization steps for optimal performance, and a higher energy budget improves the robustness of the oscillator. These results unfold a novel mode by which living systems trade energy for regulatory function. PMID:26317492

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.

Building-to-Grid Integration through Commercial Building Portfolios Participating in Energy and Frequency Regulation Markets

NASA Astrophysics Data System (ADS)

Pavlak, Gregory S.

Building energy use is a significant contributing factor to growing worldwide energy demands. In pursuit of a sustainable energy future, commercial building operations must be intelligently integrated with the electric system to increase efficiency and enable renewable generation. Toward this end, a model-based methodology was developed to estimate the capability of commercial buildings to participate in frequency regulation ancillary service markets. This methodology was integrated into a supervisory model predictive controller to optimize building operation in consideration of energy prices, demand charges, and ancillary service revenue. The supervisory control problem was extended to building portfolios to evaluate opportunities for synergistic effect among multiple, centrally-optimized buildings. Simulation studies performed showed that the multi-market optimization was able to determine appropriate opportunities for buildings to provide frequency regulation. Total savings were increased by up to thirteen percentage points, depending on the simulation case. Furthermore, optimizing buildings as a portfolio achieved up to seven additional percentage points of savings, depending on the case. Enhanced energy and cost savings opportunities were observed by taking the novel perspective of optimizing building portfolios in multiple grid markets, motivating future pursuits of advanced control paradigms that enable a more intelligent electric grid.

Optimization Under Uncertainty of Site-Specific Turbine Configurations

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

Quick, J.; Dykes, K.; Graf, P.

Uncertainty affects many aspects of wind energy plant performance and cost. In this study, we explore opportunities for site-specific turbine configuration optimization that accounts for uncertainty in the wind resource. As a demonstration, a simple empirical model for wind plant cost of energy is used in an optimization under uncertainty to examine how different risk appetites affect the optimal selection of a turbine configuration for sites of different wind resource profiles. Lastly, if there is unusually high uncertainty in the site wind resource, the optimal turbine configuration diverges from the deterministic case and a generally more conservative design is obtainedmore » with increasing risk aversion on the part of the designer.« less

Optimization under Uncertainty of Site-Specific Turbine Configurations: Preprint

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

Quick, Julian; Dykes, Katherine; Graf, Peter

Uncertainty affects many aspects of wind energy plant performance and cost. In this study, we explore opportunities for site-specific turbine configuration optimization that accounts for uncertainty in the wind resource. As a demonstration, a simple empirical model for wind plant cost of energy is used in an optimization under uncertainty to examine how different risk appetites affect the optimal selection of a turbine configuration for sites of different wind resource profiles. If there is unusually high uncertainty in the site wind resource, the optimal turbine configuration diverges from the deterministic case and a generally more conservative design is obtained withmore » increasing risk aversion on the part of the designer.« less

Optimization Under Uncertainty of Site-Specific Turbine Configurations

DOE PAGES

Quick, J.; Dykes, K.; Graf, P.; ...

2016-10-03

Uncertainty affects many aspects of wind energy plant performance and cost. In this study, we explore opportunities for site-specific turbine configuration optimization that accounts for uncertainty in the wind resource. As a demonstration, a simple empirical model for wind plant cost of energy is used in an optimization under uncertainty to examine how different risk appetites affect the optimal selection of a turbine configuration for sites of different wind resource profiles. Lastly, if there is unusually high uncertainty in the site wind resource, the optimal turbine configuration diverges from the deterministic case and a generally more conservative design is obtainedmore » with increasing risk aversion on the part of the designer.« less

Energy Storage Thermal Management | Transportation Research | NREL

Science.gov Websites

Thermal Management Energy Storage Thermal Management Infrared image of rectangular battery cell -designed thermal management system is critical to the life and performance of electric-drive vehicles (EDVs . NREL conducts thermal management research and development (R&D) to optimize battery performance and

Effectiveness Testing of a Piezoelectric Energy Harvester for an Automobile Wheel Using Stochastic Resonance

PubMed Central

Zhang, Yunshun; Zheng, Rencheng; Shimono, Keisuke; Kaizuka, Tsutomu; Nakano, Kimihiko

2016-01-01

The collection of clean power from ambient vibrations is considered a promising method for energy harvesting. For the case of wheel rotation, the present study investigates the effectiveness of a piezoelectric energy harvester, with the application of stochastic resonance to optimize the efficiency of energy harvesting. It is hypothesized that when the wheel rotates at variable speeds, the energy harvester is subjected to on-road noise as ambient excitations and a tangentially acting gravity force as a periodic modulation force, which can stimulate stochastic resonance. The energy harvester was miniaturized with a bistable cantilever structure, and the on-road noise was measured for the implementation of a vibrator in an experimental setting. A validation experiment revealed that the harvesting system was optimized to capture power that was approximately 12 times that captured under only on-road noise excitation and 50 times that captured under only the periodic gravity force. Moreover, the investigation of up-sweep excitations with increasing rotational frequency confirmed that stochastic resonance is effective in optimizing the performance of the energy harvester, with a certain bandwidth of vehicle speeds. An actual-vehicle experiment validates that the prototype harvester using stochastic resonance is capable of improving power generation performance for practical tire application. PMID:27763522

Effectiveness Testing of a Piezoelectric Energy Harvester for an Automobile Wheel Using Stochastic Resonance.

PubMed

Zhang, Yunshun; Zheng, Rencheng; Shimono, Keisuke; Kaizuka, Tsutomu; Nakano, Kimihiko

2016-10-17

The collection of clean power from ambient vibrations is considered a promising method for energy harvesting. For the case of wheel rotation, the present study investigates the effectiveness of a piezoelectric energy harvester, with the application of stochastic resonance to optimize the efficiency of energy harvesting. It is hypothesized that when the wheel rotates at variable speeds, the energy harvester is subjected to on-road noise as ambient excitations and a tangentially acting gravity force as a periodic modulation force, which can stimulate stochastic resonance. The energy harvester was miniaturized with a bistable cantilever structure, and the on-road noise was measured for the implementation of a vibrator in an experimental setting. A validation experiment revealed that the harvesting system was optimized to capture power that was approximately 12 times that captured under only on-road noise excitation and 50 times that captured under only the periodic gravity force. Moreover, the investigation of up-sweep excitations with increasing rotational frequency confirmed that stochastic resonance is effective in optimizing the performance of the energy harvester, with a certain bandwidth of vehicle speeds. An actual-vehicle experiment validates that the prototype harvester using stochastic resonance is capable of improving power generation performance for practical tire application.

A collimator optimization method for quantitative imaging: application to Y-90 bremsstrahlung SPECT.

PubMed

Rong, Xing; Frey, Eric C

2013-08-01

Post-therapy quantitative 90Y bremsstrahlung single photon emission computed tomography (SPECT) has shown great potential to provide reliable activity estimates, which are essential for dose verification. Typically 90Y imaging is performed with high- or medium-energy collimators. However, the energy spectrum of 90Y bremsstrahlung photons is substantially different than typical for these collimators. In addition, dosimetry requires quantitative images, and collimators are not typically optimized for such tasks. Optimizing a collimator for 90Y imaging is both novel and potentially important. Conventional optimization methods are not appropriate for 90Y bremsstrahlung photons, which have a continuous and broad energy distribution. In this work, the authors developed a parallel-hole collimator optimization method for quantitative tasks that is particularly applicable to radionuclides with complex emission energy spectra. The authors applied the proposed method to develop an optimal collimator for quantitative 90Y bremsstrahlung SPECT in the context of microsphere radioembolization. To account for the effects of the collimator on both the bias and the variance of the activity estimates, the authors used the root mean squared error (RMSE) of the volume of interest activity estimates as the figure of merit (FOM). In the FOM, the bias due to the null space of the image formation process was taken in account. The RMSE was weighted by the inverse mass to reflect the application to dosimetry; for a different application, more relevant weighting could easily be adopted. The authors proposed a parameterization for the collimator that facilitates the incorporation of the important factors (geometric sensitivity, geometric resolution, and septal penetration fraction) determining collimator performance, while keeping the number of free parameters describing the collimator small (i.e., two parameters). To make the optimization results for quantitative 90Y bremsstrahlung SPECT more general, the authors simulated multiple tumors of various sizes in the liver. The authors realistically simulated human anatomy using a digital phantom and the image formation process using a previously validated and computationally efficient method for modeling the image-degrading effects including object scatter, attenuation, and the full collimator-detector response (CDR). The scatter kernels and CDR function tables used in the modeling method were generated using a previously validated Monte Carlo simulation code. The hole length, hole diameter, and septal thickness of the obtained optimal collimator were 84, 3.5, and 1.4 mm, respectively. Compared to a commercial high-energy general-purpose collimator, the optimal collimator improved the resolution and FOM by 27% and 18%, respectively. The proposed collimator optimization method may be useful for improving quantitative SPECT imaging for radionuclides with complex energy spectra. The obtained optimal collimator provided a substantial improvement in quantitative performance for the microsphere radioembolization task considered.

QM/MM Geometry Optimization on Extensive Free-Energy Surfaces for Examination of Enzymatic Reactions and Design of Novel Functional Properties of Proteins.

PubMed

Hayashi, Shigehiko; Uchida, Yoshihiro; Hasegawa, Taisuke; Higashi, Masahiro; Kosugi, Takahiro; Kamiya, Motoshi

2017-05-05

Many remarkable molecular functions of proteins use their characteristic global and slow conformational dynamics through coupling of local chemical states in reaction centers with global conformational changes of proteins. To theoretically examine the functional processes of proteins in atomic detail, a methodology of quantum mechanical/molecular mechanical (QM/MM) free-energy geometry optimization is introduced. In the methodology, a geometry optimization of a local reaction center is performed with a quantum mechanical calculation on a free-energy surface constructed with conformational samples of the surrounding protein environment obtained by a molecular dynamics simulation with a molecular mechanics force field. Geometry optimizations on extensive free-energy surfaces by a QM/MM reweighting free-energy self-consistent field method designed to be variationally consistent and computationally efficient have enabled examinations of the multiscale molecular coupling of local chemical states with global protein conformational changes in functional processes and analysis and design of protein mutants with novel functional properties.

QM/MM Geometry Optimization on Extensive Free-Energy Surfaces for Examination of Enzymatic Reactions and Design of Novel Functional Properties of Proteins

NASA Astrophysics Data System (ADS)

Hayashi, Shigehiko; Uchida, Yoshihiro; Hasegawa, Taisuke; Higashi, Masahiro; Kosugi, Takahiro; Kamiya, Motoshi

2017-05-01

Many remarkable molecular functions of proteins use their characteristic global and slow conformational dynamics through coupling of local chemical states in reaction centers with global conformational changes of proteins. To theoretically examine the functional processes of proteins in atomic detail, a methodology of quantum mechanical/molecular mechanical (QM/MM) free-energy geometry optimization is introduced. In the methodology, a geometry optimization of a local reaction center is performed with a quantum mechanical calculation on a free-energy surface constructed with conformational samples of the surrounding protein environment obtained by a molecular dynamics simulation with a molecular mechanics force field. Geometry optimizations on extensive free-energy surfaces by a QM/MM reweighting free-energy self-consistent field method designed to be variationally consistent and computationally efficient have enabled examinations of the multiscale molecular coupling of local chemical states with global protein conformational changes in functional processes and analysis and design of protein mutants with novel functional properties.

Hierarchical fuzzy control of low-energy building systems

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

Yu, Zhen; Dexter, Arthur

2010-04-15

A hierarchical fuzzy supervisory controller is described that is capable of optimizing the operation of a low-energy building, which uses solar energy to heat and cool its interior spaces. The highest level fuzzy rules choose the most appropriate set of lower level rules according to the weather and occupancy information; the second level fuzzy rules determine an optimal energy profile and the overall modes of operation of the heating, ventilating and air-conditioning system (HVAC); the third level fuzzy rules select the mode of operation of specific equipment, and assign schedules to the local controllers so that the optimal energy profilemore » can be achieved in the most efficient way. Computer simulation is used to compare the hierarchical fuzzy control scheme with a supervisory control scheme based on expert rules. The performance is evaluated by comparing the energy consumption and thermal comfort. (author)« less

Energy Performance Monitoring and Optimization System for DoD Campuses

DTIC Science & Technology

2014-02-01

estimated that, on average, the EPMO system exceeded the energy consumption reduction target of 20% and improved occupant thermal comfort by reducing the...dynamic models, operational and thermal comfort constraints, and plant efficiency in the same framework (Borrelli and Keviczky, 2008; Borrelli, Pekar...optimization modeling language uses the models described above in conjunction with information such as: thermal comfort constraints, equipment constraints, and

Thermodynamic Performance and Cost Optimization of a Novel Hybrid Thermal-Compressed Air Energy Storage System Design

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

Houssainy, Sammy; Janbozorgi, Mohammad; Kavehpour, Pirouz

Compressed Air Energy Storage (CAES) can potentially allow renewable energy sources to meet electricity demands as reliably as coal-fired power plants. However, conventional CAES systems rely on the combustion of natural gas, require large storage volumes, and operate at high pressures, which possess inherent problems such as high costs, strict geological locations, and the production of greenhouse gas emissions. A novel and patented hybrid thermal-compressed air energy storage (HT-CAES) design is presented which allows a portion of the available energy, from the grid or renewable sources, to operate a compressor and the remainder to be converted and stored in themore » form of heat, through joule heating in a sensible thermal storage medium. The HT-CAES design incudes a turbocharger unit that provides supplementary mass flow rate alongside the air storage. The hybrid design and the addition of a turbocharger have the beneficial effect of mitigating the shortcomings of conventional CAES systems and its derivatives by eliminating combustion emissions and reducing storage volumes, operating pressures, and costs. Storage efficiency and cost are the two key factors, which upon integration with renewable energies would allow the sources to operate as independent forms of sustainable energy. The potential of the HT-CAES design is illustrated through a thermodynamic optimization study, which outlines key variables that have a major impact on the performance and economics of the storage system. The optimization analysis quantifies the required distribution of energy between thermal and compressed air energy storage, for maximum efficiency, and for minimum cost. This study provides a roundtrip energy and exergy efficiency map of the storage system and illustrates a trade off that exists between its capital cost and performance.« less

Technology and Performance Analysis Tools | Energy Analysis | NREL

Science.gov Websites

optimize renewable energy and energy efficiency technologies for your project. Many of these tools can be the consumer or energy professional. Biomass Scenario Model (BSM) Determine which supply chain changes (BLCC) Analyze capital investments in buildings. Includes the Energy Escalation Rate Calculator 2.0-15

Integrated Solutions for a Complex Energy World - Continuum Magazine |

Science.gov Websites

NREL Integrated Solutions for a Complex Energy World Integrated Solutions for a Complex Energy World Energy systems integration optimizes electrical, thermal, fuel, and data technologies design and performance. An array of clean energy technologies, including wind, solar, and electric vehicle batteries, is

An Energy-Aware Trajectory Optimization Layer for sUAS

NASA Astrophysics Data System (ADS)

Silva, William A.

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

Sport nutrition for young athletes

PubMed Central

Purcell, Laura K

2013-01-01

Nutrition is an important part of sport performance for young athletes, in addition to allowing for optimal growth and development. Macronutrients, micronutrients and fluids in the proper amounts are essential to provide energy for growth and activity. To optimize performance, young athletes need to learn what, when and how to eat and drink before, during and after activity. PMID:24421690

Microgrid Design Analysis Using Technology Management Optimization and the Performance Reliability Model

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

Stamp, Jason E.; Eddy, John P.; Jensen, Richard P.

Microgrids are a focus of localized energy production that support resiliency, security, local con- trol, and increased access to renewable resources (among other potential benefits). The Smart Power Infrastructure Demonstration for Energy Reliability and Security (SPIDERS) Joint Capa- bility Technology Demonstration (JCTD) program between the Department of Defense (DOD), Department of Energy (DOE), and Department of Homeland Security (DHS) resulted in the pre- liminary design and deployment of three microgrids at military installations. This paper is focused on the analysis process and supporting software used to determine optimal designs for energy surety microgrids (ESMs) in the SPIDERS project. There aremore » two key pieces of software, an ex- isting software application developed by Sandia National Laboratories (SNL) called Technology Management Optimization (TMO) and a new simulation developed for SPIDERS called the per- formance reliability model (PRM). TMO is a decision support tool that performs multi-objective optimization over a mixed discrete/continuous search space for which the performance measures are unrestricted in form. The PRM is able to statistically quantify the performance and reliability of a microgrid operating in islanded mode (disconnected from any utility power source). Together, these two software applications were used as part of the ESM process to generate the preliminary designs presented by SNL-led DOE team to the DOD. Acknowledgements Sandia National Laboratories and the SPIDERS technical team would like to acknowledge the following for help in the project: * Mike Hightower, who has been the key driving force for Energy Surety Microgrids * Juan Torres and Abbas Akhil, who developed the concept of microgrids for military instal- lations * Merrill Smith, U.S. Department of Energy SPIDERS Program Manager * Ross Roley and Rich Trundy from U.S. Pacific Command * Bill Waugaman and Bill Beary from U.S. Northern Command * Tarek Abdallah, Melanie Johnson, and Harold Sanborn of the U.S. Army Corps of Engineers Construction Engineering Research Laboratory * Colleagues from Sandia National Laboratories (SNL) for their reviews, suggestions, and participation in the work.« less

Optimized design and control of an off grid solar PV/hydrogen fuel cell power system for green buildings

NASA Astrophysics Data System (ADS)

Ghenai, C.; Bettayeb, M.

2017-11-01

Modelling, simulation, optimization and control strategies are used in this study to design a stand-alone solar PV/Fuel Cell/Battery/Generator hybrid power system to serve the electrical load of a commercial building. The main objective is to design an off grid energy system to meet the desired electric load of the commercial building with high renewable fraction, low emissions and low cost of energy. The goal is to manage the energy consumption of the building, reduce the associate cost and to switch from grid-tied fossil fuel power system to an off grid renewable and cleaner power system. Energy audit was performed in this study to determine the energy consumption of the building. Hourly simulations, modelling and optimization were performed to determine the performance and cost of the hybrid power configurations using different control strategies. The results show that the hybrid off grid solar PV/Fuel Cell/Generator/Battery/Inverter power system offers the best performance for the tested system architectures. From the total energy generated from the off grid hybrid power system, 73% is produced from the solar PV, 24% from the fuel cell and 3% from the backup Diesel generator. The produced power is used to meet all the AC load of the building without power shortage (<0.1%). The hybrid power system produces 18.2% excess power that can be used to serve the thermal load of the building. The proposed hybrid power system is sustainable, economically viable and environmentally friendly: High renewable fraction (66.1%), low levelized cost of energy (92 /MWh), and low carbon dioxide emissions (24 kg CO2/MWh) are achieved.

Full Wave Function Optimization with Quantum Monte Carlo and Its Effect on the Dissociation Energy of FeS.

PubMed

Haghighi Mood, Kaveh; Lüchow, Arne

2017-08-17

Diffusion quantum Monte Carlo calculations with partial and full optimization of the guide function are carried out for the dissociation of the FeS molecule. For the first time, quantum Monte Carlo orbital optimization for transition metal compounds is performed. It is demonstrated that energy optimization of the orbitals of a complete active space wave function in the presence of a Jastrow correlation function is required to obtain agreement with the experimental dissociation energy. Furthermore, it is shown that orbital optimization leads to a 5 Δ ground state, in agreement with experiments but in disagreement with other high-level ab initio wave function calculations which all predict a 5 Σ + ground state. The role of the Jastrow factor in DMC calculations with pseudopotentials is investigated. The results suggest that a large Jastrow factor may improve the DMC accuracy substantially at small additional cost.

Simultaneous optimization of biomolecular energy function on features from small molecules and macromolecules

PubMed Central

Park, Hahnbeom; Bradley, Philip; Greisen, Per; Liu, Yuan; Mulligan, Vikram Khipple; Kim, David E.; Baker, David; DiMaio, Frank

2017-01-01

Most biomolecular modeling energy functions for structure prediction, sequence design, and molecular docking, have been parameterized using existing macromolecular structural data; this contrasts molecular mechanics force fields which are largely optimized using small-molecule data. In this study, we describe an integrated method that enables optimization of a biomolecular modeling energy function simultaneously against small-molecule thermodynamic data and high-resolution macromolecular structural data. We use this approach to develop a next-generation Rosetta energy function that utilizes a new anisotropic implicit solvation model, and an improved electrostatics and Lennard-Jones model, illustrating how energy functions can be considerably improved in their ability to describe large-scale energy landscapes by incorporating both small-molecule and macromolecule data. The energy function improves performance in a wide range of protein structure prediction challenges, including monomeric structure prediction, protein-protein and protein-ligand docking, protein sequence design, and prediction of the free energy changes by mutation, while reasonably recapitulating small-molecule thermodynamic properties. PMID:27766851

Dual-Energy Contrast-Enhanced Breast Tomosynthesis: Optimization of Beam Quality for Dose and Image Quality

PubMed Central

Samei, Ehsan; Saunders, Robert S.

2014-01-01

Dual-energy contrast-enhanced breast tomosynthesis is a promising technique to obtain three-dimensional functional information from the breast with high resolution and speed. To optimize this new method, this study searched for the beam quality that maximized image quality in terms of mass detection performance. A digital tomosynthesis system was modeled using a fast ray-tracing algorithm, which created simulated projection images by tracking photons through a voxelized anatomical breast phantom containing iodinated lesions. The single-energy images were combined into dual-energy images through a weighted log subtraction process. The weighting factor was optimized to minimize anatomical noise, while the dose distribution was chosen to minimize quantum noise. The dual-energy images were analyzed for the signal difference to noise ratio (SdNR) of iodinated masses. The fast ray-tracing explored 523,776 dual-energy combinations to identify which yields optimum mass SdNR. The ray-tracing results were verified using a Monte Carlo model for a breast tomosynthesis system with a selenium-based flat-panel detector. The projection images from our voxelized breast phantom were obtained at a constant total glandular dose. The projections were combined using weighted log subtraction and reconstructed using commercial reconstruction software. The lesion SdNR was measured in the central reconstructed slice. The SdNR performance varied markedly across the kVp and filtration space. Ray-tracing results indicated that the mass SdNR was maximized with a high-energy tungsten beam at 49 kVp with 92.5 μm of copper filtration and a low-energy tungsten beam at 49 kVp with 95 μm of tin filtration. This result was consistent with Monte Carlo findings. This mammographic technique led to a mass SdNR of 0.92 ± 0.03 in the projections and 3.68 ± 0.19 in the reconstructed slices. These values were markedly higher than those for non-optimized techniques. Our findings indicate that dual-energy breast tomosynthesis can be performed optimally at 49 kVp with alternative copper and tin filters, with reconstruction following weighted subtraction. The optimum technique provides best visibility of iodine against structured breast background in dual-energy contrast-enhanced breast tomosynthesis. PMID:21908902

An optimal open/closed-loop control method with application to a pre-stressed thin duralumin plate

NASA Astrophysics Data System (ADS)

Nadimpalli, Sruthi Raju

The excessive vibrations of a pre-stressed duralumin plate, suppressed by a combination of open-loop and closed-loop controls, also known as open/closed-loop control, is studied in this thesis. The two primary steps involved in this process are: Step (I) with an assumption that the closed-loop control law is proportional, obtain the optimal open-loop control by direct minimization of the performance measure consisting of energy at terminal time and a penalty on open-loop control force via calculus of variations. If the performance measure also involves a penalty on closed-loop control effort then a Fourier based method is utilized. Step (II) the energy at terminal time is minimized numerically to obtain optimal values of feedback gains. The optimal closed-loop control gains obtained are used to describe the displacement and the velocity of open-loop, closed-loop and open/closed-loop controlled duralumin plate.

Development of a novel optimization tool for electron linacs inspired by artificial intelligence techniques in video games

NASA Astrophysics Data System (ADS)

Meier, E.; Biedron, S. G.; LeBlanc, G.; Morgan, M. J.

2011-03-01

This paper reports the results of an advanced algorithm for the optimization of electron beam parameters in Free Electron Laser (FEL) Linacs. In the novel approach presented in this paper, the system uses state of the art developments in video games to mimic an operator's decisions to perform an optimization task when no prior knowledge, other than constraints on the actuators is available. The system was tested for the simultaneous optimization of the energy spread and the transmission of the Australian Synchrotron Linac. The proposed system successfully increased the transmission of the machine from 90% to 97% and decreased the energy spread of the beam from 1.04% to 0.91%. Results of a control experiment performed at the new FERMI@Elettra FEL is also reported, suggesting the adaptability of the scheme for beam-based control.

Energy Performance Monitoring and Optimization System for DoD Campuses

DTIC Science & Technology

2014-02-01

EPMO system exceeded the energy consumption reduction target of 20% and improved occupant thermal comfort by reducing the number of instances outside... thermal comfort constraints, and plant efficiency EW2011-42 Final Report 8 February 2014 in the same framework [30-33]. In this framework, 4-hour...conjunction with information such as: thermal comfort constraints, equipment constraints, energy performance objectives. All the information is

Incentive-compatible demand-side management for smart grids based on review strategies

NASA Astrophysics Data System (ADS)

Xu, Jie; van der Schaar, Mihaela

2015-12-01

Demand-side load management is able to significantly improve the energy efficiency of smart grids. Since the electricity production cost depends on the aggregate energy usage of multiple consumers, an important incentive problem emerges: self-interested consumers want to increase their own utilities by consuming more than the socially optimal amount of energy during peak hours since the increased cost is shared among the entire set of consumers. To incentivize self-interested consumers to take the socially optimal scheduling actions, we design a new class of protocols based on review strategies. These strategies work as follows: first, a review stage takes place in which a statistical test is performed based on the daily prices of the previous billing cycle to determine whether or not the other consumers schedule their electricity loads in a socially optimal way. If the test fails, the consumers trigger a punishment phase in which, for a certain time, they adjust their energy scheduling in such a way that everybody in the consumer set is punished due to an increased price. Using a carefully designed protocol based on such review strategies, consumers then have incentives to take the socially optimal load scheduling to avoid entering this punishment phase. We rigorously characterize the impact of deploying protocols based on review strategies on the system's as well as the users' performance and determine the optimal design (optimal billing cycle, punishment length, etc.) for various smart grid deployment scenarios. Even though this paper considers a simplified smart grid model, our analysis provides important and useful insights for designing incentive-compatible demand-side management schemes based on aggregate energy usage information in a variety of practical scenarios.

Performance metric comparison study for non-magnetic bi-stable energy harvesters

NASA Astrophysics Data System (ADS)

Udani, Janav P.; Wrigley, Cailin; Arrieta, Andres F.

2017-04-01

Energy harvesting employing non-linear systems offers considerable advantages over linear systems given the broadband resonant response which is favorable for applications involving diverse input vibrations. In this respect, the rich dynamics of bi-stable systems present a promising means for harvesting vibrational energy from ambient sources. Harvesters deriving their bi-stability from thermally induced stresses as opposed to magnetic forces are receiving significant attention as it reduces the need for ancillary components and allows for bio- compatible constructions. However, the design of these bi-stable harvesters still requires further optimization to completely exploit the dynamic behavior of these systems. This study presents a comparison of the harvesting capabilities of non-magnetic, bi-stable composite laminates under variations in the design parameters as evaluated utilizing established power metrics. Energy output characteristics of two bi-stable composite laminate plates with a piezoelectric patch bonded on the top surface are experimentally investigated for variations in the thickness ratio and inertial mass positions for multiple load conditions. A particular design configuration is found to perform better over the entire range of testing conditions which include single and multiple frequency excitation, thus indicating that design optimization over the geometry of the harvester yields robust performance. The experimental analysis further highlights the need for appropriate design guidelines for optimization and holistic performance metrics to account for the range of operational conditions.

Optimization of energy window and evaluation of scatter compensation methods in MPS using the ideal observer with model mismatch

NASA Astrophysics Data System (ADS)

Ghaly, Michael; Links, Jonathan M.; Frey, Eric

2015-03-01

In this work, we used the ideal observer (IO) and IO with model mismatch (IO-MM) applied in the projection domain and an anthropomorphic Channelized Hotelling Observer (CHO) applied to reconstructed images to optimize the acquisition energy window width and evaluate various scatter compensation methods in the context of a myocardial perfusion SPECT defect detection task. The IO has perfect knowledge of the image formation process and thus reflects performance with perfect compensation for image-degrading factors. Thus, using the IO to optimize imaging systems could lead to suboptimal parameters compared to those optimized for humans interpreting SPECT images reconstructed with imperfect or no compensation. The IO-MM allows incorporating imperfect system models into the IO optimization process. We found that with near-perfect scatter compensation, the optimal energy window for the IO and CHO were similar; in its absence the IO-MM gave a better prediction of the optimal energy window for the CHO using different scatter compensation methods. These data suggest that the IO-MM may be useful for projection-domain optimization when model mismatch is significant, and that the IO is useful when followed by reconstruction with good models of the image formation process.

An approach to modeling and optimization of integrated renewable energy system (ires)

NASA Astrophysics Data System (ADS)

Maheshwari, Zeel

The purpose of this study was to cost optimize electrical part of IRES (Integrated Renewable Energy Systems) using HOMER and maximize the utilization of resources using MATLAB programming. IRES is an effective and a viable strategy that can be employed to harness renewable energy resources to energize remote rural areas of developing countries. The resource- need matching, which is the basis for IRES makes it possible to provide energy in an efficient and cost effective manner. Modeling and optimization of IRES for a selected study area makes IRES more advantageous when compared to hybrid concepts. A remote rural area with a population of 700 in 120 households and 450 cattle is considered as an example for cost analysis and optimization. Mathematical models for key components of IRES such as biogas generator, hydropower generator, wind turbine, PV system and battery banks are developed. A discussion of the size of water reservoir required is also presented. Modeling of IRES on the basis of need to resource and resource to need matching is pursued to help in optimum use of resources for the needs. Fixed resources such as biogas and water are used in prioritized order whereas movable resources such as wind and solar can be used simultaneously for different priorities. IRES is cost optimized for electricity demand using HOMER software that is developed by the NREL (National Renewable Energy Laboratory). HOMER optimizes configuration for electrical demand only and does not consider other demands such as biogas for cooking and water for domestic and irrigation purposes. Hence an optimization program based on the need-resource modeling of IRES is performed in MATLAB. Optimization of the utilization of resources for several needs is performed. Results obtained from MATLAB clearly show that the available resources can fulfill the demand of the rural areas. Introduction of IRES in rural communities has many socio-economic implications. It brings about improvement in living environment and community welfare by supplying the basic needs such as biogas for cooking, water for domestic and irrigation purposes and electrical energy for lighting, communication, cold storage, educational and small- scale industrial purposes.

Smart grid technologies in local electric grids

NASA Astrophysics Data System (ADS)

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

2017-08-01

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

A Lifetime Maximization Relay Selection Scheme in Wireless Body Area Networks.

PubMed

Zhang, Yu; Zhang, Bing; Zhang, Shi

2017-06-02

Network Lifetime is one of the most important metrics in Wireless Body Area Networks (WBANs). In this paper, a relay selection scheme is proposed under the topology constrains specified in the IEEE 802.15.6 standard to maximize the lifetime of WBANs through formulating and solving an optimization problem where relay selection of each node acts as optimization variable. Considering the diversity of the sensor nodes in WBANs, the optimization problem takes not only energy consumption rate but also energy difference among sensor nodes into account to improve the network lifetime performance. Since it is Non-deterministic Polynomial-hard (NP-hard) and intractable, a heuristic solution is then designed to rapidly address the optimization. The simulation results indicate that the proposed relay selection scheme has better performance in network lifetime compared with existing algorithms and that the heuristic solution has low time complexity with only a negligible performance degradation gap from optimal value. Furthermore, we also conduct simulations based on a general WBAN model to comprehensively illustrate the advantages of the proposed algorithm. At the end of the evaluation, we validate the feasibility of our proposed scheme via an implementation discussion.

Compressed Air System Optimization: Case Study Food Industry in Indonesia

NASA Astrophysics Data System (ADS)

Widayati, Endang; Nuzahar, Hasril

2016-01-01

Compressors and compressed air systems was one of the most important utilities in industries or factories. Approximately 10% of the cost of electricity in the industry was used to produce compressed air. Therefore the potential for energy savings in the compressors and compressed air systems had a big challenge. This field was conducted especially in Indonesia food industry or factory. Compressed air system optimization was a technique approach to determine the optimal conditions for the operation of compressors and compressed air systems that included evaluation of the energy needs, supply adjustment, eliminating or reconfiguring the use and operation of inefficient, changing and complementing some equipment and improving operating efficiencies. This technique gave the significant impact for energy saving and costs. The potential savings based on this study through measurement and optimization e.g. system that lowers the pressure of 7.5 barg to 6.8 barg would reduce energy consumption and running costs approximately 4.2%, switch off the compressor GA110 and GA75 was obtained annual savings of USD 52,947 ≈ 455 714 kWh, running GA75 light load or unloaded then obtained annual savings of USD 31,841≈ 270,685 kWh, install new compressor 2x132 kW and 1x 132 kW VSD obtained annual savings of USD 108,325≈ 928,500 kWh. Furthermore it was needed to conduct study of technical aspect of energy saving potential (Investment Grade Audit) and performed Cost Benefit Analysis. This study was one of best practice solutions how to save energy and improve energy performance in compressors and compressed air system.

Optimization and comparison of simultaneous and separate acquisition protocols for dual isotope myocardial perfusion SPECT.

PubMed

Ghaly, Michael; Links, Jonathan M; Frey, Eric C

2015-07-07

Dual-isotope simultaneous-acquisition (DISA) rest-stress myocardial perfusion SPECT (MPS) protocols offer a number of advantages over separate acquisition. However, crosstalk contamination due to scatter in the patient and interactions in the collimator degrade image quality. Compensation can reduce the effects of crosstalk, but does not entirely eliminate image degradations. Optimizing acquisition parameters could further reduce the impact of crosstalk. In this paper we investigate the optimization of the rest Tl-201 energy window width and relative injected activities using the ideal observer (IO), a realistic digital phantom population and Monte Carlo (MC) simulated Tc-99m and Tl-201 projections as a means to improve image quality. We compared performance on a perfusion defect detection task for Tl-201 acquisition energy window widths varying from 4 to 40 keV centered at 72 keV for a camera with a 9% energy resolution. We also investigated 7 different relative injected activities, defined as the ratio of Tc-99m and Tl-201 activities, while keeping the total effective dose constant at 13.5 mSv. For each energy window and relative injected activity, we computed the IO test statistics using a Markov chain Monte Carlo (MCMC) method for an ensemble of 1,620 triplets of fixed and reversible defect-present, and defect-absent noisy images modeling realistic background variations. The volume under the 3-class receiver operating characteristic (ROC) surface (VUS) was estimated and served as the figure of merit. For simultaneous acquisition, the IO suggested that relative Tc-to-Tl injected activity ratios of 2.6-5 and acquisition energy window widths of 16-22% were optimal. For separate acquisition, we observed a broad range of optimal relative injected activities from 2.6 to 12.1 and acquisition energy window of widths 16-22%. A negative correlation between Tl-201 injected activity and the width of the Tl-201 energy window was observed in these ranges. The results also suggested that DISA methods could potentially provide image quality as good as that obtained with separate acquisition protocols. We compared observer performance for the optimized protocols and the current clinical protocol using separate acquisition. The current clinical protocols provided better performance at a cost of injecting the patient with approximately double the injected activity of Tc-99m and Tl-201, resulting in substantially increased radiation dose.

Optimization of Design Parameters and Operating Conditions of Electrochemical Capacitors for High Energy and Power Performance

NASA Astrophysics Data System (ADS)

Ike, Innocent S.; Sigalas, Iakovos; Iyuke, Sunny E.

2017-03-01

Theoretical expressions for performance parameters of different electrochemical capacitors (ECs) have been optimized by solving them using MATLAB scripts as well as via the MATLAB R2014a optimization toolbox. The performance of the different kinds of ECs under given conditions was compared using theoretical equations and simulations of various models based on the conditions of device components, using optimal values for the coefficient associated with the battery-kind material ( K BMopt) and the constant associated with the electrolyte material ( K Eopt), as well as our symmetric electric double-layer capacitor (EDLC) experimental data. Estimation of performance parameters was possible based on values for the mass ratio of electrodes, operating potential range ratio, and specific capacitance of electrolyte. The performance of asymmetric ECs with suitable electrode mass and operating potential range ratios using aqueous or organic electrolyte at appropriate operating potential range and specific capacitance was 2.2 and 5.56 times greater, respectively, than for the symmetric EDLC and asymmetric EC using the same aqueous electrolyte, respectively. This enhancement was accompanied by reduced cell mass and volume. Also, the storable and deliverable energies of the asymmetric EC with suitable electrode mass and operating potential range ratios using the proper organic electrolyte were 12.9 times greater than those of the symmetric EDLC using aqueous electrolyte, again with reduced cell mass and volume. The storable energy, energy density, and power density of the asymmetric EDLC with suitable electrode mass and operating potential range ratios using the proper organic electrolyte were 5.56 times higher than for a similar symmetric EDLC using aqueous electrolyte, with cell mass and volume reduced by a factor of 1.77. Also, the asymmetric EDLC with the same type of electrode and suitable electrode mass ratio, working potential range ratio, and proper organic electrolyte showed enhanced performance compared with the conventional symmetric EDLC using aqueous electrolyte, with reduced cell mass and volume. These results can obviously reduce the number of experiments required to determine the optimum manufacturing design for ECs and also demonstrate that use of an asymmetric electrode and organic electrolyte was very successful for improving the performance of the EC, with reduced cell mass and volume. These results can also act as guidelines for design, fabrication, and operation of electrochemical capacitors with outstanding storable energy, energy density, and power density.

Process and Energy Optimization Assessment, Tobyhanna Army Depot, PA

DTIC Science & Technology

2006-04-17

assembly of electronic-communication components, different welding processes are performed at TYAD. It uses shielded arc, metal inert gas (MIG...tungsten inert gas ( TIG ), and silver braz- ing oxygen/acetylene cutting plasma arc methods to complete mission re- quirements. Major welding jobs are...ER D C/ CE R L TR -0 6 -1 1 Process and Energy Optimization Assessment Tobyhanna Army Depot, PA Mike C.J. Lin, Alexander M. Zhivov

Simulation and optimal control of wind-farm boundary layers

NASA Astrophysics Data System (ADS)

Meyers, Johan; Goit, Jay

2014-05-01

In large wind farms, the effect of turbine wakes, and their interaction leads to a reduction in farm efficiency, with power generated by turbines in a farm being lower than that of a lone-standing turbine by up to 50%. In very large wind farms or `deep arrays', this efficiency loss is related to interaction of the wind farms with the planetary boundary layer, leading to lower wind speeds at turbine level. Moreover, for these cases it has been demonstrated both in simulations and wind-tunnel experiments that the wind-farm energy extraction is dominated by the vertical turbulent transport of kinetic energy from higher regions in the boundary layer towards the turbine level. In the current study, we investigate the use of optimal control techniques combined with Large-Eddy Simulations (LES) of wind-farm boundary layer interaction for the increase of total energy extraction in very large `infinite' wind farms. We consider the individual wind turbines as flow actuators, whose energy extraction can be dynamically regulated in time so as to optimally influence the turbulent flow field, maximizing the wind farm power. For the simulation of wind-farm boundary layers we use large-eddy simulations in combination with actuator-disk and actuator-line representations of wind turbines. Simulations are performed in our in-house pseudo-spectral code SP-Wind that combines Fourier-spectral discretization in horizontal directions with a fourth-order finite-volume approach in the vertical direction. For the optimal control study, we consider the dynamic control of turbine-thrust coefficients in an actuator-disk model. They represent the effect of turbine blades that can actively pitch in time, changing the lift- and drag coefficients of the turbine blades. Optimal model-predictive control (or optimal receding horizon control) is used, where the model simply consists of the full LES equations, and the time horizon is approximately 280 seconds. The optimization is performed using a nonlinear conjugate gradient method, and the gradients are calculated by solving the adjoint LES equations. We find that the extracted farm power increases by approximately 20% when using optimal model-predictive control. However, the increased power output is also responsible for an increase in turbulent dissipation, and a deceleration of the boundary layer. Further investigating the energy balances in the boundary layer, it is observed that this deceleration is mainly occurring in the outer layer as a result of higher turbulent energy fluxes towards the turbines. In a second optimization case, we penalize boundary-layer deceleration, and find an increase of energy extraction of approximately 10%. In this case, increased energy extraction is balanced by a reduction in of turbulent dissipation in the boundary layer. J.M. acknowledges support from the European Research Council (FP7-Ideas, grant no. 306471). Simulations were performed on the computing infrastructure of the VSC Flemish Supercomputer Center, funded by the Hercules Foundation and the Flemish Government.

Economic Evaluation of Observatory Solar-Energy System

NASA Technical Reports Server (NTRS)

1982-01-01

Long-term economic performance of a commercial solar-energy system was analyzed and used to predict economic performance at four additional sites. Analysis described in report was done to demonstrate viability of design over a broad range of environmental/economic conditions. Topics covered are system description, study approach, economic analysis and system optimization.

Optimization of the Neutrino Factory, revisited

NASA Astrophysics Data System (ADS)

Agarwalla, Sanjib K.; Huber, Patrick; Tang, Jian; Winter, Walter

2011-01-01

We perform the baseline and energy optimization of the Neutrino Factory including the latest simulation results on the magnetized iron detector (MIND). We also consider the impact of τ decays, generated by νμ → ντ or ν e → ντ appearance, on the mass hierarchy, CP violation, and θ 13 discovery reaches, which we find to be negligible for the considered detector. For the baseline-energy optimization for small sin2 2 θ 13, we qualitatively recover the results with earlier simulations of the MIND detector. We find optimal baselines of about 2500km to 5000km for the CP violation measurement, where now values of E μ as low as about 12 GeV may be possible. However, for large sin2 2 θ 13, we demonstrate that the lower threshold and the backgrounds reconstructed at lower energies allow in fact for muon energies as low as 5 GeV at considerably shorter baselines, such as FNAL-Homestake. This implies that with the latest MIND analysis, low-and high-energy versions of the Neutrino Factory are just two different versions of the same experiment optimized for different parts of the parameter space. Apart from a green-field study of the updated detector performance, we discuss specific implementations for the two-baseline Neutrino Factory, where the considered detector sites are taken to be currently discussed underground laboratories. We find that reasonable setups can be found for the Neutrino Factory source in Asia, Europe, and North America, and that a triangular-shaped storage ring is possible in all cases based on geometrical arguments only.

An optimized computational method for determining the beta dose distribution using a multiple-element thermoluminescent dosimeter system.

PubMed

Shen, L; Levine, S H; Catchen, G L

1987-07-01

This paper describes an optimization method for determining the beta dose distribution in tissue, and it describes the associated testing and verification. The method uses electron transport theory and optimization techniques to analyze the responses of a three-element thermoluminescent dosimeter (TLD) system. Specifically, the method determines the effective beta energy distribution incident on the dosimeter system, and thus the system performs as a beta spectrometer. Electron transport theory provides the mathematical model for performing the optimization calculation. In this calculation, parameters are determined that produce calculated doses for each of the chip/absorber components in the three-element TLD system. The resulting optimized parameters describe an effective incident beta distribution. This method can be used to determine the beta dose specifically at 7 mg X cm-2 or at any depth of interest. The doses at 7 mg X cm-2 in tissue determined by this method are compared to those experimentally determined using an extrapolation chamber. For a great variety of pure beta sources having different incident beta energy distributions, good agreement is found. The results are also compared to those produced by a commonly used empirical algorithm. Although the optimization method produces somewhat better results, the advantage of the optimization method is that its performance is not sensitive to the specific method of calibration.

Parameter study and optimization for piezoelectric energy harvester for TPMS considering speed variation

NASA Astrophysics Data System (ADS)

Toghi Eshghi, Amin; Lee, Soobum; Lee, Hanmin; Kim, Young-Cheol

2016-04-01

In this paper, we perform design parameter study and design optimization for a piezoelectric energy harvester considering vehicle speed variation. Initially, a FEM model using ANSYS is developed to appraise the performance of a piezoelectric harvester in a rotating tire. The energy harvester proposed here uses the vertical deformation at contact patch area from the car weight and centrifugal acceleration. This harvester is composed of a beam which is clamped at both ends and a piezoelectric material is attached on the top of that. The piezoelectric material possesses the 31 mode of transduction in which the direction of applied field is perpendicular to that of the electric field. To optimize the harvester performance, we would change the geometrical parameters of the harvester to obtain the maximum power. One of the main challenges in the design process is obtaining the required power while considering the constraints for harvester weight and volume. These two concerns are addressed in this paper. Since the final goal of this study is the development of an energy harvester with a wireless sensor system installed in a real car, the real time data for varied velocity of a vehicle are taken into account for power measurements. This study concludes that the proposed design is applicable to wireless tire sensor systems.

Performance evaluation and parameter sensitivity of energy-harvesting shock absorbers on different vehicles

NASA Astrophysics Data System (ADS)

Guo, Sijing; Liu, Yilun; Xu, Lin; Guo, Xuexun; Zuo, Lei

2016-07-01

Traditional shock absorbers provide favourable ride comfort and road handling by dissipating the suspension vibration energy into heat waste. In order to harvest this dissipated energy and improve the vehicle fuel efficiency, many energy-harvesting shock absorbers (EHSAs) have been proposed in recent years. Among them, two types of EHSAs have attracted much attention. One is a traditional EHSA which converts the oscillatory vibration into bidirectional rotation using rack-pinion, ball-screw or other mechanisms. The other EHSA is equipped with a mechanical motion rectifier (MMR) that transforms the bidirectional vibration into unidirectional rotation. Hereinafter, they are referred to as NonMMR-EHSA and MMR-EHSA, respectively. This paper compares their performances with the corresponding traditional shock absorber by using closed-form analysis and numerical simulations on various types of vehicles, including passenger cars, buses and trucks. Results suggest that MMR-EHSA provides better ride performances than NonMMR-EHSA, and that MMR-EHSA is able to improve both the ride comfort and road handling simultaneously over the traditional shock absorber when installed on light-damped, heavy-duty vehicles. Additionally, the optimal parameters of MMR-EHSA are obtained for ride comfort. The optimal solutions ('Pareto-optimal solutions') are also obtained by considering the trade-off between ride comfort and road handling.

Performance evaluation of the inverse dynamics method for optimal spacecraft reorientation

NASA Astrophysics Data System (ADS)

Ventura, Jacopo; Romano, Marcello; Walter, Ulrich

2015-05-01

This paper investigates the application of the inverse dynamics in the virtual domain method to Euler angles, quaternions, and modified Rodrigues parameters for rapid optimal attitude trajectory generation for spacecraft reorientation maneuvers. The impact of the virtual domain and attitude representation is numerically investigated for both minimum time and minimum energy problems. Owing to the nature of the inverse dynamics method, it yields sub-optimal solutions for minimum time problems. Furthermore, the virtual domain improves the optimality of the solution, but at the cost of more computational time. The attitude representation also affects solution quality and computational speed. For minimum energy problems, the optimal solution can be obtained without the virtual domain with any considered attitude representation.

Structural optimization of structured carbon-based energy-storing composite materials used in space vehicles.

PubMed

Yu, Jia; Yu, Zhichao; Tang, Chenlong

2016-07-04

The hot work environment of electronic components in the instrument cabin of spacecraft was researched, and a new thermal protection structure, namely graphite carbon foam, which is an impregnated phase-transition material, was adopted to implement the thermal control on the electronic components. We used the optimized parameters obtained from ANSYS to conduct 2D optimization, 3-D modeling and simulation, as well as the strength check. Finally, the optimization results were verified by experiments. The results showed that after optimization, the structured carbon-based energy-storing composite material could reduce the mass and realize the thermal control over electronic components. This phase-transition composite material still possesses excellent temperature control performance after its repeated melting and solidifying.

High performance solutions and data for nZEBs offices located in warm climates.

PubMed

Congedo, Paolo Maria; Baglivo, Cristina; Zacà, Ilaria; D Agostino, Delia

2015-12-01

This data article contains eleven tables supporting the research article entitled: Cost-Optimal Design For Nearly Zero Energy Office Buildings Located In Warm Climates [1]. The data explain the procedure of minimum energy performance requirements presented by the European Directive (EPBD) [2] to establish several variants of energy efficiency measures with the integration of renewable energy sources in order to reach nZEBs (nearly zero energy buildings) by 2020. This files include the application of comparative methodological framework and give the cost-optimal solutions for non-residential building located in Southern Italy. The data describe office sector in which direct the current European policies and investments [3], [4]. In particular, the localization of the building, geometrical features, thermal properties of the envelope and technical systems for HVAC are reported in the first sections. Energy efficiency measures related to orientation, walls, windows, heating, cooling, dhw and RES are given in the second part of the group; this data article provides 256 combinations for a financial and macroeconomic analysis.

Optimization Performance of a CO[subscript 2] Pulsed Tuneable Laser

ERIC Educational Resources Information Center

Ribeiro, J. H. F.; Lobo, R. F. M.

2009-01-01

In this paper, a procedure is presented that will allow (i) the power and (ii) the energy of a pulsed and tuneable TEA CO[subscript 2] laser to be optimized. This type of laser represents a significant improvement in performance and portability. Combining a pulse mode with a grating tuning facility, it enables us to scan the working wavelength…

Ultra-fast escape maneuver of an octopus-inspired robot.

PubMed

Weymouth, G D; Subramaniam, V; Triantafyllou, M S

2015-02-02

We design and test an octopus-inspired flexible hull robot that demonstrates outstanding fast-starting performance. The robot is hyper-inflated with water, and then rapidly deflates to expel the fluid so as to power the escape maneuver. Using this robot we verify for the first time in laboratory testing that rapid size-change can substantially reduce separation in bluff bodies traveling several body lengths, and recover fluid energy which can be employed to improve the propulsive performance. The robot is found to experience speeds over ten body lengths per second, exceeding that of a similarly propelled optimally streamlined rigid rocket. The peak net thrust force on the robot is more than 2.6 times that on an optimal rigid body performing the same maneuver, experimentally demonstrating large energy recovery and enabling acceleration greater than 14 body lengths per second squared. Finally, over 53% of the available energy is converted into payload kinetic energy, a performance that exceeds the estimated energy conversion efficiency of fast-starting fish. The Reynolds number based on final speed and robot length is [Formula: see text]. We use the experimental data to establish a fundamental deflation scaling parameter [Formula: see text] which characterizes the mechanisms of flow control via shape change. Based on this scaling parameter, we find that the fast-starting performance improves with increasing size.

Improving energy sustainability for public buildings in Italian mountain communities.

PubMed

Mutani, Guglielmina; Cornaglia, Mauro; Berto, Massimo

2018-05-01

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

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

Optimal Sizing Tool for Battery Storage in Grid Applications

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

2015-09-24

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

Strategies to optimize lithium-ion supercapacitors achieving high-performance: Cathode configurations, lithium loadings on anode, and types of separator

NASA Astrophysics Data System (ADS)

Cao, Wanjun; Li, Yangxing; Fitch, Brian; Shih, Jonathan; Doung, Tien; Zheng, Jim

2014-12-01

The Li-ion capacitor (LIC) is composed of a lithium-doped carbon anode and an activated carbon cathode, which is a half Li-ion battery (LIB) and a half electrochemical double-layer capacitor (EDLC). LICs can achieve much more energy density than EDLC without sacrificing the high power performance advantage of capacitors over batteries. LIC pouch cells were assembled using activated carbon (AC) cathode and hard carbon (HC) + stabilized lithium metal power (SLMP®) anode. Different cathode configurations, various SLMP loadings on HC anode, and two types of separators were investigated to achieve the optimal electrochemical performance of the LIC. Firstly, the cathode binders study suggests that the PTFE binder offers improved energy and power performances for LIC in comparison to PVDF. Secondly, the mass ratio of SLMP to HC is at 1:7 to obtain the optimized electrochemical performance for LIC among all the various studied mass ratios between lithium loading amounts and active anode material. Finally, compared to the separator Celgard PP 3501, cellulose based TF40-30 is proven to be a preferred separator for LIC.

Cross-layer cluster-based energy-efficient protocol for wireless sensor networks.

PubMed

Mammu, Aboobeker Sidhik Koyamparambil; Hernandez-Jayo, Unai; Sainz, Nekane; de la Iglesia, Idoia

2015-04-09

Recent developments in electronics and wireless communications have enabled the improvement of low-power and low-cost wireless sensors networks (WSNs). One of the most important challenges in WSNs is to increase the network lifetime due to the limited energy capacity of the network nodes. Another major challenge in WSNs is the hot spots that emerge as locations under heavy traffic load. Nodes in such areas quickly drain energy resources, leading to disconnection in network services. In such an environment, cross-layer cluster-based energy-efficient algorithms (CCBE) can prolong the network lifetime and energy efficiency. CCBE is based on clustering the nodes to different hexagonal structures. A hexagonal cluster consists of cluster members (CMs) and a cluster head (CH). The CHs are selected from the CMs based on nodes near the optimal CH distance and the residual energy of the nodes. Additionally, the optimal CH distance that links to optimal energy consumption is derived. To balance the energy consumption and the traffic load in the network, the CHs are rotated among all CMs. In WSNs, energy is mostly consumed during transmission and reception. Transmission collisions can further decrease the energy efficiency. These collisions can be avoided by using a contention-free protocol during the transmission period. Additionally, the CH allocates slots to the CMs based on their residual energy to increase sleep time. Furthermore, the energy consumption of CH can be further reduced by data aggregation. In this paper, we propose a data aggregation level based on the residual energy of CH and a cost-aware decision scheme for the fusion of data. Performance results show that the CCBE scheme performs better in terms of network lifetime, energy consumption and throughput compared to low-energy adaptive clustering hierarchy (LEACH) and hybrid energy-efficient distributed clustering (HEED).

Fast exploration of an optimal path on the multidimensional free energy surface

PubMed Central

Chen, Changjun

2017-01-01

In a reaction, determination of an optimal path with a high reaction rate (or a low free energy barrier) is important for the study of the reaction mechanism. This is a complicated problem that involves lots of degrees of freedom. For simple models, one can build an initial path in the collective variable space by the interpolation method first and then update the whole path constantly in the optimization. However, such interpolation method could be risky in the high dimensional space for large molecules. On the path, steric clashes between neighboring atoms could cause extremely high energy barriers and thus fail the optimization. Moreover, performing simulations for all the snapshots on the path is also time-consuming. In this paper, we build and optimize the path by a growing method on the free energy surface. The method grows a path from the reactant and extends its length in the collective variable space step by step. The growing direction is determined by both the free energy gradient at the end of the path and the direction vector pointing at the product. With fewer snapshots on the path, this strategy can let the path avoid the high energy states in the growing process and save the precious simulation time at each iteration step. Applications show that the presented method is efficient enough to produce optimal paths on either the two-dimensional or the twelve-dimensional free energy surfaces of different small molecules. PMID:28542475

Network Modeling and Energy-Efficiency Optimization for Advanced Machine-to-Machine Sensor Networks

PubMed Central

Jung, Sungmo; Kim, Jong Hyun; Kim, Seoksoo

2012-01-01

Wireless machine-to-machine sensor networks with multiple radio interfaces are expected to have several advantages, including high spatial scalability, low event detection latency, and low energy consumption. Here, we propose a network model design method involving network approximation and an optimized multi-tiered clustering algorithm that maximizes node lifespan by minimizing energy consumption in a non-uniformly distributed network. Simulation results show that the cluster scales and network parameters determined with the proposed method facilitate a more efficient performance compared to existing methods. PMID:23202190

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

NASA Astrophysics Data System (ADS)

Mir, Imran; Maqsood, Adnan; Akhtar, Suhail

2017-06-01

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

Investigations of calcium spectral lines in laser-induced breakdown spectroscopy

NASA Astrophysics Data System (ADS)

Ching, Sim Yit; Tariq, Usman; Haider, Zuhaib; Tufail, Kashif; Sabri, Salwanie; Imran, Muhammad; Ali, Jalil

2017-03-01

Laser-induced breakdown spectroscopy (LIBS) is a direct and versatile analytical technique that performs the elemental composition analysis based on optical emission produced by laser induced-plasma, with a little or no sample preparation. The performance of the LIBS technique relies on the choice of experimental conditions which must be thoroughly explored and optimized for each application. The main parameters affecting the LIBS performance are the laser energy, laser wavelength, pulse duration, gate delay, geometrical set-up of the focusing and collecting optics. In LIBS quantitative analysis, the gate delay and laser energy are very important parameters that have pronounced impact on the accuracy of the elemental composition information of the materials. The determination of calcium elements in the pelletized samples was investigated and served for the purpose of optimizing the gate delay and laser energy by studying and analyzing the results from emission intensities collected and signal to background ratio (S/B) for the specified wavelengths.

Behavior-aware cache hierarchy optimization for low-power multi-core embedded systems

NASA Astrophysics Data System (ADS)

Zhao, Huatao; Luo, Xiao; Zhu, Chen; Watanabe, Takahiro; Zhu, Tianbo

2017-07-01

In modern embedded systems, the increasing number of cores requires efficient cache hierarchies to ensure data throughput, but such cache hierarchies are restricted by their tumid size and interference accesses which leads to both performance degradation and wasted energy. In this paper, we firstly propose a behavior-aware cache hierarchy (BACH) which can optimally allocate the multi-level cache resources to many cores and highly improved the efficiency of cache hierarchy, resulting in low energy consumption. The BACH takes full advantage of the explored application behaviors and runtime cache resource demands as the cache allocation bases, so that we can optimally configure the cache hierarchy to meet the runtime demand. The BACH was implemented on the GEM5 simulator. The experimental results show that energy consumption of a three-level cache hierarchy can be saved from 5.29% up to 27.94% compared with other key approaches while the performance of the multi-core system even has a slight improvement counting in hardware overhead.

A Comparison of Quantum and Molecular Mechanical Methods to Estimate Strain Energy in Druglike Fragments.

PubMed

Sellers, Benjamin D; James, Natalie C; Gobbi, Alberto

2017-06-26

Reducing internal strain energy in small molecules is critical for designing potent drugs. Quantum mechanical (QM) and molecular mechanical (MM) methods are often used to estimate these energies. In an effort to determine which methods offer an optimal balance in accuracy and performance, we have carried out torsion scan analyses on 62 fragments. We compared nine QM and four MM methods to reference energies calculated at a higher level of theory: CCSD(T)/CBS single point energies (coupled cluster with single, double, and perturbative triple excitations at the complete basis set limit) calculated on optimized geometries using MP2/6-311+G**. The results show that both the more recent MP2.X perturbation method as well as MP2/CBS perform quite well. In addition, combining a Hartree-Fock geometry optimization with a MP2/CBS single point energy calculation offers a fast and accurate compromise when dispersion is not a key energy component. Among MM methods, the OPLS3 force field accurately reproduces CCSD(T)/CBS torsion energies on more test cases than the MMFF94s or Amber12:EHT force fields, which struggle with aryl-amide and aryl-aryl torsions. Using experimental conformations from the Cambridge Structural Database, we highlight three example structures for which OPLS3 significantly overestimates the strain. The energies and conformations presented should enable scientists to estimate the expected error for the methods described and we hope will spur further research into QM and MM methods.

Constant-Envelope Waveform Design for Optimal Target-Detection and Autocorrelation Performances

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

Sen, Satyabrata

2013-01-01

We propose an algorithm to directly synthesize in time-domain a constant-envelope transmit waveform that achieves the optimal performance in detecting an extended target in the presence of signal-dependent interference. This approach is in contrast to the traditional indirect methods that synthesize the transmit signal following the computation of the optimal energy spectral density. Additionally, we aim to maintain a good autocorrelation property of the designed signal. Therefore, our waveform design technique solves a bi-objective optimization problem in order to simultaneously improve the detection and autocorrelation performances, which are in general conflicting in nature. We demonstrate this compromising characteristics of themore » detection and autocorrelation performances with numerical examples. Furthermore, in the absence of the autocorrelation criterion, our designed signal is shown to achieve a near-optimum detection performance.« less

Improvement of the GERDA Ge Detectors Energy Resolution by an Optimized Digital Signal Processing

NASA Astrophysics Data System (ADS)

Benato, G.; D'Andrea, V.; Cattadori, C.; Riboldi, S.

GERDA is a new generation experiment searching for neutrinoless double beta decay of 76Ge, operating at INFN Gran Sasso Laboratories (LNGS) since 2010. Coaxial and Broad Energy Germanium (BEGe) Detectors have been operated in liquid argon (LAr) in GERDA Phase I. In the framework of the second GERDA experimental phase, both the contacting technique, the connection to and the location of the front end readout devices are novel compared to those previously adopted, and several tests have been performed. In this work, starting from considerations on the energy scale stability of the GERDA Phase I calibrations and physics data sets, an optimized pulse filtering method has been developed and applied to the Phase II pilot tests data sets, and to few GERDA Phase I data sets. In this contribution the detector performances in term of energy resolution and time stability are here presented. The improvement of the energy resolution, compared to standard Gaussian shaping adopted for Phase I data analysis, is discussed and related to the optimized noise filtering capability. The result is an energy resolution better than 0.1% at 2.6 MeV for the BEGe detectors operated in the Phase II pilot tests and an improvement of the energy resolution in LAr of about 8% achieved on the GERDA Phase I calibration runs, compared to previous analysis algorithms.

Development of optimized segmentation map in dual energy computed tomography

NASA Astrophysics Data System (ADS)

Yamakawa, Keisuke; Ueki, Hironori

2012-03-01

Dual energy computed tomography (DECT) has been widely used in clinical practice and has been particularly effective for tissue diagnosis. In DECT the difference of two attenuation coefficients acquired by two kinds of X-ray energy enables tissue segmentation. One problem in conventional DECT is that the segmentation deteriorates in some cases, such as bone removal. This is due to two reasons. Firstly, the segmentation map is optimized without considering the Xray condition (tube voltage and current). If we consider the tube voltage, it is possible to create an optimized map, but unfortunately we cannot consider the tube current. Secondly, the X-ray condition is not optimized. The condition can be set empirically, but this means that the optimized condition is not used correctly. To solve these problems, we have developed methods for optimizing the map (Method-1) and the condition (Method-2). In Method-1, the map is optimized to minimize segmentation errors. The distribution of the attenuation coefficient is modeled by considering the tube current. In Method-2, the optimized condition is decided to minimize segmentation errors depending on tube voltagecurrent combinations while keeping the total exposure constant. We evaluated the effectiveness of Method-1 by performing a phantom experiment under the fixed condition and of Method-2 by performing a phantom experiment under different combinations calculated from the total exposure constant. When Method-1 was followed with Method-2, the segmentation error was reduced from 37.8 to 13.5 %. These results demonstrate that our developed methods can achieve highly accurate segmentation while keeping the total exposure constant.

Pulsed Inductive Plasma Acceleration: Performance Optimization Criteria

NASA Technical Reports Server (NTRS)

Polzin, Kurt A.

2014-01-01

Optimization criteria for pulsed inductive plasma acceleration are developed using an acceleration model consisting of a set of coupled circuit equations describing the time-varying current in the thruster and a one-dimensional momentum equation. The model is nondimensionalized, resulting in the identification of several scaling parameters that are varied to optimize the performance of the thruster. The analysis reveals the benefits of underdamped current waveforms and leads to a performance optimization criterion that requires the matching of the natural period of the discharge and the acceleration timescale imposed by the inertia of the working gas. In addition, the performance increases when a greater fraction of the propellant is initially located nearer to the inductive acceleration coil. While the dimensionless model uses a constant temperature formulation in calculating performance, the scaling parameters that yield the optimum performance are shown to be relatively invariant if a self-consistent description of energy in the plasma is instead used.

Case study on impact performance optimization of hydraulic breakers.

PubMed

Noh, Dae-Kyung; Kang, Young-Ky; Cho, Jae-Sang; Jang, Joo-Sup

2016-01-01

In order to expand the range of activities of an excavator, attachments, such as hydraulic breakers have been developed to be applied to buckets. However, it is very difficult to predict the dynamic behavior of hydraulic impact devices such as breakers because of high non-linearity. Thus, the purpose of this study is to optimize the impact performance of hydraulic breakers. The ultimate goal of the optimization is to increase the impact energy and impact frequency and to reduce the pressure pulsation of the supply and return lines. The optimization results indicated that the four parameters used to optimize the impact performance of the breaker showed considerable improvement over the results reported in the literature. A test was also conducted and the results were compared with those obtained through optimization in order to verify the optimization results. The comparison showed an average relative error of 8.24 %, which seems to be in good agreement. The results of this study can be used to optimize the impact performance of hydraulic impact devices such as breakers, thus facilitating its application to excavators and increasing the range of activities of an excavator.

Optimal Battery Sizing in Photovoltaic Based Distributed Generation Using Enhanced Opposition-Based Firefly Algorithm for Voltage Rise Mitigation

PubMed Central

Wong, Ling Ai; Shareef, Hussain; Mohamed, Azah; Ibrahim, Ahmad Asrul

2014-01-01

This paper presents the application of enhanced opposition-based firefly algorithm in obtaining the optimal battery energy storage systems (BESS) sizing in photovoltaic generation integrated radial distribution network in order to mitigate the voltage rise problem. Initially, the performance of the original firefly algorithm is enhanced by utilizing the opposition-based learning and introducing inertia weight. After evaluating the performance of the enhanced opposition-based firefly algorithm (EOFA) with fifteen benchmark functions, it is then adopted to determine the optimal size for BESS. Two optimization processes are conducted where the first optimization aims to obtain the optimal battery output power on hourly basis and the second optimization aims to obtain the optimal BESS capacity by considering the state of charge constraint of BESS. The effectiveness of the proposed method is validated by applying the algorithm to the 69-bus distribution system and by comparing the performance of EOFA with conventional firefly algorithm and gravitational search algorithm. Results show that EOFA has the best performance comparatively in terms of mitigating the voltage rise problem. PMID:25054184

Optimal battery sizing in photovoltaic based distributed generation using enhanced opposition-based firefly algorithm for voltage rise mitigation.

PubMed

Wong, Ling Ai; Shareef, Hussain; Mohamed, Azah; Ibrahim, Ahmad Asrul

2014-01-01

This paper presents the application of enhanced opposition-based firefly algorithm in obtaining the optimal battery energy storage systems (BESS) sizing in photovoltaic generation integrated radial distribution network in order to mitigate the voltage rise problem. Initially, the performance of the original firefly algorithm is enhanced by utilizing the opposition-based learning and introducing inertia weight. After evaluating the performance of the enhanced opposition-based firefly algorithm (EOFA) with fifteen benchmark functions, it is then adopted to determine the optimal size for BESS. Two optimization processes are conducted where the first optimization aims to obtain the optimal battery output power on hourly basis and the second optimization aims to obtain the optimal BESS capacity by considering the state of charge constraint of BESS. The effectiveness of the proposed method is validated by applying the algorithm to the 69-bus distribution system and by comparing the performance of EOFA with conventional firefly algorithm and gravitational search algorithm. Results show that EOFA has the best performance comparatively in terms of mitigating the voltage rise problem.

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

DOE PAGES

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

2017-11-03

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

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.

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

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

Bankole, Temitayo; Jones, Dustin; Bhattacharyya, Debangsu

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

Wireless sensor and actuator networks for lighting energy efficiency and user satisfaction

NASA Astrophysics Data System (ADS)

Wen, Yao-Jung

Buildings consume more than one third of the primary energy generated in the U.S., and lighting alone accounts for approximately 30% of the energy usage in commercial buildings. As the largest electricity consumer of all building electrical systems, lighting harbors the greatest potential for energy savings in the commercial sector. Fifty percent of current energy consumption could be reduced with energy-efficient lighting management strategies. While commercial products do exist, they are poorly received due to exorbitant retrofitting cost and unsatisfactory performance. As a result, most commercial buildings, especially legacy buildings, have not taken advantage of the opportunity to generate savings from lighting. The emergence of wireless sensor and actuator network (WSAN) technologies presents an alternative that circumvents costly rewiring and promises better performance than existing commercial lighting systems. The goal of this dissertation research is to develop a framework for wireless-networked lighting systems with increased cost effectiveness, energy efficiency, and user satisfaction. This research is realized through both theoretical developments and implementations. The theoretical research aims at developing techniques for harnessing WSAN technologies to lighting hardware and control strategies. Leveraging redundancy, a sensor validation and fusion algorithm is developed for extracting pertinent lighting information from the disturbance-prone desktop-mounted photosensors. An adaptive sensing strategy optimizes the timing of data acquisition and power-hungry wireless transmission of sensory feedback in real-time lighting control. Exploiting the individual addressability of wireless-enabled luminaires, a lighting optimization algorithm is developed to create the optimal lighting that minimizes energy usage while satisfying occupants' diverse lighting preferences. The wireless-networked lighting system was implemented and tested in a number of real-life settings. A human subject study conducted in a private office concluded that the research system was competitive with the commercial lighting system with much fewer retrofitting requirements. The system implemented in a shared-space office realized a self-configuring mesh network with wireless photosensors and light actuators, and demonstrated a 50% energy savings and increased performance when harvesting daylight through windows is possible. The cost analysis revealed a reasonable payback period after the system is optimized for commercialization and confirms the marketing feasibility.

Large size biogas-fed Solid Oxide Fuel Cell power plants with carbon dioxide management: Technical and economic optimization

NASA Astrophysics Data System (ADS)

Curletti, F.; Gandiglio, M.; Lanzini, A.; Santarelli, M.; Maréchal, F.

2015-10-01

This article investigates the techno-economic performance of large integrated biogas Solid Oxide Fuel Cell (SOFC) power plants. Both atmospheric and pressurized operation is analysed with CO2 vented or captured. The SOFC module produces a constant electrical power of 1 MWe. Sensitivity analysis and multi-objective optimization are the mathematical tools used to investigate the effects of Fuel Utilization (FU), SOFC operating temperature and pressure on the plant energy and economic performances. FU is the design variable that most affects the plant performance. Pressurized SOFC with hybridization with a gas turbine provides a notable boost in electrical efficiency. For most of the proposed plant configurations, the electrical efficiency ranges in the interval 50-62% (LHV biogas) when a trade-off of between energy and economic performances is applied based on Pareto charts obtained from multi-objective plant optimization. The hybrid SOFC is potentially able to reach an efficiency above 70% when FU is 90%. Carbon capture entails a penalty of more 10 percentage points in pressurized configurations mainly due to the extra energy burdens of captured CO2 pressurization and oxygen production and for the separate and different handling of the anode and cathode exhausts and power recovery from them.

An Optimization Framework for Dynamic Hybrid Energy Systems

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

Wenbo Du; Humberto E Garcia; Christiaan J.J. Paredis

A computational framework for the efficient analysis and optimization of dynamic hybrid energy systems (HES) is developed. A microgrid system with multiple inputs and multiple outputs (MIMO) is modeled using the Modelica language in the Dymola environment. The optimization loop is implemented in MATLAB, with the FMI Toolbox serving as the interface between the computational platforms. Two characteristic optimization problems are selected to demonstrate the methodology and gain insight into the system performance. The first is an unconstrained optimization problem that optimizes the dynamic properties of the battery, reactor and generator to minimize variability in the HES. The second problemmore » takes operating and capital costs into consideration by imposing linear and nonlinear constraints on the design variables. The preliminary optimization results obtained in this study provide an essential step towards the development of a comprehensive framework for designing HES.« less

Applications of the Renewable Energy Network Optimization Tool

NASA Astrophysics Data System (ADS)

Alliss, R.; Link, R.; Apling, D.; Kiley, H.; Mason, M.; Darmenova, K.

2010-12-01

As the renewable energy industry continues to grow so does the requirement for atmospheric modeling and analysis tools to maximize both wind and solar power. Renewable energy generation is variable however; presenting challenges for electrical grid operation and requires a variety of measures to adequately firm power. These measures include the production of non-renewable generation during times when renewables are not available. One strategy for minimizing the variability of renewable energy production is site diversity. Assuming that a network of renewable energy systems feed a common electrical grid, site diversity ensures that when one system on the network has a reduction in generation others on the same grid make up the difference. The site-diversity strategy can be used to mitigate the intermittency in alternative energy production systems while still maximizing saleable energy. The Renewable Energy Network Optimization Tool (ReNOT) has recently been developed to study the merits of site optimization for wind farms. The modeling system has a plug-in architecture that allows us to accommodate a wide variety of renewable energy system designs and performance metrics. The Weather Research and Forecasting (WRF) mesoscale model is applied to generate high-resolution wind databases to support the site selection of wind farms. These databases are generated on High Performance Computing systems such as the Rocky Mountain Supercomputing Center (RMSC). The databases are then accessed by ReNOT and an optimized site selection is developed. We can accommodate numerous constraints (e.g., number of sites, the geographic extent of the optimization, proximity to high-voltage transport lines, etc.). As part of our collaboration with RMSC and the State of Montana a study was performed to estimate the optimal locations of a network of wind farms. Comparisons were made to four existing wind farm locations in Montana including Glacier with a 210 MW name plate capacity, Horseshoe Bend with a total capacity of 9 MW, Diamond Willow with a capacity of 20MW and Judith Gap with a total capacity of 135 MW. The goal of this study was to see if ReNOT could find a four site network that made more effective use of the existing four site network of wind farms' 374 MW nameplate capacity. We developed three different metrics in which to pick sites. Metric 3 (M3) picks sites based on the previous day's mean power, and accounts for short-term variability (i.e., 1 hour). M3 attempts to approximate usable power by minimizing ramping events which are so important to industry. In addition we investigated several performance metrics including Mean Power, Usable Power, and ramping event frequency. A ramping event is defined as an increase or decrease in power production over the course of one hour. Of interest was the frequency of ramping events that exceeded 10% of total capacity for the network. Networks with few ramping events are markedly superior to networks producing otherwise identical aggregate power. The optimization was run over the 15-year period of hub-height wind data (40 meters AGL). The ReNOT derived network produces 58% more usable power than the four existing and operating wind farms. In addition, the optimized four site network produces three times fewer significant ramping events.

Improvement and analysis of the hydrogen-cerium redox flow cell

NASA Astrophysics Data System (ADS)

Tucker, Michael C.; Weiss, Alexandra; Weber, Adam Z.

2016-09-01

The H2-Ce redox flow cell is optimized using commercially-available cell materials. Cell performance is found to be sensitive to the upper charge cutoff voltage, membrane boiling pretreatment, methanesulfonic-acid concentration, (+) electrode surface area and flow pattern, and operating temperature. Performance is relatively insensitive to membrane thickness, Cerium concentration, and all features of the (-) electrode including hydrogen flow. Cell performance appears to be limited by mass transport and kinetics in the cerium (+) electrode. Maximum discharge power of 895 mW cm-2 was observed at 60 °C; an energy efficiency of 90% was achieved at 50 °C. The H2-Ce cell is promising for energy storage assuming one can optimize Ce reaction kinetics and electrolyte.

Optimal race strategy for a 200-m flying sprint in a human-powered vehicle: A case study of a world-record attempt.

PubMed

de Koning, Jos J; van der Zweep, Cees-Jan; Cornelissen, Jesper; Kuiper, Bouke

2013-03-01

Optimal pacing strategy was determined for breaking the world speed record on a human-powered vehicle (HPV) using an energy-flow model in which the rider's physical capacities, the vehicle's properties, and the environmental conditions were included. Power data from world-record attempts were compared with data from the model, and race protocols were adjusted to the results from the model. HPV performance can be improved by using an energy-flow model for optimizing race strategy. A biphased in-run followed by a sprint gave best results.

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

An optimal autonomous microgrid cluster based on distributed generation droop parameter optimization and renewable energy sources using an improved grey wolf optimizer

NASA Astrophysics Data System (ADS)

Moazami Goodarzi, Hamed; Kazemi, Mohammad Hosein

2018-05-01

Microgrid (MG) clustering is regarded as an important driver in improving the robustness of MGs. However, little research has been conducted on providing appropriate MG clustering. This article addresses this shortfall. It proposes a novel multi-objective optimization approach for finding optimal clustering of autonomous MGs by focusing on variables such as distributed generation (DG) droop parameters, the location and capacity of DG units, renewable energy sources, capacitors and powerline transmission. Power losses are minimized and voltage stability is improved while virtual cut-set lines with minimum power transmission for clustering MGs are obtained. A novel chaotic grey wolf optimizer (CGWO) algorithm is applied to solve the proposed multi-objective problem. The performance of the approach is evaluated by utilizing a 69-bus MG in several scenarios.

The application of simulation modeling to the cost and performance ranking of solar thermal power plants

NASA Technical Reports Server (NTRS)

Rosenberg, L. S.; Revere, W. R.; Selcuk, M. K.

1981-01-01

A computer simulation code was employed to evaluate several generic types of solar power systems (up to 10 MWe). Details of the simulation methodology, and the solar plant concepts are given along with cost and performance results. The Solar Energy Simulation computer code (SESII) was used, which optimizes the size of the collector field and energy storage subsystem for given engine-generator and energy-transport characteristics. Nine plant types were examined which employed combinations of different technology options, such as: distributed or central receivers with one- or two-axis tracking or no tracking; point- or line-focusing concentrator; central or distributed power conversion; Rankin, Brayton, or Stirling thermodynamic cycles; and thermal or electrical storage. Optimal cost curves were plotted as a function of levelized busbar energy cost and annualized plant capacity. Point-focusing distributed receiver systems were found to be most efficient (17-26 percent).

Near-Optimal Re-Entry Trajectories for Reusable Launch Vehicles

NASA Technical Reports Server (NTRS)

Chou, H.-C.; Ardema, M. D.; Bowles, J. V.

1997-01-01

A near-optimal guidance law for the descent trajectory for earth orbit re-entry of a fully reusable single-stage-to-orbit pure rocket launch vehicle is derived. A methodology is developed to investigate using both bank angle and altitude as control variables and selecting parameters that maximize various performance functions. The method is based on the energy-state model of the aircraft equations of motion. The major task of this paper is to obtain optimal re-entry trajectories under a variety of performance goals: minimum time, minimum surface temperature, minimum heating, and maximum heading change; four classes of trajectories were investigated: no banking, optimal left turn banking, optimal right turn banking, and optimal bank chattering. The cost function is in general a weighted sum of all performance goals. In particular, the trade-off between minimizing heat load into the vehicle and maximizing cross range distance is investigated. The results show that the optimization methodology can be used to derive a wide variety of near-optimal trajectories.

Optimization of Supersonic Transport Trajectories

NASA Technical Reports Server (NTRS)

Ardema, Mark D.; Windhorst, Robert; Phillips, James

1998-01-01

This paper develops a near-optimal guidance law for generating minimum fuel, time, or cost fixed-range trajectories for supersonic transport aircraft. The approach uses a choice of new state variables along with singular perturbation techniques to time-scale decouple the dynamic equations into multiple equations of single order (second order for the fast dynamics). Application of the maximum principle to each of the decoupled equations, as opposed to application to the original coupled equations, avoids the two point boundary value problem and transforms the problem from one of a functional optimization to one of multiple function optimizations. It is shown that such an approach produces well known aircraft performance results such as minimizing the Brequet factor for minimum fuel consumption and the energy climb path. Furthermore, the new state variables produce a consistent calculation of flight path angle along the trajectory, eliminating one of the deficiencies in the traditional energy state approximation. In addition, jumps in the energy climb path are smoothed out by integration of the original dynamic equations at constant load factor. Numerical results performed for a supersonic transport design show that a pushover dive followed by a pullout at nominal load factors are sufficient maneuvers to smooth the jump.

Agreement Technologies for Energy Optimization at Home.

PubMed

González-Briones, Alfonso; Chamoso, Pablo; De La Prieta, Fernando; Demazeau, Yves; Corchado, Juan M

2018-05-19

Nowadays, it is becoming increasingly common to deploy sensors in public buildings or homes with the aim of obtaining data from the environment and taking decisions that help to save energy. Many of the current state-of-the-art systems make decisions considering solely the environmental factors that cause the consumption of energy. These systems are successful at optimizing energy consumption; however, they do not adapt to the preferences of users and their comfort. Any system that is to be used by end-users should consider factors that affect their wellbeing. Thus, this article proposes an energy-saving system, which apart from considering the environmental conditions also adapts to the preferences of inhabitants. The architecture is based on a Multi-Agent System (MAS), its agents use Agreement Technologies (AT) to perform a negotiation process between the comfort preferences of the users and the degree of optimization that the system can achieve according to these preferences. A case study was conducted in an office building, showing that the proposed system achieved average energy savings of 17.15%.

RGCA: A Reliable GPU Cluster Architecture for Large-Scale Internet of Things Computing Based on Effective Performance-Energy Optimization

PubMed Central

Chen, Qingkui; Zhao, Deyu; Wang, Jingjuan

2017-01-01

This paper aims to develop a low-cost, high-performance and high-reliability computing system to process large-scale data using common data mining algorithms in the Internet of Things (IoT) computing environment. Considering the characteristics of IoT data processing, similar to mainstream high performance computing, we use a GPU (Graphics Processing Unit) cluster to achieve better IoT services. Firstly, we present an energy consumption calculation method (ECCM) based on WSNs. Then, using the CUDA (Compute Unified Device Architecture) Programming model, we propose a Two-level Parallel Optimization Model (TLPOM) which exploits reasonable resource planning and common compiler optimization techniques to obtain the best blocks and threads configuration considering the resource constraints of each node. The key to this part is dynamic coupling Thread-Level Parallelism (TLP) and Instruction-Level Parallelism (ILP) to improve the performance of the algorithms without additional energy consumption. Finally, combining the ECCM and the TLPOM, we use the Reliable GPU Cluster Architecture (RGCA) to obtain a high-reliability computing system considering the nodes’ diversity, algorithm characteristics, etc. The results show that the performance of the algorithms significantly increased by 34.1%, 33.96% and 24.07% for Fermi, Kepler and Maxwell on average with TLPOM and the RGCA ensures that our IoT computing system provides low-cost and high-reliability services. PMID:28777325

RGCA: A Reliable GPU Cluster Architecture for Large-Scale Internet of Things Computing Based on Effective Performance-Energy Optimization.

PubMed

Fang, Yuling; Chen, Qingkui; Xiong, Neal N; Zhao, Deyu; Wang, Jingjuan

2017-08-04

This paper aims to develop a low-cost, high-performance and high-reliability computing system to process large-scale data using common data mining algorithms in the Internet of Things (IoT) computing environment. Considering the characteristics of IoT data processing, similar to mainstream high performance computing, we use a GPU (Graphics Processing Unit) cluster to achieve better IoT services. Firstly, we present an energy consumption calculation method (ECCM) based on WSNs. Then, using the CUDA (Compute Unified Device Architecture) Programming model, we propose a Two-level Parallel Optimization Model (TLPOM) which exploits reasonable resource planning and common compiler optimization techniques to obtain the best blocks and threads configuration considering the resource constraints of each node. The key to this part is dynamic coupling Thread-Level Parallelism (TLP) and Instruction-Level Parallelism (ILP) to improve the performance of the algorithms without additional energy consumption. Finally, combining the ECCM and the TLPOM, we use the Reliable GPU Cluster Architecture (RGCA) to obtain a high-reliability computing system considering the nodes' diversity, algorithm characteristics, etc. The results show that the performance of the algorithms significantly increased by 34.1%, 33.96% and 24.07% for Fermi, Kepler and Maxwell on average with TLPOM and the RGCA ensures that our IoT computing system provides low-cost and high-reliability services.

Evaluating the quality of feed fats and oils and their effects on pig growth performance

USDA-ARS?s Scientific Manuscript database

Optimizing energy utilization efficiency of swine diets is essential because energy represents the greatest proportion of total diet cost. Various feed fats and oils, as well as other feed ingredients containing moderate amounts of lipid, provide significant amounts of energy to swine diets. However...

Energy Management and Optimization Methods for Grid Energy Storage Systems

DOE PAGES

Byrne, Raymond H.; Nguyen, Tu A.; Copp, David A.; ...

2017-08-24

Today, the stability of the electric power grid is maintained through real time balancing of generation and demand. Grid scale energy storage systems are increasingly being deployed to provide grid operators the flexibility needed to maintain this balance. Energy storage also imparts resiliency and robustness to the grid infrastructure. Over the last few years, there has been a significant increase in the deployment of large scale energy storage systems. This growth has been driven by improvements in the cost and performance of energy storage technologies and the need to accommodate distributed generation, as well as incentives and government mandates. Energymore » management systems (EMSs) and optimization methods are required to effectively and safely utilize energy storage as a flexible grid asset that can provide multiple grid services. The EMS needs to be able to accommodate a variety of use cases and regulatory environments. In this paper, we provide a brief history of grid-scale energy storage, an overview of EMS architectures, and a summary of the leading applications for storage. These serve as a foundation for a discussion of EMS optimization methods and design.« less

Energy Management and Optimization Methods for Grid Energy Storage Systems

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

Byrne, Raymond H.; Nguyen, Tu A.; Copp, David A.

Today, the stability of the electric power grid is maintained through real time balancing of generation and demand. Grid scale energy storage systems are increasingly being deployed to provide grid operators the flexibility needed to maintain this balance. Energy storage also imparts resiliency and robustness to the grid infrastructure. Over the last few years, there has been a significant increase in the deployment of large scale energy storage systems. This growth has been driven by improvements in the cost and performance of energy storage technologies and the need to accommodate distributed generation, as well as incentives and government mandates. Energymore » management systems (EMSs) and optimization methods are required to effectively and safely utilize energy storage as a flexible grid asset that can provide multiple grid services. The EMS needs to be able to accommodate a variety of use cases and regulatory environments. In this paper, we provide a brief history of grid-scale energy storage, an overview of EMS architectures, and a summary of the leading applications for storage. These serve as a foundation for a discussion of EMS optimization methods and design.« less

The optimal operation of cooling tower systems with variable-frequency control

NASA Astrophysics Data System (ADS)

Cao, Yong; Huang, Liqing; Cui, Zhiguo; Liu, Jing

2018-02-01

This study investigates the energy performance of chiller and cooling tower systems integrated with variable-frequency control for cooling tower fans and condenser water pumps. With regard to an example chiller system serving an office building, Chiller and cooling towers models were developed to assess how different variable-frequency control methods of cooling towers fans and condenser water pumps influence the trade-off between the chiller power, pump power and fan power under various operating conditions. The matching relationship between the cooling tower fans frequency and condenser water pumps frequency at optimal energy consumption of the system is introduced to achieve optimum system performance.

Co-Optimization of Fuels and Engines

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

Farrell, John

2016-03-24

The Co-Optimization of Fuels and Engines (Co-Optima) initiative is a new DOE initiative focused on accelerating the introduction of affordable, scalable, and sustainable biofuels and high-efficiency, low-emission vehicle engines. The simultaneous fuels and vehicles research and development (R&D) are designed to deliver maximum energy savings, emissions reduction, and on-road vehicle performance. The initiative's integrated approach combines the previously independent areas of biofuels and combustion R&D, bringing together two DOE Office of Energy Efficiency & Renewable Energy research offices, ten national laboratories, and numerous industry and academic partners to simultaneously tackle fuel and engine research and development (R&D) to maximize energymore » savings and on-road vehicle performance while dramatically reducing transportation-related petroleum consumption and greenhouse gas (GHG) emissions. This multi-year project will provide industry with the scientific underpinnings required to move new biofuels and advanced engine systems to market faster while identifying and addressing barriers to their commercialization. This project's ambitious, first-of-its-kind approach simultaneously tackles fuel and engine innovation to co-optimize performance of both elements and provide dramatic and rapid cuts in fuel use and emissions. This presentation provides an overview of the project.« less

Multichannel-Sensing Scheduling and Transmission-Energy Optimizing in Cognitive Radio Networks with Energy Harvesting.

PubMed

Hoan, Tran-Nhut-Khai; Hiep, Vu-Van; Koo, In-Soo

2016-03-31

This paper considers cognitive radio networks (CRNs) utilizing multiple time-slotted primary channels in which cognitive users (CUs) are powered by energy harvesters. The CUs are under the consideration that hardware constraints on radio devices only allow them to sense and transmit on one channel at a time. For a scenario where the arrival of harvested energy packets and the battery capacity are finite, we propose a scheme to optimize (i) the channel-sensing schedule (consisting of finding the optimal action (silent or active) and sensing order of channels) and (ii) the optimal transmission energy set corresponding to the channels in the sensing order for the operation of the CU in order to maximize the expected throughput of the CRN over multiple time slots. Frequency-switching delay, energy-switching cost, correlation in spectrum occupancy across time and frequency and errors in spectrum sensing are also considered in this work. The performance of the proposed scheme is evaluated via simulation. The simulation results show that the throughput of the proposed scheme is greatly improved, in comparison to related schemes in the literature. The collision ratio on the primary channels is also investigated.

Novel optimization technique of isolated microgrid with hydrogen energy storage.

PubMed

Beshr, Eman Hassan; Abdelghany, Hazem; Eteiba, Mahmoud

2018-01-01

This paper presents a novel optimization technique for energy management studies of an isolated microgrid. The system is supplied by various Distributed Energy Resources (DERs), Diesel Generator (DG), a Wind Turbine Generator (WTG), Photovoltaic (PV) arrays and supported by fuel cell/electrolyzer Hydrogen storage system for short term storage. Multi-objective optimization is used through non-dominated sorting genetic algorithm to suit the load requirements under the given constraints. A novel multi-objective flower pollination algorithm is utilized to check the results. The Pros and cons of the two optimization techniques are compared and evaluated. An isolated microgrid is modelled using MATLAB software package, dispatch of active/reactive power, optimal load flow analysis with slack bus selection are carried out to be able to minimize fuel cost and line losses under realistic constraints. The performance of the system is studied and analyzed during both summer and winter conditions and three case studies are presented for each condition. The modified IEEE 15 bus system is used to validate the proposed algorithm.

Novel optimization technique of isolated microgrid with hydrogen energy storage

PubMed Central

Abdelghany, Hazem; Eteiba, Mahmoud

2018-01-01

This paper presents a novel optimization technique for energy management studies of an isolated microgrid. The system is supplied by various Distributed Energy Resources (DERs), Diesel Generator (DG), a Wind Turbine Generator (WTG), Photovoltaic (PV) arrays and supported by fuel cell/electrolyzer Hydrogen storage system for short term storage. Multi-objective optimization is used through non-dominated sorting genetic algorithm to suit the load requirements under the given constraints. A novel multi-objective flower pollination algorithm is utilized to check the results. The Pros and cons of the two optimization techniques are compared and evaluated. An isolated microgrid is modelled using MATLAB software package, dispatch of active/reactive power, optimal load flow analysis with slack bus selection are carried out to be able to minimize fuel cost and line losses under realistic constraints. The performance of the system is studied and analyzed during both summer and winter conditions and three case studies are presented for each condition. The modified IEEE 15 bus system is used to validate the proposed algorithm. PMID:29466433

Power optimization of ultrasonic friction-modulation tactile interfaces.

PubMed

Wiertlewski, Michael; Colgate, J Edward

2015-01-01

Ultrasonic friction-modulation devices provide rich tactile sensation on flat surfaces and have the potential to restore tangibility to touchscreens. To date, their adoption into consumer electronics has been in part limited by relatively high power consumption, incompatible with the requirements of battery-powered devices. This paper introduces a method that optimizes the energy efficiency and performance of this class of devices. It considers optimal energy transfer to the impedance provided by the finger interacting with the surface. Constitutive equations are determined from the mode shape of the interface and the piezoelectric coupling of the actuator. The optimization procedure employs a lumped parameter model to simplify the treatment of the problem. Examples and an experimental study show the evolution of the optimal design as a function of the impedance of the finger.

A study of the optimal transition temperatue of PCM (Phase Change Material) wallboard for solar energy storage

NASA Astrophysics Data System (ADS)

Drake, J. B.

1987-09-01

The performance of wallboard impregnated with phase change material (PCM) is considered. An ideal setting is assumed and several measures of performance discussed. With a definition of optimal performance given, the performance with respect to variation of transition temperature is studied. Results are based on computer simulations of PCM wallboard with a standard stud wall construction. The diurnal heat capacity was found to be to be overly sensitive to numerical errors for use in PCM applications. The other measures of performance, diurnal effectiveness, net collected to storage ratio, and absolute discharge flux, all indicate similar trends. It is shown that the optimal transition temperature of the PCM is strongly influenced by the amount of solar flux absorbed.

Globally optimal superconducting magnets part II: symmetric MSE coil arrangement.

PubMed

Tieng, Quang M; Vegh, Viktor; Brereton, Ian M

2009-01-01

A globally optimal superconducting magnet coil design procedure based on the Minimum Stored Energy (MSE) current density map is outlined. The method has the ability to arrange coils in a manner that generates a strong and homogeneous axial magnetic field over a predefined region, and ensures the stray field external to the assembly and peak magnetic field at the wires are in acceptable ranges. The outlined strategy of allocating coils within a given domain suggests that coils should be placed around the perimeter of the domain with adjacent coils possessing alternating winding directions for optimum performance. The underlying current density maps from which the coils themselves are derived are unique, and optimized to possess minimal stored energy. Therefore, the method produces magnet designs with the lowest possible overall stored energy. Optimal coil layouts are provided for unshielded and shielded short bore symmetric superconducting magnets.

Co-Optimization of Fuels & Engines for Tomorrow's Energy-Efficient Vehicles

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

2016-03-01

A new U.S. Department of Energy (DOE) initiative is accelerating the introduction of affordable, scalable, and sustainable biofuels and high-efficiency, low-emission vehicle engines. The simultaneous fuels and vehicles research and development (R&D) is designed to deliver maximum energy savings, emissions reduction, and on-road vehicle performance. The initiative's integrated approach combines the previously independent areas of biofuels and combustion R&D, bringing together two DOE Office of Energy Efficiency & Renewable Energy research offices, nine national laboratories, and numerous industry and academic partners to more rapidly identify commercially viable solutions. This multi-year project will provide industry with the scientific underpinnings required tomore » move new biofuels and advanced engine systems to market faster while identifying and addressing barriers to their commercialization. This project's ambitious, first-of-its-kind approach simultaneously tackles fuel and engine innovation to co-optimize performance of both elements and provide dramatic and rapid cuts in fuel use and emissions.« less

Analytical Study on Multi-Tier 5G Heterogeneous Small Cell Networks: Coverage Performance and Energy Efficiency.

PubMed

Xiao, Zhu; Liu, Hongjing; Havyarimana, Vincent; Li, Tong; Wang, Dong

2016-11-04

In this paper, we investigate the coverage performance and energy efficiency of multi-tier heterogeneous cellular networks (HetNets) which are composed of macrocells and different types of small cells, i.e., picocells and femtocells. By virtue of stochastic geometry tools, we model the multi-tier HetNets based on a Poisson point process (PPP) and analyze the Signal to Interference Ratio (SIR) via studying the cumulative interference from pico-tier and femto-tier. We then derive the analytical expressions of coverage probabilities in order to evaluate coverage performance in different tiers and investigate how it varies with the small cells' deployment density. By taking the fairness and user experience into consideration, we propose a disjoint channel allocation scheme and derive the system channel throughput for various tiers. Further, we formulate the energy efficiency optimization problem for multi-tier HetNets in terms of throughput performance and resource allocation fairness. To solve this problem, we devise a linear programming based approach to obtain the available area of the feasible solutions. System-level simulations demonstrate that the small cells' deployment density has a significant effect on the coverage performance and energy efficiency. Simulation results also reveal that there exits an optimal small cell base station (SBS) density ratio between pico-tier and femto-tier which can be applied to maximize the energy efficiency and at the same time enhance the system performance. Our findings provide guidance for the design of multi-tier HetNets for improving the coverage performance as well as the energy efficiency.

Analytical Study on Multi-Tier 5G Heterogeneous Small Cell Networks: Coverage Performance and Energy Efficiency

PubMed Central

Xiao, Zhu; Liu, Hongjing; Havyarimana, Vincent; Li, Tong; Wang, Dong

2016-01-01

In this paper, we investigate the coverage performance and energy efficiency of multi-tier heterogeneous cellular networks (HetNets) which are composed of macrocells and different types of small cells, i.e., picocells and femtocells. By virtue of stochastic geometry tools, we model the multi-tier HetNets based on a Poisson point process (PPP) and analyze the Signal to Interference Ratio (SIR) via studying the cumulative interference from pico-tier and femto-tier. We then derive the analytical expressions of coverage probabilities in order to evaluate coverage performance in different tiers and investigate how it varies with the small cells’ deployment density. By taking the fairness and user experience into consideration, we propose a disjoint channel allocation scheme and derive the system channel throughput for various tiers. Further, we formulate the energy efficiency optimization problem for multi-tier HetNets in terms of throughput performance and resource allocation fairness. To solve this problem, we devise a linear programming based approach to obtain the available area of the feasible solutions. System-level simulations demonstrate that the small cells’ deployment density has a significant effect on the coverage performance and energy efficiency. Simulation results also reveal that there exits an optimal small cell base station (SBS) density ratio between pico-tier and femto-tier which can be applied to maximize the energy efficiency and at the same time enhance the system performance. Our findings provide guidance for the design of multi-tier HetNets for improving the coverage performance as well as the energy efficiency. PMID:27827917

Performance of discrete heat engines and heat pumps in finite time

PubMed

Feldmann; Kosloff

2000-05-01

The performance in finite time of a discrete heat engine with internal friction is analyzed. The working fluid of the engine is composed of an ensemble of noninteracting two level systems. External work is applied by changing the external field and thus the internal energy levels. The friction induces a minimal cycle time. The power output of the engine is optimized with respect to time allocation between the contact time with the hot and cold baths as well as the adiabats. The engine's performance is also optimized with respect to the external fields. By reversing the cycle of operation a heat pump is constructed. The performance of the engine as a heat pump is also optimized. By varying the time allocation between the adiabats and the contact time with the reservoir a universal behavior can be identified. The optimal performance of the engine when the cold bath is approaching absolute zero is studied. It is found that the optimal cooling rate converges linearly to zero when the temperature approaches absolute zero.

Online energy management strategy of fuel cell hybrid electric vehicles based on data fusion approach

NASA Astrophysics Data System (ADS)

Zhou, Daming; Al-Durra, Ahmed; Gao, Fei; Ravey, Alexandre; Matraji, Imad; Godoy Simões, Marcelo

2017-10-01

Energy management strategy plays a key role for Fuel Cell Hybrid Electric Vehicles (FCHEVs), it directly affects the efficiency and performance of energy storages in FCHEVs. For example, by using a suitable energy distribution controller, the fuel cell system can be maintained in a high efficiency region and thus saving hydrogen consumption. In this paper, an energy management strategy for online driving cycles is proposed based on a combination of the parameters from three offline optimized fuzzy logic controllers using data fusion approach. The fuzzy logic controllers are respectively optimized for three typical driving scenarios: highway, suburban and city in offline. To classify patterns of online driving cycles, a Probabilistic Support Vector Machine (PSVM) is used to provide probabilistic classification results. Based on the classification results of the online driving cycle, the parameters of each offline optimized fuzzy logic controllers are then fused using Dempster-Shafer (DS) evidence theory, in order to calculate the final parameters for the online fuzzy logic controller. Three experimental validations using Hardware-In-the-Loop (HIL) platform with different-sized FCHEVs have been performed. Experimental comparison results show that, the proposed PSVM-DS based online controller can achieve a relatively stable operation and a higher efficiency of fuel cell system in real driving cycles.

Construction Performance Optimization toward Green Building Premium Cost Based on Greenship Rating Tools Assessment with Value Engineering Method

NASA Astrophysics Data System (ADS)

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

2017-07-01

Green building concept becomes important in current building life cycle to mitigate environment issues. The purpose of this paper is to optimize building construction performance towards green building premium cost, achieving green building rating tools with optimizing life cycle cost. Therefore, this study helps building stakeholder determining building fixture to achieve green building certification target. Empirically the paper collects data of green building in the Indonesian construction industry such as green building fixture, initial cost, operational and maintenance cost, and certification score achievement. After that, using value engineering method optimized green building fixture based on building function and cost aspects. Findings indicate that construction performance optimization affected green building achievement with increasing energy and water efficiency factors and life cycle cost effectively especially chosen green building fixture.

NREL Evaluates Performance of Fast-Charge Electric Buses

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

2016-09-16

This real-world performance evaluation is designed to enhance understanding of the overall usage and effectiveness of electric buses in transit operation and to provide unbiased technical information to other agencies interested in adding such vehicles to their fleets. Initial results indicate that the electric buses under study offer significant fuel and emissions savings. The final results will help Foothill Transit optimize the energy-saving potential of its transit fleet. NREL's performance evaluations help vehicle manufacturers fine-tune their designs and help fleet managers select fuel-efficient, low-emission vehicles that meet their bottom line and operational goals. help Foothill Transit optimize the energy-saving potentialmore » of its transit fleet. NREL's performance evaluations help vehicle manufacturers fine-tune their designs and help fleet managers select fuel-efficient, low-emission vehicles that meet their bottom line and operational goals.« less

Central Plant Optimization for Waste Energy Reduction (CPOWER). ESTCP Cost and Performance Report

DTIC Science & Technology

2016-12-01

in the regression models. The solar radiation data did not appear reliable in the weather dataset for the location, and hence it was not used. The...and additional factors (e.g., solar insolation) may be needed to obtain a better model. 2. Inputs to optimizer: During several periods of...Location: North Carolina Energy Consumption Cost Savings $ 443,698.00 Analysis Type: FEMP PV of total savings 215,698.00$ Base Date: April 1

2-D Ultrasound Sparse Arrays Multidepth Radiation Optimization Using Simulated Annealing and Spiral-Array Inspired Energy Functions.

PubMed

Roux, Emmanuel; Ramalli, Alessandro; Tortoli, Piero; Cachard, Christian; Robini, Marc C; Liebgott, Herve

2016-12-01

Full matrix arrays are excellent tools for 3-D ultrasound imaging, but the required number of active elements is too high to be individually controlled by an equal number of scanner channels. The number of active elements is significantly reduced by the sparse array techniques, but the position of the remaining elements must be carefully optimized. This issue is faced here by introducing novel energy functions in the simulated annealing (SA) algorithm. At each iteration step of the optimization process, one element is freely translated and the associated radiated pattern is simulated. To control the pressure field behavior at multiple depths, three energy functions inspired by the pressure field radiated by a Blackman-tapered spiral array are introduced. Such energy functions aim at limiting the main lobe width while lowering the side lobe and grating lobe levels at multiple depths. Numerical optimization results illustrate the influence of the number of iterations, pressure measurement points, and depths, as well as the influence of the energy function definition on the optimized layout. It is also shown that performance close to or even better than the one provided by a spiral array, here assumed as reference, may be obtained. The finite-time convergence properties of SA allow the duration of the optimization process to be set in advance.

Binding Free Energy Calculations for Lead Optimization: Assessment of Their Accuracy in an Industrial Drug Design Context.

PubMed

Homeyer, Nadine; Stoll, Friederike; Hillisch, Alexander; Gohlke, Holger

2014-08-12

Correctly ranking compounds according to their computed relative binding affinities will be of great value for decision making in the lead optimization phase of industrial drug discovery. However, the performance of existing computationally demanding binding free energy calculation methods in this context is largely unknown. We analyzed the performance of the molecular mechanics continuum solvent, the linear interaction energy (LIE), and the thermodynamic integration (TI) approach for three sets of compounds from industrial lead optimization projects. The data sets pose challenges typical for this early stage of drug discovery. None of the methods was sufficiently predictive when applied out of the box without considering these challenges. Detailed investigations of failures revealed critical points that are essential for good binding free energy predictions. When data set-specific features were considered accordingly, predictions valuable for lead optimization could be obtained for all approaches but LIE. Our findings lead to clear recommendations for when to use which of the above approaches. Our findings also stress the important role of expert knowledge in this process, not least for estimating the accuracy of prediction results by TI, using indicators such as the size and chemical structure of exchanged groups and the statistical error in the predictions. Such knowledge will be invaluable when it comes to the question which of the TI results can be trusted for decision making.

A review on optimization production and upgrading biogas through CO2 removal using various techniques.

PubMed

Andriani, Dian; Wresta, Arini; Atmaja, Tinton Dwi; Saepudin, Aep

2014-02-01

Biogas from anaerobic digestion of organic materials is a renewable energy resource that consists mainly of CH4 and CO2. Trace components that are often present in biogas are water vapor, hydrogen sulfide, siloxanes, hydrocarbons, ammonia, oxygen, carbon monoxide, and nitrogen. Considering the biogas is a clean and renewable form of energy that could well substitute the conventional source of energy (fossil fuels), the optimization of this type of energy becomes substantial. Various optimization techniques in biogas production process had been developed, including pretreatment, biotechnological approaches, co-digestion as well as the use of serial digester. For some application, the certain purity degree of biogas is needed. The presence of CO2 and other trace components in biogas could affect engine performance adversely. Reducing CO2 content will significantly upgrade the quality of biogas and enhancing the calorific value. Upgrading is generally performed in order to meet the standards for use as vehicle fuel or for injection in the natural gas grid. Different methods for biogas upgrading are used. They differ in functioning, the necessary quality conditions of the incoming gas, and the efficiency. Biogas can be purified from CO2 using pressure swing adsorption, membrane separation, physical or chemical CO2 absorption. This paper reviews the various techniques, which could be used to optimize the biogas production as well as to upgrade the biogas quality.

Process Optimization Assessment: Fort Leonard Wood, MO and Fort Carson, CO

DTIC Science & Technology

2003-11-01

IUJ US Army Corps of Engineers, Engineer Research and Development Center Process Optimization Assessment Fort Leonard Wood, MO and Fort Carson, CO... Optimization Assessment: Fort Leonard Wood, MO and Fort Carson, CO Mike C.J. Lin and John Vavrin Construction Engineering Research Laboratory PO Box 9005...work performed a Process Optimization Assessment (POA) on behalf of Fort Leonard Wood, MO and Fort Carson, CO to identify process, energy, and

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

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

Kistler, B.L.

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

Optimizing Sustainable Geothermal Heat Extraction

NASA Astrophysics Data System (ADS)

Patel, Iti; Bielicki, Jeffrey; Buscheck, Thomas

2016-04-01

Geothermal heat, though renewable, can be depleted over time if the rate of heat extraction exceeds the natural rate of renewal. As such, the sustainability of a geothermal resource is typically viewed as preserving the energy of the reservoir by weighing heat extraction against renewability. But heat that is extracted from a geothermal reservoir is used to provide a service to society and an economic gain to the provider of that service. For heat extraction used for market commodities, sustainability entails balancing the rate at which the reservoir temperature renews with the rate at which heat is extracted and converted into economic profit. We present a model for managing geothermal resources that combines simulations of geothermal reservoir performance with natural resource economics in order to develop optimal heat mining strategies. Similar optimal control approaches have been developed for managing other renewable resources, like fisheries and forests. We used the Non-isothermal Unsaturated-saturated Flow and Transport (NUFT) model to simulate the performance of a sedimentary geothermal reservoir under a variety of geologic and operational situations. The results of NUFT are integrated into the optimization model to determine the extraction path over time that maximizes the net present profit given the performance of the geothermal resource. Results suggest that the discount rate that is used to calculate the net present value of economic gain is a major determinant of the optimal extraction path, particularly for shallower and cooler reservoirs, where the regeneration of energy due to the natural geothermal heat flux is a smaller percentage of the amount of energy that is extracted from the reservoir.

Performance evaluation and comparison of three-terminal energy selective electron devices with different connective ways and filter configurations

NASA Astrophysics Data System (ADS)

Peng, Wanli; Zhang, Yanchao; Yang, Zhimin; Chen, Jincan

2018-02-01

Three-terminal energy selective electron (ESE) devices consisting of three electronic reservoirs connected by two energy filters and an electronic conductor with negligible resistance may work as ESE refrigerators and amplifiers. They have three possible connective ways for the electronic conductor and six electronic transmission forms. The configuration of energy filters may be described by the different transmission functions such as the rectangular and Lorentz transmission functions. The ESE devices with three connective ways can be, respectively, regarded as three equivalent hybrid systems composed of an ESE heat engine and an ESE refrigerator/heat pump. With the help of the theory of the ESE devices operated between two electronic reservoirs, the coefficients of performance and cooling rates (heat-pumping rates) of hybrid systems are directly derived. The general performance characteristics of hybrid systems are revealed. The optimal regions of these devices are determined. The performances of the devices with three connective ways of the electronic conductor and two configurations of energy filters are compared in detail. The advantages and disadvantages of each of three-terminal ESE devices are expounded. The results obtained here may provide some guidance for the optimal design and operation of three-terminal ESE devices.

Energy acceptance and on momentum aperture optimization for the Sirius project

NASA Astrophysics Data System (ADS)

Dester, P. S.; Sá, F. H.; Liu, L.

2017-07-01

A fast objective function to calculate Touschek lifetime and on momentum aperture is essential to explore the vast search space of strength of quadrupole and sextupole families in Sirius. Touschek lifetime is estimated by using the energy aperture (dynamic and physical), RF system parameters and driving terms. Non-linear induced betatron oscillations are considered to determine the energy aperture. On momentum aperture is estimated by using a chaos indicator and resonance crossing considerations. Touschek lifetime and on momentum aperture constitute the objective function, which was used in a multi-objective genetic algorithm to perform an optimization for Sirius.

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

DTIC Science & Technology

2014-02-01

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

Performance characteristics of a thermal energy storage module - A transient PCM/forced convection conjugate analysis

NASA Technical Reports Server (NTRS)

Cao, Y.; Faghri, A.

1991-01-01

The performance of a thermal energy storage module is simulated numerically. The change of phase of the phase-change material (PCM) and the transient forced convective heat transfer for the transfer fluid with low Prandtl numbers are solved simultaneously as a conjugate problem. A parametric study and a system optimization are conducted. The numerical results show that module geometry is crucial to the design of a space-based thermal energy storage system.

Integrative modeling and novel particle swarm-based optimal design of wind farms

NASA Astrophysics Data System (ADS)

Chowdhury, Souma

To meet the energy needs of the future, while seeking to decrease our carbon footprint, a greater penetration of sustainable energy resources such as wind energy is necessary. However, a consistent growth of wind energy (especially in the wake of unfortunate policy changes and reported under-performance of existing projects) calls for a paradigm shift in wind power generation technologies. This dissertation develops a comprehensive methodology to explore, analyze and define the interactions between the key elements of wind farm development, and establish the foundation for designing high-performing wind farms. The primary contribution of this research is the effective quantification of the complex combined influence of wind turbine features, turbine placement, farm-land configuration, nameplate capacity, and wind resource variations on the energy output of the wind farm. A new Particle Swarm Optimization (PSO) algorithm, uniquely capable of preserving population diversity while addressing discrete variables, is also developed to provide powerful solutions towards optimizing wind farm configurations. In conventional wind farm design, the major elements that influence the farm performance are often addressed individually. The failure to fully capture the critical interactions among these factors introduces important inaccuracies in the projected farm performance and leads to suboptimal wind farm planning. In this dissertation, we develop the Unrestricted Wind Farm Layout Optimization (UWFLO) methodology to model and optimize the performance of wind farms. The UWFLO method obviates traditional assumptions regarding (i) turbine placement, (ii) turbine-wind flow interactions, (iii) variation of wind conditions, and (iv) types of turbines (single/multiple) to be installed. The allowance of multiple turbines, which demands complex modeling, is rare in the existing literature. The UWFLO method also significantly advances the state of the art in wind farm optimization by allowing simultaneous optimization of the type and the location of the turbines. Layout optimization (using UWFLO) of a hypothetical 25-turbine commercial-scale wind farm provides a remarkable 4.4% increase in capacity factor compared to a conventional array layout. A further 2% increase in capacity factor is accomplished when the types of turbines are also optimally selected. The scope of turbine selection and placement however depends on the land configuration and the nameplate capacity of the farm. Such dependencies are not clearly defined in the existing literature. We develop response surface-based models, which implicitly employ UWFLO, to quantify and analyze the roles of these other crucial design factors in optimal wind farm planning. The wind pattern at a site can vary significantly from year to year, which is not adequately captured by conventional wind distribution models. The resulting ill-predictability of the annual distribution of wind conditions introduces significant uncertainties in the estimated energy output of the wind farm. A new method is developed to characterize these wind resource uncertainties and model the propagation of these uncertainties into the estimated farm output. The overall wind pattern/regime also varies from one region to another, which demands turbines with capabilities uniquely suited for different wind regimes. Using the UWFLO method, we model the performance potential of currently available turbines for different wind regimes, and quantify their feature-based expected market suitability. Such models can initiate an understanding of the product variation that current turbine manufacturers should pursue, to adequately satisfy the needs of the naturally diverse wind energy market. The wind farm design problems formulated in this dissertation involve highly multimodal objective and constraint functions and a large number of continuous and discrete variables. An effective modification of the PSO algorithm is developed to address such challenging problems. Continuous search, as in conventional PSO, is implemented as the primary search strategy; discrete variables are then updated using a nearest-allowed-discrete-point criterion. Premature stagnation of particles due to loss of population diversity is one of the primary drawbacks of the basic PSO dynamics. A new measure of population diversity is formulated, which unlike existing metrics capture both the overall spread and the distribution of particles in the variable space. This diversity metric is then used to apply (i) an adaptive repulsion away from the best global solution in the case of continuous variables, and (ii) a stochastic update of the discrete variables. The new PSO algorithm provides competitive performance compared to a popular genetic algorithm, when applied to solve a comprehensive set of 98 mixed-integer nonlinear programming problems.

Assessment of Energy Storage Alternatives in the Puget Sound Energy System Volume 2: Energy Storage Evaluation Tool

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

Wu, Di; Jin, Chunlian; Balducci, Patrick J.

2013-12-01

This volume presents the battery storage evaluation tool developed at Pacific Northwest National Laboratory (PNNL), which is used to evaluate benefits of battery storage for multiple grid applications, including energy arbitrage, balancing service, capacity value, distribution system equipment deferral, and outage mitigation. This tool is based on the optimal control strategies to capture multiple services from a single energy storage device. In this control strategy, at each hour, a look-ahead optimization is first formulated and solved to determine battery base operating point. The minute by minute simulation is then performed to simulate the actual battery operation. This volume provide backgroundmore » and manual for this evaluation tool.« less

A hybrid multi-objective evolutionary algorithm for wind-turbine blade optimization

NASA Astrophysics Data System (ADS)

Sessarego, M.; Dixon, K. R.; Rival, D. E.; Wood, D. H.

2015-08-01

A concurrent-hybrid non-dominated sorting genetic algorithm (hybrid NSGA-II) has been developed and applied to the simultaneous optimization of the annual energy production, flapwise root-bending moment and mass of the NREL 5 MW wind-turbine blade. By hybridizing a multi-objective evolutionary algorithm (MOEA) with gradient-based local search, it is believed that the optimal set of blade designs could be achieved in lower computational cost than for a conventional MOEA. To measure the convergence between the hybrid and non-hybrid NSGA-II on a wind-turbine blade optimization problem, a computationally intensive case was performed using the non-hybrid NSGA-II. From this particular case, a three-dimensional surface representing the optimal trade-off between the annual energy production, flapwise root-bending moment and blade mass was achieved. The inclusion of local gradients in the blade optimization, however, shows no improvement in the convergence for this three-objective problem.

Unleashing elastic energy: dynamics of energy release in rubber bands and impulsive biological systems

NASA Astrophysics Data System (ADS)

Ilton, Mark; Cox, Suzanne; Egelmeers, Thijs; Patek, S. N.; Crosby, Alfred J.

Impulsive biological systems - which include mantis shrimp, trap-jaw ants, and venus fly traps - can reach high speeds by using elastic elements to store and rapidly release energy. The material behavior and shape changes critical to achieving rapid energy release in these systems are largely unknown due to limitations of materials testing instruments operating at high speed and large displacement. In this work, we perform fundamental, proof-of-concept measurements on the tensile retraction of elastomers. Using high speed imaging, the kinematics of retraction are measured for elastomers with varying mechanical properties and geometry. Based on the kinematics, the rate of energy dissipation in the material is determined as a function of strain and strain-rate, along with a scaling relation which describes the dependence of maximum velocity on material properties. Understanding this scaling relation along with the material failure limits of the elastomer allows the prediction of material properties required for optimal performance. We demonstrate this concept experimentally by optimizing for maximum velocity in our synthetic model system, and achieve retraction velocities that exceed those in biological impulsive systems. This model system provides a foundation for future work connecting continuum performance to molecular architecture in impulsive systems.

Optimization and comparison of simultaneous and separate acquisition protocols for dual isotope myocardial perfusion SPECT

PubMed Central

Ghaly, Michael; Links, Jonathan M; Frey, Eric C

2015-01-01

Dual-isotope simultaneous-acquisition (DISA) rest-stress myocardial perfusion SPECT (MPS) protocols offer a number of advantages over separate acquisition. However, crosstalk contamination due to scatter in the patient and interactions in the collimator degrade image quality. Compensation can reduce the effects of crosstalk, but does not entirely eliminate image degradations. Optimizing acquisition parameters could further reduce the impact of crosstalk. In this paper we investigate the optimization of the rest Tl-201 energy window width and relative injected activities using the ideal observer (IO), a realistic digital phantom population and Monte Carlo (MC) simulated Tc-99m and Tl-201 projections as a means to improve image quality. We compared performance on a perfusion defect detection task for Tl-201 acquisition energy window widths varying from 4 to 40 keV centered at 72 keV for a camera with a 9% energy resolution. We also investigated 7 different relative injected activities, defined as the ratio of Tc-99m and Tl-201 activities, while keeping the total effective dose constant at 13.5 mSv. For each energy window and relative injected activity, we computed the IO test statistics using a Markov chain Monte Carlo (MCMC) method for an ensemble of 1,620 triplets of fixed and reversible defect-present, and defect-absent noisy images modeling realistic background variations. The volume under the 3-class receiver operating characteristic (ROC) surface (VUS) was estimated and served as the figure of merit. For simultaneous acquisition, the IO suggested that relative Tc-to-Tl injected activity ratios of 2.6–5 and acquisition energy window widths of 16–22% were optimal. For separate acquisition, we observed a broad range of optimal relative injected activities from 2.6 to 12.1 and acquisition energy window of widths 16–22%. A negative correlation between Tl-201 injected activity and the width of the Tl-201 energy window was observed in these ranges. The results also suggested that DISA methods could potentially provide image quality as good as that obtained with separate acquisition protocols. We compared observer performance for the optimized protocols and the current clinical protocol using separate acquisition. The current clinical protocols provided better performance at a cost of injecting the patient with approximately double the injected activity of Tc-99m and Tl-201, resulting in substantially increased radiation dose. PMID:26083239

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

Water and Power Systems Co-optimization under a High Performance Computing Framework

NASA Astrophysics Data System (ADS)

Xuan, Y.; Arumugam, S.; DeCarolis, J.; Mahinthakumar, K.

2016-12-01

Water and energy systems optimizations are traditionally being treated as two separate processes, despite their intrinsic interconnections (e.g., water is used for hydropower generation, and thermoelectric cooling requires a large amount of water withdrawal). Given the challenges of urbanization, technology uncertainty and resource constraints, and the imminent threat of climate change, a cyberinfrastructure is needed to facilitate and expedite research into the complex management of these two systems. To address these issues, we developed a High Performance Computing (HPC) framework for stochastic co-optimization of water and energy resources to inform water allocation and electricity demand. The project aims to improve conjunctive management of water and power systems under climate change by incorporating improved ensemble forecast models of streamflow and power demand. First, by downscaling and spatio-temporally disaggregating multimodel climate forecasts from General Circulation Models (GCMs), temperature and precipitation forecasts are obtained and input into multi-reservoir and power systems models. Extended from Optimus (Optimization Methods for Universal Simulators), the framework drives the multi-reservoir model and power system model, Temoa (Tools for Energy Model Optimization and Analysis), and uses Particle Swarm Optimization (PSO) algorithm to solve high dimensional stochastic problems. The utility of climate forecasts on the cost of water and power systems operations is assessed and quantified based on different forecast scenarios (i.e., no-forecast, multimodel forecast and perfect forecast). Analysis of risk management actions and renewable energy deployments will be investigated for the Catawba River basin, an area with adequate hydroclimate predicting skill and a critical basin with 11 reservoirs that supplies water and generates power for both North and South Carolina. Further research using this scalable decision supporting framework will provide understanding and elucidate the intricate and interdependent relationship between water and energy systems and enhance the security of these two critical public infrastructures.

Comparative assessment of computational methods for the determination of solvation free energies in alcohol-based molecules.

PubMed

Martins, Silvia A; Sousa, Sergio F

2013-06-05

The determination of differences in solvation free energies between related drug molecules remains an important challenge in computational drug optimization, when fast and accurate calculation of differences in binding free energy are required. In this study, we have evaluated the performance of five commonly used polarized continuum model (PCM) methodologies in the determination of solvation free energies for 53 typical alcohol and alkane small molecules. In addition, the performance of these PCM methods, of a thermodynamic integration (TI) protocol and of the Poisson-Boltzmann (PB) and generalized Born (GB) methods, were tested in the determination of solvation free energies changes for 28 common alkane-alcohol transformations, by the substitution of an hydrogen atom for a hydroxyl substituent. The results show that the solvation model D (SMD) performs better among the PCM-based approaches in estimating solvation free energies for alcohol molecules, and solvation free energy changes for alkane-alcohol transformations, with an average error below 1 kcal/mol for both quantities. However, for the determination of solvation free energy changes on alkane-alcohol transformation, PB and TI yielded better results. TI was particularly accurate in the treatment of hydroxyl groups additions to aromatic rings (0.53 kcal/mol), a common transformation when optimizing drug-binding in computer-aided drug design. Copyright © 2013 Wiley Periodicals, Inc.

Distributed Wind Competitiveness Improvement Project

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

The Competitiveness Improvement Project (CIP) is a periodic solicitation through the U.S. Department of Energy and its National Renewable Energy Laboratory. The Competitiveness Improvement Project (CIP) is a periodic solicitation through the U.S. Department of Energy and its National Renewable Energy Laboratory. Manufacturers of small and medium wind turbines are awarded cost-shared grants via a competitive process to optimize their designs, develop advanced manufacturing processes, and perform turbine testing. The goals of the CIP are to make wind energy cost competitive with other distributed generation technology and increase the number of wind turbine designs certified to national testing standards. Thismore » fact sheet describes the CIP and funding awarded as part of the project.ufacturers of small and medium wind turbines are awarded cost-shared grants via a competitive process to optimize their designs, develop advanced manufacturing processes, and perform turbine testing. The goals of the CIP are to make wind energy cost competitive with other distributed generation technology and increase the number of wind turbine designs certified to national testing standards. This fact sheet describes the CIP and funding awarded as part of the project.« less

Modeling and optimization of a concentrated solar supercritical CO2 power plant

NASA Astrophysics Data System (ADS)

Osorio, Julian D.

Renewable energy sources are fundamental alternatives to supply the rising energy demand in the world and to reduce or replace fossil fuel technologies. In order to make renewable-based technologies suitable for commercial and industrial applications, two main challenges need to be solved: the design and manufacture of highly efficient devices and reliable systems to operate under intermittent energy supply conditions. In particular, power generation technologies based on solar energy are one of the most promising alternatives to supply the world energy demand and reduce the dependence on fossil fuel technologies. In this dissertation, the dynamic behavior of a Concentrated Solar Power (CSP) supercritical CO2 cycle is studied under different seasonal conditions. The system analyzed is composed of a central receiver, hot and cold thermal energy storage units, a heat exchanger, a recuperator, and multi-stage compression-expansion subsystems with intercoolers and reheaters between compressors and turbines respectively. The effects of operating and design parameters on the system performance are analyzed. Some of these parameters are the mass flow rate, intermediate pressures, number of compression-expansion stages, heat exchangers' effectiveness, multi-tank thermal energy storage, overall heat transfer coefficient between the solar receiver and the environment and the effective area of the recuperator. Energy and exergy models for each component of the system are developed to optimize operating parameters in order to lead to maximum efficiency. From the exergy analysis, the components with high contribution to exergy destruction were identified. These components, which represent an important potential of improvement, are the recuperator, the hot thermal energy storage tank and the solar receiver. Two complementary alternatives to improve the efficiency of concentrated solar thermal systems are proposed in this dissertation: the optimization of the system's operating parameters and optimization of less efficient components. The parametric optimization is developed for a 1MW reference CSP system with CO2 as the working fluid. The component optimization, focused on the less efficient components, comprises some design modifications to the traditional component configuration for the recuperator, the hot thermal energy storage tank and the solar receiver. The proposed optimization alternatives include the heat exchanger's effectiveness enhancement by optimizing fins shapes, multi-tank thermal energy storage configurations for the hot thermal energy storage tank and the incorporation of a transparent insulation material into the solar receiver. Some of the optimizations are conducted in a generalized way, using dimensionless models to be applicable no only to the CSP but also to other thermal systems. This project is therefore an effort to improve the efficiency of power generation systems based on solar energy in order to make them competitive with conventional fossil fuel power generation devices. The results show that the parametric optimization leads the system to an efficiency of about 21% and a maximum power output close to 1.5 MW. The process efficiencies obtained in this work, of more than 21%, are relatively good for a solar-thermal conversion system and are also comparable with efficiencies of conversion of high performance PV panels. The thermal energy storage allows the system to operate for several hours after sunset. This operating time is approximately increased from 220 to 480 minutes after optimization. The hot and cold thermal energy storage also lessens the temperature fluctuations by providing smooth changes of temperatures at the turbines' and compressors' inlets. Additional improvements in the overall system efficiency are possible by optimizing the less efficient components. In particular, the fin's effectiveness can be improved in more than 5% after its shape is optimized, increments in the efficiency of the thermal energy storage of about 5.7% are possible when the mass is divided into four tanks, and solar receiver efficiencies up to 70% can be maintained for high operating temperatures (~ 1200°C) when a transparent insulation material is incorporated to the receiver. The results obtained in this dissertation indicate that concentrated solar systems using supercritical CO2 could be a viable alternative to satisfying energy needs in desert areas with scarce water and fossil fuel resources.

Machine Learning Force Field Parameters from Ab Initio Data

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

Li, Ying; Li, Hui; Pickard, Frank C.

Machine learning (ML) techniques with the genetic algorithm (GA) have been applied to determine a polarizable force field parameters using only ab initio data from quantum mechanics (QM) calculations of molecular clusters at the MP2/6-31G(d,p), DFMP2(fc)/jul-cc-pVDZ, and DFMP2(fc)/jul-cc-pVTZ levels to predict experimental condensed phase properties (i.e., density and heat of vaporization). The performance of this ML/GA approach is demonstrated on 4943 dimer electrostatic potentials and 1250 cluster interaction energies for methanol. Excellent agreement between the training data set from QM calculations and the optimized force field model was achieved. The results were further improved by introducing an offset factor duringmore » the machine learning process to compensate for the discrepancy between the QM calculated energy and the energy reproduced by optimized force field, while maintaining the local “shape” of the QM energy surface. Throughout the machine learning process, experimental observables were not involved in the objective function, but were only used for model validation. The best model, optimized from the QM data at the DFMP2(fc)/jul-cc-pVTZ level, appears to perform even better than the original AMOEBA force field (amoeba09.prm), which was optimized empirically to match liquid properties. The present effort shows the possibility of using machine learning techniques to develop descriptive polarizable force field using only QM data. The ML/GA strategy to optimize force fields parameters described here could easily be extended to other molecular systems.« less

Design Optimization of a Magnetically Levitated Electromagnetic Vibration Energy Harvester for Body Motion

NASA Astrophysics Data System (ADS)

Pancharoen, K.; Zhu, D.; Beeby, S. P.

2016-11-01

This paper presents a magnetically levitated electromagnetic vibration energy harvester based on magnet arrays. It has a nonlinear response that extends the operating bandwidth and enhances the power output of the harvesting device. The harvester is designed to be embedded in a hip prosthesis and harvest energy from low frequency movements (< 5 Hz) associated with human motion. The design optimization is performed using Comsol simulation considering the constraints on size of the harvester and low operating frequency. The output voltage across the optimal load 3.5kΩ generated from hip movement is 0.137 Volts during walking and 0.38 Volts during running. The power output harvested from hip movement during walking and running is 5.35 μW and 41.36 μW respectively..

Energy-Efficient Cognitive Radio Sensor Networks: Parametric and Convex Transformations

PubMed Central

Naeem, Muhammad; Illanko, Kandasamy; Karmokar, Ashok; Anpalagan, Alagan; Jaseemuddin, Muhammad

2013-01-01

Designing energy-efficient cognitive radio sensor networks is important to intelligently use battery energy and to maximize the sensor network life. In this paper, the problem of determining the power allocation that maximizes the energy-efficiency of cognitive radio-based wireless sensor networks is formed as a constrained optimization problem, where the objective function is the ratio of network throughput and the network power. The proposed constrained optimization problem belongs to a class of nonlinear fractional programming problems. Charnes-Cooper Transformation is used to transform the nonlinear fractional problem into an equivalent concave optimization problem. The structure of the power allocation policy for the transformed concave problem is found to be of a water-filling type. The problem is also transformed into a parametric form for which a ε-optimal iterative solution exists. The convergence of the iterative algorithms is proven, and numerical solutions are presented. The iterative solutions are compared with the optimal solution obtained from the transformed concave problem, and the effects of different system parameters (interference threshold level, the number of primary users and secondary sensor nodes) on the performance of the proposed algorithms are investigated. PMID:23966194

Improvement and analysis of the hydrogen-cerium redox flow cell

DOE PAGES

Tucker, Michael C.; Weiss, Alexandra; Weber, Adam Z.

2016-08-03

In this paper, the H 2-Ce redox flow cell is optimized using commercially-available cell materials. Cell performance is found to be sensitive to the upper charge cutoff voltage, membrane boiling pretreatment, methanesulfonic-acid concentration, (+) electrode surface area and flow pattern, and operating temperature. Performance is relatively insensitive to membrane thickness, Cerium concentration, and all features of the (-) electrode including hydrogen flow. Cell performance appears to be limited by mass transport and kinetics in the cerium (+) electrode. Maximum discharge power of 895 mW cm -2 was observed at 60 °C; an energy efficiency of 90% was achieved at 50more » °C. Finally, the H 2-Ce cell is promising for energy storage assuming one can optimize Ce reaction kinetics and electrolyte.« 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

Optimized design of total energy systems: The RETE project

NASA Astrophysics Data System (ADS)

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

1980-05-01

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

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.

An Energy Storage Assessment: Using Optimal Control Strategies to Capture Multiple Services

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

Wu, Di; Jin, Chunlian; Balducci, Patrick J.

2015-09-01

This paper presents a methodology for evaluating benefits of battery storage for multiple grid applications, including energy arbitrage, balancing service, capacity value, distribution system equipment deferral, and outage mitigation. In the proposed method, at each hour, a look-ahead optimization is first formulated and solved to determine battery base operating point. The minute by minute simulation is then performed to simulate the actual battery operation. This methodology is used to assess energy storage alternatives in Puget Sound Energy System. Different battery storage candidates are simulated for a period of one year to assess different value streams and overall benefits, as partmore » of a financial feasibility evaluation of battery storage projects.« less

Optimization of power generating thermoelectric modules utilizing LNG cold energy

NASA Astrophysics Data System (ADS)

Jeong, Eun Soo

2017-12-01

A theoretical investigation to optimize thermoelectric modules, which convert LNG cold energy into electrical power, is performed using a novel one-dimensional analytic model. In the model the optimum thermoelement length and external load resistance, which maximize the energy conversion ratio, are determined by the heat supplied to the cold heat reservoir, the hot and cold side temperatures, the thermal and electrical contact resistances and the properties of thermoelectric materials. The effects of the thermal and electrical contact resistances and the heat supplied to the cold heat reservoir on the maximum energy conversion ratio, the optimum thermoelement length and the optimum external load resistance are shown.

Physiological and psychological effects of testosterone during severe energy deficit and recovery: A study protocol for a randomized, placebo-controlled trial for Optimizing Performance for Soldiers (OPS).

PubMed

Pasiakos, Stefan M; Berryman, Claire E; Karl, J Philip; Lieberman, Harris R; Orr, Jeb S; Margolis, Lee M; Caldwell, John A; Young, Andrew J; Montano, Monty A; Evans, William J; Vartanian, Oshin; Carmichael, Owen T; Gadde, Kishore M; Harris, Melissa; Rood, Jennifer C

2017-07-01

The physiological consequences of severe energy deficit include hypogonadism and the loss of fat-free mass. Prolonged energy deficit also impacts physical performance, mood, attentiveness, and decision-making capabilities. This study will determine whether maintaining a eugonadal state during severe, sustained energy deficit attenuates physiological decrements and maintains mental performance. This study will also assess the effects of normalizing testosterone levels during severe energy deficit and recovery on gut health and appetite regulation. Fifty physically active men will participate in a 3-phase, randomized, placebo-controlled study. After completing a 14-d, energy-adequate, diet acclimation phase (protein: 1.6g∙kg -1 ∙d -1 ; fat: 30% total energy intake), participants will be randomized to undergo a 28-d, 55% energy deficit phase with (DEF+TEST: 200mg testosterone enanthate per week) or without (DEF) exogenous testosterone. Diet and physical activity will be rigorously controlled. Recovery from the energy deficit (ad libitum diet, no testosterone) will be assessed until body mass has been recovered within ±2.5% of initial body mass. Body composition, stable isotope methodologies, proteomics, muscle biopsies, whole-room calorimetry, molecular biology, activity/sleep monitoring, personality and cognitive function assessments, functional MRI, and comprehensive biochemistries will be used to assess physiological and psychological responses to energy restriction and recovery feeding while volunteers are in an expected hypogonadal versus eugonadal state. The Optimizing Performance for Soldiers (OPS) study aims to determine whether preventing hypogonadism will mitigate declines in physical and mental function that typically occur during prolonged energy deficit, and the efficacy of testosterone replacement on recovery from severe underfeeding. NCT02734238. Copyright © 2017. Published by Elsevier Inc.

An energy-optimal solution for transportation control of cranes with double pendulum dynamics: Design and experiments

NASA Astrophysics Data System (ADS)

Sun, Ning; Wu, Yiming; Chen, He; Fang, Yongchun

2018-03-01

Underactuated cranes play an important role in modern industry. Specifically, in most situations of practical applications, crane systems exhibit significant double pendulum characteristics, which makes the control problem quite challenging. Moreover, most existing planners/controllers obtained with standard methods/techniques for double pendulum cranes cannot minimize the energy consumption when fulfilling the transportation tasks. Therefore, from a practical perspective, this paper proposes an energy-optimal solution for transportation control of double pendulum cranes. By applying the presented approach, the transportation objective, including fast trolley positioning and swing elimination, is achieved with minimized energy consumption, and the residual oscillations are suppressed effectively with all the state constrains being satisfied during the entire transportation process. As far as we know, this is the first energy-optimal solution for transportation control of underactuated double pendulum cranes with various state and control constraints. Hardware experimental results are included to verify the effectiveness of the proposed approach, whose superior performance is reflected by being experimentally compared with some comparative controllers.

An Optimal CDS Construction Algorithm with Activity Scheduling in Ad Hoc Networks

PubMed Central

Penumalli, Chakradhar; Palanichamy, Yogesh

2015-01-01

A new energy efficient optimal Connected Dominating Set (CDS) algorithm with activity scheduling for mobile ad hoc networks (MANETs) is proposed. This algorithm achieves energy efficiency by minimizing the Broadcast Storm Problem [BSP] and at the same time considering the node's remaining energy. The Connected Dominating Set is widely used as a virtual backbone or spine in mobile ad hoc networks [MANETs] or Wireless Sensor Networks [WSN]. The CDS of a graph representing a network has a significant impact on an efficient design of routing protocol in wireless networks. Here the CDS is a distributed algorithm with activity scheduling based on unit disk graph [UDG]. The node's mobility and residual energy (RE) are considered as parameters in the construction of stable optimal energy efficient CDS. The performance is evaluated at various node densities, various transmission ranges, and mobility rates. The theoretical analysis and simulation results of this algorithm are also presented which yield better results. PMID:26221627

A predictive control framework for optimal energy extraction of wind farms

NASA Astrophysics Data System (ADS)

Vali, M.; van Wingerden, J. W.; Boersma, S.; Petrović, V.; Kühn, M.

2016-09-01

This paper proposes an adjoint-based model predictive control for optimal energy extraction of wind farms. It employs the axial induction factor of wind turbines to influence their aerodynamic interactions through the wake. The performance index is defined here as the total power production of the wind farm over a finite prediction horizon. A medium-fidelity wind farm model is utilized to predict the inflow propagation in advance. The adjoint method is employed to solve the formulated optimization problem in a cost effective way and the first part of the optimal solution is implemented over the control horizon. This procedure is repeated at the next controller sample time providing the feedback into the optimization. The effectiveness and some key features of the proposed approach are studied for a two turbine test case through simulations.

Walking on a moving surface: energy-optimal walking motions on a shaky bridge and a shaking treadmill can reduce energy costs below normal.

PubMed

Joshi, Varun; Srinivasan, Manoj

2015-02-08

Understanding how humans walk on a surface that can move might provide insights into, for instance, whether walking humans prioritize energy use or stability. Here, motivated by the famous human-driven oscillations observed in the London Millennium Bridge, we introduce a minimal mathematical model of a biped, walking on a platform (bridge or treadmill) capable of lateral movement. This biped model consists of a point-mass upper body with legs that can exert force and perform mechanical work on the upper body. Using numerical optimization, we obtain energy-optimal walking motions for this biped, deriving the periodic body and platform motions that minimize a simple metabolic energy cost. When the platform has an externally imposed sinusoidal displacement of appropriate frequency and amplitude, we predict that body motion entrained to platform motion consumes less energy than walking on a fixed surface. When the platform has finite inertia, a mass- spring-damper with similar parameters to the Millennium Bridge, we show that the optimal biped walking motion sustains a large lateral platform oscillation when sufficiently many people walk on the bridge. Here, the biped model reduces walking metabolic cost by storing and recovering energy from the platform, demonstrating energy benefits for two features observed for walking on the Millennium Bridge: crowd synchrony and large lateral oscillations.

Walking on a moving surface: energy-optimal walking motions on a shaky bridge and a shaking treadmill can reduce energy costs below normal

PubMed Central

Joshi, Varun; Srinivasan, Manoj

2015-01-01

Understanding how humans walk on a surface that can move might provide insights into, for instance, whether walking humans prioritize energy use or stability. Here, motivated by the famous human-driven oscillations observed in the London Millennium Bridge, we introduce a minimal mathematical model of a biped, walking on a platform (bridge or treadmill) capable of lateral movement. This biped model consists of a point-mass upper body with legs that can exert force and perform mechanical work on the upper body. Using numerical optimization, we obtain energy-optimal walking motions for this biped, deriving the periodic body and platform motions that minimize a simple metabolic energy cost. When the platform has an externally imposed sinusoidal displacement of appropriate frequency and amplitude, we predict that body motion entrained to platform motion consumes less energy than walking on a fixed surface. When the platform has finite inertia, a mass- spring-damper with similar parameters to the Millennium Bridge, we show that the optimal biped walking motion sustains a large lateral platform oscillation when sufficiently many people walk on the bridge. Here, the biped model reduces walking metabolic cost by storing and recovering energy from the platform, demonstrating energy benefits for two features observed for walking on the Millennium Bridge: crowd synchrony and large lateral oscillations. PMID:25663810

Analysis and optimization of population annealing

NASA Astrophysics Data System (ADS)

Amey, Christopher; Machta, Jonathan

2018-03-01

Population annealing is an easily parallelizable sequential Monte Carlo algorithm that is well suited for simulating the equilibrium properties of systems with rough free-energy landscapes. In this work we seek to understand and improve the performance of population annealing. We derive several useful relations between quantities that describe the performance of population annealing and use these relations to suggest methods to optimize the algorithm. These optimization methods were tested by performing large-scale simulations of the three-dimensional (3D) Edwards-Anderson (Ising) spin glass and measuring several observables. The optimization methods were found to substantially decrease the amount of computational work necessary as compared to previously used, unoptimized versions of population annealing. We also obtain more accurate values of several important observables for the 3D Edwards-Anderson model.

Performance of an Optimally Tuned Range-Separated Hybrid Functional for 0-0 Electronic Excitation Energies.

PubMed

Jacquemin, Denis; Moore, Barry; Planchat, Aurélien; Adamo, Carlo; Autschbach, Jochen

2014-04-08

Using a set of 40 conjugated molecules, we assess the performance of an "optimally tuned" range-separated hybrid functional in reproducing the experimental 0-0 energies. The selected protocol accounts for the impact of solvation using a corrected linear-response continuum approach and vibrational corrections through calculations of the zero-point energies of both ground and excited-states and provides basis set converged data thanks to the systematic use of diffuse-containing atomic basis sets at all computational steps. It turns out that an optimally tuned long-range corrected hybrid form of the Perdew-Burke-Ernzerhof functional, LC-PBE*, delivers both the smallest mean absolute error (0.20 eV) and standard deviation (0.15 eV) of all tested approaches, while the obtained correlation (0.93) is large but remains slightly smaller than its M06-2X counterpart (0.95). In addition, the efficiency of two other recently developed exchange-correlation functionals, namely SOGGA11-X and ωB97X-D, has been determined in order to allow more complete comparisons with previously published data.

Validating Savings Claims of Cold Climate Zero Energy Ready Homes

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

Williamson, J.; Puttagunta, S.

This study was intended to validate actual performance of three ZERHs in the Northeast to energy models created in REM/Rate v14.5 (one of the certified software programs used to generate a HERS Index) and the National Renewable Energy Laboratory’s Building Energy Optimization (BEopt™) v2.3 E+ (a more sophisticated hourly energy simulation software). This report details the validation methods used to analyze energy consumption at each home.

Adiabatic quantum optimization for associative memory recall

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

Seddiqi, Hadayat; Humble, Travis S.

Hopfield networks are a variant of associative memory that recall patterns stored in the couplings of an Ising model. Stored memories are conventionally accessed as fixed points in the network dynamics that correspond to energetic minima of the spin state. We show that memories stored in a Hopfield network may also be recalled by energy minimization using adiabatic quantum optimization (AQO). Numerical simulations of the underlying quantum dynamics allow us to quantify AQO recall accuracy with respect to the number of stored memories and noise in the input key. We investigate AQO performance with respect to how memories are storedmore » in the Ising model according to different learning rules. Our results demonstrate that AQO recall accuracy varies strongly with learning rule, a behavior that is attributed to differences in energy landscapes. Consequently, learning rules offer a family of methods for programming adiabatic quantum optimization that we expect to be useful for characterizing AQO performance.« less

Adiabatic Quantum Optimization for Associative Memory Recall

NASA Astrophysics Data System (ADS)

Seddiqi, Hadayat; Humble, Travis

2014-12-01

Hopfield networks are a variant of associative memory that recall patterns stored in the couplings of an Ising model. Stored memories are conventionally accessed as fixed points in the network dynamics that correspond to energetic minima of the spin state. We show that memories stored in a Hopfield network may also be recalled by energy minimization using adiabatic quantum optimization (AQO). Numerical simulations of the underlying quantum dynamics allow us to quantify AQO recall accuracy with respect to the number of stored memories and noise in the input key. We investigate AQO performance with respect to how memories are stored in the Ising model according to different learning rules. Our results demonstrate that AQO recall accuracy varies strongly with learning rule, a behavior that is attributed to differences in energy landscapes. Consequently, learning rules offer a family of methods for programming adiabatic quantum optimization that we expect to be useful for characterizing AQO performance.

Adiabatic quantum optimization for associative memory recall

DOE PAGES

Seddiqi, Hadayat; Humble, Travis S.

2014-12-22

Hopfield networks are a variant of associative memory that recall patterns stored in the couplings of an Ising model. Stored memories are conventionally accessed as fixed points in the network dynamics that correspond to energetic minima of the spin state. We show that memories stored in a Hopfield network may also be recalled by energy minimization using adiabatic quantum optimization (AQO). Numerical simulations of the underlying quantum dynamics allow us to quantify AQO recall accuracy with respect to the number of stored memories and noise in the input key. We investigate AQO performance with respect to how memories are storedmore » in the Ising model according to different learning rules. Our results demonstrate that AQO recall accuracy varies strongly with learning rule, a behavior that is attributed to differences in energy landscapes. Consequently, learning rules offer a family of methods for programming adiabatic quantum optimization that we expect to be useful for characterizing AQO performance.« less

Using ant colony optimization on the quadratic assignment problem to achieve low energy cost in geo-distributed data centers

NASA Astrophysics Data System (ADS)

Osei, Richard

There are many problems associated with operating a data center. Some of these problems include data security, system performance, increasing infrastructure complexity, increasing storage utilization, keeping up with data growth, and increasing energy costs. Energy cost differs by location, and at most locations fluctuates over time. The rising cost of energy makes it harder for data centers to function properly and provide a good quality of service. With reduced energy cost, data centers will have longer lasting servers/equipment, higher availability of resources, better quality of service, a greener environment, and reduced service and software costs for consumers. Some of the ways that data centers have tried to using to reduce energy costs include dynamically switching on and off servers based on the number of users and some predefined conditions, the use of environmental monitoring sensors, and the use of dynamic voltage and frequency scaling (DVFS), which enables processors to run at different combinations of frequencies with voltages to reduce energy cost. This thesis presents another method by which energy cost at data centers could be reduced. This method involves the use of Ant Colony Optimization (ACO) on a Quadratic Assignment Problem (QAP) in assigning user request to servers in geo-distributed data centers. In this paper, an effort to reduce data center energy cost involves the use of front portals, which handle users' requests, were used as ants to find cost effective ways to assign users requests to a server in heterogeneous geo-distributed data centers. The simulation results indicate that the ACO for Optimal Server Activation and Task Placement algorithm reduces energy cost on a small and large number of users' requests in a geo-distributed data center and its performance increases as the input data grows. In a simulation with 3 geo-distributed data centers, and user's resource request ranging from 25,000 to 25,000,000, the ACO algorithm was able to reduce energy cost on an average of $.70 per second. The ACO for Optimal Server Activation and Task Placement algorithm has proven to work as an alternative or improvement in reducing energy cost in geo-distributed data centers.

Energy Technology Allocation for Distributed Energy Resources: A Technology-Policy Framework

NASA Astrophysics Data System (ADS)

Mallikarjun, Sreekanth

Distributed energy resources (DER) are emerging rapidly. New engineering technologies, materials, and designs improve the performance and extend the range of locations for DER. In contrast, constructing new or modernizing existing high voltage transmission lines for centralized generation are expensive and challenging. In addition, customer demand for reliability has increased and concerns about climate change have created a pull for swift renewable energy penetration. In this context, DER policy makers, developers, and users are interested in determining which energy technologies to use to accommodate different end-use energy demands. We present a two-stage multi-objective strategic technology-policy framework for determining the optimal energy technology allocation for DER. The framework simultaneously considers economic, technical, and environmental objectives. The first stage utilizes a Data Envelopment Analysis model for each end-use to evaluate the performance of each energy technology based on the three objectives. The second stage incorporates factor efficiencies determined in the first stage, capacity limitations, dispatchability, and renewable penetration for each technology, and demand for each end-use into a bottleneck multi-criteria decision model which provides the Pareto-optimal energy resource allocation. We conduct several case studies to understand the roles of various distributed energy technologies in different scenarios. We construct some policy implications based on the model results of set of case studies.

ASSESSMENT OF A WIND TURBINE INTELLIGENT CONTROLLER FOR ENHANCED ENERGY PRODUCTION AND POLLUTION REDUCTION

EPA Science Inventory

This study assessed the enhanced energy production which is possible when variable-speed wind turbines are electronically controlled by an intelligent controller for efficiency optimization and performance improvement. The control system consists of three fuzzy- logic controllers...

High-energy, high-average-power laser with Nd:YLF rods corrected by magnetorheological finishing.

PubMed

Bagnoud, Vincent; Guardalben, Mark J; Puth, Jason; Zuegel, Jonathan D; Mooney, Ted; Dumas, Paul

2005-01-10

A high-energy, high-average-power laser system, optimized to efficiently pump a high-performance optical parametric chirped-pulse amplifier at 527 nm, has been demonstrated. The crystal large-aperture ring amplifier employs two flash-lamp-pumped, 25.4-mm-diameter Nd:YLF rods. The transmitted wave front of these rods is corrected by magnetorheological finishing to achieve nearly diffraction-limited output performance with frequency-doubled pulse energies up to 1.8 J at 5 Hz.

DOE Zero Energy Ready Home Case Study: United Way of Long Island, United Veterans Beacon House

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

Pacific Northwest National Laboratory

United Way of Long Island’s Housing Development Corporation built this 3,719-ft2 two–story, 5-bedroom home in Huntington Station, New York, to the rigorous performance requirements of the U.S. Department of Energy’s Zero Energy Ready Home Program. The home is packed with high-performance features like LED lighting and ENERGY STAR appliances. The asymmetrical, optimally angled roof provides plenty of space for roof-mounted solar panels for electric generation and hot water.

Aerodynamic performance of conventional and advanced design labyrinth seals with solid-smooth abradable, and honeycomb lands. [gas turbine engines

NASA Technical Reports Server (NTRS)

Stocker, H. L.; Cox, D. M.; Holle, G. F.

1977-01-01

Labyrinth air seal static and dynamic performance was evaluated using solid, abradable, and honeycomb lands with standard and advanced seal designs. The effects on leakage of land surface roughness, abradable land porosity, rub grooves in abradable lands, and honeycomb land cell size and depth were studied using a standard labyrinth seal. The effects of rotation on the optimum seal knife pitch were also investigated. Selected geometric and aerodynamic parameters for an advanced seal design were evaluated to derive an optimized performance configuration. The rotational energy requirements were also measured to determine the inherent friction and pumping energy absorbed by the various seal knife and land configurations tested in order to properly assess the net seal system performance level. Results indicate that: (1) seal leakage can be significantly affected with honeycomb or abradable lands; (2) rotational energy absorption does not vary significantly with the use of a solid-smooth, an abradable, or a honeycomb land; and (3) optimization of an advanced lab seal design produced a configuration that had leakage 25% below a conventional stepped seal.

Energy Aware Cluster-Based Routing in Flying Ad-Hoc Networks.

PubMed

Aadil, Farhan; Raza, Ali; Khan, Muhammad Fahad; Maqsood, Muazzam; Mehmood, Irfan; Rho, Seungmin

2018-05-03

Flying ad-hoc networks (FANETs) are a very vibrant research area nowadays. They have many military and civil applications. Limited battery energy and the high mobility of micro unmanned aerial vehicles (UAVs) represent their two main problems, i.e., short flight time and inefficient routing. In this paper, we try to address both of these problems by means of efficient clustering. First, we adjust the transmission power of the UAVs by anticipating their operational requirements. Optimal transmission range will have minimum packet loss ratio (PLR) and better link quality, which ultimately save the energy consumed during communication. Second, we use a variant of the K-Means Density clustering algorithm for selection of cluster heads. Optimal cluster heads enhance the cluster lifetime and reduce the routing overhead. The proposed model outperforms the state of the art artificial intelligence techniques such as Ant Colony Optimization-based clustering algorithm and Grey Wolf Optimization-based clustering algorithm. The performance of the proposed algorithm is evaluated in term of number of clusters, cluster building time, cluster lifetime and energy consumption.

Protein Folding Free Energy Landscape along the Committor - the Optimal Folding Coordinate.

PubMed

Krivov, Sergei V

2018-06-06

Recent advances in simulation and experiment have led to dramatic increases in the quantity and complexity of produced data, which makes the development of automated analysis tools very important. A powerful approach to analyze dynamics contained in such data sets is to describe/approximate it by diffusion on a free energy landscape - free energy as a function of reaction coordinates (RC). For the description to be quantitatively accurate, RCs should be chosen in an optimal way. Recent theoretical results show that such an optimal RC exists; however, determining it for practical systems is a very difficult unsolved problem. Here we describe a solution to this problem. We describe an adaptive nonparametric approach to accurately determine the optimal RC (the committor) for an equilibrium trajectory of a realistic system. In contrast to alternative approaches, which require a functional form with many parameters to approximate an RC and thus extensive expertise with the system, the suggested approach is nonparametric and can approximate any RC with high accuracy without system specific information. To avoid overfitting for a realistically sampled system, the approach performs RC optimization in an adaptive manner by focusing optimization on less optimized spatiotemporal regions of the RC. The power of the approach is illustrated on a long equilibrium atomistic folding simulation of HP35 protein. We have determined the optimal folding RC - the committor, which was confirmed by passing a stringent committor validation test. It allowed us to determine a first quantitatively accurate protein folding free energy landscape. We have confirmed the recent theoretical results that diffusion on such a free energy profile can be used to compute exactly the equilibrium flux, the mean first passage times, and the mean transition path times between any two points on the profile. We have shown that the mean squared displacement along the optimal RC grows linear with time as for simple diffusion. The free energy profile allowed us to obtain a direct rigorous estimate of the pre-exponential factor for the folding dynamics.

Inert gas ion thruster development

NASA Technical Reports Server (NTRS)

Ramsey, W. D.

1980-01-01

Two 12 cm magneto-electrostatic containment (MESC) ion thrusters were performance mapped with argon and xenon. The first, hexagonal, thruster produced optimized performance of 48.5to 79 percent argon mass utilization efficiencies at discharge energies of 240 to 425 eV/ion, respectively, Xenon mass utilization efficiencies of 78 to 95 percent were observed at discharge energies of 220 to 290 eV/ion with the same optimized hexagonal thruster. Changes to the cathode baffle reduced the discharge anode potential during xenon operation from approximately 40 volts to about 30 volts. Preliminary tests conducted with the second, hemispherical, MESC thruster showed a nonuniform anode magnetic field adversely affected thruster performance. This performance degradation was partially overcome by changes in the boundary anode placement. Conclusions drawn the hemispherical thruster tests gave insights into the plasma processes in the MESC discharge that will aid in the design of future thrusters.

Amber Plug-In for Protein Shop

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

Oliva, Ricardo

2004-05-10

The Amber Plug-in for ProteinShop has two main components: an AmberEngine library to compute the protein energy models, and a module to solve the energy minimization problem using an optimization algorithm in the OPTI-+ library. Together, these components allow the visualization of the protein folding process in ProteinShop. AmberEngine is a object-oriented library to compute molecular energies based on the Amber model. The main class is called ProteinEnergy. Its main interface methods are (1) "init" to initialize internal variables needed to compute the energy. (2) "eval" to evaluate the total energy given a vector of coordinates. Additional methods allow themore » user to evaluate the individual components of the energy model (bond, angle, dihedral, non-bonded-1-4, and non-bonded energies) and to obtain the energy of each individual atom. The Amber Engine library source code includes examples and test routines that illustrate the use of the library in stand alone programs. The energy minimization module uses the AmberEngine library and the nonlinear optimization library OPT++. OPT++ is open source software available under the GNU Lesser General Public License. The minimization module currently makes use of the LBFGS optimization algorithm in OPT++ to perform the energy minimization. Future releases may give the user a choice of other algorithms available in OPT++.« less

Robust energy harvesting from walking vibrations by means of nonlinear cantilever beams

NASA Astrophysics Data System (ADS)

Kluger, Jocelyn M.; Sapsis, Themistoklis P.; Slocum, Alexander H.

2015-04-01

In the present work we examine how mechanical nonlinearity can be appropriately utilized to achieve strong robustness of performance in an energy harvesting setting. More specifically, for energy harvesting applications, a great challenge is the uncertain character of the excitation. The combination of this uncertainty with the narrow range of good performance for linear oscillators creates the need for more robust designs that adapt to a wider range of excitation signals. A typical application of this kind is energy harvesting from walking vibrations. Depending on the particular characteristics of the person that walks as well as on the pace of walking, the excitation signal obtains completely different forms. In the present work we study a nonlinear spring mechanism that is composed of a cantilever wrapping around a curved surface as it deflects. While for the free cantilever, the force acting on the free tip depends linearly on the tip displacement, the utilization of a contact surface with the appropriate distribution of curvature leads to essentially nonlinear dependence between the tip displacement and the acting force. The studied nonlinear mechanism has favorable mechanical properties such as low frictional losses, minimal moving parts, and a rugged design that can withstand excessive loads. Through numerical simulations we illustrate that by utilizing this essentially nonlinear element in a 2 degrees-of-freedom (DOF) system, we obtain strongly nonlinear energy transfers between the modes of the system. We illustrate that this nonlinear behavior is associated with strong robustness over three radically different excitation signals that correspond to different walking paces. To validate the strong robustness properties of the 2DOF nonlinear system, we perform a direct parameter optimization for 1DOF and 2DOF linear systems as well as for a class of 1DOF and 2DOF systems with nonlinear springs similar to that of the cubic spring that are physically realized by the cantilever-surface mechanism. The optimization results show that the 2DOF nonlinear system presents the best average performance when the excitation signals have three possible forms. Moreover, we observe that while for the linear systems the optimal performance is obtained for small values of the electromagnetic damping, for the 2DOF nonlinear system optimal performance is achieved for large values of damping. This feature is of particular importance for the system's robustness to parasitic damping.

Optimization control of LNG regasification plant using Model Predictive Control

NASA Astrophysics Data System (ADS)

Wahid, A.; Adicandra, F. F.

2018-03-01

Optimization of liquified natural gas (LNG) regasification plant is important to minimize costs, especially operational costs. Therefore, it is important to choose optimum LNG regasification plant design and maintaining the optimum operating conditions through the implementation of model predictive control (MPC). Optimal tuning parameter for MPC such as P (prediction horizon), M (control of the horizon) and T (sampling time) are achieved by using fine-tuning method. The optimal criterion for design is the minimum amount of energy used and for control is integral of square error (ISE). As a result, the optimum design is scheme 2 which is developed by Devold with an energy savings of 40%. To maintain the optimum conditions, required MPC with P, M and T as follows: tank storage pressure: 90, 2, 1; product pressure: 95, 2, 1; temperature vaporizer: 65, 2, 2; and temperature heater: 35, 6, 5, with ISE value at set point tracking respectively 0.99, 1792.78, 34.89 and 7.54, or improvement of control performance respectively 4.6%, 63.5%, 3.1% and 58.2% compared to PI controller performance. The energy savings that MPC controllers can make when there is a disturbance in temperature rise 1°C of sea water is 0.02 MW.

Agreement Technologies for Energy Optimization at Home

PubMed Central

2018-01-01

Nowadays, it is becoming increasingly common to deploy sensors in public buildings or homes with the aim of obtaining data from the environment and taking decisions that help to save energy. Many of the current state-of-the-art systems make decisions considering solely the environmental factors that cause the consumption of energy. These systems are successful at optimizing energy consumption; however, they do not adapt to the preferences of users and their comfort. Any system that is to be used by end-users should consider factors that affect their wellbeing. Thus, this article proposes an energy-saving system, which apart from considering the environmental conditions also adapts to the preferences of inhabitants. The architecture is based on a Multi-Agent System (MAS), its agents use Agreement Technologies (AT) to perform a negotiation process between the comfort preferences of the users and the degree of optimization that the system can achieve according to these preferences. A case study was conducted in an office building, showing that the proposed system achieved average energy savings of 17.15%. PMID:29783768

Energy efficiency analysis and optimization for mobile platforms

NASA Astrophysics Data System (ADS)

Metri, Grace Camille

The introduction of mobile devices changed the landscape of computing. Gradually, these devices are replacing traditional personal computer (PCs) to become the devices of choice for entertainment, connectivity, and productivity. There are currently at least 45.5 million people in the United States who own a mobile device, and that number is expected to increase to 1.5 billion by 2015. Users of mobile devices expect and mandate that their mobile devices have maximized performance while consuming minimal possible power. However, due to the battery size constraints, the amount of energy stored in these devices is limited and is only growing by 5% annually. As a result, we focused in this dissertation on energy efficiency analysis and optimization for mobile platforms. We specifically developed SoftPowerMon, a tool that can power profile Android platforms in order to expose the power consumption behavior of the CPU. We also performed an extensive set of case studies in order to determine energy inefficiencies of mobile applications. Through our case studies, we were able to propose optimization techniques in order to increase the energy efficiency of mobile devices and proposed guidelines for energy-efficient application development. In addition, we developed BatteryExtender, an adaptive user-guided tool for power management of mobile devices. The tool enables users to extend battery life on demand for a specific duration until a particular task is completed. Moreover, we examined the power consumption of System-on-Chips (SoCs) and observed the impact on the energy efficiency in the event of offloading tasks from the CPU to the specialized custom engines. Based on our case studies, we were able to demonstrate that current software-based power profiling techniques for SoCs can have an error rate close to 12%, which needs to be addressed in order to be able to optimize the energy consumption of the SoC. Finally, we summarize our contributions and outline possible direction for future research in this field.

Cost-performance analysis of nutrient removal in a full-scale oxidation ditch process based on kinetic modeling.

PubMed

Li, Zheng; Qi, Rong; Wang, Bo; Zou, Zhe; Wei, Guohong; Yang, Min

2013-01-01

A full-scale oxidation ditch process for treating sewage was simulated with the ASM2d model and optimized for minimal cost with acceptable performance in terms of ammonium and phosphorus removal. A unified index was introduced by integrating operational costs (aeration energy and sludge production) with effluent violations for performance evaluation. Scenario analysis showed that, in comparison with the baseline (all of the 9 aerators activated), the strategy of activating 5 aerators could save aeration energy significantly with an ammonium violation below 10%. Sludge discharge scenario analysis showed that a sludge discharge flow of 250-300 m3/day (solid retention time (SRT), 13-15 days) was appropriate for the enhancement of phosphorus removal without excessive sludge production. The proposed optimal control strategy was: activating 5 rotating disks operated with a mode of "111100100" ("1" represents activation and "0" represents inactivation) for aeration and sludge discharge flow of 200 m3/day (SRT, 19 days). Compared with the baseline, this strategy could achieve ammonium violation below 10% and TP violation below 30% with substantial reduction of aeration energy cost (46%) and minimal increment of sludge production (< 2%). This study provides a useful approach for the optimization of process operation and control.

Co-Optimization of Fuels and Engines

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

Farrell, John

2016-04-11

The Co-Optimization of Fuels and Engines (Co-Optima) initiative is a new DOE initiative focused on accelerating the introduction of affordable, scalable, and sustainable biofuels and high-efficiency, low-emission vehicle engines. The simultaneous fuels and vehicles research and development (R&D) are designed to deliver maximum energy savings, emissions reduction, and on-road vehicle performance. The initiative's integrated approach combines the previously independent areas of biofuels and combustion R&D, bringing together two DOE Office of Energy Efficiency & Renewable Energy research offices, ten national laboratories, and numerous industry and academic partners to simultaneously tackle fuel and engine research and development (R&D) to maximize energymore » savings and on-road vehicle performance while dramatically reducing transportation-related petroleum consumption and greenhouse gas (GHG) emissions. This multi-year project will provide industry with the scientific underpinnings required to move new biofuels and advanced engine systems to market faster while identifying and addressing barriers to their commercialization. This project's ambitious, first-of-its-kind approach simultaneously tackles fuel and engine innovation to co-optimize performance of both elements and provide dramatic and rapid cuts in fuel use and emissions. This presentation provides an overview of the initiative and reviews recent progress focused on both advanced spark-ignition and compression-ignition approaches.« less

Virtual sensors for active noise control in acoustic-structural coupled enclosures using structural sensing: part II--Optimization of structural sensor placement.

PubMed

Halim, Dunant; Cheng, Li; Su, Zhongqing

2011-04-01

The work proposed an optimization approach for structural sensor placement to improve the performance of vibro-acoustic virtual sensor for active noise control applications. The vibro-acoustic virtual sensor was designed to estimate the interior sound pressure of an acoustic-structural coupled enclosure using structural sensors. A spectral-spatial performance metric was proposed, which was used to quantify the averaged structural sensor output energy of a vibro-acoustic system excited by a spatially varying point source. It was shown that (i) the overall virtual sensing error energy was contributed additively by the modal virtual sensing error and the measurement noise energy; (ii) each of the modal virtual sensing error system was contributed by both the modal observability levels for the structural sensing and the target acoustic virtual sensing; and further (iii) the strength of each modal observability level was influenced by the modal coupling and resonance frequencies of the associated uncoupled structural/cavity modes. An optimal design of structural sensor placement was proposed to achieve sufficiently high modal observability levels for certain important panel- and cavity-controlled modes. Numerical analysis on a panel-cavity system demonstrated the importance of structural sensor placement on virtual sensing and active noise control performance, particularly for cavity-controlled modes.

Optimization of the level and range of working temperature of the PCM in the gypsum-microencapsulated PCM thermal energy storage unit for summer conditions in Central Poland

NASA Astrophysics Data System (ADS)

Łapka, P.; Jaworski, M.

2017-10-01

In this paper thermal energy storage (TES) unit in a form of a ceiling panel made of gypsum-microencapsulated PCM composite with internal U-shaped channels was considered and optimal characteristics of the microencapsulated PCM were determined. This panel may be easily incorporated into, e.g., an office or residential ventilation system in order to reduce daily variations of air temperature during the summer without additional costs related to the consumption of energy for preparing air parameters to the desired level. For the purpose of the analysis of heat transfer in the panel, a novel numerical simulator was developed. The numerical model consists of two coupled parts, i.e., the 1D which deals with the air flowing through the U-shaped channel and the 3D which deals with heat transfer in the body of the panel. The computational tool was validated based on the experimental study performed on the special set-up. Using this tool an optimization of parameters of the gypsum-microencapsulated PCM composite was performed in order to determine its most appropriate properties for the application under study. The analyses were performed for averaged local summer conditions in Warsaw, Poland.

The application of simulation modeling to the cost and performance ranking of solar thermal power plants

NASA Technical Reports Server (NTRS)

Rosenberg, L. S.; Revere, W. R.; Selcuk, M. K.

1981-01-01

Small solar thermal power systems (up to 10 MWe in size) were tested. The solar thermal power plant ranking study was performed to aid in experiment activity and support decisions for the selection of the most appropriate technological approach. The cost and performance were determined for insolation conditions by utilizing the Solar Energy Simulation computer code (SESII). This model optimizes the size of the collector field and energy storage subsystem for given engine generator and energy transport characteristics. The development of the simulation tool, its operation, and the results achieved from the analysis are discussed.

Performance outcomes and unwanted side effects associated with energy drinks.

PubMed

Mora-Rodriguez, Ricardo; Pallarés, Jesús G

2014-10-01

Energy drinks are increasingly popular among athletes and others. Advertising for these products typically features images conjuring great muscle power and endurance; however, the scientific literature provides sparse evidence for an ergogenic role of energy drinks. Although the composition of energy drinks varies, most contain caffeine; carbohydrates, amino acids, herbs, and vitamins are other typical ingredients. This report analyzes the effects of energy drink ingredients on prolonged submaximal (endurance) exercise as well as on short-term strength and power (neuromuscular performance). It also analyzes the effects of energy drink ingredients on the fluid and electrolyte deficit during prolonged exercise. In several studies, energy drinks have been found to improve endurance performance, although the effects could be attributable to the caffeine and/or carbohydrate content. In contrast, fewer studies find an ergogenic effect of energy drinks on muscle strength and power. The existing data suggest that the caffeine dose given in studies of energy drinks is insufficient to enhance neuromuscular performance. Finally, it is unclear if energy drinks are the optimal vehicle to deliver caffeine when high doses are needed to improve neuromuscular performance. © 2014 International Life Sciences Institute.

Optimized MPPT-based converter for TEG energy harvester to power wireless sensor and monitoring system in nuclear power plant

NASA Astrophysics Data System (ADS)

Xing, Shaoxu; Anakok, Isil; Zuo, Lei

2017-04-01

Accidents like Fukushima Disasters push people to improve the monitoring systems for the nuclear power plants. Thus, various types of energy harvesters are designed to power these systems and the Thermoelectric Generator (TEG) energy harvester is one of them. In order to enhance the amount of harvested power and the system efficiency, the power management stage needs to be carefully designed. In this paper, a power converter with optimized Maximum Power Point Tracking (MPPT) is proposed for the TEG Energy Harvester to power the wireless sensor network in nuclear power plant. The TEG Energy Harvester is installed on the coolant pipe of the nuclear plant and harvests energy from its heat energy while the power converter with optimized MPPT can make the TEG Energy Harvester output the maximum power, quickly response to the voltage change and provide sufficient energy for wireless sensor system to monitor the operation of the nuclear power plant. Due to the special characteristics of the Single-Ended Primary Inductor Converter (SEPIC) when it is working in the Discontinuous Inductor Current Mode (DICM) and Continuous Conduction Mode (CCM), the MPPT method presented in this paper would be able to control the converter to achieve the maximum output power in any working conditions of the TEG system with a simple circuit. The optimized MPPT algorithm will significantly reduce the cost and simplify the system as well as achieve a good performance. Experiment test results have shown that, comparing to a fixed- duty-cycle SEPIC which is specifically designed for the working on the secondary coolant loop in nuclear power plant, the optimized MPPT algorithm increased the output power by 55%.

Ab Initio Assessment of the Thermoelectric Performance of Ruthenium-Doped Gadolinium Orthotantalate

NASA Technical Reports Server (NTRS)

Goldsby, Jon

2016-01-01

Solid state energy harvesting using waste heat available in gas turbine engine, offers potential for power generation to meet growing power needs of aircraft. Thermoelectric material advances offer new opportunities. Weight-optimized integrated turbine engine structure incorporating energy conversion devices.

Energy Efficiency Optimization in Relay-Assisted MIMO Systems With Perfect and Statistical CSI

NASA Astrophysics Data System (ADS)

Zappone, Alessio; Cao, Pan; Jorswieck, Eduard A.

2014-01-01

A framework for energy-efficient resource allocation in a single-user, amplify-and-forward relay-assisted MIMO system is devised in this paper. Previous results in this area have focused on rate maximization or sum power minimization problems, whereas fewer results are available when bits/Joule energy efficiency (EE) optimization is the goal. The performance metric to optimize is the ratio between the system's achievable rate and the total consumed power. The optimization is carried out with respect to the source and relay precoding matrices, subject to QoS and power constraints. Such a challenging non-convex problem is tackled by means of fractional programming and and alternating maximization algorithms, for various CSI assumptions at the source and relay. In particular the scenarios of perfect CSI and those of statistical CSI for either the source-relay or the relay-destination channel are addressed. Moreover, sufficient conditions for beamforming optimality are derived, which is useful in simplifying the system design. Numerical results are provided to corroborate the validity of the theoretical findings.

Evaluation and optimization of footwear comfort parameters using finite element analysis and a discrete optimization algorithm

NASA Astrophysics Data System (ADS)

Papagiannis, P.; Azariadis, P.; Papanikos, P.

2017-10-01

Footwear is subject to bending and torsion deformations that affect comfort perception. Following review of Finite Element Analysis studies of sole rigidity and comfort, a three-dimensional, linear multi-material finite element sole model for quasi-static bending and torsion simulation, overcoming boundary and optimisation limitations, is described. Common footwear materials properties and boundary conditions from gait biomechanics are used. The use of normalised strain energy for product benchmarking is demonstrated along with comfort level determination through strain energy density stratification. Sensitivity of strain energy against material thickness is greater for bending than for torsion, with results of both deformations showing positive correlation. Optimization for a targeted performance level and given layer thickness is demonstrated with bending simulations sufficing for overall comfort assessment. An algorithm for comfort optimization w.r.t. bending is presented, based on a discrete approach with thickness values set in line with practical manufacturing accuracy. This work illustrates the potential of the developed finite element analysis applications to offer viable and proven aids to modern footwear sole design assessment and optimization.

Self-adaptive multimethod optimization applied to a tailored heating forging process

NASA Astrophysics Data System (ADS)

Baldan, M.; Steinberg, T.; Baake, E.

2018-05-01

The presented paper describes an innovative self-adaptive multi-objective optimization code. Investigation goals concern proving the superiority of this code compared to NGSA-II and applying it to an inductor’s design case study addressed to a “tailored” heating forging application. The choice of the frequency and the heating time are followed by the determination of the turns number and their positions. Finally, a straightforward optimization is performed in order to minimize energy consumption using “optimal control”.

Energy Efficiency and Performance Limiting Effects in Thermo-Osmotic Energy Conversion from Low-Grade Heat.

PubMed

Straub, Anthony P; Elimelech, Menachem

2017-11-07

Low-grade heat energy from sources below 100 °C is available in massive quantities around the world, but cannot be converted to electricity effectively using existing technologies due to variability in the heat output and the small temperature difference between the source and environment. The recently developed thermo-osmotic energy conversion (TOEC) process has the potential to harvest energy from low-grade heat sources by using a temperature difference to create a pressurized liquid flux across a membrane, which can be converted to mechanical work via a turbine. In this study, we perform the first analysis of energy efficiency and the expected performance of the TOEC technology, focusing on systems utilizing hydrophobic porous vapor-gap membranes and water as a working fluid. We begin by developing a framework to analyze realistic mass and heat transport in the process, probing the impact of various membrane parameters and system operating conditions. Our analysis reveals that an optimized system can achieve heat-to-electricity energy conversion efficiencies up to 4.1% (34% of the Carnot efficiency) with hot and cold working temperatures of 60 and 20 °C, respectively, and an operating pressure of 5 MPa (50 bar). Lower energy efficiencies, however, will occur in systems operating with high power densities (>5 W/m 2 ) and with finite-sized heat exchangers. We identify that the most important membrane properties for achieving high performance are an asymmetric pore structure, high pressure resistance, a high porosity, and a thickness of 30 to 100 μm. We also quantify the benefits in performance from utilizing deaerated water streams, strong hydrodynamic mixing in the membrane module, and high heat exchanger efficiencies. Overall, our study demonstrates the promise of full-scale TOEC systems to extract energy from low-grade heat and identifies key factors for performance optimization moving forward.

SU-F-T-193: Evaluation of a GPU-Based Fast Monte Carlo Code for Proton Therapy Biological Optimization

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

Taleei, R; Qin, N; Jiang, S

2016-06-15

Purpose: Biological treatment plan optimization is of great interest for proton therapy. It requires extensive Monte Carlo (MC) simulations to compute physical dose and biological quantities. Recently, a gPMC package was developed for rapid MC dose calculations on a GPU platform. This work investigated its suitability for proton therapy biological optimization in terms of accuracy and efficiency. Methods: We performed simulations of a proton pencil beam with energies of 75, 150 and 225 MeV in a homogeneous water phantom using gPMC and FLUKA. Physical dose and energy spectra for each ion type on the central beam axis were scored. Relativemore » Biological Effectiveness (RBE) was calculated using repair-misrepair-fixation model. Microdosimetry calculations were performed using Monte Carlo Damage Simulation (MCDS). Results: Ranges computed by the two codes agreed within 1 mm. Physical dose difference was less than 2.5 % at the Bragg peak. RBE-weighted dose agreed within 5 % at the Bragg peak. Differences in microdosimetric quantities such as dose average lineal energy transfer and specific energy were < 10%. The simulation time per source particle with FLUKA was 0.0018 sec, while gPMC was ∼ 600 times faster. Conclusion: Physical dose computed by FLUKA and gPMC were in a good agreement. The RBE differences along the central axis were small, and RBE-weighted dose difference was found to be acceptable. The combined accuracy and efficiency makes gPMC suitable for proton therapy biological optimization.« less

Optimal control of energy extraction in LES of large wind farms

NASA Astrophysics Data System (ADS)

Meyers, Johan; Goit, Jay; Munters, Wim

2014-11-01

We investigate the use of optimal control combined with Large-Eddy Simulations (LES) of wind-farm boundary layer interaction for the increase of total energy extraction in very large ``infinite'' wind farms and in finite farms. We consider the individual wind turbines as flow actuators, whose energy extraction can be dynamically regulated in time so as to optimally influence the turbulent flow field, maximizing the wind farm power. For the simulation of wind-farm boundary layers we use large-eddy simulations in combination with an actuator-disk representation of wind turbines. Simulations are performed in our in-house pseudo-spectral code SP-Wind. For the optimal control study, we consider the dynamic control of turbine-thrust coefficients in the actuator-disk model. They represent the effect of turbine blades that can actively pitch in time, changing the lift- and drag coefficients of the turbine blades. In a first infinite wind-farm case, we find that farm power is increases by approximately 16% over one hour of operation. This comes at the cost of a deceleration of the outer layer of the boundary layer. A detailed analysis of energy balances is presented, and a comparison is made between infinite and finite farm cases, for which boundary layer entrainment plays an import role. The authors acknowledge support from the European Research Council (FP7-Ideas, Grant No. 306471). Simulations were performed on the computing infrastructure of the VSC Flemish Supercomputer Center, funded by the Hercules Foundation and the Flemish Govern.

A transmission power optimization with a minimum node degree for energy-efficient wireless sensor networks with full-reachability.

PubMed

Chen, Yi-Ting; Horng, Mong-Fong; Lo, Chih-Cheng; Chu, Shu-Chuan; Pan, Jeng-Shyang; Liao, Bin-Yih

2013-03-20

Transmission power optimization is the most significant factor in prolonging the lifetime and maintaining the connection quality of wireless sensor networks. Un-optimized transmission power of nodes either interferes with or fails to link neighboring nodes. The optimization of transmission power depends on the expected node degree and node distribution. In this study, an optimization approach to an energy-efficient and full reachability wireless sensor network is proposed. In the proposed approach, an adjustment model of the transmission range with a minimum node degree is proposed that focuses on topology control and optimization of the transmission range according to node degree and node density. The model adjusts the tradeoff between energy efficiency and full reachability to obtain an ideal transmission range. In addition, connectivity and reachability are used as performance indices to evaluate the connection quality of a network. The two indices are compared to demonstrate the practicability of framework through simulation results. Furthermore, the relationship between the indices under the conditions of various node degrees is analyzed to generalize the characteristics of node densities. The research results on the reliability and feasibility of the proposed approach will benefit the future real deployments.

A Transmission Power Optimization with a Minimum Node Degree for Energy-Efficient Wireless Sensor Networks with Full-Reachability

PubMed Central

Chen, Yi-Ting; Horng, Mong-Fong; Lo, Chih-Cheng; Chu, Shu-Chuan; Pan, Jeng-Shyang; Liao, Bin-Yih

2013-01-01

Transmission power optimization is the most significant factor in prolonging the lifetime and maintaining the connection quality of wireless sensor networks. Un-optimized transmission power of nodes either interferes with or fails to link neighboring nodes. The optimization of transmission power depends on the expected node degree and node distribution. In this study, an optimization approach to an energy-efficient and full reachability wireless sensor network is proposed. In the proposed approach, an adjustment model of the transmission range with a minimum node degree is proposed that focuses on topology control and optimization of the transmission range according to node degree and node density. The model adjusts the tradeoff between energy efficiency and full reachability to obtain an ideal transmission range. In addition, connectivity and reachability are used as performance indices to evaluate the connection quality of a network. The two indices are compared to demonstrate the practicability of framework through simulation results. Furthermore, the relationship between the indices under the conditions of various node degrees is analyzed to generalize the characteristics of node densities. The research results on the reliability and feasibility of the proposed approach will benefit the future real deployments. PMID:23519351

Discrete Particle Swarm Optimization Routing Protocol for Wireless Sensor Networks with Multiple Mobile Sinks.

PubMed

Yang, Jin; Liu, Fagui; Cao, Jianneng; Wang, Liangming

2016-07-14

Mobile sinks can achieve load-balancing and energy-consumption balancing across the wireless sensor networks (WSNs). However, the frequent change of the paths between source nodes and the sinks caused by sink mobility introduces significant overhead in terms of energy and packet delays. To enhance network performance of WSNs with mobile sinks (MWSNs), we present an efficient routing strategy, which is formulated as an optimization problem and employs the particle swarm optimization algorithm (PSO) to build the optimal routing paths. However, the conventional PSO is insufficient to solve discrete routing optimization problems. Therefore, a novel greedy discrete particle swarm optimization with memory (GMDPSO) is put forward to address this problem. In the GMDPSO, particle's position and velocity of traditional PSO are redefined under discrete MWSNs scenario. Particle updating rule is also reconsidered based on the subnetwork topology of MWSNs. Besides, by improving the greedy forwarding routing, a greedy search strategy is designed to drive particles to find a better position quickly. Furthermore, searching history is memorized to accelerate convergence. Simulation results demonstrate that our new protocol significantly improves the robustness and adapts to rapid topological changes with multiple mobile sinks, while efficiently reducing the communication overhead and the energy consumption.

A new approach on the upgrade of energetic system based on green energy. A complex comparative analysis of the EEDI and EEOI

NASA Astrophysics Data System (ADS)

Faitar, C.; Novac, I.

2016-08-01

In recent years, many environmental organizations was interested to optimize the energy consumption which has become, today, one of the main concerns to the whole world. From this point of view, the maritime industry, has strove to optimize the fuel consumption of ship through the development of engines and propulsion system, improve the hull design, or using alternative energies, this way making a reduction in the amount of CO2 released to the atmosphere. The main idea of this paper is to realize a complex comparative analysis of Energy Efficiency Design Index and Energy Efficiency Operational Indicator which are calculated in two cases: first, in a classical approach for a crude oil super tanker ship and second, after the energy performance of this ship has been improved by introducing alternative energy sources on board.

Evaluating the transport layer of the ALFA framework for the Intel® Xeon Phi™ Coprocessor

NASA Astrophysics Data System (ADS)

Santogidis, Aram; Hirstius, Andreas; Lalis, Spyros

2015-12-01

The ALFA framework supports the software development of major High Energy Physics experiments. As part of our research effort to optimize the transport layer of ALFA, we focus on profiling its data transfer performance for inter-node communication on the Intel Xeon Phi Coprocessor. In this article we present the collected performance measurements with the related analysis of the results. The optimization opportunities that are discovered, help us to formulate the future plans of enabling high performance data transfer for ALFA on the Intel Xeon Phi architecture.

Ascent trajectory optimization for stratospheric airship with thermal effects

NASA Astrophysics Data System (ADS)

Guo, Xiao; Zhu, Ming

2013-09-01

Ascent trajectory optimization with thermal effects is addressed for a stratospheric airship. Basic thermal characteristics of the stratospheric airship are introduced. Besides, the airship’s equations of motion are constructed by including the factors about aerodynamic force, added mass and wind profiles which are developed based on horizontal-wind model. For both minimum-time and minimum-energy flights during ascent, the trajectory optimization problem is described with the path and terminal constraints in different scenarios and then, is converted into a parameter optimization problem by a direct collocation method. Sparse Nonlinear OPTimizer(SNOPT) is employed as a nonlinear programming solver and two scenarios are adopted. The solutions obtained illustrate that the trajectories are greatly affected by the thermal behaviors which prolong the daytime minimum-time flights of about 20.8% compared with that of nighttime in scenario 1 and of about 10.5% in scenario 2. And there is the same trend for minimum-energy flights. For the energy consumption of minimum-time flights, 6% decrease is abstained in scenario 1 and 5% decrease in scenario 2. However, a few energy consumption reduction is achieved for minimum-energy flights. Solar radiation is the principal component and the natural wind also affects the thermal behaviors of stratospheric airship during ascent. The relationship between take-off time and performance of airship during ascent is discussed. it is found that the take-off time at dusk is best choice for stratospheric airship. And in addition, for saving energy, airship prefers to fly downwind.

Contrast-enhanced spectral mammography with a photon-counting detector.

PubMed

Fredenberg, Erik; Hemmendorff, Magnus; Cederström, Björn; Aslund, Magnus; Danielsson, Mats

2010-05-01

Spectral imaging is a method in medical x-ray imaging to extract information about the object constituents by the material-specific energy dependence of x-ray attenuation. The authors have investigated a photon-counting spectral imaging system with two energy bins for contrast-enhanced mammography. System optimization and the potential benefit compared to conventional non-energy-resolved absorption imaging was studied. A framework for system characterization was set up that included quantum and anatomical noise and a theoretical model of the system was benchmarked to phantom measurements. Optimal combination of the energy-resolved images corresponded approximately to minimization of the anatomical noise, which is commonly referred to as energy subtraction. In that case, an ideal-observer detectability index could be improved close to 50% compared to absorption imaging in the phantom study. Optimization with respect to the signal-to-quantum-noise ratio, commonly referred to as energy weighting, yielded only a minute improvement. In a simulation of a clinically more realistic case, spectral imaging was predicted to perform approximately 30% better than absorption imaging for an average glandularity breast with an average level of anatomical noise. For dense breast tissue and a high level of anatomical noise, however, a rise in detectability by a factor of 6 was predicted. Another approximately 70%-90% improvement was found to be within reach for an optimized system. Contrast-enhanced spectral mammography is feasible and beneficial with the current system, and there is room for additional improvements. Inclusion of anatomical noise is essential for optimizing spectral imaging systems.

High energy density in PVDF nanocomposites using an optimized nanowire array.

PubMed

Guo, Ru; Luo, Hang; Liu, Weiwei; Zhou, Xuefan; Tang, Lin; Zhou, Kechao; Zhang, Dou

2018-06-22

TiO2 nanowire arrays are often utilized to prepare high performance polymer nanocomposites, however, the contribution to the energy density is limited due to their non-ferroelectric characteristics. A nanocomposite with an optimized nanowire array combining the ferroelectric properties of lead zirconate titanate (PZT) with TiO2, readily forming nanowires (denoted as a TiO2-P nanowire array), is prepared to enhance the permittivity. Poly(vinylidene fluoride) (PVDF) is used as the polymer matrix due to its high breakdown strength, e.g. 600-700 kV mm-1. As a result, the permittivity and breakdown electric field reach 53 at 1 kHz and 550 kV mm-1, respectively. Therefore, the nanocomposites achieve a higher discharge energy density of 12.4 J cm-3 with excellent cycle stability, which is the highest among nanocomposites based on a nanowire array as a filler in a PVDF matrix. This work provides not only a feasible approach to obtain high performance dielectric nanocomposites, but also a wide range of potential applications in the energy storage and energy harvesting fields.

Optimization of constrained density functional theory

NASA Astrophysics Data System (ADS)

O'Regan, David D.; Teobaldi, Gilberto

2016-07-01

Constrained density functional theory (cDFT) is a versatile electronic structure method that enables ground-state calculations to be performed subject to physical constraints. It thereby broadens their applicability and utility. Automated Lagrange multiplier optimization is necessary for multiple constraints to be applied efficiently in cDFT, for it to be used in tandem with geometry optimization, or with molecular dynamics. In order to facilitate this, we comprehensively develop the connection between cDFT energy derivatives and response functions, providing a rigorous assessment of the uniqueness and character of cDFT stationary points while accounting for electronic interactions and screening. In particular, we provide a nonperturbative proof that stable stationary points of linear density constraints occur only at energy maxima with respect to their Lagrange multipliers. We show that multiple solutions, hysteresis, and energy discontinuities may occur in cDFT. Expressions are derived, in terms of convenient by-products of cDFT optimization, for quantities such as the dielectric function and a condition number quantifying ill definition in multiple constraint cDFT.

Designing train-speed trajectory with energy efficiency and service quality

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-06-01

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

On optimization of energy harvesting from base-excited vibration

NASA Astrophysics Data System (ADS)

Tai, Wei-Che; Zuo, Lei

2017-12-01

This paper re-examines and clarifies the long-believed optimization conditions of electromagnetic and piezoelectric energy harvesting from base-excited vibration. In terms of electromagnetic energy harvesting, it is typically believed that the maximum power is achieved when the excitation frequency and electrical damping equal the natural frequency and mechanical damping of the mechanical system respectively. We will show that this optimization condition is only valid when the acceleration amplitude of base excitation is constant and an approximation for small mechanical damping when the excitation displacement amplitude is constant. To this end, a two-variable optimization analysis, involving the normalized excitation frequency and electrical damping ratio, is performed to derive the exact optimization condition of each case. When the excitation displacement amplitude is constant, we analytically show that, in contrast to the long-believed optimization condition, the optimal excitation frequency and electrical damping are always larger than the natural frequency and mechanical damping ratio respectively. In particular, when the mechanical damping ratio exceeds a critical value, the optimization condition is no longer valid. Instead, the average power generally increases as the excitation frequency and electrical damping ratio increase. Furthermore, the optimization analysis is extended to consider parasitic electrical losses, which also shows different results when compared with existing literature. When the excitation acceleration amplitude is constant, on the other hand, the exact optimization condition is identical to the long-believed one. In terms of piezoelectric energy harvesting, it is commonly believed that the optimal power efficiency is achieved when the excitation and the short or open circuit frequency of the harvester are equal. Via a similar two-variable optimization analysis, we analytically show that the optimal excitation frequency depends on the mechanical damping ratio and does not equal the short or open circuit frequency. Finally, the optimal excitation frequencies and resistive loads are derived in closed-form.

Ultra Low Energy Binary Decision Diagram Circuits Using Few Electron Transistors

NASA Astrophysics Data System (ADS)

Saripalli, Vinay; Narayanan, Vijay; Datta, Suman

Novel medical applications involving embedded sensors, require ultra low energy dissipation with low-to-moderate performance (10kHz-100MHz) driving the conventional MOSFETs into sub-threshold operation regime. In this paper, we present an alternate ultra-low power computing architecture using Binary Decision Diagram based logic circuits implemented using Single Electron Transistors (SETs) operating in the Coulomb blockade regime with very low supply voltages. We evaluate the energy - performance tradeoff metrics of such BDD circuits using time domain Monte Carlo simulations and compare them with the energy-optimized CMOS logic circuits. Simulation results show that the proposed approach achieves better energy-delay characteristics than CMOS realizations.

Application of GA, PSO, and ACO algorithms to path planning of autonomous underwater vehicles

NASA Astrophysics Data System (ADS)

Aghababa, Mohammad Pourmahmood; Amrollahi, Mohammad Hossein; Borjkhani, Mehdi

2012-09-01

In this paper, an underwater vehicle was modeled with six dimensional nonlinear equations of motion, controlled by DC motors in all degrees of freedom. Near-optimal trajectories in an energetic environment for underwater vehicles were computed using a numerical solution of a nonlinear optimal control problem (NOCP). An energy performance index as a cost function, which should be minimized, was defined. The resulting problem was a two-point boundary value problem (TPBVP). A genetic algorithm (GA), particle swarm optimization (PSO), and ant colony optimization (ACO) algorithms were applied to solve the resulting TPBVP. Applying an Euler-Lagrange equation to the NOCP, a conjugate gradient penalty method was also adopted to solve the TPBVP. The problem of energetic environments, involving some energy sources, was discussed. Some near-optimal paths were found using a GA, PSO, and ACO algorithms. Finally, the problem of collision avoidance in an energetic environment was also taken into account.

Optimality Principles for Model-Based Prediction of Human Gait

PubMed Central

Ackermann, Marko; van den Bogert, Antonie J.

2010-01-01

Although humans have a large repertoire of potential movements, gait patterns tend to be stereotypical and appear to be selected according to optimality principles such as minimal energy. When applied to dynamic musculoskeletal models such optimality principles might be used to predict how a patient’s gait adapts to mechanical interventions such as prosthetic devices or surgery. In this paper we study the effects of different performance criteria on predicted gait patterns using a 2D musculoskeletal model. The associated optimal control problem for a family of different cost functions was solved utilizing the direct collocation method. It was found that fatigue-like cost functions produced realistic gait, with stance phase knee flexion, as opposed to energy-related cost functions which avoided knee flexion during the stance phase. We conclude that fatigue minimization may be one of the primary optimality principles governing human gait. PMID:20074736

Use of principle velocity patterns in the analysis of structural acoustic optimization.

PubMed

Johnson, Wayne M; Cunefare, Kenneth A

2007-02-01

This work presents an application of principle velocity patterns in the analysis of the structural acoustic design optimization of an eight ply composite cylindrical shell. The approach consists of performing structural acoustic optimizations of a composite cylindrical shell subject to external harmonic monopole excitation. The ply angles are used as the design variables in the optimization. The results of the ply angle design variable formulation are interpreted using the singular value decomposition of the interior acoustic potential energy. The decomposition of the acoustic potential energy provides surface velocity patterns associated with lower levels of interior noise. These surface velocity patterns are shown to correspond to those from the structural acoustic optimization results. Thus, it is demonstrated that the capacity to design multi-ply composite cylinders for quiet interiors is determined by how well the cylinder be can designed to exhibit particular surface velocity patterns associated with lower noise levels.

The improvement of thermal characteristics of autoclave aerated concrete for energy efficient high-rise buildings application

NASA Astrophysics Data System (ADS)

Khavanov, Pavel; Fomina, Ekaterina; Kozhukhova, Natalia

2018-03-01

Nowadays, the problem of energy saving is very relevant. One of the ways to reduction energy consumption in construction materials production and construction of civil and industrial high-rise buildings is the application of claddings with heat-insulating performance. The concept of energy efficiency of high-rise buildings is closely related to environmental aspect and sustainability of applied construction materials; reducing service costs; energy saving and microclimate comfortability. A complexity of architectural and structural design as well as aesthetic characteristics of construction materials are also should be considered. The high interest focused on materials with combined properties. This work is oriented on the study of energy efficiency of buildings by improving heat-insulation and strength performance of autoclave aerated concrete. The applied method of sulfate activation of lime allows monitoring phase and structure formation in aerated concrete. The optimal mix design of aerated concrete with the compressive strength up to 8.5 MPa and decreased density up to 760 kg/m3 was proposed. Analysis of structure at macro-and microscale was performed as well as the criteria of an optimal porosity formation was considered a number, size, shape of pore and density of interior partition. SEM analysis and BET method were performed in this research work. The research results demonstrated the correlation between structure and vapor permeability resistance, also it was found that the increase of strength can lead to reduction of thermal conductivity.

ePave: A Self-Powered Wireless Sensor for Smart and Autonomous Pavement.

PubMed

Xiao, Jian; Zou, Xiang; Xu, Wenyao

2017-09-26

"Smart Pavement" is an emerging infrastructure for various on-road applications in transportation and road engineering. However, existing road monitoring solutions demand a certain periodic maintenance effort due to battery life limits in the sensor systems. To this end, we present an end-to-end self-powered wireless sensor-ePave-to facilitate smart and autonomous pavements. The ePave system includes a self-power module, an ultra-low-power sensor system, a wireless transmission module and a built-in power management module. First, we performed an empirical study to characterize the piezoelectric module in order to optimize energy-harvesting efficiency. Second, we developed an integrated sensor system with the optimized energy harvester. An adaptive power knob is designated to adjust the power consumption according to energy budgeting. Finally, we intensively evaluated the ePave system in real-world applications to examine the system's performance and explore the trade-off.

The Next Breakthrough for Organic Photovoltaics?

PubMed

Jackson, Nicholas E; Savoie, Brett M; Marks, Tobin J; Chen, Lin X; Ratner, Mark A

2015-01-02

While the intense focus on energy level tuning in organic photovoltaic materials has afforded large gains in device performance, we argue here that strategies based on microstructural/morphological control are at least as promising in any rational design strategy. In this work, a meta-analysis of ∼150 bulk heterojunction devices fabricated with different materials combinations is performed and reveals strong correlations between power conversion efficiency and morphology-dominated properties (short-circuit current, fill factor) and surprisingly weak correlations between efficiency and energy level positioning (open-circuit voltage, enthalpic offset at the interface, optical gap). While energy level positioning should in principle provide the theoretical maximum efficiency, the optimization landscape that must be navigated to reach this maximum is unforgiving. Thus, research aimed at developing understanding-based strategies for more efficient optimization of an active layer microstructure and morphology are likely to be at least as fruitful.

ePave: A Self-Powered Wireless Sensor for Smart and Autonomous Pavement

PubMed Central

Xiao, Jian; Zou, Xiang

2017-01-01

“Smart Pavement” is an emerging infrastructure for various on-road applications in transportation and road engineering. However, existing road monitoring solutions demand a certain periodic maintenance effort due to battery life limits in the sensor systems. To this end, we present an end-to-end self-powered wireless sensor—ePave—to facilitate smart and autonomous pavements. The ePave system includes a self-power module, an ultra-low-power sensor system, a wireless transmission module and a built-in power management module. First, we performed an empirical study to characterize the piezoelectric module in order to optimize energy-harvesting efficiency. Second, we developed an integrated sensor system with the optimized energy harvester. An adaptive power knob is designated to adjust the power consumption according to energy budgeting. Finally, we intensively evaluated the ePave system in real-world applications to examine the system’s performance and explore the trade-off. PMID:28954430

Energy neutral and low power wireless communications

NASA Astrophysics Data System (ADS)

Orhan, Oner

Wireless sensor nodes are typically designed to have low cost and small size. These design objectives impose restrictions on the capacity and efficiency of the transceiver components and energy storage units that can be used. As a result, energy becomes a bottleneck and continuous operation of the sensor network requires frequent battery replacements, increasing the maintenance cost. Energy harvesting and energy efficient transceiver architectures are able to overcome these challenges by collecting energy from the environment and utilizing the energy in an intelligent manner. However, due to the nature of the ambient energy sources, the amount of useful energy that can be harvested is limited and unreliable. Consequently, optimal management of the harvested energy and design of low power transceivers pose new challenges for wireless network design and operation. The first part of this dissertation is on energy neutral wireless networking, where optimal transmission schemes under different system setups and objectives are investigated. First, throughput maximization for energy harvesting two-hop networks with decode-and-forward half-duplex relays is studied. For a system with two parallel relays, various combinations of the following four transmission modes are considered: Broadcast from the source, multi-access from the relays, and successive relaying phases I and II. Next, the energy cost of the processing circuitry as well as the transmission energy are taken into account for communication over a broadband fading channel powered by an energy harvesting transmitter. Under this setup, throughput maximization, energy maximization, and transmission completion time minimization problems are studied. Finally, source and channel coding for an energy-limited wireless sensor node is investigated under various energy constraints including energy harvesting, processing and sampling costs. For each objective, optimal transmission policies are formulated as the solutions of a convex optimization problem, and the properties of these optimal policies are identified. In the second part of this thesis, low power transceiver design is considered for millimeter wave communication systems. In particular, using an additive quantization noise model, the effect of analog-digital conversion (ADC) resolution and bandwidth on the achievable rate is investigated for a multi-antenna system under a receiver power constraint. Two receiver architectures, analog and digital combining, are compared in terms of performance.

Development of GEM detector for plasma diagnostics application: simulations addressing optimization of its performance

NASA Astrophysics Data System (ADS)

Chernyshova, M.; Malinowski, K.; Kowalska-Strzęciwilk, E.; Czarski, T.; Linczuk, P.; Wojeński, A.; Krawczyk, R. D.

2017-12-01

The advanced Soft X-ray (SXR) diagnostics setup devoted to studies of the SXR plasma emissivity is at the moment a highly relevant and important for ITER/DEMO application. Especially focusing on the energy range of tungsten emission lines, as plasma contamination by W and its transport in the plasma must be understood and monitored for W plasma-facing material. The Gas Electron Multiplier, with a spatial and energy-resolved photon detecting chamber, based SXR radiation detection system under development by our group may become such a diagnostic setup considering and solving many physical, technical and technological aspects. This work presents the results of simulations aimed to optimize a design of the detector's internal chamber and its performance. The study of the effect of electrodes alignment allowed choosing the gap distances which maximizes electron transmission and choosing the optimal magnitudes of the applied electric fields. Finally, the optimal readout structure design was identified suitable to collect a total formed charge effectively, basing on the range of the simulated electron cloud at the readout plane which was in the order of ~ 2 mm.

A study of the optimal transition temperature of PCM (phase change material) wallboard for solar energy storage

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

Drake, J.B.

1987-09-01

In this report, we consider the performance of wallboard impregnated with phase change material. An ideal setting is assumed and several measures of performance discussed. With a definition of optimal performance given, the performance with respect to variation of transition temperature is studied. Results are based on computer simulations of PCM wallboard with a standard stud wall construction. We find the diurnal heat capacity to be overly sensitive to numerical errors for use in PCM applications. The other measures of performance, diurnal effectiveness, net collected to storage ratio, and absolute discharge flux, all indicate similar trends. It is shown thatmore » the optimal transition temperature of the PCM is strongly influenced by amount of solar flux absorbed by the PCM. 6 refs., 5 figs., 5 tabs.« less

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

NASA Astrophysics Data System (ADS)

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

2015-09-01

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

Optimal Control of Distributed Energy Resources using Model Predictive Control

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

Mayhorn, Ebony T.; Kalsi, Karanjit; Elizondo, Marcelo A.

2012-07-22

In an isolated power system (rural microgrid), Distributed Energy Resources (DERs) such as renewable energy resources (wind, solar), energy storage and demand response can be used to complement fossil fueled generators. The uncertainty and variability due to high penetration of wind makes reliable system operations and controls challenging. In this paper, an optimal control strategy is proposed to coordinate energy storage and diesel generators to maximize wind penetration while maintaining system economics and normal operation. The problem is formulated as a multi-objective optimization problem with the goals of minimizing fuel costs and changes in power output of diesel generators, minimizingmore » costs associated with low battery life of energy storage and maintaining system frequency at the nominal operating value. Two control modes are considered for controlling the energy storage to compensate either net load variability or wind variability. Model predictive control (MPC) is used to solve the aforementioned problem and the performance is compared to an open-loop look-ahead dispatch problem. Simulation studies using high and low wind profiles, as well as, different MPC prediction horizons demonstrate the efficacy of the closed-loop MPC in compensating for uncertainties in wind and demand.« less

Design optimization of PVDF-based piezoelectric energy harvesters.

PubMed

Song, Jundong; Zhao, Guanxing; Li, Bo; Wang, Jin

2017-09-01

Energy harvesting is a promising technology that powers the electronic devices via scavenging the ambient energy. Piezoelectric energy harvesters have attracted considerable interest for their high conversion efficiency and easy fabrication in minimized sensors and transducers. To improve the output capability of energy harvesters, properties of piezoelectric materials is an influential factor, but the potential of the material is less likely to be fully exploited without an optimized configuration. In this paper, an optimization strategy for PVDF-based cantilever-type energy harvesters is proposed to achieve the highest output power density with the given frequency and acceleration of the vibration source. It is shown that the maximum power output density only depends on the maximum allowable stress of the beam and the working frequency of the device, and these two factors can be obtained by adjusting the geometry of piezoelectric layers. The strategy is validated by coupled finite-element-circuit simulation and a practical device. The fabricated device within a volume of 13.1 mm 3 shows an output power of 112.8 μW which is comparable to that of the best-performing piezoceramic-based energy harvesters within the similar volume reported so far.

Structural Optimization of Triboelectric Nanogenerator for Harvesting Water Wave Energy.

PubMed

Jiang, Tao; Zhang, Li Min; Chen, Xiangyu; Han, Chang Bao; Tang, Wei; Zhang, Chi; Xu, Liang; Wang, Zhong Lin

2015-12-22

Ocean waves are one of the most abundant energy sources on earth, but harvesting such energy is rather challenging due to various limitations of current technologies. Recently, networks formed by triboelectric nanogenerator (TENG) have been proposed as a promising technology for harvesting water wave energy. In this work, a basic unit for the TENG network was studied and optimized, which has a box structure composed of walls made of TENG composed of a wavy-structured Cu-Kapton-Cu film and two FEP thin films, with a metal ball enclosed inside. By combination of the theoretical calculations and experimental studies, the output performances of the TENG unit were investigated for various structural parameters, such as the size, mass, or number of the metal balls. From the viewpoint of theory, the output characteristics of TENG during its collision with the ball were numerically calculated by the finite element method and interpolation method, and there exists an optimum ball size or mass to reach maximized output power and electric energy. Moreover, the theoretical results were well verified by the experimental tests. The present work could provide guidance for structural optimization of wavy-structured TENGs for effectively harvesting water wave energy toward the dream of large-scale blue energy.

Spectral optimization for micro-CT.

PubMed

Hupfer, Martin; Nowak, Tristan; Brauweiler, Robert; Eisa, Fabian; Kalender, Willi A

2012-06-01

To optimize micro-CT protocols with respect to x-ray spectra and thereby reduce radiation dose at unimpaired image quality. Simulations were performed to assess image contrast, noise, and radiation dose for different imaging tasks. The figure of merit used to determine the optimal spectrum was the dose-weighted contrast-to-noise ratio (CNRD). Both optimal photon energy and tube voltage were considered. Three different types of filtration were investigated for polychromatic x-ray spectra: 0.5 mm Al, 3.0 mm Al, and 0.2 mm Cu. Phantoms consisted of water cylinders of 20, 32, and 50 mm in diameter with a central insert of 9 mm which was filled with different contrast materials: an iodine-based contrast medium (CM) to mimic contrast-enhanced (CE) imaging, hydroxyapatite to mimic bone structures, and water with reduced density to mimic soft tissue contrast. Validation measurements were conducted on a commercially available micro-CT scanner using phantoms consisting of water-equivalent plastics. Measurements on a mouse cadaver were performed to assess potential artifacts like beam hardening and to further validate simulation results. The optimal photon energy for CE imaging was found at 34 keV. For bone imaging, optimal energies were 17, 20, and 23 keV for the 20, 32, and 50 mm phantom, respectively. For density differences, optimal energies varied between 18 and 50 keV for the 20 and 50 mm phantom, respectively. For the 32 mm phantom and density differences, CNRD was found to be constant within 2.5% for the energy range of 21-60 keV. For polychromatic spectra and CMs, optimal settings were 50 kV with 0.2 mm Cu filtration, allowing for a dose reduction of 58% compared to the optimal setting for 0.5 mm Al filtration. For bone imaging, optimal tube voltages were below 35 kV. For soft tissue imaging, optimal tube settings strongly depended on phantom size. For 20 mm, low voltages were preferred. For 32 mm, CNRD was found to be almost independent of tube voltage. For 50 mm, voltages larger than 50 kV were preferred. For all three phantom sizes stronger filtration led to notable dose reduction for soft tissue imaging. Validation measurements were found to match simulations well, with deviations being less than 10%. Mouse measurements confirmed simulation results. Optimal photon energies and tube settings strongly depend on both phantom size and imaging task at hand. For in vivo CE imaging and density differences, strong filtration and voltages of 50-65 kV showed good overall results. For soft tissue imaging of animals the size of a rat or larger, voltages higher than 65 kV allow to greatly reduce scan times while maintaining dose efficiency. For imaging of bone structures, usage of only minimum filtration and low tube voltages of 40 kV and below allow exploiting the high contrast of bone at very low energies. Therefore, a combination of two filtrations could prove beneficial for micro-CT: a soft filtration allowing for bone imaging at low voltages, and a variable stronger filtration (e.g., 0.2 mm Cu) for soft tissue and contrast-enhanced imaging. © 2012 American Association of Physicists in Medicine.

Design of Supercapacitor Electrodes Using Molecular Dynamics Simulations

NASA Astrophysics Data System (ADS)

Bo, Zheng; Li, Changwen; Yang, Huachao; Ostrikov, Kostya; Yan, Jianhua; Cen, Kefa

2018-06-01

Electric double-layer capacitors (EDLCs) are advanced electrochemical devices for energy storage and have attracted strong interest due to their outstanding properties. Rational optimization of electrode-electrolyte interactions is of vital importance to enhance device performance for practical applications. Molecular dynamics (MD) simulations could provide theoretical guidelines for the optimal design of electrodes and the improvement of capacitive performances, e.g., energy density and power density. Here we discuss recent MD simulation studies on energy storage performance of electrode materials containing porous to nanostructures. The energy storage properties are related to the electrode structures, including electrode geometry and electrode modifications. Altering electrode geometry, i.e., pore size and surface topography, can influence EDL capacitance. We critically examine different types of electrode modifications, such as altering the arrangement of carbon atoms, doping heteroatoms and defects, which can change the quantum capacitance. The enhancement of power density can be achieved by the intensified ion dynamics and shortened ion pathway. Rational control of the electrode morphology helps improve the ion dynamics by decreasing the ion diffusion pathway. Tuning the surface properties (e.g., the affinity between the electrode and the ions) can affect the ion-packing phenomena. Our critical analysis helps enhance the energy and power densities of EDLCs by modulating the corresponding electrode structures and surface properties.[Figure not available: see fulltext.

Optimal energy harvesting from vortex-induced vibrations of cables.

PubMed

Antoine, G O; de Langre, E; Michelin, S

2016-11-01

Vortex-induced vibrations (VIV) of flexible cables are an example of flow-induced vibrations that can act as energy harvesting systems by converting energy associated with the spontaneous cable motion into electricity. This work investigates the optimal positioning of the harvesting devices along the cable, using numerical simulations with a wake oscillator model to describe the unsteady flow forcing. Using classical gradient-based optimization, the optimal harvesting strategy is determined for the generic configuration of a flexible cable fixed at both ends, including the effect of flow forces and gravity on the cable's geometry. The optimal strategy is found to consist systematically in a concentration of the harvesting devices at one of the cable's ends, relying on deformation waves along the cable to carry the energy towards this harvesting site. Furthermore, we show that the performance of systems based on VIV of flexible cables is significantly more robust to flow velocity variations, in comparison with a rigid cylinder device. This results from two passive control mechanisms inherent to the cable geometry: (i) the adaptability to the flow velocity of the fundamental frequencies of cables through the flow-induced tension and (ii) the selection of successive vibration modes by the flow velocity for cables with gravity-induced tension.

Optimal energy harvesting from vortex-induced vibrations of cables

PubMed Central

de Langre, E.; Michelin, S.

2016-01-01

Vortex-induced vibrations (VIV) of flexible cables are an example of flow-induced vibrations that can act as energy harvesting systems by converting energy associated with the spontaneous cable motion into electricity. This work investigates the optimal positioning of the harvesting devices along the cable, using numerical simulations with a wake oscillator model to describe the unsteady flow forcing. Using classical gradient-based optimization, the optimal harvesting strategy is determined for the generic configuration of a flexible cable fixed at both ends, including the effect of flow forces and gravity on the cable’s geometry. The optimal strategy is found to consist systematically in a concentration of the harvesting devices at one of the cable’s ends, relying on deformation waves along the cable to carry the energy towards this harvesting site. Furthermore, we show that the performance of systems based on VIV of flexible cables is significantly more robust to flow velocity variations, in comparison with a rigid cylinder device. This results from two passive control mechanisms inherent to the cable geometry: (i) the adaptability to the flow velocity of the fundamental frequencies of cables through the flow-induced tension and (ii) the selection of successive vibration modes by the flow velocity for cables with gravity-induced tension. PMID:27956880

Optimal energy harvesting from vortex-induced vibrations of cables

NASA Astrophysics Data System (ADS)

Antoine, G. O.; de Langre, E.; Michelin, S.

2016-11-01

Vortex-induced vibrations (VIV) of flexible cables are an example of flow-induced vibrations that can act as energy harvesting systems by converting energy associated with the spontaneous cable motion into electricity. This work investigates the optimal positioning of the harvesting devices along the cable, using numerical simulations with a wake oscillator model to describe the unsteady flow forcing. Using classical gradient-based optimization, the optimal harvesting strategy is determined for the generic configuration of a flexible cable fixed at both ends, including the effect of flow forces and gravity on the cable's geometry. The optimal strategy is found to consist systematically in a concentration of the harvesting devices at one of the cable's ends, relying on deformation waves along the cable to carry the energy towards this harvesting site. Furthermore, we show that the performance of systems based on VIV of flexible cables is significantly more robust to flow velocity variations, in comparison with a rigid cylinder device. This results from two passive control mechanisms inherent to the cable geometry: (i) the adaptability to the flow velocity of the fundamental frequencies of cables through the flow-induced tension and (ii) the selection of successive vibration modes by the flow velocity for cables with gravity-induced tension.

GEANT4 simulations of a novel 3He-free thermalization neutron detector

NASA Astrophysics Data System (ADS)

Mazzone, A.; Finocchiaro, P.; Lo Meo, S.; Colonna, N.

2018-05-01

A novel concept for 3He-free thermalization detector is here investigated by means of GEANT4 simulations. The detector is based on strips of solid-state detectors with 6Li deposit for neutron conversion. Various geometrical configurations have been investigated in order to find the optimal solution, in terms of value and energy dependence of the efficiency for neutron energies up to 10 MeV. The expected performance of the new detector are compared with those of an optimized thermalization detector based on standard 3He tubes. Although an 3He-based detector is superior in terms of performance and simplicity, the proposed solution may become more appealing in terms of costs in case of shortage of 3He supply.

Towards smart energy systems: application of kernel machine regression for medium term electricity load forecasting.

PubMed

Alamaniotis, Miltiadis; Bargiotas, Dimitrios; Tsoukalas, Lefteri H

2016-01-01

Integration of energy systems with information technologies has facilitated the realization of smart energy systems that utilize information to optimize system operation. To that end, crucial in optimizing energy system operation is the accurate, ahead-of-time forecasting of load demand. In particular, load forecasting allows planning of system expansion, and decision making for enhancing system safety and reliability. In this paper, the application of two types of kernel machines for medium term load forecasting (MTLF) is presented and their performance is recorded based on a set of historical electricity load demand data. The two kernel machine models and more specifically Gaussian process regression (GPR) and relevance vector regression (RVR) are utilized for making predictions over future load demand. Both models, i.e., GPR and RVR, are equipped with a Gaussian kernel and are tested on daily predictions for a 30-day-ahead horizon taken from the New England Area. Furthermore, their performance is compared to the ARMA(2,2) model with respect to mean average percentage error and squared correlation coefficient. Results demonstrate the superiority of RVR over the other forecasting models in performing MTLF.

Comparative Analysis of Particle Swarm and Differential Evolution via Tuning on Ultrasmall Titanium Oxide Nanoclusters

NASA Astrophysics Data System (ADS)

Inclan, Eric; Lassester, Jack; Geohegan, David; Yoon, Mina

Optimization algorithms (OA) coupled with numerical methods enable researchers to identify and study (meta) stable nanoclusters without the control restrictions of empirical methods. An algorithm's performance is governed by two factors: (1) its compatibility with an objective function, (2) the dimension of a design space, which increases with cluster size. Although researchers often tune an algorithm's user-defined parameters (UDP), tuning is not guaranteed to improve performance. In this research, Particle Swarm (PSO) and Differential Evolution (DE), are compared by tuning their UDP in a multi-objective optimization environment (MOE). Combined with a Kolmogorov Smirnov test for statistical significance, the MOE enables the study of the Pareto Front (PF), made of the UDP settings that trade-off between best performance in energy minimization (``effectiveness'') based on force-field potential energy, and best convergence rate (``efficiency''). By studying the PF, this research finds that UDP values frequently suggested in the literature do not provide best effectiveness for these methods. Additionally, monotonic convergence is found to significantly improve efficiency without sacrificing effectiveness for very small systems, suggesting better compatibility. Work is supported by the U.S. Department of Energy, Office of Science, Basic Energy Sciences, Materials Sciences and Engineering Division.

Optimal design of a main driving mechanism for servo punch press based on performance atlases

NASA Astrophysics Data System (ADS)

Zhou, Yanhua; Xie, Fugui; Liu, Xinjun

2013-09-01

The servomotor drive turret punch press is attracting more attentions and being developed more intensively due to the advantages of high speed, high accuracy, high flexibility, high productivity, low noise, cleaning and energy saving. To effectively improve the performance and lower the cost, it is necessary to develop new mechanisms and establish corresponding optimal design method with uniform performance indices. A new patented main driving mechanism and a new optimal design method are proposed. In the optimal design, the performance indices, i.e., the local motion/force transmission indices ITI, OTI, good transmission workspace good transmission workspace(GTW) and the global transmission indices GTIs are defined. The non-dimensional normalization method is used to get all feasible solutions in dimensional synthesis. Thereafter, the performance atlases, which can present all possible design solutions, are depicted. As a result, the feasible solution of the mechanism with good motion/force transmission performance is obtained. And the solution can be flexibly adjusted by designer according to the practical design requirements. The proposed mechanism is original, and the presented design method provides a feasible solution to the optimal design of the main driving mechanism for servo punch press.

A New Approach to Design Autonomous Wireless Sensor Node Based on RF Energy Harvesting System.

PubMed

Mouapi, Alex; Hakem, Nadir

2018-01-05

Energy Harvesting techniques are increasingly seen as the solution for freeing the wireless sensor nodes from their battery dependency. However, it remains evident that network performance features, such as network size, packet length, and duty cycle, are influenced by the sum of recovered energy. This paper proposes a new approach to defining the specifications of a stand-alone wireless node based on a Radio-frequency Energy Harvesting System (REHS). To achieve adequate performance regarding the range of the Wireless Sensor Network (WSN), techniques for minimizing the energy consumed by the sensor node are combined with methods for optimizing the performance of the REHS. For more rigor in the design of the autonomous node, a comprehensive energy model of the node in a wireless network is established. For an equitable distribution of network charges between the different nodes that compose it, the Low-Energy Adaptive Clustering Hierarchy (LEACH) protocol is used for this purpose. The model considers five energy-consumption sources, most of which are ignored in recently used models. By using the hardware parameters of commercial off-the-shelf components (Mica2 Motes and CC2520 of Texas Instruments), the energy requirement of a sensor node is quantified. A miniature REHS based on a judicious choice of rectifying diodes is then designed and developed to achieve optimal performance in the Industrial Scientific and Medical (ISM) band centralized at 2.45 GHz . Due to the mismatch between the REHS and the antenna, a band pass filter is designed to reduce reflection losses. A gradient method search is used to optimize the output characteristics of the adapted REHS. At 1 mW of input RF power, the REHS provides an output DC power of 0.57 mW and a comparison with the energy requirement of the node allows the Base Station (BS) to be located at 310 m from the wireless nodes when the Wireless Sensor Network (WSN) has 100 nodes evenly spread over an area of 300 × 300 m 2 and when each round lasts 10 min . The result shows that the range of the autonomous WSN increases when the controlled physical phenomenon varies very slowly. Having taken into account all the dissipation sources coexisting in a sensor node and using actual measurements of an REHS, this work provides the guidelines for the design of autonomous nodes based on REHS.

Component-based integration of chemistry and optimization software.

PubMed

Kenny, Joseph P; Benson, Steven J; Alexeev, Yuri; Sarich, Jason; Janssen, Curtis L; McInnes, Lois Curfman; Krishnan, Manojkumar; Nieplocha, Jarek; Jurrus, Elizabeth; Fahlstrom, Carl; Windus, Theresa L

2004-11-15

Typical scientific software designs make rigid assumptions regarding programming language and data structures, frustrating software interoperability and scientific collaboration. Component-based software engineering is an emerging approach to managing the increasing complexity of scientific software. Component technology facilitates code interoperability and reuse. Through the adoption of methodology and tools developed by the Common Component Architecture Forum, we have developed a component architecture for molecular structure optimization. Using the NWChem and Massively Parallel Quantum Chemistry packages, we have produced chemistry components that provide capacity for energy and energy derivative evaluation. We have constructed geometry optimization applications by integrating the Toolkit for Advanced Optimization, Portable Extensible Toolkit for Scientific Computation, and Global Arrays packages, which provide optimization and linear algebra capabilities. We present a brief overview of the component development process and a description of abstract interfaces for chemical optimizations. The components conforming to these abstract interfaces allow the construction of applications using different chemistry and mathematics packages interchangeably. Initial numerical results for the component software demonstrate good performance, and highlight potential research enabled by this platform.

Study on optimal configuration of the grid-connected wind-solar-battery hybrid power system

NASA Astrophysics Data System (ADS)

Ma, Gang; Xu, Guchao; Ju, Rong; Wu, Tiantian

2017-08-01

The capacity allocation of each energy unit in the grid-connected wind-solar-battery hybrid power system is a significant segment in system design. In this paper, taking power grid dispatching into account, the research priorities are as follows: (1) We establish the mathematic models of each energy unit in the hybrid power system. (2) Based on dispatching of the power grid, energy surplus rate, system energy volatility and total cost, we establish the evaluation system for the wind-solar-battery power system and use a number of different devices as the constraint condition. (3) Based on an improved Genetic algorithm, we put forward a multi-objective optimisation algorithm to solve the optimal configuration problem in the hybrid power system, so we can achieve the high efficiency and economy of the grid-connected hybrid power system. The simulation result shows that the grid-connected wind-solar-battery hybrid power system has a higher comprehensive performance; the method of optimal configuration in this paper is useful and reasonable.

Optimal design of a piezoelectric transducer for exciting guided wave ultrasound in rails

NASA Astrophysics Data System (ADS)

Ramatlo, Dineo A.; Wilke, Daniel N.; Loveday, Philip W.

2017-02-01

An existing Ultrasonic Broken Rail Detection System installed in South Africa on a heavy duty railway line is currently being upgraded to include defect detection and location. To accomplish this, an ultrasonic piezoelectric transducer to strongly excite a guided wave mode with energy concentrated in the web (web mode) of a rail is required. A previous study demonstrated that the recently developed SAFE-3D (Semi-Analytical Finite Element - 3 Dimensional) method can effectively predict the guided waves excited by a resonant piezoelectric transducer. In this study, the SAFE-3D model is used in the design optimization of a rail web transducer. A bound-constrained optimization problem was formulated to maximize the energy transmitted by the transducer in the web mode when driven by a pre-defined excitation signal. Dimensions of the transducer components were selected as the three design variables. A Latin hypercube sampled design of experiments that required a total of 500 SAFE-3D analyses in the design space was employed in a response surface-based optimization approach. The Nelder-Mead optimization algorithm was then used to find an optimal transducer design on the constructed response surface. The radial basis function response surface was first verified by comparing a number of predicted responses against the computed SAFE-3D responses. The performance of the optimal transducer predicted by the optimization algorithm on the response surface was also verified to be sufficiently accurate using SAFE-3D. The computational advantages of SAFE-3D in optimal transducer design are noteworthy as more than 500 analyses were performed. The optimal design was then manufactured and experimental measurements were used to validate the predicted performance. The adopted design method has demonstrated the capability to automate the design of transducers for a particular rail cross-section and frequency range.

Transmission electron microscope CCD camera

DOEpatents

Downing, Kenneth H.

1999-01-01

In order to improve the performance of a CCD camera on a high voltage electron microscope, an electron decelerator is inserted between the microscope column and the CCD. This arrangement optimizes the interaction of the electron beam with the scintillator of the CCD camera while retaining optimization of the microscope optics and of the interaction of the beam with the specimen. Changing the electron beam energy between the specimen and camera allows both to be optimized.

Experimental test of an online ion-optics optimizer

NASA Astrophysics Data System (ADS)

Amthor, A. M.; Schillaci, Z. M.; Morrissey, D. J.; Portillo, M.; Schwarz, S.; Steiner, M.; Sumithrarachchi, Ch.

2018-07-01

A technique has been developed and tested to automatically adjust multiple electrostatic or magnetic multipoles on an ion optical beam line - according to a defined optimization algorithm - until an optimal tune is found. This approach simplifies the process of determining high-performance optical tunes, satisfying a given set of optical properties, for an ion optical system. The optimization approach is based on the particle swarm method and is entirely model independent, thus the success of the optimization does not depend on the accuracy of an extant ion optical model of the system to be optimized. Initial test runs of a first order optimization of a low-energy (<60 keV) all-electrostatic beamline at the NSCL show reliable convergence of nine quadrupole degrees of freedom to well-performing tunes within a reasonable number of trial solutions, roughly 500, with full beam optimization run times of roughly two hours. Improved tunes were found both for quasi-local optimizations and for quasi-global optimizations, indicating a good ability of the optimizer to find a solution with or without a well defined set of initial multipole settings.

Increasing power generation in horizontal axis wind turbines using optimized flow control

NASA Astrophysics Data System (ADS)

Cooney, John A., Jr.

In order to effectively realize future goals for wind energy, the efficiency of wind turbines must increase beyond existing technology. One direct method for achieving increased efficiency is by improving the individual power generation characteristics of horizontal axis wind turbines. The potential for additional improvement by traditional approaches is diminishing rapidly however. As a result, a research program was undertaken to assess the potential of using distributed flow control to increase power generation. The overall objective was the development of validated aerodynamic simulations and flow control approaches to improve wind turbine power generation characteristics. BEM analysis was conducted for a general set of wind turbine models encompassing last, current, and next generation designs. This analysis indicated that rotor lift control applied in Region II of the turbine power curve would produce a notable increase in annual power generated. This was achieved by optimizing induction factors along the rotor blade for maximum power generation. In order to demonstrate this approach and other advanced concepts, the University of Notre Dame established the Laboratory for Enhanced Wind Energy Design (eWiND). This initiative includes a fully instrumented meteorological tower and two pitch-controlled wind turbines. The wind turbines are representative in their design and operation to larger multi-megawatt turbines, but of a scale that allows rotors to be easily instrumented and replaced to explore new design concepts. Baseline data detailing typical site conditions and turbine operation is presented. To realize optimized performance, lift control systems were designed and evaluated in CFD simulations coupled with shape optimization tools. These were integrated into a systematic design methodology involving BEM simulations, CFD simulations and shape optimization, and selected experimental validation. To refine and illustrate the proposed design methodology, a complete design cycle was performed for the turbine model incorporated in the wind energy lab. Enhanced power generation was obtained through passive trailing edge shaping aimed at reaching lift and lift-to-drag goals predicted to optimize performance. These targets were determined by BEM analysis to improve power generation characteristics and annual energy production (AEP) for the wind turbine. A preliminary design was validated in wind tunnel experiments on a 2D rotor section in preparation for testing in the full atmospheric environment of the eWiND Laboratory. These tests were performed for the full-scale geometry and atmospheric conditions. Upon making additional improvements to the shape optimization tools, a series of trailing edge additions were designed to optimize power generation. The trailing edge additions were predicted to increase the AEP by up to 4.2% at the White Field site. The pieces were rapid-prototyped and installed on the wind turbine in March, 2014. Field tests are ongoing.

Optimized Solvent for Energy-Efficient, Environmentally-Friendly Capture of CO{sub 2} at Coal-Fired Power Plants

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

Farthing, G. A.; Rimpf, L. M.

The overall goal of this project, as originally proposed, was to optimize the formulation of a novel solvent as a critical enabler for the cost-effective, energy-efficient, environmentally-friendly capture of CO{sub 2} at coal-fired utility plants. Aqueous blends of concentrated piperazine (PZ) with other compounds had been shown to exhibit high rates of CO{sub 2} absorption, low regeneration energy, and other desirable performance characteristics during an earlier 5-year development program conducted by B&W. The specific objective of this project was to identify PZ-based solvent formulations that globally optimize the performance of coal-fired power plants equipped with CO{sub 2} scrubbing systems. Whilemore » previous solvent development studies have tended to focus on energy consumption and absorber size, important issues to be sure, the current work seeks to explore, understand, and optimize solvent formulation across the full gamut of issues related to commercial application of the technology: capital and operating costs, operability, reliability, environmental, health and safety (EH&S), etc. Work on the project was intended to be performed under four budget periods. The objective of the work in the first budget period has been to identify several candidate formulations of a concentrated PZ-based solvent for detailed characterization and evaluation. Work in the second budget period would generate reliable and comprehensive property and performance data for the identified formulations. Work in the third budget period would quantify the expected performance of the selected formulations in a commercial CO{sub 2} scrubbing process. Finally, work in the fourth budget period would provide a final technology feasibility study and a preliminary technology EH&S assessment. Due to other business priorities, however, B&W has requested that this project be terminated at the end of the first budget period. This document therefore serves as the final report for this project. It is the first volume of the two-volume final report and summarizes Budget Period 1 accomplishments under Tasks 1-5 of the project, including the selection of four solvent formulations for further study.« less

Establishment of key grid-connected performance index system for integrated PV-ES system

NASA Astrophysics Data System (ADS)

Li, Q.; Yuan, X. D.; Qi, Q.; Liu, H. M.

2016-08-01

In order to further promote integrated optimization operation of distributed new energy/ energy storage/ active load, this paper studies the integrated photovoltaic-energy storage (PV-ES) system which is connected with the distribution network, and analyzes typical structure and configuration selection for integrated PV-ES generation system. By combining practical grid- connected characteristics requirements and technology standard specification of photovoltaic generation system, this paper takes full account of energy storage system, and then proposes several new grid-connected performance indexes such as paralleled current sharing characteristic, parallel response consistency, adjusting characteristic, virtual moment of inertia characteristic, on- grid/off-grid switch characteristic, and so on. A comprehensive and feasible grid-connected performance index system is then established to support grid-connected performance testing on integrated PV-ES system.

High-performance slow light photonic crystal waveguides with topology optimized or circular-hole based material layouts

NASA Astrophysics Data System (ADS)

Wang, Fengwen; Jensen, Jakob S.; Sigmund, Ole

2012-10-01

Photonic crystal waveguides are optimized for modal confinement and loss related to slow light with high group index. A detailed comparison between optimized circular-hole based waveguides and optimized waveguides with free topology is performed. Design robustness with respect to manufacturing imperfections is enforced by considering different design realizations generated from under-, standard- and over-etching processes in the optimization procedure. A constraint ensures a certain modal confinement, and loss related to slow light with high group index is indirectly treated by penalizing field energy located in air regions. It is demonstrated that slow light with a group index up to ng = 278 can be achieved by topology optimized waveguides with promising modal confinement and restricted group-velocity-dispersion. All the topology optimized waveguides achieve a normalized group-index bandwidth of 0.48 or above. The comparisons between circular-hole based designs and topology optimized designs illustrate that the former can be efficient for dispersion engineering but that larger improvements are possible if irregular geometries are allowed.

A permanent-magnet rotor for a high-temperature superconducting bearing

NASA Astrophysics Data System (ADS)

Mulcahy, T. M.; Hull, J. R.; Uherka, K. L.; Abboud, R. G.; Wise, J. H.; Carnegie, D. W.

1995-06-01

Design, fabrication, and performance, of a 1/3-m dia., 10-kg flywheel rotor with only one bearing is discussed. To achieve low-loss energy storage, the rotor's segmented-ring permanent-magnet (PM) is optimized for levitation and circumferential homogeneity. The magnet's carbon composite bands enable practical energy storage.

Building Performance Optimization while Empowering Occupants Toward Environmentally Sustainable Behavior through Continuous Monitoring and Diagnostics

DTIC Science & Technology

2016-12-01

investment at the PaANG installation. In compliance with the NIST handbook’s guidelines, the team used the actual energy prices of the buildings...Costing Manual for the Federal Energy Management Program. For example, the team used the actual energy price and the measured energy consumption at the...least 30% of a DOD building’s HVAC and plug load annual energy consumption can be saved through continuous diagnostics and controls, while empowering

Development Of Educational Programs In Renewable And Alternative Energy Processing: The Case Of Russia

NASA Astrophysics Data System (ADS)

Svirina, Anna; Shindor, Olga; Tatmyshevsky, Konstantin

2014-12-01

The paper deals with the main problems of Russian energy system development that proves necessary to provide educational programs in the field of renewable and alternative energy. In the paper the process of curricula development and defining teaching techniques on the basis of expert opinion evaluation is defined, and the competence model for renewable and alternative energy processing master students is suggested. On the basis of a distributed questionnaire and in-depth interviews, the data for statistical analysis was obtained. On the basis of this data, an optimization of curricula structure was performed, and three models of a structure for optimizing teaching techniques were developed. The suggested educational program structure which was adopted by employers is presented in the paper. The findings include quantitatively estimated importance of systemic thinking and professional skills and knowledge as basic competences of a masters' program graduate; statistically estimated necessity of practice-based learning approach; and optimization models for structuring curricula in renewable and alternative energy processing. These findings allow the establishment of a platform for the development of educational programs.

Electric vehicle (EV) storage supply chain risk and the energy market: A micro and macroeconomic risk management approach

NASA Astrophysics Data System (ADS)

Aguilar, Susanna D.

As a cost effective storage technology for renewable energy sources, Electric Vehicles can be integrated into energy grids. Integration must be optimized to ascertain that renewable energy is available through storage when demand exists so that cost of electricity is minimized. Optimization models can address economic risks associated with the EV supply chain- particularly the volatility in availability and cost of critical materials used in the manufacturing of EV motors and batteries. Supply chain risk can reflect itself in a shortage of storage, which can increase the price of electricity. We propose a micro-and macroeconomic framework for managing supply chain risk through utilization of a cost optimization model in combination with risk management strategies at the microeconomic and macroeconomic level. The study demonstrates how risk from the EVs vehicle critical material supply chain affects manufacturers, smart grid performance, and energy markets qualitatively and quantitatively. Our results illustrate how risk in the EV supply chain affects EV availability and the cost of ancillary services, and how EV critical material supply chain risk can be mitigated through managerial strategies and policy.

Investigation on the energy absorption performance of a fixed-bottom pressure-differential wave energy converter

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

Babarit, A.; Wendt, F.; Yu, Y. -H.

2017-04-01

In this article, we investigate the energy absorption performance of a fixed-bottom pressure-differential wave energy converter. Two versions of the technology are considered: one has the moving surfaces on the bottom of the air chambers whereas the other has the moving surfaces on the top. We developed numerical models in the frequency domain, thereby enabling the power absorption of the two versions of the device to be assessed. It is observed that the moving surfaces on the top allow for easier tuning of the natural period of the system. Taking into account stroke limitations, the design is optimized. Results indicatemore » that the pressure-differential wave energy converter is a highly efficient technology both with respect to energy absorption and selected economic performance indicators.« less

On Reliable and Efficient Data Gathering Based Routing in Underwater Wireless Sensor Networks.

PubMed

Liaqat, Tayyaba; Akbar, Mariam; Javaid, Nadeem; Qasim, Umar; Khan, Zahoor Ali; Javaid, Qaisar; Alghamdi, Turki Ali; Niaz, Iftikhar Azim

2016-08-30

This paper presents cooperative routing scheme to improve data reliability. The proposed protocol achieves its objective, however, at the cost of surplus energy consumption. Thus sink mobility is introduced to minimize the energy consumption cost of nodes as it directly collects data from the network nodes at minimized communication distance. We also present delay and energy optimized versions of our proposed RE-AEDG to further enhance its performance. Simulation results prove the effectiveness of our proposed RE-AEDG in terms of the selected performance matrics.

Development & optimization of a rule-based energy management strategy for fuel economy improvement in hybrid electric vehicles

NASA Astrophysics Data System (ADS)

Asfoor, Mostafa

The gradual decline of oil reserves and the increasing demand for energy over the past decades has resulted in automotive manufacturers seeking alternative solutions to reduce the dependency on fossil-based fuels for transportation. A viable technology that enables significant improvements in the overall energy conversion efficiencies is the hybridization of conventional vehicle drive systems. This dissertation builds on prior hybrid powertrain development at the University of Idaho. Advanced vehicle models of a passenger car with a conventional powertrain and three different hybrid powertrain layouts were created using GT-Suite. These different powertrain models were validated against a variety of standard driving cycles. The overall fuel economy, energy consumption, and losses were monitored, and a comprehensive energy analysis was performed to compare energy sources and sinks. The GT-Suite model was then used to predict the formula hybrid SAE vehicle performance. Inputs to this model were a numerically predicted engine performance map, an electric motor torque curve, vehicle geometry, and road load parameters derived from a roll-down test. In this case study, the vehicle had a supervisory controller that followed a rule-based energy management strategy to insure a proper power split during hybrid mode operation. The supervisory controller parameters were optimized using discrete grid optimization method that minimized the total amount of fuel consumed during a specific urban driving cycle with an average speed of approximately 30 [mph]. More than a 15% increase in fuel economy was achieved by adding supervisory control and managing power split. The vehicle configuration without the supervisory controller displayed a fuel economy of 25 [mpg]. With the supervisory controller this rose to 29 [mpg]. Wider applications of this research include hybrid vehicle controller designs that can extend the range and survivability of military combat platforms. Furthermore, the GT-Suite model can be easily accommodated to simulate propulsion systems that store regenerative power when braking, making it available for acceleration and off-road maneuvering.

Theoretical modelling and optimization of bubble column dehumidifier for a solar driven humidification-dehumidification system

NASA Astrophysics Data System (ADS)

Ranjitha, P. Raj; Ratheesh, R.; Jayakumar, J. S.; Balakrishnan, Shankar

2018-02-01

Availability and utilization of energy and water are the top most global challenges being faced by the new millennium. At the present state water scarcity has become a global as well as a regional challenge. 40 % of world population faces water shortage. Challenge of water scarcity can be tackled only with increase in water supply beyond what is obtained from hydrological cycle. This can be achieved either by desalinating the sea water or by reusing the waste water. High energy requirement need to be overcome for either of the two processes. Of many desalination technologies, humidification dehumidification (HDH) technology powered by solar energy is widely accepted for small scale production. Detailed optimization studies on system have the potential to effectively utilize the solar energy for brackish water desalination. Dehumidification technology, specifically, require further study because the dehumidifier effectiveness control the energetic performance of the entire HDH system. The reason attributes to the high resistance involved to diffuse dilute vapor through air in a dehumidifier. The present work intends to optimize the design of a bubble column dehumidifier for a solar energy driven desalination process. Optimization is carried out using Matlab simulation. Design process will identify the unique needs of a bubble column dehumidifier in HDH system.

Reverse Osmosis Optimization

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

McMordie Stoughton, Kate; Duan, Xiaoli; Wendel, Emily M.

This technology evaluation was prepared by Pacific Northwest National Laboratory on behalf of the U.S. Department of Energy’s Federal Energy Management Program (FEMP). ¬The technology evaluation assesses techniques for optimizing reverse osmosis (RO) systems to increase RO system performance and water efficiency. This evaluation provides a general description of RO systems, the influence of RO systems on water use, and key areas where RO systems can be optimized to reduce water and energy consumption. The evaluation is intended to help facility managers at Federal sites understand the basic concepts of the RO process and system optimization options, enabling them tomore » make informed decisions during the system design process for either new projects or recommissioning of existing equipment. This evaluation is focused on commercial-sized RO systems generally treating more than 80 gallons per hour.¬« less

Reverse Osmosis Optimization

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

None

This technology evaluation was prepared by Pacific Northwest National Laboratory on behalf of the U.S. Department of Energy’s Federal Energy Management Program (FEMP). The technology evaluation assesses techniques for optimizing reverse osmosis (RO) systems to increase RO system performance and water efficiency. This evaluation provides a general description of RO systems, the influence of RO systems on water use, and key areas where RO systems can be optimized to reduce water and energy consumption. The evaluation is intended to help facility managers at Federal sites understand the basic concepts of the RO process and system optimization options, enabling them tomore » make informed decisions during the system design process for either new projects or recommissioning of existing equipment. This evaluation is focused on commercial-sized RO systems generally treating more than 80 gallons per hour.« less

Performance of Optimized Prosthetic Ankle Designs That Are Based on a Hydraulic Variable Displacement Actuator (VDA).

PubMed

Gardiner, James; Bari, Abu Zeeshan; Kenney, Laurence; Twiste, Martin; Moser, David; Zahedi, Saeed; Howard, David

2017-12-01

Current energy storage and return prosthetic feet only marginally reduce the cost of amputee locomotion compared with basic solid ankle cushioned heel feet, possibly due to their lack of push-off at the end of stance. To the best of our knowledge, a prosthetic ankle that utilizes a hydraulic variable displacement actuator (VDA) to improve push-off performance has not previously been proposed. Therefore, here we report a design optimization and simulation feasibility study for a VDA-based prosthetic ankle. The proposed device stores the eccentric ankle work done from heel strike to maximum dorsiflexion in a hydraulic accumulator and then returns the stored energy to power push-off. Optimization was used to establish the best spring characteristic and gear ratio between ankle and VDA. The corresponding simulations show that, in level walking, normal push-off is achieved and, per gait cycle, the energy stored in the accumulator increases by 22% of the requirements for normal push-off. Although the results are promising, there are many unanswered questions and, for this approach to be a success, a new miniature, low-losses, and lightweight VDA would be required that is half the size of the smallest commercially available device.

Development of Advanced Methods of Structural and Trajectory Analysis for Transport Aircraft

NASA Technical Reports Server (NTRS)

Ardema, Mark D.; Windhorst, Robert; Phillips, James

1998-01-01

This paper develops a near-optimal guidance law for generating minimum fuel, time, or cost fixed-range trajectories for supersonic transport aircraft. The approach uses a choice of new state variables along with singular perturbation techniques to time-scale decouple the dynamic equations into multiple equations of single order (second order for the fast dynamics). Application of the maximum principle to each of the decoupled equations, as opposed to application to the original coupled equations, avoids the two point boundary value problem and transforms the problem from one of a functional optimization to one of multiple function optimizations. It is shown that such an approach produces well known aircraft performance results such as minimizing the Brequet factor for minimum fuel consumption and the energy climb path. Furthermore, the new state variables produce a consistent calculation of flight path angle along the trajectory, eliminating one of the deficiencies in the traditional energy state approximation. In addition, jumps in the energy climb path are smoothed out by integration of the original dynamic equations at constant load factor. Numerical results performed for a supersonic transport design show that a pushover dive followed by a pullout at nominal load factors are sufficient maneuvers to smooth the jump.

Gaussian process regression for geometry optimization

NASA Astrophysics Data System (ADS)

Denzel, Alexander; Kästner, Johannes

2018-03-01

We implemented a geometry optimizer based on Gaussian process regression (GPR) to find minimum structures on potential energy surfaces. We tested both a two times differentiable form of the Matérn kernel and the squared exponential kernel. The Matérn kernel performs much better. We give a detailed description of the optimization procedures. These include overshooting the step resulting from GPR in order to obtain a higher degree of interpolation vs. extrapolation. In a benchmark against the Limited-memory Broyden-Fletcher-Goldfarb-Shanno optimizer of the DL-FIND library on 26 test systems, we found the new optimizer to generally reduce the number of required optimization steps.

A new optimal seam method for seamless image stitching

NASA Astrophysics Data System (ADS)

Xue, Jiale; Chen, Shengyong; Cheng, Xu; Han, Ying; Zhao, Meng

2017-07-01

A novel optimal seam method which aims to stitch those images with overlapping area more seamlessly has been propos ed. Considering the traditional gradient domain optimal seam method and fusion algorithm result in bad color difference measurement and taking a long time respectively, the input images would be converted to HSV space and a new energy function is designed to seek optimal stitching path. To smooth the optimal stitching path, a simplified pixel correction and weighted average method are utilized individually. The proposed methods exhibit performance in eliminating the stitching seam compared with the traditional gradient optimal seam and high efficiency with multi-band blending algorithm.

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.

Size-guided multi-seed heuristic method for geometry optimization of clusters: Application to benzene clusters.

PubMed

Takeuchi, Hiroshi

2018-05-08

Since searching for the global minimum on the potential energy surface of a cluster is very difficult, many geometry optimization methods have been proposed, in which initial geometries are randomly generated and subsequently improved with different algorithms. In this study, a size-guided multi-seed heuristic method is developed and applied to benzene clusters. It produces initial configurations of the cluster with n molecules from the lowest-energy configurations of the cluster with n - 1 molecules (seeds). The initial geometries are further optimized with the geometrical perturbations previously used for molecular clusters. These steps are repeated until the size n satisfies a predefined one. The method locates putative global minima of benzene clusters with up to 65 molecules. The performance of the method is discussed using the computational cost, rates to locate the global minima, and energies of initial geometries. © 2018 Wiley Periodicals, Inc. © 2018 Wiley Periodicals, Inc.

Development of a Platform for Simulating and Optimizing Thermoelectric Energy Systems

NASA Astrophysics Data System (ADS)

Kreuder, John J.

Thermoelectrics are solid state devices that can convert thermal energy directly into electrical energy. They have historically been used only in niche applications because of their relatively low efficiencies. With the advent of nanotechnology and improved manufacturing processes thermoelectric materials have become less costly and more efficient As next generation thermoelectric materials become available there is a need for industries to quickly and cost effectively seek out feasible applications for thermoelectric heat recovery platforms. Determining the technical and economic feasibility of such systems requires a model that predicts performance at the system level. Current models focus on specific system applications or neglect the rest of the system altogether, focusing on only module design and not an entire energy system. To assist in screening and optimizing entire energy systems using thermoelectrics, a novel software tool, Thermoelectric Power System Simulator (TEPSS), is developed for system level simulation and optimization of heat recovery systems. The platform is designed for use with a generic energy system so that most types of thermoelectric heat recovery applications can be modeled. TEPSS is based on object-oriented programming in MATLABRTM. A modular, shell based architecture is developed to carry out concept generation, system simulation and optimization. Systems are defined according to the components and interconnectivity specified by the user. An iterative solution process based on Newton's Method is employed to determine the system's steady state so that an objective function representing the cost of the system can be evaluated at the operating point. An optimization algorithm from MATLAB's Optimization Toolbox uses sequential quadratic programming to minimize this objective function with respect to a set of user specified design variables and constraints. During this iterative process many independent system simulations are executed and the optimal operating condition of the system is determined. A comprehensive guide to using the software platform is included. TEPSS is intended to be expandable so that users can add new types of components and implement component models with an adequate degree of complexity for a required application. Special steps are taken to ensure that the system of nonlinear algebraic equations presented in the system engineering model is square and that all equations are independent. In addition, the third party program FluidProp is leveraged to allow for simulations of systems with a range of fluids. Sequential unconstrained minimization techniques are used to prevent physical variables like pressure and temperature from trending to infinity during optimization. Two case studies are performed to verify and demonstrate the simulation and optimization routines employed by TEPSS. The first is of a simple combined cycle in which the size of the heat exchanger and fuel rate are optimized. The second case study is the optimization of geometric parameters of a thermoelectric heat recovery platform in a regenerative Brayton Cycle. A basic package of components and interconnections are verified and provided as well.

Optimization methods applied to hybrid vehicle design

NASA Technical Reports Server (NTRS)

Donoghue, J. F.; Burghart, J. H.

1983-01-01

The use of optimization methods as an effective design tool in the design of hybrid vehicle propulsion systems is demonstrated. Optimization techniques were used to select values for three design parameters (battery weight, heat engine power rating and power split between the two on-board energy sources) such that various measures of vehicle performance (acquisition cost, life cycle cost and petroleum consumption) were optimized. The apporach produced designs which were often significant improvements over hybrid designs already reported on in the literature. The principal conclusions are as follows. First, it was found that the strategy used to split the required power between the two on-board energy sources can have a significant effect on life cycle cost and petroleum consumption. Second, the optimization program should be constructed so that performance measures and design variables can be easily changed. Third, the vehicle simulation program has a significant effect on the computer run time of the overall optimization program; run time can be significantly reduced by proper design of the types of trips the vehicle takes in a one year period. Fourth, care must be taken in designing the cost and constraint expressions which are used in the optimization so that they are relatively smooth functions of the design variables. Fifth, proper handling of constraints on battery weight and heat engine rating, variables which must be large enough to meet power demands, is particularly important for the success of an optimization study. Finally, the principal conclusion is that optimization methods provide a practical tool for carrying out the design of a hybrid vehicle propulsion system.

Parameters optimization for the energy management system of hybrid electric vehicle

NASA Astrophysics Data System (ADS)

Tseng, Chyuan-Yow; Hung, Yi-Hsuan; Tsai, Chien-Hsiung; Huang, Yu-Jen

2007-12-01

Hybrid electric vehicle (HEV) has been widely studied recently due to its high potential in reduction of fuel consumption, exhaust emission, and lower noise. Because of comprised of two power sources, the HEV requires an energy management system (EMS) to distribute optimally the power sources for various driving conditions. The ITRI in Taiwan has developed a HEV consisted of a 2.2L internal combustion engine (ICE), a 18KW motor/generator (M/G), a 288V battery pack, and a continuous variable transmission (CVT). The task of the present study is to design an energy management strategy of the EMS for the HEV. Due to the nonlinear nature and the fact of unknown system model of the system, a kind of simplex method based energy management strategy is proposed for the HEV system. The simplex method is a kind of optimization strategy which is generally used to find out the optimal parameters for un-modeled systems. The way to apply the simplex method for the design of the EMS is presented. The feasibility of the proposed method was verified by perform numerical simulation on the FTP75 drive cycles.

A novel multireceiver communications system configuration based on optimal estimation theory

NASA Technical Reports Server (NTRS)

Kumar, R.

1990-01-01

A multireceiver configuration for the purpose of carrier arraying and/or signal arraying is presented. Such a problem arises for example, in the NASA Deep Space Network where the same data-modulated signal from a spacecraft is received by a number of geographically separated antennas and the data detection must be efficiently performed on the basis of the various received signals. The proposed configuration is arrived at by formulating the carrier and/or signal arraying problem as an optimal estimation problem. Two specific solutions are proposed. The first solution is to simultaneously and optimally estimate the various phase processes received at different receivers with coupled phase locked loops (PLLs) wherein the individual PLLs acquire and track their respective receivers' phase processes, but are aided by each other in an optimal manner. However, when the phase processes are relatively weakly correlated, and for the case of relatively high values of symbol energy-to-noise spectral density ratio, a novel configuration for combining the data modulated, loop-output signals is proposed. The scheme can be extended to the case of low symbol energy-to-noise case by performing the combining/detection process over a multisymbol period. Such a configuration results in the minimization of the effective radio loss at the combiner output, and thus a maximization of energy per bit to noise-power spectral density ration is achieved.

SPOKES: An end-to-end simulation facility for spectroscopic cosmological surveys

DOE PAGES

Nord, B.; Amara, A.; Refregier, A.; ...

2016-03-03

The nature of dark matter, dark energy and large-scale gravity pose some of the most pressing questions in cosmology today. These fundamental questions require highly precise measurements, and a number of wide-field spectroscopic survey instruments are being designed to meet this requirement. A key component in these experiments is the development of a simulation tool to forecast science performance, define requirement flow-downs, optimize implementation, demonstrate feasibility, and prepare for exploitation. We present SPOKES (SPectrOscopic KEn Simulation), an end-to-end simulation facility for spectroscopic cosmological surveys designed to address this challenge. SPOKES is based on an integrated infrastructure, modular function organization, coherentmore » data handling and fast data access. These key features allow reproducibility of pipeline runs, enable ease of use and provide flexibility to update functions within the pipeline. The cyclic nature of the pipeline offers the possibility to make the science output an efficient measure for design optimization and feasibility testing. We present the architecture, first science, and computational performance results of the simulation pipeline. The framework is general, but for the benchmark tests, we use the Dark Energy Spectrometer (DESpec), one of the early concepts for the upcoming project, the Dark Energy Spectroscopic Instrument (DESI). As a result, we discuss how the SPOKES framework enables a rigorous process to optimize and exploit spectroscopic survey experiments in order to derive high-precision cosmological measurements optimally.« less

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

Nord, B.; Amara, A.; Refregier, A.

The nature of dark matter, dark energy and large-scale gravity pose some of the most pressing questions in cosmology today. These fundamental questions require highly precise measurements, and a number of wide-field spectroscopic survey instruments are being designed to meet this requirement. A key component in these experiments is the development of a simulation tool to forecast science performance, define requirement flow-downs, optimize implementation, demonstrate feasibility, and prepare for exploitation. We present SPOKES (SPectrOscopic KEn Simulation), an end-to-end simulation facility for spectroscopic cosmological surveys designed to address this challenge. SPOKES is based on an integrated infrastructure, modular function organization, coherentmore » data handling and fast data access. These key features allow reproducibility of pipeline runs, enable ease of use and provide flexibility to update functions within the pipeline. The cyclic nature of the pipeline offers the possibility to make the science output an efficient measure for design optimization and feasibility testing. We present the architecture, first science, and computational performance results of the simulation pipeline. The framework is general, but for the benchmark tests, we use the Dark Energy Spectrometer (DESpec), one of the early concepts for the upcoming project, the Dark Energy Spectroscopic Instrument (DESI). As a result, we discuss how the SPOKES framework enables a rigorous process to optimize and exploit spectroscopic survey experiments in order to derive high-precision cosmological measurements optimally.« less

Statistical-QoS Guaranteed Energy Efficiency Optimization for Energy Harvesting Wireless Sensor Networks

PubMed Central

Cheng, Wenchi; Zhang, Hailin

2017-01-01

Energy harvesting, which offers a never-ending energy supply, has emerged as a prominent technology to prolong the lifetime and reduce costs for the battery-powered wireless sensor networks. However, how to improve the energy efficiency while guaranteeing the quality of service (QoS) for energy harvesting based wireless sensor networks is still an open problem. In this paper, we develop statistical delay-bounded QoS-driven power control policies to maximize the effective energy efficiency (EEE), which is defined as the spectrum efficiency under given specified QoS constraints per unit harvested energy, for energy harvesting based wireless sensor networks. For the battery-infinite wireless sensor networks, our developed QoS-driven power control policy converges to the Energy harvesting Water Filling (E-WF) scheme and the Energy harvesting Channel Inversion (E-CI) scheme under the very loose and stringent QoS constraints, respectively. For the battery-finite wireless sensor networks, our developed QoS-driven power control policy becomes the Truncated energy harvesting Water Filling (T-WF) scheme and the Truncated energy harvesting Channel Inversion (T-CI) scheme under the very loose and stringent QoS constraints, respectively. Furthermore, we evaluate the outage probabilities to theoretically analyze the performance of our developed QoS-driven power control policies. The obtained numerical results validate our analysis and show that our developed optimal power control policies can optimize the EEE over energy harvesting based wireless sensor networks. PMID:28832509

Statistical-QoS Guaranteed Energy Efficiency Optimization for Energy Harvesting Wireless Sensor Networks.

PubMed

Gao, Ya; Cheng, Wenchi; Zhang, Hailin

2017-08-23

Energy harvesting, which offers a never-ending energy supply, has emerged as a prominent technology to prolong the lifetime and reduce costs for the battery-powered wireless sensor networks. However, how to improve the energy efficiency while guaranteeing the quality of service (QoS) for energy harvesting based wireless sensor networks is still an open problem. In this paper, we develop statistical delay-bounded QoS-driven power control policies to maximize the effective energy efficiency (EEE), which is defined as the spectrum efficiency under given specified QoS constraints per unit harvested energy, for energy harvesting based wireless sensor networks. For the battery-infinite wireless sensor networks, our developed QoS-driven power control policy converges to the Energy harvesting Water Filling (E-WF) scheme and the Energy harvesting Channel Inversion (E-CI) scheme under the very loose and stringent QoS constraints, respectively. For the battery-finite wireless sensor networks, our developed QoS-driven power control policy becomes the Truncated energy harvesting Water Filling (T-WF) scheme and the Truncated energy harvesting Channel Inversion (T-CI) scheme under the very loose and stringent QoS constraints, respectively. Furthermore, we evaluate the outage probabilities to theoretically analyze the performance of our developed QoS-driven power control policies. The obtained numerical results validate our analysis and show that our developed optimal power control policies can optimize the EEE over energy harvesting based wireless sensor networks.

Improving the Performance of PbS Quantum Dot Solar Cells by Optimizing ZnO Window Layer

NASA Astrophysics Data System (ADS)

Yang, Xiaokun; Hu, Long; Deng, Hui; Qiao, Keke; Hu, Chao; Liu, Zhiyong; Yuan, Shengjie; Khan, Jahangeer; Li, Dengbing; Tang, Jiang; Song, Haisheng; Cheng, Chun

2017-04-01

Comparing with hot researches in absorber layer, window layer has attracted less attention in PbS quantum dot solar cells (QD SCs). Actually, the window layer plays a key role in exciton separation, charge drifting, and so on. Herein, ZnO window layer was systematically investigated for its roles in QD SCs performance. The physical mechanism of improved performance was also explored. It was found that the optimized ZnO films with appropriate thickness and doping concentration can balance the optical and electrical properties, and its energy band align well with the absorber layer for efficient charge extraction. Further characterizations demonstrated that the window layer optimization can help to reduce the surface defects, improve the heterojunction quality, as well as extend the depletion width. Compared with the control devices, the optimized devices have obtained an efficiency of 6.7% with an enhanced V oc of 18%, J sc of 21%, FF of 10%, and power conversion efficiency of 58%. The present work suggests a useful strategy to improve the device performance by optimizing the window layer besides the absorber layer.

Assessment of solar-assisted gas-fired heat pump systems

NASA Technical Reports Server (NTRS)

Lansing, F. L.

1981-01-01

As a possible application for the Goldstone Energy Project, the performance of a 10 ton heat pump unit using a hybrid solar gas energy source was evaluated in an effort to optimize the solar collector size. The heat pump system is designed to provide all the cooling and/or heating requirements of a selected office building. The system performance is to be augmented in the heating mode by utilizing the waste heat from the power cycle. A simplified system analysis is described to assess and compute interrrelationships of the engine, heat pump, and solar and building performance parameters, and to optimize the solar concentrator/building area ratio for a minimum total system cost. In addition, four alternative heating cooling systems, commonly used for building comfort, are described; their costs are compared, and are found to be less competitive with the gas solar heat pump system at the projected solar equipment costs.

Direct quantification of energy intake in an apex marine predator suggests physiology is a key driver of migrations

PubMed Central

Whitlock, Rebecca E.; Hazen, Elliott L.; Walli, Andreas; Farwell, Charles; Bograd, Steven J.; Foley, David G.; Castleton, Michael; Block, Barbara A.

2015-01-01

Pacific bluefin tuna (Thunnus orientalis) are highly migratory apex marine predators that inhabit a broad thermal niche. The energy needed for migration must be garnered by foraging, but measuring energy intake in the marine environment is challenging. We quantified the energy intake of Pacific bluefin tuna in the California Current using a laboratory-validated model, the first such measurement in a wild marine predator. Mean daily energy intake was highest off the coast of Baja California, Mexico in summer (mean ± SD, 1034 ± 669 kcal), followed by autumn when Pacific bluefin achieve their northernmost range in waters off northern California (944 ± 579 kcal). Movements were not always consistent with maximizing energy intake: the Pacific bluefin move out of energy rich waters both in late summer and winter, coincident with rising and falling water temperatures, respectively. We hypothesize that temperature-related physiological constraints drive migration and that Pacific bluefin tuna optimize energy intake within a range of optimal aerobic performance. PMID:26601248

Direct quantification of energy intake in an apex marine predator suggests physiology is a key driver of migrations.

PubMed

Whitlock, Rebecca E; Hazen, Elliott L; Walli, Andreas; Farwell, Charles; Bograd, Steven J; Foley, David G; Castleton, Michael; Block, Barbara A

2015-09-01

Pacific bluefin tuna (Thunnus orientalis) are highly migratory apex marine predators that inhabit a broad thermal niche. The energy needed for migration must be garnered by foraging, but measuring energy intake in the marine environment is challenging. We quantified the energy intake of Pacific bluefin tuna in the California Current using a laboratory-validated model, the first such measurement in a wild marine predator. Mean daily energy intake was highest off the coast of Baja California, Mexico in summer (mean ± SD, 1034 ± 669 kcal), followed by autumn when Pacific bluefin achieve their northernmost range in waters off northern California (944 ± 579 kcal). Movements were not always consistent with maximizing energy intake: the Pacific bluefin move out of energy rich waters both in late summer and winter, coincident with rising and falling water temperatures, respectively. We hypothesize that temperature-related physiological constraints drive migration and that Pacific bluefin tuna optimize energy intake within a range of optimal aerobic performance.

Design and optimization of an energy degrader with a multi-wedge scheme based on Geant4

NASA Astrophysics Data System (ADS)

Liang, Zhikai; Liu, Kaifeng; Qin, Bin; Chen, Wei; Liu, Xu; Li, Dong; Xiong, Yongqian

2018-05-01

A proton therapy facility based on an isochronous superconducting cyclotron is under construction in Huazhong University of Science and Technology (HUST). To meet the clinical requirements, an energy degrader is essential in the beamline to modulate the fixed beam energy extracted from the cyclotron. Because of the multiple Coulomb scattering in the degrader, the beam emittance and the energy spread will be considerably increased during the energy degradation process. Therefore, a set of collimators is designed to restrict the increase in beam emittance after the energy degradation. The energy spread will be reduced in the following beam line which is not discussed in this paper. In this paper, the design considerations of an energy degrader and collimators are introduced, and the properties of the degrader material, degrader structure and the initial beam parameters are discussed using the Geant4 Monte-Carlo toolkit, with the main purpose of improving the overall performance of the degrader by multiple parameter optimization.

Design guidelines of triboelectric nanogenerator for water wave energy harvesters.

PubMed

Ahmed, Abdelsalam; Hassan, Islam; Jiang, Tao; Youssef, Khalid; Liu, Lian; Hedaya, Mohammad; Yazid, Taher Abu; Zu, Jean; Wang, Zhong Lin

2017-05-05

Ocean waves are one of the cleanest and most abundant energy sources on earth, and wave energy has the potential for future power generation. Triboelectric nanogenerator (TENG) technology has recently been proposed as a promising technology to harvest wave energy. In this paper, a theoretical study is performed on a duck-shaped TENG wave harvester recently introduced in our work. To enhance the design of the duck-shaped TENG wave harvester, the mechanical and electrical characteristics of the harvester's overall structure, as well as its inner configuration, are analyzed, respectively, under different wave conditions, to optimize parameters such as duck radius and mass. Furthermore, a comprehensive hybrid 3D model is introduced to quantify the performance of the TENG wave harvester. Finally, the influence of different TENG parameters is validated by comparing the performance of several existing TENG wave harvesters. This study can be applied as a guideline for enhancing the performance of TENG wave energy harvesters.

Renewable Energy Optimization Report for Naval Station Newport

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

Robichaud, R.; Mosey, G.; Olis, D.

2012-02-01

In 2008, the U.S. Environmental Protection Agency (EPA) launched the RE-Powering America's Land initiative to encourage the development of renewable energy (RE) on potentially contaminated land and mine sites. As part of this effort, EPA is collaborating with the U.S. Department of Energy's (DOE's) National Renewable Energy Laboratory (NREL) to evaluate RE options at Naval Station (NAVSTA) Newport in Newport, Rhode Island. NREL's Renewable Energy Optimization (REO) tool was utilized to identify RE technologies that present the best opportunity for life-cycle cost-effective implementation while also serving to reduce energy-related carbon dioxide emissions and increase the percentage of RE used atmore » NAVSTA Newport. The technologies included in REO are daylighting, wind, solar ventilation preheating (SVP), solar water heating, photovoltaics (PV), solar thermal (heating and electric), and biomass (gasification and cogeneration). The optimal mix of RE technologies depends on several factors including RE resources; technology cost and performance; state, utility, and federal incentives; and economic parameters (discount and inflation rates). Each of these factors was considered in this analysis. Technologies not included in REO that were investigated separately per NAVSTA Newport request include biofuels from algae, tidal power, and ground source heat pumps (GSHP).« less

Application configuration selection for energy-efficient execution on multicore systems

DOE PAGES

Wang, Shinan; Luo, Bing; Shi, Weisong; ...

2015-09-21

Balanced performance and energy consumption are incorporated in the design of modern computer systems. Several runtime factors, such as concurrency levels, thread mapping strategies, and dynamic voltage and frequency scaling (DVFS) should be considered in order to achieve optimal energy efficiency fora workload. Selecting appropriate run-time factors, however, is one of the most challenging tasks because the run-time factors are architecture-specific and workload-specific. And while most existing works concentrate on either static analysis of the workload or run-time prediction results, we present a hybrid two-step method that utilizes concurrency levels and DVFS settings to achieve the energy efficiency configuration formore » a worldoad. The experimental results based on a Xeon E5620 server with NPB and PARSEC benchmark suites show that the model is able to predict the energy efficient configuration accurately. On average, an additional 10% EDP (Energy Delay Product) saving is obtained by using run-time DVFS for the entire system. An off-line optimal solution is used to compare with the proposed scheme. Finally, the experimental results show that the average extra EDP saved by the optimal solution is within 5% on selective parallel benchmarks.« less

Manual of phosphoric acid fuel cell power plant optimization model and computer program

NASA Technical Reports Server (NTRS)

Lu, C. Y.; Alkasab, K. A.

1984-01-01

An optimized cost and performance model for a phosphoric acid fuel cell power plant system was derived and developed into a modular FORTRAN computer code. Cost, energy, mass, and electrochemical analyses were combined to develop a mathematical model for optimizing the steam to methane ratio in the reformer, hydrogen utilization in the PAFC plates per stack. The nonlinear programming code, COMPUTE, was used to solve this model, in which the method of mixed penalty function combined with Hooke and Jeeves pattern search was chosen to evaluate this specific optimization problem.

Optimal trajectories for hypersonic launch vehicles

NASA Technical Reports Server (NTRS)

Ardema, Mark D.; Bowles, Jeffrey V.; Whittaker, Thomas

1992-01-01

In this paper, we derive a near-optimal guidance law for the ascent trajectory from Earth surface to Earth orbit of a hypersonic, dual-mode propulsion, lifting vehicle. Of interest are both the optimal flight path and the optimal operation of the propulsion system. The guidance law is developed from the energy-state approximation of the equations of motion. The performance objective is a weighted sum of fuel mass and volume, with the weighting factor selected to give minimum gross take-off weight for a specific payload mass and volume.

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

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

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

2016-03-31

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

Distributed Wireless Power Transfer With Energy Feedback

NASA Astrophysics Data System (ADS)

Lee, Seunghyun; Zhang, Rui

2017-04-01

Energy beamforming (EB) is a key technique for achieving efficient radio-frequency (RF) transmission enabled wireless energy transfer (WET). By optimally designing the waveforms from multiple energy transmitters (ETs) over the wireless channels, they can be constructively combined at the energy receiver (ER) to achieve an EB gain that scales with the number of ETs. However, the optimal design of EB waveforms requires accurate channel state information (CSI) at the ETs, which is challenging to obtain practically, especially in a distributed system with ETs at separate locations. In this paper, we study practical and efficient channel training methods to achieve optimal EB in a distributed WET system. We propose two protocols with and without centralized coordination, respectively, where distributed ETs either sequentially or in parallel adapt their transmit phases based on a low-complexity energy feedback from the ER. The energy feedback only depends on the received power level at the ER, where each feedback indicates one particular transmit phase that results in the maximum harvested power over a set of previously used phases. Simulation results show that the two proposed training protocols converge very fast in practical WET systems even with a large number of distributed ETs, while the protocol with sequential ET phase adaptation is also analytically shown to converge to the optimal EB design with perfect CSI by increasing the training time. Numerical results are also provided to evaluate the performance of the proposed distributed EB and training designs as compared to other benchmark schemes.

Procedure for minimizing the cost per watt of photovoltaic systems

NASA Technical Reports Server (NTRS)

Redfield, D.

1977-01-01

A general analytic procedure is developed that provides a quantitative method for optimizing any element or process in the fabrication of a photovoltaic energy conversion system by minimizing its impact on the cost per watt of the complete system. By determining the effective value of any power loss associated with each element of the system, this procedure furnishes the design specifications that optimize the cost-performance tradeoffs for each element. A general equation is derived that optimizes the properties of any part of the system in terms of appropriate cost and performance functions, although the power-handling components are found to have a different character from the cell and array steps. Another principal result is that a fractional performance loss occurring at any cell- or array-fabrication step produces that same fractional increase in the cost per watt of the complete array. It also follows that no element or process step can be optimized correctly by considering only its own cost and performance

Scalable and Power Efficient Data Analytics for Hybrid Exascale Systems

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

Choudhary, Alok; Samatova, Nagiza; Wu, Kesheng

This project developed a generic and optimized set of core data analytics functions. These functions organically consolidate a broad constellation of high performance analytical pipelines. As the architectures of emerging HPC systems become inherently heterogeneous, there is a need to design algorithms for data analysis kernels accelerated on hybrid multi-node, multi-core HPC architectures comprised of a mix of CPUs, GPUs, and SSDs. Furthermore, the power-aware trend drives the advances in our performance-energy tradeoff analysis framework which enables our data analysis kernels algorithms and software to be parameterized so that users can choose the right power-performance optimizations.

Active optimal control strategies for increasing the efficiency of photovoltaic cells

NASA Astrophysics Data System (ADS)

Aljoaba, Sharif Zidan Ahmad

Energy consumption has increased drastically during the last century. Currently, the worldwide energy consumption is about 17.4 TW and is predicted to reach 25 TW by 2035. Solar energy has emerged as one of the potential renewable energy sources. Since its first physical recognition in 1887 by Adams and Day till nowadays, research in solar energy is continuously developing. This has lead to many achievements and milestones that introduced it as one of the most reliable and sustainable energy sources. Recently, the International Energy Agency declared that solar energy is predicted to be one of the major electricity production energy sources by 2035. Enhancing the efficiency and lifecycle of photovoltaic (PV) modules leads to significant cost reduction. Reducing the temperature of the PV module improves its efficiency and enhances its lifecycle. To better understand the PV module performance, it is important to study the interaction between the output power and the temperature. A model that is capable of predicting the PV module temperature and its effects on the output power considering the individual contribution of the solar spectrum wavelengths significantly advances the PV module edsigns toward higher efficiency. In this work, a thermoelectrical model is developed to predict the effects of the solar spectrum wavelengths on the PV module performance. The model is characterized and validated under real meteorological conditions where experimental temperature and output power of the PV module measurements are shown to agree with the predicted results. The model is used to validate the concept of active optical filtering. Since this model is wavelength-based, it is used to design an active optical filter for PV applications. Applying this filter to the PV module is expected to increase the output power of the module by filtering the spectrum wavelengths. The active filter performance is optimized, where different cutoff wavelengths are used to maximize the module output power. It is predicted that if the optimized active optical filter is applied to the PV module, the module efficiency is predicted to increase by about 1%. Different technologies are considered for physical implementation of the active optical filter.

Optimizing Energy Consumption in Building Designs Using Building Information Model (BIM)

NASA Astrophysics Data System (ADS)

Egwunatum, Samuel; Joseph-Akwara, Esther; Akaigwe, Richard

2016-09-01

Given the ability of a Building Information Model (BIM) to serve as a multi-disciplinary data repository, this paper seeks to explore and exploit the sustainability value of Building Information Modelling/models in delivering buildings that require less energy for their operation, emit less CO2 and at the same time provide a comfortable living environment for their occupants. This objective was achieved by a critical and extensive review of the literature covering: (1) building energy consumption, (2) building energy performance and analysis, and (3) building information modeling and energy assessment. The literature cited in this paper showed that linking an energy analysis tool with a BIM model helped project design teams to predict and create optimized energy consumption. To validate this finding, an in-depth analysis was carried out on a completed BIM integrated construction project using the Arboleda Project in the Dominican Republic. The findings showed that the BIM-based energy analysis helped the design team achieve the world's first 103% positive energy building. From the research findings, the paper concludes that linking an energy analysis tool with a BIM model helps to expedite the energy analysis process, provide more detailed and accurate results as well as deliver energy-efficient buildings. The study further recommends that the adoption of a level 2 BIM and the integration of BIM in energy optimization analyse should be made compulsory for all projects irrespective of the method of procurement (government-funded or otherwise) or its size.

Energy-efficient growth of phage Q Beta in Escherichia coli.

PubMed

Kim, Hwijin; Yin, John

2004-10-20

The role of natural selection in the optimal design of organisms is controversial. Optimal forms, functions, or behaviors of organisms have long been claimed without knowledge of how genotype contributes to phenotype, delineation of design constraints, or reference to alternative designs. Moreover, arguments for optimal designs have been often based on models that were difficult, if not impossible, to test. Here, we begin to address these issues by developing and probing a kinetic model for the intracellular growth of bacteriophage Q beta in Escherichia coli. The model accounts for the energetic costs of all template-dependent polymerization reactions, in ATP equivalents, including RNA-dependent RNA elongation by the phage replicase and synthesis of all phage proteins by the translation machinery of the E. coli host cell. We found that translation dominated phage growth, requiring 85% of the total energy expenditure. Only 10% of the total energy was applied to activities other than the direct synthesis of progeny phage components, reflecting primarily the cost of making the negative-strand RNA template that is needed for replication of phage genomic RNA. Further, we defined an energy efficiency of phage growth and showed its direct relationship to the yield of phage progeny. Finally, we performed a sensitivity analysis and found that the growth of wild-type phage was optimized for progeny yield or energy efficiency, suggesting that phage Q beta has evolved to optimally utilize the finite resources of its host cells.

Optimization and Performance Study of Select Heating Ventilation and Air Conditioning Technologies for Commercial Buildings

NASA Astrophysics Data System (ADS)

Kamal, Rajeev

Buildings contribute a significant part to the electricity demand profile and peak demand for the electrical utilities. The addition of renewable energy generation adds additional variability and uncertainty to the power system. Demand side management in the buildings can help improve the demand profile for the utilities by shifting some of the demand from peak to off-peak times. Heating, ventilation and air-conditioning contribute around 45% to the overall demand of a building. This research studies two strategies for reducing the peak as well as shifting some demand from peak to off-peak periods in commercial buildings: 1. Use of gas heat pumps in place of electric heat pumps, and 2. Shifting demand for air conditioning from peak to off-peak by thermal energy storage in chilled water and ice. The first part of this study evaluates the field performance of gas engine-driven heat pumps (GEHP) tested in a commercial building in Florida. Four GEHP units of 8 Tons of Refrigeration (TR) capacity each providing air-conditioning to seven thermal zones in a commercial building, were instrumented for measuring their performance. The operation of these GEHPs was recorded for ten months, analyzed and compared with prior results reported in the literature. The instantaneous COPunit of these systems varied from 0.1 to 1.4 during typical summer week operation. The COP was low because the gas engines for the heat pumps were being used for loads that were much lower than design capacity which resulted in much lower efficiencies than expected. The performance of equivalent electric heat pump was simulated from a building energy model developed to mimic the measured building loads. An economic comparison of GEHPs and conventional electrical heat pumps was done based on the measured and simulated results. The average performance of the GEHP units was estimated to lie between those of EER-9.2 and EER-11.8 systems. The performance of GEHP systems suffers due to lower efficiency at part load operation. The study highlighted the need for optimum system sizing for GEHP/HVAC systems to meet the building load to obtain better performance in buildings. The second part of this study focusses on using chilled water or ice as thermal energy storage for shifting the air conditioning load from peak to off-peak in a commercial building. Thermal energy storage can play a very important role in providing demand-side management for diversifying the utility demand from buildings. Model of a large commercial office building is developed with thermal storage for cooling for peak power shifting. Three variations of the model were developed and analyzed for their performance with 1) ice storage, 2) chilled water storage with mixed storage tank and 3) chilled water storage with stratified tank, using EnergyPlus 8.5 software developed by the US Department of Energy. Operation strategy with tactical control to incorporate peak power schedule was developed using energy management system (EMS). The modeled HVAC system was optimized for minimum cost with the optimal storage capacity and chiller size using JEPlus. Based on the simulation, an optimal storage capacity of 40-45 GJ was estimated for the large office building model along with 40% smaller chiller capacity resulting in higher chiller part-load performance. Additionally, the auxiliary system like pump and condenser were also optimized to smaller capacities and thus resulting in less power demand during operation. The overall annual saving potential was found in the range of 7-10% for cooling electricity use resulting in 10-17% reduction in costs to the consumer. A possible annual peak shifting of 25-78% was found from the simulation results after comparing with the reference models. Adopting TES in commercial buildings and achieving 25% peak shifting could result in a reduction in peak summer demand of 1398 MW in Tampa.

Approximating Optimal Behavioural Strategies Down to Rules-of-Thumb: Energy Reserve Changes in Pairs of Social Foragers

PubMed Central

Rands, Sean A.

2011-01-01

Functional explanations of behaviour often propose optimal strategies for organisms to follow. These ‘best’ strategies could be difficult to perform given biological constraints such as neural architecture and physiological constraints. Instead, simple heuristics or ‘rules-of-thumb’ that approximate these optimal strategies may instead be performed. From a modelling perspective, rules-of-thumb are also useful tools for considering how group behaviour is shaped by the behaviours of individuals. Using simple rules-of-thumb reduces the complexity of these models, but care needs to be taken to use rules that are biologically relevant. Here, we investigate the similarity between the outputs of a two-player dynamic foraging game (which generated optimal but complex solutions) and a computational simulation of the behaviours of the two members of a foraging pair, who instead followed a rule-of-thumb approximation of the game's output. The original game generated complex results, and we demonstrate here that the simulations following the much-simplified rules-of-thumb also generate complex results, suggesting that the rule-of-thumb was sufficient to make some of the model outcomes unpredictable. There was some agreement between both modelling techniques, but some differences arose – particularly when pair members were not identical in how they gained and lost energy. We argue that exploring how rules-of-thumb perform in comparison to their optimal counterparts is an important exercise for biologically validating the output of agent-based models of group behaviour. PMID:21765938

Approximating optimal behavioural strategies down to rules-of-thumb: energy reserve changes in pairs of social foragers.

PubMed

Rands, Sean A

2011-01-01

Functional explanations of behaviour often propose optimal strategies for organisms to follow. These 'best' strategies could be difficult to perform given biological constraints such as neural architecture and physiological constraints. Instead, simple heuristics or 'rules-of-thumb' that approximate these optimal strategies may instead be performed. From a modelling perspective, rules-of-thumb are also useful tools for considering how group behaviour is shaped by the behaviours of individuals. Using simple rules-of-thumb reduces the complexity of these models, but care needs to be taken to use rules that are biologically relevant. Here, we investigate the similarity between the outputs of a two-player dynamic foraging game (which generated optimal but complex solutions) and a computational simulation of the behaviours of the two members of a foraging pair, who instead followed a rule-of-thumb approximation of the game's output. The original game generated complex results, and we demonstrate here that the simulations following the much-simplified rules-of-thumb also generate complex results, suggesting that the rule-of-thumb was sufficient to make some of the model outcomes unpredictable. There was some agreement between both modelling techniques, but some differences arose - particularly when pair members were not identical in how they gained and lost energy. We argue that exploring how rules-of-thumb perform in comparison to their optimal counterparts is an important exercise for biologically validating the output of agent-based models of group behaviour.

Discrete Particle Swarm Optimization Routing Protocol for Wireless Sensor Networks with Multiple Mobile Sinks

PubMed Central

Yang, Jin; Liu, Fagui; Cao, Jianneng; Wang, Liangming

2016-01-01

Mobile sinks can achieve load-balancing and energy-consumption balancing across the wireless sensor networks (WSNs). However, the frequent change of the paths between source nodes and the sinks caused by sink mobility introduces significant overhead in terms of energy and packet delays. To enhance network performance of WSNs with mobile sinks (MWSNs), we present an efficient routing strategy, which is formulated as an optimization problem and employs the particle swarm optimization algorithm (PSO) to build the optimal routing paths. However, the conventional PSO is insufficient to solve discrete routing optimization problems. Therefore, a novel greedy discrete particle swarm optimization with memory (GMDPSO) is put forward to address this problem. In the GMDPSO, particle’s position and velocity of traditional PSO are redefined under discrete MWSNs scenario. Particle updating rule is also reconsidered based on the subnetwork topology of MWSNs. Besides, by improving the greedy forwarding routing, a greedy search strategy is designed to drive particles to find a better position quickly. Furthermore, searching history is memorized to accelerate convergence. Simulation results demonstrate that our new protocol significantly improves the robustness and adapts to rapid topological changes with multiple mobile sinks, while efficiently reducing the communication overhead and the energy consumption. PMID:27428971

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.

Nanomaterials derived from metal-organic frameworks

NASA Astrophysics Data System (ADS)

Dang, Song; Zhu, Qi-Long; Xu, Qiang

2018-01-01

The thermal transformation of metal-organic frameworks (MOFs) generates a variety of nanostructured materials, including carbon-based materials, metal oxides, metal chalcogenides, metal phosphides and metal carbides. These derivatives of MOFs have characteristics such as high surface areas, permanent porosities and controllable functionalities that enable their good performance in sensing, gas storage, catalysis and energy-related applications. Although progress has been made to tune the morphologies of MOF-derived structures at the nanometre scale, it remains crucial to further our knowledge of the relationship between morphology and performance. In this Review, we summarize the synthetic strategies and optimized methods that enable control over the size, morphology, composition and structure of the derived nanomaterials. In addition, we compare the performance of materials prepared by the MOF-templated strategy and other synthetic methods. Our aim is to reveal the relationship between the morphology and the physico-chemical properties of MOF-derived nanostructures to optimize their performance for applications such as sensing, catalysis, and energy storage and conversion.

Outage Performance Analysis of Relay Selection Schemes in Wireless Energy Harvesting Cooperative Networks over Non-Identical Rayleigh Fading Channels †

PubMed Central

Do, Nhu Tri; Bao, Vo Nguyen Quoc; An, Beongku

2016-01-01

In this paper, we study relay selection in decode-and-forward wireless energy harvesting cooperative networks. In contrast to conventional cooperative networks, the relays harvest energy from the source’s radio-frequency radiation and then use that energy to forward the source information. Considering power splitting receiver architecture used at relays to harvest energy, we are concerned with the performance of two popular relay selection schemes, namely, partial relay selection (PRS) scheme and optimal relay selection (ORS) scheme. In particular, we analyze the system performance in terms of outage probability (OP) over independent and non-identical (i.n.i.d.) Rayleigh fading channels. We derive the closed-form approximations for the system outage probabilities of both schemes and validate the analysis by the Monte-Carlo simulation. The numerical results provide comprehensive performance comparison between the PRS and ORS schemes and reveal the effect of wireless energy harvesting on the outage performances of both schemes. Additionally, we also show the advantages and drawbacks of the wireless energy harvesting cooperative networks and compare to the conventional cooperative networks. PMID:26927119

Outage Performance Analysis of Relay Selection Schemes in Wireless Energy Harvesting Cooperative Networks over Non-Identical Rayleigh Fading Channels.

PubMed

Do, Nhu Tri; Bao, Vo Nguyen Quoc; An, Beongku

2016-02-26

In this paper, we study relay selection in decode-and-forward wireless energy harvesting cooperative networks. In contrast to conventional cooperative networks, the relays harvest energy from the source's radio-frequency radiation and then use that energy to forward the source information. Considering power splitting receiver architecture used at relays to harvest energy, we are concerned with the performance of two popular relay selection schemes, namely, partial relay selection (PRS) scheme and optimal relay selection (ORS) scheme. In particular, we analyze the system performance in terms of outage probability (OP) over independent and non-identical (i.n.i.d.) Rayleigh fading channels. We derive the closed-form approximations for the system outage probabilities of both schemes and validate the analysis by the Monte-Carlo simulation. The numerical results provide comprehensive performance comparison between the PRS and ORS schemes and reveal the effect of wireless energy harvesting on the outage performances of both schemes. Additionally, we also show the advantages and drawbacks of the wireless energy harvesting cooperative networks and compare to the conventional cooperative networks.

A long-range-corrected density functional that performs well for both ground-state properties and time-dependent density functional theory excitation energies, including charge-transfer excited states.

PubMed

Rohrdanz, Mary A; Martins, Katie M; Herbert, John M

2009-02-07

We introduce a hybrid density functional that asymptotically incorporates full Hartree-Fock exchange, based on the long-range-corrected exchange-hole model of Henderson et al. [J. Chem. Phys. 128, 194105 (2008)]. The performance of this functional, for ground-state properties and for vertical excitation energies within time-dependent density functional theory, is systematically evaluated, and optimal values are determined for the range-separation parameter, omega, and for the fraction of short-range Hartree-Fock exchange. We denote the new functional as LRC-omegaPBEh, since it reduces to the standard PBEh hybrid functional (also known as PBE0 or PBE1PBE) for a certain choice of its two parameters. Upon optimization of these parameters against a set of ground- and excited-state benchmarks, the LRC-omegaPBEh functional fulfills three important requirements: (i) It outperforms the PBEh hybrid functional for ground-state atomization energies and reaction barrier heights; (ii) it yields statistical errors comparable to PBEh for valence excitation energies in both small and medium-sized molecules; and (iii) its performance for charge-transfer excitations is comparable to its performance for valence excitations. LRC-omegaPBEh, with the parameters determined herein, is the first density functional that satisfies all three criteria. Notably, short-range Hartree-Fock exchange appears to be necessary in order to obtain accurate ground-state properties and vertical excitation energies using the same value of omega.

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

PubMed

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

2016-06-01

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

Influence of Structural Parameters on the Performance of Vortex Valve Variable-Thrust Solid Rocket Motor

NASA Astrophysics Data System (ADS)

Wei, Xianggeng; Li, Jiang; He, Guoqiang

2017-04-01

The vortex valve solid variable thrust motor is a new solid motor which can achieve Vehicle system trajectory optimization and motor energy management. Numerical calculation was performed to investigate the influence of vortex chamber diameter, vortex chamber shape, and vortex chamber height of the vortex valve solid variable thrust motor on modulation performance. The test results verified that the calculation results are consistent with laboratory results with a maximum error of 9.5%. The research drew the following major conclusions: the optimal modulation performance was achieved in a cylindrical vortex chamber, increasing the vortex chamber diameter improved the modulation performance of the vortex valve solid variable thrust motor, optimal modulation performance could be achieved when the height of the vortex chamber is half of the vortex chamber outlet diameter, and the hot gas control flow could result in an enhancement of modulation performance. The results can provide the basis for establishing the design method of the vortex valve solid variable thrust motor.

Reference Model MHK Turbine Array Optimization Study within a Generic River System.

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

Johnson, Erick; Barco Mugg, Janet; James, Scott

2011-12-01

Increasing interest in marine hydrokinetic (MHK) energy has spurred to significant research on optimal placement of emerging technologies to maximize energy conversion and minimize potential effects on the environment. However, these devices will be deployed as an array in order to reduce the cost of energy and little work has been done to understand the impact these arrays will have on the flow dynamics, sediment-bed transport and benthic habitats and how best to optimize these arrays for both performance and environmental considerations. An "MHK-friendly" routine has been developed and implemented by Sandia National Laboratories (SNL) into the flow, sediment dynamicsmore » and water-quality code, SNL-EFDC. This routine has been verified and validated against three separate sets of experimental data. With SNL-EFDC, water quality and array optimization studies can be carried out to optimize an MHK array in a resource and study its effects on the environment. The present study examines the effect streamwise and spanwise spacing has on the array performance. Various hypothetical MHK array configurations are simulated within a trapezoidal river channel. Results show a non-linear increase in array-power efficiency as turbine spacing is increased in each direction, which matches the trends seen experimentally. While the sediment transport routines were not used in these simulations, the flow acceleration seen around the MHK arrays has the potential to significantly affect the sediment transport characteristics and benthic habitat of a resource. Evaluation Only. Created with Aspose.Pdf.Kit. Copyright 2002-2011 Aspose Pty Ltd Evaluation Only. Created with Aspose.Pdf.Kit. Copyright 2002-2011 Aspose Pty Ltd« less

High-power-density, high-energy-density fluorinated graphene for primary lithium batteries

NASA Astrophysics Data System (ADS)

Zhong, Guiming; Chen, Huixin; Huang, Xingkang; Yue, Hongjun; Lu, Canzhong

2018-03-01

Li/CFx is one of the highest-energy-density primary batteries; however, poor rate capability hinders its practical applications in high-power devices. Here we report a preparation of fluorinated graphene (GFx) with superior performance through a direct gas fluorination. We find that the so-called “semi-ionic” C-F bond content in all C-F bonds presents a more critical impact on rate performance of the GFx in comparison with sp2 C content in the GFx, morphology, structure, and specific surface area of the materials. The rate capability remains excellent before the semi-ionic C-F bond proportion in the GFx decreases. Thus, by optimizing semi-ionic C-F content in our GFx, we obtain the optimal x of 0.8, with which the GF0.8 exhibits a very high energy density of 1073 Wh kg-1 and an excellent power density of 21460 W kg-1 at a high current density of 10 A g-1. More importantly, our approach opens a new avenue to obtain fluorinated carbon with high energy densities without compromising high power densities.

Commande optimale minimisant la consommation d'energie d'un drone utilise comme relai de communication

NASA Astrophysics Data System (ADS)

Mechirgui, Monia

The purpose of this project is to implement an optimal control regulator, particularly the linear quadratic regulator in order to control the position of an unmanned aerial vehicle known as a quadrotor. This type of UAV has a symmetrical and simple structure. Thus, its control is relatively easy compared to conventional helicopters. Optimal control can be proven to be an ideal controller to reconcile between the tracking performance and energy consumption. In practice, the linearity requirements are not met, but some elaborations of the linear quadratic regulator have been used in many nonlinear applications with good results. The linear quadratic controller used in this thesis is presented in two forms: simple and adapted to the state of charge of the battery. Based on the traditional structure of the linear quadratic regulator, we introduced a new criterion which relies on the state of charge of the battery, in order to optimize energy consumption. This command is intended to be used to monitor and maintain the desired trajectory during several maneuvers while minimizing energy consumption. Both simple and adapted, linear quadratic controller are implemented in Simulink in discrete time. The model simulates the dynamics and control of a quadrotor. Performance and stability of the system are analyzed with several tests, from the simply hover to the complex trajectories in closed loop.

AMMOS2: a web server for protein-ligand-water complexes refinement via molecular mechanics.

PubMed

Labbé, Céline M; Pencheva, Tania; Jereva, Dessislava; Desvillechabrol, Dimitri; Becot, Jérôme; Villoutreix, Bruno O; Pajeva, Ilza; Miteva, Maria A

2017-07-03

AMMOS2 is an interactive web server for efficient computational refinement of protein-small organic molecule complexes. The AMMOS2 protocol employs atomic-level energy minimization of a large number of experimental or modeled protein-ligand complexes. The web server is based on the previously developed standalone software AMMOS (Automatic Molecular Mechanics Optimization for in silico Screening). AMMOS utilizes the physics-based force field AMMP sp4 and performs optimization of protein-ligand interactions at five levels of flexibility of the protein receptor. The new version 2 of AMMOS implemented in the AMMOS2 web server allows the users to include explicit water molecules and individual metal ions in the protein-ligand complexes during minimization. The web server provides comprehensive analysis of computed energies and interactive visualization of refined protein-ligand complexes. The ligands are ranked by the minimized binding energies allowing the users to perform additional analysis for drug discovery or chemical biology projects. The web server has been extensively tested on 21 diverse protein-ligand complexes. AMMOS2 minimization shows consistent improvement over the initial complex structures in terms of minimized protein-ligand binding energies and water positions optimization. The AMMOS2 web server is freely available without any registration requirement at the URL: http://drugmod.rpbs.univ-paris-diderot.fr/ammosHome.php. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

AMMOS2: a web server for protein–ligand–water complexes refinement via molecular mechanics

PubMed Central

Labbé, Céline M.; Pencheva, Tania; Jereva, Dessislava; Desvillechabrol, Dimitri; Becot, Jérôme; Villoutreix, Bruno O.; Pajeva, Ilza

2017-01-01

Abstract AMMOS2 is an interactive web server for efficient computational refinement of protein–small organic molecule complexes. The AMMOS2 protocol employs atomic-level energy minimization of a large number of experimental or modeled protein–ligand complexes. The web server is based on the previously developed standalone software AMMOS (Automatic Molecular Mechanics Optimization for in silico Screening). AMMOS utilizes the physics-based force field AMMP sp4 and performs optimization of protein–ligand interactions at five levels of flexibility of the protein receptor. The new version 2 of AMMOS implemented in the AMMOS2 web server allows the users to include explicit water molecules and individual metal ions in the protein–ligand complexes during minimization. The web server provides comprehensive analysis of computed energies and interactive visualization of refined protein–ligand complexes. The ligands are ranked by the minimized binding energies allowing the users to perform additional analysis for drug discovery or chemical biology projects. The web server has been extensively tested on 21 diverse protein–ligand complexes. AMMOS2 minimization shows consistent improvement over the initial complex structures in terms of minimized protein–ligand binding energies and water positions optimization. The AMMOS2 web server is freely available without any registration requirement at the URL: http://drugmod.rpbs.univ-paris-diderot.fr/ammosHome.php. PMID:28486703

Superconducting High Energy Resolution Gamma-ray Spectrometers

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

Chow, D T

2002-02-22

We have demonstrated that a bulk absorber coupled to a TES can serve as a good gamma-ray spectrometer. Our measured energy resolution of 70 eV at 60 keV is among the best measurements in this field. We have also shown excellent agreement between the noise predictions and measured noise. Despite this good result, we noted that our detector design has shortcomings with a low count rate and vulnerabilities with the linearity of energy response. We addressed these issues by implementation of an active negative feedback bias. We demonstrated the effects of active bias such as additional pulse shortening, reduction ofmore » TES change in temperature during a pulse, and linearization of energy response at low energy. Linearization at higher energy is possible with optimized heat capacities and thermal conductivities of the microcalorimeter. However, the current fabrication process has low control and repeatability over the thermal properties. Thus, optimization of the detector performance is difficult until the fabrication process is improved. Currently, several efforts are underway to better control the fabrication of our gamma-ray spectrometers. We are developing a full-wafer process to produce TES films. We are investigating the thermal conductivity and surface roughness of thicker SiN membranes. We are exploring alternative methods to couple the absorber to the TES film for reproducibility. We are also optimizing the thermal conductivities within the detector to minimize two-element phonon noise. We are experimenting with different absorber materials to optimize absorption efficiency and heat capacity. We are also working on minimizing Johnson noise from the E S shunt and SQUID amplifier noise. We have shown that our performance, noise, and active bias models agree very well with measured data from several microcalorimeters. Once the fabrication improvements have been implemented, we have no doubt that our gamma-ray spectrometer will achieve even more spectacular results.« less

A two-hop based adaptive routing protocol for real-time wireless sensor networks.

PubMed

Rachamalla, Sandhya; Kancherla, Anitha Sheela

2016-01-01

One of the most important and challenging issues in wireless sensor networks (WSNs) is to optimally manage the limited energy of nodes without degrading the routing efficiency. In this paper, we propose an energy-efficient adaptive routing mechanism for WSNs, which saves energy of nodes by removing the much delayed packets without degrading the real-time performance of the used routing protocol. It uses the adaptive transmission power algorithm which is based on the attenuation of the wireless link to improve the energy efficiency. The proposed routing mechanism can be associated with any geographic routing protocol and its performance is evaluated by integrating with the well known two-hop based real-time routing protocol, PATH and the resulting protocol is energy-efficient adaptive routing protocol (EE-ARP). The EE-ARP performs well in terms of energy consumption, deadline miss ratio, packet drop and end-to-end delay.

Spectral optimization for micro-CT

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

Hupfer, Martin; Nowak, Tristan; Brauweiler, Robert

2012-06-15

Purpose: To optimize micro-CT protocols with respect to x-ray spectra and thereby reduce radiation dose at unimpaired image quality. Methods: Simulations were performed to assess image contrast, noise, and radiation dose for different imaging tasks. The figure of merit used to determine the optimal spectrum was the dose-weighted contrast-to-noise ratio (CNRD). Both optimal photon energy and tube voltage were considered. Three different types of filtration were investigated for polychromatic x-ray spectra: 0.5 mm Al, 3.0 mm Al, and 0.2 mm Cu. Phantoms consisted of water cylinders of 20, 32, and 50 mm in diameter with a central insert of 9more » mm which was filled with different contrast materials: an iodine-based contrast medium (CM) to mimic contrast-enhanced (CE) imaging, hydroxyapatite to mimic bone structures, and water with reduced density to mimic soft tissue contrast. Validation measurements were conducted on a commercially available micro-CT scanner using phantoms consisting of water-equivalent plastics. Measurements on a mouse cadaver were performed to assess potential artifacts like beam hardening and to further validate simulation results. Results: The optimal photon energy for CE imaging was found at 34 keV. For bone imaging, optimal energies were 17, 20, and 23 keV for the 20, 32, and 50 mm phantom, respectively. For density differences, optimal energies varied between 18 and 50 keV for the 20 and 50 mm phantom, respectively. For the 32 mm phantom and density differences, CNRD was found to be constant within 2.5% for the energy range of 21-60 keV. For polychromatic spectra and CMs, optimal settings were 50 kV with 0.2 mm Cu filtration, allowing for a dose reduction of 58% compared to the optimal setting for 0.5 mm Al filtration. For bone imaging, optimal tube voltages were below 35 kV. For soft tissue imaging, optimal tube settings strongly depended on phantom size. For 20 mm, low voltages were preferred. For 32 mm, CNRD was found to be almost independent of tube voltage. For 50 mm, voltages larger than 50 kV were preferred. For all three phantom sizes stronger filtration led to notable dose reduction for soft tissue imaging. Validation measurements were found to match simulations well, with deviations being less than 10%. Mouse measurements confirmed simulation results. Conclusions: Optimal photon energies and tube settings strongly depend on both phantom size and imaging task at hand. For in vivo CE imaging and density differences, strong filtration and voltages of 50-65 kV showed good overall results. For soft tissue imaging of animals the size of a rat or larger, voltages higher than 65 kV allow to greatly reduce scan times while maintaining dose efficiency. For imaging of bone structures, usage of only minimum filtration and low tube voltages of 40 kV and below allow exploiting the high contrast of bone at very low energies. Therefore, a combination of two filtrations could prove beneficial for micro-CT: a soft filtration allowing for bone imaging at low voltages, and a variable stronger filtration (e.g., 0.2 mm Cu) for soft tissue and contrast-enhanced imaging.« less

Life cycle assessment of biodiesel production from algal bio-crude oils extracted under subcritical water conditions.

PubMed

Ponnusamy, Sundaravadivelnathan; Reddy, Harvind Kumar; Muppaneni, Tapaswy; Downes, Cara Meghan; Deng, Shuguang

2014-10-01

A life cycle assessment study is performed for the energy requirements and greenhouse gas emissions in an algal biodiesel production system. Subcritical water (SCW) extraction was applied for extracting bio-crude oil from algae, and conventional transesterification method was used for converting the algal oil to biodiesel. 58MJ of energy is required to produce 1kg of biodiesel without any co-products management, of which 36% was spent on cultivation and 56% on lipid extraction. SCW extraction with thermal energy recovery reduces the energy consumption by 3-5 folds when compared to the traditional solvent extraction. It is estimated that 1kg of algal biodiesel fixes about 0.6kg of CO2. An optimized case considering the energy credits from co-products could further reduce the total energy demand. The energy demand for producing 1kg of biodiesel in the optimized case is 28.23MJ. Copyright © 2014 Elsevier Ltd. All rights reserved.

A Framework for Optimizing the Placement of Tidal Turbines

NASA Astrophysics Data System (ADS)

Nelson, K. S.; Roberts, J.; Jones, C.; James, S. C.

2013-12-01

Power generation with marine hydrokinetic (MHK) current energy converters (CECs), often in the form of underwater turbines, is receiving growing global interest. Because of reasonable investment, maintenance, reliability, and environmental friendliness, this technology can contribute to national (and global) energy markets and is worthy of research investment. Furthermore, in remote areas, small-scale MHK energy from river, tidal, or ocean currents can provide a local power supply. However, little is known about the potential environmental effects of CEC operation in coastal embayments, estuaries, or rivers, or of the cumulative impacts of these devices on aquatic ecosystems over years or decades of operation. There is an urgent need for practical, accessible tools and peer-reviewed publications to help industry and regulators evaluate environmental impacts and mitigation measures, while establishing best sitting and design practices. Sandia National Laboratories (SNL) and Sea Engineering, Inc. (SEI) have investigated the potential environmental impacts and performance of individual tidal energy converters (TECs) in Cobscook Bay, ME; TECs are a subset of CECs that are specifically deployed in tidal channels. Cobscook Bay is the first deployment location of Ocean Renewable Power Company's (ORPC) TidGenTM unit. One unit is currently in place with four more to follow. Together, SNL and SEI built a coarse-grid, regional-scale model that included Cobscook Bay and all other landward embayments using the modeling platform SNL-EFDC. Within SNL-EFDC tidal turbines are represented using a unique set of momentum extraction, turbulence generation, and turbulence dissipation equations at TEC locations. The global model was then coupled to a local-scale model that was centered on the proposed TEC deployment locations. An optimization frame work was developed that used the refined model to determine optimal device placement locations that maximized array performance. Within the framework, environmental effects are considered to minimize the possibility of altering flows to an extent that would affect fish-swimming behavior and sediment-transport trends. Simulation results were compared between model runs with the optimized array configuration, and the originally purposed deployment locations; the optimized array showed a 17% increase in power generation. The developed framework can provide regulators and developers with a tool for assessing environmental impacts and device-performance parameters for the deployment of MHK devices. The more thoroughly understood this promising technology, the more likely it will become a viable source of alternative energy.

An enhanced performance through agent-based secure approach for mobile ad hoc networks

NASA Astrophysics Data System (ADS)

Bisen, Dhananjay; Sharma, Sanjeev

2018-01-01

This paper proposes an agent-based secure enhanced performance approach (AB-SEP) for mobile ad hoc network. In this approach, agent nodes are selected through optimal node reliability as a factor. This factor is calculated on the basis of node performance features such as degree difference, normalised distance value, energy level, mobility and optimal hello interval of node. After selection of agent nodes, a procedure of malicious behaviour detection is performed using fuzzy-based secure architecture (FBSA). To evaluate the performance of the proposed approach, comparative analysis is done with conventional schemes using performance parameters such as packet delivery ratio, throughput, total packet forwarding, network overhead, end-to-end delay and percentage of malicious detection.

Energy-efficient container handling using hybrid model predictive control

NASA Astrophysics Data System (ADS)

Xin, Jianbin; Negenborn, Rudy R.; Lodewijks, Gabriel

2015-11-01

The performance of container terminals needs to be improved to adapt the growth of containers while maintaining sustainability. This paper provides a methodology for determining the trajectory of three key interacting machines for carrying out the so-called bay handling task, involving transporting containers between a vessel and the stacking area in an automated container terminal. The behaviours of the interacting machines are modelled as a collection of interconnected hybrid systems. Hybrid model predictive control (MPC) is proposed to achieve optimal performance, balancing the handling capacity and energy consumption. The underlying control problem is hereby formulated as a mixed-integer linear programming problem. Simulation studies illustrate that a higher penalty on energy consumption indeed leads to improved sustainability using less energy. Moreover, simulations illustrate how the proposed energy-efficient hybrid MPC controller performs under different types of uncertainties.

Optimizing cosmological surveys in a crowded market

NASA Astrophysics Data System (ADS)

Bassett, Bruce A.

2005-04-01

Optimizing the major next-generation cosmological surveys (such as SNAP, KAOS, etc.) is a key problem given our ignorance of the physics underlying cosmic acceleration and the plethora of surveys planned. We propose a Bayesian design framework which (1) maximizes the discrimination power of a survey without assuming any underlying dark-energy model, (2) finds the best niche survey geometry given current data and future competing experiments, (3) maximizes the cross section for serendipitous discoveries and (4) can be adapted to answer specific questions (such as “is dark energy dynamical?”). Integrated parameter-space optimization (IPSO) is a design framework that integrates projected parameter errors over an entire dark energy parameter space and then extremizes a figure of merit (such as Shannon entropy gain which we show is stable to off-diagonal covariance matrix perturbations) as a function of survey parameters using analytical, grid or MCMC techniques. We discuss examples where the optimization can be performed analytically. IPSO is thus a general, model-independent and scalable framework that allows us to appropriately use prior information to design the best possible surveys.

Direct Optimal Control of Duffing Dynamics

NASA Technical Reports Server (NTRS)

Oz, Hayrani; Ramsey, John K.

2002-01-01

The "direct control method" is a novel concept that is an attractive alternative and competitor to the differential-equation-based methods. The direct method is equally well applicable to nonlinear, linear, time-varying, and time-invariant systems. For all such systems, the method yields explicit closed-form control laws based on minimization of a quadratic control performance measure. We present an application of the direct method to the dynamics and optimal control of the Duffing system where the control performance measure is not restricted to a quadratic form and hence may include a quartic energy term. The results we present in this report also constitute further generalizations of our earlier work in "direct optimal control methodology." The approach is demonstrated for the optimal control of the Duffing equation with a softening nonlinear stiffness.

Enhanced Particle Swarm Optimization Algorithm: Efficient Training of ReaxFF Reactive Force Fields.

PubMed

Furman, David; Carmeli, Benny; Zeiri, Yehuda; Kosloff, Ronnie

2018-06-12

Particle swarm optimization (PSO) is a powerful metaheuristic population-based global optimization algorithm. However, when it is applied to nonseparable objective functions, its performance on multimodal landscapes is significantly degraded. Here we show that a significant improvement in the search quality and efficiency on multimodal functions can be achieved by enhancing the basic rotation-invariant PSO algorithm with isotropic Gaussian mutation operators. The new algorithm demonstrates superior performance across several nonlinear, multimodal benchmark functions compared with the rotation-invariant PSO algorithm and the well-established simulated annealing and sequential one-parameter parabolic interpolation methods. A search for the optimal set of parameters for the dispersion interaction model in the ReaxFF- lg reactive force field was carried out with respect to accurate DFT-TS calculations. The resulting optimized force field accurately describes the equations of state of several high-energy molecular crystals where such interactions are of crucial importance. The improved algorithm also presents better performance compared to a genetic algorithm optimization method in the optimization of the parameters of a ReaxFF- lg correction model. The computational framework is implemented in a stand-alone C++ code that allows the straightforward development of ReaxFF reactive force fields.

Exhaust emission reduction for intermittent combustion aircraft engines

NASA Technical Reports Server (NTRS)

Moffett, R. N.

1979-01-01

Three concepts for optimizing the performance, increasing the fuel economy, and reducing exhaust emission of the piston aircraft engine were investigated. High energy-multiple spark discharge and spark plug tip penetration, ultrasonic fuel vaporization, and variable valve timing were evaluated individually. Ultrasonic fuel vaporization did not demonstrate sufficient improvement in distribution to offset the performance loss caused by the additional manifold restriction. High energy ignition and revised spark plug tip location provided no change in performance or emissions. Variable valve timing provided some performance benefit; however, even greater performance improvement was obtained through induction system tuning which could be accomplished with far less complexity.

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

PubMed

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

2016-12-01

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

Inverse problem and variation method to optimize cascade heat exchange network in central heating system

NASA Astrophysics Data System (ADS)

Zhang, Yin; Wei, Zhiyuan; Zhang, Yinping; Wang, Xin

2017-12-01

Urban heating in northern China accounts for 40% of total building energy usage. In central heating systems, heat is often transferred from heat source to users by the heat network where several heat exchangers are installed at heat source, substations and terminals respectively. For given overall heating capacity and heat source temperature, increasing the terminal fluid temperature is an effective way to improve the thermal performance of such cascade heat exchange network for energy saving. In this paper, the mathematical optimization model of the cascade heat exchange network with three-stage heat exchangers in series is established. Aim at maximizing the cold fluid temperature for given hot fluid temperature and overall heating capacity, the optimal heat exchange area distribution and the medium fluids' flow rates are determined through inverse problem and variation method. The preliminary results show that the heat exchange areas should be distributed equally for each heat exchanger. It also indicates that in order to improve the thermal performance of the whole system, more heat exchange areas should be allocated to the heat exchanger where flow rate difference between two fluids is relatively small. This work is important for guiding the optimization design of practical cascade heating systems.

Modeling and optimization of actively Q-switched Nd-doped quasi-three-level laser

NASA Astrophysics Data System (ADS)

Yan, Renpeng; Yu, Xin; Li, Xudong; Chen, Deying; Gao, Jing

2013-09-01

The energy transfer upconversion and the ground state absorption are considered in solving the rate equations for an active Q-switched quasi-three-level laser. The dependence of output pulse characters on the laser parameters is investigated by solving the rate equations. The influence of the energy transfer upconversion on the pulsed laser performance is illustrated and discussed. By this model, the optimal parameters could be achieved for arbitrary quasi-three-level Q-switched lasers. An acousto-optical Q-switched Nd:YAG 946 nm laser is constructed and the reliability of the theoretical model is demonstrated.

Battery Storage Evaluation Tool, version 1.x

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

2015-10-02

The battery storage evaluation tool developed at Pacific Northwest National Laboratory is used to run a one-year simulation to evaluate the benefits of battery storage for multiple grid applications, including energy arbitrage, balancing service, capacity value, distribution system equipment deferral, and outage mitigation. This tool is based on the optimal control strategies to capture multiple services from a single energy storage device. In this control strategy, at each hour, a lookahead optimization is first formulated and solved to determine the battery base operating point. The minute-by-minute simulation is then performed to simulate the actual battery operation.

Comparison of stochastic optimization methods for all-atom folding of the Trp-Cage protein.

PubMed

Schug, Alexander; Herges, Thomas; Verma, Abhinav; Lee, Kyu Hwan; Wenzel, Wolfgang

2005-12-09

The performances of three different stochastic optimization methods for all-atom protein structure prediction are investigated and compared. We use the recently developed all-atom free-energy force field (PFF01), which was demonstrated to correctly predict the native conformation of several proteins as the global optimum of the free energy surface. The trp-cage protein (PDB-code 1L2Y) is folded with the stochastic tunneling method, a modified parallel tempering method, and the basin-hopping technique. All the methods correctly identify the native conformation, and their relative efficiency is discussed.

Chance-Constrained AC Optimal Power Flow for Distribution Systems With Renewables

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

DallAnese, Emiliano; Baker, Kyri; Summers, Tyler

This paper focuses on distribution systems featuring renewable energy sources (RESs) and energy storage systems, and presents an AC optimal power flow (OPF) approach to optimize system-level performance objectives while coping with uncertainty in both RES generation and loads. The proposed method hinges on a chance-constrained AC OPF formulation where probabilistic constraints are utilized to enforce voltage regulation with prescribed probability. A computationally more affordable convex reformulation is developed by resorting to suitable linear approximations of the AC power-flow equations as well as convex approximations of the chance constraints. The approximate chance constraints provide conservative bounds that hold for arbitrarymore » distributions of the forecasting errors. An adaptive strategy is then obtained by embedding the proposed AC OPF task into a model predictive control framework. Finally, a distributed solver is developed to strategically distribute the solution of the optimization problems across utility and customers.« less

Performance optimization of a bendable parabolic cylinder collimating X-ray mirror for the ALS micro-XAS beamline 10.3.2

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

Yashchuk, Valeriy V.; Morrison, Gregory Y.; Marcus, Matthew A.

The Advanced Light Source (ALS) beamline (BL) 10.3.2 is an apparatus for X-ray microprobe spectroscopy and diffraction experiments, operating in the energy range 2.4–17 keV. The performance of the beamline, namely the spatial and energy resolutions of the measurements, depends significantly on the collimation quality of light incident on the monochromator. In the BL 10.3.2 end-station, the synchrotron source is imaged 1:1 onto a set of roll slits which form a virtual source. The light from this source is collimated in the vertical direction by a bendable parabolic cylinder mirror. Details are presented of the mirror design, which allows formore » precision assembly, alignment and shaping of the mirror, as well as for extending of the mirror operating lifetime by a factor of ~10. Assembly, mirror optimal shaping and preliminary alignment were performed ex situ in the ALS X-ray Optics Laboratory (XROL). Using an original method for optimal ex situ characterization and setting of bendable X-ray optics developed at the XROL, a root-mean-square (RMS) residual surface slope error of 0.31 µrad with respect to the desired parabola, and an RMS residual height error of less than 3 nm were achieved. Once in place at the beamline, deviations from the designed optical geometry ( e.g. due to the tolerances for setting the distance to the virtual source, the grazing incidence angle, the transverse position) and/or mirror shape ( e.g. due to a heat load deformation) may appear. Due to the errors, on installation the energy spread from the monochromator is typically a few electron-volts. Here, a new technique developed and successfully implemented for at-wavelength ( in situ) fine optimal tuning of the mirror, enabling us to reduce the collimation-induced energy spread to ~0.05 eV, is described.« less

Performance optimization of a bendable parabolic cylinder collimating X-ray mirror for the ALS micro-XAS beamline 10.3.2

PubMed Central

Yashchuk, Valeriy V.; Morrison, Gregory Y.; Marcus, Matthew A.; Domning, Edward E.; Merthe, Daniel J.; Salmassi, Farhad; Smith, Brian V.

2015-01-01

The Advanced Light Source (ALS) beamline (BL) 10.3.2 is an apparatus for X-ray microprobe spectroscopy and diffraction experiments, operating in the energy range 2.4–17 keV. The performance of the beamline, namely the spatial and energy resolutions of the measurements, depends significantly on the collimation quality of light incident on the monochromator. In the BL 10.3.2 end-station, the synchrotron source is imaged 1:1 onto a set of roll slits which form a virtual source. The light from this source is collimated in the vertical direction by a bendable parabolic cylinder mirror. Details are presented of the mirror design, which allows for precision assembly, alignment and shaping of the mirror, as well as for extending of the mirror operating lifetime by a factor of ∼10. Assembly, mirror optimal shaping and preliminary alignment were performed ex situ in the ALS X-ray Optics Laboratory (XROL). Using an original method for optimal ex situ characterization and setting of bendable X-ray optics developed at the XROL, a root-mean-square (RMS) residual surface slope error of 0.31 µrad with respect to the desired parabola, and an RMS residual height error of less than 3 nm were achieved. Once in place at the beamline, deviations from the designed optical geometry (e.g. due to the tolerances for setting the distance to the virtual source, the grazing incidence angle, the transverse position) and/or mirror shape (e.g. due to a heat load deformation) may appear. Due to the errors, on installation the energy spread from the monochromator is typically a few electron-volts. Here, a new technique developed and successfully implemented for at-wavelength (in situ) fine optimal tuning of the mirror, enabling us to reduce the collimation-induced energy spread to ∼0.05 eV, is described. PMID:25931083

Performance optimization of a bendable parabolic cylinder collimating X-ray mirror for the ALS micro-XAS beamline 10.3.2

DOE PAGES

Yashchuk, Valeriy V.; Morrison, Gregory Y.; Marcus, Matthew A.; ...

2015-04-08

The Advanced Light Source (ALS) beamline (BL) 10.3.2 is an apparatus for X-ray microprobe spectroscopy and diffraction experiments, operating in the energy range 2.4–17 keV. The performance of the beamline, namely the spatial and energy resolutions of the measurements, depends significantly on the collimation quality of light incident on the monochromator. In the BL 10.3.2 end-station, the synchrotron source is imaged 1:1 onto a set of roll slits which form a virtual source. The light from this source is collimated in the vertical direction by a bendable parabolic cylinder mirror. Details are presented of the mirror design, which allows formore » precision assembly, alignment and shaping of the mirror, as well as for extending of the mirror operating lifetime by a factor of ~10. Assembly, mirror optimal shaping and preliminary alignment were performed ex situ in the ALS X-ray Optics Laboratory (XROL). Using an original method for optimal ex situ characterization and setting of bendable X-ray optics developed at the XROL, a root-mean-square (RMS) residual surface slope error of 0.31 µrad with respect to the desired parabola, and an RMS residual height error of less than 3 nm were achieved. Once in place at the beamline, deviations from the designed optical geometry ( e.g. due to the tolerances for setting the distance to the virtual source, the grazing incidence angle, the transverse position) and/or mirror shape ( e.g. due to a heat load deformation) may appear. Due to the errors, on installation the energy spread from the monochromator is typically a few electron-volts. Here, a new technique developed and successfully implemented for at-wavelength ( in situ) fine optimal tuning of the mirror, enabling us to reduce the collimation-induced energy spread to ~0.05 eV, is described.« less

CaloCube: An isotropic spaceborne calorimeter for high-energy cosmic rays. Optimization of the detector performance for protons and nuclei

NASA Astrophysics Data System (ADS)

Adriani, O.; Albergo, S.; Auditore, L.; Basti, A.; Berti, E.; Bigongiari, G.; Bonechi, L.; Bonechi, S.; Bongi, M.; Bonvicini, V.; Bottai, S.; Brogi, P.; Carotenuto, G.; Castellini, G.; Cattaneo, P. W.; Daddi, N.; D'Alessandro, R.; Detti, S.; Finetti, N.; Italiano, A.; Lenzi, P.; Maestro, P.; Marrocchesi, P. S.; Mori, N.; Orzan, G.; Olmi, M.; Pacini, L.; Papini, P.; Pellegriti, M. G.; Rappoldi, A.; Ricciarini, S.; Sciuto, A.; Spillantini, P.; Starodubtsev, O.; Stolzi, F.; Suh, J. E.; Sulaj, A.; Tiberio, A.; Tricomi, A.; Trifiro', A.; Trimarchi, M.; Vannuccini, E.; Zampa, G.; Zampa, N.

2017-11-01

The direct detection of high-energy cosmic rays up to the PeV region is one of the major challenges for the next generation of space-borne cosmic-ray detectors. The physics performance will be primarily determined by their geometrical acceptance and energy resolution. CaloCube is a homogeneous calorimeter whose geometry allows an almost isotropic response, so as to detect particles arriving from every direction in space, thus maximizing the acceptance. A comparative study of different scintillating materials and mechanical structures has been performed by means of Monte Carlo simulation. The scintillation-Cherenkov dual read-out technique has been also considered and its benefit evaluated.

Aerodynamics as a subway design parameter

NASA Technical Reports Server (NTRS)

Kurtz, D. W.

1976-01-01

A parametric sensitivity study has been performed on the system operational energy requirement in order to guide subway design strategy. Aerodynamics can play a dominant or trivial role, depending upon the system characteristics. Optimization of the aerodynamic parameters may not minimize the total operational energy. Isolation of the station box from the tunnel and reduction of the inertial power requirements pay the largest dividends in terms of the operational energy requirement.

Optimization of bottom-hinged flap-type wave energy converter for a specific wave rose

NASA Astrophysics Data System (ADS)

Behzad, Hamed; Panahi, Roozbeh

2017-06-01

In this paper, we conducted a numerical analysis on the bottom-hinged flap-type Wave Energy Convertor (WEC). The basic model, implemented through the study using ANSYS-AQWA, has been validated by a three-dimensional physical model of a pitching vertical cylinder. Then, a systematic parametric assessment has been performed on stiffness, damping, and WEC direction against an incoming wave rose, resulting in an optimized flap-type WEC for a specific spot in the Persian Gulf. Here, stiffness is tuned to have a near-resonance condition considering the wave rose, while damping is modified to capture the highest energy for each device direction. Moreover, such sets of specifications have been checked at different directions to present the best combination of stiffness, damping, and device heading. It has been shown that for a real condition, including different wave heights, periods, and directions, it is very important to implement the methodology introduced here to guarantee device performance.

Recovery of water and minerals from shale gas produced water by membrane distillation crystallization.

PubMed

Kim, Junghyun; Kim, Jungwon; Hong, Seungkwan

2018-02-01

Shale gas produced water (SGPW) treatment imposes greater technical challenges because of its high concentration of various contaminants. Membrane distillation crystallization (MDC) has a great potential to manage SGPW since it is capable of recovering both water and minerals at high rates, up to near a zero liquid discharge (ZLD) condition. To evaluate the feasibility of MDC for SGPW treatment, MDC performance indicators, such as water recovery rate, solid production rate (SPR) and specific energy consumption (SEC), were systematically investigated, to our knowledge for the first time, by using actual SGPW from Eagle Ford Shale (USA). The main operating parameters including feed cross-flow velocity (CFV) and crystallization temperature (T Cr ) were optimized by performing a series of MDC experiments. The results reported that water and minerals were effectively recovered with 84% of recovery rate and 2.72 kg/m 2 day of SPR under respective optimal operating conditions. Furthermore, the scale mechanism was firstly identified as limiting factor for MDC performance degradation. Lastly, SEC of MDC was estimated to be as low as 28.2 kWh/m 3 under ideal optimal operating conditions. Our experimental observations demonstrated that MDC could sustainably and effectively recover water and mineral with low energy consumption from SGPW by optimizing operating condition. Copyright © 2017 Elsevier Ltd. All rights reserved.

Wilson Dslash Kernel From Lattice QCD Optimization

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

Joo, Balint; Smelyanskiy, Mikhail; Kalamkar, Dhiraj D.

2015-07-01

Lattice Quantum Chromodynamics (LQCD) is a numerical technique used for calculations in Theoretical Nuclear and High Energy Physics. LQCD is traditionally one of the first applications ported to many new high performance computing architectures and indeed LQCD practitioners have been known to design and build custom LQCD computers. Lattice QCD kernels are frequently used as benchmarks (e.g. 168.wupwise in the SPEC suite) and are generally well understood, and as such are ideal to illustrate several optimization techniques. In this chapter we will detail our work in optimizing the Wilson-Dslash kernels for Intel Xeon Phi, however, as we will show themore » technique gives excellent performance on regular Xeon Architecture as well.« less

Phase 1 of the First Small Power System Experiment (engineering Experiment No. 1). Volume 2: System Concept Selection. [development and testing of a solar thermal power plant

NASA Technical Reports Server (NTRS)

Holl, R. J.

1979-01-01

The development of a modular solar thermal power system for application in the 1 to 10 MWe range is presented. The system is used in remote utility applications, small communities, rural areas, and for industrial uses. Systems design and systems optimization studies are conducted which consider plant size, annual capacity factors, and startup time as variables. Investigations are performed on the energy storage requirements and type of energy storage, concentrator design and field optimization, energy transport, and power conversion subsystems. The system utilizes a Rankine cycle, an axial flow steam turbine for power conversion, and heat transfer sodium for collector fluid.

Costs and Operating Dynamics of Integrating Distributed Energy Resources in Commercial and Industrial Buildings with Electric Vehicle Charging

NASA Astrophysics Data System (ADS)

Flores, Robert Joseph

Growing concerns over greenhouse gas and pollutant emissions have increased the pressure to shift energy conversion paradigms from current forms to more sustainable methods, such as through the use of distributed energy resources (DER) at industrial and commercial buildings. This dissertation is concerned with the optimal design and dispatch of a DER system installed at an industrial or commercial building. An optimization model that accurately captures typical utility costs and the physical constraints of a combined cooling, heating, and power (CCHP) system is designed to size and operate a DER system at a building. The optimization model is then used with cooperative game theory to evaluate the financial performance of a CCHP investment. The CCHP model is then modified to include energy storage, solar powered generators, alternative fuel sources, carbon emission limits, and building interactions with public and fleet PEVs. Then, a separate plugin electric vehicle (PEV) refueling model is developed to determine the cost to operate a public Level 3 fast charging station. The CCHP design and dispatch results show the size of the building load and consistency of the thermal loads are critical to positive financial performance. While using the CCHP system to produce cooling can provide savings, heat production drives positive financial performance. When designing the DER system to reduce carbon emissions, the use of renewable fuels can allow for a gas turbine system with heat recovery to reduce carbon emissions for a large university by 67%. Further reductions require large photovoltaic installations coupled with energy storage or the ability to export electricity back to the grid if costs are to remain relatively low. When considering Level 3 fast charging equipment, demand charges at low PEV travel levels are sufficiently high to discourage adoption. Integration of the equipment can reduce demand charge costs only if the building maximum demand does not coincide with PEV refueling. Electric vehicle refueling does not typically affect DER design at low PEV travel levels, but can as electric vehicle travel increases. However, as PEV travel increases, the stochastic nature of PEV refueling disappears, and the optimization problem may become deterministic.

Data of cost-optimal solutions and retrofit design methods for school renovation in a warm climate.

PubMed

Zacà, Ilaria; Tornese, Giuliano; Baglivo, Cristina; Congedo, Paolo Maria; D'Agostino, Delia

2016-12-01

"Efficient Solutions and Cost-Optimal Analysis for Existing School Buildings" (Paolo Maria Congedo, Delia D'Agostino, Cristina Baglivo, Giuliano Tornese, Ilaria Zacà) [1] is the paper that refers to this article. It reports the data related to the establishment of several variants of energy efficient retrofit measures selected for two existing school buildings located in the Mediterranean area. In compliance with the cost-optimal analysis described in the Energy Performance of Buildings Directive and its guidelines (EU, Directive, EU 244,) [2], [3], these data are useful for the integration of renewable energy sources and high performance technical systems for school renovation. The data of cost-efficient high performance solutions are provided in tables that are explained within the following sections. The data focus on the describe school refurbishment sector to which European policies and investments are directed. A methodological approach already used in previous studies about new buildings is followed (Baglivo Cristina, Congedo Paolo Maria, D׳Agostino Delia, Zacà Ilaria, 2015; IlariaZacà, Delia D'Agostino, Paolo Maria Congedo, Cristina Baglivo; Baglivo Cristina, Congedo Paolo Maria, D'Agostino Delia, Zacà Ilaria, 2015; Ilaria Zacà, Delia D'Agostino, Paolo Maria Congedo, Cristina Baglivo, 2015; Paolo Maria Congedo, Cristina Baglivo, IlariaZacà, Delia D'Agostino,2015) [4], [5], [6], [7], [8]. The files give the cost-optimal solutions for a kindergarten (REF1) and a nursery (REF2) school located in Sanarica and Squinzano (province of Lecce Southern Italy). The two reference buildings differ for construction period, materials and systems. The eleven tables provided contain data about the localization of the buildings, geometrical features and thermal properties of the envelope, as well as the energy efficiency measures related to walls, windows, heating, cooling, dhw and renewables. Output values of energy consumption, gas emission and costs are given for a financial and a macro-economic analysis. This data article provides 288 and 96 combinations for REF1 and REF2, respectively. The output values are obtained using the software ProCasaClima 2015v.2.0.

Optimization of permeate flux produced by solar energy driven membrane distillation process using central composite design approach.

PubMed

Bouguecha, Salah T; Boubakri, Ali; Aly, Samir E; Al-Beirutty, Mohammad H; Hamdi, Mohamed M

2016-01-01

Membrane distillation (MD) is considered as a relatively high-energy requirement. To overcome this drawback, it is recommended to couple the MD process with solar energy as the renewable energy source in order to provide heat energy required to optimize its performance to produce permeate flux. In the present work, an original solar energy driven direct contact membrane distillation (DCMD) pilot plant was built and tested under actual weather conditions at Jeddah, KSA, in order to model and optimize permeate flux. The dependency of permeate flux on various operating parameters such as feed temperature (46.6-63.4°C), permeate temperature (6.6-23.4°C), feed flow rate (199-451L/h) and permeate flow rate (199-451L/h) was studied by response surface methodology based on central composite design approach. The analysis of variance (ANOVA) confirmed that all independent variables had significant influence on the model (where P-value <0.05). The high coefficient of determination (R(2) = 0.9644 and R(adj)(2) = 0.9261) obtained by ANOVA demonstrated good correlation between experimental and predicted values of the response. The optimized conditions, determined using desirability function, were T(f) = 63.4°C, Tp = 6.6°C, Q(f) = 451L/h and Q(p) = 451L/h. Under these conditions, the maximum permeate flux of 6.122 kg/m(2).h was achieved, which was close to the predicted value of 6.398 kg/m(2).h.

A novel vortex tube-based N2-expander liquefaction process for enhancing the energy efficiency of natural gas liquefaction

NASA Astrophysics Data System (ADS)

Qyyum, Muhammad Abdul; Wei, Feng; Hussain, Arif; Ali, Wahid; Sehee, Oh; Lee, Moonyong

2017-11-01

This research work unfolds a simple, safe, and environment-friendly energy efficient novel vortex tube-based natural gas liquefaction process (LNG). A vortex tube was introduced to the popular N2-expander liquefaction process to enhance the liquefaction efficiency. The process structure and condition were modified and optimized to take a potential advantage of the vortex tube on the natural gas liquefaction cycle. Two commercial simulators ANSYS® and Aspen HYSYS® were used to investigate the application of vortex tube in the refrigeration cycle of LNG process. The Computational fluid dynamics (CFD) model was used to simulate the vortex tube with nitrogen (N2) as a working fluid. Subsequently, the results of the CFD model were embedded in the Aspen HYSYS® to validate the proposed LNG liquefaction process. The proposed natural gas liquefaction process was optimized using the knowledge-based optimization (KBO) approach. The overall energy consumption was chosen as an objective function for optimization. The performance of the proposed liquefaction process was compared with the conventional N2-expander liquefaction process. The vortex tube-based LNG process showed a significant improvement of energy efficiency by 20% in comparison with the conventional N2-expander liquefaction process. This high energy efficiency was mainly due to the isentropic expansion of the vortex tube. It turned out that the high energy efficiency of vortex tube-based process is totally dependent on the refrigerant cold fraction, operating conditions as well as refrigerant cycle configurations.

[Modeling and analysis of volume conduction based on field-circuit coupling].

PubMed

Tang, Zhide; Liu, Hailong; Xie, Xiaohui; Chen, Xiufa; Hou, Deming

2012-08-01

Numerical simulations of volume conduction can be used to analyze the process of energy transfer and explore the effects of some physical factors on energy transfer efficiency. We analyzed the 3D quasi-static electric field by the finite element method, and developed A 3D coupled field-circuit model of volume conduction basing on the coupling between the circuit and the electric field. The model includes a circuit simulation of the volume conduction to provide direct theoretical guidance for energy transfer optimization design. A field-circuit coupling model with circular cylinder electrodes was established on the platform of the software FEM3.5. Based on this, the effects of electrode cross section area, electrode distance and circuit parameters on the performance of volume conduction system were obtained, which provided a basis for optimized design of energy transfer efficiency.

Developing a Shuffled Complex-Self Adaptive Hybrid Evolution (SC-SAHEL) Framework for Water Resources Management and Water-Energy System Optimization

NASA Astrophysics Data System (ADS)

Rahnamay Naeini, M.; Sadegh, M.; AghaKouchak, A.; Hsu, K. L.; Sorooshian, S.; Yang, T.

2017-12-01

Meta-Heuristic optimization algorithms have gained a great deal of attention in a wide variety of fields. Simplicity and flexibility of these algorithms, along with their robustness, make them attractive tools for solving optimization problems. Different optimization methods, however, hold algorithm-specific strengths and limitations. Performance of each individual algorithm obeys the "No-Free-Lunch" theorem, which means a single algorithm cannot consistently outperform all possible optimization problems over a variety of problems. From users' perspective, it is a tedious process to compare, validate, and select the best-performing algorithm for a specific problem or a set of test cases. In this study, we introduce a new hybrid optimization framework, entitled Shuffled Complex-Self Adaptive Hybrid EvoLution (SC-SAHEL), which combines the strengths of different evolutionary algorithms (EAs) in a parallel computing scheme, and allows users to select the most suitable algorithm tailored to the problem at hand. The concept of SC-SAHEL is to execute different EAs as separate parallel search cores, and let all participating EAs to compete during the course of the search. The newly developed SC-SAHEL algorithm is designed to automatically select, the best performing algorithm for the given optimization problem. This algorithm is rigorously effective in finding the global optimum for several strenuous benchmark test functions, and computationally efficient as compared to individual EAs. We benchmark the proposed SC-SAHEL algorithm over 29 conceptual test functions, and two real-world case studies - one hydropower reservoir model and one hydrological model (SAC-SMA). Results show that the proposed framework outperforms individual EAs in an absolute majority of the test problems, and can provide competitive results to the fittest EA algorithm with more comprehensive information during the search. The proposed framework is also flexible for merging additional EAs, boundary-handling techniques, and sampling schemes, and has good potential to be used in Water-Energy system optimal operation and management.

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.

Atomic Charge Parameters for the Finite Difference Poisson-Boltzmann Method Using Electronegativity Neutralization.

PubMed

Yang, Qingyi; Sharp, Kim A

2006-07-01

An optimization of Rappe and Goddard's charge equilibration (QEq) method of assigning atomic partial charges is described. This optimization is designed for fast and accurate calculation of solvation free energies using the finite difference Poisson-Boltzmann (FDPB) method. The optimization is performed against experimental small molecule solvation free energies using the FDPB method and adjusting Rappe and Goddard's atomic electronegativity values. Using a test set of compounds for which experimental solvation energies are available and a rather small number of parameters, very good agreement was obtained with experiment, with a mean unsigned error of about 0.5 kcal/mol. The QEq atomic partial charge assignment method can reflect the effects of the conformational changes and solvent induction on charge distribution in molecules. In the second section of the paper we examined this feature with a study of the alanine dipeptide conformations in water solvent. The different contributions to the energy surface of the dipeptide were examined and compared with the results from fixed CHARMm charge potential, which is widely used for molecular dynamics studies.

Kinetics of ultrasound-assisted extraction of antioxidant polyphenols from food by-products: Extraction and energy consumption optimization.

PubMed

Pradal, Delphine; Vauchel, Peggy; Decossin, Stéphane; Dhulster, Pascal; Dimitrov, Krasimir

2016-09-01

Ultrasound-assisted extraction (UAE) of antioxidant polyphenols from chicory grounds was studied in order to propose a suitable valorization of this food industry by-product. The main parameters influencing the extraction process were identified. A new mathematical model for multi-criteria optimization of UAE was proposed. This kinetic model permitted the following and the prediction of the yield of extracted polyphenols, the antioxidant activity of the obtained extracts and the energy consumption during the extraction process in wide ranges of temperature (20-60°C), ethanol content in the solvent (0-60% (vol.) in ethanol-water mixtures) and ultrasound power (0-100W). After experimental validation of the model, several simulations at different technological restrictions were performed to illustrate the potentiality of the model to find the optimal conditions for obtaining a given yield within minimal process duration or with minimal energy consumption. The advantage of ultrasound assistance was clearly demonstrated both for the reduction of extraction duration and for the reduction of energy consumption. Copyright © 2016 Elsevier B.V. All rights reserved.

Hierarchical image segmentation via recursive superpixel with adaptive regularity

NASA Astrophysics Data System (ADS)

Nakamura, Kensuke; Hong, Byung-Woo

2017-11-01

A fast and accurate segmentation algorithm in a hierarchical way based on a recursive superpixel technique is presented. We propose a superpixel energy formulation in which the trade-off between data fidelity and regularization is dynamically determined based on the local residual in the energy optimization procedure. We also present an energy optimization algorithm that allows a pixel to be shared by multiple regions to improve the accuracy and appropriate the number of segments. The qualitative and quantitative evaluations demonstrate that our algorithm, combining the proposed energy and optimization, outperforms the conventional k-means algorithm by up to 29.10% in F-measure. We also perform comparative analysis with state-of-the-art algorithms in the hierarchical segmentation. Our algorithm yields smooth regions throughout the hierarchy as opposed to the others that include insignificant details. Our algorithm overtakes the other algorithms in terms of balance between accuracy and computational time. Specifically, our method runs 36.48% faster than the region-merging approach, which is the fastest of the comparing algorithms, while achieving a comparable accuracy.

Wind offering in energy and reserve markets

NASA Astrophysics Data System (ADS)

Soares, T.; Pinson, P.; Morais, H.

2016-09-01

The increasing penetration of wind generation in power systems to fulfil the ambitious European targets will make wind power producers to play an even more important role in the future power system. Wind power producers are being incentivized to participate in reserve markets to increase their revenue, since currently wind turbine/farm technologies allow them to provide ancillary services. Thus, wind power producers are to develop offering strategies for participation in both energy and reserve markets, accounting for market rules, while ensuring optimal revenue. We consider a proportional offering strategy to optimally decide upon participation in both markets by maximizing expected revenue from day-ahead decisions while accounting for estimated regulation costs for failing to provide the services. An evaluation of considering the same proportional splitting of energy and reserve in both day- ahead and balancing market is performed. A set of numerical examples illustrate the behavior of such strategy. An important conclusion is that the optimal split of the available wind power between energy and reserve strongly depends upon prices and penalties on both market trading floors.

The Mechanical Design Optimization of a High Field HTS Solenoid

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

Lalitha, SL; Gupta, RC

2015-06-01

This paper describes the conceptual design optimization of a large aperture, high field (24 T at 4 K) solenoid for a 1.7 MJ superconducting magnetic energy storage device. The magnet is designed to be built entirely of second generation (2G) high temperature superconductor tape with excellent electrical and mechanical properties at the cryogenic temperatures. The critical parameters that govern the magnet performance are examined in detail through a multiphysics approach using ANSYS software. The analysis results formed the basis for the performance specification as well as the construction of the magnet.

Energy Systems Integration Facility (ESIF) Facility Stewardship Plan: Revision 2.1

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

Torres, Juan; Anderson, Art

The U.S. Department of Energy (DOE), Office of Energy Efficiency and Renewable Energy (EERE), has established the Energy Systems Integration Facility (ESIF) on the campus of the National Renewable Energy Laboratory (NREL) and has designated it as a DOE user facility. This 182,500-ft2 research facility provides state-of-the-art laboratory and support infrastructure to optimize the design and performance of electrical, thermal, fuel, and information technologies and systems at scale. This Facility Stewardship Plan provides DOE and other decision makers with information about the existing and expected capabilities of the ESIF and the expected performance metrics to be applied to ESIF operations.more » This plan is a living document that will be updated and refined throughout the lifetime of the facility.« less

Machine learning techniques for energy optimization in mobile embedded systems

NASA Astrophysics Data System (ADS)

Donohoo, Brad Kyoshi

Mobile smartphones and other portable battery operated embedded systems (PDAs, tablets) are pervasive computing devices that have emerged in recent years as essential instruments for communication, business, and social interactions. While performance, capabilities, and design are all important considerations when purchasing a mobile device, a long battery lifetime is one of the most desirable attributes. Battery technology and capacity has improved over the years, but it still cannot keep pace with the power consumption demands of today's mobile devices. This key limiter has led to a strong research emphasis on extending battery lifetime by minimizing energy consumption, primarily using software optimizations. This thesis presents two strategies that attempt to optimize mobile device energy consumption with negligible impact on user perception and quality of service (QoS). The first strategy proposes an application and user interaction aware middleware framework that takes advantage of user idle time between interaction events of the foreground application to optimize CPU and screen backlight energy consumption. The framework dynamically classifies mobile device applications based on their received interaction patterns, then invokes a number of different power management algorithms to adjust processor frequency and screen backlight levels accordingly. The second strategy proposes the usage of machine learning techniques to learn a user's mobile device usage pattern pertaining to spatiotemporal and device contexts, and then predict energy-optimal data and location interface configurations. By learning where and when a mobile device user uses certain power-hungry interfaces (3G, WiFi, and GPS), the techniques, which include variants of linear discriminant analysis, linear logistic regression, non-linear logistic regression, and k-nearest neighbor, are able to dynamically turn off unnecessary interfaces at runtime in order to save energy.

A New Approach to Design Autonomous Wireless Sensor Node Based on RF Energy Harvesting System

PubMed Central

Hakem, Nadir

2018-01-01

Energy Harvesting techniques are increasingly seen as the solution for freeing the wireless sensor nodes from their battery dependency. However, it remains evident that network performance features, such as network size, packet length, and duty cycle, are influenced by the sum of recovered energy. This paper proposes a new approach to defining the specifications of a stand-alone wireless node based on a Radio-frequency Energy Harvesting System (REHS). To achieve adequate performance regarding the range of the Wireless Sensor Network (WSN), techniques for minimizing the energy consumed by the sensor node are combined with methods for optimizing the performance of the REHS. For more rigor in the design of the autonomous node, a comprehensive energy model of the node in a wireless network is established. For an equitable distribution of network charges between the different nodes that compose it, the Low-Energy Adaptive Clustering Hierarchy (LEACH) protocol is used for this purpose. The model considers five energy-consumption sources, most of which are ignored in recently used models. By using the hardware parameters of commercial off-the-shelf components (Mica2 Motes and CC2520 of Texas Instruments), the energy requirement of a sensor node is quantified. A miniature REHS based on a judicious choice of rectifying diodes is then designed and developed to achieve optimal performance in the Industrial Scientific and Medical (ISM) band centralized at 2.45 GHz. Due to the mismatch between the REHS and the antenna, a band pass filter is designed to reduce reflection losses. A gradient method search is used to optimize the output characteristics of the adapted REHS. At 1 mW of input RF power, the REHS provides an output DC power of 0.57 mW and a comparison with the energy requirement of the node allows the Base Station (BS) to be located at 310 m from the wireless nodes when the Wireless Sensor Network (WSN) has 100 nodes evenly spread over an area of 300 × 300 m2 and when each round lasts 10 min. The result shows that the range of the autonomous WSN increases when the controlled physical phenomenon varies very slowly. Having taken into account all the dissipation sources coexisting in a sensor node and using actual measurements of an REHS, this work provides the guidelines for the design of autonomous nodes based on REHS. PMID:29304002

A Method to Determine Supply Voltage of Permanent Magnet Motor at Optimal Design Stage

NASA Astrophysics Data System (ADS)

Matustomo, Shinya; Noguchi, So; Yamashita, Hideo; Tanimoto, Shigeya

The permanent magnet motors (PM motors) are widely used in electrical machinery, such as air conditioner, refrigerator and so on. In recent years, from the point of view of energy saving, it is necessary to improve the efficiency of PM motor by optimization. However, in the efficiency optimization of PM motor, many design variables and many restrictions are required. In this paper, the efficiency optimization of PM motor with many design variables was performed by using the voltage driven finite element analysis with the rotating simulation of the motor and the genetic algorithm.

Optimization of Perfect Absorbers with Multilayer Structures

NASA Astrophysics Data System (ADS)

Li Voti, Roberto

2018-02-01

We study wide-angle and broadband perfect absorbers with compact multilayer structures made of a sequence of ITO and TiN layers deposited onto a silver thick layer. An optimization procedure is introduced for searching the optimal thicknesses of the layers so as to design a perfect broadband absorber from 400 nm to 750 nm, for a wide range of angles of incidence from 0{°} to 50{°}, for both polarizations and with a low emissivity in the mid-infrared. We eventually compare the performances of several optimal structures that can be very promising for solar thermal energy harvesting and collectors.

Optimization methodology for the global 10 Hz orbit feedback in RHIC

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

Liu, Chuyu; Hulsart, R.; Mernick, K.

To combat beam oscillations induced by triplet vibrations at the Relativistic Heavy Ion Collider (RHIC), a global orbit feedback system was developed and applied at injection and top energy in 2011, and during beam acceleration in 2012. Singular Value Decomposition (SVD) was employed to determine the strengths and currents of the applied corrections. The feedback algorithm was optimized for different magnetic configurations (lattices) at fixed beam energies and during beam acceleration. While the orbit feedback performed well since its inception, corrector current transients and feedback-induced beam oscillations were observed during the polarized proton program in 2015. In this paper, wemore » present the feedback algorithm, the optimization of the algorithm for various lattices and the solution adopted to mitigate the observed current transients during beam acceleration.« less

Optimization methodology for the global 10 Hz orbit feedback in RHIC

DOE PAGES

Liu, Chuyu; Hulsart, R.; Mernick, K.; ...

2018-05-08

To combat beam oscillations induced by triplet vibrations at the Relativistic Heavy Ion Collider (RHIC), a global orbit feedback system was developed and applied at injection and top energy in 2011, and during beam acceleration in 2012. Singular Value Decomposition (SVD) was employed to determine the strengths and currents of the applied corrections. The feedback algorithm was optimized for different magnetic configurations (lattices) at fixed beam energies and during beam acceleration. While the orbit feedback performed well since its inception, corrector current transients and feedback-induced beam oscillations were observed during the polarized proton program in 2015. In this paper, wemore » present the feedback algorithm, the optimization of the algorithm for various lattices and the solution adopted to mitigate the observed current transients during beam acceleration.« less

Towards a framework for selection of supervisory control for commercial buildings: HVAC system energy efficiency

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

Ramachandran, Thiagarajan; Kundu, Soumya; Chen, Yan

This paper develops and utilizes an optimization based framework to investigate the maximal energy efficiency potentially attainable by HVAC system operation in a non-predictive context. Performance is evaluated relative to the existing state of the art set point reset strategies. The expected efficiency increase driven by operation constraints relaxations is evaluated.

Towards a framework for selection of supervisory control for commercial buildings: HVAC system energy efficiency

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

Ramachandran, Thiagarajan; Kundu, Soumya; Chen, Yan

This paper develops and utilizes an optimization based framework to investigate the maximal energy efficiency potentially attainable by HVAC system operation in a non-predictive context. Performance is evaluated relative to the existing state of the art set-point reset strategies. The expected efficiency increase driven by operation constraints relaxations is evaluated.

Ceramic Integration Technologies for Energy and Aerospace Applications

NASA Technical Reports Server (NTRS)

Singh, Mrityunjay; Asthana, Ralph N.

2007-01-01

Robust and affordable integration technologies for advanced ceramics are required to improve the performance, reliability, efficiency, and durability of components, devices, and systems based on them in a wide variety of energy, aerospace, and environmental applications. Many thermochemical and thermomechanical factors including joint design, analysis, and optimization must be considered in integration of similar and dissimilar material systems.

A Maximum-Likelihood Approach to Force-Field Calibration.

PubMed

Zaborowski, Bartłomiej; Jagieła, Dawid; Czaplewski, Cezary; Hałabis, Anna; Lewandowska, Agnieszka; Żmudzińska, Wioletta; Ołdziej, Stanisław; Karczyńska, Agnieszka; Omieczynski, Christian; Wirecki, Tomasz; Liwo, Adam

2015-09-28

A new approach to the calibration of the force fields is proposed, in which the force-field parameters are obtained by maximum-likelihood fitting of the calculated conformational ensembles to the experimental ensembles of training system(s). The maximum-likelihood function is composed of logarithms of the Boltzmann probabilities of the experimental conformations, calculated with the current energy function. Because the theoretical distribution is given in the form of the simulated conformations only, the contributions from all of the simulated conformations, with Gaussian weights in the distances from a given experimental conformation, are added to give the contribution to the target function from this conformation. In contrast to earlier methods for force-field calibration, the approach does not suffer from the arbitrariness of dividing the decoy set into native-like and non-native structures; however, if such a division is made instead of using Gaussian weights, application of the maximum-likelihood method results in the well-known energy-gap maximization. The computational procedure consists of cycles of decoy generation and maximum-likelihood-function optimization, which are iterated until convergence is reached. The method was tested with Gaussian distributions and then applied to the physics-based coarse-grained UNRES force field for proteins. The NMR structures of the tryptophan cage, a small α-helical protein, determined at three temperatures (T = 280, 305, and 313 K) by Hałabis et al. ( J. Phys. Chem. B 2012 , 116 , 6898 - 6907 ), were used. Multiplexed replica-exchange molecular dynamics was used to generate the decoys. The iterative procedure exhibited steady convergence. Three variants of optimization were tried: optimization of the energy-term weights alone and use of the experimental ensemble of the folded protein only at T = 280 K (run 1); optimization of the energy-term weights and use of experimental ensembles at all three temperatures (run 2); and optimization of the energy-term weights and the coefficients of the torsional and multibody energy terms and use of experimental ensembles at all three temperatures (run 3). The force fields were subsequently tested with a set of 14 α-helical and two α + β proteins. Optimization run 1 resulted in better agreement with the experimental ensemble at T = 280 K compared with optimization run 2 and in comparable performance on the test set but poorer agreement of the calculated folding temperature with the experimental folding temperature. Optimization run 3 resulted in the best fit of the calculated ensembles to the experimental ones for the tryptophan cage but in much poorer performance on the training set, suggesting that use of a small α-helical protein for extensive force-field calibration resulted in overfitting of the data for this protein at the expense of transferability. The optimized force field resulting from run 2 was found to fold 13 of the 14 tested α-helical proteins and one small α + β protein with the correct topologies; the average structures of 10 of them were predicted with accuracies of about 5 Å C(α) root-mean-square deviation or better. Test simulations with an additional set of 12 α-helical proteins demonstrated that this force field performed better on α-helical proteins than the previous parametrizations of UNRES. The proposed approach is applicable to any problem of maximum-likelihood parameter estimation when the contributions to the maximum-likelihood function cannot be evaluated at the experimental points and the dimension of the configurational space is too high to construct histograms of the experimental distributions.

Immunity-Based Optimal Estimation Approach for a New Real Time Group Elevator Dynamic Control Application for Energy and Time Saving

PubMed Central

Baygin, Mehmet; Karakose, Mehmet

2013-01-01

Nowadays, the increasing use of group elevator control systems owing to increasing building heights makes the development of high-performance algorithms necessary in terms of time and energy saving. Although there are many studies in the literature about this topic, they are still not effective enough because they are not able to evaluate all features of system. In this paper, a new approach of immune system-based optimal estimate is studied for dynamic control of group elevator systems. The method is mainly based on estimation of optimal way by optimizing all calls with genetic, immune system and DNA computing algorithms, and it is evaluated with a fuzzy system. The system has a dynamic feature in terms of the situation of calls and the option of the most appropriate algorithm, and it also adaptively works in terms of parameters such as the number of floors and cabins. This new approach which provides both time and energy saving was carried out in real time. The experimental results comparatively demonstrate the effects of method. With dynamic and adaptive control approach in this study carried out, a significant progress on group elevator control systems has been achieved in terms of time and energy efficiency according to traditional methods. PMID:23935433

Portfolio-Scale Optimization of Customer Energy Efficiency Incentive and Marketing: Cooperative Research and Development Final Report, CRADA Number CRD-13-535

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

Brackney, Larry J.

North East utility National Grid (NGrid) is developing a portfolio-scale application of OpenStudio designed to optimize incentive and marketing expenditures for their energy efficiency (EE) programs. NGrid wishes to leverage a combination of geographic information systems (GIS), public records, customer data, and content from the Building Component Library (BCL) to form a JavaScript Object Notation (JSON) input file that is consumed by an OpenStudio-based expert system for automated model generation. A baseline model for each customer building will be automatically tuned using electricity and gas consumption data, and a set of energy conservation measures (ECMs) associated with each NGrid incentivemore » program will be applied to the model. The simulated energy performance and return on investment (ROI) will be compared with customer hurdle rates and available incentives to A) optimize the incentive required to overcome the customer hurdle rate and B) determine if marketing activity associated with the specific ECM is warranted for that particular customer. Repeated across their portfolio, this process will enable NGrid to substantially optimize their marketing and incentive expenditures, targeting those customers that will likely adopt and benefit from specific EE programs.« less

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

NASA Astrophysics Data System (ADS)

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

2017-06-01

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

Actuation Using Piezoelectric Materials: Application in Augmenters, Energy Harvesters, and Motors

NASA Technical Reports Server (NTRS)

Hasenoehrl, Jennifer

2012-01-01

Piezoelectric actuators are used in many manipulation, movement, and mobility applications as well as transducers and sensors. When used at the resonance frequencies of the piezoelectric stack, the actuator performs at its maximum actuation capability. In this Space Grant internship, three applications of piezoelectric actuators were investigated including hammering augmenters of rotary drills, energy harvesters, and piezo-motors. The augmenter shows improved drill performance over rotation only. The energy harvesters rely on moving fluid to convert mechanical energy into electrical power. Specific designs allow the harvesters more freedom to move, which creates more power. The motor uses the linear movement of the actuator with a horn applied to the side of a rotor to create rotational motion. Friction inhibits this motion and is to be minimized for best performance. Tests and measurements were made during this internship to determine the requirements for optimal performance of the studied mechanisms and devices.

Optimal cycling time trial position models: aerodynamics versus power output and metabolic energy.

PubMed

Fintelman, D M; Sterling, M; Hemida, H; Li, F-X

2014-06-03

The aerodynamic drag of a cyclist in time trial (TT) position is strongly influenced by the torso angle. While decreasing the torso angle reduces the drag, it limits the physiological functioning of the cyclist. Therefore the aims of this study were to predict the optimal TT cycling position as function of the cycling speed and to determine at which speed the aerodynamic power losses start to dominate. Two models were developed to determine the optimal torso angle: a 'Metabolic Energy Model' and a 'Power Output Model'. The Metabolic Energy Model minimised the required cycling energy expenditure, while the Power Output Model maximised the cyclists׳ power output. The input parameters were experimentally collected from 19 TT cyclists at different torso angle positions (0-24°). The results showed that for both models, the optimal torso angle depends strongly on the cycling speed, with decreasing torso angles at increasing speeds. The aerodynamic losses outweigh the power losses at cycling speeds above 46km/h. However, a fully horizontal torso is not optimal. For speeds below 30km/h, it is beneficial to ride in a more upright TT position. The two model outputs were not completely similar, due to the different model approaches. The Metabolic Energy Model could be applied for endurance events, while the Power Output Model is more suitable in sprinting or in variable conditions (wind, undulating course, etc.). It is suggested that despite some limitations, the models give valuable information about improving the cycling performance by optimising the TT cycling position. Copyright © 2014 Elsevier Ltd. All rights reserved.

Performance Analysis of Solar-Wind-Diesel-Battery Hybrid Energy System for KLIA Sepang Station of Malaysia

NASA Astrophysics Data System (ADS)

Shezan, S. K. A.; Saidur, R.; Hossain, A.; Chong, W. T.; Kibria, M. A.

2015-09-01

A large number of populations of the world live in rural or remote areas those are geographically isolated. Power supply and uninterrupted fuel transportation to produce electrical power for these remote areas poses a great challenge. Using renewable energy in hybrid energy system might be a pathway to solve this problem. Malaysia is a large hilly land with the gift of renewable energy resources. There is a good chance to utilize these renewable resources to produce electrical power and to limit the dependency on the fossil fuel as well as reduce the carbon emissions. In this perspective, a research is carried out to analyze the performance of a solar-wind-diesel-battery hybrid energy system for a remote area named “KLIA Sepang station” in the state of Selangor, Malaysia. In this study, a 56 kW hybrid energy system has been proposed that is capable to support more than 50 households and 6 shops in that area. Real time field data of solar radiation and wind speed is used for the simulation and optimization of operations using “Homer” renewable energy software. The proposed system can reduce CO2 emission by about 16 tons per year compared to diesel generator only. In the same time the Cost of energy (COE) of the optimized system is USD 5.126/kWh.The proposed hybrid energy system might be applicable for other parts of the world where the climate conditions are similar.

Outage Probability Minimization for Energy Harvesting Cognitive Radio Sensor Networks

PubMed Central

Zhang, Fan; Jing, Tao; Huo, Yan; Jiang, Kaiwei

2017-01-01

The incorporation of cognitive radio (CR) capability in wireless sensor networks yields a promising network paradigm known as CR sensor networks (CRSNs), which is able to provide spectrum efficient data communication. However, due to the high energy consumption results from spectrum sensing, as well as subsequent data transmission, the energy supply for the conventional sensor nodes powered by batteries is regarded as a severe bottleneck for sustainable operation. The energy harvesting technique, which gathers energy from the ambient environment, is regarded as a promising solution to perpetually power-up energy-limited devices with a continual source of energy. Therefore, applying the energy harvesting (EH) technique in CRSNs is able to facilitate the self-sustainability of the energy-limited sensors. The primary concern of this study is to design sensing-transmission policies to minimize the long-term outage probability of EH-powered CR sensor nodes. We formulate this problem as an infinite-horizon discounted Markov decision process and propose an ϵ-optimal sensing-transmission (ST) policy through using the value iteration algorithm. ϵ is the error bound between the ST policy and the optimal policy, which can be pre-defined according to the actual need. Moreover, for a special case that the signal-to-noise (SNR) power ratio is sufficiently high, we present an efficient transmission (ET) policy and prove that the ET policy achieves the same performance with the ST policy. Finally, extensive simulations are conducted to evaluate the performance of the proposed policies and the impaction of various network parameters. PMID:28125023

Outage Probability Minimization for Energy Harvesting Cognitive Radio Sensor Networks.

PubMed

Zhang, Fan; Jing, Tao; Huo, Yan; Jiang, Kaiwei

2017-01-24

The incorporation of cognitive radio (CR) capability in wireless sensor networks yields a promising network paradigm known as CR sensor networks (CRSNs), which is able to provide spectrum efficient data communication. However, due to the high energy consumption results from spectrum sensing, as well as subsequent data transmission, the energy supply for the conventional sensor nodes powered by batteries is regarded as a severe bottleneck for sustainable operation. The energy harvesting technique, which gathers energy from the ambient environment, is regarded as a promising solution to perpetually power-up energy-limited devices with a continual source of energy. Therefore, applying the energy harvesting (EH) technique in CRSNs is able to facilitate the self-sustainability of the energy-limited sensors. The primary concern of this study is to design sensing-transmission policies to minimize the long-term outage probability of EH-powered CR sensor nodes. We formulate this problem as an infinite-horizon discounted Markov decision process and propose an ϵ -optimal sensing-transmission (ST) policy through using the value iteration algorithm. ϵ is the error bound between the ST policy and the optimal policy, which can be pre-defined according to the actual need. Moreover, for a special case that the signal-to-noise (SNR) power ratio is sufficiently high, we present an efficient transmission (ET) policy and prove that the ET policy achieves the same performance with the ST policy. Finally, extensive simulations are conducted to evaluate the performance of the proposed policies and the impaction of various network parameters.

Spectrally Selective Mirrors with Combined Optical and Thermal Benefit for Photovoltaic Module Thermal Management

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

Slauch, Ian M.; Deceglie, Michael G.; Silverman, Timothy J.

Waste heat generated during daytime operation of a solar module will raise its temperature and reduce cell efficiency. In addition to thermalization and carrier recombination, one major source of excess heat in modules is the parasitic absorption of light with sub-bandgap energy. Parasitic absorption can be prevented if sub-bandgap radiation is reflected away from the module. We report on the design considerations and projected changes to module energy yield for photonic reflectors capable of reflecting a portion of sub-bandgap radiation while maintaining or improving transmission of light with energy greater than the semiconductor bandgap. Using a previously developed, self-consistent opto-electro-thermalmore » finite-element simulation, we calculate the total additional energy generated by a module, including various photonic reflectors, and decompose these benefits into thermal and optical effects. We show that the greatest total energy yield improvement comes from photonic mirrors designed for the outside of the glass, but that mirrors placed between the glass and the encapsulant can have significant thermal benefit. We then show that optimal photonic mirror design requires consideration of all angles of incidence, despite unequal amounts of radiation arriving at each angle. We find that optimized photonic mirrors will be omnidirectional in the sense that they have beneficial performance, regardless of the angle of incidence of radiation. By fulfilling these criteria, photonic mirrors can be used at different geographic locations or different tilt angles than their original optimization conditions with only marginal changes in performance. We show designs that improve energy output in Golden, Colorado by 3.7% over a full year. This work demonstrates the importance of considering real-world irradiance and weather conditions when designing optical structures for solar applications.« less

Spectrally Selective Mirrors with Combined Optical and Thermal Benefit for Photovoltaic Module Thermal Management

DOE PAGES

Slauch, Ian M.; Deceglie, Michael G.; Silverman, Timothy J.; ...

2018-03-02

Waste heat generated during daytime operation of a solar module will raise its temperature and reduce cell efficiency. In addition to thermalization and carrier recombination, one major source of excess heat in modules is the parasitic absorption of light with sub-bandgap energy. Parasitic absorption can be prevented if sub-bandgap radiation is reflected away from the module. We report on the design considerations and projected changes to module energy yield for photonic reflectors capable of reflecting a portion of sub-bandgap radiation while maintaining or improving transmission of light with energy greater than the semiconductor bandgap. Using a previously developed, self-consistent opto-electro-thermalmore » finite-element simulation, we calculate the total additional energy generated by a module, including various photonic reflectors, and decompose these benefits into thermal and optical effects. We show that the greatest total energy yield improvement comes from photonic mirrors designed for the outside of the glass, but that mirrors placed between the glass and the encapsulant can have significant thermal benefit. We then show that optimal photonic mirror design requires consideration of all angles of incidence, despite unequal amounts of radiation arriving at each angle. We find that optimized photonic mirrors will be omnidirectional in the sense that they have beneficial performance, regardless of the angle of incidence of radiation. By fulfilling these criteria, photonic mirrors can be used at different geographic locations or different tilt angles than their original optimization conditions with only marginal changes in performance. We show designs that improve energy output in Golden, Colorado by 3.7% over a full year. This work demonstrates the importance of considering real-world irradiance and weather conditions when designing optical structures for solar applications.« less

Capacitive Energy Extraction by Few-Layer Graphene Electrodes

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

Lian, Cheng; Zhan, Cheng; Jiang, De-en

Capacitive double-layer expansion is a promising technology to harvest energy arising from the salinity difference between freshwater and seawater. Its optimal performance requires a careful selection of the operation potentials and electrode materials. While carbonaceous materials such as graphene and various forms of activated carbons are routinely used as the electrodes, there is little knowledge on how the quantum capacitance and the electric double-layer (EDL) capacitance, which are on the same order of magnitude, affect the capacitive performance. Toward understanding that from a theoretical perspective, here we study the capacitive energy extraction with graphene electrodes as a function of themore » number of graphene layers. The classical density functional theory is joined with the electronic density functional theory to obtain the EDL and the quantum capacitance, respectively. The theoretical results show that the quantum capacitance contribution plays a dominant role in extracting energy using the single-layer graphene, but its effect diminishes as the number of graphene layers increases. The overall extracted energy is dominated by the EDL contribution beyond about four graphene layers. Electrodes with more graphene layers are able to extract more energy at low charging potential. Here, because many porous carbons have nanopores with stacked graphene layers, our theoretical predictions are useful to identify optimal operation parameters for capacitive energy extraction with porous electrodes of different wall thickness.« less

Capacitive Energy Extraction by Few-Layer Graphene Electrodes

DOE PAGES

Lian, Cheng; Zhan, Cheng; Jiang, De-en; ...

2017-06-09

Capacitive double-layer expansion is a promising technology to harvest energy arising from the salinity difference between freshwater and seawater. Its optimal performance requires a careful selection of the operation potentials and electrode materials. While carbonaceous materials such as graphene and various forms of activated carbons are routinely used as the electrodes, there is little knowledge on how the quantum capacitance and the electric double-layer (EDL) capacitance, which are on the same order of magnitude, affect the capacitive performance. Toward understanding that from a theoretical perspective, here we study the capacitive energy extraction with graphene electrodes as a function of themore » number of graphene layers. The classical density functional theory is joined with the electronic density functional theory to obtain the EDL and the quantum capacitance, respectively. The theoretical results show that the quantum capacitance contribution plays a dominant role in extracting energy using the single-layer graphene, but its effect diminishes as the number of graphene layers increases. The overall extracted energy is dominated by the EDL contribution beyond about four graphene layers. Electrodes with more graphene layers are able to extract more energy at low charging potential. Here, because many porous carbons have nanopores with stacked graphene layers, our theoretical predictions are useful to identify optimal operation parameters for capacitive energy extraction with porous electrodes of different wall thickness.« less

Colliders Come of Age in Europe: PETRA and LEP

NASA Astrophysics Data System (ADS)

Hofmann, Albert

2003-04-01

Based on the success with early electron positron rings a new generation of facilities was constructed, optimized in cost and performance. In Europe PETRA was built at DESY with many innovations: smooth vacuum chamber with small impedance, efficient multi-cell RF-cavities, an optics giving an emittance optimized for luminosity, few bunches in head-on collision, a mini-beta scheme, accurate energy calibration based on depolarization resonances. From 1978 to 1986 PETRA provided high luminosity with over 22 GeV beam energy for particle physics experiments. The next ring, LEP at CERN, was optimized for two beam energy ranges, 46 and 93 - 105 GeV for Z0 and W production and particle search. This resulted in a large circumference of 27 km and low field bending magnets which had widely spaced laminations filled with concrete. The RF-voltage was produced in Cu cavities being coupled to low loss storage cavities at the lower, and with a superconducting RF-system, exceeding 3.6 GV, at the higher energy. Superconducting low beta insertions helped to obtain a high luminosity which reached integrated values of over 2000 1/nb per day at high energy. Very important for LEP was a precise energy calibration using depolarizing resonaces and careful control of all relevant parameters. LEP operated with four experiments from 1989 to 2000.

Hydropower Generation Performance Testing at Plants in Thailand and Laos

DOE PAGES

Kern, Jamie; Hadjerioua, Boualem; Christian, Mark H.; ...

2017-04-01

An operational assessment of four hydropower plants in Southeast Asia revealed that gains in both energy production and water conservation could be achieved with little monetary investment through operational optimization efforts.

Hydropower Generation Performance Testing at Plants in Thailand and Laos

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

Kern, Jamie; Hadjerioua, Boualem; Christian, Mark H.

An operational assessment of four hydropower plants in Southeast Asia revealed that gains in both energy production and water conservation could be achieved with little monetary investment through operational optimization efforts.

Porphyrin-sensitized solar cells: systematic molecular optimization, coadsorption and cosensitization.

PubMed

Song, Heli; Liu, Qingyun; Xie, Yongshu

2018-02-15

As a promising low-cost solar energy conversion technique, dye-sensitized solar cells have undergone spectacular development since 1991. For practical applications, improvement of power conversion efficiency has always been one of the major research topics. Porphyrins are outstanding sensitizers endowed with strong sunlight harvesting ability in the visible region and multiple reaction sites available for functionalization. However, judicious molecular design in consideration of light-harvest, energy levels, operational dynamics, adsorption geometry and suppression of back reactions is specifically required for achieving excellent photovoltaic performance. This feature article highlights some of the recently developed porphyrin sensitizers, especially focusing on the systematic dye structure optimization approach in combination with coadsorption and cosensitization methods in pursuing higher efficiencies. Herein, we expect to provide more insights into the structure-performance correlation and molecular engineering strategies in a stepwise manner.

Inert gas ion source program

NASA Technical Reports Server (NTRS)

Ramsey, W. D.

1978-01-01

THe original 12 cm hexagonal magneto-electrostatic containment discharge chamber has been optimized for argon and xenon operation. Argon mass utilization efficiencies of 65 to 77 percent were achieved at keeper-plus-main discharge energy consumptions of 200 to 458 eV/ion, respectively. Xenon performance of 84 to 96 percent mass utilization was realized at 203 to 350 eV/ion. The optimization process and test results are discussed.

Energy Storage: Batteries and Fuel Cells for Exploration

NASA Technical Reports Server (NTRS)

Manzo, Michelle A.; Miller, Thomas B.; Hoberecht, Mark A.; Baumann, Eric D.

2007-01-01

NASA's Vision for Exploration requires safe, human-rated, energy storage technologies with high energy density, high specific energy and the ability to perform in a variety of unique environments. The Exploration Technology Development Program is currently supporting the development of battery and fuel cell systems that address these critical technology areas. Specific technology efforts that advance these systems and optimize their operation in various space environments are addressed in this overview of the Energy Storage Technology Development Project. These technologies will support a new generation of more affordable, more reliable, and more effective space systems.

Adaptive control schemes for improving dynamic performance of efficiency-optimized induction motor drives.

PubMed

Kumar, Navneet; Raj Chelliah, Thanga; Srivastava, S P

2015-07-01

Model Based Control (MBC) is one of the energy optimal controllers used in vector-controlled Induction Motor (IM) for controlling the excitation of motor in accordance with torque and speed. MBC offers energy conservation especially at part-load operation, but it creates ripples in torque and speed during load transition, leading to poor dynamic performance of the drive. This study investigates the opportunity for improving dynamic performance of a three-phase IM operating with MBC and proposes three control schemes: (i) MBC with a low pass filter (ii) torque producing current (iqs) injection in the output of speed controller (iii) Variable Structure Speed Controller (VSSC). The pre and post operation of MBC during load transition is also analyzed. The dynamic performance of a 1-hp, three-phase squirrel-cage IM with mine-hoist load diagram is tested. Test results are provided for the conventional field-oriented (constant flux) control and MBC (adjustable excitation) with proposed schemes. The effectiveness of proposed schemes is also illustrated for parametric variations. The test results and subsequent analysis confer that the motor dynamics improves significantly with all three proposed schemes in terms of overshoot/undershoot peak amplitude of torque and DC link power in addition to energy saving during load transitions. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Simulation of a 20-ton LiBr/H{sub 2}O absorption cooling system

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

Wardono, B.; Nelson, R.M.

The possibility of using solar energy as the main heat input for cooling systems has led to several studies of available cooling technologies that use solar energy. The results show that double-effect absorption cooling systems give relatively high performance. To further study absorption cooling systems, a computer code was developed for a double-effect lithium bromide/water (LiBr/H{sub 2}O) absorption system. To evaluate the performance, two objective functions were developed including the coefficient of performance (COP) and the system cost. Based on the system cost, an optimization to find the minimum cost was performed to determine the nominal heat transfer areas ofmore » each heat exchanger. The nominal values of other system variables, such as the mass flow rates and inlet temperatures of the hot water, cooling water, and chilled water, are specified as commonly used values for commercial machines. The results of the optimization show that there are optimum heat transfer areas. In this study, hot water is used as the main energy input. Using a constant load of 20 tons cooling capacity, the effects of various variables including the heat transfer ares, mass flow rates, and inlet temperatures of hot water, cooling water, and chilled water are presented.« less

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

NASA Astrophysics Data System (ADS)

Kefayati, Mahdi; Baldick, Ross

2015-07-01

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

Simulation and optimum design of hybrid solar-wind and solar-wind-diesel power generation systems

NASA Astrophysics Data System (ADS)

Zhou, Wei

Solar and wind energy systems are considered as promising power generating sources due to its availability and topological advantages in local power generations. However, a drawback, common to solar and wind options, is their unpredictable nature and dependence on weather changes, both of these energy systems would have to be oversized to make them completely reliable. Fortunately, the problems caused by variable nature of these resources can be partially overcome by integrating these two resources in a proper combination to form a hybrid system. However, with the increased complexity in comparison with single energy systems, optimum design of hybrid system becomes more complicated. In order to efficiently and economically utilize the renewable energy resources, one optimal sizing method is necessary. This thesis developed an optimal sizing method to find the global optimum configuration of stand-alone hybrid (both solar-wind and solar-wind-diesel) power generation systems. By using Genetic Algorithm (GA), the optimal sizing method was developed to calculate the system optimum configuration which offers to guarantee the lowest investment with full use of the PV array, wind turbine and battery bank. For the hybrid solar-wind system, the optimal sizing method is developed based on the Loss of Power Supply Probability (LPSP) and the Annualized Cost of System (ACS) concepts. The optimization procedure aims to find the configuration that yields the best compromise between the two considered objectives: LPSP and ACS. The decision variables, which need to be optimized in the optimization process, are the PV module capacity, wind turbine capacity, battery capacity, PV module slope angle and wind turbine installation height. For the hybrid solar-wind-diesel system, minimization of the system cost is achieved not only by selecting an appropriate system configuration, but also by finding a suitable control strategy (starting and stopping point) of the diesel generator. The optimal sizing method was developed to find the system optimum configuration and settings that can achieve the custom-required Renewable Energy Fraction (fRE) of the system with minimum Annualized Cost of System (ACS). Du to the need for optimum design of the hybrid systems, an analysis of local weather conditions (solar radiation and wind speed) was carried out for the potential installation site, and mathematical simulation of the hybrid systems' components was also carried out including PV array, wind turbine and battery bank. By statistically analyzing the long-term hourly solar and wind speed data, Hong Kong area is found to have favorite solar and wind power resources compared with other areas, which validates the practical applications in Hong Kong and Guangdong area. Simulation of PV array performance includes three main parts: modeling of the maximum power output of the PV array, calculation of the total solar radiation on any tilted surface with any orientations, and PV module temperature predictions. Five parameters are introduced to account for the complex dependence of PV array performance upon solar radiation intensities and PV module temperatures. The developed simulation model was validated by using the field-measured data from one existing building-integrated photovoltaic system (BIPV) in Hong Kong, and good simulation performance of the model was achieved. Lead-acid batteries used in hybrid systems operate under very specific conditions, which often cause difficulties to predict when energy will be extracted from or supplied to the battery. In this thesis, the lead-acid battery performance is simulated by three different characteristics: battery state of charge (SOC), battery floating charge voltage and the expected battery lifetime. Good agreements were found between the predicted values and the field-measured data of a hybrid solar-wind project. At last, one 19.8kW hybrid solar-wind power generation project, designed by the optimal sizing method and set up to supply power for a telecommunication relay station on a remote island of Guangdong province, was studied. Simulation and experimental results about the operating performances and characteristics of the hybrid solar-wind project have demonstrated the feasibility and accuracy of the recommended optimal sizing method developed in this thesis.

Comparative study of air-conditioning energy use of four office buildings in China and USA

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

Zhou, Xin; Yan, Da; An, Jingjing

Energy use in buildings has great variability. In order to design and operate low energy buildings as well as to establish building energy codes and standards and effective energy policy, it is crucial to understand and quantify key factors influencing building energy performance. Here, this study investigates air-conditioning (AC) energy use of four office buildings in four locations: Beijing, Taiwan, Hong Kong, and Berkeley. Building simulation was employed to quantify the influences of key factors, including climate, building envelope and occupant behavior. Through simulation of various combinations of the three influencing elements, it is found that climate can lead tomore » AC cooling consumption differences by almost two times, while occupant behavior resulted in the greatest differences (of up to three times) in AC cooling consumption. The influence of occupant behavior on AC energy consumption is not homogeneous. Under similar climates, when the occupant behavior in the building differed, the optimized building envelope design also differed. In conclusion, the optimal building envelope should be determined according to the climate as well as the occupants who use the building.« less

Comparative study of air-conditioning energy use of four office buildings in China and USA

DOE PAGES

Zhou, Xin; Yan, Da; An, Jingjing; ...

2018-04-05

Energy use in buildings has great variability. In order to design and operate low energy buildings as well as to establish building energy codes and standards and effective energy policy, it is crucial to understand and quantify key factors influencing building energy performance. Here, this study investigates air-conditioning (AC) energy use of four office buildings in four locations: Beijing, Taiwan, Hong Kong, and Berkeley. Building simulation was employed to quantify the influences of key factors, including climate, building envelope and occupant behavior. Through simulation of various combinations of the three influencing elements, it is found that climate can lead tomore » AC cooling consumption differences by almost two times, while occupant behavior resulted in the greatest differences (of up to three times) in AC cooling consumption. The influence of occupant behavior on AC energy consumption is not homogeneous. Under similar climates, when the occupant behavior in the building differed, the optimized building envelope design also differed. In conclusion, the optimal building envelope should be determined according to the climate as well as the occupants who use the building.« less

Design and Implementation of a Wireless Sensor and Actuator Network to Support the Intelligent Control of Efficient Energy Usage.

PubMed

Blanco, Jesús; García, Andrés; Morenas, Javier de Las

2018-06-09

Energy saving has become a major concern for the developed society of our days. This paper presents a Wireless Sensor and Actuator Network (WSAN) designed to provide support to an automatic intelligent system, based on the Internet of Things (IoT), which enables a responsible consumption of energy. The proposed overall system performs an efficient energetic management of devices, machines and processes, optimizing their operation to achieve a reduction in their overall energy usage at any given time. For this purpose, relevant data is collected from intelligent sensors, which are in-stalled at the required locations, as well as from the energy market through the Internet. This information is analysed to provide knowledge about energy utilization, and to improve efficiency. The system takes autonomous decisions automatically, based on the available information and the specific requirements in each case. The proposed system has been implanted and tested in a food factory. Results show a great optimization of energy efficiency and a substantial improvement on energy and costs savings.

Optimal design of a shear magnetorheological damper for turning vibration suppression

NASA Astrophysics Data System (ADS)

Zhou, Y.; Zhang, Y. L.

2013-09-01

The intelligent material, so-called magnetorheological (MR) fluid, is utilized to control turning vibration. According to the structure of a common lathe CA6140, a shear MR damper is conceived by designing its structure and magnetic circuit. The vibration suppression effect of the damper is proved with dynamic analysis and simulation. Further, the magnetic circuit of the damper is optimized with the ANSYS parametric design language (APDL). In the optimization course, the area of the magnetic circuit and the damping force are considered. After optimization, the damper’s structure and its efficiency of electrical energy consumption are improved. Additionally, a comparative study on damping forces acquired from the initial and optimal design is conducted. A prototype of the developed MR damper is fabricated and magnetic tests are performed to measure the magnetic flux intensities and the residual magnetism in four damping gaps. Then, the testing results are compared with the simulated results. Finally, the suppressing vibration experimental system is set up and cylindrical turning experiments are performed to investigate the working performance of the MR damper.

Conformal growth of Mo/Si multilayers on grating substrates using collimated ion beam sputtering

NASA Astrophysics Data System (ADS)

Voronov, D. L.; Gawlitza, P.; Cambie, R.; Dhuey, S.; Gullikson, E. M.; Warwick, T.; Braun, S.; Yashchuk, V. V.; Padmore, H. A.

2012-05-01

Deposition of multilayers on saw-tooth substrates is a key step in the fabrication of multilayer blazed gratings (MBG) for extreme ultraviolet and soft x-rays. Growth of the multilayers can be perturbed by shadowing effects caused by the highly corrugated surface of the substrates, which results in distortion of the multilayer stack structure and degradation of performance of MBGs. To minimize the shadowing effects, we used an ion-beam sputtering machine with a highly collimated atomic flux to deposit Mo/Si multilayers on saw-tooth substrates. The sputtering conditions were optimized by finding a balance between smoothening and roughening processes in order to minimize degradation of the groove profile in the course of deposition and at the same time to keep the interfaces of a multilayer stack smooth enough for high efficiency. An optimal value of energy of 200 eV for sputtering Kr+ ions was found by deposition of test multilayers on flat substrates at a range of ion energies. Two saw-tooth substrates were deposited at energies of 200 eV and 700 eV for the sputtering ions. It was found that reduction of the ion energy improved the blazing performance of the MBG and resulted in a 40% gain in the diffraction efficiency due to better replication of the groove profile by the multilayer. As a result of the optimization performed, an absolute diffraction efficiency of 28.8% was achieved for the 2nd blaze order of the MBG with a groove density of 7350 lines/mm at a wavelength of 13.5 nm. Details of the growth behavior of the multilayers on flat and saw-tooth substrates are discussed in terms of the linear continuous model of film growth.

Conformal growth of Mo/Si multilayers on grating substrates using collimated ion beam sputtering

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

Voronov, D. L.; Cambie, R.; Dhuey, S.

2012-05-01

Deposition of multilayers on saw-tooth substrates is a key step in the fabrication of multilayer blazed gratings (MBG) for extreme ultraviolet and soft x-rays. Growth of the multilayers can be perturbed by shadowing effects caused by the highly corrugated surface of the substrates, which results in distortion of the multilayer stack structure and degradation of performance of MBGs. To minimize the shadowing effects, we used an ion-beam sputtering machine with a highly collimated atomic flux to deposit Mo/Si multilayers on saw-tooth substrates. The sputtering conditions were optimized by finding a balance between smoothening and roughening processes in order to minimizemore » degradation of the groove profile in the course of deposition and at the same time to keep the interfaces of a multilayer stack smooth enough for high efficiency. An optimal value of energy of 200 eV for sputtering Kr{sup +} ions was found by deposition of test multilayers on flat substrates at a range of ion energies. Two saw-tooth substrates were deposited at energies of 200 eV and 700 eV for the sputtering ions. It was found that reduction of the ion energy improved the blazing performance of the MBG and resulted in a 40% gain in the diffraction efficiency due to better replication of the groove profile by the multilayer. As a result of the optimization performed, an absolute diffraction efficiency of 28.8% was achieved for the 2nd blaze order of the MBG with a groove density of 7350 lines/mm at a wavelength of 13.5 nm. Details of the growth behavior of the multilayers on flat and saw-tooth substrates are discussed in terms of the linear continuous model of film growth.« less

Conformal growth of Mo/Si multilayers on grating substrates using collimated ion beam sputtering

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

Voronov, D. L.; Gawlitza, Peter; Cambie, Rossana

2012-05-07

Deposition of multilayers on saw-tooth substrates is a key step in the fabrication of multilayer blazed gratings (MBG) for extreme ultraviolet and soft x-rays. Growth of the multilayers can be perturbed by shadowing effects caused by the highly corrugated surface of the substrates, which results in distortion of the multilayer stack structure and degradation of performance of MBGs. In this study, to minimize the shadowing effects, we used an ion-beamsputtering machine with a highly collimated atomic flux to deposit Mo/Si multilayers on saw-tooth substrates. The sputtering conditions were optimized by finding a balance between smoothening and roughening processes in ordermore » to minimize degradation of the groove profile in the course of deposition and at the same time to keep the interfaces of a multilayer stack smooth enough for high efficiency. An optimal value of energy of 200 eV for sputtering Kr + ions was found by deposition of test multilayers on flat substrates at a range of ion energies. Two saw-tooth substrates were deposited at energies of 200 eV and 700 eV for the sputtering ions. It was found that reduction of the ion energy improved the blazing performance of the MBG and resulted in a 40% gain in the diffraction efficiency due to better replication of the groove profile by the multilayer. As a result of the optimization performed, an absolute diffraction efficiency of 28.8% was achieved for the 2nd blaze order of the MBG with a groove density of 7350 lines/mm at a wavelength of 13.5 nm. Lastly, details of the growth behavior of the multilayers on flat and saw-tooth substrates are discussed in terms of the linear continuous model of film growth.« less

Dual-energy contrast-enhanced digital mammography (DE-CEDM): optimization on digital subtraction with practical x-ray low/high-energy spectra

NASA Astrophysics Data System (ADS)

Chen, Biao; Jing, Zhenxue; Smith, Andrew P.; Parikh, Samir; Parisky, Yuri

2006-03-01

Dual-energy contrast enhanced digital mammography (DE-CEDM), which is based upon the digital subtraction of low/high-energy image pairs acquired before/after the administration of contrast agents, may provide physicians physiologic and morphologic information of breast lesions and help characterize their probability of malignancy. This paper proposes to use only one pair of post-contrast low / high-energy images to obtain digitally subtracted dual-energy contrast-enhanced images with an optimal weighting factor deduced from simulated characteristics of the imaging chain. Based upon our previous CEDM framework, quantitative characteristics of the materials and imaging components in the x-ray imaging chain, including x-ray tube (tungsten) spectrum, filters, breast tissues / lesions, contrast agents (non-ionized iodine solution), and selenium detector, were systemically modeled. Using the base-material (polyethylene-PMMA) decomposition method based on entrance low / high-energy x-ray spectra and breast thickness, the optimal weighting factor was calculated to cancel the contrast between fatty and glandular tissues while enhancing the contrast of iodized lesions. By contrast, previous work determined the optimal weighting factor through either a calibration step or through acquisition of a pre-contrast low/high-energy image pair. Computer simulations were conducted to determine weighting factors, lesions' contrast signal values, and dose levels as functions of x-ray techniques and breast thicknesses. Phantom and clinical feasibility studies were performed on a modified Selenia full field digital mammography system to verify the proposed method and computer-simulated results. The resultant conclusions from the computer simulations and phantom/clinical feasibility studies will be used in the upcoming clinical study.

Particle flow oriented electromagnetic calorimeter optimization for the circular electron positron collider

NASA Astrophysics Data System (ADS)

Zhao, H.; Fu, C.; Yu, D.; Wang, Z.; Hu, T.; Ruan, M.

2018-03-01

The design and optimization of the Electromagnetic Calorimeter (ECAL) are crucial for the Circular Electron Positron Collider (CEPC) project, a proposed future Higgs/Z factory. Following the reference design of the International Large Detector (ILD), a set of silicon-tungsten sampling ECAL geometries are implemented into the Geant4 simulation, whose performance is then scanned using Arbor algorithm. The photon energy response at different ECAL longitudinal structures is analyzed, and the separation performance between nearby photon showers with different ECAL transverse cell sizes is investigated and parametrized. The overall performance is characterized by a set of physics benchmarks, including νν H events where Higgs boson decays into a pair of photons (EM objects) or gluons (jets) and Z→τ+τ- events. Based on these results, we propose an optimized ECAL geometry for the CEPC project.

NREL module energy rating methodology

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

Whitaker, C.; Newmiller, J.; Kroposki, B.

1995-11-01

The goals of this project were to develop a tool for: evaluating one module in different climates; comparing different modules; provide a Q&D method for estimating periodic energy production; provide an achievable module rating; provide an incentive for manufacturers to optimize modules to non-STC conditions; and to have a consensus-based, NREL-sponsored activity. The approach taken was to simulate module energy for five reference days of various weather conditions. A performance model was developed.

The Effects of Creatine Supplementation on Explosive Performance and Optimal Individual Postactivation Potentiation Time.

PubMed

Wang, Chia-Chi; Yang, Ming-Ta; Lu, Kang-Hao; Chan, Kuei-Hui

2016-03-04

Creatine plays an important role in muscle energy metabolism. Postactivation potentiation (PAP) is a phenomenon that can acutely increase muscle power, but it is an individualized process that is influenced by muscle fatigue. This study examined the effects of creatine supplementation on explosive performance and the optimal individual PAP time during a set of complex training bouts. Thirty explosive athletes performed tests of back squat for one repetition maximum (1RM) strength and complex training bouts for determining the individual optimal timing of PAP, height and peak power of a counter movement jump before and after the supplementation. Subjects were assigned to a creatine or placebo group and then consumed 20 g of creatine or carboxymethyl cellulose per day for six days. After the supplementation, the 1RM strength in the creatine group significantly increased (p < 0.05). The optimal individual PAP time in the creatine group was also significant earlier than the pre-supplementation and post-supplementation of the placebo group (p < 0.05). There was no significant difference in jump performance between the groups. This study demonstrates that creatine supplementation improves maximal muscle strength and the optimal individual PAP time of complex training but has no effect on explosive performance.

The Effects of Creatine Supplementation on Explosive Performance and Optimal Individual Postactivation Potentiation Time

PubMed Central

Wang, Chia-Chi; Yang, Ming-Ta; Lu, Kang-Hao; Chan, Kuei-Hui

2016-01-01

Creatine plays an important role in muscle energy metabolism. Postactivation potentiation (PAP) is a phenomenon that can acutely increase muscle power, but it is an individualized process that is influenced by muscle fatigue. This study examined the effects of creatine supplementation on explosive performance and the optimal individual PAP time during a set of complex training bouts. Thirty explosive athletes performed tests of back squat for one repetition maximum (1RM) strength and complex training bouts for determining the individual optimal timing of PAP, height and peak power of a counter movement jump before and after the supplementation. Subjects were assigned to a creatine or placebo group and then consumed 20 g of creatine or carboxymethyl cellulose per day for six days. After the supplementation, the 1RM strength in the creatine group significantly increased (p < 0.05). The optimal individual PAP time in the creatine group was also significant earlier than the pre-supplementation and post-supplementation of the placebo group (p < 0.05). There was no significant difference in jump performance between the groups. This study demonstrates that creatine supplementation improves maximal muscle strength and the optimal individual PAP time of complex training but has no effect on explosive performance. PMID:26959056

SU-D-218-05: Material Quantification in Spectral X-Ray Imaging: Optimization and Validation.

PubMed

Nik, S J; Thing, R S; Watts, R; Meyer, J

2012-06-01

To develop and validate a multivariate statistical method to optimize scanning parameters for material quantification in spectral x-rayimaging. An optimization metric was constructed by extensively sampling the thickness space for the expected number of counts for m (two or three) materials. This resulted in an m-dimensional confidence region ofmaterial quantities, e.g. thicknesses. Minimization of the ellipsoidal confidence region leads to the optimization of energy bins. For the given spectrum, the minimum counts required for effective material separation can be determined by predicting the signal-to-noise ratio (SNR) of the quantification. A Monte Carlo (MC) simulation framework using BEAM was developed to validate the metric. Projection data of the m-materials was generated and material decomposition was performed for combinations of iodine, calcium and water by minimizing the z-score between the expected spectrum and binned measurements. The mean square error (MSE) and variance were calculated to measure the accuracy and precision of this approach, respectively. The minimum MSE corresponds to the optimal energy bins in the BEAM simulations. In the optimization metric, this is equivalent to the smallest confidence region. The SNR of the simulated images was also compared to the predictions from the metric. TheMSE was dominated by the variance for the given material combinations,which demonstrates accurate material quantifications. The BEAMsimulations revealed that the optimization of energy bins was accurate to within 1keV. The SNRs predicted by the optimization metric yielded satisfactory agreement but were expectedly higher for the BEAM simulations due to the inclusion of scattered radiation. The validation showed that the multivariate statistical method provides accurate material quantification, correct location of optimal energy bins and adequateprediction of image SNR. The BEAM code system is suitable for generating spectral x- ray imaging simulations. © 2012 American Association of Physicists in Medicine.

Biomass-to-electricity: analysis and optimization of the complete pathway steam explosion--enzymatic hydrolysis--anaerobic digestion with ICE vs SOFC as biogas users.

PubMed

Santarelli, M; Barra, S; Sagnelli, F; Zitella, P

2012-11-01

The paper deals with the energy analysis and optimization of a complete biomass-to-electricity energy pathway, starting from raw biomass towards the production of renewable electricity. The first step (biomass-to-biogas) is based on a real pilot plant located in Environment Park S.p.A. (Torino, Italy) with three main steps ((1) impregnation; (2) steam explosion; (3) enzymatic hydrolysis), completed by a two-step anaerobic fermentation. In the second step (biogas-to-electricity), the paper considers two technologies: internal combustion engines and a stack of solid oxide fuel cells. First, the complete pathway has been modeled and validated through experimental data. After, the model has been used for an analysis and optimization of the complete thermo-chemical and biological process, with the objective function of maximization of the energy balance at minimum consumption. The comparison between ICE and SOFC shows the better performance of the integrated plants based on SOFC. Copyright © 2012 Elsevier Ltd. All rights reserved.

Attack on centrifugal costs

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

Murray, P.F.

1986-03-01

The Monsanto Chocolate Bayou plant has had an aggressive and successful energy conservation program. The combined efforts have resulted in a 80% reduction in unit energy consumption compared to 1972. The approach of using system audits to optimize fluid systems was developed. Since most of the fluid movers are centrifugal, the name Centrifugal Savings Task Force was adopted. There are three tools that are particularly valuable in optimizing fluid systems. First, a working level understanding of the Affinity Laws seems a must. In addition, the performance curves for the fluid movers is needed. The last need is accurate system fieldmore » data. Systems effectively managed at the Chocolate Bayou plant were process air improvement, feed-water pressure reduction, combustion air blower turbine speed control, and cooling tower pressure reduction. Optimization of centrifugal systems is an often-overlooked opportunity for energy savings. The basic guidelines are to move only the fluid needed, and move it at as low a pressure as possible.« less

Factors affecting optimal linear endovenous energy density for endovenous laser ablation in incompetent lower limb truncal veins - A review of the clinical evidence.

PubMed

Cowpland, Christine A; Cleese, Amy L; Whiteley, Mark S

2017-06-01

Objectives The objective is to identify the factors that affect the optimal linear endovenous energy density (LEED) to ablate incompetent truncal veins. Methods We performed a literature review of clinical studies, which reported truncal vein ablation rates and LEED. A PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) flow diagram documents the search strategy. We analysed 13 clinical papers which fulfilled the criteria to be able to compare results of great saphenous vein occlusion as defined by venous duplex ultrasound, with the LEED used in the treatment. Results Evidence suggests that the optimal LEED for endovenous laser ablation of the great saphenous vein is >80 J/cm and <100 J/cm in terms of optimal closure rates with minimal side-effects and complications. Longer wavelengths targeting water might have a lower optimal LEED. A LEED <60 J/cm has reduced efficacy regardless of wavelength. The optimal LEED may vary with vein diameter and may be reduced by using specially shaped fibre tips. Laser delivery technique and type as well as the duration time of energy delivery appear to play a role in determining LEED. Conclusion The optimal LEED to ablate an incompetent great saphenous vein appears to be >80 J/cm and <95 J/cm based on current evidence for shorter wavelength lasers. There is evidence that longer wavelength lasers may be effective at LEEDs of <85 J/cm.

Design guidelines of triboelectric nanogenerator for water wave energy harvesters

NASA Astrophysics Data System (ADS)

Ahmed, Abdelsalam; Hassan, Islam; Jiang, Tao; Youssef, Khalid; Liu, Lian; Hedaya, Mohammad; Abu Yazid, Taher; Zu, Jean; Wang, Zhong Lin

2017-05-01

Ocean waves are one of the cleanest and most abundant energy sources on earth, and wave energy has the potential for future power generation. Triboelectric nanogenerator (TENG) technology has recently been proposed as a promising technology to harvest wave energy. In this paper, a theoretical study is performed on a duck-shaped TENG wave harvester recently introduced in our work. To enhance the design of the duck-shaped TENG wave harvester, the mechanical and electrical characteristics of the harvester’s overall structure, as well as its inner configuration, are analyzed, respectively, under different wave conditions, to optimize parameters such as duck radius and mass. Furthermore, a comprehensive hybrid 3D model is introduced to quantify the performance of the TENG wave harvester. Finally, the influence of different TENG parameters is validated by comparing the performance of several existing TENG wave harvesters. This study can be applied as a guideline for enhancing the performance of TENG wave energy harvesters.

Experimental study of a fuel cell power train for road transport application

NASA Astrophysics Data System (ADS)

Corbo, P.; Corcione, F. E.; Migliardini, F.; Veneri, O.

The development of fuel cell electric vehicles requires the on-board integration of fuel cell systems and electric energy storage devices, with an appropriate energy management system. The optimization of performance and efficiency needs an experimental analysis of the power train, which has to be effected in both stationary and transient conditions (including standard driving cycles). In this paper experimental results concerning the performance of a fuel cell power train are reported and discussed. In particular characterization results for a small sized fuel cell system (FCS), based on a 2.5 kW PEM stack, alone and coupled to an electric propulsion chain of 3.7 kW are presented and discussed. The control unit of the FCS allowed the main stack operative parameters (stoichiometric ratio, hydrogen and air pressure, temperature) to be varied and regulated in order to obtain optimized polarization and efficiency curves. Experimental runs effected on the power train during standard driving cycles have allowed the performance and efficiency of the individual components (fuel cell stack and auxiliaries, dc-dc converter, traction batteries, electric engine) to be evaluated, evidencing the role of output current and voltage of the dc-dc converter in directing the energy flows within the propulsion system.

Influence of ion-implanted profiles on the performance of GaAs MESFET's and MMIC amplifiers

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

Pavlidis, D.; Cazaux, J.L.; Graffeuil, J.

1988-04-01

The RF small-signal performance of GaAs MESFET's and MMIC amplifiers as a function of various ion-implanted profiles is theoretically and experimentally investigated. Implantation energy, dose, and recess depth influence are theoretically analyzed with the help of a specially developed device simulator. The performance of MMIC amplifiers processed with various energies, doses, recess depths, and bias conditions is discussed and compared to experimental characteristics. Some criteria are finally proposed for the choice of implantation conditions and process in order to optimize the characteristics of ion-implanted FET's and to realize process-tolerant MMIC amplifiers.

Performance evaluation of an evaporative pad greenhouse system for utilization of power plant reject heat

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

Olszewski, M.; Trezek, G.J.

1976-01-01

The overall performance of an evaporative pad greenhouse is considered in terms of the pad heat and mass transfer, the energy budget of the vegetation, and the performance of the power plant. An analytical predictive model for the pad performance was developed utilizing the Merkel total heat approximation. Data obtained from actual greenhouse performance provides an experimental verification of the pad model. Energy balance considerations on the vegetation provide a means of viewing optimal plant growth in terms of the power plant energy dissipation. In general, the results indicate that when an evaporative pad greenhouse system is used for wastemore » heat dispersal, the vegetation can be maintained within its thermal requirement zone, crop irrigation requirements are significantly reduced, and the power plant performance is comparable with conventional closed loop heat rejection systems.« less

a Statistical Analysis on the System Performance of a Bluetooth Low Energy Indoor Positioning System in a 3d Environment

NASA Astrophysics Data System (ADS)

Haagmans, G. G.; Verhagen, S.; Voûte, R. L.; Verbree, E.

2017-09-01

Since GPS tends to fail for indoor positioning purposes, alternative methods like indoor positioning systems (IPS) based on Bluetooth low energy (BLE) are developing rapidly. Generally, IPS are deployed in environments covered with obstacles such as furniture, walls, people and electronics influencing the signal propagation. The major factor influencing the system performance and to acquire optimal positioning results is the geometry of the beacons. The geometry of the beacons is limited to the available infrastructure that can be deployed (number of beacons, basestations and tags), which leads to the following challenge: Given a limited number of beacons, where should they be placed in a specified indoor environment, such that the geometry contributes to optimal positioning results? This paper aims to propose a statistical model that is able to select the optimal configuration that satisfies the user requirements in terms of precision. The model requires the definition of a chosen 3D space (in our case 7 × 10 × 6 meter), number of beacons, possible user tag locations and a performance threshold (e.g. required precision). For any given set of beacon and receiver locations, the precision, internal- and external reliability can be determined on forehand. As validation, the modeled precision has been compared with observed precision results. The measurements have been performed with an IPS of BlooLoc at a chosen set of user tag locations for a given geometric configuration. Eventually, the model is able to select the optimal geometric configuration out of millions of possible configurations based on a performance threshold (e.g. required precision).

Challenges in Maintaining Emotion Regulation in a Sleep and Energy Deprived State Induced by the 4800Km Ultra-Endurance Bicycle Race; The Race Across AMerica (RAAM).

PubMed

Lahart, Ian M; Lane, Andrew M; Hulton, Andrew; Williams, Karen; Godfrey, Richard; Pedlar, Charles; Wilson, Mathew G; Whyte, Gregory P

2013-01-01

Multiday ultra-endurance races present athletes with a significant number of physiological and psychological challenges. We examined emotions, the perceived functionality (optimal-dysfunctional) of emotions, strategies to regulate emotions, sleep quality, and energy intake-expenditure in a four-man team participating in the Race Across AMerica (RAAM); a 4856km continuous cycle race. Cyclists reported experiencing an optimal emotional state for less than 50% of total competition, with emotional states differing significantly between each cyclist over time. Coupled with this emotional disturbance, each cyclist experienced progressively worsening sleep deprivation and daily negative energy balances throughout the RAAM. Cyclists managed less than one hour of continuous sleep per sleep episode, high sleep latency and high percentage moving time. Of note, actual sleep and sleep efficiency were better maintained during longer rest periods, highlighting the importance of a race strategy that seeks to optimise the balance between average cycling velocity and sleep time. Our data suggests that future RAAM cyclists and crew should: 1) identify beliefs on the perceived functionality of emotions in relation to best (functional-optimal) and worst (dysfunctional) performance as the starting point to intervention work; 2) create a plan for support sufficient sleep and recovery; 3) create nutritional strategies that maintain energy intake and thus reduce energy deficits; and 4) prepare for the deleterious effects of sleep deprivation so that they are able to appropriately respond to unexpected stressors and foster functional working interpersonal relationships. Key PointsCompleting the Race Across AMerica (RAAM); a 4856km continuous cycle race associated with sleep disturbance, an energy-deficient state, and experiencing intense unwanted emotions.Cyclists reported experiencing an optimal emotional state for less than 50% of total competition and actual sleep and sleep efficiency was better maintained during longer rest periods.We suggest that future RAAM cyclists and crew should:Identify individual beliefs on the perceived functionality of emotional states in relation to best (optimal) and worst (dysfunctional) performance as the starting point to identifying if emotion regulation strategies should be initiated.Plan for enhanced sleep and recovery not just plan and train for maintaining a high average velocity;Create nutritional strategies that maintain energy intake and thus reduce energy deficits;Psychologically prepare cyclists and crew for the deleterious effects of sleep deprivation so that they both are able to appropriately respond to unexpected stressors and foster functional interpersonal working relationships.

Extreme Scale Plasma Turbulence Simulations on Top Supercomputers Worldwide

DOE PAGES

Tang, William; Wang, Bei; Ethier, Stephane; ...

2016-11-01

The goal of the extreme scale plasma turbulence studies described in this paper is to expedite the delivery of reliable predictions on confinement physics in large magnetic fusion systems by using world-class supercomputers to carry out simulations with unprecedented resolution and temporal duration. This has involved architecture-dependent optimizations of performance scaling and addressing code portability and energy issues, with the metrics for multi-platform comparisons being 'time-to-solution' and 'energy-to-solution'. Realistic results addressing how confinement losses caused by plasma turbulence scale from present-day devices to the much larger $25 billion international ITER fusion facility have been enabled by innovative advances in themore » GTC-P code including (i) implementation of one-sided communication from MPI 3.0 standard; (ii) creative optimization techniques on Xeon Phi processors; and (iii) development of a novel performance model for the key kernels of the PIC code. Our results show that modeling data movement is sufficient to predict performance on modern supercomputer platforms.« less

Simulation of floor heating in a combined solar-biomass system integrated in a public bathhouse located in Marrakech

NASA Astrophysics Data System (ADS)

Krarouch, M.; Hamdi, H.; Lamghari, S.; Outzourhit, A.

2018-05-01

This study was conducted in the framework of the HYBRID-BATH project aiming at improving the energy efficiency of traditional Hammams (Turkish baths) and the reduction of the use of wood energy and therefore of greenhouse gases emissions. The present work focuses on the energetic performance of a two-room Hammam located in Marrakech. The rooms were heated by the ground using a hybrid system Micro-CSP/biomass boiler. The dynamic simulation of the system (Hammam coupled with the hybrid system Micro-CSP/biomass boiler) was conducted using TRNSYS18 software. The parametric study was performed on a Typical Meteorological Year data (TMY). This study is devoted to presenting the results of the dynamic simulation of a part of the Hammam investigated, in order to optimize the underfloor heating system. The models and the results of the simulations will be validated by comparisons with experimental results. The main objective is to optimize the operation of such system and to improve its performance.