Optimal weight based on energy imbalance and utility maximization

NASA Astrophysics Data System (ADS)

Sun, Ruoyan

2016-01-01

This paper investigates the optimal weight for both male and female using energy imbalance and utility maximization. Based on the difference of energy intake and expenditure, we develop a state equation that reveals the weight gain from this energy gap. We ​construct an objective function considering food consumption, eating habits and survival rate to measure utility. Through applying mathematical tools from optimal control methods and qualitative theory of differential equations, we obtain some results. For both male and female, the optimal weight is larger than the physiologically optimal weight calculated by the Body Mass Index (BMI). We also study the corresponding trajectories to steady state weight respectively. Depending on the value of a few parameters, the steady state can either be a saddle point with a monotonic trajectory or a focus with dampened oscillations.

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

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.

Auto-DR and Pre-cooling of Buildings at Tri-City Corporate Center

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

Yin, Rongxin; Xu, Peng; Kiliccote, Sila

2008-11-01

Over the several past years, Lawrence Berkeley National Laboratory (LBNL) has conducted field tests for different pre-cooling strategies in different commercial buildings within California. The test results indicated that pre-cooling strategies were effective in reducing electric demand in these buildings during peak periods. This project studied how to optimize pre-cooling strategies for eleven buildings in the Tri-City Corporate Center, San Bernardino, California with the assistance of a building energy simulation tool -- the Demand Response Quick Assessment Tool (DRQAT) developed by LBNL's Demand Response Research Center funded by the California Energy Commission's Public Interest Energy Research (PIER) Program. From themore » simulation results of these eleven buildings, optimal pre-cooling and temperature reset strategies were developed. The study shows that after refining and calibrating initial models with measured data, the accuracy of the models can be greatly improved and the models can be used to predict load reductions for automated demand response (Auto-DR) events. This study summarizes the optimization experience of the procedure to develop and calibrate building models in DRQAT. In order to confirm the actual effect of demand response strategies, the simulation results were compared to the field test data. The results indicated that the optimal demand response strategies worked well for all buildings in the Tri-City Corporate Center. This study also compares DRQAT with other building energy simulation tools (eQUEST and BEST). The comparison indicate that eQUEST and BEST underestimate the actual demand shed of the pre-cooling strategies due to a flaw in DOE2's simulation engine for treating wall thermal mass. DRQAT is a more accurate tool in predicting thermal mass effects of DR events.« less

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).

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

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.

Towards a generalized energy prediction model for machine tools

PubMed Central

Bhinge, Raunak; Park, Jinkyoo; Law, Kincho H.; Dornfeld, David A.; Helu, Moneer; Rachuri, Sudarsan

2017-01-01

Energy prediction of machine tools can deliver many advantages to a manufacturing enterprise, ranging from energy-efficient process planning to machine tool monitoring. Physics-based, energy prediction models have been proposed in the past to understand the energy usage pattern of a machine tool. However, uncertainties in both the machine and the operating environment make it difficult to predict the energy consumption of the target machine reliably. Taking advantage of the opportunity to collect extensive, contextual, energy-consumption data, we discuss a data-driven approach to develop an energy prediction model of a machine tool in this paper. First, we present a methodology that can efficiently and effectively collect and process data extracted from a machine tool and its sensors. We then present a data-driven model that can be used to predict the energy consumption of the machine tool for machining a generic part. Specifically, we use Gaussian Process (GP) Regression, a non-parametric machine-learning technique, to develop the prediction model. The energy prediction model is then generalized over multiple process parameters and operations. Finally, we apply this generalized model with a method to assess uncertainty intervals to predict the energy consumed to machine any part using a Mori Seiki NVD1500 machine tool. Furthermore, the same model can be used during process planning to optimize the energy-efficiency of a machining process. PMID:28652687

Towards a generalized energy prediction model for machine tools.

PubMed

Bhinge, Raunak; Park, Jinkyoo; Law, Kincho H; Dornfeld, David A; Helu, Moneer; Rachuri, Sudarsan

2017-04-01

Energy prediction of machine tools can deliver many advantages to a manufacturing enterprise, ranging from energy-efficient process planning to machine tool monitoring. Physics-based, energy prediction models have been proposed in the past to understand the energy usage pattern of a machine tool. However, uncertainties in both the machine and the operating environment make it difficult to predict the energy consumption of the target machine reliably. Taking advantage of the opportunity to collect extensive, contextual, energy-consumption data, we discuss a data-driven approach to develop an energy prediction model of a machine tool in this paper. First, we present a methodology that can efficiently and effectively collect and process data extracted from a machine tool and its sensors. We then present a data-driven model that can be used to predict the energy consumption of the machine tool for machining a generic part. Specifically, we use Gaussian Process (GP) Regression, a non-parametric machine-learning technique, to develop the prediction model. The energy prediction model is then generalized over multiple process parameters and operations. Finally, we apply this generalized model with a method to assess uncertainty intervals to predict the energy consumed to machine any part using a Mori Seiki NVD1500 machine tool. Furthermore, the same model can be used during process planning to optimize the energy-efficiency of a machining process.

Analysis of EnergyPlus for use in residential building energy optimization

NASA Astrophysics Data System (ADS)

Spencer, Justin S.

This work explored the utility of EnergyPlus as a simulation engine for doing residential building energy optimization, with the objective of finding the modeling areas that require further development in EnergyPlus for residential optimization applications. This work was conducted primarily during 2006-2007, with publication occurring later in 2010. The assessments and recommendations apply to the simulation tool versions available in 2007. During this work, an EnergyPlus v2.0 (2007) input file generator was developed for use in BEopt 0.8.0.4 (2007). BEopt 0.8.0.4 is a residential Building Energy optimization program developed at the National Renewable Energy Laboratory in Golden, Colorado. Residential modeling capabilities of EnergyPlus v2.0 were scrutinized and tested. Modeling deficiencies were identified in a number of areas. These deficiencies were compared to deficiencies in the DOE2.2 V44E4(2007)/TRNSYS simulation engines. The highest priority gaps in EnergyPlus v2.0's residential modeling capability are in infiltration, duct leakage, and foundation modeling. Optimization results from DOE2.2 V44E4 and EnergyPlus v2.0 were analyzed to search for modeling differences that have a significant impact on optimization results. Optimal buildings at different energy savings levels were compared to look for biases. It was discovered that the EnergyPlus v2.0 optimizations consistently chose higher wall insulation levels than the DOE2.2 V44E4 optimizations. The points composing the optimal paths chosen by DOE2.2 V44E4 and EnergyPlus v2.0 were compared to look for points chosen by one optimization that were significantly different from the other optimal path. These outliers were compared to consensus optimal points to determine the simulation differences that cause disparities in the optimization results. The differences were primarily caused by modeling of window radiation exchange and HVAC autosizing.

The optimization problems of CP operation

NASA Astrophysics Data System (ADS)

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

2017-11-01

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

Assessment of the Charging Policy in Energy Efficiency of the Enterprise

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

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.

Optimal Energy Measurement in Nonlinear Systems: An Application of Differential Geometry

NASA Technical Reports Server (NTRS)

Fixsen, Dale J.; Moseley, S. H.; Gerrits, T.; Lita, A.; Nam, S. W.

2014-01-01

Design of TES microcalorimeters requires a tradeoff between resolution and dynamic range. Often, experimenters will require linearity for the highest energy signals, which requires additional heat capacity be added to the detector. This results in a reduction of low energy resolution in the detector. We derive and demonstrate an algorithm that allows operation far into the nonlinear regime with little loss in spectral resolution. We use a least squares optimal filter that varies with photon energy to accommodate the nonlinearity of the detector and the non-stationarity of the noise. The fitting process we use can be seen as an application of differential geometry. This recognition provides a set of well-developed tools to extend our work to more complex situations. The proper calibration of a nonlinear microcalorimeter requires a source with densely spaced narrow lines. A pulsed laser multi-photon source is used here, and is seen to be a powerful tool for allowing us to develop practical systems with significant detector nonlinearity. The combination of our analysis techniques and the multi-photon laser source create a powerful tool for increasing the performance of future TES microcalorimeters.

Center for the Built Environment: Research on Building HVAC Systems

Science.gov Websites

, and lessons learned. Underfloor Air Distribution (UFAD) Cooling Airflow Design Tool Developing simplified design tools for optimization of underfloor systems. Underfloor Air Distribution (UFAD) Cost Near-ZNE Buildings Setpoint Energy Savings Calculator UFAD Case Studies UFAD Cooling Design Tool UFAD

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.

Effective Energy Simulation and Optimal Design of Side-lit Buildings with Venetian Blinds

NASA Astrophysics Data System (ADS)

Cheng, Tian

Venetian blinds are popularly used in buildings to control the amount of incoming daylight for improving visual comfort and reducing heat gains in air-conditioning systems. Studies have shown that the proper design and operation of window systems could result in significant energy savings in both lighting and cooling. However, there is no convenient computer tool that allows effective and efficient optimization of the envelope of side-lit buildings with blinds now. Three computer tools, Adeline, DOE2 and EnergyPlus widely used for the above-mentioned purpose have been experimentally examined in this study. Results indicate that the two former tools give unacceptable accuracy due to unrealistic assumptions adopted while the last one may generate large errors in certain conditions. Moreover, current computer tools have to conduct hourly energy simulations, which are not necessary for life-cycle energy analysis and optimal design, to provide annual cooling loads. This is not computationally efficient, particularly not suitable for optimal designing a building at initial stage because the impacts of many design variations and optional features have to be evaluated. A methodology is therefore developed for efficient and effective thermal and daylighting simulations and optimal design of buildings with blinds. Based on geometric optics and radiosity method, a mathematical model is developed to reasonably simulate the daylighting behaviors of venetian blinds. Indoor illuminance at any reference point can be directly and efficiently computed. They have been validated with both experiments and simulations with Radiance. Validation results show that indoor illuminances computed by the new models agree well with the measured data, and the accuracy provided by them is equivalent to that of Radiance. The computational efficiency of the new models is much higher than that of Radiance as well as EnergyPlus. Two new methods are developed for the thermal simulation of buildings. A fast Fourier transform (FFT) method is presented to avoid the root-searching process in the inverse Laplace transform of multilayered walls. Generalized explicit FFT formulae for calculating the discrete Fourier transform (DFT) are developed for the first time. They can largely facilitate the implementation of FFT. The new method also provides a basis for generating the symbolic response factors. Validation simulations show that it can generate the response factors as accurate as the analytical solutions. The second method is for direct estimation of annual or seasonal cooling loads without the need for tedious hourly energy simulations. It is validated by hourly simulation results with DOE2. Then symbolic long-term cooling load can be created by combining the two methods with thermal network analysis. The symbolic long-term cooling load can keep the design parameters of interest as symbols, which is particularly useful for the optimal design and sensitivity analysis. The methodology is applied to an office building in Hong Kong for the optimal design of building envelope. Design variables such as window-to-wall ratio, building orientation, and glazing optical and thermal properties are included in the study. Results show that the selected design values could significantly impact the energy performance of windows, and the optimal design of side-lit buildings could greatly enhance energy savings. The application example also demonstrates that the developed methodology significantly facilitates the optimal building design and sensitivity analysis, and leads to high computational efficiency.

Maximization of the annual energy production of wind power plants by optimization of layout and yaw-based wake control: Maximization of wind plant AEP by optimization of layout and wake control

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

Gebraad, Pieter; Thomas, Jared J.; Ning, Andrew

This paper presents a wind plant modeling and optimization tool that enables the maximization of wind plant annual energy production (AEP) using yaw-based wake steering control and layout changes. The tool is an extension of a wake engineering model describing the steady-state effects of yaw on wake velocity profiles and power productions of wind turbines in a wind plant. To make predictions of a wind plant's AEP, necessary extensions of the original wake model include coupling it with a detailed rotor model and a control policy for turbine blade pitch and rotor speed. This enables the prediction of power productionmore » with wake effects throughout a range of wind speeds. We use the tool to perform an example optimization study on a wind plant based on the Princess Amalia Wind Park. In this case study, combined optimization of layout and wake steering control increases AEP by 5%. The power gains from wake steering control are highest for region 1.5 inflow wind speeds, and they continue to be present to some extent for the above-rated inflow wind speeds. The results show that layout optimization and wake steering are complementary because significant AEP improvements can be achieved with wake steering in a wind plant layout that is already optimized to reduce wake losses.« less

Cyber Security Audit and Attack Detection Toolkit

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

Peterson, Dale

2012-05-31

This goal of this project was to develop cyber security audit and attack detection tools for industrial control systems (ICS). Digital Bond developed and released a tool named Bandolier that audits ICS components commonly used in the energy sector against an optimal security configuration. The Portaledge Project developed a capability for the PI Historian, the most widely used Historian in the energy sector, to aggregate security events and detect cyber attacks.

Thermal energy and economic analysis of a PCM-enhanced household envelope considering different climate zones in Morocco

NASA Astrophysics Data System (ADS)

Kharbouch, Yassine; Mimet, Abdelaziz; El Ganaoui, Mohammed; Ouhsaine, Lahoucine

2018-07-01

This study investigates the thermal energy potentials and economic feasibility of an air-conditioned family household-integrated phase change material (PCM) considering different climate zones in Morocco. A simulation-based optimisation was carried out in order to define the optimal design of a PCM-enhanced household envelope for thermal energy effectiveness and cost-effectiveness of predefined candidate solutions. The optimisation methodology is based on coupling Energyplus® as a dynamic simulation tool and GenOpt® as an optimisation tool. Considering the obtained optimum design strategies, a thermal energy and economic analysis are carried out to investigate PCMs' integration feasibility in the Moroccan constructions. The results show that the PCM-integrated household envelope allows minimising the cooling/heating thermal energy demand vs. a reference household without PCM. While for the cost-effectiveness optimisation, it has been deduced that the economic feasibility is stilling insufficient under the actual PCM market conditions. The optimal design parameters results are also analysed.

Development of a Suite of Analytical Tools for Energy and Water Infrastructure Knowledge Discovery

NASA Astrophysics Data System (ADS)

Morton, A.; Piburn, J.; Stewart, R.; Chandola, V.

2017-12-01

Energy and water generation and delivery systems are inherently interconnected. With demand for energy growing, the energy sector is experiencing increasing competition for water. With increasing population and changing environmental, socioeconomic, and demographic scenarios, new technology and investment decisions must be made for optimized and sustainable energy-water resource management. This also requires novel scientific insights into the complex interdependencies of energy-water infrastructures across multiple space and time scales. To address this need, we've developed a suite of analytical tools to support an integrated data driven modeling, analysis, and visualization capability for understanding, designing, and developing efficient local and regional practices related to the energy-water nexus. This work reviews the analytical capabilities available along with a series of case studies designed to demonstrate the potential of these tools for illuminating energy-water nexus solutions and supporting strategic (federal) policy decisions.

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.

Technical Note: spektr 3.0-A computational tool for x-ray spectrum modeling and analysis.

PubMed

Punnoose, J; Xu, J; Sisniega, A; Zbijewski, W; Siewerdsen, J H

2016-08-01

A computational toolkit (spektr 3.0) has been developed to calculate x-ray spectra based on the tungsten anode spectral model using interpolating cubic splines (TASMICS) algorithm, updating previous work based on the tungsten anode spectral model using interpolating polynomials (TASMIP) spectral model. The toolkit includes a matlab (The Mathworks, Natick, MA) function library and improved user interface (UI) along with an optimization algorithm to match calculated beam quality with measurements. The spektr code generates x-ray spectra (photons/mm(2)/mAs at 100 cm from the source) using TASMICS as default (with TASMIP as an option) in 1 keV energy bins over beam energies 20-150 kV, extensible to 640 kV using the TASMICS spectra. An optimization tool was implemented to compute the added filtration (Al and W) that provides a best match between calculated and measured x-ray tube output (mGy/mAs or mR/mAs) for individual x-ray tubes that may differ from that assumed in TASMICS or TASMIP and to account for factors such as anode angle. The median percent difference in photon counts for a TASMICS and TASMIP spectrum was 4.15% for tube potentials in the range 30-140 kV with the largest percentage difference arising in the low and high energy bins due to measurement errors in the empirically based TASMIP model and inaccurate polynomial fitting. The optimization tool reported a close agreement between measured and calculated spectra with a Pearson coefficient of 0.98. The computational toolkit, spektr, has been updated to version 3.0, validated against measurements and existing models, and made available as open source code. Video tutorials for the spektr function library, UI, and optimization tool are available.

Lifecycle Industry GreenHouse gas, Technology and Energy through the Use Phase (LIGHTEnUP) – Analysis Tool User’s Guide

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

Morrow, William R.; Shehabi, Arman; Smith, Sarah

The LIGHTEnUP Analysis Tool (Lifecycle Industry GreenHouse gas, Technology and Energy through the Use Phase) has been developed for The United States Department of Energy’s (U.S. DOE) Advanced Manufacturing Office (AMO) to forecast both the manufacturing sector and product life-cycle energy consumption implications of manufactured products across the U.S. economy. The tool architecture incorporates publicly available historic and projection datasets of U.S. economy-wide energy use including manufacturing, buildings operations, electricity generation and transportation. The tool requires minimal inputs to define alternate scenarios to business-as-usual projection data. The tool is not an optimization or equilibrium model and therefore does not selectmore » technologies or deployment scenarios endogenously. Instead, inputs are developed exogenous to the tool by the user to reflect detailed engineering calculations, future targets and goals, or creative insights. The tool projects the scenario’s energy, CO 2 emissions, and energy expenditure (i.e., economic spending to purchase energy) implications and provides documentation to communicate results. The tool provides a transparent and uniform system of comparing manufacturing and use-phase impacts of technologies. The tool allows the user to create multiple scenarios that can reflect a range of possible future outcomes. However, reasonable scenarios require careful attention to assumptions and details about the future. This tool is part of an emerging set of AMO’s life cycle analysis (LCA) tool such as the Material Flows the Industry (MFI) tool, and the Additive Manufacturing LCA tool.« less

Optimizing Biorefinery Design and Operations via Linear Programming Models

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

Talmadge, Michael; Batan, Liaw; Lamers, Patrick

The ability to assess and optimize economics of biomass resource utilization for the production of fuels, chemicals and power is essential for the ultimate success of a bioenergy industry. The team of authors, consisting of members from the National Renewable Energy Laboratory (NREL) and the Idaho National Laboratory (INL), has developed simple biorefinery linear programming (LP) models to enable the optimization of theoretical or existing biorefineries. The goal of this analysis is to demonstrate how such models can benefit the developing biorefining industry. It focuses on a theoretical multi-pathway, thermochemical biorefinery configuration and demonstrates how the biorefinery can use LPmore » models for operations planning and optimization in comparable ways to the petroleum refining industry. Using LP modeling tools developed under U.S. Department of Energy's Bioenergy Technologies Office (DOE-BETO) funded efforts, the authors investigate optimization challenges for the theoretical biorefineries such as (1) optimal feedstock slate based on available biomass and prices, (2) breakeven price analysis for available feedstocks, (3) impact analysis for changes in feedstock costs and product prices, (4) optimal biorefinery operations during unit shutdowns / turnarounds, and (5) incentives for increased processing capacity. These biorefinery examples are comparable to crude oil purchasing and operational optimization studies that petroleum refiners perform routinely using LPs and other optimization models. It is important to note that the analyses presented in this article are strictly theoretical and they are not based on current energy market prices. The pricing structure assigned for this demonstrative analysis is consistent with $4 per gallon gasoline, which clearly assumes an economic environment that would favor the construction and operation of biorefineries. The analysis approach and examples provide valuable insights into the usefulness of analysis tools for maximizing the potential benefits of biomass utilization for production of fuels, chemicals and power.« less

Optimal quantum operations at zero energy cost

NASA Astrophysics Data System (ADS)

Chiribella, Giulio; Yang, Yuxiang

2017-08-01

Quantum technologies are developing powerful tools to generate and manipulate coherent superpositions of different energy levels. Envisaging a new generation of energy-efficient quantum devices, here we explore how coherence can be manipulated without exchanging energy with the surrounding environment. We start from the task of converting a coherent superposition of energy eigenstates into another. We identify the optimal energy-preserving operations, both in the deterministic and in the probabilistic scenario. We then design a recursive protocol, wherein a branching sequence of energy-preserving filters increases the probability of success while reaching maximum fidelity at each iteration. Building on the recursive protocol, we construct efficient approximations of the optimal fidelity-probability trade-off, by taking coherent superpositions of the different branches generated by probabilistic filtering. The benefits of this construction are illustrated in applications to quantum metrology, quantum cloning, coherent state amplification, and ancilla-driven computation. Finally, we extend our results to transitions where the input state is generally mixed and we apply our findings to the task of purifying quantum coherence.

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.

Improving Building Energy Simulation Programs Through Diagnostic Testing (Fact Sheet)

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

Not Available

2012-02-01

New test procedure evaluates quality and accuracy of energy analysis tools for the residential building retrofit market. Reducing the energy use of existing homes in the United States offers significant energy-saving opportunities, which can be identified through building simulation software tools that calculate optimal packages of efficiency measures. To improve the accuracy of energy analysis for residential buildings, the National Renewable Energy Laboratory's (NREL) Buildings Research team developed the Building Energy Simulation Test for Existing Homes (BESTEST-EX), a method for diagnosing and correcting errors in building energy audit software and calibration procedures. BESTEST-EX consists of building physics and utility billmore » calibration test cases, which software developers can use to compare their tools simulation findings to reference results generated with state-of-the-art simulation tools. Overall, the BESTEST-EX methodology: (1) Tests software predictions of retrofit energy savings in existing homes; (2) Ensures building physics calculations and utility bill calibration procedures perform to a minimum standard; and (3) Quantifies impacts of uncertainties in input audit data and occupant behavior. BESTEST-EX is helping software developers identify and correct bugs in their software, as well as develop and test utility bill calibration procedures.« less

Plasma Diagnostics: Use and Justification in an Industrial Environment

NASA Astrophysics Data System (ADS)

Loewenhardt, Peter

1998-10-01

The usefulness and importance of plasma diagnostics have played a major role in the development of plasma processing tools in the semiconductor industry. As can be seen through marketing materials from semiconductor equipment manufacturers, results from plasma diagnostic equipment can be a powerful tool in selling the technological leadership of tool design. Some diagnostics have long been used for simple process control such as optical emission for endpoint determination, but in recent years more sophisticated and involved diagnostic tools have been utilized in chamber and plasma source development and optimization. It is now common to find an assortment of tools at semiconductor equipment companies such as Langmuir probes, mass spectrometers, spatial optical emission probes, impedance, ion energy and ion flux probes. An outline of how the importance of plasma diagnostics has grown at an equipment manufacturer over the last decade will be given, with examples of significant and useful results obtained. Examples will include the development and optimization of an inductive plasma source, trends and hardware effects on ion energy distributions, mass spectrometry influences on process development and investigations of plasma-wall interactions. Plasma diagnostic focus, in-house development and proliferation in an environment where financial justification requirements are both strong and necessary will be discussed.

Open source Modeling and optimization tools for Planning

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

Peles, S.

Open source modeling and optimization tools for planning The existing tools and software used for planning and analysis in California are either expensive, difficult to use, or not generally accessible to a large number of participants. These limitations restrict the availability of participants for larger scale energy and grid studies in the state. The proposed initiative would build upon federal and state investments in open source software, and create and improve open source tools for use in the state planning and analysis activities. Computational analysis and simulation frameworks in development at national labs and universities can be brought forward tomore » complement existing tools. An open source platform would provide a path for novel techniques and strategies to be brought into the larger community and reviewed by a broad set of stakeholders.« less

Parallel Harmony Search Based Distributed Energy Resource Optimization

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

Ceylan, Oguzhan; Liu, Guodong; Tomsovic, Kevin

2015-01-01

This paper presents a harmony search based parallel optimization algorithm to minimize voltage deviations in three phase unbalanced electrical distribution systems and to maximize active power outputs of distributed energy resources (DR). The main contribution is to reduce the adverse impacts on voltage profile during a day as photovoltaics (PVs) output or electrical vehicles (EVs) charging changes throughout a day. The IEEE 123- bus distribution test system is modified by adding DRs and EVs under different load profiles. The simulation results show that by using parallel computing techniques, heuristic methods may be used as an alternative optimization tool in electricalmore » power distribution systems operation.« less

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).

REopt Lite Web Tool

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

NREL developed a free, publicly available web version of the REopt (TM) renewable energy integration and optimization platform called REopt Lite. REopt Lite recommends the optimal size and dispatch strategy for grid-connected photovoltaics (PV) and battery storage at a site. It also allows users to explore how PV and storage can increase a site's resiliency during a grid outage.

A Python tool to set up relative free energy calculations in GROMACS

PubMed Central

Klimovich, Pavel V.; Mobley, David L.

2015-01-01

Free energy calculations based on molecular dynamics (MD) simulations have seen a tremendous growth in the last decade. However, it is still difficult and tedious to set them up in an automated manner, as the majority of the present-day MD simulation packages lack that functionality. Relative free energy calculations are a particular challenge for several reasons, including the problem of finding a common substructure and mapping the transformation to be applied. Here we present a tool, alchemical-setup.py, that automatically generates all the input files needed to perform relative solvation and binding free energy calculations with the MD package GROMACS. When combined with Lead Optimization Mapper [14], recently developed in our group, alchemical-setup.py allows fully automated setup of relative free energy calculations in GROMACS. Taking a graph of the planned calculations and a mapping, both computed by LOMAP, our tool generates the topology and coordinate files needed to perform relative free energy calculations for a given set of molecules, and provides a set of simulation input parameters. The tool was validated by performing relative hydration free energy calculations for a handful of molecules from the SAMPL4 challenge [16]. Good agreement with previously published results and the straightforward way in which free energy calculations can be conducted make alchemical-setup.py a promising tool for automated setup of relative solvation and binding free energy calculations. PMID:26487189

Technical Note: spektr 3.0—A computational tool for x-ray spectrum modeling and analysis

PubMed Central

Punnoose, J.; Xu, J.; Sisniega, A.; Zbijewski, W.; Siewerdsen, J. H.

2016-01-01

Purpose: A computational toolkit (spektr 3.0) has been developed to calculate x-ray spectra based on the tungsten anode spectral model using interpolating cubic splines (TASMICS) algorithm, updating previous work based on the tungsten anode spectral model using interpolating polynomials (TASMIP) spectral model. The toolkit includes a matlab (The Mathworks, Natick, MA) function library and improved user interface (UI) along with an optimization algorithm to match calculated beam quality with measurements. Methods: The spektr code generates x-ray spectra (photons/mm2/mAs at 100 cm from the source) using TASMICS as default (with TASMIP as an option) in 1 keV energy bins over beam energies 20–150 kV, extensible to 640 kV using the TASMICS spectra. An optimization tool was implemented to compute the added filtration (Al and W) that provides a best match between calculated and measured x-ray tube output (mGy/mAs or mR/mAs) for individual x-ray tubes that may differ from that assumed in TASMICS or TASMIP and to account for factors such as anode angle. Results: The median percent difference in photon counts for a TASMICS and TASMIP spectrum was 4.15% for tube potentials in the range 30–140 kV with the largest percentage difference arising in the low and high energy bins due to measurement errors in the empirically based TASMIP model and inaccurate polynomial fitting. The optimization tool reported a close agreement between measured and calculated spectra with a Pearson coefficient of 0.98. Conclusions: The computational toolkit, spektr, has been updated to version 3.0, validated against measurements and existing models, and made available as open source code. Video tutorials for the spektr function library, UI, and optimization tool are available. PMID:27487888

Technical Note: SPEKTR 3.0—A computational tool for x-ray spectrum modeling and analysis

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

Punnoose, J.; Xu, J.; Sisniega, A.

2016-08-15

Purpose: A computational toolkit (SPEKTR 3.0) has been developed to calculate x-ray spectra based on the tungsten anode spectral model using interpolating cubic splines (TASMICS) algorithm, updating previous work based on the tungsten anode spectral model using interpolating polynomials (TASMIP) spectral model. The toolkit includes a MATLAB (The Mathworks, Natick, MA) function library and improved user interface (UI) along with an optimization algorithm to match calculated beam quality with measurements. Methods: The SPEKTR code generates x-ray spectra (photons/mm{sup 2}/mAs at 100 cm from the source) using TASMICS as default (with TASMIP as an option) in 1 keV energy bins overmore » beam energies 20–150 kV, extensible to 640 kV using the TASMICS spectra. An optimization tool was implemented to compute the added filtration (Al and W) that provides a best match between calculated and measured x-ray tube output (mGy/mAs or mR/mAs) for individual x-ray tubes that may differ from that assumed in TASMICS or TASMIP and to account for factors such as anode angle. Results: The median percent difference in photon counts for a TASMICS and TASMIP spectrum was 4.15% for tube potentials in the range 30–140 kV with the largest percentage difference arising in the low and high energy bins due to measurement errors in the empirically based TASMIP model and inaccurate polynomial fitting. The optimization tool reported a close agreement between measured and calculated spectra with a Pearson coefficient of 0.98. Conclusions: The computational toolkit, SPEKTR, has been updated to version 3.0, validated against measurements and existing models, and made available as open source code. Video tutorials for the SPEKTR function library, UI, and optimization tool are available.« less

Materials and Waste Management Research

EPA Pesticide Factsheets

EPA is developing data and tools to reduce waste, manage risks, reuse and conserve natural materials, and optimize energy recovery. Collaboration with states facilitates assessment and utilization of technologies developed by the private sector.

Energy Storage Sizing Taking Into Account Forecast Uncertainties and Receding Horizon Operation

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

Baker, Kyri; Hug, Gabriela; Li, Xin

Energy storage systems (ESS) have the potential to be very beneficial for applications such as reducing the ramping of generators, peak shaving, and balancing not only the variability introduced by renewable energy sources, but also the uncertainty introduced by errors in their forecasts. Optimal usage of storage may result in reduced generation costs and an increased use of renewable energy. However, optimally sizing these devices is a challenging problem. This paper aims to provide the tools to optimally size an ESS under the assumption that it will be operated under a model predictive control scheme and that the forecast ofmore » the renewable energy resources include prediction errors. A two-stage stochastic model predictive control is formulated and solved, where the optimal usage of the storage is simultaneously determined along with the optimal generation outputs and size of the storage. Wind forecast errors are taken into account in the optimization problem via probabilistic constraints for which an analytical form is derived. This allows for the stochastic optimization problem to be solved directly, without using sampling-based approaches, and sizing the storage to account not only for a wide range of potential scenarios, but also for a wide range of potential forecast errors. In the proposed formulation, we account for the fact that errors in the forecast affect how the device is operated later in the horizon and that a receding horizon scheme is used in operation to optimally use the available storage.« less

BASIMO - Borehole Heat Exchanger Array Simulation and Optimization Tool

NASA Astrophysics Data System (ADS)

Schulte, Daniel O.; Bastian, Welsch; Wolfram, Rühaak; Kristian, Bär; Ingo, Sass

2017-04-01

Arrays of borehole heat exchangers are an increasingly popular source for renewable energy. Furthermore, they can serve as borehole thermal energy storage (BTES) systems for seasonally fluctuating heat sources like solar thermal energy or district heating grids. The high temperature level of these heat sources prohibits the use of the shallow subsurface for environmental reasons. Therefore, deeper reservoirs have to be accessed instead. The increased depth of the systems results in high investment costs and has hindered the implementation of this technology until now. Therefore, research of medium deep BTES systems relies on numerical simulation models. Current simulation tools cannot - or only to some extent - describe key features like partly insulated boreholes unless they run fully discretized models of the borehole heat exchangers. However, fully discretized models often come at a high computational cost, especially for large arrays of borehole heat exchangers. We give an update on the development of BASIMO: a tool, which uses one dimensional thermal resistance and capacity models for the borehole heat exchangers coupled with a numerical finite element model for the subsurface heat transport in a dual-continuum approach. An unstructured tetrahedral mesh bypasses the limitations of structured grids for borehole path geometries, while the thermal resistance and capacity model is improved to account for borehole heat exchanger properties changing with depth. Thereby, partly insulated boreholes can be considered in the model. Furthermore, BASIMO can be used to improve the design of BTES systems: the tool allows for automated parameter variations and is readily coupled to other code like mathematical optimization algorithms. Optimization can be used to determine the required minimum system size or to increase the system performance.

REopt Lite Web Tool Evaluates Photovoltaics and Battery Storage

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

Building on the success of the REopt renewable energy integration and optimization platform, NREL has developed a free, publicly available web version of REopt called REopt Lite. REopt Lite evaluates the economics of grid-connected photovoltaics (PV) and battery storage at a site. It allows building owners to identify the system sizes and battery dispatch strategy that minimize their life cycle cost of energy. This web tool also estimates the amount of time a PV and storage system can sustain the site's critical load during a grid outage.

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

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

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

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

Collaborative Emission Reduction Model Based on Multi-Objective Optimization for Greenhouse Gases and Air Pollutants.

PubMed

Meng, Qing-chun; Rong, Xiao-xia; Zhang, Yi-min; Wan, Xiao-le; Liu, Yuan-yuan; Wang, Yu-zhi

2016-01-01

CO2 emission influences not only global climate change but also international economic and political situations. Thus, reducing the emission of CO2, a major greenhouse gas, has become a major issue in China and around the world as regards preserving the environmental ecology. Energy consumption from coal, oil, and natural gas is primarily responsible for the production of greenhouse gases and air pollutants such as SO2 and NOX, which are the main air pollutants in China. In this study, a mathematical multi-objective optimization method was adopted to analyze the collaborative emission reduction of three kinds of gases on the basis of their common restraints in different ways of energy consumption to develop an economic, clean, and efficient scheme for energy distribution. The first part introduces the background research, the collaborative emission reduction for three kinds of gases, the multi-objective optimization, the main mathematical modeling, and the optimization method. The second part discusses the four mathematical tools utilized in this study, which include the Granger causality test to analyze the causality between air quality and pollutant emission, a function analysis to determine the quantitative relation between energy consumption and pollutant emission, a multi-objective optimization to set up the collaborative optimization model that considers energy consumption, and an optimality condition analysis for the multi-objective optimization model to design the optimal-pole algorithm and obtain an efficient collaborative reduction scheme. In the empirical analysis, the data of pollutant emission and final consumption of energies of Tianjin in 1996-2012 was employed to verify the effectiveness of the model and analyze the efficient solution and the corresponding dominant set. In the last part, several suggestions for collaborative reduction are recommended and the drawn conclusions are stated.

Collaborative Emission Reduction Model Based on Multi-Objective Optimization for Greenhouse Gases and Air Pollutants

PubMed Central

Zhang, Yi-min; Wan, Xiao-le; Liu, Yuan-yuan; Wang, Yu-zhi

2016-01-01

CO2 emission influences not only global climate change but also international economic and political situations. Thus, reducing the emission of CO2, a major greenhouse gas, has become a major issue in China and around the world as regards preserving the environmental ecology. Energy consumption from coal, oil, and natural gas is primarily responsible for the production of greenhouse gases and air pollutants such as SO2 and NOX, which are the main air pollutants in China. In this study, a mathematical multi-objective optimization method was adopted to analyze the collaborative emission reduction of three kinds of gases on the basis of their common restraints in different ways of energy consumption to develop an economic, clean, and efficient scheme for energy distribution. The first part introduces the background research, the collaborative emission reduction for three kinds of gases, the multi-objective optimization, the main mathematical modeling, and the optimization method. The second part discusses the four mathematical tools utilized in this study, which include the Granger causality test to analyze the causality between air quality and pollutant emission, a function analysis to determine the quantitative relation between energy consumption and pollutant emission, a multi-objective optimization to set up the collaborative optimization model that considers energy consumption, and an optimality condition analysis for the multi-objective optimization model to design the optimal-pole algorithm and obtain an efficient collaborative reduction scheme. In the empirical analysis, the data of pollutant emission and final consumption of energies of Tianjin in 1996–2012 was employed to verify the effectiveness of the model and analyze the efficient solution and the corresponding dominant set. In the last part, several suggestions for collaborative reduction are recommended and the drawn conclusions are stated. PMID:27010658

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.

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.

A graph-based computational framework for simulation and optimisation of coupled infrastructure networks

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

Jalving, Jordan; Abhyankar, Shrirang; Kim, Kibaek

Here, we present a computational framework that facilitates the construction, instantiation, and analysis of large-scale optimization and simulation applications of coupled energy networks. The framework integrates the optimization modeling package PLASMO and the simulation package DMNetwork (built around PETSc). These tools use a common graphbased abstraction that enables us to achieve compatibility between data structures and to build applications that use network models of different physical fidelity. We also describe how to embed these tools within complex computational workflows using SWIFT, which is a tool that facilitates parallel execution of multiple simulation runs and management of input and output data.more » We discuss how to use these capabilities to target coupled natural gas and electricity systems.« less

A graph-based computational framework for simulation and optimisation of coupled infrastructure networks

DOE PAGES

Jalving, Jordan; Abhyankar, Shrirang; Kim, Kibaek; ...

2017-04-24

Here, we present a computational framework that facilitates the construction, instantiation, and analysis of large-scale optimization and simulation applications of coupled energy networks. The framework integrates the optimization modeling package PLASMO and the simulation package DMNetwork (built around PETSc). These tools use a common graphbased abstraction that enables us to achieve compatibility between data structures and to build applications that use network models of different physical fidelity. We also describe how to embed these tools within complex computational workflows using SWIFT, which is a tool that facilitates parallel execution of multiple simulation runs and management of input and output data.more » We discuss how to use these capabilities to target coupled natural gas and electricity systems.« 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.

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.

Supporting Current Energy Conversion Projects through Numerical Modeling

NASA Astrophysics Data System (ADS)

James, S. C.; Roberts, J.

2016-02-01

The primary goals of current energy conversion (CEC) technology being developed today are to optimize energy output and minimize environmental impact. CEC turbines generate energy from tidal and current systems and create wakes that interact with turbines located downstream of a device. The placement of devices can greatly influence power generation and structural reliability. CECs can also alter the environment surrounding the turbines, such as flow regimes, sediment dynamics, and water quality. These alterations pose potential stressors to numerous environmental receptors. Software is needed to investigate specific CEC sites to simulate power generation and hydrodynamic responses of a flow through a CEC turbine array so that these potential impacts can be evaluated. Moreover, this software can be used to optimize array layouts that yield the least changes to the environmental (i.e., hydrodynamics, sediment dynamics, and water quality). Through model calibration exercises, simulated wake profiles and turbulence intensities compare favorably to the experimental data and demonstrate the utility and accuracy of a fast-running tool for future siting and analysis of CEC arrays in complex domains. The Delft3D modeling tool facilitates siting of CEC projects through optimization of array layouts and evaluation of potential environmental effect all while provide a common "language" for academics, industry, and regulators to be able to discuss the implications of marine renewable energy projects. Given the enormity of any full-scale marine renewable energy project, it necessarily falls to modeling to evaluate how array operations must be addressed in an environmental impact statement in a way that engenders confidence in the assessment of the CEC array to minimize environmental effects.

Modeling and Optimization of Commercial Buildings and Stationary Fuel Cell Systems (Presentation)

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

Ainscough, C.; McLarty, D.; Sullivan, R.

2013-10-01

This presentation describes the Distributed Generation Building Energy Assessment Tool (DG-BEAT) developed by the National Renewable Energy Laboratory and the University of California Irvine. DG-BEAT is designed to allow stakeholders to assess the economics of installing stationary fuel cell systems in a variety of building types in the United States.

Martian resource locations: Identification and optimization

NASA Astrophysics Data System (ADS)

Chamitoff, Gregory; James, George; Barker, Donald; Dershowitz, Adam

2005-04-01

The identification and utilization of in situ Martian natural resources is the key to enable cost-effective long-duration missions and permanent human settlements on Mars. This paper presents a powerful software tool for analyzing Martian data from all sources, and for optimizing mission site selection based on resource collocation. This program, called Planetary Resource Optimization and Mapping Tool (PROMT), provides a wide range of analysis and display functions that can be applied to raw data or imagery. Thresholds, contours, custom algorithms, and graphical editing are some of the various methods that can be used to process data. Output maps can be created to identify surface regions on Mars that meet any specific criteria. The use of this tool for analyzing data, generating maps, and collocating features is demonstrated using data from the Mars Global Surveyor and the Odyssey spacecraft. The overall mission design objective is to maximize a combination of scientific return and self-sufficiency based on utilization of local materials. Landing site optimization involves maximizing accessibility to collocated science and resource features within a given mission radius. Mission types are categorized according to duration, energy resources, and in situ resource utilization. Preliminary optimization results are shown for a number of mission scenarios.

Rural Energy Options Analysis Training Development and Implementation at NREL

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

Gilman, P.

2005-01-01

NREL has developed a rural energy options analysis training program for rural energy decision makers that provides knowledge, skills and tools for the evaluation of technologies, including renewables, for rural energy applications. Through the Department of Energy (DOE) Solar Energy Technologies Program (SETP), NREL has refined materials for the program and developed a module that offers hands-on training in the preparation of data for options analysis using HOMER, NREL's micropower optimization model. NREL has used the materials for training in Brazil, the Maldives, Mexico, and Sri Lanka.

Solar Power Tower Integrated Layout and Optimization Tool | Concentrating

Science.gov Websites

methods to reduce the overall computational burden while generating accurate and precise results. These methods have been developed as part of the U.S. Department of Energy (DOE) SunShot Initiative research

Block-diagonalization as a tool for the robust diabatization of high-dimensional potential energy surfaces

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

Venghaus, Florian; Eisfeld, Wolfgang, E-mail: wolfgang.eisfeld@uni-bielefeld.de

2016-03-21

Robust diabatization techniques are key for the development of high-dimensional coupled potential energy surfaces (PESs) to be used in multi-state quantum dynamics simulations. In the present study we demonstrate that, besides the actual diabatization technique, common problems with the underlying electronic structure calculations can be the reason why a diabatization fails. After giving a short review of the theoretical background of diabatization, we propose a method based on the block-diagonalization to analyse the electronic structure data. This analysis tool can be used in three different ways: First, it allows to detect issues with the ab initio reference data and ismore » used to optimize the setup of the electronic structure calculations. Second, the data from the block-diagonalization are utilized for the development of optimal parametrized diabatic model matrices by identifying the most significant couplings. Third, the block-diagonalization data are used to fit the parameters of the diabatic model, which yields an optimal initial guess for the non-linear fitting required by standard or more advanced energy based diabatization methods. The new approach is demonstrated by the diabatization of 9 electronic states of the propargyl radical, yielding fully coupled full-dimensional (12D) PESs in closed form.« less

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.

Optimizing the milling characteristics of Al-SiC particulate composites

NASA Astrophysics Data System (ADS)

Karthikeyan, R.; Raghukandan, K.; Naagarazan, R. S.; Pai, B. C.

2000-12-01

The present investigation focuses on the face milling characteristics of LM25Al-SiC particulate composites produced through stir casting. Experiments were conducted according to an L27 orthogonal array and mathematical models were developed for such machining characteristics as flank wear, specific energy and surface roughness whose adequacy was checked. The insignificant effects present in the models were eliminated using a t-test. Goal programming was employed to optimize the cutting conditions by considering such primary objectives as maximizing the metal removal rate and minimizing tool wear, specific energy and surface roughness.

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.

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.

Integration of prebend optimization in a holistic wind turbine design tool

NASA Astrophysics Data System (ADS)

Sartori, L.; Bortolotti, P.; Croce, A.; Bottasso, C. L.

2016-09-01

This paper considers the problem of identifying the optimal combination of blade prebend, rotor cone angle and nacelle uptilt, within an integrated aero-structural design environment. Prebend is designed to reach maximum rotor area at rated conditions, while cone and uptilt are computed together with all other design variables to minimize the cost of energy. Constraints are added to the problem formulation in order to translate various design requirements. The proposed optimization approach is applied to a conceptual 10 MW offshore wind turbine, highlighting the benefits of an optimal combination of blade curvature, cone and uptilt angles.

Decision making based on data analysis and optimization algorithm applied for cogeneration systems integration into a grid

NASA Astrophysics Data System (ADS)

Asmar, Joseph Al; Lahoud, Chawki; Brouche, Marwan

2018-05-01

Cogeneration and trigeneration systems can contribute to the reduction of primary energy consumption and greenhouse gas emissions in residential and tertiary sectors, by reducing fossil fuels demand and grid losses with respect to conventional systems. The cogeneration systems are characterized by a very high energy efficiency (80 to 90%) as well as a less polluting aspect compared to the conventional energy production. The integration of these systems into the energy network must simultaneously take into account their economic and environmental challenges. In this paper, a decision-making strategy will be introduced and is divided into two parts. The first one is a strategy based on a multi-objective optimization tool with data analysis and the second part is based on an optimization algorithm. The power dispatching of the Lebanese electricity grid is then simulated and considered as a case study in order to prove the compatibility of the cogeneration power calculated by our decision-making technique. In addition, the thermal energy produced by the cogeneration systems which capacity is selected by our technique shows compatibility with the thermal demand for district heating.

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.

A Python tool to set up relative free energy calculations in GROMACS.

PubMed

Klimovich, Pavel V; Mobley, David L

2015-11-01

Free energy calculations based on molecular dynamics (MD) simulations have seen a tremendous growth in the last decade. However, it is still difficult and tedious to set them up in an automated manner, as the majority of the present-day MD simulation packages lack that functionality. Relative free energy calculations are a particular challenge for several reasons, including the problem of finding a common substructure and mapping the transformation to be applied. Here we present a tool, alchemical-setup.py, that automatically generates all the input files needed to perform relative solvation and binding free energy calculations with the MD package GROMACS. When combined with Lead Optimization Mapper (LOMAP; Liu et al. in J Comput Aided Mol Des 27(9):755-770, 2013), recently developed in our group, alchemical-setup.py allows fully automated setup of relative free energy calculations in GROMACS. Taking a graph of the planned calculations and a mapping, both computed by LOMAP, our tool generates the topology and coordinate files needed to perform relative free energy calculations for a given set of molecules, and provides a set of simulation input parameters. The tool was validated by performing relative hydration free energy calculations for a handful of molecules from the SAMPL4 challenge (Mobley et al. in J Comput Aided Mol Des 28(4):135-150, 2014). Good agreement with previously published results and the straightforward way in which free energy calculations can be conducted make alchemical-setup.py a promising tool for automated setup of relative solvation and binding free energy calculations.

Mathematical modeling of unicellular microalgae and cyanobacteria metabolism for biofuel production.

PubMed

Baroukh, Caroline; Muñoz-Tamayo, Rafael; Bernard, Olivier; Steyer, Jean-Philippe

2015-06-01

The conversion of microalgae lipids and cyanobacteria carbohydrates into biofuels appears to be a promising source of renewable energy. This requires a thorough understanding of their carbon metabolism, supported by mathematical models, in order to optimize biofuel production. However, unlike heterotrophic microorganisms that utilize the same substrate as sources of energy and carbon, photoautotrophic microorganisms require light for energy and CO2 as carbon source. Furthermore, they are submitted to permanent fluctuating light environments due to outdoor cultivation or mixing inducing a flashing effect. Although, modeling these nonstandard organisms is a major challenge for which classical tools are often inadequate, this step remains a prerequisite towards efficient optimization of outdoor biofuel production at an industrial scale. Copyright © 2015 Elsevier Ltd. All rights reserved.

Deterministic Computer-Controlled Polishing Process for High-Energy X-Ray Optics

NASA Technical Reports Server (NTRS)

Khan, Gufran S.; Gubarev, Mikhail; Speegle, Chet; Ramsey, Brian

2010-01-01

A deterministic computer-controlled polishing process for large X-ray mirror mandrels is presented. Using tool s influence function and material removal rate extracted from polishing experiments, design considerations of polishing laps and optimized operating parameters are discussed

Increasing energy efficiency level of building production based on applying modern mechanization facilities

NASA Astrophysics Data System (ADS)

Prokhorov, Sergey

2017-10-01

Building industry in a present day going through the hard times. Machine and mechanism exploitation cost, on a field of construction and installation works, takes a substantial part in total building construction expenses. There is a necessity to elaborate high efficient method, which allows not only to increase production, but also to reduce direct costs during machine fleet exploitation, and to increase its energy efficiency. In order to achieve the goal we plan to use modern methods of work production, hi-tech and energy saving machine tools and technologies, and use of optimal mechanization sets. As the optimization criteria there are exploitation prime cost and set efficiency. During actual task-solving process we made a conclusion, which shows that mechanization works, energy audit with production juxtaposition, prime prices and costs for energy resources allow to make complex machine fleet supply, improve ecological level and increase construction and installation work quality.

Open Tools for Integrated Modelling to Understand SDG development - The OPTIMUS program

NASA Astrophysics Data System (ADS)

Howells, Mark; Zepeda, Eduardo; Rogner, H. Holger; Sanchez, Marco; Roehrl, Alexander; Cicowiez, Matrin; Mentis, Dimitris; Korkevelos, Alexandros; Taliotis, Constantinos; Broad, Oliver; Alfstad, Thomas

2016-04-01

The recently adopted Sustainable Development Goals (SDGs) - a set of 17 measurable and time-bound goals with 169 associated targets for 2030 - are highly inclusive challenges before the world community ranging from eliminating poverty to human rights, inequality, a secure world and protection of the environment. Each individual goal or target by themselves present enormous tasks, taken together they are overwhelming. There strong and weak interlinkages, hence trade-offs and complementarities among goals and targets. Some targets may affect several goals while other goals and targets may conflict or be mutually exclusive (Ref). Meeting each of these requires the judicious exploitation of resource, with energy playing an important role. Such complexity demands to be addressed in an integrated way using systems analysis tools to support informed policy formulation, planning, allocation of scarce resources, monitoring progress, effectiveness and review at different scales. There is no one size fits all methodology that conceivably could include all goal and targets simultaneously. But there are methodologies encapsulating critical subsets of the goal and targets with strong interlinkages with a 'soft' reflection on the weak interlinkages. Universal food security or sustainable energy for all inherently support goals and targets on human rights and equality but possibly at the cost of biodiversity or desertification. Integrated analysis and planning tools are not yet commonplace at national universities - or indeed in many policy making organs. What is needed is a fundamental realignment of institutions and integrations of their planning processes and decision making. We introduce a series of open source tools to support the SDG planning and implementation process. The Global User-friendly CLEW Open Source (GLUCOSE) tool optimizes resource interactions and constraints; The Global Electrification Tool kit (GETit) provides the first global spatially explicit electrification simulator; A national CLEW tool allows for the optimization of national level integrated resource use and Macro-CLEW presents the same allowing for detailed economic-biophysical interactions. Finally open Model Management Infrastructure (MoManI) is presented that allows for the rapid prototyping of new additions to, or new resource optimization tools. Collectively these tools provide insights to some fifteen of the SDGs and are made publicly available with support to governments and academic institutions.

First-Stage Development and Validation of a Web-Based Automated Dietary Modeling Tool: Using Constraint Optimization Techniques to Streamline Food Group and Macronutrient Focused Dietary Prescriptions for Clinical Trials.

PubMed

Probst, Yasmine; Morrison, Evan; Sullivan, Emma; Dam, Hoa Khanh

2016-07-28

Standardizing the background diet of participants during a dietary randomized controlled trial is vital to trial outcomes. For this process, dietary modeling based on food groups and their target servings is employed via a dietary prescription before an intervention, often using a manual process. Partial automation has employed the use of linear programming. Validity of the modeling approach is critical to allow trial outcomes to be translated to practice. This paper describes the first-stage development of a tool to automatically perform dietary modeling using food group and macronutrient requirements as a test case. The Dietary Modeling Tool (DMT) was then compared with existing approaches to dietary modeling (manual and partially automated), which were previously available to dietitians working within a dietary intervention trial. Constraint optimization techniques were implemented to determine whether nonlinear constraints are best suited to the development of the automated dietary modeling tool using food composition and food consumption data. Dietary models were produced and compared with a manual Microsoft Excel calculator, a partially automated Excel Solver approach, and the automated DMT that was developed. The web-based DMT was produced using nonlinear constraint optimization, incorporating estimated energy requirement calculations, nutrition guidance systems, and the flexibility to amend food group targets for individuals. Percentage differences between modeling tools revealed similar results for the macronutrients. Polyunsaturated fatty acids and monounsaturated fatty acids showed greater variation between tools (practically equating to a 2-teaspoon difference), although it was not considered clinically significant when the whole diet, as opposed to targeted nutrients or energy requirements, were being addressed. Automated modeling tools can streamline the modeling process for dietary intervention trials ensuring consistency of the background diets, although appropriate constraints must be used in their development to achieve desired results. The DMT was found to be a valid automated tool producing similar results to tools with less automation. The results of this study suggest interchangeability of the modeling approaches used, although implementation should reflect the requirements of the dietary intervention trial in which it is used.

First-Stage Development and Validation of a Web-Based Automated Dietary Modeling Tool: Using Constraint Optimization Techniques to Streamline Food Group and Macronutrient Focused Dietary Prescriptions for Clinical Trials

PubMed Central

Morrison, Evan; Sullivan, Emma; Dam, Hoa Khanh

2016-01-01

Background Standardizing the background diet of participants during a dietary randomized controlled trial is vital to trial outcomes. For this process, dietary modeling based on food groups and their target servings is employed via a dietary prescription before an intervention, often using a manual process. Partial automation has employed the use of linear programming. Validity of the modeling approach is critical to allow trial outcomes to be translated to practice. Objective This paper describes the first-stage development of a tool to automatically perform dietary modeling using food group and macronutrient requirements as a test case. The Dietary Modeling Tool (DMT) was then compared with existing approaches to dietary modeling (manual and partially automated), which were previously available to dietitians working within a dietary intervention trial. Methods Constraint optimization techniques were implemented to determine whether nonlinear constraints are best suited to the development of the automated dietary modeling tool using food composition and food consumption data. Dietary models were produced and compared with a manual Microsoft Excel calculator, a partially automated Excel Solver approach, and the automated DMT that was developed. Results The web-based DMT was produced using nonlinear constraint optimization, incorporating estimated energy requirement calculations, nutrition guidance systems, and the flexibility to amend food group targets for individuals. Percentage differences between modeling tools revealed similar results for the macronutrients. Polyunsaturated fatty acids and monounsaturated fatty acids showed greater variation between tools (practically equating to a 2-teaspoon difference), although it was not considered clinically significant when the whole diet, as opposed to targeted nutrients or energy requirements, were being addressed. Conclusions Automated modeling tools can streamline the modeling process for dietary intervention trials ensuring consistency of the background diets, although appropriate constraints must be used in their development to achieve desired results. The DMT was found to be a valid automated tool producing similar results to tools with less automation. The results of this study suggest interchangeability of the modeling approaches used, although implementation should reflect the requirements of the dietary intervention trial in which it is used. PMID:27471104

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.

Streamflow variability and optimal capacity of run-of-river hydropower plants

NASA Astrophysics Data System (ADS)

Basso, S.; Botter, G.

2012-10-01

The identification of the capacity of a run-of-river plant which allows for the optimal utilization of the available water resources is a challenging task, mainly because of the inherent temporal variability of river flows. This paper proposes an analytical framework to describe the energy production and the economic profitability of small run-of-river power plants on the basis of the underlying streamflow regime. We provide analytical expressions for the capacity which maximize the produced energy as a function of the underlying flow duration curve and minimum environmental flow requirements downstream of the plant intake. Similar analytical expressions are derived for the capacity which maximize the economic return deriving from construction and operation of a new plant. The analytical approach is applied to a minihydro plant recently proposed in a small Alpine catchment in northeastern Italy, evidencing the potential of the method as a flexible and simple design tool for practical application. The analytical model provides useful insight on the major hydrologic and economic controls (e.g., streamflow variability, energy price, costs) on the optimal plant capacity and helps in identifying policy strategies to reduce the current gap between the economic and energy optimizations of run-of-river plants.

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.

NASA Products to Enhance Energy Utility Load Forecasting

NASA Technical Reports Server (NTRS)

Lough, G.; Zell, E.; Engel-Cox, J.; Fungard, Y.; Jedlovec, G.; Stackhouse, P.; Homer, R.; Biley, S.

2012-01-01

Existing energy load forecasting tools rely upon historical load and forecasted weather to predict load within energy company service areas. The shortcomings of load forecasts are often the result of weather forecasts that are not at a fine enough spatial or temporal resolution to capture local-scale weather events. This project aims to improve the performance of load forecasting tools through the integration of high-resolution, weather-related NASA Earth Science Data, such as temperature, relative humidity, and wind speed. Three companies are participating in operational testing one natural gas company, and two electric providers. Operational results comparing load forecasts with and without NASA weather forecasts have been generated since March 2010. We have worked with end users at the three companies to refine selection of weather forecast information and optimize load forecast model performance. The project will conclude in 2012 with transitioning documented improvements from the inclusion of NASA forecasts for sustained use by energy utilities nationwide in a variety of load forecasting tools. In addition, Battelle has consulted with energy companies nationwide to document their information needs for long-term planning, in light of climate change and regulatory impacts.

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

No Cost – Low Cost Compressed Air System Optimization in Industry

NASA Astrophysics Data System (ADS)

Dharma, A.; Budiarsa, N.; Watiniasih, N.; Antara, N. G.

2018-04-01

Energy conservation is a systematic, integrated of effort, in order to preserve energy sources and improve energy utilization efficiency. Utilization of energy in efficient manner without reducing the energy usage it must. Energy conservation efforts are applied at all stages of utilization, from utilization of energy resources to final, using efficient technology, and cultivating an energy-efficient lifestyle. The most common way is to promote energy efficiency in the industry on end use and overcome barriers to achieve such efficiency by using system energy optimization programs. The facts show that energy saving efforts in the process usually only focus on replacing tools and not an overall system improvement effort. In this research, a framework of sustainable energy reduction work in companies that have or have not implemented energy management system (EnMS) will be conducted a systematic technical approach in evaluating accurately a compressed-air system and potential optimization through observation, measurement and verification environmental conditions and processes, then processing the physical quantities of systems such as air flow, pressure and electrical power energy at any given time measured using comparative analysis methods in this industry, to provide the potential savings of energy saving is greater than the component approach, with no cost to the lowest cost (no cost - low cost). The process of evaluating energy utilization and energy saving opportunities will provide recommendations for increasing efficiency in the industry and reducing CO2 emissions and improving environmental quality.

2-D energy analyzer for low energy electrons

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

Karkare, Siddharth, E-mail: ssk226@cornell.edu; Cultrera, Luca; Hwang, Yoon-Woo

2015-03-15

A 2-D electron energy analyzer is designed and constructed to measure the transverse and longitudinal energy distribution of low energy (<1 eV) electrons. The analyzer operates on the principle of adiabatic invariance and motion of low energy electrons in a strong longitudinal magnetic field. The operation of the analyzer is studied in detail and a design to optimize the energy resolution, signal to noise ratio, and physical size is presented. An energy resolution better than 6 meV has been demonstrated. Such an analyzer is a powerful tool to study the process of photoemission which limits the beam quality in modernmore » accelerators.« less

Enhanced Energy Localization in Hyperthermia Treatment Based on Hybrid Electromagnetic and Ultrasonic System: Proof of Concept with Numerical Simulations.

PubMed

Nizam-Uddin, N; Elshafiey, Ibrahim

2017-01-01

This paper proposes a hybrid hyperthermia treatment system, utilizing two noninvasive modalities for treating brain tumors. The proposed system depends on focusing electromagnetic (EM) and ultrasound (US) energies. The EM hyperthermia subsystem enhances energy localization by incorporating a multichannel wideband setting and coherent-phased-array technique. A genetic algorithm based optimization tool is developed to enhance the specific absorption rate (SAR) distribution by reducing hotspots and maximizing energy deposition at tumor regions. The treatment performance is also enhanced by augmenting an ultrasonic subsystem to allow focused energy deposition into deep tumors. The therapeutic faculty of ultrasonic energy is assessed by examining the control of mechanical alignment of transducer array elements. A time reversal (TR) approach is then investigated to address challenges in energy focus in both subsystems. Simulation results of the synergetic effect of both modalities assuming a simplified model of human head phantom demonstrate the feasibility of the proposed hybrid technique as a noninvasive tool for thermal treatment of brain tumors.

Enhanced Energy Localization in Hyperthermia Treatment Based on Hybrid Electromagnetic and Ultrasonic System: Proof of Concept with Numerical Simulations

PubMed Central

Elshafiey, Ibrahim

2017-01-01

This paper proposes a hybrid hyperthermia treatment system, utilizing two noninvasive modalities for treating brain tumors. The proposed system depends on focusing electromagnetic (EM) and ultrasound (US) energies. The EM hyperthermia subsystem enhances energy localization by incorporating a multichannel wideband setting and coherent-phased-array technique. A genetic algorithm based optimization tool is developed to enhance the specific absorption rate (SAR) distribution by reducing hotspots and maximizing energy deposition at tumor regions. The treatment performance is also enhanced by augmenting an ultrasonic subsystem to allow focused energy deposition into deep tumors. The therapeutic faculty of ultrasonic energy is assessed by examining the control of mechanical alignment of transducer array elements. A time reversal (TR) approach is then investigated to address challenges in energy focus in both subsystems. Simulation results of the synergetic effect of both modalities assuming a simplified model of human head phantom demonstrate the feasibility of the proposed hybrid technique as a noninvasive tool for thermal treatment of brain tumors. PMID:28840125

Application of a forest-simulation model to assess the energy yield and ecological impact of forest utilization for energy

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

Doyle, T W; Shugart, H H; West, D C

1981-01-01

This study examines the utilization and management of natural forest lands to meet growing wood-energy demands. An application of a forest simulation model is described for assessing energy returns and long-term ecological impacts of wood-energy harvesting under four general silvicultural practices. Results indicate that moderate energy yields could be expected from mild cutting operations which would significantly effect neither the commercial timber market nor the composition, structure, or diversity of these forests. Forest models can provide an effective tool for determining optimal management strategies that maximize energy returns, minimize environmental detriment, and complement existing land-use plans.

Battery Lifetime Analysis and Simulation Tool (BLAST) Documentation

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

Neubauer, J.

2014-12-01

The deployment and use of lithium-ion (Li-ion) batteries in automotive and stationary energy storage applications must be optimized to justify their high up-front costs. Given that batteries degrade with use and storage, such optimizations must evaluate many years of operation. As the degradation mechanisms are sensitive to temperature, state-of-charge (SOC) histories, current levels, and cycle depth and frequency, it is important to model both the battery and the application to a high level of detail to ensure battery response is accurately predicted. To address these issues, the National Renewable Energy Laboratory (NREL) has developed the Battery Lifetime Analysis and Simulationmore » Tool (BLAST) suite. This suite of tools pairs NREL’s high-fidelity battery degradation model with a battery electrical and thermal performance model, application-specific electrical and thermal performance models of the larger system (e.g., an electric vehicle), application-specific system use data (e.g., vehicle travel patterns and driving data), and historic climate data from cities across the United States. This provides highly realistic long-term predictions of battery response and thereby enables quantitative comparisons of varied battery use strategies.« less

Optimized dispatch in a first-principles concentrating solar power production model

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

Wagner, Michael J.; Newman, Alexandra M.; Hamilton, William T.

Concentrating solar power towers, which include a steam-Rankine cycle with molten salt thermal energy storage, is an emerging technology whose maximum effectiveness relies on an optimal operational and dispatch policy. Given parameters such as start-up and shut-down penalties, expected electricity price profiles, solar availability, and system interoperability requirements, this paper seeks a profit-maximizing solution that determines start-up and shut-down times for the power cycle and solar receiver, and the times at which to dispatch stored and instantaneous quantities of energy over a 48-h horizon at hourly fidelity. The mixed-integer linear program (MIP) is subject to constraints including: (i) minimum andmore » maximum rates of start-up and shut-down, (ii) energy balance, including energetic state of the system as a whole and its components, (iii) logical rules governing the operational modes of the power cycle and solar receiver, and (iv) operational consistency between time periods. The novelty in this work lies in the successful integration of a dispatch optimization model into a detailed techno-economic analysis tool, specifically, the National Renewable Energy Laboratory's System Advisor Model (SAM). The MIP produces an optimized operating strategy, historically determined via a heuristic. Using several market electricity pricing profiles, we present comparative results for a system with and without dispatch optimization, indicating that dispatch optimization can improve plant profitability by 5-20% and thereby alter the economics of concentrating solar power technology. While we examine a molten salt power tower system, this analysis is equally applicable to the more mature concentrating solar parabolic trough system with thermal energy storage.« less

Harnessing the power of emerging petascale platforms

NASA Astrophysics Data System (ADS)

Mellor-Crummey, John

2007-07-01

As part of the US Department of Energy's Scientific Discovery through Advanced Computing (SciDAC-2) program, science teams are tackling problems that require computational simulation and modeling at the petascale. A grand challenge for computer science is to develop software technology that makes it easier to harness the power of these systems to aid scientific discovery. As part of its activities, the SciDAC-2 Center for Scalable Application Development Software (CScADS) is building open source software tools to support efficient scientific computing on the emerging leadership-class platforms. In this paper, we describe two tools for performance analysis and tuning that are being developed as part of CScADS: a tool for analyzing scalability and performance, and a tool for optimizing loop nests for better node performance. We motivate these tools by showing how they apply to S3D, a turbulent combustion code under development at Sandia National Laboratory. For S3D, our node performance analysis tool helped uncover several performance bottlenecks. Using our loop nest optimization tool, we transformed S3D's most costly loop nest to reduce execution time by a factor of 2.94 for a processor working on a 503 domain.

A Summary Description of a Computer Program Concept for the Design and Simulation of Solar Pond Electric Power Generation Systems

NASA Technical Reports Server (NTRS)

1984-01-01

A solar pond electric power generation subsystem, an electric power transformer and switch yard, a large solar pond, a water treatment plant, and numerous storage and evaporation ponds. Because a solar pond stores thermal energy over a long period of time, plant operation at any point in time is dependent upon past operation and future perceived generation plans. This time or past history factor introduces a new dimension in the design process. The design optimization of a plant must go beyond examination of operational state points and consider the seasonal variations in solar, solar pond energy storage, and desired plant annual duty-cycle profile. Models or design tools will be required to optimize a plant design. These models should be developed in order to include a proper but not excessive level of detail. The model should be targeted to a specific objective and not conceived as a do everything analysis tool, i.e., system design and not gradient-zone stability.

Complex-energy approach to sum rules within nuclear density functional theory

DOE PAGES

Hinohara, Nobuo; Kortelainen, Markus; Nazarewicz, Witold; ...

2015-04-27

The linear response of the nucleus to an external field contains unique information about the effective interaction, correlations governing the behavior of the many-body system, and properties of its excited states. To characterize the response, it is useful to use its energy-weighted moments, or sum rules. By comparing computed sum rules with experimental values, the information content of the response can be utilized in the optimization process of the nuclear Hamiltonian or nuclear energy density functional (EDF). But the additional information comes at a price: compared to the ground state, computation of excited states is more demanding. To establish anmore » efficient framework to compute energy-weighted sum rules of the response that is adaptable to the optimization of the nuclear EDF and large-scale surveys of collective strength, we have developed a new technique within the complex-energy finite-amplitude method (FAM) based on the quasiparticle random- phase approximation. The proposed sum-rule technique based on the complex-energy FAM is a tool of choice when optimizing effective interactions or energy functionals. The method is very efficient and well-adaptable to parallel computing. As a result, the FAM formulation is especially useful when standard theorems based on commutation relations involving the nuclear Hamiltonian and external field cannot be used.« less

Campus Energy Approach, REopt Overview, and Solar for Universities

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

Elgqvist, Emma M; Van Geet, Otto D

2017-10-19

This presentation gives an overview of the climate neutral research campus framework for reducing energy use and meeting net zero electricity on research campuses. It gives an overview of REopt and the REopt Lite web tool, which can be used to evaluate cost optimal sizes of behind the meter PV and storage. It includes solar PV installation trends at universities and case studies for projects implemented on university campuses.

Material Distribution Optimization for the Shell Aircraft Composite Structure

NASA Astrophysics Data System (ADS)

Shevtsov, S.; Zhilyaev, I.; Oganesyan, P.; Axenov, V.

2016-09-01

One of the main goal in aircraft structures designing isweight decreasing and stiffness increasing. Composite structures recently became popular in aircraft because of their mechanical properties and wide range of optimization possibilities.Weight distribution and lay-up are keys to creating lightweight stiff strictures. In this paperwe discuss optimization of specific structure that undergoes the non-uniform air pressure at the different flight conditions and reduce a level of noise caused by the airflowinduced vibrations at the constrained weight of the part. Initial model was created with CAD tool Siemens NX, finite element analysis and post processing were performed with COMSOL Multiphysicsr and MATLABr. Numerical solutions of the Reynolds averaged Navier-Stokes (RANS) equations supplemented by k-w turbulence model provide the spatial distributions of air pressure applied to the shell surface. At the formulation of optimization problem the global strain energy calculated within the optimized shell was assumed as the objective. Wall thickness has been changed using parametric approach by an initiation of auxiliary sphere with varied radius and coordinates of the center, which were the design variables. To avoid a local stress concentration, wall thickness increment was defined as smooth function on the shell surface dependent of auxiliary sphere position and size. Our study consists of multiple steps: CAD/CAE transformation of the model, determining wind pressure for different flow angles, optimizing wall thickness distribution for specific flow angles, designing a lay-up for optimal material distribution. The studied structure was improved in terms of maximum and average strain energy at the constrained expense ofweight growth. Developed methods and tools can be applied to wide range of shell-like structures made of multilayered quasi-isotropic laminates.

Mars Mission Optimization Based on Collocation of Resources

NASA Technical Reports Server (NTRS)

Chamitoff, G. E.; James, G. H.; Barker, D. C.; Dershowitz, A. L.

2003-01-01

This paper presents a powerful approach for analyzing Martian data and for optimizing mission site selection based on resource collocation. This approach is implemented in a program called PROMT (Planetary Resource Optimization and Mapping Tool), which provides a wide range of analysis and display functions that can be applied to raw data or imagery. Thresholds, contours, custom algorithms, and graphical editing are some of the various methods that can be used to process data. Output maps can be created to identify surface regions on Mars that meet any specific criteria. The use of this tool for analyzing data, generating maps, and collocating features is demonstrated using data from the Mars Global Surveyor and the Odyssey spacecraft. The overall mission design objective is to maximize a combination of scientific return and self-sufficiency based on utilization of local materials. Landing site optimization involves maximizing accessibility to collocated science and resource features within a given mission radius. Mission types are categorized according to duration, energy resources, and in-situ resource utilization. Optimization results are shown for a number of mission scenarios.

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

New Approaches to Minimum-Energy Design of Integer- and Fractional-Order Perfect Control Algorithms

NASA Astrophysics Data System (ADS)

Hunek, Wojciech P.; Wach, Łukasz

2017-10-01

In this paper the new methods concerning the energy-based minimization of the perfect control inputs is presented. For that reason the multivariable integer- and fractional-order models are applied which can be used for describing a various real world processes. Up to now, the classical approaches have been used in forms of minimum-norm/least squares inverses. Notwithstanding, the above-mentioned tool do not guarantee the optimal control corresponding to optimal input energy. Therefore the new class of inversebased methods has been introduced, in particular the new σ- and H-inverse of nonsquare parameter and polynomial matrices. Thus a proposed solution remarkably outperforms the typical ones in systems where the control runs can be understood in terms of different physical quantities, for example heat and mass transfer, electricity etc. A simulation study performed in Matlab/Simulink environment confirms the big potential of the new energy-based approaches.

High Performance Computing Modeling Advances Accelerator Science for High-Energy Physics

DOE PAGES

Amundson, James; Macridin, Alexandru; Spentzouris, Panagiotis

2014-07-28

The development and optimization of particle accelerators are essential for advancing our understanding of the properties of matter, energy, space, and time. Particle accelerators are complex devices whose behavior involves many physical effects on multiple scales. Therefore, advanced computational tools utilizing high-performance computing are essential for accurately modeling them. In the past decade, the US Department of Energy's SciDAC program has produced accelerator-modeling tools that have been employed to tackle some of the most difficult accelerator science problems. The authors discuss the Synergia framework and its applications to high-intensity particle accelerator physics. Synergia is an accelerator simulation package capable ofmore » handling the entire spectrum of beam dynamics simulations. Our authors present Synergia's design principles and its performance on HPC platforms.« less

Evaluation of the Predictive Index for Osteoporosis as a Clinical Tool to Identify the Risk of Osteoporosis in Korean Men by Using the Korea National Health and Nutrition Examination Survey Data.

PubMed

Moon, Ji Hyun; Kim, Lee Oh; Kim, Hyeon Ju; Kong, Mi Hee

2016-11-01

We previously proposed the Predictive Index for Osteoporosis as a new index to identify men who require bone mineral density measurement. However, the previous study had limitations such as a single-center design and small sample size. Here, we evaluated the usefulness of the Predictive Index for Osteoporosis using the nationally representative data of the Korea National Health and Nutrition Examination Survey. Participants underwent bone mineral density measurements via dual energy X-ray absorptiometry, and the Predictive Index for Osteoporosis and Osteoporosis Self-Assessment Tool for Asians were assessed. Receiver operating characteristic analysis was used to obtain optimal cut-off points for the Predictive Index for Osteoporosis and Osteoporosis Self-Assessment Tool for Asians, and the predictability of osteoporosis for the 2 indices was compared. Both indices were useful clinical tools for identifying osteoporosis risk in Korean men. The optimal cut-off value for the Predictive Index for Osteoporosis was 1.07 (sensitivity, 67.6%; specificity, 72.7%; area under the curve, 0.743). When using a cut-off point of 0.5 for the Osteoporosis Self-Assessment Tool for Asians, the sensitivity and specificity were 71.9% and 64.0%, respectively, and the area under the curve was 0.737. The Predictive Index for Osteoporosis was as useful as the Osteoporosis Self-Assessment Tool for Asians as a screening index to identify candidates for dual energy X-ray absorptiometry among men aged 50-69 years.

Energy Saving Melting and Revert Reduction Technology (E-SMARRT): Development of Surface Engineered Coating Systems for Aluminum Pressure Die Casting Dies: Towards a 'Smart' Die Coating

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

Dr. John J. Moore; Dr. Jianliang Lin,

2012-07-31

The main objective of this research program was to design and develop an optimal coating system that extends die life by minimizing premature die failure. In high-pressure aluminum die-casting, the die, core pins and inserts must withstand severe processing conditions. Many of the dies and tools in the industry are being coated to improve wear-resistance and decrease down-time for maintenance. However, thermal fatigue in metal itself can still be a major problem, especially since it often leads to catastrophic failure (i.e. die breakage) as opposed to a wear-based failure (parts begin to go out of tolerance). Tooling costs remain themore » largest portion of production costs for many of these parts, so the ability prevent catastrophic failures would be transformative for the manufacturing industry.The technology offers energy savings through reduced energy use in the die casting process from several factors, including increased life of the tools and dies, reuse of the dies and die components, reduction/elimination of lubricants, and reduced machine down time, and reduction of Al solder sticking on the die. The use of the optimized die coating system will also reduce environmental wastes and scrap parts. Current (2012) annual energy saving estimates, based on initial dissemination to the casting industry in 2010 and market penetration of 80% by 2020, is 3.1 trillion BTU's/year. The average annual estimate of CO2 reduction per year through 2020 is 0.63 Million Metric Tons of Carbon Equivalent (MM TCE).« less

Electrification pathways for Kenya-linking spatial electrification analysis and medium to long term energy planning

NASA Astrophysics Data System (ADS)

Moksnes, Nandi; Korkovelos, Alexandros; Mentis, Dimitrios; Howells, Mark

2017-09-01

In September 2015 UN announced 17 Sustainable Development goals (SDG) from which goal number 7 envisions universal access to modern energy services for all by 2030. In Kenya only about 46% of the population currently has access to electricity. This paper analyses hypothetical scenarios, and selected implications, investigating pathways that would allow the country to reach its electrification targets by 2030. Two modelling tools were used for the purposes of this study, namely OnSSET and OSeMOSYS. The tools were soft-linked in order to capture both the spatial and temporal dynamics of their nature. Two electricity demand scenarios were developed representing low and high end user consumption goals respectively. Indicatively, results show that geothermal, coal, hydro and natural gas would consist the optimal energy mix for the centralized national grid. However, in the case of the low demand scenario a high penetration of stand-alone systems is evident in the country, reaching out to approximately 47% of the electrified population. Increasing end user consumption leads to a shift in the optimal technology mix, with higher penetration of mini-grid technologies and grid extension.

Global parameter optimization of a Mather-type plasma focus in the framework of the Gratton-Vargas two-dimensional snowplow model

NASA Astrophysics Data System (ADS)

Auluck, S. K. H.

2014-12-01

Dense plasma focus (DPF) is known to produce highly energetic ions, electrons and plasma environment which can be used for breeding short-lived isotopes, plasma nanotechnology and other material processing applications. Commercial utilization of DPF in such areas would need a design tool that can be deployed in an automatic search for the best possible device configuration for a given application. The recently revisited (Auluck 2013 Phys. Plasmas 20 112501) Gratton-Vargas (GV) two-dimensional analytical snowplow model of plasma focus provides a numerical formula for dynamic inductance of a Mather-type plasma focus fitted to thousands of automated computations, which enables the construction of such a design tool. This inductance formula is utilized in the present work to explore global optimization, based on first-principles optimality criteria, in a four-dimensional parameter-subspace of the zero-resistance GV model. The optimization process is shown to reproduce the empirically observed constancy of the drive parameter over eight decades in capacitor bank energy. The optimized geometry of plasma focus normalized to the anode radius is shown to be independent of voltage, while the optimized anode radius is shown to be related to capacitor bank inductance.

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

DOE PAGES

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

2014-10-15

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

The use of least squares methods in functional optimization of energy use prediction models

NASA Astrophysics Data System (ADS)

Bourisli, Raed I.; Al-Shammeri, Basma S.; AlAnzi, Adnan A.

2012-06-01

The least squares method (LSM) is used to optimize the coefficients of a closed-form correlation that predicts the annual energy use of buildings based on key envelope design and thermal parameters. Specifically, annual energy use is related to a number parameters like the overall heat transfer coefficients of the wall, roof and glazing, glazing percentage, and building surface area. The building used as a case study is a previously energy-audited mosque in a suburb of Kuwait City, Kuwait. Energy audit results are used to fine-tune the base case mosque model in the VisualDOE{trade mark, serif} software. Subsequently, 1625 different cases of mosques with varying parameters were developed and simulated in order to provide the training data sets for the LSM optimizer. Coefficients of the proposed correlation are then optimized using multivariate least squares analysis. The objective is to minimize the difference between the correlation-predicted results and the VisualDOE-simulation results. It was found that the resulting correlation is able to come up with coefficients for the proposed correlation that reduce the difference between the simulated and predicted results to about 0.81%. In terms of the effects of the various parameters, the newly-defined weighted surface area parameter was found to have the greatest effect on the normalized annual energy use. Insulating the roofs and walls also had a major effect on the building energy use. The proposed correlation and methodology can be used during preliminary design stages to inexpensively assess the impacts of various design variables on the expected energy use. On the other hand, the method can also be used by municipality officials and planners as a tool for recommending energy conservation measures and fine-tuning energy codes.

Global optimization framework for solar building design

NASA Astrophysics Data System (ADS)

Silva, N.; Alves, N.; Pascoal-Faria, P.

2017-07-01

The generative modeling paradigm is a shift from static models to flexible models. It describes a modeling process using functions, methods and operators. The result is an algorithmic description of the construction process. Each evaluation of such an algorithm creates a model instance, which depends on its input parameters (width, height, volume, roof angle, orientation, location). These values are normally chosen according to aesthetic aspects and style. In this study, the model's parameters are automatically generated according to an objective function. A generative model can be optimized according to its parameters, in this way, the best solution for a constrained problem is determined. Besides the establishment of an overall framework design, this work consists on the identification of different building shapes and their main parameters, the creation of an algorithmic description for these main shapes and the formulation of the objective function, respecting a building's energy consumption (solar energy, heating and insulation). Additionally, the conception of an optimization pipeline, combining an energy calculation tool with a geometric scripting engine is presented. The methods developed leads to an automated and optimized 3D shape generation for the projected building (based on the desired conditions and according to specific constrains). The approach proposed will help in the construction of real buildings that account for less energy consumption and for a more sustainable world.

OPTIMIZATION OF MUD HAMMER DRILLING PERFORMANCE - A PROGRAM TO BENCHMARK THE VIABILITY OF ADVANCED MUD HAMMER DRILLING

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

Arnis Judzis

2003-07-01

This document details the progress to date on the ''OPTIMIZATION OF MUD HAMMER DRILLING PERFORMANCE--A PROGRAM TO BENCHMARK THE VIABILITY OF ADVANCED MUD HAMMER DRILLING'' contract for the quarter starting April 2003 through June 2003. The DOE and TerraTek continue to wait for Novatek on the optimization portion of the testing program (they are completely rebuilding their fluid hammer). Accomplishments included the following: (1) Hughes Christensen has recently expressed interest in the possibility of a program to examine cutter impact testing, which would be useful in a better understanding of the physics of rock impact. Their interest however is notmore » necessarily fluid hammers, but to use the information for drilling bit development. (2) Novatek (cost sharing supplier of tools) has informed the DOE project manager that their tool may not be ready for ''optimization'' testing late summer 2003 (August-September timeframe) as originally anticipated. During 3Q Novatek plans to meet with TerraTek to discuss progress with their tool for 4Q 2003 testing. (3) A task for an addendum to the hammer project related to cutter impact studies was written during 2Q 2003. (4) Smith International internally is upgrading their hammer for the optimization testing phase. One currently known area of improvement is their development program to significantly increase the hammer blow energy.« less

Thermal environment analysis and energy conservation research of rural residence in cold regions of China based on BIM platform

NASA Astrophysics Data System (ADS)

Dong, J. Y.; Cheng, W.; Ma, C. P.; Xin, L. S.; Tan, Y. T.

2017-06-01

In order to study the issue of rural residential energy consumption in cold regions of China, modeled an architecture prototype based on BIM platform according to the affecting factors of rural residential thermal environment, and imported the virtual model which contains building information into energy analysis tools and chose the appropriate building orientation. By analyzing the energy consumption of the residential buildings with different enclosure structure forms, we designed the optimal energy-saving residence form. There is a certain application value of this method for researching the energy consumption and energy-saving design for the rural residence in cold regions of China.

Mitigating energy loss on distribution lines through the allocation of reactors

NASA Astrophysics Data System (ADS)

Miranda, T. M.; Romero, F.; Meffe, A.; Castilho Neto, J.; Abe, L. F. T.; Corradi, F. E.

2018-03-01

This paper presents a methodology for automatic reactors allocation on medium voltage distribution lines to reduce energy loss. In Brazil, some feeders are distinguished by their long lengths and very low load, which results in a high influence of the capacitance of the line on the circuit’s performance, requiring compensation through the installation of reactors. The automatic allocation is accomplished using an optimization meta-heuristic called Global Neighbourhood Algorithm. Given a set of reactor models and a circuit, it outputs an optimal solution in terms of reduction of energy loss. The algorithm is also able to verify if the voltage limits determined by the user are not being violated, besides checking for energy quality. The methodology was implemented in a software tool, which can also show the allocation graphically. A simulation with four real feeders is presented in the paper. The obtained results were able to reduce the energy loss significantly, from 50.56%, in the worst case, to 93.10%, in the best case.

Large Scale Bacterial Colony Screening of Diversified FRET Biosensors

PubMed Central

Litzlbauer, Julia; Schifferer, Martina; Ng, David; Fabritius, Arne; Thestrup, Thomas; Griesbeck, Oliver

2015-01-01

Biosensors based on Förster Resonance Energy Transfer (FRET) between fluorescent protein mutants have started to revolutionize physiology and biochemistry. However, many types of FRET biosensors show relatively small FRET changes, making measurements with these probes challenging when used under sub-optimal experimental conditions. Thus, a major effort in the field currently lies in designing new optimization strategies for these types of sensors. Here we describe procedures for optimizing FRET changes by large scale screening of mutant biosensor libraries in bacterial colonies. We describe optimization of biosensor expression, permeabilization of bacteria, software tools for analysis, and screening conditions. The procedures reported here may help in improving FRET changes in multiple suitable classes of biosensors. PMID:26061878

Designs for Risk Evaluation and Management

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

The Designs for Risk Evaluation and Management (DREAM) tool was developed as part of the effort to quantify the risk of geologic storage of carbon dioxide (CO 2) under the U.S. Department of Energy's National Risk Assessment Partnership (NRAP). DREAM is an optimization tool created to identify optimal monitoring schemes that minimize the time to first detection of CO 2 leakage from a subsurface storage formation. DREAM acts as a post-processer on user-provided output from subsurface leakage simulations. While DREAM was developed for CO 2 leakage scenarios, it is applicable to any subsurface leakage simulation of the same output format.more » The DREAM tool is comprised of three main components: (1) a Java wizard used to configure and execute the simulations, (2) a visualization tool to view the domain space and optimization results, and (3) a plotting tool used to analyze the results. A secondary Java application is provided to aid users in converting common American Standard Code for Information Interchange (ASCII) output data to the standard DREAM hierarchical data format (HDF5). DREAM employs a simulated annealing approach that searches the solution space by iteratively mutating potential monitoring schemes built of various configurations of monitoring locations and leak detection parameters. This approach has proven to be orders of magnitude faster than an exhaustive search of the entire solution space. The user's manual illustrates the program graphical user interface (GUI), describes the tool inputs, and includes an example application.« less

Contributions on Optimizing Approximations in the Study of Melting and Solidification Processes That Occur in Processing by Electro-Erosion

NASA Astrophysics Data System (ADS)

Potra, F. L.; Potra, T.; Soporan, V. F.

We propose two optimization methods of the processes which appear in EDM (Electrical Discharge Machining). First refers to the introduction of a new function approximating the thermal flux energy in EDM machine. Classical researches approximate this energy with the Gauss' function. In the case of unconventional technology the Gauss' bell became null only for r → +∞, where r is the radius of crater produced by EDM. We introduce a cubic spline regression which descends to zero at the crater's boundary. In the second optimization we propose modifications in technologies' work regarding the displacement of the tool electrode to the piece electrode such that the material melting to be realized in optimal time and the feeding speed with dielectric liquid regarding the solidification of the expulsed material. This we realize using the FAHP algorithm based on the theory of eigenvalues and eigenvectors, which lead to mean values of best approximation. [6

E-novo: an automated workflow for efficient structure-based lead optimization.

PubMed

Pearce, Bradley C; Langley, David R; Kang, Jia; Huang, Hongwei; Kulkarni, Amit

2009-07-01

An automated E-Novo protocol designed as a structure-based lead optimization tool was prepared through Pipeline Pilot with existing CHARMm components in Discovery Studio. A scaffold core having 3D binding coordinates of interest is generated from a ligand-bound protein structural model. Ligands of interest are generated from the scaffold using an R-group fragmentation/enumeration tool within E-Novo, with their cores aligned. The ligand side chains are conformationally sampled and are subjected to core-constrained protein docking, using a modified CHARMm-based CDOCKER method to generate top poses along with CDOCKER energies. In the final stage of E-Novo, a physics-based binding energy scoring function ranks the top ligand CDOCKER poses using a more accurate Molecular Mechanics-Generalized Born with Surface Area method. Correlation of the calculated ligand binding energies with experimental binding affinities were used to validate protocol performance. Inhibitors of Src tyrosine kinase, CDK2 kinase, beta-secretase, factor Xa, HIV protease, and thrombin were used to test the protocol using published ligand crystal structure data within reasonably defined binding sites. In-house Respiratory Syncytial Virus inhibitor data were used as a more challenging test set using a hand-built binding model. Least squares fits for all data sets suggested reasonable validation of the protocol within the context of observed ligand binding poses. The E-Novo protocol provides a convenient all-in-one structure-based design process for rapid assessment and scoring of lead optimization libraries.

Planning low-carbon electricity systems under uncertainty considering operational flexibility and smart grid technologies.

PubMed

Moreno, Rodrigo; Street, Alexandre; Arroyo, José M; Mancarella, Pierluigi

2017-08-13

Electricity grid operators and planners need to deal with both the rapidly increasing integration of renewables and an unprecedented level of uncertainty that originates from unknown generation outputs, changing commercial and regulatory frameworks aimed to foster low-carbon technologies, the evolving availability of market information on feasibility and costs of various technologies, etc. In this context, there is a significant risk of locking-in to inefficient investment planning solutions determined by current deterministic engineering practices that neither capture uncertainty nor represent the actual operation of the planned infrastructure under high penetration of renewables. We therefore present an alternative optimization framework to plan electricity grids that deals with uncertain scenarios and represents increased operational details. The presented framework is able to model the effects of an array of flexible, smart grid technologies that can efficiently displace the need for conventional solutions. We then argue, and demonstrate via the proposed framework and an illustrative example, that proper modelling of uncertainty and operational constraints in planning is key to valuing operationally flexible solutions leading to optimal investment in a smart grid context. Finally, we review the most used practices in power system planning under uncertainty, highlight the challenges of incorporating operational aspects and advocate the need for new and computationally effective optimization tools to properly value the benefits of flexible, smart grid solutions in planning. Such tools are essential to accelerate the development of a low-carbon energy system and investment in the most appropriate portfolio of renewable energy sources and complementary enabling smart technologies.This article is part of the themed issue 'Energy management: flexibility, risk and optimization'. © 2017 The Author(s).

Energy solutions in rural Africa: mapping electrification costs of distributed solar and diesel generation versus grid extension

NASA Astrophysics Data System (ADS)

Szabó, S.; Bódis, K.; Huld, T.; Moner-Girona, M.

2011-07-01

Three rural electrification options are analysed showing the cost optimal conditions for a sustainable energy development applying renewable energy sources in Africa. A spatial electricity cost model has been designed to point out whether diesel generators, photovoltaic systems or extension of the grid are the least-cost option in off-grid areas. The resulting mapping application offers support to decide in which regions the communities could be electrified either within the grid or in an isolated mini-grid. Donor programs and National Rural Electrification Agencies (or equivalent governmental departments) could use this type of delineation for their program boundaries and then could use the local optimization tools adapted to the prevailing parameters. The views expressed in this paper are those of the authors and do not necessarily represent European Commission and UNEP policy.

Trajectory optimization for the National Aerospace Plane

NASA Technical Reports Server (NTRS)

Lu, Ping

1993-01-01

The objective of this second phase research is to investigate the optimal ascent trajectory for the National Aerospace Plane (NASP) from runway take-off to orbital insertion and address the unique problems associated with the hypersonic flight trajectory optimization. The trajectory optimization problem for an aerospace plane is a highly challenging problem because of the complexity involved. Previous work has been successful in obtaining sub-optimal trajectories by using energy-state approximation and time-scale decomposition techniques. But it is known that the energy-state approximation is not valid in certain portions of the trajectory. This research aims at employing full dynamics of the aerospace plane and emphasizing direct trajectory optimization methods. The major accomplishments of this research include the first-time development of an inverse dynamics approach in trajectory optimization which enables us to generate optimal trajectories for the aerospace plane efficiently and reliably, and general analytical solutions to constrained hypersonic trajectories that has wide application in trajectory optimization as well as in guidance and flight dynamics. Optimal trajectories in abort landing and ascent augmented with rocket propulsion and thrust vectoring control were also investigated. Motivated by this study, a new global trajectory optimization tool using continuous simulated annealing and a nonlinear predictive feedback guidance law have been under investigation and some promising results have been obtained, which may well lead to more significant development and application in the near future.

High density plasmas and new diagnostics: An overview (invited).

PubMed

Celona, L; Gammino, S; Mascali, D

2016-02-01

One of the limiting factors for the full understanding of Electron Cyclotron Resonance Ion Sources (ECRISs) fundamental mechanisms consists of few types of diagnostic tools so far available for such compact machines. Microwave-to-plasma coupling optimisation, new methods of density overboost provided by plasma wave generation, and magnetostatic field tailoring for generating a proper electron energy distribution function, suitable for optimal ion beams formation, require diagnostic tools spanning across the entire electromagnetic spectrum from microwave interferometry to X-ray spectroscopy; these methods are going to be implemented including high resolution and spatially resolved X-ray spectroscopy made by quasi-optical methods (pin-hole cameras). The ion confinement optimisation also requires a complete control of cold electrons displacement, which can be performed by optical emission spectroscopy. Several diagnostic tools have been recently developed at INFN-LNS, including "volume-integrated" X-ray spectroscopy in low energy domain (2-30 keV, by using silicon drift detectors) or high energy regime (>30 keV, by using high purity germanium detectors). For the direct detection of the spatially resolved spectral distribution of X-rays produced by the electronic motion, a "pin-hole camera" has been developed also taking profit from previous experiences in the ECRIS field. The paper will give an overview of INFN-LNS strategy in terms of new microwave-to-plasma coupling schemes and advanced diagnostics supporting the design of new ion sources and for optimizing the performances of the existing ones, with the goal of a microwave-absorption oriented design of future machines.

Selection of optimal oligonucleotide probes for microarrays usingmultiple criteria, global alignment and parameter estimation.

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

Li, Xingyuan; He, Zhili; Zhou, Jizhong

2005-10-30

The oligonucleotide specificity for microarray hybridizationcan be predicted by its sequence identity to non-targets, continuousstretch to non-targets, and/or binding free energy to non-targets. Mostcurrently available programs only use one or two of these criteria, whichmay choose 'false' specific oligonucleotides or miss 'true' optimalprobes in a considerable proportion. We have developed a software tool,called CommOligo using new algorithms and all three criteria forselection of optimal oligonucleotide probes. A series of filters,including sequence identity, free energy, continuous stretch, GC content,self-annealing, distance to the 3'-untranslated region (3'-UTR) andmelting temperature (Tm), are used to check each possibleoligonucleotide. A sequence identity is calculated based onmore » gapped globalalignments. A traversal algorithm is used to generate alignments for freeenergy calculation. The optimal Tm interval is determined based on probecandidates that have passed all other filters. Final probes are pickedusing a combination of user-configurable piece-wise linear functions andan iterative process. The thresholds for identity, stretch and freeenergy filters are automatically determined from experimental data by anaccessory software tool, CommOligo_PE (CommOligo Parameter Estimator).The program was used to design probes for both whole-genome and highlyhomologous sequence data. CommOligo and CommOligo_PE are freely availableto academic users upon request.« less

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

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

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

Analysis and Optimization of Pulse Dynamics for Magnetic Stimulation

PubMed Central

Goetz, Stefan M.; Truong, Cong Nam; Gerhofer, Manuel G.; Peterchev, Angel V.; Herzog, Hans-Georg; Weyh, Thomas

2013-01-01

Magnetic stimulation is a standard tool in brain research and has found important clinical applications in neurology, psychiatry, and rehabilitation. Whereas coil designs and the spatial field properties have been intensively studied in the literature, the temporal dynamics of the field has received less attention. Typically, the magnetic field waveform is determined by available device circuit topologies rather than by consideration of what is optimal for neural stimulation. This paper analyzes and optimizes the waveform dynamics using a nonlinear model of a mammalian axon. The optimization objective was to minimize the pulse energy loss. The energy loss drives power consumption and heating, which are the dominating limitations of magnetic stimulation. The optimization approach is based on a hybrid global-local method. Different coordinate systems for describing the continuous waveforms in a limited parameter space are defined for numerical stability. The optimization results suggest that there are waveforms with substantially higher efficiency than that of traditional pulse shapes. One class of optimal pulses is analyzed further. Although the coil voltage profile of these waveforms is almost rectangular, the corresponding current shape presents distinctive characteristics, such as a slow low-amplitude first phase which precedes the main pulse and reduces the losses. Representatives of this class of waveforms corresponding to different maximum voltages are linked by a nonlinear transformation. The main phase, however, scales with time only. As with conventional magnetic stimulation pulses, briefer pulses result in lower energy loss but require higher coil voltage than longer pulses. PMID:23469168

Models for residential-and commercial-sector energy conservation analysis: Applications, limitations, and future potential

NASA Astrophysics Data System (ADS)

Cole, H. E.; Fuller, R. E.

1980-09-01

Four of the major models used by DOE for energy conservation analyses in the residential and commercial building sectors are reviewed and critically analyzed to determine how these models can serve as tools for DOE and its Conservation Policy Office in evaluating and quantifying their policy and program requirements. The most effective role for each model in addressing future issues of buildings energy conservation policy and analysis is assessed. The four models covered are: Oak Ridge Residential Energy Model; Micro Analysis of Transfers to Households/Comprehensive Human Resources Data System (MATH/CHRDS) Model; Oak Ridge Commercial Energy Model; and Brookhaven Buildings Energy Conservation Optimization Model (BECOM).

Re-scheduling as a tool for the power management on board a spacecraft

NASA Technical Reports Server (NTRS)

Albasheer, Omar; Momoh, James A.

1995-01-01

The scheduling of events on board a spacecraft is based on forecast energy levels. The real time values of energy may not coincide with the forecast values; consequently, a dynamic revising to the allocation of power is needed. The re-scheduling is also needed for other reasons on board a spacecraft like the addition of new event which must be scheduled, or a failure of an event due to many different contingencies. This need of rescheduling is very important to the survivability of the spacecraft. In this presentation, a re-scheduling tool will be presented as a part of an overall scheme for the power management on board a spacecraft from the allocation of energy point of view. The overall scheme is based on the optimal use of energy available on board a spacecraft using expert systems combined with linear optimization techniques. The system will be able to schedule maximum number of events utilizing most energy available. The outcome is more events scheduled to share the operation cost of that spacecraft. The system will also be able to re-schedule in case of a contingency with minimal time and minimal disturbance of the original schedule. The end product is a fully integrated planning system capable of producing the right decisions in short time with less human error. The overall system will be presented with the re-scheduling algorithm discussed in detail, then the tests and results will be presented for validations.

A water management decision support system contributing to sustainability

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

Distributed Energy Systems Integration and Demand Optimization for Autonomous Operations and Electric Grid Transactions

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

Ghatikar, Girish; Mashayekh, Salman; Stadler, Michael

Distributed power systems in the U.S. and globally are evolving to provide reliable and clean energy to consumers. In California, existing regulations require significant increases in renewable generation, as well as identification of customer-side distributed energy resources (DER) controls, communication technologies, and standards for interconnection with the electric grid systems. As DER deployment expands, customer-side DER control and optimization will be critical for system flexibility and demand response (DR) participation, which improves the economic viability of DER systems. Current DER systems integration and communication challenges include leveraging the existing DER and DR technology and systems infrastructure, and enabling optimized cost,more » energy and carbon choices for customers to deploy interoperable grid transactions and renewable energy systems at scale. Our paper presents a cost-effective solution to these challenges by exploring communication technologies and information models for DER system integration and interoperability. This system uses open standards and optimization models for resource planning based on dynamic-pricing notifications and autonomous operations within various domains of the smart grid energy system. It identifies architectures and customer engagement strategies in dynamic DR pricing transactions to generate feedback information models for load flexibility, load profiles, and participation schedules. The models are tested at a real site in California—Fort Hunter Liggett (FHL). Furthermore, our results for FHL show that the model fits within the existing and new DR business models and networked systems for transactive energy concepts. Integrated energy systems, communication networks, and modeling tools that coordinate supply-side networks and DER will enable electric grid system operators to use DER for grid transactions in an integrated system.« less

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.

SOC-DS computer code provides tool for design evaluation of homogeneous two-material nuclear shield

NASA Technical Reports Server (NTRS)

Disney, R. K.; Ricks, L. O.

1967-01-01

SOC-DS Code /Shield Optimization Code-Direc Search/, selects a nuclear shield material of optimum volume, weight, or cost to meet the requirments of a given radiation dose rate or energy transmission constraint. It is applicable to evaluating neutron and gamma ray shields for all nuclear reactors.

Optimization of exposure factors for X-ray radiography non-destructive testing of pearl oyster

NASA Astrophysics Data System (ADS)

Susilo; Yulianti, I.; Addawiyah, A.; Setiawan, R.

2018-03-01

One of the processes in pearl oyster cultivation is detecting the pearl nucleus to gain information whether the pearl nucleus is still attached in the shell or vomited. The common tool used to detect pearl nucleus is an X-ray machine. However, an X-ray machine has a drawback that is the energy used is higher than that used by digital radiography. The high energy make the resulted image is difficult to be analysed. One of the advantages of digital radiography is the energy used can be adjusted so that the resulted image can be analysed easily. To obtain a high quality of pearl image using digital radiography, the exposure factors should be optimized. In this work, optimization was done by varying the voltage, current, and exposure time. Then, the radiography images were analysed using Contrast to Noise Ratio (CNR). From the analysis, it can be determined that the optimum exposure factors are 60 kV of voltage, 16 mA of current, and 0.125 s of exposure time which result in CNR of 5.71.

SHARPEN-systematic hierarchical algorithms for rotamers and proteins on an extended network.

PubMed

Loksha, Ilya V; Maiolo, James R; Hong, Cheng W; Ng, Albert; Snow, Christopher D

2009-04-30

Algorithms for discrete optimization of proteins play a central role in recent advances in protein structure prediction and design. We wish to improve the resources available for computational biologists to rapidly prototype such algorithms and to easily scale these algorithms to many processors. To that end, we describe the implementation and use of two new open source resources, citing potential benefits over existing software. We discuss CHOMP, a new object-oriented library for macromolecular optimization, and SHARPEN, a framework for scaling CHOMP scripts to many computers. These tools allow users to develop new algorithms for a variety of applications including protein repacking, protein-protein docking, loop rebuilding, or homology model remediation. Particular care was taken to allow modular energy function design; protein conformations may currently be scored using either the OPLSaa molecular mechanical energy function or an all-atom semiempirical energy function employed by Rosetta. (c) 2009 Wiley Periodicals, Inc.

Integrated modeling approach for optimal management of water, energy and food security nexus

NASA Astrophysics Data System (ADS)

Zhang, Xiaodong; Vesselinov, Velimir V.

2017-03-01

Water, energy and food (WEF) are inextricably interrelated. Effective planning and management of limited WEF resources to meet current and future socioeconomic demands for sustainable development is challenging. WEF production/delivery may also produce environmental impacts; as a result, green-house-gas emission control will impact WEF nexus management as well. Nexus management for WEF security necessitates integrated tools for predictive analysis that are capable of identifying the tradeoffs among various sectors, generating cost-effective planning and management strategies and policies. To address these needs, we have developed an integrated model analysis framework and tool called WEFO. WEFO provides a multi-period socioeconomic model for predicting how to satisfy WEF demands based on model inputs representing productions costs, socioeconomic demands, and environmental controls. WEFO is applied to quantitatively analyze the interrelationships and trade-offs among system components including energy supply, electricity generation, water supply-demand, food production as well as mitigation of environmental impacts. WEFO is demonstrated to solve a hypothetical nexus management problem consistent with real-world management scenarios. Model parameters are analyzed using global sensitivity analysis and their effects on total system cost are quantified. The obtained results demonstrate how these types of analyses can be helpful for decision-makers and stakeholders to make cost-effective decisions for optimal WEF management.

Development of a Rolling Process Design Tool for Use in Improving Hot Roll Slab Recovery

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

Couch, R; Becker, R; Rhee, M

2004-09-24

Lawrence Livermore National Laboratory participated in a U. S. Department of Energy/Office of Industrial Technology sponsored research project 'Development of a Rolling Process Design Tool for Use in Improving Hot Roll Slab Recovery', as a Cooperative Agreement TC-02028 with the Alcoa Technical Center (ATC). The objective of the joint project with Alcoa is to develop a numerical modeling capability to optimize the hot rolling process used to produce aluminum plate. Product lost in the rolling process and subsequent recycling, wastes resources consumed in the energy-intensive steps of remelting and reprocessing the ingot. The modeling capability developed by project partners willmore » be used to produce plate more efficiently and with reduced product loss.« less

Optimizing Distributed Energy Resources and building retrofits with the strategic DER-CAModel

DOE PAGES

Stadler, M.; Groissböck, M.; Cardoso, G.; ...

2014-08-05

The pressuring need to reduce the import of fossil fuels as well as the need to dramatically reduce CO 2 emissions in Europe motivated the European Commission (EC) to implement several regulations directed to building owners. Most of these regulations focus on increasing the number of energy efficient buildings, both new and retrofitted, since retrofits play an important role in energy efficiency. Overall, this initiative results from the realization that buildings will have a significant impact in fulfilling the 20/20/20-goals of reducing the greenhouse gas emissions by 20%, increasing energy efficiency by 20%, and increasing the share of renewables tomore » 20%, all by 2020. The Distributed Energy Resources Customer Adoption Model (DER-CAM) is an optimization tool used to support DER investment decisions, typically by minimizing total annual costs or CO 2 emissions while providing energy services to a given building or microgrid site. This document shows enhancements made to DER-CAM to consider building retrofit measures along with DER investment options. Specifically, building shell improvement options have been added to DER-CAM as alternative or complementary options to investments in other DER such as PV, solar thermal, combined heat and power, or energy storage. The extension of the mathematical formulation required by the new features introduced in DER-CAM is presented and the resulting model is demonstrated at an Austrian Campus building by comparing DER-CAM results with and without building shell improvement options. Strategic investment results are presented and compared to the observed investment decision at the test site. Results obtained considering building shell improvement options suggest an optimal weighted average U value of about 0.53 W/(m 2K) for the test site. This result is approximately 25% higher than what is currently observed in the building, suggesting that the retrofits made in 2002 were not optimal. Furthermore, the results obtained with DER-CAM illustrate the complexity of interactions between DER and passive measure options, showcasing the need for a holistic optimization approach to effectively optimize energy costs and CO 2 emissions. Lastly, the simultaneous optimization of building shell improvements and DER investments enables building owners to take one step further towards nearly zero energy buildings (nZEB) or nearly zero carbon emission buildings (nZCEB), and therefore support the 20/20/20 goals.« less

Optimizing Distributed Energy Resources and building retrofits with the strategic DER-CAModel

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

Stadler, M.; Groissböck, M.; Cardoso, G.

The pressuring need to reduce the import of fossil fuels as well as the need to dramatically reduce CO 2 emissions in Europe motivated the European Commission (EC) to implement several regulations directed to building owners. Most of these regulations focus on increasing the number of energy efficient buildings, both new and retrofitted, since retrofits play an important role in energy efficiency. Overall, this initiative results from the realization that buildings will have a significant impact in fulfilling the 20/20/20-goals of reducing the greenhouse gas emissions by 20%, increasing energy efficiency by 20%, and increasing the share of renewables tomore » 20%, all by 2020. The Distributed Energy Resources Customer Adoption Model (DER-CAM) is an optimization tool used to support DER investment decisions, typically by minimizing total annual costs or CO 2 emissions while providing energy services to a given building or microgrid site. This document shows enhancements made to DER-CAM to consider building retrofit measures along with DER investment options. Specifically, building shell improvement options have been added to DER-CAM as alternative or complementary options to investments in other DER such as PV, solar thermal, combined heat and power, or energy storage. The extension of the mathematical formulation required by the new features introduced in DER-CAM is presented and the resulting model is demonstrated at an Austrian Campus building by comparing DER-CAM results with and without building shell improvement options. Strategic investment results are presented and compared to the observed investment decision at the test site. Results obtained considering building shell improvement options suggest an optimal weighted average U value of about 0.53 W/(m 2K) for the test site. This result is approximately 25% higher than what is currently observed in the building, suggesting that the retrofits made in 2002 were not optimal. Furthermore, the results obtained with DER-CAM illustrate the complexity of interactions between DER and passive measure options, showcasing the need for a holistic optimization approach to effectively optimize energy costs and CO 2 emissions. Lastly, the simultaneous optimization of building shell improvements and DER investments enables building owners to take one step further towards nearly zero energy buildings (nZEB) or nearly zero carbon emission buildings (nZCEB), and therefore support the 20/20/20 goals.« less

Waveform Analysis Optimization for the 45Ca Beta Decay Experiment

NASA Astrophysics Data System (ADS)

Whitehead, Ryan; ⁴⁵Ca Collaboration

2017-09-01

The 45Ca experiment is searching for a non-zero Fierz interference term, which would imply a tensor type contribution to the low-energy weak interaction, possibly signaling Beyond-the-Standard-Model (BSM) physics. Beta spectrum measurements are being performed at LANL, using the segmented, large area, Si detectors developed for the Nab and UCNB experiments. 109 events have been recorded, with 38 of the 254 pixels instrumented, during the summers of 2016 and 2017. An important step to extracting the energy spectra is the correction of the waveform for pile-up events. A set of analysis tools has been developed to address this issue. A trapezoidal filter has been characterized and optimized for the experimental waveforms. This filter is primarily used for energy extraction, but, by adjusting certain parameters, it has been modified to identify pile-up events. The efficiency varies with the total energy of the particle and the amount deposited with each detector interaction. Preliminary results of this analysis will be presented.

Numerical optimization of three-dimensional coils for NSTX-U

NASA Astrophysics Data System (ADS)

Lazerson, S. A.; Park, J.-K.; Logan, N.; Boozer, A.

2015-10-01

A tool for the calculation of optimal three-dimensional (3D) perturbative magnetic fields in tokamaks has been developed. The IPECOPT code builds upon the stellarator optimization code STELLOPT to allow for optimization of linear ideal magnetohydrodynamic perturbed equilibrium (IPEC). This tool has been applied to NSTX-U equilibria, addressing which fields are the most effective at driving NTV torques. The NTV torque calculation is performed by the PENT code. Optimization of the normal field spectrum shows that fields with n  =  1 character can drive a large core torque. It is also shown that fields with n  =  3 features are capable of driving edge torque and some core torque. Coil current optimization (using the planned in-vessel and existing RWM coils) on NSTX-U suggest the planned coils set is adequate for core and edge torque control. Comparison between error field correction experiments on DIII-D and the optimizer show good agreement. Notice: This manuscript has been authored by Princeton University under Contract Number DE-AC02-09CH11466 with the U.S. Department of Energy. The publisher, by accepting the article for publication acknowledges, that the United States Government retains a non-exclusive,paid-up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes.

Optimization and parallelization of the thermal–hydraulic subchannel code CTF for high-fidelity multi-physics applications

DOE PAGES

Salko, Robert K.; Schmidt, Rodney C.; Avramova, Maria N.

2014-11-23

This study describes major improvements to the computational infrastructure of the CTF subchannel code so that full-core, pincell-resolved (i.e., one computational subchannel per real bundle flow channel) simulations can now be performed in much shorter run-times, either in stand-alone mode or as part of coupled-code multi-physics calculations. These improvements support the goals of the Department Of Energy Consortium for Advanced Simulation of Light Water Reactors (CASL) Energy Innovation Hub to develop high fidelity multi-physics simulation tools for nuclear energy design and analysis.

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.

A dielectric logging tool with insulated collar for formation fluid detection around borehole

NASA Astrophysics Data System (ADS)

Wang, Bin; Li, Kang; Kong, Fan-Min; Zhao, Jia

2015-08-01

A dielectric tool with insulated collar for analyzing fluid saturation outside a borehole was introduced. The UWB (ultra-wideband) antenna mounted on the tool was optimized to launch a transient pulse. The broadband evaluation method provided more advantages when compared with traditional dielectric tools. The EM (electromagnetic) power distribution outside the borehole was studied, and it was shown that energy was propagated in two modes. Furthermore, the mechanism of the modes was discussed. In order to increase this tools' investigation depth, a novel insulated collar was introduced. In addition, operation in difference formations was discussed and this tool proved to be able to efficiently launch lateral EM waves. Response voltages indicated that the proposed scheme was able to evaluate the fluid saturation of reservoir formations and dielectric dispersion properties. It may be used as an alternative tool for imaging logging applications.

A deterministic method for estimating free energy genetic network landscapes with applications to cell commitment and reprogramming paths.

PubMed

Olariu, Victor; Manesso, Erica; Peterson, Carsten

2017-06-01

Depicting developmental processes as movements in free energy genetic landscapes is an illustrative tool. However, exploring such landscapes to obtain quantitative or even qualitative predictions is hampered by the lack of free energy functions corresponding to the biochemical Michaelis-Menten or Hill rate equations for the dynamics. Being armed with energy landscapes defined by a network and its interactions would open up the possibility of swiftly identifying cell states and computing optimal paths, including those of cell reprogramming, thereby avoiding exhaustive trial-and-error simulations with rate equations for different parameter sets. It turns out that sigmoidal rate equations do have approximate free energy associations. With this replacement of rate equations, we develop a deterministic method for estimating the free energy surfaces of systems of interacting genes at different noise levels or temperatures. Once such free energy landscape estimates have been established, we adapt a shortest path algorithm to determine optimal routes in the landscapes. We explore the method on three circuits for haematopoiesis and embryonic stem cell development for commitment and reprogramming scenarios and illustrate how the method can be used to determine sequential steps for onsets of external factors, essential for efficient reprogramming.

Energy efficiency drives the global seasonal distribution of birds.

PubMed

Somveille, Marius; Rodrigues, Ana S L; Manica, Andrea

2018-06-01

The uneven distribution of biodiversity on Earth is one of the most general and puzzling patterns in ecology. Many hypotheses have been proposed to explain it, based on evolutionary processes or on constraints related to geography and energy. However, previous studies investigating these hypotheses have been largely descriptive due to the logistical difficulties of conducting controlled experiments on such large geographical scales. Here, we use bird migration-the seasonal redistribution of approximately 15% of bird species across the world-as a natural experiment for testing the species-energy relationship, the hypothesis that animal diversity is driven by energetic constraints. We develop a mechanistic model of bird distributions across the world, and across seasons, based on simple ecological and energetic principles. Using this model, we show that bird species distributions optimize the balance between energy acquisition and energy expenditure while taking into account competition with other species. These findings support, and provide a mechanistic explanation for, the species-energy relationship. The findings also provide a general explanation of migration as a mechanism that allows birds to optimize their energy budget in the face of seasonality and competition. Finally, our mechanistic model provides a tool for predicting how ecosystems will respond to global anthropogenic change.

A deterministic method for estimating free energy genetic network landscapes with applications to cell commitment and reprogramming paths

PubMed Central

Olariu, Victor; Manesso, Erica

2017-01-01

Depicting developmental processes as movements in free energy genetic landscapes is an illustrative tool. However, exploring such landscapes to obtain quantitative or even qualitative predictions is hampered by the lack of free energy functions corresponding to the biochemical Michaelis–Menten or Hill rate equations for the dynamics. Being armed with energy landscapes defined by a network and its interactions would open up the possibility of swiftly identifying cell states and computing optimal paths, including those of cell reprogramming, thereby avoiding exhaustive trial-and-error simulations with rate equations for different parameter sets. It turns out that sigmoidal rate equations do have approximate free energy associations. With this replacement of rate equations, we develop a deterministic method for estimating the free energy surfaces of systems of interacting genes at different noise levels or temperatures. Once such free energy landscape estimates have been established, we adapt a shortest path algorithm to determine optimal routes in the landscapes. We explore the method on three circuits for haematopoiesis and embryonic stem cell development for commitment and reprogramming scenarios and illustrate how the method can be used to determine sequential steps for onsets of external factors, essential for efficient reprogramming. PMID:28680655

Production of biodiesel from coastal macroalgae (Chara vulgaris) and optimization of process parameters using Box-Behnken design.

PubMed

Siddiqua, Shaila; Mamun, Abdullah Al; Enayetul Babar, Sheikh Md

2015-01-01

Renewable biodiesels are needed as an alternative to petroleum-derived transport fuels, which contribute to global warming and are of limited availability. Algae biomass, are a potential source of renewable energy, and they can be converted into energy such as biofuels. This study introduces an integrated method for the production of biodiesel from Chara vulgaris algae collected from the coastal region of Bangladesh. The Box-Behnken design based on response surface methods (RSM) used as the statistical tool to optimize three variables for predicting the best performing conditions (calorific value and yield) of algae biodiesel. The three parameters for production condition were chloroform (X1), sodium chloride concentration (X2) and temperature (X3). Optimal conditions were estimated by the aid of statistical regression analysis and surface plot chart. The optimal condition of biodiesel production parameter for 12 g of dry algae biomass was observed to be 198 ml chloroform with 0.75 % sodium chloride at 65 °C temperature, where the calorific value of biodiesel is 9255.106 kcal/kg and yield 3.6 ml.

LLIMAS: Revolutionizing integrating modeling and analysis at MIT Lincoln Laboratory

NASA Astrophysics Data System (ADS)

Doyle, Keith B.; Stoeckel, Gerhard P.; Rey, Justin J.; Bury, Mark E.

2017-08-01

MIT Lincoln Laboratory's Integrated Modeling and Analysis Software (LLIMAS) enables the development of novel engineering solutions for advanced prototype systems through unique insights into engineering performance and interdisciplinary behavior to meet challenging size, weight, power, environmental, and performance requirements. LLIMAS is a multidisciplinary design optimization tool that wraps numerical optimization algorithms around an integrated framework of structural, thermal, optical, stray light, and computational fluid dynamics analysis capabilities. LLIMAS software is highly extensible and has developed organically across a variety of technologies including laser communications, directed energy, photometric detectors, chemical sensing, laser radar, and imaging systems. The custom software architecture leverages the capabilities of existing industry standard commercial software and supports the incorporation of internally developed tools. Recent advances in LLIMAS's Structural-Thermal-Optical Performance (STOP), aeromechanical, and aero-optical capabilities as applied to Lincoln prototypes are presented.

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.

Multidisciplinary Optimization for Aerospace Using Genetic Optimization

NASA Technical Reports Server (NTRS)

Pak, Chan-gi; Hahn, Edward E.; Herrera, Claudia Y.

2007-01-01

In support of the ARMD guidelines NASA's Dryden Flight Research Center is developing a multidisciplinary design and optimization tool This tool will leverage existing tools and practices, and allow the easy integration and adoption of new state-of-the-art software. Optimization has made its way into many mainstream applications. For example NASTRAN(TradeMark) has its solution sequence 200 for Design Optimization, and MATLAB(TradeMark) has an Optimization Tool box. Other packages, such as ZAERO(TradeMark) aeroelastic panel code and the CFL3D(TradeMark) Navier-Stokes solver have no built in optimizer. The goal of the tool development is to generate a central executive capable of using disparate software packages ina cross platform network environment so as to quickly perform optimization and design tasks in a cohesive streamlined manner. A provided figure (Figure 1) shows a typical set of tools and their relation to the central executive. Optimization can take place within each individual too, or in a loop between the executive and the tool, or both.

Radio-frequency energy quantification in magnetic resonance imaging

NASA Astrophysics Data System (ADS)

Alon, Leeor

Mapping of radio frequency (RF) energy deposition has been challenging for 50+ years, especially, when scanning patients in the magnetic resonance imaging (MRI) environment. As result, electromagnetic simulation software is often used for estimating the specific absorption rate (SAR), the rate of RF energy deposition in tissue. The thesis work presents challenges associated with aligning information provided by electromagnetic simulation and MRI experiments. As result of the limitations of simulations, experimental methods for the quantification of SAR were established. A system for quantification of the total RF energy deposition was developed for parallel transmit MRI (a system that uses multiple antennas to excite and image the body). The system is capable of monitoring and predicting channel-by-channel RF energy deposition, whole body SAR and capable of tracking potential hardware failures that occur in the transmit chain and may cause the deposition of excessive energy into patients. Similarly, we demonstrated that local RF power deposition can be mapped and predicted for parallel transmit systems based on a series of MRI temperature mapping acquisitions. Resulting from the work, we developed tools for optimal reconstruction temperature maps from MRI acquisitions. The tools developed for temperature mapping paved the way for utilizing MRI as a diagnostic tool for evaluation of RF/microwave emitting device safety. Quantification of the RF energy was demonstrated for both MRI compatible and non-MRI-compatible devices (such as cell phones), while having the advantage of being noninvasive, of providing millimeter resolution and high accuracy.

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.

Modeling Urban Energy Savings Scenarios Using Earth System Microclimate and Urban Morphology

NASA Astrophysics Data System (ADS)

Allen, M. R.; Rose, A.; New, J. R.; Yuan, J.; Omitaomu, O.; Sylvester, L.; Branstetter, M. L.; Carvalhaes, T. M.; Seals, M.; Berres, A.

2017-12-01

We analyze and quantify the relationships among climatic conditions, urban morphology, population, land cover, and energy use so that these relationships can be used to inform energy-efficient urban development and planning. We integrate different approaches across three research areas: earth system modeling; impacts, adaptation and vulnerability; and urban planning in order to address three major gaps in the existing capability in these areas: i) neighborhood resolution modeling and simulation of urban micrometeorological processes and their effect on and from regional climate; ii) projections for future energy use under urbanization and climate change scenarios identifying best strategies for urban morphological development and energy savings; iii) analysis and visualization tools to help planners optimally use these projections.

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

Gifford, Jason S.; Grace, Robert C.; Rickerson, Wilson H.

This report serves as a resource for policymakers who wish to learn more about levelized cost of energy (LCOE) calculations, including cost-based incentives. The report identifies key renewable energy cost modeling options, highlights the policy implications of choosing one approach over the other, and presents recommendations on the optimal characteristics of a model to calculate rates for cost-based incentives, FITs, or similar policies. These recommendations shaped the design of NREL's Cost of Renewable Energy Spreadsheet Tool (CREST), which is used by state policymakers, regulators, utilities, developers, and other stakeholders to assist with analyses of policy and renewable energy incentive paymentmore » structures. Authored by Jason S. Gifford and Robert C. Grace of Sustainable Energy Advantage LLC and Wilson H. Rickerson of Meister Consultants Group, Inc.« less

The development of a volume element model for energy systems engineering and integrative thermodynamic optimization

NASA Astrophysics Data System (ADS)

Yang, Sam

The dissertation presents the mathematical formulation, experimental validation, and application of a volume element model (VEM) devised for modeling, simulation, and optimization of energy systems in their early design stages. The proposed model combines existing modeling techniques and experimental adjustment to formulate a reduced-order model, while retaining sufficient accuracy to serve as a practical system-level design analysis and optimization tool. In the VEM, the physical domain under consideration is discretized in space using lumped hexahedral elements (i.e., volume elements), and the governing equations for the variable of interest are applied to each element to quantify diverse types of flows that cross it. Subsequently, a system of algebraic and ordinary differential equations is solved with respect to time and scalar (e.g., temperature, relative humidity, etc.) fields are obtained in both spatial and temporal domains. The VEM is capable of capturing and predicting dynamic physical behaviors in the entire system domain (i.e., at system level), including mutual interactions among system constituents, as well as with their respective surroundings and cooling systems, if any. The VEM is also generalizable; that is, the model can be easily adapted to simulate and optimize diverse systems of different scales and complexity and attain numerical convergence with sufficient accuracy. Both the capability and generalizability of the VEM are demonstrated in the dissertation via thermal modeling and simulation of an Off-Grid Zero Emissions Building, an all-electric ship, and a vapor compression refrigeration (VCR) system. Furthermore, the potential of the VEM as an optimization tool is presented through the integrative thermodynamic optimization of a VCR system, whose results are used to evaluate the trade-offs between various objective functions, namely, coefficient of performance, second law efficiency, pull-down time, and refrigerated space temperature, in both transient and steady-state operations.

Developing a framework for energy technology portfolio selection

NASA Astrophysics Data System (ADS)

Davoudpour, Hamid; Ashrafi, Maryam

2012-11-01

Today, the increased consumption of energy in world, in addition to the risk of quick exhaustion of fossil resources, has forced industrial firms and organizations to utilize energy technology portfolio management tools viewed both as a process of diversification of energy sources and optimal use of available energy sources. Furthermore, the rapid development of technologies, their increasing complexity and variety, and market dynamics have made the task of technology portfolio selection difficult. Considering high level of competitiveness, organizations need to strategically allocate their limited resources to the best subset of possible candidates. This paper presents the results of developing a mathematical model for energy technology portfolio selection at a R&D center maximizing support of the organization's strategy and values. The model balances the cost and benefit of the entire portfolio.

The energy trilogy: An integrated sustainability model to bridge wastewater treatment plant energy and emissions gaps

NASA Astrophysics Data System (ADS)

Al-Talibi, A. Adhim

An estimated 4% of national energy consumption is used for drinking water and wastewater services. Despite the awareness and optimization initiatives for energy conservation, energy consumption is on the rise owing to population and urbanization expansion and to commercial and industrial business advancement. The principal concern is since energy consumption grows, the higher will be the energy production demand, leading to an increase in CO2 footprints and the contribution to global warming potential. This research is in the area of energy-water nexus, focusing on wastewater treatment plant (WWTP) energy trilogy -- the group of three related entities, which includes processes: (1) consuming energy, (2) producing energy, and (3) the resulting -- CO2 equivalents. Detailed and measurable energy information is not readily obtained for wastewater facilities, specifically during facility preliminary design phases. These limitations call for data-intensive research approach on GHG emissions quantification, plant efficiencies and source reduction techniques. To achieve these goals, this research introduced a model integrating all plant processes and their pertinent energy sources. In a comprehensive and "Energy Source-to-Effluent Discharge" pattern, this model is capable of bridging the gaps of WWTP energy, facilitating plant designers' decision-making for meeting energy assessment, sustainability and the environmental regulatory compliance. Protocols for estimating common emissions sources are available such as for fuels, whereas, site-specific emissions for other sources have to be developed and are captured in this research. The dissertation objectives were met through an extensive study of the relevant literature, models and tools, originating comprehensive lists of processes and energy sources for WWTPs, locating estimation formulas for each source, identifying site specific emissions factors, and linking the sources in a mathematical model for site specific CO2 e determination. The model was verified and showed a good agreement with billed and measured data from a base case study. In a next phase, a supplemental computational tool can be created for conducting plant energy design comparisons and plant energy and emissions parameters assessments. The main conclusions drawn from this research is that current approaches are severely limited, not covering plant's design phase and not fully considering the balance of energy consumed (EC), energy produced (EP) and the resulting CO2 e emission integration. Finally their results are not representative. This makes reported governmental and institutional national energy consumption figures incomplete and/or misleading, since they are mainly considering energy consumptions from electricity and some fuels or certain processes only. The distinction of the energy trilogy model over existing approaches is based on the following: (1) the ET energy model is unprecedented, prepared to fit WWTP energy assessment during the design and rehabilitation phases, (2) links the energy trilogy eliminating the need for using several models or tools, (3) removes the need for on-site expensive energy measurements or audits, (4) offers alternatives for energy optimization during plant's life-cycle, and (5) ensures reliable GHG emissions inventory reporting for permitting and regulatory compliance.

A simplified lumped model for the optimization of post-buckled beam architecture wideband generator

NASA Astrophysics Data System (ADS)

Liu, Weiqun; Formosa, Fabien; Badel, Adrien; Hu, Guangdi

2017-11-01

Buckled beams structures are a classical kind of bistable energy harvesters which attract more and more interests because of their capability to scavenge energy over a large frequency band in comparison with linear generator. The usual modeling approach uses the Galerkin mode discretization method with relatively high complexity, while the simplification with a single-mode solution lacks accuracy. It stems on the optimization of the energy potential features to finally define the physical and geometrical parameters. Therefore, in this paper, a simple lumped model is proposed with explicit relationship between the potential shape and parameters to allow efficient design of bistable beams based generator. The accuracy of the approximation model is studied with the effectiveness of application analyzed. Moreover, an important fact, that the bending stiffness has little influence on the potential shape with low buckling level and the sectional area determined, is found. This feature extends the applicable range of the model by utilizing the design of high moment of inertia. Numerical investigations demonstrate that the proposed model is a simple and reliable tool for design. An optimization example of using the proposed model is demonstrated with satisfactory performance.

Integrated Modeling Approach for Optimal Management of Water, Energy and Food Security Nexus

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

Zhang, Xiaodong; Vesselinov, Velimir Valentinov

We report that water, energy and food (WEF) are inextricably interrelated. Effective planning and management of limited WEF resources to meet current and future socioeconomic demands for sustainable development is challenging. WEF production/delivery may also produce environmental impacts; as a result, green-house-gas emission control will impact WEF nexus management as well. Nexus management for WEF security necessitates integrated tools for predictive analysis that are capable of identifying the tradeoffs among various sectors, generating cost-effective planning and management strategies and policies. To address these needs, we have developed an integrated model analysis framework and tool called WEFO. WEFO provides a multi-periodmore » socioeconomic model for predicting how to satisfy WEF demands based on model inputs representing productions costs, socioeconomic demands, and environmental controls. WEFO is applied to quantitatively analyze the interrelationships and trade-offs among system components including energy supply, electricity generation, water supply-demand, food production as well as mitigation of environmental impacts. WEFO is demonstrated to solve a hypothetical nexus management problem consistent with real-world management scenarios. Model parameters are analyzed using global sensitivity analysis and their effects on total system cost are quantified. Lastly, the obtained results demonstrate how these types of analyses can be helpful for decision-makers and stakeholders to make cost-effective decisions for optimal WEF management.« less

Integrated Modeling Approach for Optimal Management of Water, Energy and Food Security Nexus

DOE PAGES

Zhang, Xiaodong; Vesselinov, Velimir Valentinov

2016-12-28

We report that water, energy and food (WEF) are inextricably interrelated. Effective planning and management of limited WEF resources to meet current and future socioeconomic demands for sustainable development is challenging. WEF production/delivery may also produce environmental impacts; as a result, green-house-gas emission control will impact WEF nexus management as well. Nexus management for WEF security necessitates integrated tools for predictive analysis that are capable of identifying the tradeoffs among various sectors, generating cost-effective planning and management strategies and policies. To address these needs, we have developed an integrated model analysis framework and tool called WEFO. WEFO provides a multi-periodmore » socioeconomic model for predicting how to satisfy WEF demands based on model inputs representing productions costs, socioeconomic demands, and environmental controls. WEFO is applied to quantitatively analyze the interrelationships and trade-offs among system components including energy supply, electricity generation, water supply-demand, food production as well as mitigation of environmental impacts. WEFO is demonstrated to solve a hypothetical nexus management problem consistent with real-world management scenarios. Model parameters are analyzed using global sensitivity analysis and their effects on total system cost are quantified. Lastly, the obtained results demonstrate how these types of analyses can be helpful for decision-makers and stakeholders to make cost-effective decisions for optimal WEF management.« less

Open-WiSe: a solar powered wireless sensor network platform.

PubMed

González, Apolinar; Aquino, Raúl; Mata, Walter; Ochoa, Alberto; Saldaña, Pedro; Edwards, Arthur

2012-01-01

Because battery-powered nodes are required in wireless sensor networks and energy consumption represents an important design consideration, alternate energy sources are needed to provide more effective and optimal function. The main goal of this work is to present an energy harvesting wireless sensor network platform, the Open Wireless Sensor node (WiSe). The design and implementation of the solar powered wireless platform is described including the hardware architecture, firmware, and a POSIX Real-Time Kernel. A sleep and wake up strategy was implemented to prolong the lifetime of the wireless sensor network. This platform was developed as a tool for researchers investigating Wireless sensor network or system integrators.

Contributing Data to the Fleet DNA Project (Brochure)

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

Not Available

2014-09-01

The Fleet DNA clearinghouse of commercial fleet transportation data helps vehicle manufacturers and developers optimize vehicle designs and helps fleet managers choose advanced technologies for their fleets. This online tool - available at www.nrel.gov/fleetdna - provides data summaries and visualizations similar to real-world 'genetics' for medium- and heavy-duty commercial fleet vehicles operating within a variety of vocations. To contribute your fleet data, please contact Adam Duran of the U.S. Department of Energy's National Renewable Energy Laboratory (NREL) at adam.duran@nrel.gov or 303-275-4586.

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

NASA Astrophysics Data System (ADS)

Palchak, David

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

Strategy and gaps for modeling, simulation, and control of hybrid systems

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

Rabiti, Cristian; Garcia, Humberto E.; Hovsapian, Rob

2015-04-01

The purpose of this report is to establish a strategy for modeling and simulation of candidate hybrid energy systems. Modeling and simulation is necessary to design, evaluate, and optimize the system technical and economic performance. Accordingly, this report first establishes the simulation requirements to analysis candidate hybrid systems. Simulation fidelity levels are established based on the temporal scale, real and synthetic data availability or needs, solution accuracy, and output parameters needed to evaluate case-specific figures of merit. Accordingly, the associated computational and co-simulation resources needed are established; including physical models when needed, code assembly and integrated solutions platforms, mathematical solvers,more » and data processing. This report first attempts to describe the figures of merit, systems requirements, and constraints that are necessary and sufficient to characterize the grid and hybrid systems behavior and market interactions. Loss of Load Probability (LOLP) and effective cost of Effective Cost of Energy (ECE), as opposed to the standard Levelized Cost of Electricty (LCOE), are introduced as technical and economical indices for integrated energy system evaluations. Financial assessment methods are subsequently introduced for evaluation of non-traditional, hybrid energy systems. Algorithms for coupled and iterative evaluation of the technical and economic performance are subsequently discussed. This report further defines modeling objectives, computational tools, solution approaches, and real-time data collection and processing (in some cases using real test units) that will be required to model, co-simulate, and optimize; (a) an energy system components (e.g., power generation unit, chemical process, electricity management unit), (b) system domains (e.g., thermal, electrical or chemical energy generation, conversion, and transport), and (c) systems control modules. Co-simulation of complex, tightly coupled, dynamic energy systems requires multiple simulation tools, potentially developed in several programming languages and resolved on separate time scales. Whereas further investigation and development of hybrid concepts will provide a more complete understanding of the joint computational and physical modeling needs, this report highlights areas in which co-simulation capabilities are warranted. The current development status, quality assurance, availability and maintainability of simulation tools that are currently available for hybrid systems modeling is presented. Existing gaps in the modeling and simulation toolsets and development needs are subsequently discussed. This effort will feed into a broader Roadmap activity for designing, developing, and demonstrating hybrid energy systems.« less

A near-optimal guidance for cooperative docking maneuvers

NASA Astrophysics Data System (ADS)

Ciarcià, Marco; Grompone, Alessio; Romano, Marcello

2014-09-01

In this work we study the problem of minimum energy docking maneuvers between two Floating Spacecraft Simulators. The maneuvers are planar and conducted autonomously in a cooperative mode. The proposed guidance strategy is based on the direct method known as Inverse Dynamics in the Virtual Domain, and the nonlinear programming solver known as Sequential Gradient-Restoration Algorithm. The combination of these methods allows for the quick prototyping of near-optimal trajectories, and results in an implementable tool for real-time closed-loop maneuvering. The experimental results included in this paper were obtained by exploiting the recently upgraded Floating Spacecraft-Simulator Testbed of the Spacecraft Robotics Laboratory at the Naval Postgraduate School. A direct performances comparison, in terms of maneuver energy and propellant mass, between the proposed guidance strategy and a LQR controller, demonstrates the effectiveness of the method.

Multicriteria analysis for the selection of the most appropriate energy crops: the case of Cyprus

NASA Astrophysics Data System (ADS)

Kylili, Angeliki; Christoforou, Elias; Fokaides, Paris A.; Polycarpou, Polycarpos

2016-01-01

Energy crops are considered key actors in meeting the international and European carbon reduction targets, increasing the national energy security through renewable energy production, mitigating climate change impacts, and promoting sustainability. Multicriteria analysis is a suitable decision-making tool for the energy sector, where the final decisions have to consider for a range of aspects, and can be utilised as well for deciding on appropriate energy crops. In this paper, a popular multicriteria method, PROMETHEE, is employed for the identification of the most optimal energy crops for their exploitation in Cyprus. The criteria and the weights of each are defined, and accordingly five different scenarios are developed and examined. The obtained results indicated that the promotion of second-generation energy crops is more ideal in terms of the set objectives, as well as more sustainable than the exploitation of any first-generation energy crop.

Research on a power management system for thermoelectric generators to drive wireless sensors on a spindle unit.

PubMed

Li, Sheng; Yao, Xinhua; Fu, Jianzhong

2014-07-16

Thermoelectric energy harvesting is emerging as a promising alternative energy source to drive wireless sensors in mechanical systems. Typically, the waste heat from spindle units in machine tools creates potential for thermoelectric generation. However, the problem of low and fluctuant ambient temperature differences in spindle units limits the application of thermoelectric generation to drive a wireless sensor. This study is devoted to presenting a transformer-based power management system and its associated control strategy to make the wireless sensor work stably at different speeds of the spindle. The charging/discharging time of capacitors is optimized through this energy-harvesting strategy. A rotating spindle platform is set up to test the performance of the power management system at different speeds. The experimental results show that a longer sampling cycle time will increase the stability of the wireless sensor. The experiments also prove that utilizing the optimal time can make the power management system work more effectively compared with other systems using the same sample cycle.

Design of a nondestructive two-in-one instrument for measuring the polarization and energy spectrum at an X-ray FEL facility

NASA Astrophysics Data System (ADS)

Zhang, Qingmin; Deng, Bangjie; Chen, Yuanmiaoliang; Liu, Bochao; Chen, Shaofei; Fan, Jinquan; Feng, Lie; Deng, Haixiao; Liu, Bo; Wang, Dong

2017-10-01

The free electron laser (FEL), as a next-generation light source, is an attractive tool in scientific frontier research because of its advantages of full coherence, ultra-short pulse duration, and controllable polarization. Owing to the demand of real-time bunch diagnosis during FEL experiments, precise nondestructive measurements of the polarization and X-ray energy spectrum using one instrument are preferred. In this paper, such an instrument based on the electron time-of-flight technique is proposed. By considering the complexity and nonlinearity, a numerical model in the framework of Geant4 has been developed for optimization. Taking the Shanghai Soft X-ray FEL user facility as an example, its measurement performances' dependence on the critical parameters was studied systematically, and, finally, an optimal design was obtained, achieving resolutions of 0.5% for the polarization degree and 0.3 eV for the X-ray energy spectrum.

Research on a Power Management System for Thermoelectric Generators to Drive Wireless Sensors on a Spindle Unit

PubMed Central

Li, Sheng; Yao, Xinhua; Fu, Jianzhong

2014-01-01

Thermoelectric energy harvesting is emerging as a promising alternative energy source to drive wireless sensors in mechanical systems. Typically, the waste heat from spindle units in machine tools creates potential for thermoelectric generation. However, the problem of low and fluctuant ambient temperature differences in spindle units limits the application of thermoelectric generation to drive a wireless sensor. This study is devoted to presenting a transformer-based power management system and its associated control strategy to make the wireless sensor work stably at different speeds of the spindle. The charging/discharging time of capacitors is optimized through this energy-harvesting strategy. A rotating spindle platform is set up to test the performance of the power management system at different speeds. The experimental results show that a longer sampling cycle time will increase the stability of the wireless sensor. The experiments also prove that utilizing the optimal time can make the power management system work more effectively compared with other systems using the same sample cycle. PMID:25033189

Infrastructure Analysis Tools: A Focus on Cash Flow Analysis (Presentation)

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

Melaina, M.; Penev, M.

2012-09-01

NREL has developed and maintains a variety of infrastructure analysis models for the U.S. Department of Energy. Business case analysis has recently been added to this tool set. This presentation focuses on cash flow analysis. Cash flows depend upon infrastructure costs, optimized spatially and temporally, and assumptions about financing and revenue. NREL has incorporated detailed metrics on financing and incentives into the models. Next steps in modeling include continuing to collect feedback on regional/local infrastructure development activities and 'roadmap' dynamics, and incorporating consumer preference assumptions on infrastructure to provide direct feedback between vehicles and station rollout.

Refrigeration Playbook. Heat Reclaim; Optimizing Heat Rejection and Refrigeration Heat Reclaim for Supermarket Energy Conservation

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

Reis, Chuck; Nelson, Eric; Armer, James

The purpose of this playbook and accompanying spreadsheets is to generalize the detailed CBP analysis and to put tools in the hands of experienced refrigeration designers to evaluate multiple applications of refrigeration waste heat reclaim across the United States. Supermarkets with large portfolios of similar buildings can use these tools to assess the impact of large-scale implementation of heat reclaim systems. In addition, the playbook provides best practices for implementing heat reclaim systems to achieve the best long-term performance possible. It includes guidance on operations and maintenance as well as measurement and verification.

Generalized Differential Calculus and Applications to Optimization

NASA Astrophysics Data System (ADS)

Rector, Robert Blake Hayden

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

Recycling production designs: the value of coordination and flexibility in aluminum recycling operations

NASA Astrophysics Data System (ADS)

Brommer, Tracey H.

The growing motivation for aluminum recycling has prompted interest in recycling alternative and more challenging secondary materials. The nature of these alternative secondary materials necessitates the development of an intermediate recycling facility that can reprocess the secondary materials into a liquid product Two downstream aluminum remelters will incorporate the liquid products into their aluminum alloy production schedules. Energy and environmental benefits result from delivering the products as liquid but coordination challenges persist because of the energy cost to maintain the liquid. Further coordination challenges result from the necessity to establish a long term recycling production plan in the presence of long term downstream aluminum remelter production uncertainty and inherent variation in the daily order schedule of the downstream aluminum remelters. In this context a fundamental question arises, considering the metallurgical complexities of dross reprocessing, what is the value of operating a coordinated set of by-product reprocessing plants and remelting cast houses? A methodology is presented to calculate the optimal recycling center production parameters including 1) the number of recycled products, 2) the volume of recycled products, 3) allocation of recycled materials across recycled products, 4) allocation of recycled products across finished alloys, 4) the level of flexibility for the recycling center to operate. The methods implemented include, 1) an optimization model to describe the long term operations of the recycling center, 2) an uncertainty simulation tool, 3) a simulation optimization method, 4) a dynamic simulation tool with four embedded daily production optimization models of varying degrees of flexibility. This methodology is used to quantify the performance of several recycling center production designs of varying levels of coordination and flexibility. This analysis allowed the identification of the optimal recycling center production design based on maximizing liquid recycled product incorporation and minimizing cast sows. The long term production optimization model was used to evaluate the theoretical viability of the proposed two stage scrap and aluminum dross reprocessing operation including the impact of reducing coordination on model performance. Reducing the coordination between the recycling center and downstream remelters by reducing the number of recycled products from ten to five resulted in only 1.3% less secondary materials incorporated into downstream production. The dynamic simulation tool was used to evaluate the performance of the calculated recycling center production plan when resolved on a daily timeframe for varying levels of operational flexibility. The dynamic simulation revealed the optimal performance corresponded to the fixed recipe with flexible production daily optimization model formulation. Calculating recycled product characteristics using the proposed simulation optimization method increased profitability in cases of uncertain downstream remelter production and expensive aluminum dross and post-consumed secondary materials. (Copies available exclusively from MIT Libraries, libraries.mit.edu/docs - docs@mit.edu)

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.

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

Guided wave energy trapping to detect hidden multilayer delamination damage

NASA Astrophysics Data System (ADS)

Leckey, Cara A. C.; Seebo, Jeffrey P.

2015-03-01

Nondestructive Evaluation (NDE) and Structural Health Monitoring (SHM) simulation tools capable of modeling three-dimensional (3D) realistic energy-damage interactions are needed for aerospace composites. Current practice in NDE/SHM simulation for composites commonly involves over-simplification of the material parameters and/or a simplified two-dimensional (2D) approach. The unique damage types that occur in composite materials (delamination, microcracking, etc) develop as complex 3D geometry features. This paper discusses the application of 3D custom ultrasonic simulation tools to study wave interaction with multilayer delamination damage in carbon-fiber reinforced polymer (CFRP) composites. In particular, simulation based studies of ultrasonic guided wave energy trapping due to multilayer delamination damage were performed. The simulation results show changes in energy trapping at the composite surface as additional delaminations are added through the composite thickness. The results demonstrate a potential approach for identifying the presence of hidden multilayer delamination damage in applications where only single-sided access to a component is available. The paper also describes recent advancements in optimizing the custom ultrasonic simulation code for increases in computation speed.

Effect of collision energy optimization on the measurement of peptides by selected reaction monitoring (SRM) mass spectrometry.

PubMed

Maclean, Brendan; Tomazela, Daniela M; Abbatiello, Susan E; Zhang, Shucha; Whiteaker, Jeffrey R; Paulovich, Amanda G; Carr, Steven A; Maccoss, Michael J

2010-12-15

Proteomics experiments based on Selected Reaction Monitoring (SRM, also referred to as Multiple Reaction Monitoring or MRM) are being used to target large numbers of protein candidates in complex mixtures. At present, instrument parameters are often optimized for each peptide, a time and resource intensive process. Large SRM experiments are greatly facilitated by having the ability to predict MS instrument parameters that work well with the broad diversity of peptides they target. For this reason, we investigated the impact of using simple linear equations to predict the collision energy (CE) on peptide signal intensity and compared it with the empirical optimization of the CE for each peptide and transition individually. Using optimized linear equations, the difference between predicted and empirically derived CE values was found to be an average gain of only 7.8% of total peak area. We also found that existing commonly used linear equations fall short of their potential, and should be recalculated for each charge state and when introducing new instrument platforms. We provide a fully automated pipeline for calculating these equations and individually optimizing CE of each transition on SRM instruments from Agilent, Applied Biosystems, Thermo-Scientific and Waters in the open source Skyline software tool ( http://proteome.gs.washington.edu/software/skyline ).

Artificial Intelligence Based Selection of Optimal Cutting Tool and Process Parameters for Effective Turning and Milling Operations

NASA Astrophysics Data System (ADS)

Saranya, Kunaparaju; John Rozario Jegaraj, J.; Ramesh Kumar, Katta; Venkateshwara Rao, Ghanta

2016-06-01

With the increased trend in automation of modern manufacturing industry, the human intervention in routine, repetitive and data specific activities of manufacturing is greatly reduced. In this paper, an attempt has been made to reduce the human intervention in selection of optimal cutting tool and process parameters for metal cutting applications, using Artificial Intelligence techniques. Generally, the selection of appropriate cutting tool and parameters in metal cutting is carried out by experienced technician/cutting tool expert based on his knowledge base or extensive search from huge cutting tool database. The present proposed approach replaces the existing practice of physical search for tools from the databooks/tool catalogues with intelligent knowledge-based selection system. This system employs artificial intelligence based techniques such as artificial neural networks, fuzzy logic and genetic algorithm for decision making and optimization. This intelligence based optimal tool selection strategy is developed using Mathworks Matlab Version 7.11.0 and implemented. The cutting tool database was obtained from the tool catalogues of different tool manufacturers. This paper discusses in detail, the methodology and strategies employed for selection of appropriate cutting tool and optimization of process parameters based on multi-objective optimization criteria considering material removal rate, tool life and tool cost.

Influence of Process Parameters on the Process Efficiency in Laser Metal Deposition Welding

NASA Astrophysics Data System (ADS)

Güpner, Michael; Patschger, Andreas; Bliedtner, Jens

Conventionally manufactured tools are often completely constructed of a high-alloyed, expensive tool steel. An alternative way to manufacture tools is the combination of a cost-efficient, mild steel and a functional coating in the interaction zone of the tool. Thermal processing methods, like laser metal deposition, are always characterized by thermal distortion. The resistance against the thermal distortion decreases with the reduction of the material thickness. As a consequence, there is a necessity of a special process management for the laser based coating of thin parts or tools. The experimental approach in the present paper is to keep the energy and the mass per unit length constant by varying the laser power, the feed rate and the powder mass flow. The typical seam parameters are measured in order to characterize the cladding process, define process limits and evaluate the process efficiency. Ways to optimize dilution, angular distortion and clad height are presented.

Optimization of Thick, Large Area YBCO Film Growth Through Response Surface Methods

NASA Astrophysics Data System (ADS)

Porzio, J.; Mahoney, C. H.; Sullivan, M. C.

2014-03-01

We present our work on the optimization of thick, large area YB2C3O7-δ (YBCO) film growth through response surface methods. Thick, large area films have commercial uses and have recently been used in dramatic demonstrations of levitation and suspension. Our films are grown via pulsed laser deposition and we have optimized growth parameters via response surface methods. Response surface methods is a statistical tool to optimize selected quantities with respect to a set of variables. We optimized our YBCO films' critical temperatures, thicknesses, and structures with respect to three PLD growth parameters: deposition temperature, laser energy, and deposition pressure. We will present an overview of YBCO growth via pulsed laser deposition, the statistical theory behind response surface methods, and the application of response surface methods to pulsed laser deposition growth of YBCO. Results from the experiment will be presented in a discussion of the optimized film quality. Supported by NFS grant DMR-1305637

Multidisciplinary Shape Optimization of a Composite Blended Wing Body Aircraft

NASA Astrophysics Data System (ADS)

Boozer, Charles Maxwell

A multidisciplinary shape optimization tool coupling aerodynamics, structure, and performance was developed for battery powered aircraft. Utilizing high-fidelity computational fluid dynamics analysis tools and a structural wing weight tool, coupled based on the multidisciplinary feasible optimization architecture; aircraft geometry is modified in the optimization of the aircraft's range or endurance. The developed tool is applied to three geometries: a hybrid blended wing body, delta wing UAS, the ONERA M6 wing, and a modified ONERA M6 wing. First, the optimization problem is presented with the objective function, constraints, and design vector. Next, the tool's architecture and the analysis tools that are utilized are described. Finally, various optimizations are described and their results analyzed for all test subjects. Results show that less computationally expensive inviscid optimizations yield positive performance improvements using planform, airfoil, and three-dimensional degrees of freedom. From the results obtained through a series of optimizations, it is concluded that the newly developed tool is both effective at improving performance and serves as a platform ready to receive additional performance modules, further improving its computational design support potential.

What can wave energy learn from offshore oil and gas?

PubMed

Jefferys, E R

2012-01-28

This title may appear rather presumptuous in the light of the progress made by the leading wave energy devices. However, there may still be some useful lessons to be learnt from current 'offshore' practice, and there are certainly some awful warnings from the past. Wave energy devices and the marine structures used in oil and gas exploration as well as production share a common environment and both are subject to wave, wind and current loads, which may be evaluated with well-validated, albeit imperfect, tools. Both types of structure can be designed, analysed and fabricated using similar tools and technologies. They fulfil very different missions and are subject to different economic and performance requirements; hence 'offshore' design tools must be used appropriately in wave energy project and system design, and 'offshore' cost data should be adapted for 'wave' applications. This article reviews the similarities and differences between the fields and highlights the differing economic environments; offshore structures are typically a small to moderate component of field development cost, while wave power devices will dominate overall system cost. The typical 'offshore' design process is summarized and issues such as reliability-based design and design of not normally manned structures are addressed. Lessons learned from poor design in the past are discussed to highlight areas where care is needed, and wave energy-specific design areas are reviewed. Opportunities for innovation and optimization in wave energy project and device design are discussed; wave energy projects must ultimately compete on a level playing field with other routes to low CO₂ energy and/or energy efficiency. This article is a personal viewpoint and not an expression of a ConocoPhillips position.

Advances in Optimizing Weather Driven Electric Power Systems.

NASA Astrophysics Data System (ADS)

Clack, C.; MacDonald, A. E.; Alexander, A.; Dunbar, A. D.; Xie, Y.; Wilczak, J. M.

2014-12-01

The importance of weather-driven renewable energies for the United States (and global) energy portfolio is growing. The main perceived problems with weather-driven renewable energies are their intermittent nature, low power density, and high costs. The National Energy with Weather System Simulator (NEWS) is a mathematical optimization tool that allows the construction of weather-driven energy sources that will work in harmony with the needs of the system. For example, it will match the electric load, reduce variability, decrease costs, and abate carbon emissions. One important test run included existing US carbon-free power sources, natural gas power when needed, and a High Voltage Direct Current power transmission network. This study shows that the costs and carbon emissions from an optimally designed national system decrease with geographic size. It shows that with achievable estimates of wind and solar generation costs, that the US could decrease its carbon emissions by up to 80% by the early 2030s, without an increase in electric costs. The key requirement would be a 48 state network of HVDC transmission, creating a national market for electricity not possible in the current AC grid. These results were found without the need for storage. Further, we tested the effect of changing natural gas fuel prices on the optimal configuration of the national electric power system. Another test that was carried out was an extension to global regions. The extension study shows that the same properties found in the US study extend to the most populous regions of the planet. The extra test is a simplified version of the US study, and is where much more research can be carried out. We compare our results to other model results.

Optimal policy for mitigating emissions in the European transport sector

NASA Astrophysics Data System (ADS)

Leduc, Sylvain; Piera, Patrizio; Sennai, Mesfun; Igor, Staritsky; Berien, Elbersen; Tijs, Lammens; Florian, Kraxner

2017-04-01

A geographic explicit techno-economic model, BeWhere (www.iiasa.ac.at/bewhere), has been developed at the European scale (Europe 28, the Balkans countries, Turkey, Moldavia and Ukraine) at a 40km grid size, to assess the potential of bioenergy from non-food feedstock. Based on the minimization of the supply chain from feedstock collection to the final energy product distribution, the model identifies the optimal bioenergy production plants in terms of spatial location, technology and capacity. The feedstock of interests are woody biomass (divided into eight types from conifers and non-conifers) and five different crop residuals. For each type of feedstock, one or multiple technologies can be applied for either heat, electricity or biofuel production. The model is run for different policy tools such as carbon cost, biofuel support, or subsidies, and the optimal mix of technologies and biomass needed is optimized to reach a production cost competitive against the actual reference system which is fossil fuel based. From this approach, the optimal mix of policy tools that can be applied country wide in Europe will be identified. The preliminary results show that high carbon tax and biofuel support contribute to the development of large scale biofuel production based on woody biomass plants mainly located in the northern part of Europe. Finally the highest emission reduction is reached with low biofuel support and high carbon tax evenly distributed in Europe.

Optimizing energy growth as a tool for finding exact coherent structures

NASA Astrophysics Data System (ADS)

Olvera, D.; Kerswell, R. R.

2017-08-01

We discuss how searching for finite-amplitude disturbances of a given energy that maximize their subsequent energy growth after a certain later time T can be used to probe the phase space around a reference state and ultimately to find other nearby solutions. The procedure relies on the fact that of all the initial disturbances on a constant-energy hypersphere, the optimization procedure will naturally select the one that lies closest to the stable manifold of a nearby solution in phase space if T is large enough. Then, when in its subsequent evolution the optimal disturbance transiently approaches the new solution, a flow state at this point can be used as an initial guess to converge the solution to machine precision. We illustrate this approach in plane Couette flow by rediscovering the spanwise-localized "snake" solutions of Schneider et al. [Phys. Rev. Lett. 104, 104501 (2010), 10.1103/PhysRevLett.104.104501], probing phase space at very low Reynolds numbers (less than 127.7 ) where the constant-shear solution is believed to be the global attractor and examining how the edge between laminar and turbulent flow evolves when stable stratification eliminates the turbulence. We also show that the steady snake solution smoothly delocalizes as unstable stratification is gradually turned on until it connects (via an intermediary global three-dimensional solution) to two-dimensional Rayleigh-Bénard roll solutions.

Tidal Turbine Array Optimization Based on the Discrete Particle Swarm Algorithm

NASA Astrophysics Data System (ADS)

Wu, Guo-wei; Wu, He; Wang, Xiao-yong; Zhou, Qing-wei; Liu, Xiao-man

2018-06-01

In consideration of the resource wasted by unreasonable layout scheme of tidal current turbines, which would influence the ratio of cost and power output, particle swarm optimization algorithm is introduced and improved in the paper. In order to solve the problem of optimal array of tidal turbines, the discrete particle swarm optimization (DPSO) algorithm has been performed by re-defining the updating strategies of particles' velocity and position. This paper analyzes the optimization problem of micrositing of tidal current turbines by adjusting each turbine's position, where the maximum value of total electric power is obtained at the maximum speed in the flood tide and ebb tide. Firstly, the best installed turbine number is generated by maximizing the output energy in the given tidal farm by the Farm/Flux and empirical method. Secondly, considering the wake effect, the reasonable distance between turbines, and the tidal velocities influencing factors in the tidal farm, Jensen wake model and elliptic distribution model are selected for the turbines' total generating capacity calculation at the maximum speed in the flood tide and ebb tide. Finally, the total generating capacity, regarded as objective function, is calculated in the final simulation, thus the DPSO could guide the individuals to the feasible area and optimal position. The results have been concluded that the optimization algorithm, which increased 6.19% more recourse output than experience method, can be thought as a good tool for engineering design of tidal energy demonstration.

Enabling Web-Based GIS Tools for Internet and Mobile Devices To Improve and Expand NASA Data Accessibility and Analysis Functionality for the Renewable Energy and Agricultural Applications

NASA Astrophysics Data System (ADS)

Ross, A.; Stackhouse, P. W.; Tisdale, B.; Tisdale, M.; Chandler, W.; Hoell, J. M., Jr.; Kusterer, J.

2014-12-01

The NASA Langley Research Center Science Directorate and Atmospheric Science Data Center have initiated a pilot program to utilize Geographic Information System (GIS) tools that enable, generate and store climatological averages using spatial queries and calculations in a spatial database resulting in greater accessibility of data for government agencies, industry and private sector individuals. The major objectives of this effort include the 1) Processing and reformulation of current data to be consistent with ESRI and openGIS tools, 2) Develop functions to improve capability and analysis that produce "on-the-fly" data products, extending these past the single location to regional and global scales. 3) Update the current web sites to enable both web-based and mobile application displays for optimization on mobile platforms, 4) Interact with user communities in government and industry to test formats and usage of optimization, and 5) develop a series of metrics that allow for monitoring of progressive performance. Significant project results will include the the development of Open Geospatial Consortium (OGC) compliant web services (WMS, WCS, WFS, WPS) that serve renewable energy and agricultural application products to users using GIS software and tools. Each data product and OGC service will be registered within ECHO, the Common Metadata Repository, the Geospatial Platform, and Data.gov to ensure the data are easily discoverable and provide data users with enhanced access to SSE data, parameters, services, and applications. This effort supports cross agency, cross organization, and interoperability of SSE data products and services by collaborating with DOI, NRCan, NREL, NCAR, and HOMER for requirements vetting and test bed users before making available to the wider public.

The Nitrogen Footprint Tool Network: A Multi-Institution Program To Reduce Nitrogen Pollution

PubMed Central

Leach, Allison M.; Leary, Neil; Baron, Jill; Compton, Jana E.; Galloway, James N.; Hastings, Meredith G.; Kimiecik, Jacob; Lantz-Trissel, Jonathan; de la Reguera, Elizabeth; Ryals, Rebecca

2017-01-01

Abstract Anthropogenic sources of reactive nitrogen have local and global impacts on air and water quality and detrimental effects on human and ecosystem health. This article uses the Nitrogen Footprint Tool (NFT) to determine the amount of nitrogen (N) released as a result of institutional consumption. The sectors accounted for include food (consumption and upstream production), energy, transportation, fertilizer, research animals, and agricultural research. The NFT is then used for scenario analysis to manage and track reductions, which are driven by the consumption behaviors of both the institution itself and its constituent individuals. In this article, the first seven completed institution nitrogen footprint results are presented. The Nitrogen Footprint Tool Network aims to develop footprints for many institutions to encourage widespread upper-level management strategies that will create significant reductions in reactive nitrogen released to the environment. Energy use and food purchases are the two largest sectors contributing to institution nitrogen footprints. Ongoing efforts by institutions to reduce greenhouse gas emissions also help to reduce the nitrogen footprint, but the impact of food production on nitrogen pollution has not been directly addressed by the higher education sustainability community. The Nitrogen Footprint Tool Network found that institutions could reduce their nitrogen footprints by optimizing food purchasing to reduce consumption of animal products and minimize food waste, as well as by reducing dependence on fossil fuels for energy. PMID:29350216

NREL's Water Power Software Makes a Splash; NREL Highlights, Research & Development, NREL (National Renewable Energy Laboratory)

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

None

2015-06-01

WEC-Sim is a DOE-funded software tool being jointly developed by NREL and SNL. WEC-Sim computationally models wave energy converters (WEC), devices that generate electricity using movement of water systems such as oceans, rivers, etc. There is great potential for WECs to generate electricity, but as of yet, the industry has yet to establish a commercially viable concept. Modeling, design, and simulations tools are essential to the successful development of WECs. Commercial WEC modeling software tools can't be modified by the user. In contrast, WEC-Sim is a free, open-source, and flexible enough to be modified to meet the rapidly evolving needsmore » of the WEC industry. By modeling the power generation performance and dynamic loads of WEC designs, WEC-Sim can help support the development of new WEC devices by optimizing designs for cost of energy and competitiveness. By being easily accessible, WEC-Sim promises to help level the playing field in the WEC industry. Importantly, WEC-Sim is also excellent at its job! In 2014, WEC-Sim was used in conjunction with NREL’s FAST modeling software to win a hydrodynamic modeling competition. WEC-Sim and FAST performed very well at predicting the motion of a test device in comparison to other modeling tools. The most recent version of WEC-Sim (v1.1) was released in April 2015.« less

Power Hardware-in-the-Loop (PHIL) Testing Facility for Distributed Energy Storage (Poster)

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

Neubauer.J.; Lundstrom, B.; Simpson, M.

2014-06-01

The growing deployment of distributed, variable generation and evolving end-user load profiles presents a unique set of challenges to grid operators responsible for providing reliable and high quality electrical service. Mass deployment of distributed energy storage systems (DESS) has the potential to solve many of the associated integration issues while offering reliability and energy security benefits other solutions cannot. However, tools to develop, optimize, and validate DESS control strategies and hardware are in short supply. To fill this gap, NREL has constructed a power hardware-in-the-loop (PHIL) test facility that connects DESS, grid simulator, and load bank hardware to a distributionmore » feeder simulation.« less

Open-WiSe: A Solar Powered Wireless Sensor Network Platform

PubMed Central

González, Apolinar; Aquino, Raúl; Mata, Walter; Ochoa, Alberto; Saldaña, Pedro; Edwards, Arthur

2012-01-01

Because battery-powered nodes are required in wireless sensor networks and energy consumption represents an important design consideration, alternate energy sources are needed to provide more effective and optimal function. The main goal of this work is to present an energy harvesting wireless sensor network platform, the Open Wireless Sensor node (WiSe). The design and implementation of the solar powered wireless platform is described including the hardware architecture, firmware, and a POSIX Real-Time Kernel. A sleep and wake up strategy was implemented to prolong the lifetime of the wireless sensor network. This platform was developed as a tool for researchers investigating Wireless sensor network or system integrators. PMID:22969396

Cascaded systems analysis of noise and detectability in dual-energy cone-beam CT

PubMed Central

Gang, Grace J.; Zbijewski, Wojciech; Webster Stayman, J.; Siewerdsen, Jeffrey H.

2012-01-01

Purpose: Dual-energy computed tomography and dual-energy cone-beam computed tomography (DE-CBCT) are promising modalities for applications ranging from vascular to breast, renal, hepatic, and musculoskeletal imaging. Accordingly, the optimization of imaging techniques for such applications would benefit significantly from a general theoretical description of image quality that properly incorporates factors of acquisition, reconstruction, and tissue decomposition in DE tomography. This work reports a cascaded systems analysis model that includes the Poisson statistics of x rays (quantum noise), detector model (flat-panel detectors), anatomical background, image reconstruction (filtered backprojection), DE decomposition (weighted subtraction), and simple observer models to yield a task-based framework for DE technique optimization. Methods: The theoretical framework extends previous modeling of DE projection radiography and CBCT. Signal and noise transfer characteristics are propagated through physical and mathematical stages of image formation and reconstruction. Dual-energy decomposition was modeled according to weighted subtraction of low- and high-energy images to yield the 3D DE noise-power spectrum (NPS) and noise-equivalent quanta (NEQ), which, in combination with observer models and the imaging task, yields the dual-energy detectability index (d′). Model calculations were validated with NPS and NEQ measurements from an experimental imaging bench simulating the geometry of a dedicated musculoskeletal extremities scanner. Imaging techniques, including kVp pair and dose allocation, were optimized using d′ as an objective function for three example imaging tasks: (1) kidney stone discrimination; (2) iodine vs bone in a uniform, soft-tissue background; and (3) soft tissue tumor detection on power-law anatomical background. Results: Theoretical calculations of DE NPS and NEQ demonstrated good agreement with experimental measurements over a broad range of imaging conditions. Optimization results suggest a lower fraction of total dose imparted by the low-energy acquisition, a finding consistent with previous literature. The selection of optimal kVp pair reveals the combined effect of both quantum noise and contrast in the kidney stone discrimination and soft-tissue tumor detection tasks, whereas the K-edge effect of iodine was the dominant factor in determining kVp pairs in the iodine vs bone task. The soft-tissue tumor task illustrated the benefit of dual-energy imaging in eliminating anatomical background noise and improving detectability beyond that achievable by single-energy scans. Conclusions: This work established a task-based theoretical framework that is predictive of DE image quality. The model can be utilized in optimizing a broad range of parameters in image acquisition, reconstruction, and decomposition, providing a useful tool for maximizing DE-CBCT image quality and reducing dose. PMID:22894440

Rotorcraft Optimization Tools: Incorporating Rotorcraft Design Codes into Multi-Disciplinary Design, Analysis, and Optimization

NASA Technical Reports Server (NTRS)

Meyn, Larry A.

2018-01-01

One of the goals of NASA's Revolutionary Vertical Lift Technology Project (RVLT) is to provide validated tools for multidisciplinary design, analysis and optimization (MDAO) of vertical lift vehicles. As part of this effort, the software package, RotorCraft Optimization Tools (RCOTOOLS), is being developed to facilitate incorporating key rotorcraft conceptual design codes into optimizations using the OpenMDAO multi-disciplinary optimization framework written in Python. RCOTOOLS, also written in Python, currently supports the incorporation of the NASA Design and Analysis of RotorCraft (NDARC) vehicle sizing tool and the Comprehensive Analytical Model of Rotorcraft Aerodynamics and Dynamics II (CAMRAD II) analysis tool into OpenMDAO-driven optimizations. Both of these tools use detailed, file-based inputs and outputs, so RCOTOOLS provides software wrappers to update input files with new design variable values, execute these codes and then extract specific response variable values from the file outputs. These wrappers are designed to be flexible and easy to use. RCOTOOLS also provides several utilities to aid in optimization model development, including Graphical User Interface (GUI) tools for browsing input and output files in order to identify text strings that are used to identify specific variables as optimization input and response variables. This paper provides an overview of RCOTOOLS and its use

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

Zitney, S.E.

This presentation will examine process systems engineering R&D needs for application to advanced fossil energy (FE) systems and highlight ongoing research activities at the National Energy Technology Laboratory (NETL) under the auspices of a recently launched Collaboratory for Process & Dynamic Systems Research. The three current technology focus areas include: 1) High-fidelity systems with NETL's award-winning Advanced Process Engineering Co-Simulator (APECS) technology for integrating process simulation with computational fluid dynamics (CFD) and virtual engineering concepts, 2) Dynamic systems with R&D on plant-wide IGCC dynamic simulation, control, and real-time training applications, and 3) Systems optimization including large-scale process optimization, stochastic simulationmore » for risk/uncertainty analysis, and cost estimation. Continued R&D aimed at these and other key process systems engineering models, methods, and tools will accelerate the development of advanced gasification-based FE systems and produce increasingly valuable outcomes for DOE and the Nation.« less

Vibrational energy distribution analysis (VEDA): scopes and limitations.

PubMed

Jamróz, Michał H

2013-10-01

The principle of operations of the VEDA program written by the author for Potential Energy Distribution (PED) analysis of theoretical vibrational spectra is described. Nowadays, the PED analysis is indispensible tool in serious analysis of the vibrational spectra. To perform the PED analysis it is necessary to define 3N-6 linearly independent local mode coordinates. Already for 20-atomic molecules it is a difficult task. The VEDA program reads the input data automatically from the Gaussian program output files. Then, VEDA automatically proposes an introductory set of local mode coordinates. Next, the more adequate coordinates are proposed by the program and optimized to obtain maximal elements of each column (internal coordinate) of the PED matrix (the EPM parameter). The possibility for an automatic optimization of PED contributions is a unique feature of the VEDA program absent in any other programs performing PED analysis. Copyright © 2013 Elsevier B.V. All rights reserved.

Vibrational Energy Distribution Analysis (VEDA): Scopes and limitations

NASA Astrophysics Data System (ADS)

Jamróz, Michał H.

2013-10-01

The principle of operations of the VEDA program written by the author for Potential Energy Distribution (PED) analysis of theoretical vibrational spectra is described. Nowadays, the PED analysis is indispensible tool in serious analysis of the vibrational spectra. To perform the PED analysis it is necessary to define 3N-6 linearly independent local mode coordinates. Already for 20-atomic molecules it is a difficult task. The VEDA program reads the input data automatically from the Gaussian program output files. Then, VEDA automatically proposes an introductory set of local mode coordinates. Next, the more adequate coordinates are proposed by the program and optimized to obtain maximal elements of each column (internal coordinate) of the PED matrix (the EPM parameter). The possibility for an automatic optimization of PED contributions is a unique feature of the VEDA program absent in any other programs performing PED analysis.

New efficient optimizing techniques for Kalman filters and numerical weather prediction models

NASA Astrophysics Data System (ADS)

Famelis, Ioannis; Galanis, George; Liakatas, Aristotelis

2016-06-01

The need for accurate local environmental predictions and simulations beyond the classical meteorological forecasts are increasing the last years due to the great number of applications that are directly or not affected: renewable energy resource assessment, natural hazards early warning systems, global warming and questions on the climate change can be listed among them. Within this framework the utilization of numerical weather and wave prediction systems in conjunction with advanced statistical techniques that support the elimination of the model bias and the reduction of the error variability may successfully address the above issues. In the present work, new optimization methods are studied and tested in selected areas of Greece where the use of renewable energy sources is of critical. The added value of the proposed work is due to the solid mathematical background adopted making use of Information Geometry and Statistical techniques, new versions of Kalman filters and state of the art numerical analysis tools.

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

NASA Astrophysics Data System (ADS)

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

2017-03-01

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

Implementation of Biogas Stations into Smart Heating and Cooling Network

NASA Astrophysics Data System (ADS)

Milčák, P.; Konvička, J.; Jasenská, M.

2016-10-01

The paper is aimed at the description of implementation of a biogas station into software environment for the "Smart Heating and Cooling Networks". The aim of this project is creation of a software tool for preparation of operation and optimization of treatment of heat/cool in small regions. In this case, the biogas station represents a kind of renewable energy source, which, however, has its own operational specifics which need to be taken into account at the creation of an implementation project. For a specific biogas station, a detailed computational model was elaborated, which is parameterized in particular for an optimization of the total computational time.

Modelling and Optimising the Value of a Hybrid Solar-Wind System

NASA Astrophysics Data System (ADS)

Nair, Arjun; Murali, Kartik; Anbuudayasankar, S. P.; Arjunan, C. V.

2017-05-01

In this paper, a net present value (NPV) approach for a solar hybrid system has been presented. The system, in question aims at supporting an investor by assessing an investment in solar-wind hybrid system in a given area. The approach follow a combined process of modelling the system, with optimization of major investment-related variables to maximize the financial yield of the investment. The consideration of solar wind hybrid supply presents significant potential for cost reduction. The investment variables concern the location of solar wind plant, and its sizing. The system demand driven, meaning that its primary aim is to fully satisfy the energy demand of the customers. Therefore, the model is a practical tool in the hands of investor to assess and optimize in financial terms an investment aiming at covering real energy demand. Optimization is performed by taking various technical, logical constraints. The relation between the maximum power obtained between individual system and the hybrid system as a whole in par with the net present value of the system has been highlighted.

Analysis of grinding of superalloys and ceramics for off-line process optimization

NASA Astrophysics Data System (ADS)

Sathyanarayanan, G.

The present study has compared the performances of resinoid, vitrified, and electroplated CBN wheels in creep feed grinding of M42 and D2 tool steels. Responses such as a specific energy, normal and tangential forces, and surface roughness were used as measures of performance. It was found that creep feed grinding with resinoid, vitrified, and electroplated CBN wheels has its own advantages, but no single wheel could provide good finish, lower specific energy, and high material removal rates simultaneously. To optimize the CBN grinding with different bonded wheels, a Multiple Criteria Decision Making (MCDM) methodology was used. Creep feed grinding of superalloys, Ti-6Al-4V and Inconel 718, has been modeled by utilizing neural networks to optimize the grinding process. A parallel effort was directed at creep feed grinding of alumina ceramics with diamond wheels to investigate the influence of process variables on responses based on experimental results and statistical analysis. The conflicting influence of variables was observed. This led to the formulation of ceramic grinding process as a multi-objective nonlinear mixed integer problem.

Real-time energy-saving metro train rescheduling with primary delay identification

PubMed Central

Li, Keping; Schonfeld, Paul

2018-01-01

This paper aims to reschedule online metro trains in delay scenarios. A graph representation and a mixed integer programming model are proposed to formulate the optimization problem. The solution approach is a two-stage optimization method. In the first stage, based on a proposed train state graph and system analysis, the primary and flow-on delays are specifically analyzed and identified with a critical path algorithm. For the second stage a hybrid genetic algorithm is designed to optimize the schedule, with the delay identification results as input. Then, based on the infrastructure data of Beijing Subway Line 4 of China, case studies are presented to demonstrate the effectiveness and efficiency of the solution approach. The results show that the algorithm can quickly and accurately identify primary delays among different types of delays. The economic cost of energy consumption and total delay is considerably reduced (by more than 10% in each case). The computation time of the Hybrid-GA is low enough for rescheduling online. Sensitivity analyses further demonstrate that the proposed approach can be used as a decision-making support tool for operators. PMID:29474471

IEA EBC Annex 66: Definition and simulation of occupant behavior in buildings

DOE PAGES

Yan, Da; Hong, Tianzhen; Dong, Bing; ...

2017-09-28

Here, more than 30% of the total primary energy in the world is consumed in buildings. It is crucial to reduce building energy consumption in order to preserve energy resources and mitigate global climate change. Building performance simulations have been widely used for the estimation and optimization of building performance, providing reference values for the assessment of building energy consumption and the effects of energy-saving technologies. Among the various factors influencing building energy consumption, occupant behavior has drawn increasing attention. Occupant behavior includes occupant presence, movement, and interaction with building energy devices and systems. However, there are gaps in occupantmore » behavior modeling as different energy modelers have employed varied data and tools to simulate occupant behavior, therefore producing different and incomparable results. Aiming to address these gaps, the International Energy Agency (IEA) Energy in Buildings and Community (EBC) Programme Annex 66 has established a scientific methodological framework for occupant behavior research, including data collection, behavior model representation, modeling and evaluation approaches, and the integration of behavior modeling tools with building performance simulation programs. Annex 66 also includes case studies and application guidelines to assist in building design, operation, and policymaking, using interdisciplinary approaches to reduce energy use in buildings and improve occupant comfort and productivity. This paper highlights the key research issues, methods, and outcomes pertaining to Annex 66, and offers perspectives on future research needs to integrate occupant behavior with the building life cycle.« less

IEA EBC Annex 66: Definition and simulation of occupant behavior in buildings

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

Yan, Da; Hong, Tianzhen; Dong, Bing

Here, more than 30% of the total primary energy in the world is consumed in buildings. It is crucial to reduce building energy consumption in order to preserve energy resources and mitigate global climate change. Building performance simulations have been widely used for the estimation and optimization of building performance, providing reference values for the assessment of building energy consumption and the effects of energy-saving technologies. Among the various factors influencing building energy consumption, occupant behavior has drawn increasing attention. Occupant behavior includes occupant presence, movement, and interaction with building energy devices and systems. However, there are gaps in occupantmore » behavior modeling as different energy modelers have employed varied data and tools to simulate occupant behavior, therefore producing different and incomparable results. Aiming to address these gaps, the International Energy Agency (IEA) Energy in Buildings and Community (EBC) Programme Annex 66 has established a scientific methodological framework for occupant behavior research, including data collection, behavior model representation, modeling and evaluation approaches, and the integration of behavior modeling tools with building performance simulation programs. Annex 66 also includes case studies and application guidelines to assist in building design, operation, and policymaking, using interdisciplinary approaches to reduce energy use in buildings and improve occupant comfort and productivity. This paper highlights the key research issues, methods, and outcomes pertaining to Annex 66, and offers perspectives on future research needs to integrate occupant behavior with the building life cycle.« less

Cross-sectoral optimization and visualization of transformation processes in urban water infrastructures in rural areas.

PubMed

Baron, S; Kaufmann Alves, I; Schmitt, T G; Schöffel, S; Schwank, J

2015-01-01

Predicted demographic, climatic and socio-economic changes will require adaptations of existing water supply and wastewater disposal systems. Especially in rural areas, these new challenges will affect the functionality of the present systems. This paper presents a joint interdisciplinary research project with the objective of developing an innovative software-based optimization and decision support system for the implementation of long-term transformations of existing infrastructures of water supply, wastewater and energy. The concept of the decision support and optimization tool is described and visualization methods for the presentation of results are illustrated. The model is tested in a rural case study region in the Southwest of Germany. A transformation strategy for a decentralized wastewater treatment concept and its visualization are presented for a model village.

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.

Analysis of laser surgery in non-melanoma skin cancer for optimal tissue removal

NASA Astrophysics Data System (ADS)

Fanjul-Vélez, Félix; Salas-García, Irene; Arce-Diego, José Luis

2015-02-01

Laser surgery is a commonly used technique for tissue ablation or the resection of malignant tumors. It presents advantages over conventional non-optical ablation techniques, like a scalpel or electrosurgery, such as the increased precision of the resected volume, minimization of scars and shorter recovery periods. Laser surgery is employed in medical branches such as ophthalmology or dermatology. The application of laser surgery requires the optimal adjustment of laser beam parameters, taking into account the particular patient and lesion. In this work we present a predictive tool for tissue resection in biological tissue after laser surgery, which allows an a priori knowledge of the tissue ablation volume, area and depth. The model employs a Monte Carlo 3D approach for optical propagation and a rate equation for plasma-induced ablation. The tool takes into account characteristics of the specific lesion to be ablated, mainly the geometric, optical and ablation properties. It also considers the parameters of the laser beam, such as the radius, spatial profile, pulse width, total delivered energy or wavelength. The predictive tool is applied to dermatology tumor resection, particularly to different types of non-melanoma skin cancer tumors: basocellular carcinoma, squamous cell carcinoma and infiltrative carcinoma. The ablation volume, area and depth are calculated for healthy skin and for each type of tumor as a function of the laser beam parameters. The tool could be used for laser surgery planning before the clinical application. The laser parameters could be adjusted for optimal resection volume, by personalizing the process to the particular patient and lesion.

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

for public release; distribution is unlimited 13. SUPPLEMENTARY NOTES None 14. ABSTRACT ESTCP project EW-201409 aimed at demonstrating the benefits ...of innovative software technology for building HV AC systems. These benefits included reduced system energy use and cost as wetl as improved...Control Approach March 2017 This document has been cleared for public release; Distribution Statement A

Determination of solute descriptors by chromatographic methods.

PubMed

Poole, Colin F; Atapattu, Sanka N; Poole, Salwa K; Bell, Andrea K

2009-10-12

The solvation parameter model is now well established as a useful tool for obtaining quantitative structure-property relationships for chemical, biomedical and environmental processes. The model correlates a free-energy related property of a system to six free-energy derived descriptors describing molecular properties. These molecular descriptors are defined as L (gas-liquid partition coefficient on hexadecane at 298K), V (McGowan's characteristic volume), E (excess molar refraction), S (dipolarity/polarizability), A (hydrogen-bond acidity), and B (hydrogen-bond basicity). McGowan's characteristic volume is trivially calculated from structure and the excess molar refraction can be calculated for liquids from their refractive index and easily estimated for solids. The remaining four descriptors are derived by experiment using (largely) two-phase partitioning, chromatography, and solubility measurements. In this article, the use of gas chromatography, reversed-phase liquid chromatography, micellar electrokinetic chromatography, and two-phase partitioning for determining solute descriptors is described. A large database of experimental retention factors and partition coefficients is constructed after first applying selection tools to remove unreliable experimental values and an optimized collection of varied compounds with descriptor values suitable for calibrating chromatographic systems is presented. These optimized descriptors are demonstrated to be robust and more suitable than other groups of descriptors characterizing the separation properties of chromatographic systems.

3Drefine: an interactive web server for efficient protein structure refinement

PubMed Central

Bhattacharya, Debswapna; Nowotny, Jackson; Cao, Renzhi; Cheng, Jianlin

2016-01-01

3Drefine is an interactive web server for consistent and computationally efficient protein structure refinement with the capability to perform web-based statistical and visual analysis. The 3Drefine refinement protocol utilizes iterative optimization of hydrogen bonding network combined with atomic-level energy minimization on the optimized model using a composite physics and knowledge-based force fields for efficient protein structure refinement. The method has been extensively evaluated on blind CASP experiments as well as on large-scale and diverse benchmark datasets and exhibits consistent improvement over the initial structure in both global and local structural quality measures. The 3Drefine web server allows for convenient protein structure refinement through a text or file input submission, email notification, provided example submission and is freely available without any registration requirement. The server also provides comprehensive analysis of submissions through various energy and statistical feedback and interactive visualization of multiple refined models through the JSmol applet that is equipped with numerous protein model analysis tools. The web server has been extensively tested and used by many users. As a result, the 3Drefine web server conveniently provides a useful tool easily accessible to the community. The 3Drefine web server has been made publicly available at the URL: http://sysbio.rnet.missouri.edu/3Drefine/. PMID:27131371

The perceived value of using BIM for energy simulation

NASA Astrophysics Data System (ADS)

Lewis, Anderson M.

Building Information Modeling (BIM) is becoming an increasingly important tool in the Architectural, Engineering & Construction (AEC) industries. Some of the benefits associated with BIM include but are not limited to cost and time savings through greater trade and design coordination, and more accurate estimating take-offs. BIM is a virtual 3D, parametric design software that allows users to store information of a model within and can be used as a communication platform between project stakeholders. Likewise, energy simulation is an integral tool for predicting and optimizing a building's performance during design. Creating energy models and running energy simulations can be a time consuming activity due to the large number of parameters and assumptions that must be addressed to achieve reasonably accurate results. However, leveraging information imbedded within Building Information Models (BIMs) has the potential to increase accuracy and reduce the amount of time required to run energy simulations and can facilitate continuous energy simulations throughout the design process, thus optimizing building performance. Although some literature exists on how design stakeholders perceive the benefits associated with leveraging BIM for energy simulation, little is known about how perceptions associated with leveraging BIM for energy simulation differ between various green design stakeholder user groups. Through an e-survey instrument, this study seeks to determine how perceptions of using BIMs to inform energy simulation differ among distinct design stakeholder groups, which include BIM-only users, energy simulation-only users and BIM and energy simulation users. Additionally, this study seeks to determine what design stakeholders perceive as the main barriers and benefits of implementing BIM-based energy simulation. Results from this study suggest that little to no correlation exists between green design stakeholders' perceptions of the value associated with using information from BIMs to inform energy simulation and their engagement level with BIM and/or energy simulation. However, green design stakeholder perceptions of the value associated with using information from BIMs to inform energy simulation and their engagement with BIM and/or energy simulation may differ between different user groups (i.e. BIM users only, energy simulation users only, and BIM and energy simulation users). For example, the BIM-only user groups appeared to have a strong positive correlation between the perceptions of the value associated with using information from BIMs to inform energy simulation and their engagement with BIM. Additionally, this study suggests that the top perceived benefits of using BIMs to inform energy simulations among green design stakeholders are: facilitation of communication, reducing of process related costs, and giving users the ability examine more design options. The main perceived barrier of using BIMs to inform energy simulations among green design stakeholders was a lack of BIM standards for model integration with multidisciplinary teams. Results from this study will help readers understand how to better implement BIM-based energy simulation while mitigating barriers and optimizing benefits. Additionally, examining discrepancies between user groups can lead the identification and improvement of shortfalls in current BIM-based energy simulation processes. Understanding how perceptions and engagement levels differ among different software user groups will help in developing a strategies for implementing BIM-based energy simulation that are tailored to each specific user group.

Energy landscapes for a machine-learning prediction of patient discharge

NASA Astrophysics Data System (ADS)

Das, Ritankar; Wales, David J.

2016-06-01

The energy landscapes framework is applied to a configuration space generated by training the parameters of a neural network. In this study the input data consists of time series for a collection of vital signs monitored for hospital patients, and the outcomes are patient discharge or continued hospitalisation. Using machine learning as a predictive diagnostic tool to identify patterns in large quantities of electronic health record data in real time is a very attractive approach for supporting clinical decisions, which have the potential to improve patient outcomes and reduce waiting times for discharge. Here we report some preliminary analysis to show how machine learning might be applied. In particular, we visualize the fitting landscape in terms of locally optimal neural networks and the connections between them in parameter space. We anticipate that these results, and analogues of thermodynamic properties for molecular systems, may help in the future design of improved predictive tools.

Spatial decision support system to evaluate crop residue energy potential by anaerobic digestion.

PubMed

Escalante, Humberto; Castro, Liliana; Gauthier-Maradei, Paola; Rodríguez De La Vega, Reynel

2016-11-01

Implementing anaerobic digestion (AD) in energy production from crop residues requires development of decision tools to assess its feasibility and sustainability. A spatial decision support system (SDSS) was constructed to assist decision makers to select appropriate feedstock according to biomethanation potential, identify the most suitable location for biogas facilities, determine optimum plant capacity and supply chain, and evaluate associated risks and costs. SDSS involves a spatially explicit analysis, fuzzy multi-criteria analysis, and statistical and optimization models. The tool was validated on seven crop residues located in Santander, Colombia. For example, fique bagasse generates about 0.21millionm(3)CH4year(-1) (0.329m(3)CH4kg(-1) volatile solids) with a minimum profitable plant of about 2000tonyear(-1) and an internal rate of return of 10.5%. SDSS can be applied to evaluate other biomass resources, availability periods, and co-digestion potential. Copyright © 2016. Published by Elsevier Ltd.

Energy demand and thermal comfort of HVAC systems with thermally activated building systems as a function of user profile

NASA Astrophysics Data System (ADS)

Pałaszyńska, Katarzyna; Bandurski, Karol; Porowski, Mieczysław

2017-11-01

Thermally Activated Building Systems (TABS) are a way to use building structure as a thermal energy storage. As a result, renewable energy sources may be used more efficiently. The paper presents numerical analysis of a HVAC system with TABS energy demand and indoor thermal comfort of a representative room in a non-residential building (governmental, commercial, educational). The purpose of analysis is to investigate the influence of a user profile on system performance. The time span of the analysis is one year - a typical meteorological year. The model was prepared using a generally accepted simulation tool - TRNSYS 17. The results help to better understand the interaction of a user profile with TABS. Therefore they are important for the development of optimal control algorithms for energy efficient buildings equipped with such systems.

A New Tool for Environmental and Economic Optimization of Hydropower Operations

NASA Astrophysics Data System (ADS)

Saha, S.; Hayse, J. W.

2012-12-01

As part of a project funded by the U.S. Department of Energy, researchers from Argonne, Oak Ridge, Pacific Northwest, and Sandia National Laboratories collaborated on the development of an integrated toolset to enhance hydropower operational decisions related to economic value and environmental performance. As part of this effort, we developed an analytical approach (Index of River Functionality, IRF) and an associated software tool to evaluate how well discharge regimes achieve ecosystem management goals for hydropower facilities. This approach defines site-specific environmental objectives using relationships between environmental metrics and hydropower-influenced flow characteristics (e.g., discharge or temperature), with consideration given to seasonal timing, duration, and return frequency requirements for the environmental objectives. The IRF approach evaluates the degree to which an operational regime meets each objective and produces a score representing how well that regime meets the overall set of defined objectives. When integrated with other components in the toolset that are used to plan hydropower operations based upon hydrologic forecasts and various constraints on operations, the IRF approach allows an optimal release pattern to be developed based upon tradeoffs between environmental performance and economic value. We tested the toolset prototype to generate a virtual planning operation for a hydropower facility located in the Upper Colorado River basin as a demonstration exercise. We conducted planning as if looking five months into the future using data for the recently concluded 2012 water year. The environmental objectives for this demonstration were related to spawning and nursery habitat for endangered fishes using metrics associated with maintenance of instream habitat and reconnection of the main channel with floodplain wetlands in a representative reach of the river. We also applied existing mandatory operational constraints for the facility during the demonstration. We compared the optimized virtual operation identified by the toolset to actual operations at the facility for the same time period to evaluate implications of the optimized operational regime on power/revenue generation and environmental performance. Argonne National Laboratory's work was part of a larger "Water-Use-Optimization" project supported by the U.S. Department of Energy Office of Energy Efficiency and Renewable Energy, Water Power Program, under Announcement DE-FOA-0000070. The submitted manuscript has been created by UChicago Argonne, LLC, Operator of Argonne National Laboratory ("Argonne"). Argonne, a U.S. Department of Energy Office of Science laboratory, is operated under Contract No. DE-AC02-06CH11357. The U.S. Government retains for itself, and others acting on its behalf, a paid-up nonexclusive, irrevocable worldwide license in said article to reproduce, prepare derivative works, distribute copies to the public, and perform publicly and display publicly, by or on behalf of the Government.

Multi-objective Optimization of a Solar Humidification Dehumidification Desalination Unit

NASA Astrophysics Data System (ADS)

Rafigh, M.; Mirzaeian, M.; Najafi, B.; Rinaldi, F.; Marchesi, R.

2017-11-01

In the present paper, a humidification-dehumidification desalination unit integrated with solar system is considered. In the first step mathematical model of the whole plant is represented. Next, taking into account the logical constraints, the performance of the system is optimized. On one hand it is desired to have higher energetic efficiency, while on the other hand, higher efficiency results in an increment in the required area for each subsystem which consequently leads to an increase in the total cost of the plant. In the present work, the optimum solution is achieved when the specific energy of the solar heater and also the areas of humidifier and dehumidifier are minimized. Due to the fact that considered objective functions are in conflict, conventional optimization methods are not applicable. Hence, multi objective optimization using genetic algorithm which is an efficient tool for dealing with problems with conflicting objectives has been utilized and a set of optimal solutions called Pareto front each of which is a tradeoff between the mentioned objectives is generated.

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

Conceptual Design of Optimized Fossil Energy Systems with Capture and Sequestration of Carbon Dioxide

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

Nils Johnson; Joan Ogden

2010-12-31

In this final report, we describe research results from Phase 2 of a technical/economic study of fossil hydrogen energy systems with carbon dioxide (CO{sub 2}) capture and storage (CCS). CO{sub 2} capture and storage, or alternatively, CO{sub 2} capture and sequestration, involves capturing CO{sub 2} from large point sources and then injecting it into deep underground reservoirs for long-term storage. By preventing CO{sub 2} emissions into the atmosphere, this technology has significant potential to reduce greenhouse gas (GHG) emissions from fossil-based facilities in the power and industrial sectors. Furthermore, the application of CCS to power plants and hydrogen production facilitiesmore » can reduce CO{sub 2} emissions associated with electric vehicles (EVs) and hydrogen fuel cell vehicles (HFCVs) and, thus, can also improve GHG emissions in the transportation sector. This research specifically examines strategies for transitioning to large-scale coal-derived energy systems with CCS for both hydrogen fuel production and electricity generation. A particular emphasis is on the development of spatially-explicit modeling tools for examining how these energy systems might develop in real geographic regions. We employ an integrated modeling approach that addresses all infrastructure components involved in the transition to these energy systems. The overall objective is to better understand the system design issues and economics associated with the widespread deployment of hydrogen and CCS infrastructure in real regions. Specific objectives of this research are to: Develop improved techno-economic models for all components required for the deployment of both hydrogen and CCS infrastructure, Develop novel modeling methods that combine detailed spatial data with optimization tools to explore spatially-explicit transition strategies, Conduct regional case studies to explore how these energy systems might develop in different regions of the United States, and Examine how the design and cost of coal-based H{sub 2} and CCS infrastructure depend on geography and location.« less

Contingency Contractor Optimization Phase 3 Sustainment Software Design Document - Contingency Contractor Optimization Tool - Prototype

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

Durfee, Justin David; Frazier, Christopher Rawls; Bandlow, Alisa

This document describes the final software design of the Contingency Contractor Optimization Tool - Prototype. Its purpose is to provide the overall architecture of the software and the logic behind this architecture. Documentation for the individual classes is provided in the application Javadoc. The Contingency Contractor Optimization project is intended to address Department of Defense mandates by delivering a centralized strategic planning tool that allows senior decision makers to quickly and accurately assess the impacts, risks, and mitigation strategies associated with utilizing contract support. The Contingency Contractor Optimization Tool - Prototype was developed in Phase 3 of the OSD ATLmore » Contingency Contractor Optimization project to support strategic planning for contingency contractors. The planning tool uses a model to optimize the Total Force mix by minimizing the combined total costs for selected mission scenarios. The model optimizes the match of personnel types (military, DoD civilian, and contractors) and capabilities to meet mission requirements as effectively as possible, based on risk, cost, and other requirements.« less

Battery Pack Thermal Design

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

Pesaran, Ahmad

This presentation describes the thermal design of battery packs at the National Renewable Energy Laboratory. A battery thermal management system essential for xEVs for both normal operation during daily driving (achieving life and performance) and off-normal operation during abuse conditions (achieving safety). The battery thermal management system needs to be optimized with the right tools for the lowest cost. Experimental tools such as NREL's isothermal battery calorimeter, thermal imaging, and heat transfer setups are needed. Thermal models and computer-aided engineering tools are useful for robust designs. During abuse conditions, designs should prevent cell-to-cell propagation in a module/pack (i.e., keep themore » fire small and manageable). NREL's battery ISC device can be used for evaluating the robustness of a module/pack to cell-to-cell propagation.« less

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.

The Salem Smart Power Center: An Assessment of Battery Performance and Economic Potential

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

Balducci, Patrick J.; Alam, M. J.E.; Viswanathan, Vilayanur

This paper presents an assessment of the economic potential of a 5 MW/1.25 MWh Energy Storage System (ESS) installed at the Salem Smart Power Center (SSPC), a smart grid technology demonstration facility owned and operated by Portland General Electric (PGE) in Salem, Oregon. The ESS and the grid conditions in which it operates were modeled using Pacific Northwest National Laboratory’s Battery Storage Evaluation Tool (BSET) to explore tradeoffs between services, and to develop optimal control strategies. This assessment monetized the value derived from nine services the SSPC could provide to PGE and the customers it serves. The ESS and themore » grid conditions in which it operates were modeled using PNNL’s in-house optimization tool BSET to explore tradeoffs between services, and to develop optimal control strategies. The analysis resulted in a number of lessons that provide crucial insights into the practical application of ESS, including; The SSPC, which was originally conceived as a research and test facility and built with the prevailing maturity technology level, was built at a cost ($20.4 million) that exceeds current day prices ($5.4 million) for a similarly designed and built 5 MW/1.25 MWh system; In terms of economic operation, the SSPC is currently underutilized, deployed only for primary frequency response. PNNL modeling indicates that optimal operation of the ESS could generate an additional value of $2.3 million over 20 years. It should also be noted that primary frequency response is the highest benefit application but requires a response from the SSPC only 17 hours each year. While optimally engaged, the ESS would provide arbitrage and ancillary services 78 percent of the time, but those services generate only 27 percent of the total value; Participation in Western EIM represents an interesting opportunity for PGE with a potential to generate $2.1 million value in PV terms over 20 years in the 5-min real-time market; With an energy to power ratio of only 0.25, the SSPC is not well suited to engage in most energy-intensive applications such as arbitrage or ancillary services. By upsizing the storage capacity to 5 MWh and 10MWh, the additional value allows the benefits ($13.3 million and 20.3 million, respectively) to exceed the system’s revenue requirements ($11.5 and $16.4 million, respectively). For the SSPC, ROI ratios exceeded 1.0 when the energy to power ratio fell between 0.5 and 3.5, and peaked at an energy to power ratio of 2.0. This report represents the output of the first of a two-phase effort. Phase II will involve the development of enhanced control strategies to assist PGE in realizing the benefits of energy storage in real-time.« less

Optimizing light delivery for a photoacoustic surgical system

NASA Astrophysics Data System (ADS)

Eddins, Blackberrie; Lediju Bell, Muyinatu A.

2017-03-01

This work explores light delivery optimization for a photoacoustic surgical system previously proposed to provide real-time, intraoperative visualization of the internal carotid arteries hidden by bone during minimally invasive neurosurgeries. Monte Carlo simulations were employed to study 3D light propagation in tissue. For a 2.4 mm diameter drill shaft and 2.9 mm spherical drill tip, the optimal fiber distance from the drill shaft was 2 mm, determined from the maximum normalized fluence seen by the artery. A single fiber was insufficient to deliver light to arteries separated by a minimum of 8 mm. Using similar drill geometry and the optimal 2 mm fiber-to-drill shaft distance, Zemax ray tracing simulations were employed to propagate a 950 nm wavelength Gaussian beam through one or more 600 μm core diameter optical fibers, and the resulting optical beam profile was detected on the representative bone surface. For equally spaced fibers, a single merged optical profile formed with 7 or more fibers, determined by thresholding the resulting light profile images at 1/e times the maximum intensity. The corresponding spot size was larger than that of a single fiber transmitting the same input energy, thus reducing the fluence delivered to the sphenoid bone and enabling higher energies within safety limits. A prototype was designed and built based on these optimization parameters. The methodology we used to optimize our light delivery system to surround surgical tools is generalizable to multiple interventional photoacoustic applications.

Multi-Scale Modeling, Surrogate-Based Analysis, and Optimization of Lithium-Ion Batteries for Vehicle Applications

NASA Astrophysics Data System (ADS)

Du, Wenbo

A common attribute of electric-powered aerospace vehicles and systems such as unmanned aerial vehicles, hybrid- and fully-electric aircraft, and satellites is that their performance is usually limited by the energy density of their batteries. Although lithium-ion batteries offer distinct advantages such as high voltage and low weight over other battery technologies, they are a relatively new development, and thus significant gaps in the understanding of the physical phenomena that govern battery performance remain. As a result of this limited understanding, batteries must often undergo a cumbersome design process involving many manual iterations based on rules of thumb and ad-hoc design principles. A systematic study of the relationship between operational, geometric, morphological, and material-dependent properties and performance metrics such as energy and power density is non-trivial due to the multiphysics, multiphase, and multiscale nature of the battery system. To address these challenges, two numerical frameworks are established in this dissertation: a process for analyzing and optimizing several key design variables using surrogate modeling tools and gradient-based optimizers, and a multi-scale model that incorporates more detailed microstructural information into the computationally efficient but limited macro-homogeneous model. In the surrogate modeling process, multi-dimensional maps for the cell energy density with respect to design variables such as the particle size, ion diffusivity, and electron conductivity of the porous cathode material are created. A combined surrogate- and gradient-based approach is employed to identify optimal values for cathode thickness and porosity under various operating conditions, and quantify the uncertainty in the surrogate model. The performance of multiple cathode materials is also compared by defining dimensionless transport parameters. The multi-scale model makes use of detailed 3-D FEM simulations conducted at the particle-level. A monodisperse system of ellipsoidal particles is used to simulate the effective transport coefficients and interfacial reaction current density within the porous microstructure. Microscopic simulation results are shown to match well with experimental measurements, while differing significantly from homogenization approximations used in the macroscopic model. Global sensitivity analysis and surrogate modeling tools are applied to couple the two length scales and complete the multi-scale model.

Area- and energy-efficient CORDIC accelerators in deep sub-micron CMOS technologies

NASA Astrophysics Data System (ADS)

Vishnoi, U.; Noll, T. G.

2012-09-01

The COordinate Rotate DIgital Computer (CORDIC) algorithm is a well known versatile approach and is widely applied in today's SoCs for especially but not restricted to digital communications. Dedicated CORDIC blocks can be implemented in deep sub-micron CMOS technologies at very low area and energy costs and are attractive to be used as hardware accelerators for Application Specific Instruction Processors (ASIPs). Thereby, overcoming the well known energy vs. flexibility conflict. Optimizing Global Navigation Satellite System (GNSS) receivers to reduce the hardware complexity is an important research topic at present. In such receivers CORDIC accelerators can be used for digital baseband processing (fixed-point) and in Position-Velocity-Time estimation (floating-point). A micro architecture well suited to such applications is presented. This architecture is parameterized according to the wordlengths as well as the number of iterations and can be easily extended for floating point data format. Moreover, area can be traded for throughput by partially or even fully unrolling the iterations, whereby the degree of pipelining is organized with one CORDIC iteration per cycle. From the architectural description, the macro layout can be generated fully automatically using an in-house datapath generator tool. Since the adders and shifters play an important role in optimizing the CORDIC block, they must be carefully optimized for high area and energy efficiency in the underlying technology. So, for this purpose carry-select adders and logarithmic shifters have been chosen. Device dimensioning was automatically optimized with respect to dynamic and static power, area and performance using the in-house tool. The fully sequential CORDIC block for fixed-point digital baseband processing features a wordlength of 16 bits, requires 5232 transistors, which is implemented in a 40-nm CMOS technology and occupies a silicon area of 1560 μm2 only. Maximum clock frequency from circuit simulation of extracted netlist is 768 MHz under typical, and 463 MHz under worst case technology and application corner conditions, respectively. Simulated dynamic power dissipation is 0.24 uW MHz-1 at 0.9 V; static power is 38 uW in slow corner, 65 uW in typical corner and 518 uW in fast corner, respectively. The latter can be reduced by 43% in a 40-nm CMOS technology using 0.5 V reverse-backbias. These features are compared with the results from different design styles as well as with an implementation in 28-nm CMOS technology. It is interesting that in the latter case area scales as expected, but worst case performance and energy do not scale well anymore.

Efficiency Enhancement of a Cantilever-Based Vibration Energy Harvester

PubMed Central

Kubba, Ali E.; Jiang, Kyle

2014-01-01

Extracting energy from ambient vibration to power wireless sensor nodes has been an attractive area of research, particularly in the automotive monitoring field. This article reports the design, analysis and testing of a vibration energy harvesting device based on a miniature asymmetric air-spaced cantilever. The developed design offers high power density, and delivers electric power that is sufficient to support most wireless sensor nodes for structural health monitoring (SHM) applications. The optimized design underwent three evolutionary steps, starting from a simple cantilever design, going through an air-spaced cantilever, and ending up with an optimized air-spaced geometry with boosted power density level. Finite Element Analysis (FEA) was used as an initial tool to compare the three geometries' stiffness (K), output open-circuit voltage (Vave), and average normal strain in the piezoelectric transducer (εave) that directly affect its output voltage. Experimental tests were also carried out in order to examine the energy harvesting level in each of the three designs. The experimental results show how to boost the power output level in a thin air-spaced cantilever beam for energy within the same space envelope. The developed thin air-spaced cantilever (8.37 cm3), has a maximum power output of 2.05 mW (H = 29.29 μJ/cycle). PMID:24366177

Efficiency enhancement of a cantilever-based vibration energy harvester.

PubMed

Kubba, Ali E; Jiang, Kyle

2013-12-23

Extracting energy from ambient vibration to power wireless sensor nodes has been an attractive area of research, particularly in the automotive monitoring field. This article reports the design, analysis and testing of a vibration energy harvesting device based on a miniature asymmetric air-spaced cantilever. The developed design offers high power density, and delivers electric power that is sufficient to support most wireless sensor nodes for structural health monitoring (SHM) applications. The optimized design underwent three evolutionary steps, starting from a simple cantilever design, going through an air-spaced cantilever, and ending up with an optimized air-spaced geometry with boosted power density level. Finite Element Analysis (FEA) was used as an initial tool to compare the three geometries' stiffness (K), output open-circuit voltage (V(ave)), and average normal strain in the piezoelectric transducer (ε(ave)) that directly affect its output voltage. Experimental tests were also carried out in order to examine the energy harvesting level in each of the three designs. The experimental results show how to boost the power output level in a thin air-spaced cantilever beam for energy within the same space envelope. The developed thin air-spaced cantilever (8.37 cm3), has a maximum power output of 2.05 mW (H = 29.29 μJ/cycle).

Software augmented buildings: Exploiting existing infrastructure to improve energy efficiency and comfort in commercial buildings

NASA Astrophysics Data System (ADS)

Balaji, Bharathan

Commercial buildings consume 19% of energy in the US as of 2010, and traditionally, their energy use has been optimized through improved equipment efficiency and retrofits. Beyond improved hardware and infrastructure, there exists a tremendous potential in reducing energy use through better monitoring and operation. We present several applications that we developed and deployed to support our thesis that building energy use can be reduced through sensing, monitoring and optimization software that modulates use of building subsystems including HVAC. We focus on HVAC systems as these constitute 48-55% of building energy use. Specifically, in case of sensing, we describe an energy apportionment system that enables us to estimate real-time zonal HVAC power consumption by analyzing existing sensor information. With this energy breakdown, we can measure effectiveness of optimization solutions and identify inefficiencies. Central to energy efficiency improvement is determination of human occupancy in buildings. But this information is often unavailable or expensive to obtain using wide scale sensor deployment. We present our system that infers room level occupancy inexpensively by leveraging existing WiFi infrastructure. Occupancy information can be used not only to directly control HVAC but also to infer state of the building for predictive control. Building energy use is strongly influenced by human behaviors, and timely feedback mechanisms can encourage energy saving behavior. Occupants interact with HVAC using thermostats which has shown to be inadequate for thermal comfort. Building managers are responsible for incorporating energy efficiency measures, but our interviews reveal that they struggle to maintain efficiency due to lack of analytical tools and contextual information. We present our software services that provide energy feedback to occupants and building managers, improves comfort with personalized control and identifies energy wasting faults. For wide scale deployment of such energy saving software, they need to be portable across multiple buildings. However, buildings consist of heterogeneous equipment and use inconsistent naming schema, and developers need extensive domain knowledge to map sensor information to a standard format. To enable portability, we present an active learning algorithm that automates mapping building sensor metadata to a standard naming schema.

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.

Modeling surgical tool selection patterns as a "traveling salesman problem" for optimizing a modular surgical tool system.

PubMed

Nelson, Carl A; Miller, David J; Oleynikov, Dmitry

2008-01-01

As modular systems come into the forefront of robotic telesurgery, streamlining the process of selecting surgical tools becomes an important consideration. This paper presents a method for optimal queuing of tools in modular surgical tool systems, based on patterns in tool-use sequences, in order to minimize time spent changing tools. The solution approach is to model the set of tools as a graph, with tool-change frequency expressed as edge weights in the graph, and to solve the Traveling Salesman Problem for the graph. In a set of simulations, this method has shown superior performance at optimizing tool arrangements for streamlining surgical procedures.

Lunar South Pole Illumination: Review, Reassessment, and Power System Implications

NASA Technical Reports Server (NTRS)

Fincannon, James

2007-01-01

This paper reviews past analyses and research related to lunar south pole illumination and presents results of independent illumination analyses using an analytical tool and a radar digital elevation model. The analysis tool enables assessment at most locations near the lunar poles for any time and any year. Average illumination fraction, energy storage duration, solar/horizon terrain elevation profiles and illumination fraction profiles are presented for various highly illuminated sites which have been identified for manned or unmanned operations. The format of the data can be used by power system designers to develop mass optimized solar and energy storage systems. Data are presented for the worse case lunar day (a critical power planning bottleneck) as well as three lunar days during lunar south pole winter. The main site under consideration by present lunar mission planners (on the Crater Shackleton rim) is shown to have, for the worse case lunar day, a 0.71 average illumination fraction and 73 to 117 hours required for energy storage (depending on power system type). Linking other sites and including towers at either site are shown to not completely eliminate the need for energy storage.

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

NASA Astrophysics Data System (ADS)

Veselka, T. D.; Mahalik, M.

2012-12-01

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

Nutritionally Optimized, Culturally Acceptable, Cost-Minimized Diets for Low Income Ghanaian Families Using Linear Programming.

PubMed

Nykänen, Esa-Pekka A; Dunning, Hanna E; Aryeetey, Richmond N O; Robertson, Aileen; Parlesak, Alexandr

2018-04-07

The Ghanaian population suffers from a double burden of malnutrition. Cost of food is considered a barrier to achieving a health-promoting diet. Food prices were collected in major cities and in rural areas in southern Ghana. Linear programming (LP) was used to calculate nutritionally optimized diets (food baskets (FBs)) for a low-income Ghanaian family of four that fulfilled energy and nutrient recommendations in both rural and urban settings. Calculations included implementing cultural acceptability for families living in extreme and moderate poverty (food budget under USD 1.9 and 3.1 per day respectively). Energy-appropriate FBs minimized for cost, following Food Balance Sheets (FBS), lacked key micronutrients such as iodine, vitamin B12 and iron for the mothers. Nutritionally adequate FBs were achieved in all settings when optimizing for a diet cheaper than USD 3.1. However, when delimiting cost to USD 1.9 in rural areas, wild foods had to be included in order to meet nutritional adequacy. Optimization suggested to reduce roots, tubers and fruits and to increase cereals, vegetables and oil-bearing crops compared with FBS. LP is a useful tool to design culturally acceptable diets at minimum cost for low-income Ghanaian families to help advise national authorities how to overcome the double burden of malnutrition.

Nutritionally Optimized, Culturally Acceptable, Cost-Minimized Diets for Low Income Ghanaian Families Using Linear Programming

PubMed Central

Robertson, Aileen

2018-01-01

The Ghanaian population suffers from a double burden of malnutrition. Cost of food is considered a barrier to achieving a health-promoting diet. Food prices were collected in major cities and in rural areas in southern Ghana. Linear programming (LP) was used to calculate nutritionally optimized diets (food baskets (FBs)) for a low-income Ghanaian family of four that fulfilled energy and nutrient recommendations in both rural and urban settings. Calculations included implementing cultural acceptability for families living in extreme and moderate poverty (food budget under USD 1.9 and 3.1 per day respectively). Energy-appropriate FBs minimized for cost, following Food Balance Sheets (FBS), lacked key micronutrients such as iodine, vitamin B12 and iron for the mothers. Nutritionally adequate FBs were achieved in all settings when optimizing for a diet cheaper than USD 3.1. However, when delimiting cost to USD 1.9 in rural areas, wild foods had to be included in order to meet nutritional adequacy. Optimization suggested to reduce roots, tubers and fruits and to increase cereals, vegetables and oil-bearing crops compared with FBS. LP is a useful tool to design culturally acceptable diets at minimum cost for low-income Ghanaian families to help advise national authorities how to overcome the double burden of malnutrition. PMID:29642444

A new optimization tool path planning for 3-axis end milling of free-form surfaces based on efficient machining intervals

NASA Astrophysics Data System (ADS)

Vu, Duy-Duc; Monies, Frédéric; Rubio, Walter

2018-05-01

A large number of studies, based on 3-axis end milling of free-form surfaces, seek to optimize tool path planning. Approaches try to optimize the machining time by reducing the total tool path length while respecting the criterion of the maximum scallop height. Theoretically, the tool path trajectories that remove the most material follow the directions in which the machined width is the largest. The free-form surface is often considered as a single machining area. Therefore, the optimization on the entire surface is limited. Indeed, it is difficult to define tool trajectories with optimal feed directions which generate largest machined widths. Another limiting point of previous approaches for effectively reduce machining time is the inadequate choice of the tool. Researchers use generally a spherical tool on the entire surface. However, the gains proposed by these different methods developed with these tools lead to relatively small time savings. Therefore, this study proposes a new method, using toroidal milling tools, for generating toolpaths in different regions on the machining surface. The surface is divided into several regions based on machining intervals. These intervals ensure that the effective radius of the tool, at each cutter-contact points on the surface, is always greater than the radius of the tool in an optimized feed direction. A parallel plane strategy is then used on the sub-surfaces with an optimal specific feed direction for each sub-surface. This method allows one to mill the entire surface with efficiency greater than with the use of a spherical tool. The proposed method is calculated and modeled using Maple software to find optimal regions and feed directions in each region. This new method is tested on a free-form surface. A comparison is made with a spherical cutter to show the significant gains obtained with a toroidal milling cutter. Comparisons with CAM software and experimental validations are also done. The results show the efficiency of the method.

REopt Improves the Operations of Alcatraz's Solar PV-Battery-Diesel Hybrid System

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

Olis, Daniel R; Walker, H. A; Van Geet, Otto D

This poster identifies operations improvement strategies for a photovoltaic (PV)-battery-diesel hybrid system at the National Park Service's Alcatraz Island using NREL's REopt analysis tool. The current 'cycle charging' strategy results in significant curtailing of energy production from the PV array, requiring excessive diesel use, while also incurring high wear on batteries without benefit of improved efficiency. A simple 'load following' strategy results in near optimal operating cost reduction.

Assessing the Operational Robustness of the Homer Model for Marine Corps Use in Expeditionary Environments

DTIC Science & Technology

2014-06-01

systems. It can model systems including both conventional, diesel powered generators and renewable power sources such as photovoltaic arrays and wind...conducted an experiment where he assessed the capabilities of the HOMER model in forecasting the power output of a solar panel at NPS [32]. In his ex...energy efficiency in expeditionary operations, the HOMER micropower optimization model provides potential to serve as a powerful tool for improving

A comparison of renewable energy technologies using two simulation softwares: HOMER and RETScreen

NASA Astrophysics Data System (ADS)

Ramli, Mohd Sufian; Wahid, Siti Sufiah Abd; Hassan, Khairul Kamarudin

2017-08-01

This paper concerns on modelling renewable energy technologies including PV standalone system (PVSS) and wind standalone system (WSS) as well as PV-wind hybrid system (PVWHS). To evaluate the performance of all power system configurations in term of economic analysis and optimization, simulation tools called HOMER and RETScreen are used in this paper. HOMER energy modeling software is a powerful tool for designing and analyzing hybrid power systems, which contains a mix of conventional generators, wind turbines, solar photovoltaic's, hydropower, batteries, and other inputs. RETScreen uses a Microsoft Excel-based spreadsheet model that consists of a set of workbooks which calculates the annual average energy flows with adjustment factors to account for temporal effects such as solar-load coincidence. Sizes of equipments are calculated and inserted as inputs to HOMER and RETScreen. The result obtained are analyzed and discussed. The cost per kWh to generate electricity using the PVSS system to supply the average demand of 8.4 kWh/day ranges between RM 1.953/kWh to RM 3.872/kWh. It has been found that the PVSS gives the lowest cost of energy compared to the other proposed two technologies that have been simulated by using HOMER and RETScreen.

Identifying energy and carbon footprint optimization potentials of a sludge treatment line with Life Cycle Assessment.

PubMed

Remy, C; Lesjean, B; Waschnewski, J

2013-01-01

This study exemplifies the use of Life Cycle Assessment (LCA) as a tool to quantify the environmental impacts of processes for wastewater treatment. In a case study, the sludge treatment line of a large wastewater treatment plant (WWTP) is analysed in terms of cumulative energy demand and the emission of greenhouse gases (carbon footprint). Sludge treatment consists of anaerobic digestion, dewatering, drying, and disposal of stabilized sludge in mono- or co-incineration in power plants or cement kilns. All relevant forms of energy demand (electricity, heat, chemicals, fossil fuels, transport) and greenhouse gas emissions (fossil CO(2), CH(4), N(2)O) are accounted in the assessment, including the treatment of return liquor from dewatering in the WWTP. Results show that the existing process is positive in energy balance (-162 MJ/PE(COD) * a) and carbon footprint (-11.6 kg CO(2)-eq/PE(COD) * a) by supplying secondary products such as electricity from biogas production or mono-incineration and substituting fossil fuels in co-incineration. However, disposal routes for stabilized sludge differ considerably in their energy and greenhouse gas profiles. In total, LCA proves to be a suitable tool to support future investment decisions with information of environmental relevance on the impact of wastewater treatment, but also urban water systems in general.

GLIMPSE: A decision support tool for simultaneously achieving our air quality management and climate change mitigation goals

NASA Astrophysics Data System (ADS)

Pinder, R. W.; Akhtar, F.; Loughlin, D. H.; Henze, D. K.; Bowman, K. W.

2012-12-01

Poor air quality, ecosystem damages, and climate change all are caused by the combustion of fossil fuels, yet environmental management often addresses each of these challenges separately. This can lead to sub-optimal strategies and unintended consequences. Here we present GLIMPSE -- a decision support tool for simultaneously achieving our air quality and climate change mitigation goals. GLIMPSE comprises of two types of models, (i) the adjoint of the GEOS-Chem chemical transport model, to calculate the relationship between emissions and impacts at high spatial resolution, and (ii) the MARKAL energy system model, to calculate the relationship between energy technologies and emissions. This presentation will demonstrate how GLIMPSE can be used to explore energy scenarios to better achieve both improved air quality and mitigate climate change. Second, this presentation will discuss how space-based observations can be incorporated into GLIMPSE to improve decision-making. NASA satellite products, namely ozone radiative forcing from the Tropospheric Emission Spectrometer (TES), are used to extend GLIMPSE to include the impact of emissions on ozone radiative forcing. This provides a much needed observational constraint on ozone radiative forcing.

National Ignition Facility Control and Information System Operational Tools

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

Marshall, C D; Beeler, R G; Bowers, G A

The National Ignition Facility (NIF) in Livermore, California, is the world's highest-energy laser fusion system and one of the premier large scale scientific projects in the United States. The system is designed to setup and fire a laser shot to a fusion ignition or high energy density target at rates up to a shot every 4 hours. NIF has 192 laser beams delivering up to 1.8 MJ of energy to a {approx}2 mm target that is planned to produce >100 billion atm of pressure and temperatures of >100 million degrees centigrade. NIF is housed in a ten-story building footprint themore » size of three football fields as shown in Fig. 1. Commissioning was recently completed and NIF will be formally dedicated at Lawrence Livermore National Laboratory on May 29, 2009. The control system has 60,000 hardware controls points and employs 2 million lines of control system code. The control room has highly automated equipment setup prior to firing laser system shots. This automation has a data driven implementation that is conducive to dynamic modification and optimization depending on the shot goals defined by the end user experimenters. NIF has extensive facility machine history and infrastructure maintenance workflow tools both under development and deployed. An extensive operational tools suite has been developed to support facility operations including experimental shot setup, machine readiness, machine health and safety, and machine history. The following paragraphs discuss the current state and future upgrades to these four categories of operational tools.« less

Experimental design for the formulation and optimization of novel cross-linked oilispheres developed for in vitro site-specific release of Mentha piperita oil.

PubMed

Sibanda, Wilbert; Pillay, Viness; Danckwerts, Michael P; Viljoen, Alvaro M; van Vuuren, Sandy; Khan, Riaz A

2004-03-12

A Plackett-Burman design was employed to develop and optimize a novel crosslinked calcium-aluminum-alginate-pectinate oilisphere complex as a potential system for the in vitro site-specific release of Mentha piperita, an essential oil used for the treatment of irritable bowel syndrome. The physicochemical and textural properties (dependent variables) of this complex were found to be highly sensitive to changes in the concentration of the polymers (0%-1.5% wt/vol), crosslinkers (0%-4% wt/vol), and crosslinking reaction times (0.5-6 hours) (independent variables). Particle size analysis indicated both unimodal and bimodal populations with the highest frequency of 2 mm oilispheres. Oil encapsulation ranged from 6 to 35 mg/100 mg oilispheres. Gravimetric changes of the crosslinked matrix indicated significant ion sequestration and loss in an exponential manner, while matrix erosion followed Higuchi's cube root law. Among the various measured responses, the total fracture energy was the most suitable optimization objective (R2 = 0.88, Durbin-Watson Index = 1.21%, Coefficient of Variation (CV) = 33.21%). The Lagrangian technique produced no significant differences (P > .05) between the experimental and predicted total fracture energy values (0.0150 vs 0.0107 J). Artificial Neural Networks, as an alternative predictive tool of the total fracture energy, was highly accurate (final mean square error of optimal network epoch approximately 0.02). Fused-coated optimized oilispheres produced a 4-hour lag phase followed by zero-order kinetics (n > 0.99), whereby analysis of release data indicated that diffusion (Fickian constant k1 = 0.74 vs relaxation constant k2 = 0.02) was the predominant release mechanism.

Optimization of binding electrostatics: Charge complementarity in the barnase-barstar protein complex

PubMed Central

lee, Lee-Peng; Tidor, Bruce

2001-01-01

Theoretical and experimental studies have shown that the large desolvation penalty required for polar and charged groups frequently precludes their involvement in electrostatic interactions that contribute strongly to net stability in the folding or binding of proteins in aqueous solution near room temperature. We have previously developed a theoretical framework for computing optimized electrostatic interactions and illustrated use of the algorithm with simplified geometries. Given a receptor and model assumptions, the method computes the ligand-charge distribution that provides the most favorable balance of desolvation and interaction effects on binding. In this paper the method has been extended to treat complexes using actual molecular shapes. The barnase-barstar protein complex was investigated with barnase treated as a target receptor. The atomic point charges of barstar were varied to optimize the electrostatic binding free energy. Barnase and natural barstar form a tight complex (Kd ∼ 10−14 M) with many charged and polar groups near the interface that make this a particularly relevant system for investigating the role of electrostatic effects on binding. The results show that sets of barstar charges (resulting from optimization with different constraints) can be found that give rise to relatively large predicted improvements in electrostatic binding free energy. Principles for enhancing the effect of electrostatic interactions in molecular binding in aqueous environments are discussed in light of the optima. Our findings suggest that, in general, the enhancements in electrostatic binding free energy resulting from modification of polar and charged groups can be substantial. Moreover, a recently proposed definition of electrostatic complementarity is shown to be a useful tool for examining binding interfaces. Finally, calculational results suggest that wild-type barstar is closer to being affinity optimized than is barnase for their mutual binding, consistent with the known roles of these proteins. PMID:11266622

Annual Report: Carbon Capture Simulation Initiative (CCSI) (30 September 2012)

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

Miller, David C.; Syamlal, Madhava; Cottrell, Roger

2012-09-30

The Carbon Capture Simulation Initiative (CCSI) is a partnership among national laboratories, industry and academic institutions that is developing and deploying state-of-the-art computational modeling and simulation tools to accelerate the commercialization of carbon capture technologies from discovery to development, demonstration, and ultimately the widespread deployment to hundreds of power plants. The CCSI Toolset will provide end users in industry with a comprehensive, integrated suite of scientifically validated models, with uncertainty quantification (UQ), optimization, risk analysis and decision making capabilities. The CCSI Toolset incorporates commercial and open-source software currently in use by industry and is also developing new software tools asmore » necessary to fill technology gaps identified during execution of the project. Ultimately, the CCSI Toolset will (1) enable promising concepts to be more quickly identified through rapid computational screening of devices and processes; (2) reduce the time to design and troubleshoot new devices and processes; (3) quantify the technical risk in taking technology from laboratory-scale to commercial-scale; and (4) stabilize deployment costs more quickly by replacing some of the physical operational tests with virtual power plant simulations. CCSI is organized into 8 technical elements that fall under two focus areas. The first focus area (Physicochemical Models and Data) addresses the steps necessary to model and simulate the various technologies and processes needed to bring a new Carbon Capture and Storage (CCS) technology into production. The second focus area (Analysis & Software) is developing the software infrastructure to integrate the various components and implement the tools that are needed to make quantifiable decisions regarding the viability of new CCS technologies. CCSI also has an Industry Advisory Board (IAB). By working closely with industry from the inception of the project to identify industrial challenge problems, CCSI ensures that the simulation tools are developed for the carbon capture technologies of most relevance to industry. CCSI is led by the National Energy Technology Laboratory (NETL) and leverages the Department of Energy (DOE) national laboratories' core strengths in modeling and simulation, bringing together the best capabilities at NETL, Los Alamos National Laboratory (LANL), Lawrence Berkeley National Laboratory (LBNL), Lawrence Livermore National Laboratory (LLNL), and Pacific Northwest National Laboratory (PNNL). The CCSI's industrial partners provide representation from the power generation industry, equipment manufacturers, technology providers and engineering and construction firms. The CCSI's academic participants (Carnegie Mellon University, Princeton University, West Virginia University, and Boston University) bring unparalleled expertise in multiphase flow reactors, combustion, process synthesis and optimization, planning and scheduling, and process control techniques for energy processes. During Fiscal Year (FY) 12, CCSI released its first set of computational tools and models. This pre-release, a year ahead of the originally planned first release, is the result of intense industry interest in getting early access to the tools and the phenomenal progress of the CCSI technical team. These initial components of the CCSI Toolset provide new models and computational capabilities that will accelerate the commercial development of carbon capture technologies as well as related technologies, such as those found in the power, refining, chemicals, and gas production industries. The release consists of new tools for process synthesis and optimization to help identify promising concepts more quickly, new physics-based models of potential capture equipment and processes that will reduce the time to design and troubleshoot new systems, a framework to quantify the uncertainty of model predictions, and various enabling tools that provide new capabilities such as creating reduced order models (ROMs) from reacting multiphase flow simulations and running thousands of process simulations concurrently for optimization and UQ.« less

Optimization of the propulsion for multistage solid rocket motor launchers

NASA Astrophysics Data System (ADS)

Calabro, M.; Dufour, A.; Macaire, A.

2002-02-01

Some tools focused on a rapid multidisciplinary optimization capability for multistage launch vehicle design were developed at EADS-LV. These tools may be broken down into two categories, those related to propulsion design optimization and a computer code devoted to trajectories and under constraints optimization. Both are linked in order to obtain optimal vehicle design after an iterative process. After a description of the two categories tools, an example of application is given on a small space launcher.

Educational Tool for Optimal Controller Tuning Using Evolutionary Strategies

ERIC Educational Resources Information Center

Carmona Morales, D.; Jimenez-Hornero, J. E.; Vazquez, F.; Morilla, F.

2012-01-01

In this paper, an optimal tuning tool is presented for control structures based on multivariable proportional-integral-derivative (PID) control, using genetic algorithms as an alternative to traditional optimization algorithms. From an educational point of view, this tool provides students with the necessary means to consolidate their knowledge on…

Plasma for environment

NASA Astrophysics Data System (ADS)

Van Oost, G.

2017-11-01

Human activity is associated with the permanent emergence of a very wide range of waste streams. The most widely used treatment of waste is thermal processing such as incineration. An alternative environmentally friendly process is based on thermal plasma technology which is a very flexible tool because it allows to operate in a wide temperature range with almost any chemical composition of waste and chemicals needed for processing this waste, and to convert organic waste into energy or chemical substances as well as to destroy toxic organic compounds, and to vitrify radioactive waste in a scenario that for each specific type of waste can be considered optimal, both in terms of energy efficiency and environmental safety.

Plasma for environment

NASA Astrophysics Data System (ADS)

Van Oost, G.

2017-12-01

Human activity is associated with the permanent emergence of a very wide range of waste streams. The most widely used treatment of waste is thermal processing such as incineration. An alternative environmentally friendly process is based on thermal plasma technology which is a very flexible tool because it allows to operate in a wide temperature range with almost any chemical composition of waste and chemicals needed for processing this waste. It allows the conversion of organic waste into energy or chemical substances as well as the destruction of toxic organic compounds in a scenario that for each specific type of waste can be considered optimal, both in terms of energy efficiency and environmental safety.

Genome-Based Models to Optimize In Situ Bioremediation of Uranium and Harvesting Electrical Energy from Waste Organic Matter

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

Lovley, Derek R

2012-12-28

The goal of this research was to provide computational tools to predictively model the behavior of two microbial communities of direct relevance to Department of Energy interests: 1) the microbial community responsible for in situ bioremediation of uranium in contaminated subsurface environments; and 2) the microbial community capable of harvesting electricity from waste organic matter and renewable biomass. During this project the concept of microbial electrosynthesis, a novel form of artificial photosynthesis for the direct production of fuels and other organic commodities from carbon dioxide and water was also developed and research was expanded into this area as well.

Graphical analysis of power systems for mobile robotics

NASA Astrophysics Data System (ADS)

Raade, Justin William

The field of mobile robotics places stringent demands on the power system. Energetic autonomy, or the ability to function for a useful operation time independent of any tether, refueling, or recharging, is a driving force in a robot designed for a field application. The focus of this dissertation is the development of two graphical analysis tools, namely Ragone plots and optimal hybridization plots, for the design of human scale mobile robotic power systems. These tools contribute to the intuitive understanding of the performance of a power system and expand the toolbox of the design engineer. Ragone plots are useful for graphically comparing the merits of different power systems for a wide range of operation times. They plot the specific power versus the specific energy of a system on logarithmic scales. The driving equations in the creation of a Ragone plot are derived in terms of several important system parameters. Trends at extreme operation times (both very short and very long) are examined. Ragone plot analysis is applied to the design of several power systems for high-power human exoskeletons. Power systems examined include a monopropellant-powered free piston hydraulic pump, a gasoline-powered internal combustion engine with hydraulic actuators, and a fuel cell with electric actuators. Hybrid power systems consist of two or more distinct energy sources that are used together to meet a single load. They can often outperform non-hybrid power systems in low duty-cycle applications or those with widely varying load profiles and long operation times. Two types of energy sources are defined: engine-like and capacitive. The hybridization rules for different combinations of energy sources are derived using graphical plots of hybrid power system mass versus the primary system power. Optimal hybridization analysis is applied to several power systems for low-power human exoskeletons. Hybrid power systems examined include a fuel cell and a solar panel coupled with lithium polymer batteries. In summary, this dissertation describes the development and application of two graphical analysis tools for the intuitive design of mobile robotic power systems. Several design examples are discussed involving human exoskeleton power systems.

Combining LCT tools for the optimization of an industrial process: material and energy flow analysis and best available techniques.

PubMed

Rodríguez, M T Torres; Andrade, L Cristóbal; Bugallo, P M Bello; Long, J J Casares

2011-09-15

Life cycle thinking (LCT) is one of the philosophies that has recently appeared in the context of the sustainable development. Some of the already existing tools and methods, as well as some of the recently emerged ones, which seek to understand, interpret and design the life of a product, can be included into the scope of the LCT philosophy. That is the case of the material and energy flow analysis (MEFA), a tool derived from the industrial metabolism definition. This paper proposes a methodology combining MEFA with another technique derived from sustainable development which also fits the LCT philosophy, the BAT (best available techniques) analysis. This methodology, applied to an industrial process, seeks to identify the so-called improvable flows by MEFA, so that the appropriate candidate BAT can be selected by BAT analysis. Material and energy inputs, outputs and internal flows are quantified, and sustainable solutions are provided on the basis of industrial metabolism. The methodology has been applied to an exemplary roof tile manufacture plant for validation. 14 Improvable flows have been identified and 7 candidate BAT have been proposed aiming to reduce these flows. The proposed methodology provides a way to detect improvable material or energy flows in a process and selects the most sustainable options to enhance them. Solutions are proposed for the detected improvable flows, taking into account their effectiveness on improving such flows. Copyright © 2011 Elsevier B.V. All rights reserved.

Optima Nutrition: an allocative efficiency tool to reduce childhood stunting by better targeting of nutrition-related interventions.

PubMed

Pearson, Ruth; Killedar, Madhura; Petravic, Janka; Kakietek, Jakub J; Scott, Nick; Grantham, Kelsey L; Stuart, Robyn M; Kedziora, David J; Kerr, Cliff C; Skordis-Worrall, Jolene; Shekar, Meera; Wilson, David P

2018-03-20

Child stunting due to chronic malnutrition is a major problem in low- and middle-income countries due, in part, to inadequate nutrition-related practices and insufficient access to services. Limited budgets for nutritional interventions mean that available resources must be targeted in the most cost-effective manner to have the greatest impact. Quantitative tools can help guide budget allocation decisions. The Optima approach is an established framework to conduct resource allocation optimization analyses. We applied this approach to develop a new tool, 'Optima Nutrition', for conducting allocative efficiency analyses that address childhood stunting. At the core of the Optima approach is an epidemiological model for assessing the burden of disease; we use an adapted version of the Lives Saved Tool (LiST). Six nutritional interventions have been included in the first release of the tool: antenatal micronutrient supplementation, balanced energy-protein supplementation, exclusive breastfeeding promotion, promotion of improved infant and young child feeding (IYCF) practices, public provision of complementary foods, and vitamin A supplementation. To demonstrate the use of this tool, we applied it to evaluate the optimal allocation of resources in 7 districts in Bangladesh, using both publicly available data (such as through DHS) and data from a complementary costing study. Optima Nutrition can be used to estimate how to target resources to improve nutrition outcomes. Specifically, for the Bangladesh example, despite only limited nutrition-related funding available (an estimated $0.75 per person in need per year), even without any extra resources, better targeting of investments in nutrition programming could increase the cumulative number of children living without stunting by 1.3 million (an extra 5%) by 2030 compared to the current resource allocation. To minimize stunting, priority interventions should include promotion of improved IYCF practices as well as vitamin A supplementation. Once these programs are adequately funded, the public provision of complementary foods should be funded as the next priority. Programmatic efforts should give greatest emphasis to the regions of Dhaka and Chittagong, which have the greatest number of stunted children. A resource optimization tool can provide important guidance for targeting nutrition investments to achieve greater impact.

The importance of geospatial data to calculate the optimal distribution of renewable energies

NASA Astrophysics Data System (ADS)

Díaz, Paula; Masó, Joan

2013-04-01

Specially during last three years, the renewable energies are revolutionizing the international trade while they are geographically diversifying markets. Renewables are experiencing a rapid growth in power generation. According to REN21 (2012), during last six years, the total renewables capacity installed grew at record rates. In 2011, the EU raised its share of global new renewables capacity till 44%. The BRICS nations (Brazil, Russia, India and China) accounted for about 26% of the total global. Moreover, almost twenty countries in the Middle East, North Africa, and sub-Saharan Africa have currently active markets in renewables. The energy return ratios are commonly used to calculate the efficiency of the traditional energy sources. The Energy Return On Investment (EROI) compares the energy returned for a certain source and the energy used to get it (explore, find, develop, produce, extract, transform, harvest, grow, process, etc.). These energy return ratios have demonstrated a general decrease of efficiency of the fossil fuels and gas. When considering the limitations of the quantity of energy produced by some sources, the energy invested to obtain them and the difficulties of finding optimal locations for the establishment of renewables farms (e.g. due to an ever increasing scarce of appropriate land) the EROI becomes relevant in renewables. A spatialized EROI, which uses variables with spatial distribution, enables the optimal position in terms of both energy production and associated costs. It is important to note that the spatialized EROI can be mathematically formalized and calculated the same way for different locations in a reproducible way. This means that having established a concrete EROI methodology it is possible to generate a continuous map that will highlight the best productive zones for renewable energies in terms of maximum energy return at minimum cost. Relevant variables to calculate the real energy invested are the grid connections between production and consumption, transportation loses and efficiency of the grid. If appropriate, the spatialized EROI analysis could include any indirect costs that the source of energy might produce, such as visual impacts, food market impacts and land price. Such a spatialized study requires GIS tools to compute operations using both spatial relations like distances and frictions, and topological relations like connectivity, not easy to consider in the way that EROI is currently calculated. In a broader perspective, by applying the EROI to various energy sources, a comparative analysis of the efficiency to obtain different source can be done in a quantitative way. The increase in energy investment is also accompanied by the increase of manufactures and policies. Further efforts will be necessary in the coming years to provide energy access through smart grids and to determine the efficient areas in terms of cost of production and energy returned on investment. The authors present the EROI as a reliable solution to address the input and output energy relationship and increase the efficiency in energy investment considering the appropriate geospatial variables. The spatialized EROI can be a useful tool to consider by decision makers when designing energy policies and programming energy funds, because it is an objective demonstration of which energy sources are more convenient in terms of costs and efficiency.

Decision Support for Integrated Energy-Water Planning

NASA Astrophysics Data System (ADS)

Tidwell, V. C.; William, H.; Klise, G.; Kobos, P. H.; Malczynski, L. A.

2008-12-01

Currently, electrical power generation uses about 140 billion gallons of water per day accounting for over 40% of all freshwater withdrawals thus competing with irrigated agriculture as the leading user of water. To meet their demand for water, proposed power plants must often target waterways and aquifers prone to overdraft or which may be home to environmentally sensitive species. Acquisition of water rights, permits and public support may therefore be a formidable hurdle when licensing new power plants. Given these current difficulties, what does the future hold when projected growth in population and the economy may require a 30% increase in power generation capacity by 2025? Technology solutions can only take us so far, as noted by the National Energy-Water Roadmap Exercise. This roadmap identified the need for long-term and integrated resource planning supported with scientifically credible models as a leading issue. To address this need a decision support framework is being developed that targets the shared needs of energy and water producers, resource managers, regulators, and decision makers at the federal, state and local levels. The framework integrates analysis and optimization capabilities to help identify potential trade-offs, and "best" alternatives among an overwhelming number of energy/water options and objectives. The decision support tool is comprised of three basic elements: a system dynamics model coupling the physical and economic systems important to integrated energy-water planning and management; an optimization toolbox; and a software wrapper that integrates the aforementioned elements along with additional external energy/water models, databases, and visualization products. An interactive interface allows direct interaction with the model and access to real-time results organized according to a variety of reference systems, e.g., from a political, watershed, or electric power grid perspective. With this unique synthesis of various perspectives, the tool may help highlight looming changes where policy, technical, economic, and data collection options may alleviate stresses within the underlying water systems that support electricity generation. Sandia is a multiprogram laboratory operated by Sandia Corporation, a Lockheed Martin Company, for the United States Department of Energy's National Nuclear Security Administration under contract DE-AC04- 94AL85000.

Development of Chemical Process Design and Control for ...

EPA Pesticide Factsheets

This contribution describes a novel process systems engineering framework that couples advanced control with sustainability evaluation and decision making for the optimization of process operations to minimize environmental impacts associated with products, materials, and energy. The implemented control strategy combines a biologically inspired method with optimal control concepts for finding more sustainable operating trajectories. The sustainability assessment of process operating points is carried out by using the U.S. E.P.A.’s Gauging Reaction Effectiveness for the ENvironmental Sustainability of Chemistries with a multi-Objective Process Evaluator (GREENSCOPE) tool that provides scores for the selected indicators in the economic, material efficiency, environmental and energy areas. The indicator scores describe process performance on a sustainability measurement scale, effectively determining which operating point is more sustainable if there are more than several steady states for one specific product manufacturing. Through comparisons between a representative benchmark and the optimal steady-states obtained through implementation of the proposed controller, a systematic decision can be made in terms of whether the implementation of the controller is moving the process towards a more sustainable operation. The effectiveness of the proposed framework is illustrated through a case study of a continuous fermentation process for fuel production, whose materi

DNA Assembly with De Bruijn Graphs Using an FPGA Platform.

PubMed

Poirier, Carl; Gosselin, Benoit; Fortier, Paul

2018-01-01

This paper presents an FPGA implementation of a DNA assembly algorithm, called Ray, initially developed to run on parallel CPUs. The OpenCL language is used and the focus is placed on modifying and optimizing the original algorithm to better suit the new parallelization tool and the radically different hardware architecture. The results show that the execution time is roughly one fourth that of the CPU and factoring energy consumption yields a tenfold savings.

Frontiers of beam diagnostics in plasma accelerators: Measuring the ultra-fast and ultra-cold

NASA Astrophysics Data System (ADS)

Cianchi, A.; Anania, M. P.; Bisesto, F.; Chiadroni, E.; Curcio, A.; Ferrario, M.; Giribono, A.; Marocchino, A.; Pompili, R.; Scifo, J.; Shpakov, V.; Vaccarezza, C.; Villa, F.; Mostacci, A.; Bacci, A.; Rossi, A. R.; Serafini, L.; Zigler, A.

2018-05-01

Advanced diagnostics are essential tools in the development of plasma-based accelerators. The accurate measurement of the quality of beams at the exit of the plasma channel is crucial to optimize the parameters of the plasma accelerator. 6D electron beam diagnostics will be reviewed with emphasis on emittance measurement, which is particularly complex due to large energy spread and divergence of the emerging beams, and on femtosecond bunch length measurements.

Short-term bulk energy storage system scheduling for load leveling in unit commitment: modeling, optimization, and sensitivity analysis

PubMed Central

Hemmati, Reza; Saboori, Hedayat

2016-01-01

Energy storage systems (ESSs) have experienced a very rapid growth in recent years and are expected to be a promising tool in order to improving power system reliability and being economically efficient. The ESSs possess many potential benefits in various areas in the electric power systems. One of the main benefits of an ESS, especially a bulk unit, relies on smoothing the load pattern by decreasing on-peak and increasing off-peak loads, known as load leveling. These devices require new methods and tools in order to model and optimize their effects in the power system studies. In this respect, this paper will model bulk ESSs based on the several technical characteristics, introduce the proposed model in the thermal unit commitment (UC) problem, and analyze it with respect to the various sensitive parameters. The technical limitations of the thermal units and transmission network constraints are also considered in the model. The proposed model is a Mixed Integer Linear Programming (MILP) which can be easily solved by strong commercial solvers (for instance CPLEX) and it is appropriate to be used in the practical large scale networks. The results of implementing the proposed model on a test system reveal that proper load leveling through optimum storage scheduling leads to considerable operation cost reduction with respect to the storage system characteristics. PMID:27222741

Short-term bulk energy storage system scheduling for load leveling in unit commitment: modeling, optimization, and sensitivity analysis.

PubMed

Hemmati, Reza; Saboori, Hedayat

2016-05-01

Energy storage systems (ESSs) have experienced a very rapid growth in recent years and are expected to be a promising tool in order to improving power system reliability and being economically efficient. The ESSs possess many potential benefits in various areas in the electric power systems. One of the main benefits of an ESS, especially a bulk unit, relies on smoothing the load pattern by decreasing on-peak and increasing off-peak loads, known as load leveling. These devices require new methods and tools in order to model and optimize their effects in the power system studies. In this respect, this paper will model bulk ESSs based on the several technical characteristics, introduce the proposed model in the thermal unit commitment (UC) problem, and analyze it with respect to the various sensitive parameters. The technical limitations of the thermal units and transmission network constraints are also considered in the model. The proposed model is a Mixed Integer Linear Programming (MILP) which can be easily solved by strong commercial solvers (for instance CPLEX) and it is appropriate to be used in the practical large scale networks. The results of implementing the proposed model on a test system reveal that proper load leveling through optimum storage scheduling leads to considerable operation cost reduction with respect to the storage system characteristics.

3Drefine: an interactive web server for efficient protein structure refinement.

PubMed

Bhattacharya, Debswapna; Nowotny, Jackson; Cao, Renzhi; Cheng, Jianlin

2016-07-08

3Drefine is an interactive web server for consistent and computationally efficient protein structure refinement with the capability to perform web-based statistical and visual analysis. The 3Drefine refinement protocol utilizes iterative optimization of hydrogen bonding network combined with atomic-level energy minimization on the optimized model using a composite physics and knowledge-based force fields for efficient protein structure refinement. The method has been extensively evaluated on blind CASP experiments as well as on large-scale and diverse benchmark datasets and exhibits consistent improvement over the initial structure in both global and local structural quality measures. The 3Drefine web server allows for convenient protein structure refinement through a text or file input submission, email notification, provided example submission and is freely available without any registration requirement. The server also provides comprehensive analysis of submissions through various energy and statistical feedback and interactive visualization of multiple refined models through the JSmol applet that is equipped with numerous protein model analysis tools. The web server has been extensively tested and used by many users. As a result, the 3Drefine web server conveniently provides a useful tool easily accessible to the community. The 3Drefine web server has been made publicly available at the URL: http://sysbio.rnet.missouri.edu/3Drefine/. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Comparison of Artificial Immune System and Particle Swarm Optimization Techniques for Error Optimization of Machine Vision Based Tool Movements

NASA Astrophysics Data System (ADS)

Mahapatra, Prasant Kumar; Sethi, Spardha; Kumar, Amod

2015-10-01

In conventional tool positioning technique, sensors embedded in the motion stages provide the accurate tool position information. In this paper, a machine vision based system and image processing technique for motion measurement of lathe tool from two-dimensional sequential images captured using charge coupled device camera having a resolution of 250 microns has been described. An algorithm was developed to calculate the observed distance travelled by the tool from the captured images. As expected, error was observed in the value of the distance traversed by the tool calculated from these images. Optimization of errors due to machine vision system, calibration, environmental factors, etc. in lathe tool movement was carried out using two soft computing techniques, namely, artificial immune system (AIS) and particle swarm optimization (PSO). The results show better capability of AIS over PSO.

Effects of Different Cutting Patterns and Experimental Conditions on the Performance of a Conical Drag Tool

NASA Astrophysics Data System (ADS)

Copur, Hanifi; Bilgin, Nuh; Balci, Cemal; Tumac, Deniz; Avunduk, Emre

2017-06-01

This study aims at determining the effects of single-, double-, and triple-spiral cutting patterns; the effects of tool cutting speeds on the experimental scale; and the effects of the method of yield estimation on cutting performance by performing a set of full-scale linear cutting tests with a conical cutting tool. The average and maximum normal, cutting and side forces; specific energy; yield; and coarseness index are measured and compared in each cutting pattern at a 25-mm line spacing, at varying depths of cut per revolution, and using two cutting speeds on five different rock samples. The results indicate that the optimum specific energy decreases by approximately 25% with an increasing number of spirals from the single- to the double-spiral cutting pattern for the hard rocks, whereas generally little effect was observed for the soft- and medium-strength rocks. The double-spiral cutting pattern appeared to be more effective than the single- or triple-spiral cutting pattern and had an advantage of lower side forces. The tool cutting speed had no apparent effect on the cutting performance. The estimation of the specific energy by the yield based on the theoretical swept area was not significantly different from that estimated by the yield based on the muck weighing, especially for the double- and triple-spiral cutting patterns and with the optimum ratio of line spacing to depth of cut per revolution. This study also demonstrated that the cutterhead and mechanical miner designs, semi-theoretical deterministic computer simulations and empirical performance predictions and optimization models should be based on realistic experimental simulations. Studies should be continued to obtain more reliable results by creating a larger database of laboratory tests and field performance records for mechanical miners using drag tools.

Optimized theory for simple and molecular fluids.

PubMed

Marucho, M; Montgomery Pettitt, B

2007-03-28

An optimized closure approximation for both simple and molecular fluids is presented. A smooth interpolation between Perkus-Yevick and hypernetted chain closures is optimized by minimizing the free energy self-consistently with respect to the interpolation parameter(s). The molecular version is derived from a refinement of the method for simple fluids. In doing so, a method is proposed which appropriately couples an optimized closure with the variant of the diagrammatically proper integral equation recently introduced by this laboratory [K. M. Dyer et al., J. Chem. Phys. 123, 204512 (2005)]. The simplicity of the expressions involved in this proposed theory has allowed the authors to obtain an analytic expression for the approximate excess chemical potential. This is shown to be an efficient tool to estimate, from first principles, the numerical value of the interpolation parameters defining the aforementioned closure. As a preliminary test, representative models for simple fluids and homonuclear diatomic Lennard-Jones fluids were analyzed, obtaining site-site correlation functions in excellent agreement with simulation data.

DEVELOPMENT OF A SOFTWARE DESIGN TOOL FOR HYBRID SOLAR-GEOTHERMAL HEAT PUMP SYSTEMS IN HEATING- AND COOLING-DOMINATED BUILDINGS

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

Yavuzturk, C. C.; Chiasson, A. D.; Filburn, T. P.

This project provides an easy-to-use, menu-driven, software tool for designing hybrid solar-geothermal heat pump systems (GHP) for both heating- and cooling-dominated buildings. No such design tool currently exists. In heating-dominated buildings, the design approach takes advantage of glazed solar collectors to effectively balance the annual thermal loads on the ground with renewable solar energy. In cooling-dominated climates, the design approach takes advantage of relatively low-cost, unglazed solar collectors as the heat rejecting component. The primary benefit of hybrid GHPs is the reduced initial cost of the ground heat exchanger (GHX). Furthermore, solar thermal collectors can be used to balance themore » ground loads over the annual cycle, thus making the GHX fully sustainable; in heating-dominated buildings, the hybrid energy source (i.e., solar) is renewable, in contrast to a typical fossil fuel boiler or electric resistance as the hybrid component; in cooling-dominated buildings, use of unglazed solar collectors as a heat rejecter allows for passive heat rejection, in contrast to a cooling tower that consumes a significant amount of energy to operate, and hybrid GHPs can expand the market by allowing reduced GHX footprint in both heating- and cooling-dominated climates. The design tool allows for the straight-forward design of innovative GHP systems that currently pose a significant design challenge. The project lays the foundations for proper and reliable design of hybrid GHP systems, overcoming a series of difficult and cumbersome steps without the use of a system simulation approach, and without an automated optimization scheme. As new technologies and design concepts emerge, sophisticated design tools and methodologies must accompany them and be made usable for practitioners. Lack of reliable design tools results in reluctance of practitioners to implement more complex systems. A menu-driven software tool for the design of hybrid solar GHP systems is provided that is based on mathematically robust, validated models. An automated optimization tool is used to balance ground loads and incorporated into the simulation engine. With knowledge of the building loads, thermal properties of the ground, the borehole heat exchanger configuration, the heat pump peak hourly and seasonal COP for heating and cooling, the critical heat pump design entering fluid temperature, and the thermal performance of a solar collector, the total GHX length can be calculated along with the area of a supplemental solar collector array and the corresponding reduced GHX length. An economic analysis module allows for the calculation of the lowest capital cost combination of solar collector area and GHX length. ACKNOWLEDGMENTS This project was funded by the United States Department of Energy DOE-DE-FOA-0000116, Recovery Act Geothermal Technologies Program: Ground Source Heat Pumps. The lead contractor, The University of Hartford, was supported by The University of Dayton, and the Oak Ridge National Laboratories. All funding and support for this project as well as contributions of graduate and undergraduate students from the contributing institutions are gratefully acknowledged.« less

Geomega: MEGAlib's Uniform Geometry and Detector Description Tool for Geant3, MGGPOD, and Geant4

NASA Astrophysics Data System (ADS)

Zoglauer, Andreas C.; Andritschke, R.; Schopper, F.; Wunderer, C. B.

2006-09-01

The Medium Energy Gamma-ray Astronomy library MEGAlib is a set of software tools for the analysis of low to medium energy gamma-ray telescopes, especially Compton telescopes. It comprises all necessary data analysis steps from simulation/measurements via event reconstruction to image reconstruction and enables detailed performance assessments. In the energy range of Compton telescopes (with energy deposits from a few keV up to hundreds of MeV), the Geant Monte-Carlo software packages (Geant3 with its MGGPOD extension as well as Geant4) are widely used. Since each tool has its unique advantages, MEGAlib contains a geometry and detector description library, called Geomega, which allows to use those tools in a uniform way. It incorporates the versatile 3D display facilities available within the ROOT libraries. The same geometry, material, trigger, and detector description can be used for all simulation tools as well as for the later event analysis in the MEGAlib framework. This is done by converting the MEGAlib geometry into the Geant3 or MGGPOD format or directly linking the Geomega library into Geant4. The geometry description can handle most (and can be extended to handle all) volumes common to Geant3, Geant4 and ROOT. In Geomega a list of features is implemented which are especially useful for optimizing detector geometries: It allows to define constants, can handle mathematical operations, enables volume scaling, checks for overlaps of detector volumes, does mass calculations, etc. Used in combination with MEGAlib, Geomega enables discretization, application of detector noise, thresholds, various trigger conditions, defective pixels, etc. The highly modular and completely object-oriented library is written in C++ and based on ROOT. It has been originally developed for the tracking Compton scattering and Pair creation telescope MEGA and has been successfully applied to a wide variety of telescopes, such as ACT, NuSTAR, or GRI.

The system design and performance test of hybrid vertical axis wind turbine

NASA Astrophysics Data System (ADS)

Dwiyantoro, Bambang Arip; Suphandani, Vivien

2017-04-01

Vertical axis wind turbine is a tool that is being developed to generate energy from wind. One cause is still little use of wind energy is the design of wind turbines that are less precise. Therefore in this study will be developed the system design of hybrid vertical axis wind turbine and tested performance with experimental methods. The design of hybrid turbine based on a straight bladed Darrieus turbine along with a double step Savonius turbine. The method used to design wind turbines is by studying literature, analyzing the critical parts of a wind turbine and the structure of the optimal design. Wind turbine prototype of the optimal design characteristic tests in the wind tunnel experimentally by varying the speed of the wind. From the experimental results show that the greater the wind speed, the greater the wind turbine rotation and torque is raised. The hybrid vertical axis wind turbine has much better self-starting and better conversion efficiency.

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.

Patient-specific dosimetric endpoints based treatment plan quality control in radiotherapy.

PubMed

Song, Ting; Staub, David; Chen, Mingli; Lu, Weiguo; Tian, Zhen; Jia, Xun; Li, Yongbao; Zhou, Linghong; Jiang, Steve B; Gu, Xuejun

2015-11-07

In intensity modulated radiotherapy (IMRT), the optimal plan for each patient is specific due to unique patient anatomy. To achieve such a plan, patient-specific dosimetric goals reflecting each patient's unique anatomy should be defined and adopted in the treatment planning procedure for plan quality control. This study is to develop such a personalized treatment plan quality control tool by predicting patient-specific dosimetric endpoints (DEs). The incorporation of patient specific DEs is realized by a multi-OAR geometry-dosimetry model, capable of predicting optimal DEs based on the individual patient's geometry. The overall quality of a treatment plan is then judged with a numerical treatment plan quality indicator and characterized as optimal or suboptimal. Taking advantage of clinically available prostate volumetric modulated arc therapy (VMAT) treatment plans, we built and evaluated our proposed plan quality control tool. Using our developed tool, six of twenty evaluated plans were identified as sub-optimal plans. After plan re-optimization, these suboptimal plans achieved better OAR dose sparing without sacrificing the PTV coverage, and the dosimetric endpoints of the re-optimized plans agreed well with the model predicted values, which validate the predictability of the proposed tool. In conclusion, the developed tool is able to accurately predict optimally achievable DEs of multiple OARs, identify suboptimal plans, and guide plan optimization. It is a useful tool for achieving patient-specific treatment plan quality control.

A test of the optimality approach to modelling canopy properties and CO2 uptake by natural vegetation.

PubMed

Schymanski, Stanislaus J; Roderick, Michael L; Sivapalan, Murugesu; Hutley, Lindsay B; Beringer, Jason

2007-12-01

Photosynthesis provides plants with their main building material, carbohydrates, and with the energy necessary to thrive and prosper in their environment. We expect, therefore, that natural vegetation would evolve optimally to maximize its net carbon profit (NCP), the difference between carbon acquired by photosynthesis and carbon spent on maintenance of the organs involved in its uptake. We modelled N(CP) for an optimal vegetation for a site in the wet-dry tropics of north Australia based on this hypothesis and on an ecophysiological gas exchange and photosynthesis model, and compared the modelled CO2 fluxes and canopy properties with observations from the site. The comparison gives insights into theoretical and real controls on gas exchange and canopy structure, and supports the optimality approach for the modelling of gas exchange of natural vegetation. The main advantage of the optimality approach we adopt is that no assumptions about the particular vegetation of a site are required, making it a very powerful tool for predicting vegetation response to long-term climate or land use change.

Surveying implicit solvent models for estimating small molecule absolute hydration free energies

PubMed Central

Knight, Jennifer L.

2011-01-01

Implicit solvent models are powerful tools in accounting for the aqueous environment at a fraction of the computational expense of explicit solvent representations. Here, we compare the ability of common implicit solvent models (TC, OBC, OBC2, GBMV, GBMV2, GBSW, GBSW/MS, GBSW/MS2 and FACTS) to reproduce experimental absolute hydration free energies for a series of 499 small neutral molecules that are modeled using AMBER/GAFF parameters and AM1-BCC charges. Given optimized surface tension coefficients for scaling the surface area term in the nonpolar contribution, most implicit solvent models demonstrate reasonable agreement with extensive explicit solvent simulations (average difference 1.0-1.7 kcal/mol and R2=0.81-0.91) and with experimental hydration free energies (average unsigned errors=1.1-1.4 kcal/mol and R2=0.66-0.81). Chemical classes of compounds are identified that need further optimization of their ligand force field parameters and others that require improvement in the physical parameters of the implicit solvent models themselves. More sophisticated nonpolar models are also likely necessary to more effectively represent the underlying physics of solvation and take the quality of hydration free energies estimated from implicit solvent models to the next level. PMID:21735452

Optimizing the ASC WAN: evaluating network performance tools for comparing transport protocols.

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

Lydick, Christopher L.

2007-07-01

The Advanced Simulation & Computing Wide Area Network (ASC WAN), which is a high delay-bandwidth network connection between US Department of Energy National Laboratories, is constantly being examined and evaluated for efficiency. One of the current transport-layer protocols which is used, TCP, was developed for traffic demands which are different from that on the ASC WAN. The Stream Control Transport Protocol (SCTP), on the other hand, has shown characteristics which make it more appealing to networks such as these. Most important, before considering a replacement for TCP on any network, a testing tool that performs well against certain criteria needsmore » to be found. In order to try to find such a tool, two popular networking tools (Netperf v.2.4.3 & v.2.4.6 (OpenSS7 STREAMS), and Iperf v.2.0.6) were tested. These tools implement both TCP and SCTP and were evaluated using four metrics: (1) How effectively can the tool reach a throughput near the bandwidth? (2) How much of the CPU does the tool utilize during operation? (3) Is the tool freely and widely available? And, (4) Is the tool actively developed? Following the analysis of those tools, this paper goes further into explaining some recommendations and ideas for future work.« less

Evolutionary algorithm based optimization of hydraulic machines utilizing a state-of-the-art block coupled CFD solver and parametric geometry and mesh generation tools

NASA Astrophysics Data System (ADS)

S, Kyriacou; E, Kontoleontos; S, Weissenberger; L, Mangani; E, Casartelli; I, Skouteropoulou; M, Gattringer; A, Gehrer; M, Buchmayr

2014-03-01

An efficient hydraulic optimization procedure, suitable for industrial use, requires an advanced optimization tool (EASY software), a fast solver (block coupled CFD) and a flexible geometry generation tool. EASY optimization software is a PCA-driven metamodel-assisted Evolutionary Algorithm (MAEA (PCA)) that can be used in both single- (SOO) and multiobjective optimization (MOO) problems. In MAEAs, low cost surrogate evaluation models are used to screen out non-promising individuals during the evolution and exclude them from the expensive, problem specific evaluation, here the solution of Navier-Stokes equations. For additional reduction of the optimization CPU cost, the PCA technique is used to identify dependences among the design variables and to exploit them in order to efficiently drive the application of the evolution operators. To further enhance the hydraulic optimization procedure, a very robust and fast Navier-Stokes solver has been developed. This incompressible CFD solver employs a pressure-based block-coupled approach, solving the governing equations simultaneously. This method, apart from being robust and fast, also provides a big gain in terms of computational cost. In order to optimize the geometry of hydraulic machines, an automatic geometry and mesh generation tool is necessary. The geometry generation tool used in this work is entirely based on b-spline curves and surfaces. In what follows, the components of the tool chain are outlined in some detail and the optimization results of hydraulic machine components are shown in order to demonstrate the performance of the presented optimization procedure.

Monitoring Ligand-Activated Protein-Protein Interactions Using Bioluminescent Resonance Energy Transfer (BRET) Assay.

PubMed

Coriano, Carlos; Powell, Emily; Xu, Wei

2016-01-01

The bioluminescent resonance energy transfer (BRET) assay has been extensively used in cell-based and in vivo imaging systems for detecting protein-protein interactions in the native environment of living cells. These protein-protein interactions are essential for the functional response of many signaling pathways to environmental chemicals. BRET has been used as a toxicological tool for identifying chemicals that either induce or inhibit these protein-protein interactions. This chapter focuses on describing the toxicological applications of BRET and its optimization as a high-throughput detection system in live cells. Here we review the construction of BRET fusion proteins, describe the BRET methodology, and outline strategies to overcome obstacles that may arise. Furthermore, we describe the advantage of BRET over other resonance energy transfer methods for monitoring protein-protein interactions.

ToTem: a tool for variant calling pipeline optimization.

PubMed

Tom, Nikola; Tom, Ondrej; Malcikova, Jitka; Pavlova, Sarka; Kubesova, Blanka; Rausch, Tobias; Kolarik, Miroslav; Benes, Vladimir; Bystry, Vojtech; Pospisilova, Sarka

2018-06-26

High-throughput bioinformatics analyses of next generation sequencing (NGS) data often require challenging pipeline optimization. The key problem is choosing appropriate tools and selecting the best parameters for optimal precision and recall. Here we introduce ToTem, a tool for automated pipeline optimization. ToTem is a stand-alone web application with a comprehensive graphical user interface (GUI). ToTem is written in Java and PHP with an underlying connection to a MySQL database. Its primary role is to automatically generate, execute and benchmark different variant calling pipeline settings. Our tool allows an analysis to be started from any level of the process and with the possibility of plugging almost any tool or code. To prevent an over-fitting of pipeline parameters, ToTem ensures the reproducibility of these by using cross validation techniques that penalize the final precision, recall and F-measure. The results are interpreted as interactive graphs and tables allowing an optimal pipeline to be selected, based on the user's priorities. Using ToTem, we were able to optimize somatic variant calling from ultra-deep targeted gene sequencing (TGS) data and germline variant detection in whole genome sequencing (WGS) data. ToTem is a tool for automated pipeline optimization which is freely available as a web application at  https://totem.software .

Optimal visual-haptic integration with articulated tools.

PubMed

Takahashi, Chie; Watt, Simon J

2017-05-01

When we feel and see an object, the nervous system integrates visual and haptic information optimally, exploiting the redundancy in multiple signals to estimate properties more precisely than is possible from either signal alone. We examined whether optimal integration is similarly achieved when using articulated tools. Such tools (tongs, pliers, etc) are a defining characteristic of human hand function, but complicate the classical sensory 'correspondence problem' underlying multisensory integration. Optimal integration requires establishing the relationship between signals acquired by different sensors (hand and eye) and, therefore, in fundamentally unrelated units. The system must also determine when signals refer to the same property of the world-seeing and feeling the same thing-and only integrate those that do. This could be achieved by comparing the pattern of current visual and haptic input to known statistics of their normal relationship. Articulated tools disrupt this relationship, however, by altering the geometrical relationship between object properties and hand posture (the haptic signal). We examined whether different tool configurations are taken into account in visual-haptic integration. We indexed integration by measuring the precision of size estimates, and compared our results to optimal predictions from a maximum-likelihood integrator. Integration was near optimal, independent of tool configuration/hand posture, provided that visual and haptic signals referred to the same object in the world. Thus, sensory correspondence was determined correctly (trial-by-trial), taking tool configuration into account. This reveals highly flexible multisensory integration underlying tool use, consistent with the brain constructing internal models of tools' properties.

Trades Between Opposition and Conjunction Class Trajectories for Early Human Missions to Mars

NASA Technical Reports Server (NTRS)

Mattfeld, Bryan; Stromgren, Chel; Shyface, Hilary; Komar, David R.; Cirillo, William; Goodliff, Kandyce

2014-01-01

Candidate human missions to Mars, including NASA's Design Reference Architecture 5.0, have focused on conjunction-class missions with long crewed durations and minimum energy trajectories to reduce total propellant requirements and total launch mass. However, in order to progressively reduce risk and gain experience in interplanetary mission operations, it may be desirable that initial human missions to Mars, whether to the surface or to Mars orbit, have shorter total crewed durations and minimal stay times at the destination. Opposition-class missions require larger total energy requirements relative to conjunction-class missions but offer the potential for much shorter mission durations, potentially reducing risk and overall systems performance requirements. This paper will present a detailed comparison of conjunction-class and opposition-class human missions to Mars vicinity with a focus on how such missions could be integrated into the initial phases of a Mars exploration campaign. The paper will present the results of a trade study that integrates trajectory/propellant analysis, element design, logistics and sparing analysis, and risk assessment to produce a comprehensive comparison of opposition and conjunction exploration mission constructs. Included in the trade study is an assessment of the risk to the crew and the trade offs between the mission duration and element, logistics, and spares mass. The analysis of the mission trade space was conducted using four simulation and analysis tools developed by NASA. Trajectory analyses for Mars destination missions were conducted using VISITOR (Versatile ImpulSive Interplanetary Trajectory OptimizeR), an in-house tool developed by NASA Langley Research Center. Architecture elements were evaluated using EXploration Architecture Model for IN-space and Earth-to-orbit (EXAMINE), a parametric modeling tool that generates exploration architectures through an integrated systems model. Logistics analysis was conducted using NASA's Human Exploration Logistics Model (HELM), and sparing allocation predictions were generated via the Exploration Maintainability Analysis Tool (EMAT), which is a probabilistic simulation engine that evaluates trades in spacecraft reliability and sparing requirements based on spacecraft system maintainability and reparability.

Application of characteristic time concepts for hydraulic fracture configuration design, control, and optimization

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

Advani, S.H.; Lee, T.S.; Moon, H.

1992-10-01

The analysis of pertinent energy components or affiliated characteristic times for hydraulic stimulation processes serves as an effective tool for fracture configuration designs optimization, and control. This evaluation, in conjunction with parametric sensitivity studies, provides a rational base for quantifying dominant process mechanisms and the roles of specified reservoir properties relative to controllable hydraulic fracture variables for a wide spectrum of treatment scenarios. Results are detailed for the following multi-task effort: (a) Application of characteristic time concept and parametric sensitivity studies for specialized fracture geometries (rectangular, penny-shaped, elliptical) and three-layered elliptic crack models (in situ stress, elastic moduli, and fracturemore » toughness contrasts). (b) Incorporation of leak-off effects for models investigated in (a). (c) Simulation of generalized hydraulic fracture models and investigation of the role of controllable vaxiables and uncontrollable system properties. (d) Development of guidelines for hydraulic fracture design and optimization.« less

Application of characteristic time concepts for hydraulic fracture configuration design, control, and optimization. Final report

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

Advani, S.H.; Lee, T.S.; Moon, H.

1992-10-01

The analysis of pertinent energy components or affiliated characteristic times for hydraulic stimulation processes serves as an effective tool for fracture configuration designs optimization, and control. This evaluation, in conjunction with parametric sensitivity studies, provides a rational base for quantifying dominant process mechanisms and the roles of specified reservoir properties relative to controllable hydraulic fracture variables for a wide spectrum of treatment scenarios. Results are detailed for the following multi-task effort: (a) Application of characteristic time concept and parametric sensitivity studies for specialized fracture geometries (rectangular, penny-shaped, elliptical) and three-layered elliptic crack models (in situ stress, elastic moduli, and fracturemore » toughness contrasts). (b) Incorporation of leak-off effects for models investigated in (a). (c) Simulation of generalized hydraulic fracture models and investigation of the role of controllable vaxiables and uncontrollable system properties. (d) Development of guidelines for hydraulic fracture design and optimization.« less

Optimal design of nanoplasmonic materials using genetic algorithms as a multiparameter optimization tool.

PubMed

Yelk, Joseph; Sukharev, Maxim; Seideman, Tamar

2008-08-14

An optimal control approach based on multiple parameter genetic algorithms is applied to the design of plasmonic nanoconstructs with predetermined optical properties and functionalities. We first develop nanoscale metallic lenses that focus an incident plane wave onto a prespecified, spatially confined spot. Our results illustrate the mechanism of energy flow through wires and cavities. Next we design a periodic array of silver particles to modify the polarization of an incident, linearly polarized plane wave in a desired fashion while localizing the light in space. The results provide insight into the structural features that determine the birefringence properties of metal nanoparticles and their arrays. Of the variety of potential applications that may be envisioned, we note the design of nanoscale light sources with controllable coherence and polarization properties that could serve for coherent control of molecular, electronic, or electromechanical dynamics in the nanoscale.

Structural Design Optimization of Doubly-Fed Induction Generators Using GeneratorSE

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

Sethuraman, Latha; Fingersh, Lee J; Dykes, Katherine L

2017-11-13

A wind turbine with a larger rotor swept area can generate more electricity, however, this increases costs disproportionately for manufacturing, transportation, and installation. This poster presents analytical models for optimizing doubly-fed induction generators (DFIGs), with the objective of reducing the costs and mass of wind turbine drivetrains. The structural design for the induction machine includes models for the casing, stator, rotor, and high-speed shaft developed within the DFIG module in the National Renewable Energy Laboratory's wind turbine sizing tool, GeneratorSE. The mechanical integrity of the machine is verified by examining stresses, structural deflections, and modal properties. The optimization results aremore » then validated using finite element analysis (FEA). The results suggest that our analytical model correlates with the FEA in some areas, such as radial deflection, differing by less than 20 percent. But the analytical model requires further development for axial deflections, torsional deflections, and stress calculations.« less

User's manual for the BNW-II optimization code for dry/wet-cooled power plants

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

Braun, D.J.; Bamberger, J.A.; Braun, D.J.

1978-05-01

The User's Manual describes how to operate BNW-II, a computer code developed by the Pacific Northwest Laboratory (PNL) as a part of its activities under the Department of Energy (DOE) Dry Cooling Enhancement Program. The computer program offers a comprehensive method of evaluating the cost savings potential of dry/wet-cooled heat rejection systems. Going beyond simple ''figure-of-merit'' cooling tower optimization, this method includes such items as the cost of annual replacement capacity, and the optimum split between plant scale-up and replacement capacity, as well as the purchase and operating costs of all major heat rejection components. Hence the BNW-II code ismore » a useful tool for determining potential cost savings of new dry/wet surfaces, new piping, or other components as part of an optimized system for a dry/wet-cooled plant.« less

Verification of a rapid mooring and foundation design tool

DOE PAGES

Weller, Sam D.; Hardwick, Jon; Gomez, Steven; ...

2018-02-15

Marine renewable energy devices require mooring and foundation systems that suitable in terms of device operation and are also robust and cost effective. In the initial stages of mooring and foundation development a large number of possible configuration permutations exist. Filtering of unsuitable designs is possible using information specific to the deployment site (i.e. bathymetry, environmental conditions) and device (i.e. mooring and/or foundation system role and cable connection requirements). The identification of a final solution requires detailed analysis, which includes load cases based on extreme environmental statistics following certification guidance processes. Static and/or quasi-static modelling of the mooring and/or foundationmore » system serves as an intermediate design filtering stage enabling dynamic time-domain analysis to be focused on a small number of potential configurations. Mooring and foundation design is therefore reliant on logical decision making throughout this stage-gate process. The open-source DTOcean (Optimal Design Tools for Ocean Energy Arrays) Tool includes a mooring and foundation module, which automates the configuration selection process for fixed and floating wave and tidal energy devices. As far as the authors are aware, this is one of the first tools to be developed for the purpose of identifying potential solutions during the initial stages of marine renewable energy design. While the mooring and foundation module does not replace a full design assessment, it provides in addition to suitable configuration solutions, assessments in terms of reliability, economics and environmental impact. This article provides insight into the solution identification approach used by the module and features the verification of both the mooring system calculations and the foundation design using commercial software. Several case studies are investigated: a floating wave energy converter and several anchoring systems. It is demonstrated that the mooring and foundation module is able to provide device and/or site developers with rapid mooring and foundation design solutions to appropriate design criteria.« less

Verification of a rapid mooring and foundation design tool

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

Weller, Sam D.; Hardwick, Jon; Gomez, Steven

Marine renewable energy devices require mooring and foundation systems that suitable in terms of device operation and are also robust and cost effective. In the initial stages of mooring and foundation development a large number of possible configuration permutations exist. Filtering of unsuitable designs is possible using information specific to the deployment site (i.e. bathymetry, environmental conditions) and device (i.e. mooring and/or foundation system role and cable connection requirements). The identification of a final solution requires detailed analysis, which includes load cases based on extreme environmental statistics following certification guidance processes. Static and/or quasi-static modelling of the mooring and/or foundationmore » system serves as an intermediate design filtering stage enabling dynamic time-domain analysis to be focused on a small number of potential configurations. Mooring and foundation design is therefore reliant on logical decision making throughout this stage-gate process. The open-source DTOcean (Optimal Design Tools for Ocean Energy Arrays) Tool includes a mooring and foundation module, which automates the configuration selection process for fixed and floating wave and tidal energy devices. As far as the authors are aware, this is one of the first tools to be developed for the purpose of identifying potential solutions during the initial stages of marine renewable energy design. While the mooring and foundation module does not replace a full design assessment, it provides in addition to suitable configuration solutions, assessments in terms of reliability, economics and environmental impact. This article provides insight into the solution identification approach used by the module and features the verification of both the mooring system calculations and the foundation design using commercial software. Several case studies are investigated: a floating wave energy converter and several anchoring systems. It is demonstrated that the mooring and foundation module is able to provide device and/or site developers with rapid mooring and foundation design solutions to appropriate design criteria.« less

Cast Off expansion plan by rapid improvement through Optimization tool design, Tool Parameters and using Six Sigma’s ECRS Technique

NASA Astrophysics Data System (ADS)

Gopalakrishnan, T.; Saravanan, R.

2017-03-01

Powerful management concepts step-up the quality of the product, time saving in producing the product thereby increase the production rate, improves tools and techniques, work culture, work place and employee motivation and morale. In this paper discussed about the case study of optimizing the tool design, tool parameters to cast off expansion plan according ECRS technique. The proposed designs and optimal tool parameters yielded best results and meet the customer demand without expansion plan. Hence the work yielded huge savings of money (direct and indirect cost), time and improved the motivation and more of employees significantly.

Hybrid Model-Based and Data-Driven Fault Detection and Diagnostics for Commercial Buildings

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

Frank, Stephen; Heaney, Michael; Jin, Xin

Commercial buildings often experience faults that produce undesirable behavior in building systems. Building faults waste energy, decrease occupants' comfort, and increase operating costs. Automated fault detection and diagnosis (FDD) tools for buildings help building owners discover and identify the root causes of faults in building systems, equipment, and controls. Proper implementation of FDD has the potential to simultaneously improve comfort, reduce energy use, and narrow the gap between actual and optimal building performance. However, conventional rule-based FDD requires expensive instrumentation and valuable engineering labor, which limit deployment opportunities. This paper presents a hybrid, automated FDD approach that combines building energymore » models and statistical learning tools to detect and diagnose faults noninvasively, using minimal sensors, with little customization. We compare and contrast the performance of several hybrid FDD algorithms for a small security building. Our results indicate that the algorithms can detect and diagnose several common faults, but more work is required to reduce false positive rates and improve diagnosis accuracy.« less

Hybrid Model-Based and Data-Driven Fault Detection and Diagnostics for Commercial Buildings: Preprint

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

Frank, Stephen; Heaney, Michael; Jin, Xin

Commercial buildings often experience faults that produce undesirable behavior in building systems. Building faults waste energy, decrease occupants' comfort, and increase operating costs. Automated fault detection and diagnosis (FDD) tools for buildings help building owners discover and identify the root causes of faults in building systems, equipment, and controls. Proper implementation of FDD has the potential to simultaneously improve comfort, reduce energy use, and narrow the gap between actual and optimal building performance. However, conventional rule-based FDD requires expensive instrumentation and valuable engineering labor, which limit deployment opportunities. This paper presents a hybrid, automated FDD approach that combines building energymore » models and statistical learning tools to detect and diagnose faults noninvasively, using minimal sensors, with little customization. We compare and contrast the performance of several hybrid FDD algorithms for a small security building. Our results indicate that the algorithms can detect and diagnose several common faults, but more work is required to reduce false positive rates and improve diagnosis accuracy.« less

Modeling and Advanced Control for Sustainable Process ...

EPA Pesticide Factsheets

This book chapter introduces a novel process systems engineering framework that integrates process control with sustainability assessment tools for the simultaneous evaluation and optimization of process operations. The implemented control strategy consists of a biologically-inspired, multi-agent-based method. The sustainability and performance assessment of process operating points is carried out using the U.S. E.P.A.’s GREENSCOPE assessment tool that provides scores for the selected economic, material management, environmental and energy indicators. The indicator results supply information on whether the implementation of the controller is moving the process towards a more sustainable operation. The effectiveness of the proposed framework is illustrated through a case study of a continuous bioethanol fermentation process whose dynamics are characterized by steady-state multiplicity and oscillatory behavior. This book chapter contribution demonstrates the application of novel process control strategies for sustainability by increasing material management, energy efficiency, and pollution prevention, as needed for SHC Sustainable Uses of Wastes and Materials Management.

Development of Regional Excel-Based Stormwater/Nutrient BMP Optimization Tool (Opti-Tool)

EPA Science Inventory

During 2014, EPA Region 1 contracted with Tetra Tech, Inc. to work with a regional technical Advisory Committee to develop an Excel-based stormwater/nutrient BMP optimization tool (Opti-Tool) using regional precipitation data and regionally calibrated BMP performance data from UN...

Annual Report: Carbon Capture Simulation Initiative (CCSI) (30 September 2013)

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

Miller, David C.; Syamlal, Madhava; Cottrell, Roger

2013-09-30

The Carbon Capture Simulation Initiative (CCSI) is a partnership among national laboratories, industry and academic institutions that is developing and deploying state-of-the-art computational modeling and simulation tools to accelerate the commercialization of carbon capture technologies from discovery to development, demonstration, and ultimately the widespread deployment to hundreds of power plants. The CCSI Toolset will provide end users in industry with a comprehensive, integrated suite of scientifically validated models, with uncertainty quantification (UQ), optimization, risk analysis and decision making capabilities. The CCSI Toolset incorporates commercial and open-source software currently in use by industry and is also developing new software tools asmore » necessary to fill technology gaps identified during execution of the project. Ultimately, the CCSI Toolset will (1) enable promising concepts to be more quickly identified through rapid computational screening of devices and processes; (2) reduce the time to design and troubleshoot new devices and processes; (3) quantify the technical risk in taking technology from laboratory-scale to commercial-scale; and (4) stabilize deployment costs more quickly by replacing some of the physical operational tests with virtual power plant simulations. CCSI is led by the National Energy Technology Laboratory (NETL) and leverages the Department of Energy (DOE) national laboratories’ core strengths in modeling and simulation, bringing together the best capabilities at NETL, Los Alamos National Laboratory (LANL), Lawrence Berkeley National Laboratory (LBNL), Lawrence Livermore National Laboratory (LLNL), and Pacific Northwest National Laboratory (PNNL). The CCSI’s industrial partners provide representation from the power generation industry, equipment manufacturers, technology providers and engineering and construction firms. The CCSI’s academic participants (Carnegie Mellon University, Princeton University, West Virginia University, Boston University and the University of Texas at Austin) bring unparalleled expertise in multiphase flow reactors, combustion, process synthesis and optimization, planning and scheduling, and process control techniques for energy processes. During Fiscal Year (FY) 13, CCSI announced the initial release of its first set of computational tools and models during the October 2012 meeting of its Industry Advisory Board. This initial release led to five companies licensing the CCSI Toolset under a Test and Evaluation Agreement this year. By the end of FY13, the CCSI Technical Team had completed development of an updated suite of computational tools and models. The list below summarizes the new and enhanced toolset components that were released following comprehensive testing during October 2013. 1. FOQUS. Framework for Optimization and Quantification of Uncertainty and Sensitivity. Package includes: FOQUS Graphic User Interface (GUI), simulation-based optimization engine, Turbine Client, and heat integration capabilities. There is also an updated simulation interface and new configuration GUI for connecting Aspen Plus or Aspen Custom Modeler (ACM) simulations to FOQUS and the Turbine Science Gateway. 2. A new MFIX-based Computational Fluid Dynamics (CFD) model to predict particle attrition. 3. A new dynamic reduced model (RM) builder, which generates computationally efficient RMs of the behavior of a dynamic system. 4. A completely re-written version of the algebraic surrogate model builder for optimization (ALAMO). The new version is several orders of magnitude faster than the initial release and eliminates the MATLAB dependency. 5. A new suite of high resolution filtered models for the hydrodynamics associated with horizontal cylindrical objects in a flow path. 6. The new Turbine Science Gateway (Cluster), which supports FOQUS for running multiple simulations for optimization or UQ using a local computer or cluster. 7. A new statistical tool (BSS-ANOVA-UQ) for calibration and validation of CFD models. 8. A new basic data submodel in Aspen Plus format for a representative high viscosity capture solvent, 2-MPZ system. 9. An updated RM tool for CFD (REVEAL) that can create a RM from MFIX. A new lightweight, stand-alone version will be available in late 2013. 10. An updated RM integration tool to convert the RM from REVEAL into a CAPE-OPEN or ACM model for use in a process simulator. 11. An updated suite of unified steady-state and dynamic process models for solid sorbent carbon capture included bubbling fluidized bed and moving bed reactors. 12. An updated and unified set of compressor models including steady-state design point model and dynamic model with surge detection. 13. A new framework for the synthesis and optimization of coal oxycombustion power plants using advanced optimization algorithms. This release focuses on modeling and optimization of a cryogenic air separation unit (ASU). 14. A new technical risk model in spreadsheet format. 15. An updated version of the sorbent kinetic/equilibrium model for parameter estimation for the 1st generation sorbent model. 16. An updated process synthesis superstructure model to determine optimal process configurations utilizing surrogate models from ALAMO for adsorption and regeneration in a solid sorbent process. 17. Validation models for NETL Carbon Capture Unit utilizing sorbent AX. Additional validation models will be available for sorbent 32D in 2014. 18. An updated hollow fiber membrane model and system example for carbon capture. 19. An updated reference power plant model in Thermoflex that includes additional steam extraction and reinjection points to enable heat integration module. 20. An updated financial risk model in spreadsheet format.« less

Optimal GENCO bidding strategy

NASA Astrophysics Data System (ADS)

Gao, Feng

Electricity industries worldwide are undergoing a period of profound upheaval. The conventional vertically integrated mechanism is being replaced by a competitive market environment. Generation companies have incentives to apply novel technologies to lower production costs, for example: Combined Cycle units. Economic dispatch with Combined Cycle units becomes a non-convex optimization problem, which is difficult if not impossible to solve by conventional methods. Several techniques are proposed here: Mixed Integer Linear Programming, a hybrid method, as well as Evolutionary Algorithms. Evolutionary Algorithms share a common mechanism, stochastic searching per generation. The stochastic property makes evolutionary algorithms robust and adaptive enough to solve a non-convex optimization problem. This research implements GA, EP, and PS algorithms for economic dispatch with Combined Cycle units, and makes a comparison with classical Mixed Integer Linear Programming. The electricity market equilibrium model not only helps Independent System Operator/Regulator analyze market performance and market power, but also provides Market Participants the ability to build optimal bidding strategies based on Microeconomics analysis. Supply Function Equilibrium (SFE) is attractive compared to traditional models. This research identifies a proper SFE model, which can be applied to a multiple period situation. The equilibrium condition using discrete time optimal control is then developed for fuel resource constraints. Finally, the research discusses the issues of multiple equilibria and mixed strategies, which are caused by the transmission network. Additionally, an advantage of the proposed model for merchant transmission planning is discussed. A market simulator is a valuable training and evaluation tool to assist sellers, buyers, and regulators to understand market performance and make better decisions. A traditional optimization model may not be enough to consider the distributed, large-scale, and complex energy market. This research compares the performance and searching paths of different artificial life techniques such as Genetic Algorithm (GA), Evolutionary Programming (EP), and Particle Swarm (PS), and look for a proper method to emulate Generation Companies' (GENCOs) bidding strategies. After deregulation, GENCOs face risk and uncertainty associated with the fast-changing market environment. A profit-based bidding decision support system is critical for GENCOs to keep a competitive position in the new environment. Most past research do not pay special attention to the piecewise staircase characteristic of generator offer curves. This research proposes an optimal bidding strategy based on Parametric Linear Programming. The proposed algorithm is able to handle actual piecewise staircase energy offer curves. The proposed method is then extended to incorporate incomplete information based on Decision Analysis. Finally, the author develops an optimal bidding tool (GenBidding) and applies it to the RTS96 test system.

Metabolic engineering with systems biology tools to optimize production of prokaryotic secondary metabolites.

PubMed

Kim, Hyun Uk; Charusanti, Pep; Lee, Sang Yup; Weber, Tilmann

2016-08-27

Covering: 2012 to 2016Metabolic engineering using systems biology tools is increasingly applied to overproduce secondary metabolites for their potential industrial production. In this Highlight, recent relevant metabolic engineering studies are analyzed with emphasis on host selection and engineering approaches for the optimal production of various prokaryotic secondary metabolites: native versus heterologous hosts (e.g., Escherichia coli) and rational versus random approaches. This comparative analysis is followed by discussions on systems biology tools deployed in optimizing the production of secondary metabolites. The potential contributions of additional systems biology tools are also discussed in the context of current challenges encountered during optimization of secondary metabolite production.

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.

Adaptive smart simulator for characterization and MPPT construction of PV array

NASA Astrophysics Data System (ADS)

Ouada, Mehdi; Meridjet, Mohamed Salah; Dib, Djalel

2016-07-01

Partial shading conditions are among the most important problems in large photovoltaic array. Many works of literature are interested in modeling, control and optimization of photovoltaic conversion of solar energy under partial shading conditions, The aim of this study is to build a software simulator similar to hard simulator and to produce a shading pattern of the proposed photovoltaic array in order to use the delivered information to obtain an optimal configuration of the PV array and construct MPPT algorithm. Graphical user interfaces (Matlab GUI) are built using a developed script, this tool is easy to use, simple, and has a rapid of responsiveness, the simulator supports large array simulations that can be interfaced with MPPT and power electronic converters.

Optimal design of active EMC filters

NASA Astrophysics Data System (ADS)

Chand, B.; Kut, T.; Dickmann, S.

2013-07-01

A recent trend in automotive industry is adding electrical drive systems to conventional drives. The electrification allows an expansion of energy sources and provides great opportunities for environmental friendly mobility. The electrical powertrain and its components can also cause disturbances which couple into nearby electronic control units and communication cables. Therefore the communication can be degraded or even permanently disrupted. To minimize these interferences, different approaches are possible. One possibility is to use EMC filters. However, the diversity of filters is very large and the determination of an appropriate filter for each application is time-consuming. Therefore, the filter design is determined by using a simulation tool including an effective optimization algorithm. This method leads to improvements in terms of weight, volume and cost.

Development of an operation strategy for hydrogen production using solar PV energy based on fluid dynamic aspects

NASA Astrophysics Data System (ADS)

Amores, Ernesto; Rodríguez, Jesús; Oviedo, José; de Lucas-Consuegra, Antonio

2017-06-01

Alkaline water electrolysis powered by renewable energy sources is one of the most promising strategies for environmentally friendly hydrogen production. However, wind and solar energy sources are highly dependent on weather conditions. As a result, power fluctuations affect the electrolyzer and cause several negative effects. Considering these limiting effects which reduce the water electrolysis efficiency, a novel operation strategy is proposed in this study. It is based on pumping the electrolyte according to the current density supplied by a solar PV module, in order to achieve the suitable fluid dynamics conditions in an electrolysis cell. To this aim, a mathematical model including the influence of electrode-membrane distance, temperature and electrolyte flow rate has been developed and used as optimization tool. The obtained results confirm the convenience of the selected strategy, especially when the electrolyzer is powered by renewable energies.

Intelligent Controls for Net-Zero Energy Buildings

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

Li, Haorong; Cho, Yong; Peng, Dongming

2011-10-30

The goal of this project is to develop and demonstrate enabling technologies that can empower homeowners to convert their homes into net-zero energy buildings in a cost-effective manner. The project objectives and expected outcomes are as follows: • To develop rapid and scalable building information collection and modeling technologies that can obtain and process “as-built” building information in an automated or semiautomated manner. • To identify low-cost measurements and develop low-cost virtual sensors that can monitor building operations in a plug-n-play and low-cost manner. • To integrate and demonstrate low-cost building information modeling (BIM) technologies. • To develop decision supportmore » tools which can empower building owners to perform energy auditing and retrofit analysis. • To develop and demonstrate low-cost automated diagnostics and optimal control technologies which can improve building energy efficiency in a continual manner.« less

An optimization model for energy generation and distribution in a dynamic facility

NASA Technical Reports Server (NTRS)

Lansing, F. L.

1981-01-01

An analytical model is described using linear programming for the optimum generation and distribution of energy demands among competing energy resources and different economic criteria. The model, which will be used as a general engineering tool in the analysis of the Deep Space Network ground facility, considers several essential decisions for better design and operation. The decisions sought for the particular energy application include: the optimum time to build an assembly of elements, inclusion of a storage medium of some type, and the size or capacity of the elements that will minimize the total life-cycle cost over a given number of years. The model, which is structured in multiple time divisions, employ the decomposition principle for large-size matrices, the branch-and-bound method in mixed-integer programming, and the revised simplex technique for efficient and economic computer use.

Optimising energy recovery and use of chemicals, resources and materials in modern waste-to-energy plants.

PubMed

De Greef, J; Villani, K; Goethals, J; Van Belle, H; Van Caneghem, J; Vandecasteele, C

2013-11-01

Due to ongoing developments in the EU waste policy, Waste-to-Energy (WtE) plants are to be optimized beyond current acceptance levels. In this paper, a non-exhaustive overview of advanced technical improvements is presented and illustrated with facts and figures from state-of-the-art combustion plants for municipal solid waste (MSW). Some of the data included originate from regular WtE plant operation - before and after optimisation - as well as from defined plant-scale research. Aspects of energy efficiency and (re-)use of chemicals, resources and materials are discussed and support, in light of best available techniques (BAT), the idea that WtE plant performance still can be improved significantly, without direct need for expensive techniques, tools or re-design. In first instance, diagnostic skills and a thorough understanding of processes and operations allow for reclaiming the silent optimisation potential. Copyright © 2013 Elsevier Ltd. All rights reserved.

A coarse-grained model for DNA origami.

PubMed

Reshetnikov, Roman V; Stolyarova, Anastasia V; Zalevsky, Arthur O; Panteleev, Dmitry Y; Pavlova, Galina V; Klinov, Dmitry V; Golovin, Andrey V; Protopopova, Anna D

2018-02-16

Modeling tools provide a valuable support for DNA origami design. However, current solutions have limited application for conformational analysis of the designs. In this work we present a tool for a thorough study of DNA origami structure and dynamics. The tool is based on a novel coarse-grained model dedicated to geometry optimization and conformational analysis of DNA origami. We explored the ability of the model to predict dynamic behavior, global shapes, and fine details of two single-layer systems designed in hexagonal and square lattices using atomic force microscopy, Förster resonance energy transfer spectroscopy, and all-atom molecular dynamic simulations for validation of the results. We also examined the performance of the model for multilayer systems by simulation of DNA origami with published cryo-electron microscopy and atomic force microscopy structures. A good agreement between the simulated and experimental data makes the model suitable for conformational analysis of DNA origami objects. The tool is available at http://vsb.fbb.msu.ru/cosm as a web-service and as a standalone version.

A coarse-grained model for DNA origami

PubMed Central

Stolyarova, Anastasia V; Zalevsky, Arthur O; Panteleev, Dmitry Y; Pavlova, Galina V; Klinov, Dmitry V; Golovin, Andrey V; Protopopova, Anna D

2018-01-01

Abstract Modeling tools provide a valuable support for DNA origami design. However, current solutions have limited application for conformational analysis of the designs. In this work we present a tool for a thorough study of DNA origami structure and dynamics. The tool is based on a novel coarse-grained model dedicated to geometry optimization and conformational analysis of DNA origami. We explored the ability of the model to predict dynamic behavior, global shapes, and fine details of two single-layer systems designed in hexagonal and square lattices using atomic force microscopy, Förster resonance energy transfer spectroscopy, and all-atom molecular dynamic simulations for validation of the results. We also examined the performance of the model for multilayer systems by simulation of DNA origami with published cryo-electron microscopy and atomic force microscopy structures. A good agreement between the simulated and experimental data makes the model suitable for conformational analysis of DNA origami objects. The tool is available at http://vsb.fbb.msu.ru/cosm as a web-service and as a standalone version. PMID:29267876

Energy consumption estimation of an OMAP-based Android operating system

NASA Astrophysics Data System (ADS)

González, Gabriel; Juárez, Eduardo; Castro, Juan José; Sanz, César

2011-05-01

System-level energy optimization of battery-powered multimedia embedded systems has recently become a design goal. The poor operational time of multimedia terminals makes computationally demanding applications impractical in real scenarios. For instance, the so-called smart-phones are currently unable to remain in operation longer than several hours. The OMAP3530 processor basically consists of two processing cores, a General Purpose Processor (GPP) and a Digital Signal Processor (DSP). The former, an ARM Cortex-A8 processor, is aimed to run a generic Operating System (OS) while the latter, a DSP core based on the C64x+, has architecture optimized for video processing. The BeagleBoard, a commercial prototyping board based on the OMAP processor, has been used to test the Android Operating System and measure its performance. The board has 128 MB of SDRAM external memory, 256 MB of Flash external memory and several interfaces. Note that the clock frequency of the ARM and DSP OMAP cores is 600 MHz and 430 MHz, respectively. This paper describes the energy consumption estimation of the processes and multimedia applications of an Android v1.6 (Donut) OS on the OMAP3530-Based BeagleBoard. In addition, tools to communicate the two processing cores have been employed. A test-bench to profile the OS resource usage has been developed. As far as the energy estimates concern, the OMAP processor energy consumption model provided by the manufacturer has been used. The model is basically divided in two energy components. The former, the baseline core energy, describes the energy consumption that is independent of any chip activity. The latter, the module active energy, describes the energy consumed by the active modules depending on resource usage.

Improving Energy Efficiency in CNC Machining

NASA Astrophysics Data System (ADS)

Pavanaskar, Sushrut S.

We present our work on analyzing and improving the energy efficiency of multi-axis CNC milling process. Due to the differences in energy consumption behavior, we treat 3- and 5-axis CNC machines separately in our work. For 3-axis CNC machines, we first propose an energy model that estimates the energy requirement for machining a component on a specified 3-axis CNC milling machine. Our model makes machine-specific predictions of energy requirements while also considering the geometric aspects of the machining toolpath. Our model - and the associated software tool - facilitate direct comparison of various alternative toolpath strategies based on their energy-consumption performance. Further, we identify key factors in toolpath planning that affect energy consumption in CNC machining. We then use this knowledge to propose and demonstrate a novel toolpath planning strategy that may be used to generate new toolpaths that are inherently energy-efficient, inspired by research on digital micrography -- a form of computational art. For 5-axis CNC machines, the process planning problem consists of several sub-problems that researchers have traditionally solved separately to obtain an approximate solution. After illustrating the need to solve all sub-problems simultaneously for a truly optimal solution, we propose a unified formulation based on configuration space theory. We apply our formulation to solve a problem variant that retains key characteristics of the full problem but has lower dimensionality, allowing visualization in 2D. Given the complexity of the full 5-axis toolpath planning problem, our unified formulation represents an important step towards obtaining a truly optimal solution. With this work on the two types of CNC machines, we demonstrate that without changing the current infrastructure or business practices, machine-specific, geometry-based, customized toolpath planning can save energy in CNC machining.

Energy management system turns data into market info

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

Traynor, P.J.; Ackerman, W.J.

1996-09-01

The designers claim that Wisconsin Power & Light Co`s new energy management system is the first system of its type in the world in terms of the comprehensiveness and scope of its stored and retrievable data. Furthermore, the system`s link to the utility`s generating assets enables powerplant management to dispatch generation resources based on up-to-date unit characteristics. That means that the new system gives WP&L a competitive tool to optimize operations as well as fine-tune its EMS based on timely load and unit response information. Additionally, the EMS gives WP&L insight into the complex issues related to the unbundling ofmore » generation resources.« less

Low-energy impact resistance of graphite-epoxy plates and ALS honeycomb sandwich panels

NASA Technical Reports Server (NTRS)

Hui, David

1989-01-01

Low energy impact may be potentially dangerous for many highly optimized stiff structures. Impact by foreign objects such as birds, ice, and runways stones or dropping of tools occur frequently and the resulting damage and stress concentrations may be unacceptable from a designer's standpoint. The barely visible, yet potentially dangerous dents due to impact of foreign objects on the Advanced Launch System (ALS) structure are studied. Of particular interest is the computation of the maximum peak impact force for a given impactor mass and initial velocity. The theoretical impact forces will be compared with the experimental dropweight results for the ALS face sheets alone as well as the ALS honeycomb sandwich panels.

Optimization of turning process through the analytic flank wear modelling

NASA Astrophysics Data System (ADS)

Del Prete, A.; Franchi, R.; De Lorenzis, D.

2018-05-01

In the present work, the approach used for the optimization of the process capabilities for Oil&Gas components machining will be described. These components are machined by turning of stainless steel castings workpieces. For this purpose, a proper Design Of Experiments (DOE) plan has been designed and executed: as output of the experimentation, data about tool wear have been collected. The DOE has been designed starting from the cutting speed and feed values recommended by the tools manufacturer; the depth of cut parameter has been maintained as a constant. Wear data has been obtained by means the observation of the tool flank wear under an optical microscope: the data acquisition has been carried out at regular intervals of working times. Through a statistical data and regression analysis, analytical models of the flank wear and the tool life have been obtained. The optimization approach used is a multi-objective optimization, which minimizes the production time and the number of cutting tools used, under the constraint on a defined flank wear level. The technique used to solve the optimization problem is a Multi Objective Particle Swarm Optimization (MOPS). The optimization results, validated by the execution of a further experimental campaign, highlighted the reliability of the work and confirmed the usability of the optimized process parameters and the potential benefit for the company.

Dynamic optimization case studies in DYNOPT tool

NASA Astrophysics Data System (ADS)

Ozana, Stepan; Pies, Martin; Docekal, Tomas

2016-06-01

Dynamic programming is typically applied to optimization problems. As the analytical solutions are generally very difficult, chosen software tools are used widely. These software packages are often third-party products bound for standard simulation software tools on the market. As typical examples of such tools, TOMLAB and DYNOPT could be effectively applied for solution of problems of dynamic programming. DYNOPT will be presented in this paper due to its licensing policy (free product under GPL) and simplicity of use. DYNOPT is a set of MATLAB functions for determination of optimal control trajectory by given description of the process, the cost to be minimized, subject to equality and inequality constraints, using orthogonal collocation on finite elements method. The actual optimal control problem is solved by complete parameterization both the control and the state profile vector. It is assumed, that the optimized dynamic model may be described by a set of ordinary differential equations (ODEs) or differential-algebraic equations (DAEs). This collection of functions extends the capability of the MATLAB Optimization Tool-box. The paper will introduce use of DYNOPT in the field of dynamic optimization problems by means of case studies regarding chosen laboratory physical educational models.

Small Business Innovation Research (SBIR) Program, FY 1994. Program Solicitation 94.1, Closing Date: 14 January 1994

DTIC Science & Technology

1994-01-01

is to design and develop a diode laser and ssociated driver circuitry with i•eh peak power, high pulse repetition frequency (PRF), and good beam...Computer modeling tools shall be used to design and optimize breadboard model of a multi-terminal high speed ring bus for flight critical applications... design , fabricate, and test a fiber optic interface device which will improve coupling of high energy, pulsed lasers into commercial fiber optics at a

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

NASA Astrophysics Data System (ADS)

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

2011-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

PENTrack - a versatile Monte Carlo tool for ultracold neutron sources and experiments

NASA Astrophysics Data System (ADS)

Picker, Ruediger; Chahal, Sanmeet; Christopher, Nicolas; Losekamm, Martin; Marcellin, James; Paul, Stephan; Schreyer, Wolfgang; Yapa, Pramodh

2016-09-01

Ultracold neutrons have energies in the hundred nano eV region. They can be stored in traps for hundreds of seconds. This makes them the ideal tool to study the neutron itself. Measurements of neutron decay correlations, lifetime or electric dipole moment are ideally suited for ultracold neutrons, as well as experiments probing the neutron's gravitational levels in the earth's field. We have developed a Monte Carlo simulation tool that can serve to design and optimize these experiments, and possibly correct results: PENTrack is a C++ based simulation code that tracks neutrons, protons and electrons or atoms, as well as their spins, in gravitational and electromagnetic fields. In addition wall interactions of neutrons due to strong interaction are modeled with a Fermi-potential formalism and take surface roughness into account. The presentation will introduce the physics behind the simulation and provide examples of its application.

Modeling Methodologies for Design and Control of Solid Oxide Fuel Cell APUs

NASA Astrophysics Data System (ADS)

Pianese, C.; Sorrentino, M.

2009-08-01

Among the existing fuel cell technologies, Solid Oxide Fuel Cells (SOFC) are particularly suitable for both stationary and mobile applications, due to their high energy conversion efficiencies, modularity, high fuel flexibility, low emissions and noise. Moreover, the high working temperatures enable their use for efficient cogeneration applications. SOFCs are entering in a pre-industrial era and a strong interest for designing tools has growth in the last years. Optimal system configuration, components sizing, control and diagnostic system design require computational tools that meet the conflicting needs of accuracy, affordable computational time, limited experimental efforts and flexibility. The paper gives an overview on control-oriented modeling of SOFC at both single cell and stack level. Such an approach provides useful simulation tools for designing and controlling SOFC-APUs destined to a wide application area, ranging from automotive to marine and airplane APUs.

SPOT-A SENSOR PLACEMENT OPTIMIZATION TOOL FOR ...

EPA Pesticide Factsheets

journal article This paper presents SPOT, a Sensor Placement Optimization Tool. SPOT provides a toolkit that facilitates research in sensor placement optimization and enables the practical application of sensor placement solvers to real-world CWS design applications. This paper provides an overview of SPOT’s key features, and then illustrates how this tool can be flexibly applied to solve a variety of different types of sensor placement problems.

Using GeoRePORT to report socio-economic potential for geothermal development

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

Young, Katherine R.; Levine, Aaron

The Geothermal Resource Portfolio Optimization and Reporting Tool (GeoRePORT, http://en.openei.org/wiki/GeoRePORT) was developed for reporting resource grades and project readiness levels, providing the U.S. Department of Energy a consistent and comprehensible means of evaluating projects. The tool helps funding organizations (1) quantitatively identify barriers, (2) develop measureable goals, (3) objectively evaluate proposals, including contribution to goals, (4) monitor progress, and (5) report portfolio performance. GeoRePORT assesses three categories: geological, technical, and socio-economic. Here, we describe GeoRePORT, then focus on the socio-economic assessment and its applications for assessing deployment potential in the U.S. Socio-economic attributes include land access, permitting, transmission, and market.

Update on HCDstruct - A Tool for Hybrid Wing Body Conceptual Design and Structural Optimization

NASA Technical Reports Server (NTRS)

Gern, Frank H.

2015-01-01

HCDstruct is a Matlab® based software tool to rapidly build a finite element model for structural optimization of hybrid wing body (HWB) aircraft at the conceptual design level. The tool uses outputs from a Flight Optimization System (FLOPS) performance analysis together with a conceptual outer mold line of the vehicle, e.g. created by Vehicle Sketch Pad (VSP), to generate a set of MSC Nastran® bulk data files. These files can readily be used to perform a structural optimization and weight estimation using Nastran’s® Solution 200 multidisciplinary optimization solver. Initially developed at NASA Langley Research Center to perform increased fidelity conceptual level HWB centerbody structural analyses, HCDstruct has grown into a complete HWB structural sizing and weight estimation tool, including a fully flexible aeroelastic loads analysis. Recent upgrades to the tool include the expansion to a full wing tip-to-wing tip model for asymmetric analyses like engine out conditions and dynamic overswings, as well as a fully actuated trailing edge, featuring up to 15 independently actuated control surfaces and twin tails. Several example applications of the HCDstruct tool are presented.

Development of FAST.Farm: A New Multiphysics Engineering Tool for Wind Farm Design and Analysis: Preprint

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

Jonkman, Jason; Annoni, Jennifer; Hayman, Greg

2017-01-01

This paper presents the development of FAST.Farm, a new multiphysics tool applicable to engineering problems in research and industry involving wind farm performance and cost optimization that is needed to address the current underperformance, failures, and expenses plaguing the wind industry. Achieving wind cost-of-energy targets - which requires improvements in wind farm performance and reliability, together with reduced uncertainty and expenditures - has been eluded by the complicated nature of the wind farm design problem, especially the sophisticated interaction between atmospheric phenomena and wake dynamics and array effects. FAST.Farm aims to balance the need for accurate modeling of the relevantmore » physics for predicting power performance and loads while maintaining low computational cost to support a highly iterative and probabilistic design process and system-wide optimization. FAST.Farm makes use of FAST to model the aero-hydro-servo-elastics of distinct turbines in the wind farm, and it is based on some of the principles of the Dynamic Wake Meandering (DWM) model, but avoids many of the limitations of existing DWM implementations.« less

Characterization of Lunar Polar Illumination from a Power System Perspective

NASA Technical Reports Server (NTRS)

Fincannon, James

2008-01-01

This paper presents the results of illumination analyses for the lunar south and north pole regions obtained using an independently developed analytical tool and two types of digital elevation models (DEM). One DEM was based on radar height data from Earth observations of the lunar surface and the other was a combination of the radar data with a separate dataset generated using Clementine spacecraft stereo imagery. The analysis tool enables the assessment of illumination at most locations in the lunar polar regions for any time and any year. Maps are presented for both lunar poles for the worst case winter period (the critical power system design and planning bottleneck) and for the more favorable best case summer period. Average illumination maps are presented to help understand general topographic trends over the regions. Energy storage duration maps are presented to assist in power system design. Average illumination fraction, energy storage duration, solar/horizon terrain elevation profiles and illumination fraction profiles are presented for favorable lunar north and south pole sites which have the potential for manned or unmanned spacecraft operations. The format of the data is oriented for use by power system designers to develop mass optimized solar and energy storage systems.

Watershed Management Optimization Support Tool (WMOST) Workshop.

EPA Science Inventory

EPA's Watershed Management Optimization Support Tool (WMOST) version 2 is a decision support tool designed to facilitate integrated water management by communities at the small watershed scale. WMOST allows users to look across management options in stormwater (including green i...

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

PubMed

Salehi, Mojtaba; Bahreininejad, Ardeshir

2011-08-01

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

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

PubMed Central

Salehi, Mojtaba

2010-01-01

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

SU-E-T-278: Realization of Dose Verification Tool for IMRT Plan Based On DPM

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

Cai, Jinfeng; Cao, Ruifen; Dai, Yumei

Purpose: To build a Monte Carlo dose verification tool for IMRT Plan by implementing a irradiation source model into DPM code. Extend the ability of DPM to calculate any incident angles and irregular-inhomogeneous fields. Methods: With the virtual source and the energy spectrum which unfolded from the accelerator measurement data,combined with optimized intensity maps to calculate the dose distribution of the irradiation irregular-inhomogeneous field. The irradiation source model of accelerator was substituted by a grid-based surface source. The contour and the intensity distribution of the surface source were optimized by ARTS (Accurate/Advanced Radiotherapy System) optimization module based on the tumormore » configuration. The weight of the emitter was decided by the grid intensity. The direction of the emitter was decided by the combination of the virtual source and the emitter emitting position. The photon energy spectrum unfolded from the accelerator measurement data was adjusted by compensating the contaminated electron source. For verification, measured data and realistic clinical IMRT plan were compared with DPM dose calculation. Results: The regular field was verified by comparing with the measured data. It was illustrated that the differences were acceptable (<2% inside the field, 2–3mm in the penumbra). The dose calculation of irregular field by DPM simulation was also compared with that of FSPB (Finite Size Pencil Beam) and the passing rate of gamma analysis was 95.1% for peripheral lung cancer. The regular field and the irregular rotational field were all within the range of permitting error. The computing time of regular fields were less than 2h, and the test of peripheral lung cancer was 160min. Through parallel processing, the adapted DPM could complete the calculation of IMRT plan within half an hour. Conclusion: The adapted parallelized DPM code with irradiation source model is faster than classic Monte Carlo codes. Its computational accuracy and speed satisfy the clinical requirement, and it is expectable to be a Monte Carlo dose verification tool for IMRT Plan. Strategic Priority Research Program of the China Academy of Science(XDA03040000); National Natural Science Foundation of China (81101132)« less

Energy-Water Nexus: Balancing the Tradeoffs between Two-Level Decision Makers

DOE PAGES

Zhang, Xiaodong; Vesselinov, Velimir Valentinov

2016-09-03

Energy-water nexus has substantially increased importance in the recent years. Synergistic approaches based on systems-analysis and mathematical models are critical for helping decision makers better understand the interrelationships and tradeoffs between energy and water. In energywater nexus management, various decision makers with different goals and preferences, which are often conflicting, are involved. These decision makers may have different controlling power over the management objectives and the decisions. They make decisions sequentially from the upper level to the lower level, challenging decision making in energy-water nexus. In order to address such planning issues, a bi-level decision model is developed, which improvesmore » upon the existing studies by integration of bi-level programming into energy-water nexus management. The developed model represents a methodological contribution to the challenge of sequential decisionmaking in energy-water nexus through provision of an integrated modeling framework/tool. An interactive fuzzy optimization methodology is introduced to seek a satisfactory solution to meet the overall satisfaction of the two-level decision makers. The tradeoffs between the two-level decision makers in energy-water nexus management are effectively addressed and quantified. Application of the proposed model to a synthetic example problem has demonstrated its applicability in practical energy-water nexus management. Optimal solutions for electricity generation, fuel supply, water supply including groundwater, surface water and recycled water, capacity expansion of the power plants, and GHG emission control are generated. In conclusion, these analyses are capable of helping decision makers or stakeholders adjust their tolerances to make informed decisions to achieve the overall satisfaction of energy-water nexus management where bi-level sequential decision making process is involved.« less

Energy-Water Nexus: Balancing the Tradeoffs between Two-Level Decision Makers

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

Zhang, Xiaodong; Vesselinov, Velimir Valentinov

Energy-water nexus has substantially increased importance in the recent years. Synergistic approaches based on systems-analysis and mathematical models are critical for helping decision makers better understand the interrelationships and tradeoffs between energy and water. In energywater nexus management, various decision makers with different goals and preferences, which are often conflicting, are involved. These decision makers may have different controlling power over the management objectives and the decisions. They make decisions sequentially from the upper level to the lower level, challenging decision making in energy-water nexus. In order to address such planning issues, a bi-level decision model is developed, which improvesmore » upon the existing studies by integration of bi-level programming into energy-water nexus management. The developed model represents a methodological contribution to the challenge of sequential decisionmaking in energy-water nexus through provision of an integrated modeling framework/tool. An interactive fuzzy optimization methodology is introduced to seek a satisfactory solution to meet the overall satisfaction of the two-level decision makers. The tradeoffs between the two-level decision makers in energy-water nexus management are effectively addressed and quantified. Application of the proposed model to a synthetic example problem has demonstrated its applicability in practical energy-water nexus management. Optimal solutions for electricity generation, fuel supply, water supply including groundwater, surface water and recycled water, capacity expansion of the power plants, and GHG emission control are generated. In conclusion, these analyses are capable of helping decision makers or stakeholders adjust their tolerances to make informed decisions to achieve the overall satisfaction of energy-water nexus management where bi-level sequential decision making process is involved.« less

Additive manufacturing: Toward holistic design

DOE PAGES

Jared, Bradley H.; Aguilo, Miguel A.; Beghini, Lauren L.; ...

2017-03-18

Here, additive manufacturing offers unprecedented opportunities to design complex structures optimized for performance envelopes inaccessible under conventional manufacturing constraints. Additive processes also promote realization of engineered materials with microstructures and properties that are impossible via traditional synthesis techniques. Enthused by these capabilities, optimization design tools have experienced a recent revival. The current capabilities of additive processes and optimization tools are summarized briefly, while an emerging opportunity is discussed to achieve a holistic design paradigm whereby computational tools are integrated with stochastic process and material awareness to enable the concurrent optimization of design topologies, material constructs and fabrication processes.

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

Jared, Bradley H.; Aguilo, Miguel A.; Beghini, Lauren L.

Here, additive manufacturing offers unprecedented opportunities to design complex structures optimized for performance envelopes inaccessible under conventional manufacturing constraints. Additive processes also promote realization of engineered materials with microstructures and properties that are impossible via traditional synthesis techniques. Enthused by these capabilities, optimization design tools have experienced a recent revival. The current capabilities of additive processes and optimization tools are summarized briefly, while an emerging opportunity is discussed to achieve a holistic design paradigm whereby computational tools are integrated with stochastic process and material awareness to enable the concurrent optimization of design topologies, material constructs and fabrication processes.

Watershed Management Optimization Support Tool v3

EPA Science Inventory

The Watershed Management Optimization Support Tool (WMOST) is a decision support tool that facilitates integrated water management at the local or small watershed scale. WMOST models the environmental effects and costs of management decisions in a watershed context that is, accou...

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

Dholabhai, Pratik P., E-mail: pratik.dholabhai@asu.ed; Anwar, Shahriar, E-mail: anwar@asu.ed; Adams, James B., E-mail: jim.adams@asu.ed

Kinetic lattice Monte Carlo (KLMC) model is developed for investigating oxygen vacancy diffusion in praseodymium-doped ceria. The current approach uses a database of activation energies for oxygen vacancy migration, calculated using first-principles, for various migration pathways in praseodymium-doped ceria. Since the first-principles calculations revealed significant vacancy-vacancy repulsion, we investigate the importance of that effect by conducting simulations with and without a repulsive interaction. Initially, as dopant concentrations increase, vacancy concentration and thus conductivity increases. However, at higher concentrations, vacancies interfere and repel one another, and dopants trap vacancies, creating a 'traffic jam' that decreases conductivity, which is consistent with themore » experimental findings. The modeled effective activation energy for vacancy migration slightly increased with increasing dopant concentration in qualitative agreement with the experiment. The current methodology comprising a blend of first-principle calculations and KLMC model provides a very powerful fundamental tool for predicting the optimal dopant concentration in ceria related materials. -- graphical abstract: Ionic conductivity in praseodymium doped ceria as a function of dopant concentration calculated using the kinetic lattice Monte Carlo vacancy-repelling model, which predicts the optimal composition for achieving maximum conductivity. Display Omitted Research highlights: {yields} KLMC method calculates the accurate time-dependent diffusion of oxygen vacancies. {yields} KLMC-VR model predicts a dopant concentration of {approx}15-20% to be optimal in PDC. {yields} At higher dopant concentration, vacancies interfere and repel one another, and dopants trap vacancies. {yields} Activation energy for vacancy migration increases as a function of dopant content« less

Fine-Tuning the Energy Levels of a Nonfullerene Small-Molecule Acceptor to Achieve a High Short-Circuit Current and a Power Conversion Efficiency over 12% in Organic Solar Cells.

PubMed

Kan, Bin; Zhang, Jiangbin; Liu, Feng; Wan, Xiangjian; Li, Chenxi; Ke, Xin; Wang, Yunchuang; Feng, Huanran; Zhang, Yamin; Long, Guankui; Friend, Richard H; Bakulin, Artem A; Chen, Yongsheng

2018-01-01

Organic solar cell optimization requires careful balancing of current-voltage output of the materials system. Here, such optimization using ultrafast spectroscopy as a tool to optimize the material bandgap without altering ultrafast photophysics is reported. A new acceptor-donor-acceptor (A-D-A)-type small-molecule acceptor NCBDT is designed by modification of the D and A units of NFBDT. Compared to NFBDT, NCBDT exhibits upshifted highest occupied molecular orbital (HOMO) energy level mainly due to the additional octyl on the D unit and downshifted lowest unoccupied molecular orbital (LUMO) energy level due to the fluorination of A units. NCBDT has a low optical bandgap of 1.45 eV which extends the absorption range toward near-IR region, down to ≈860 nm. However, the 60 meV lowered LUMO level of NCBDT hardly changes the V oc level, and the elevation of the NCBDT HOMO does not have a substantial influence on the photophysics of the materials. Thus, for both NCBDT- and NFBDT-based systems, an unusually slow (≈400 ps) but ultimately efficient charge generation mediated by interfacial charge-pair states is observed, followed by effective charge extraction. As a result, the PBDB-T:NCBDT devices demonstrate an impressive power conversion efficiency over 12%-among the best for solution-processed organic solar cells. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Watershed Management Optimization Support Tool (WMOST) ...

EPA Pesticide Factsheets

EPA's Watershed Management Optimization Support Tool (WMOST) version 2 is a decision support tool designed to facilitate integrated water management by communities at the small watershed scale. WMOST allows users to look across management options in stormwater (including green infrastructure), wastewater, drinking water, and land conservation programs to find the least cost solutions. The pdf version of these presentations accompany the recorded webinar with closed captions to be posted on the WMOST web page. The webinar was recorded at the time a training workshop took place for EPA's Watershed Management Optimization Support Tool (WMOST, v2).

A Comparative Analysis of Life-Cycle Assessment Tools for ...

EPA Pesticide Factsheets

We identified and evaluated five life-cycle assessment tools that community decision makers can use to assess the environmental and economic impacts of end-of-life (EOL) materials management options. The tools evaluated in this report are waste reduction mode (WARM), municipal solid waste-decision support tool (MSW-DST), solid waste optimization life-cycle framework (SWOLF), environmental assessment system for environmental technologies (EASETECH), and waste and resources assessment for the environment (WRATE). WARM, MSW-DST, and SWOLF were developed for US-specific materials management strategies, while WRATE and EASETECH were developed for European-specific conditions. All of the tools (with the exception of WARM) allow specification of a wide variety of parameters (e.g., materials composition and energy mix) to a varying degree, thus allowing users to model specific EOL materials management methods even outside the geographical domain they are originally intended for. The flexibility to accept user-specified input for a large number of parameters increases the level of complexity and the skill set needed for using these tools. The tools were evaluated and compared based on a series of criteria, including general tool features, the scope of the analysis (e.g., materials and processes included), and the impact categories analyzed (e.g., climate change, acidification). A series of scenarios representing materials management problems currently relevant to c

Data and Tools | Energy Analysis | NREL

Science.gov Websites

and Tools Energy Analysis Data and Tools NREL develops energy analysis data and tools to assess collections. Data Products Technology and Performance Analysis Tools Energy Systems Analysis Tools Economic and Financial Analysis Tools

Contingency Contractor Optimization Phase 3 Sustainment Third-Party Software List - Contingency Contractor Optimization Tool - Prototype

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

Durfee, Justin David; Frazier, Christopher Rawls; Bandlow, Alisa

2016-05-01

The Contingency Contractor Optimization Tool - Prototype (CCOT-P) requires several third-party software packages. These are documented below for each of the CCOT-P elements: client, web server, database server, solver, web application and polling application.

Meeting China's electricity needs through clean energy sources: A 2030 low-carbon energy roadmap

NASA Astrophysics Data System (ADS)

Hu, Zheng

China is undergoing rapid economic development that generates significant increase in energy demand, primarily for electricity. Energy supply in China is heavily relying on coal, which leads to high carbon emissions. This dissertation explores opportunities for meeting China's growing power demand through clean energy sources. The utilization of China's clean energy sources as well as demand-side management is still at the initial phase. Therefore, development of clean energy sources would require substantial government support in order to be competitive in the market. One of the widely used means to consider clean energy in power sector supplying is Integrated Resource Strategic Planning, which aims to minimize the long term electricity costs while screening various power supply options for the power supply and demand analysis. The IRSP tool tackles the energy problem from the perspective of power sector regulators, and provides different policy scenarios to quantify the impacts of combined incentives. Through three scenario studies, Business as Usual, High Renewable, and Renewable and Demand Side Management, this dissertation identifies the optimized scenario for China to achieve the clean energy target of 2030. The scenarios are assessed through energy, economics, environment, and equity dimensions.

Aiding Design of Wave Energy Converters via Computational Simulations

NASA Astrophysics Data System (ADS)

Jebeli Aqdam, Hejar; Ahmadi, Babak; Raessi, Mehdi; Tootkaboni, Mazdak

2015-11-01

With the increasing interest in renewable energy sources, wave energy converters will continue to gain attention as a viable alternative to current electricity production methods. It is therefore crucial to develop computational tools for the design and analysis of wave energy converters. A successful design requires balance between the design performance and cost. Here an analytical solution is used for the approximate analysis of interactions between a flap-type wave energy converter (WEC) and waves. The method is verified using other flow solvers and experimental test cases. Then the model is used in conjunction with a powerful heuristic optimization engine, Charged System Search (CSS) to explore the WEC design space. CSS is inspired by charged particles behavior. It searches the design space by considering candidate answers as charged particles and moving them based on the Coulomb's laws of electrostatics and Newton's laws of motion to find the global optimum. Finally the impacts of changes in different design parameters on the power takeout of the superior WEC designs are investigated. National Science Foundation, CBET-1236462.

Assessment and Verification of SLS Block 1-B Exploration Upper Stage State and Stage Disposal Performance

NASA Technical Reports Server (NTRS)

Patrick, Sean; Oliver, Emerson

2018-01-01

One of the SLS Navigation System's key performance requirements is a constraint on the payload system's delta-v allocation to correct for insertion errors due to vehicle state uncertainty at payload separation. The SLS navigation team has developed a Delta-Delta-V analysis approach to assess the effect on trajectory correction maneuver (TCM) design needed to correct for navigation errors. This approach differs from traditional covariance analysis based methods and makes no assumptions with regard to the propagation of the state dynamics. This allows for consideration of non-linearity in the propagation of state uncertainties. The Delta-Delta-V analysis approach re-optimizes perturbed SLS mission trajectories by varying key mission states in accordance with an assumed state error. The state error is developed from detailed vehicle 6-DOF Monte Carlo analysis or generated using covariance analysis. These perturbed trajectories are compared to a nominal trajectory to determine necessary TCM design. To implement this analysis approach, a tool set was developed which combines the functionality of a 3-DOF trajectory optimization tool, Copernicus, and a detailed 6-DOF vehicle simulation tool, Marshall Aerospace Vehicle Representation in C (MAVERIC). In addition to delta-v allocation constraints on SLS navigation performance, SLS mission requirement dictate successful upper stage disposal. Due to engine and propellant constraints, the SLS Exploration Upper Stage (EUS) must dispose into heliocentric space by means of a lunar fly-by maneuver. As with payload delta-v allocation, upper stage disposal maneuvers must place the EUS on a trajectory that maximizes the probability of achieving a heliocentric orbit post Lunar fly-by considering all sources of vehicle state uncertainty prior to the maneuver. To ensure disposal, the SLS navigation team has developed an analysis approach to derive optimal disposal guidance targets. This approach maximizes the state error covariance prior to the maneuver to develop and re-optimize a nominal disposal maneuver (DM) target that, if achieved, would maximize the potential for successful upper stage disposal. For EUS disposal analysis, a set of two tools was developed. The first considers only the nominal pre-disposal maneuver state, vehicle constraints, and an a priori estimate of the state error covariance. In the analysis, the optimal nominal disposal target is determined. This is performed by re-formulating the trajectory optimization to consider constraints on the eigenvectors of the error ellipse applied to the nominal trajectory. A bisection search methodology is implemented in the tool to refine these dispersions resulting in the maximum dispersion feasible for successful disposal via lunar fly-by. Success is defined based on the probability that the vehicle will not impact the lunar surface and will achieve a characteristic energy (C3) relative to the Earth such that it is no longer in the Earth-Moon system. The second tool propagates post-disposal maneuver states to determine the success of disposal for provided trajectory achieved states. This is performed using the optimized nominal target within the 6-DOF vehicle simulation. This paper will discuss the application of the Delta-Delta-V analysis approach for performance evaluation as well as trajectory re-optimization so as to demonstrate the system's capability in meeting performance constraints. Additionally, further discussion of the implementation of assessing disposal analysis will be provided.

Computer codes for checking, plotting and processing of neutron cross-section covariance data and their application

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

Sartori, E.; Roussin, R.W.

This paper presents a brief review of computer codes concerned with checking, plotting, processing and using of covariances of neutron cross-section data. It concentrates on those available from the computer code information centers of the United States and the OECD/Nuclear Energy Agency. Emphasis will be placed also on codes using covariances for specific applications such as uncertainty analysis, data adjustment and data consistency analysis. Recent evaluations contain neutron cross section covariance information for all isotopes of major importance for technological applications of nuclear energy. It is therefore important that the available software tools needed for taking advantage of this informationmore » are widely known as hey permit the determination of better safety margins and allow the optimization of more economic, I designs of nuclear energy systems.« less

Accelerating the weighted histogram analysis method by direct inversion in the iterative subspace.

PubMed

Zhang, Cheng; Lai, Chun-Liang; Pettitt, B Montgomery

The weighted histogram analysis method (WHAM) for free energy calculations is a valuable tool to produce free energy differences with the minimal errors. Given multiple simulations, WHAM obtains from the distribution overlaps the optimal statistical estimator of the density of states, from which the free energy differences can be computed. The WHAM equations are often solved by an iterative procedure. In this work, we use a well-known linear algebra algorithm which allows for more rapid convergence to the solution. We find that the computational complexity of the iterative solution to WHAM and the closely-related multiple Bennett acceptance ratio (MBAR) method can be improved by using the method of direct inversion in the iterative subspace. We give examples from a lattice model, a simple liquid and an aqueous protein solution.

Watershed Management Optimization Support Tool (WMOST) v3: User Guide

EPA Science Inventory

The Watershed Management Optimization Support Tool (WMOST) is a decision support tool that facilitates integrated water management at the local or small watershed scale. WMOST models the environmental effects and costs of management decisions in a watershed context that is, accou...

Watershed Management Optimization Support Tool (WMOST) v3: Theoretical Documentation

EPA Science Inventory

The Watershed Management Optimization Support Tool (WMOST) is a decision support tool that facilitates integrated water management at the local or small watershed scale. WMOST models the environmental effects and costs of management decisions in a watershed context, accounting fo...

Watershed Management Optimization Support Tool (WMOST) v2: Theoretical Documentation

EPA Science Inventory

The Watershed Management Optimization Support Tool (WMOST) is a decision support tool that evaluates the relative cost-effectiveness of management practices at the local or watershed scale. WMOST models the environmental effects and costs of management decisions in a watershed c...

Illumina Production Sequencing at the DOE Joint Genome Institute - Workflow and Optimizations

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

Tarver, Angela; Fern, Alison; Diego, Matthew San

2010-06-18

The U.S. Department of Energy (DOE) Joint Genome Institute?s (JGI) Production Sequencing group is committed to the generation of high-quality genomic DNA sequence to support the DOE mission areas of renewable energy generation, global carbon management, and environmental characterization and clean-up. Within the JGI?s Production Sequencing group, the Illumina Genome Analyzer pipeline has been established as one of three sequencing platforms, along with Roche/454 and ABI/Sanger. Optimization of the Illumina pipeline has been ongoing with the aim of continual process improvement of the laboratory workflow. These process improvement projects are being led by the JGI?s Process Optimization, Sequencing Technologies, Instrumentation&more » Engineering, and the New Technology Production groups. Primary focus has been on improving the procedural ergonomics and the technicians? operating environment, reducing manually intensive technician operations with different tools, reducing associated production costs, and improving the overall process and generated sequence quality. The U.S. DOE JGI was established in 1997 in Walnut Creek, CA, to unite the expertise and resources of five national laboratories? Lawrence Berkeley, Lawrence Livermore, Los Alamos, Oak Ridge, and Pacific Northwest ? along with HudsonAlpha Institute for Biotechnology. JGI is operated by the University of California for the U.S. DOE.« less

Optimisation of cascaded Yb fiber amplifier chains using numerical-modelling

NASA Astrophysics Data System (ADS)

He, F.; Price, J. H.; Vu, K. T.; Malinowski, A.; Sahu, J. K.; Richardson, D. J.

2006-12-01

We show that it is possible to adapt existing software packages developed originally for modeling telecommunication devices and systems to reliably predict and optimize the performance of high-power Ytterbium-doped fiber amplifier and laser systems. The ready availability of a flexible, user-friendly design tool should be of considerable practical interest to scientists and engineers working with this important new laser technology since Ytterbium amplifier and amplifier cascades are often difficult to optimize experimentally due to the three-level nature of the Ytterbium laser transition. As examples of the utility and accuracy of the software, as well as the complexity of the systems and amplifier properties that can be successfully modeled, we present a comparison of experimental and theoretical results for individual core and cladding pumped amplifiers, and also for an ultra-short pulse four-stage amplifier system optimized both to provide a broad gain bandwidth and to minimize nonlinear effects. We also show how high energy 100 ns pulses with complex user definable temporal profiles can be created in a gain-saturated amplifier by suitable pre-shaping of the low-energy input pulses. Furthermore, with appropriate modifications the same software package can be applied to fiber amplifiers based on other rare-earth elements and glass hosts.

Simultaneous optimization of micro-heliostat geometry and field layout using a genetic algorithm

NASA Astrophysics Data System (ADS)

Lazardjani, Mani Yousefpour; Kronhardt, Valentina; Dikta, Gerhard; Göttsche, Joachim

2016-05-01

A new optimization tool for micro-heliostat (MH) geometry and field layout is presented. The method intends simultaneous performance improvement and cost reduction through iteration of heliostat geometry and field layout parameters. This tool was developed primarily for the optimization of a novel micro-heliostat concept, which was developed at Solar-Institut Jülich (SIJ). However, the underlying approach for the optimization can be used for any heliostat type. During the optimization the performance is calculated using the ray-tracing tool SolCal. The costs of the heliostats are calculated by use of a detailed cost function. A genetic algorithm is used to change heliostat geometry and field layout in an iterative process. Starting from an initial setup, the optimization tool generates several configurations of heliostat geometries and field layouts. For each configuration a cost-performance ratio is calculated. Based on that, the best geometry and field layout can be selected in each optimization step. In order to find the best configuration, this step is repeated until no significant improvement in the results is observed.

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.

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.

Uncertainty-based simulation-optimization using Gaussian process emulation: Application to coastal groundwater management

NASA Astrophysics Data System (ADS)

Rajabi, Mohammad Mahdi; Ketabchi, Hamed

2017-12-01

Combined simulation-optimization (S/O) schemes have long been recognized as a valuable tool in coastal groundwater management (CGM). However, previous applications have mostly relied on deterministic seawater intrusion (SWI) simulations. This is a questionable simplification, knowing that SWI models are inevitably prone to epistemic and aleatory uncertainty, and hence a management strategy obtained through S/O without consideration of uncertainty may result in significantly different real-world outcomes than expected. However, two key issues have hindered the use of uncertainty-based S/O schemes in CGM, which are addressed in this paper. The first issue is how to solve the computational challenges resulting from the need to perform massive numbers of simulations. The second issue is how the management problem is formulated in presence of uncertainty. We propose the use of Gaussian process (GP) emulation as a valuable tool in solving the computational challenges of uncertainty-based S/O in CGM. We apply GP emulation to the case study of Kish Island (located in the Persian Gulf) using an uncertainty-based S/O algorithm which relies on continuous ant colony optimization and Monte Carlo simulation. In doing so, we show that GP emulation can provide an acceptable level of accuracy, with no bias and low statistical dispersion, while tremendously reducing the computational time. Moreover, five new formulations for uncertainty-based S/O are presented based on concepts such as energy distances, prediction intervals and probabilities of SWI occurrence. We analyze the proposed formulations with respect to their resulting optimized solutions, the sensitivity of the solutions to the intended reliability levels, and the variations resulting from repeated optimization runs.

Optimization of Compressor Mounting Bracket of a Passenger Car

NASA Astrophysics Data System (ADS)

Kalsi, Sachin; Singh, Daljeet; Saini, J. S.

2018-05-01

In the present work, the CAE tools are used for the optimization of the compressor mounting bracket used in an automobile. Both static and dynamic analysis is done for the bracket. With the objective to minimize the mass and increase the stiffness of the bracket, the new design is optimized using shape and topology optimization techniques. The optimized design given by CAE tool is then validated experimentally. The new design results in lower level of vibrations, contribute to lower mass along with lesser cost which is effective in air conditioning system as well as the efficiency of a vehicle. The results given by CAE tool had a very good correlation with the experimental results.

Energy benchmarking in wastewater treatment plants: the importance of site operation and layout.

PubMed

Belloir, C; Stanford, C; Soares, A

2015-01-01

Energy benchmarking is a powerful tool in the optimization of wastewater treatment plants (WWTPs) in helping to reduce costs and greenhouse gas emissions. Traditionally, energy benchmarking methods focused solely on reporting electricity consumption, however, recent developments in this area have led to the inclusion of other types of energy, including electrical, manual, chemical and mechanical consumptions that can be expressed in kWh/m3. In this study, two full-scale WWTPs were benchmarked, both incorporated preliminary, secondary (oxidation ditch) and tertiary treatment processes, Site 1 also had an additional primary treatment step. The results indicated that Site 1 required 2.32 kWh/m3 against 0.98 kWh/m3 for Site 2. Aeration presented the highest energy consumption for both sites with 2.08 kWh/m3 required for Site 1 and 0.91 kWh/m3 in Site 2. The mechanical energy represented the second biggest consumption for Site 1 (9%, 0.212 kWh/m3) and chemical input was significant in Site 2 (4.1%, 0.026 kWh/m3). The analysis of the results indicated that Site 2 could be optimized by constructing a primary settling tank that would reduce the biochemical oxygen demand, total suspended solids and NH4 loads to the oxidation ditch by 55%, 75% and 12%, respectively, and at the same time reduce the aeration requirements by 49%. This study demonstrated that the effectiveness of the energy benchmarking exercise in identifying the highest energy-consuming assets, nevertheless it points out the need to develop a holistic overview of the WWTP and the need to include parameters such as effluent quality, site operation and plant layout to allow adequate benchmarking.

Computational tool for optimizing the essential oils utilization in inhibiting the bacterial growth

PubMed Central

El-Attar, Noha E; Awad, Wael A

2017-01-01

Day after day, the importance of relying on nature in many fields such as food, medical, pharmaceutical industries, and others is increasing. Essential oils (EOs) are considered as one of the most significant natural products for use as antimicrobials, antioxidants, antitumorals, and anti-inflammatories. Optimizing the usage of EOs is a big challenge faced by the scientific researchers because of the complexity of chemical composition of every EO, in addition to the difficulties to determine the best in inhibiting the bacterial activity. The goal of this article is to present a new computational tool based on two methodologies: reduction by using rough sets and optimization with particle swarm optimization. The developed tool dubbed as Essential Oil Reduction and Optimization Tool is applied on 24 types of EOs that have been tested toward 17 different species of bacteria. PMID:28919787

Postprocessing of docked protein-ligand complexes using implicit solvation models.

PubMed

Lindström, Anton; Edvinsson, Lotta; Johansson, Andreas; Andersson, C David; Andersson, Ida E; Raubacher, Florian; Linusson, Anna

2011-02-28

Molecular docking plays an important role in drug discovery as a tool for the structure-based design of small organic ligands for macromolecules. Possible applications of docking are identification of the bioactive conformation of a protein-ligand complex and the ranking of different ligands with respect to their strength of binding to a particular target. We have investigated the effect of implicit water on the postprocessing of binding poses generated by molecular docking using MM-PB/GB-SA (molecular mechanics Poisson-Boltzmann and generalized Born surface area) methodology. The investigation was divided into three parts: geometry optimization, pose selection, and estimation of the relative binding energies of docked protein-ligand complexes. Appropriate geometry optimization afforded more accurate binding poses for 20% of the complexes investigated. The time required for this step was greatly reduced by minimizing the energy of the binding site using GB solvation models rather than minimizing the entire complex using the PB model. By optimizing the geometries of docking poses using the GB(HCT+SA) model then calculating their free energies of binding using the PB implicit solvent model, binding poses similar to those observed in crystal structures were obtained. Rescoring of these poses according to their calculated binding energies resulted in improved correlations with experimental binding data. These correlations could be further improved by applying the postprocessing to several of the most highly ranked poses rather than focusing exclusively on the top-scored pose. The postprocessing protocol was successfully applied to the analysis of a set of Factor Xa inhibitors and a set of glycopeptide ligands for the class II major histocompatibility complex (MHC) A(q) protein. These results indicate that the protocol for the postprocessing of docked protein-ligand complexes developed in this paper may be generally useful for structure-based design in drug discovery.

Computational Tools and Algorithms for Designing Customized Synthetic Genes

PubMed Central

Gould, Nathan; Hendy, Oliver; Papamichail, Dimitris

2014-01-01

Advances in DNA synthesis have enabled the construction of artificial genes, gene circuits, and genomes of bacterial scale. Freedom in de novo design of synthetic constructs provides significant power in studying the impact of mutations in sequence features, and verifying hypotheses on the functional information that is encoded in nucleic and amino acids. To aid this goal, a large number of software tools of variable sophistication have been implemented, enabling the design of synthetic genes for sequence optimization based on rationally defined properties. The first generation of tools dealt predominantly with singular objectives such as codon usage optimization and unique restriction site incorporation. Recent years have seen the emergence of sequence design tools that aim to evolve sequences toward combinations of objectives. The design of optimal protein-coding sequences adhering to multiple objectives is computationally hard, and most tools rely on heuristics to sample the vast sequence design space. In this review, we study some of the algorithmic issues behind gene optimization and the approaches that different tools have adopted to redesign genes and optimize desired coding features. We utilize test cases to demonstrate the efficiency of each approach, as well as identify their strengths and limitations. PMID:25340050

Object-Oriented Multi-Disciplinary Design, Analysis, and Optimization Tool

NASA Technical Reports Server (NTRS)

Pak, Chan-gi

2011-01-01

An Object-Oriented Optimization (O3) tool was developed that leverages existing tools and practices, and allows the easy integration and adoption of new state-of-the-art software. At the heart of the O3 tool is the Central Executive Module (CEM), which can integrate disparate software packages in a cross platform network environment so as to quickly perform optimization and design tasks in a cohesive, streamlined manner. This object-oriented framework can integrate the analysis codes for multiple disciplines instead of relying on one code to perform the analysis for all disciplines. The CEM was written in FORTRAN and the script commands for each performance index were submitted through the use of the FORTRAN Call System command. In this CEM, the user chooses an optimization methodology, defines objective and constraint functions from performance indices, and provides starting and side constraints for continuous as well as discrete design variables. The structural analysis modules such as computations of the structural weight, stress, deflection, buckling, and flutter and divergence speeds have been developed and incorporated into the O3 tool to build an object-oriented Multidisciplinary Design, Analysis, and Optimization (MDAO) tool.

Impact of AMS-02 Measurements on Reducing GCR Model Uncertainties

NASA Technical Reports Server (NTRS)

Slaba, T. C.; O'Neill, P. M.; Golge, S.; Norbury, J. W.

2015-01-01

For vehicle design, shield optimization, mission planning, and astronaut risk assessment, the exposure from galactic cosmic rays (GCR) poses a significant and complex problem both in low Earth orbit and in deep space. To address this problem, various computational tools have been developed to quantify the exposure and risk in a wide range of scenarios. Generally, the tool used to describe the ambient GCR environment provides the input into subsequent computational tools and is therefore a critical component of end-to-end procedures. Over the past few years, several researchers have independently and very carefully compared some of the widely used GCR models to more rigorously characterize model differences and quantify uncertainties. All of the GCR models studied rely heavily on calibrating to available near-Earth measurements of GCR particle energy spectra, typically over restricted energy regions and short time periods. In this work, we first review recent sensitivity studies quantifying the ions and energies in the ambient GCR environment of greatest importance to exposure quantities behind shielding. Currently available measurements used to calibrate and validate GCR models are also summarized within this context. It is shown that the AMS-II measurements will fill a critically important gap in the measurement database. The emergence of AMS-II measurements also provides a unique opportunity to validate existing models against measurements that were not used to calibrate free parameters in the empirical descriptions. Discussion is given regarding rigorous approaches to implement the independent validation efforts, followed by recalibration of empirical parameters.

Contingency Contractor Optimization Phase 3 Sustainment Database Design Document - Contingency Contractor Optimization Tool - Prototype

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

Frazier, Christopher Rawls; Durfee, Justin David; Bandlow, Alisa

The Contingency Contractor Optimization Tool – Prototype (CCOT-P) database is used to store input and output data for the linear program model described in [1]. The database allows queries to retrieve this data and updating and inserting new input data.

An Overview of High-Resolution, Non-Dispersive, Imaging Spectrometers for High-Energy Photons

NASA Technical Reports Server (NTRS)

Kilbourne, Caroline

2010-01-01

High-resolution x-ray spectroscopy has become a powerful tool for studying the evolving universe. The grating spectrometers on the XMM and Chandra satellites initiated a new era in x-ray astronomy. Despite their successes, there is still need for instrumentation that can provide higher spectral resolution with high throughput in the Fe-K band and for extended sources. What is needed is a non-dispersive imaging spectrometer - essentially a 14-bit x-ray color camera. And a requirement for a nondispersive spectrometer designed to provide eV-scale spectral resolution is a temperature below 0.1 K. The required spectral resolution and the constraints of thermodynamics and engineering dictate the temperature regime nearly independently of the details of the sensor or the read-out technology. Low-temperature spectrometers can be divided into two classes - - equilibrium and non-equilibrium. In the equilibrium devices, or calorimeters, the energy is deposited in an isolated thermal mass and the resulting increase in temperature is measured. In the non-equilibrium devices, the absorbed energy produces quantized excitations that are counted to determine the energy. The two approaches have different strong points, and within each class a variety of optimizations have been pursued. I will present the basic fundamentals of operation and the details of the most successful device designs to date. I will also discuss how the measurement priorities (resolution, energy band, count rate) influence the optimal choice of detector technology.

Thermal Energy Storage for Electricity Peak-demand Mitigation: A Solution in Developing and Developed World Alike

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

DeForest, Nicholas; Mendes, Goncalo; Stadler, Michael

2013-06-02

In much of the developed world, air-conditioning in buildings is the dominant driver of summer peak electricity demand. In the developing world a steadily increasing utilization of air-conditioning places additional strain on already-congested grids. This common thread represents a large and growing threat to the reliable delivery of electricity around the world, requiring capital-intensive expansion of capacity and draining available investment resources. Thermal energy storage (TES), in the form of ice or chilled water, may be one of the few technologies currently capable of mitigating this problem cost effectively and at scale. The installation of TES capacity allows a buildingmore » to meet its on-peak air conditioning load without interruption using electricity purchased off-peak and operating with improved thermodynamic efficiency. In this way, TES has the potential to fundamentally alter consumption dynamics and reduce impacts of air conditioning. This investigation presents a simulation study of a large office building in four distinct geographical contexts: Miami, Lisbon, Shanghai, and Mumbai. The optimization tool DER-CAM (Distributed Energy Resources Customer Adoption Model) is applied to optimally size TES systems for each location. Summer load profiles are investigated to assess the effectiveness and consistency in reducing peak electricity demand. Additionally, annual energy requirements are used to determine system cost feasibility, payback periods and customer savings under local utility tariffs.« less

Adaptive smart simulator for characterization and MPPT construction of PV array

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

Ouada, Mehdi, E-mail: mehdi.ouada@univ-annaba.org; Meridjet, Mohamed Salah; Dib, Djalel

2016-07-25

Partial shading conditions are among the most important problems in large photovoltaic array. Many works of literature are interested in modeling, control and optimization of photovoltaic conversion of solar energy under partial shading conditions, The aim of this study is to build a software simulator similar to hard simulator and to produce a shading pattern of the proposed photovoltaic array in order to use the delivered information to obtain an optimal configuration of the PV array and construct MPPT algorithm. Graphical user interfaces (Matlab GUI) are built using a developed script, this tool is easy to use, simple, and hasmore » a rapid of responsiveness, the simulator supports large array simulations that can be interfaced with MPPT and power electronic converters.« less

DESTINY

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

2015-03-10

DESTINY is a comprehensive tool for modeling 3D and 2D cache designs using SRAM,embedded DRAM (eDRAM), spin transfer torque RAM (STT-RAM), resistive RAM (ReRAM), and phase change RAM (PCN). In its purpose, it is similar to CACTI, CACTI-3DD or NVSim. DESTINY is very useful for performing design-space exploration across several dimensions, such as optimizing for a target (e.g. latency, area or energy-delay product) for agiven memory technology, choosing the suitable memory technology or fabrication method (i.e. 2D v/s 3D) for a given optimization target, etc. DESTINY has been validated against several cache prototypes. DESTINY is expected to boost studies ofmore » next-generation memory architectures used in systems ranging from mobile devices to extreme-scale supercomputers.« less

Simultaneous Scheduling of Jobs, AGVs and Tools Considering Tool Transfer Times in Multi Machine FMS By SOS Algorithm

NASA Astrophysics Data System (ADS)

Sivarami Reddy, N.; Ramamurthy, D. V., Dr.; Prahlada Rao, K., Dr.

2017-08-01

This article addresses simultaneous scheduling of machines, AGVs and tools where machines are allowed to share the tools considering transfer times of jobs and tools between machines, to generate best optimal sequences that minimize makespan in a multi-machine Flexible Manufacturing System (FMS). Performance of FMS is expected to improve by effective utilization of its resources, by proper integration and synchronization of their scheduling. Symbiotic Organisms Search (SOS) algorithm is a potent tool which is a better alternative for solving optimization problems like scheduling and proven itself. The proposed SOS algorithm is tested on 22 job sets with makespan as objective for scheduling of machines and tools where machines are allowed to share tools without considering transfer times of jobs and tools and the results are compared with the results of existing methods. The results show that the SOS has outperformed. The same SOS algorithm is used for simultaneous scheduling of machines, AGVs and tools where machines are allowed to share tools considering transfer times of jobs and tools to determine the best optimal sequences that minimize makespan.

Combining Simulation Tools for End-to-End Trajectory Optimization

NASA Technical Reports Server (NTRS)

Whitley, Ryan; Gutkowski, Jeffrey; Craig, Scott; Dawn, Tim; Williams, Jacobs; Stein, William B.; Litton, Daniel; Lugo, Rafael; Qu, Min

2015-01-01

Trajectory simulations with advanced optimization algorithms are invaluable tools in the process of designing spacecraft. Due to the need for complex models, simulations are often highly tailored to the needs of the particular program or mission. NASA's Orion and SLS programs are no exception. While independent analyses are valuable to assess individual spacecraft capabilities, a complete end-to-end trajectory from launch to splashdown maximizes potential performance and ensures a continuous solution. In order to obtain end-to-end capability, Orion's in-space tool (Copernicus) was made to interface directly with the SLS's ascent tool (POST2) and a new tool to optimize the full problem by operating both simulations simultaneously was born.

Optimizing product life cycle processes in design phase

NASA Astrophysics Data System (ADS)

Faneye, Ola. B.; Anderl, Reiner

2002-02-01

Life cycle concepts do not only serve as basis in assisting product developers understand the dependencies between products and their life cycles, they also help in identifying potential opportunities for improvement in products. Common traditional concepts focus mainly on energy and material flow across life phases, necessitating the availability of metrics derived from a reference product. Knowledge of life cycle processes won from an existing product is directly reused in its redesign. Depending on sales volume nevertheless, the environmental impact before product optimization can be substantial. With modern information technologies today, computer-aided life cycle methodologies can be applied well before product use. On the basis of a virtual prototype, life cycle processes are analyzed and optimized, using simulation techniques. This preventive approach does not only help in minimizing (or even eliminating) environmental burdens caused by product, costs incurred due to changes in real product can also be avoided. The paper highlights the relationship between product and life cycle and presents a computer-based methodology for optimizing the product life cycle during design, as presented by SFB 392: Design for Environment - Methods and Tools at Technical University, Darmstadt.

Photonic crystal enhanced silicon cell based thermophotovoltaic systems

DOE PAGES

Yeng, Yi Xiang; Chan, Walker R.; Rinnerbauer, Veronika; ...

2015-01-30

We report the design, optimization, and experimental results of large area commercial silicon solar cell based thermophotovoltaic (TPV) energy conversion systems. Using global non-linear optimization tools, we demonstrate theoretically a maximum radiative heat-to-electricity efficiency of 6.4% and a corresponding output electrical power density of 0.39 W cm⁻² at temperature T = 1660 K when implementing both the optimized two-dimensional (2D) tantalum photonic crystal (PhC) selective emitter, and the optimized 1D tantalum pentoxide – silicon dioxide PhC cold-side selective filter. In addition, we have developed an experimental large area TPV test setup that enables accurate measurement of radiative heat-to-electricity efficiency formore » any emitter-filter-TPV cell combination of interest. In fact, the experimental results match extremely well with predictions of our numerical models. Our experimental setup achieved a maximum output electrical power density of 0.10W cm⁻² and radiative heat-to-electricity efficiency of 1.18% at T = 1380 K using commercial wafer size back-contacted silicon solar cells.« less

Challenges of NDE simulation tool validation, optimization, and utilization for composites

NASA Astrophysics Data System (ADS)

Leckey, Cara A. C.; Seebo, Jeffrey P.; Juarez, Peter

2016-02-01

Rapid, realistic nondestructive evaluation (NDE) simulation tools can aid in inspection optimization and prediction of inspectability for advanced aerospace materials and designs. NDE simulation tools may someday aid in the design and certification of aerospace components; potentially shortening the time from material development to implementation by industry and government. Furthermore, ultrasound modeling and simulation are expected to play a significant future role in validating the capabilities and limitations of guided wave based structural health monitoring (SHM) systems. The current state-of-the-art in ultrasonic NDE/SHM simulation is still far from the goal of rapidly simulating damage detection techniques for large scale, complex geometry composite components/vehicles containing realistic damage types. Ongoing work at NASA Langley Research Center is focused on advanced ultrasonic simulation tool development. This paper discusses challenges of simulation tool validation, optimization, and utilization for composites. Ongoing simulation tool development work is described along with examples of simulation validation and optimization challenges that are more broadly applicable to all NDE simulation tools. The paper will also discuss examples of simulation tool utilization at NASA to develop new damage characterization methods for composites, and associated challenges in experimentally validating those methods.

Watershed Management Optimization Support Tool (WMOST) v2: User Manual and Case Studies

EPA Science Inventory

The Watershed Management Optimization Support Tool (WMOST) is a decision support tool that evaluates the relative cost-effectiveness of management practices at the local or watershed scale. WMOST models the environmental effects and costs of management decisions in a watershed c...

Decision Support for Resilient Communities: EPA’s Watershed Management Optimization Support Tool

EPA Science Inventory

The U.S. EPA Atlantic Ecology Division is releasing version 3 of the Watershed Management Optimization Support Tool (WMOST v3) in February 2018. WMOST is a decision-support tool that facilitates integrated water resources management (IWRM) by communities and watershed organizati...

Identifying Cost-Effective Water Resources Management Strategies: Watershed Management Optimization Support Tool (WMOST)

EPA Science Inventory

The Watershed Management Optimization Support Tool (WMOST) is a public-domain software application designed to aid decision makers with integrated water resources management. The tool allows water resource managers and planners to screen a wide-range of management practices for c...

Optimization of signal versus background in liquid xenon detectors used for dark matter direct detection experiments

NASA Astrophysics Data System (ADS)

D'Arcangelo, Francesca D.

2010-02-01

The discovery of cosmic acceleration twelve years ago implies that our universe is dominated by dark energy, which is either a tiny cosmological constant or a mysterious fluid with large negative pressure, or that Einstein's successful theory of gravity needs to be modified at large scales/low energies. Since then, independent evidence of a number of cosmological probes has firmly established the picture of a universe where dark energy (or the effective contribution from a modification of gravity) makes up about 72% of the total energy density. Whichever of the options mentioned above will turn out to be the right one, a satisfying explanation for cosmic acceleration will likely lead to important new insights in fundamental physics. The question of the physics behind cosmic acceleration is thus one of the most intriguing open questions in modern physics. In this thesis, we calculate current constraints on dark energy and study how to optimally use the cosmological tools at our disposal to learn about its nature. We will first present constraints from a host of recent data on the dark energy sound speed and equation of state for different dark energy models including early dark energy. We then study the observational properties of purely kinetic k-essence models and show how they can in principle be straightforwardly distinguished from quintessence models by their equation of state behavior. We next consider a large, representative set of dark energy and modified gravity models and show that they can be divided into a small set of observationally distinct classes. We also find that all non-early dark energy models we consider can be modeled extremely well by a simple linear equation of state form. We will then go on to discuss a number of alternative, model independent parametrizations of dark energy properties. Among other things, we find that principal component analysis is not as model-independent as one would like it to be and that assuming a fixed value for the high redshift equation of state can lead to a dangerous bias in the determination of the equation of state at low redshift. Finally, we discuss using weak gravitational lensing of cosmic microwave background (CMB) anisotropies as a cosmological probe. We compare different methods for extracting cosmological information from the lensed CMB and show that CMB lensing will in the future be a useful tool for constraining dark energy and neutrino mass. Whereas marginalizing over neutrino mass can degrade dark energy constraints, CMB lensing helps to break the degeneracy between the two and restores the dark energy constraints to the level of the fixed neutrino mass case.

ConvAn: a convergence analyzing tool for optimization of biochemical networks.

PubMed

Kostromins, Andrejs; Mozga, Ivars; Stalidzans, Egils

2012-01-01

Dynamic models of biochemical networks usually are described as a system of nonlinear differential equations. In case of optimization of models for purpose of parameter estimation or design of new properties mainly numerical methods are used. That causes problems of optimization predictability as most of numerical optimization methods have stochastic properties and the convergence of the objective function to the global optimum is hardly predictable. Determination of suitable optimization method and necessary duration of optimization becomes critical in case of evaluation of high number of combinations of adjustable parameters or in case of large dynamic models. This task is complex due to variety of optimization methods, software tools and nonlinearity features of models in different parameter spaces. A software tool ConvAn is developed to analyze statistical properties of convergence dynamics for optimization runs with particular optimization method, model, software tool, set of optimization method parameters and number of adjustable parameters of the model. The convergence curves can be normalized automatically to enable comparison of different methods and models in the same scale. By the help of the biochemistry adapted graphical user interface of ConvAn it is possible to compare different optimization methods in terms of ability to find the global optima or values close to that as well as the necessary computational time to reach them. It is possible to estimate the optimization performance for different number of adjustable parameters. The functionality of ConvAn enables statistical assessment of necessary optimization time depending on the necessary optimization accuracy. Optimization methods, which are not suitable for a particular optimization task, can be rejected if they have poor repeatability or convergence properties. The software ConvAn is freely available on www.biosystems.lv/convan. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Development and Application of a Tool for Optimizing Composite Matrix Viscoplastic Material Parameters

NASA Technical Reports Server (NTRS)

Murthy, Pappu L. N.; Naghipour Ghezeljeh, Paria; Bednarcyk, Brett A.

2018-01-01

This document describes a recently developed analysis tool that enhances the resident capabilities of the Micromechanics Analysis Code with the Generalized Method of Cells (MAC/GMC) and its application. MAC/GMC is a composite material and laminate analysis software package developed at NASA Glenn Research Center. The primary focus of the current effort is to provide a graphical user interface (GUI) capability that helps users optimize highly nonlinear viscoplastic constitutive law parameters by fitting experimentally observed/measured stress-strain responses under various thermo-mechanical conditions for braided composites. The tool has been developed utilizing the MATrix LABoratory (MATLAB) (The Mathworks, Inc., Natick, MA) programming language. Illustrative examples shown are for a specific braided composite system wherein the matrix viscoplastic behavior is represented by a constitutive law described by seven parameters. The tool is general enough to fit any number of experimentally observed stress-strain responses of the material. The number of parameters to be optimized, as well as the importance given to each stress-strain response, are user choice. Three different optimization algorithms are included: (1) Optimization based on gradient method, (2) Genetic algorithm (GA) based optimization and (3) Particle Swarm Optimization (PSO). The user can mix and match the three algorithms. For example, one can start optimization with either 2 or 3 and then use the optimized solution to further fine tune with approach 1. The secondary focus of this paper is to demonstrate the application of this tool to optimize/calibrate parameters for a nonlinear viscoplastic matrix to predict stress-strain curves (for constituent and composite levels) at different rates, temperatures and/or loading conditions utilizing the Generalized Method of Cells. After preliminary validation of the tool through comparison with experimental results, a detailed virtual parametric study is presented wherein the combined effects of temperature and loading rate on the predicted response of a braided composite is investigated.

PopED lite: An optimal design software for preclinical pharmacokinetic and pharmacodynamic studies.

PubMed

Aoki, Yasunori; Sundqvist, Monika; Hooker, Andrew C; Gennemark, Peter

2016-04-01

Optimal experimental design approaches are seldom used in preclinical drug discovery. The objective is to develop an optimal design software tool specifically designed for preclinical applications in order to increase the efficiency of drug discovery in vivo studies. Several realistic experimental design case studies were collected and many preclinical experimental teams were consulted to determine the design goal of the software tool. The tool obtains an optimized experimental design by solving a constrained optimization problem, where each experimental design is evaluated using some function of the Fisher Information Matrix. The software was implemented in C++ using the Qt framework to assure a responsive user-software interaction through a rich graphical user interface, and at the same time, achieving the desired computational speed. In addition, a discrete global optimization algorithm was developed and implemented. The software design goals were simplicity, speed and intuition. Based on these design goals, we have developed the publicly available software PopED lite (http://www.bluetree.me/PopED_lite). Optimization computation was on average, over 14 test problems, 30 times faster in PopED lite compared to an already existing optimal design software tool. PopED lite is now used in real drug discovery projects and a few of these case studies are presented in this paper. PopED lite is designed to be simple, fast and intuitive. Simple, to give many users access to basic optimal design calculations. Fast, to fit a short design-execution cycle and allow interactive experimental design (test one design, discuss proposed design, test another design, etc). Intuitive, so that the input to and output from the software tool can easily be understood by users without knowledge of the theory of optimal design. In this way, PopED lite is highly useful in practice and complements existing tools. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Algorithmic design for 3D printing at building scale

DOE PAGES

Guerguis, Maged; Eikevik, Leif; Obendorf, Andrew; ...

2017-01-01

Here, this paper addresses the use of algorithmic design paired with additive manufacturing and their potential impact on architectural design and fabrication of a full-sized building, as demonstrated with the AMIE project. AMIE (Additive Manufacturing and Integrated Energy) was collaboration to 3d print a building and vehicle. Both the car and building were designed to generate, store and share energy in an effort to reduce or eliminate reliability on the power grid. This paper is intended to outline our methodology in successfully designing for these innovative strategies, with a focus on the use of computational design tools as a catalystmore » for design optimization, integrated project delivery, rapid prototyping and fabrication of building elements using additive manufacturing.« less

Algorithmic design for 3D printing at building scale

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

Guerguis, Maged; Eikevik, Leif; Obendorf, Andrew

Here, this paper addresses the use of algorithmic design paired with additive manufacturing and their potential impact on architectural design and fabrication of a full-sized building, as demonstrated with the AMIE project. AMIE (Additive Manufacturing and Integrated Energy) was collaboration to 3d print a building and vehicle. Both the car and building were designed to generate, store and share energy in an effort to reduce or eliminate reliability on the power grid. This paper is intended to outline our methodology in successfully designing for these innovative strategies, with a focus on the use of computational design tools as a catalystmore » for design optimization, integrated project delivery, rapid prototyping and fabrication of building elements using additive manufacturing.« less

Real-time Crystal Growth Visualization and Quantification by Energy-Resolved Neutron Imaging.

PubMed

Tremsin, Anton S; Perrodin, Didier; Losko, Adrian S; Vogel, Sven C; Bourke, Mark A M; Bizarri, Gregory A; Bourret, Edith D

2017-04-20

Energy-resolved neutron imaging is investigated as a real-time diagnostic tool for visualization and in-situ measurements of "blind" processes. This technique is demonstrated for the Bridgman-type crystal growth enabling remote and direct measurements of growth parameters crucial for process optimization. The location and shape of the interface between liquid and solid phases are monitored in real-time, concurrently with the measurement of elemental distribution within the growth volume and with the identification of structural features with a ~100 μm spatial resolution. Such diagnostics can substantially reduce the development time between exploratory small scale growth of new materials and their subsequent commercial production. This technique is widely applicable and is not limited to crystal growth processes.

Real-time Crystal Growth Visualization and Quantification by Energy-Resolved Neutron Imaging

NASA Astrophysics Data System (ADS)

Tremsin, Anton S.; Perrodin, Didier; Losko, Adrian S.; Vogel, Sven C.; Bourke, Mark A. M.; Bizarri, Gregory A.; Bourret, Edith D.

2017-04-01

Energy-resolved neutron imaging is investigated as a real-time diagnostic tool for visualization and in-situ measurements of “blind” processes. This technique is demonstrated for the Bridgman-type crystal growth enabling remote and direct measurements of growth parameters crucial for process optimization. The location and shape of the interface between liquid and solid phases are monitored in real-time, concurrently with the measurement of elemental distribution within the growth volume and with the identification of structural features with a ~100 μm spatial resolution. Such diagnostics can substantially reduce the development time between exploratory small scale growth of new materials and their subsequent commercial production. This technique is widely applicable and is not limited to crystal growth processes.

Challenges to diagnosis of HIV-associated wasting.

PubMed

Kotler, Donald

2004-12-01

There is a wide variability in the clinical presentation of the protein energy malnutrition often characterized as wasting in patients infected with HIV. Moreover, the clinical presentation has evolved over time. Initially, protein energy malnutrition was characterized by profound weight loss and depletion of body cell mass (BCM). Recently, unrelated concurrent metabolic abnormalities, such as lipodystrophy, may complicate the diagnosis of HIV wasting. Although measures of BCM are relatively accurate for the diagnosis of HIV wasting, the optimal tools for assessing BCM are not necessarily available to the clinician. From the practical standpoint, HIV wasting may be a self-evident diagnosis in advanced stages, but effective interpretation of the early signs of HIV wasting requires familiarity with other complications included in the differential diagnosis.

Real-time Crystal Growth Visualization and Quantification by Energy-Resolved Neutron Imaging

PubMed Central

Tremsin, Anton S.; Perrodin, Didier; Losko, Adrian S.; Vogel, Sven C.; Bourke, Mark A.M.; Bizarri, Gregory A.; Bourret, Edith D.

2017-01-01

Energy-resolved neutron imaging is investigated as a real-time diagnostic tool for visualization and in-situ measurements of “blind” processes. This technique is demonstrated for the Bridgman-type crystal growth enabling remote and direct measurements of growth parameters crucial for process optimization. The location and shape of the interface between liquid and solid phases are monitored in real-time, concurrently with the measurement of elemental distribution within the growth volume and with the identification of structural features with a ~100 μm spatial resolution. Such diagnostics can substantially reduce the development time between exploratory small scale growth of new materials and their subsequent commercial production. This technique is widely applicable and is not limited to crystal growth processes. PMID:28425461

Thermodynamics of Gas Turbine Cycles with Analytic Derivatives in OpenMDAO

NASA Technical Reports Server (NTRS)

Gray, Justin; Chin, Jeffrey; Hearn, Tristan; Hendricks, Eric; Lavelle, Thomas; Martins, Joaquim R. R. A.

2016-01-01

A new equilibrium thermodynamics analysis tool was built based on the CEA method using the OpenMDAO framework. The new tool provides forward and adjoint analytic derivatives for use with gradient based optimization algorithms. The new tool was validated against the original CEA code to ensure an accurate analysis and the analytic derivatives were validated against finite-difference approximations. Performance comparisons between analytic and finite difference methods showed a significant speed advantage for the analytic methods. To further test the new analysis tool, a sample optimization was performed to find the optimal air-fuel equivalence ratio, , maximizing combustion temperature for a range of different pressures. Collectively, the results demonstrate the viability of the new tool to serve as the thermodynamic backbone for future work on a full propulsion modeling tool.

Extension of an Object-Oriented Optimization Tool: User's Reference Manual

NASA Technical Reports Server (NTRS)

Pak, Chan-Gi; Truong, Samson S.

2015-01-01

The National Aeronautics and Space Administration Armstrong Flight Research Center has developed a cost-effective and flexible object-oriented optimization (O (sup 3)) tool that leverages existing tools and practices and allows easy integration and adoption of new state-of-the-art software. This object-oriented framework can integrate the analysis codes for multiple disciplines, as opposed to relying on one code to perform analysis for all disciplines. Optimization can thus take place within each discipline module, or in a loop between the O (sup 3) tool and the discipline modules, or both. Six different sample mathematical problems are presented to demonstrate the performance of the O (sup 3) tool. Instructions for preparing input data for the O (sup 3) tool are detailed in this user's manual.

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

Modeling of policies for reduction of GHG emissions in energy sector using ANN: case study-Croatia (EU).

PubMed

Bolanča, Tomislav; Strahovnik, Tomislav; Ukić, Šime; Stankov, Mirjana Novak; Rogošić, Marko

2017-07-01

This study describes the development of tool for testing different policies for reduction of greenhouse gas (GHG) emissions in energy sector using artificial neural networks (ANNs). The case study of Croatia was elaborated. Two different energy consumption scenarios were used as a base for calculations and predictions of GHG emissions: the business as usual (BAU) scenario and sustainable scenario. Both of them are based on predicted energy consumption using different growth rates; the growth rates within the second scenario resulted from the implementation of corresponding energy efficiency measures in final energy consumption and increasing share of renewable energy sources. Both ANN architecture and training methodology were optimized to produce network that was able to successfully describe the existing data and to achieve reliable prediction of emissions in a forward time sense. The BAU scenario was found to produce continuously increasing emissions of all GHGs. The sustainable scenario was found to decrease the GHG emission levels of all gases with respect to BAU. The observed decrease was attributed to the group of measures termed the reduction of final energy consumption through energy efficiency measures.

Achieving Actionable Results from Available Inputs: Metamodels Take Building Energy Simulations One Step Further

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

Horsey, Henry; Fleming, Katherine; Ball, Brian

Modeling commercial building energy usage can be a difficult and time-consuming task. The increasing prevalence of optimization algorithms provides one path for reducing the time and difficulty. Many use cases remain, however, where information regarding whole-building energy usage is valuable, but the time and expertise required to run and post-process a large number of building energy simulations is intractable. A relatively underutilized option to accurately estimate building energy consumption in real time is to pre-compute large datasets of potential building energy models, and use the set of results to quickly and efficiently provide highly accurate data. This process is calledmore » metamodeling. In this paper, two case studies are presented demonstrating the successful applications of metamodeling using the open-source OpenStudio Analysis Framework. The first case study involves the U.S. Department of Energy's Asset Score Tool, specifically the Preview Asset Score Tool, which is designed to give nontechnical users a near-instantaneous estimated range of expected results based on building system-level inputs. The second case study involves estimating the potential demand response capabilities of retail buildings in Colorado. The metamodel developed in this second application not only allows for estimation of a single building's expected performance, but also can be combined with public data to estimate the aggregate DR potential across various geographic (county and state) scales. In both case studies, the unique advantages of pre-computation allow building energy models to take the place of topdown actuarial evaluations. This paper ends by exploring the benefits of using metamodels and then examines the cost-effectiveness of this approach.« less

Single Phase Dual-energy CT Angiography: One-stop-shop Tool for Evaluating Aneurysmal Subarachnoid Hemorrhage.

PubMed

Ni, Qian Qian; Tang, Chun Xiang; Zhao, Yan E; Zhou, Chang Sheng; Chen, Guo Zhong; Lu, Guang Ming; Zhang, Long Jiang

2016-05-25

Aneurysmal subarachnoid hemorrhages have extremely high case fatality in clinic. Early and rapid identifications of ruptured intracranial aneurysms seem to be especially important. Here we evaluate clinical value of single phase contrast-enhanced dual-energy CT angiograph (DE-CTA) as a one-stop-shop tool in detecting aneurysmal subarachnoid hemorrhage. One hundred and five patients who underwent true non-enhanced CT (TNCT), contrast-enhanced DE-CTA and digital subtraction angiography (DSA) were included. Image quality and detectability of intracranial hemorrhage were evaluated and compared between virtual non-enhanced CT (VNCT) images reconstructed from DE-CTA and TNCT. There was no statistical difference in image quality (P > 0.05) between VNCT and TNCT. The agreement of VNCT and TNCT in detecting intracranial hemorrhage reached 98.1% on a per-patient basis. With DSA as reference standard, sensitivity and specificity on a per-patient were 98.3% and 97.9% for DE-CTA in intracranial aneurysm detection. Effective dose of DE-CTA was reduced by 75.0% compared to conventional digital subtraction CTA. Thus, single phase contrast-enhanced DE-CTA is optimal reliable one-stop-shop tool for detecting intracranial hemorrhage with VNCT and intracranial aneurysms with DE-CTA with substantial radiation dose reduction compared with conventional digital subtraction CTA.

Single Phase Dual-energy CT Angiography: One-stop-shop Tool for Evaluating Aneurysmal Subarachnoid Hemorrhage

PubMed Central

Ni, Qian Qian; Tang, Chun Xiang; Zhao, Yan E; Zhou, Chang Sheng; Chen, Guo Zhong; Lu, Guang Ming; Zhang, Long Jiang

2016-01-01

Aneurysmal subarachnoid hemorrhages have extremely high case fatality in clinic. Early and rapid identifications of ruptured intracranial aneurysms seem to be especially important. Here we evaluate clinical value of single phase contrast-enhanced dual-energy CT angiograph (DE-CTA) as a one-stop-shop tool in detecting aneurysmal subarachnoid hemorrhage. One hundred and five patients who underwent true non-enhanced CT (TNCT), contrast-enhanced DE-CTA and digital subtraction angiography (DSA) were included. Image quality and detectability of intracranial hemorrhage were evaluated and compared between virtual non-enhanced CT (VNCT) images reconstructed from DE-CTA and TNCT. There was no statistical difference in image quality (P > 0.05) between VNCT and TNCT. The agreement of VNCT and TNCT in detecting intracranial hemorrhage reached 98.1% on a per-patient basis. With DSA as reference standard, sensitivity and specificity on a per-patient were 98.3% and 97.9% for DE-CTA in intracranial aneurysm detection. Effective dose of DE-CTA was reduced by 75.0% compared to conventional digital subtraction CTA. Thus, single phase contrast-enhanced DE-CTA is optimal reliable one-stop-shop tool for detecting intracranial hemorrhage with VNCT and intracranial aneurysms with DE-CTA with substantial radiation dose reduction compared with conventional digital subtraction CTA. PMID:27222163

Data-Oriented Astrophysics at NOAO: The Science Archive & The Data Lab

NASA Astrophysics Data System (ADS)

Juneau, Stephanie; NOAO Data Lab, NOAO Science Archive

2018-06-01

As we keep progressing into an era of increasingly large astronomy datasets, NOAO’s data-oriented mission is growing in prominence. The NOAO Science Archive, which captures and processes the pixel data from mountaintops in Chile and Arizona, now contains holdings at Petabyte scales. Working at the intersection of astronomy and data science, the main goal of the NOAO Data Lab is to provide users with a suite of tools to work close to this data, the catalogs derived from them, as well as externally provided datasets, and thus optimize the scientific productivity of the astronomy community. These tools and services include databases, query tools, virtual storage space, workflows through our Jupyter Notebook server, and scripted analysis. We currently host datasets from NOAO facilities such as the Dark Energy Survey (DES), the DESI imaging Legacy Surveys (LS), the Dark Energy Camera Plane Survey (DECaPS), and the nearly all-sky NOAO Source Catalog (NSC). We are further preparing for large spectroscopy datasets such as DESI. After a brief overview of the Science Archive, the Data Lab and datasets, I will briefly showcase scientific applications showing use of our data holdings. Lastly, I will describe our vision for future developments as we tackle the next technical and scientific challenges.

Depth of manual dismantling analysis: A cost–benefit approach

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

Achillas, Ch., E-mail: c.achillas@ihu.edu.gr; Aidonis, D.; Vlachokostas, Ch.

Highlights: ► A mathematical modeling tool for OEMs. ► The tool can be used by OEMs, recyclers of electr(on)ic equipment or WEEE management systems’ regulators. ► The tool makes use of cost–benefit analysis in order to determine the optimal depth of product disassembly. ► The reusable materials and the quantity of metals and plastics recycled can be quantified in an easy-to-comprehend manner. - Abstract: This paper presents a decision support tool for manufacturers and recyclers towards end-of-life strategies for waste electrical and electronic equipment. A mathematical formulation based on the cost benefit analysis concept is herein analytically described in ordermore » to determine the parts and/or components of an obsolete product that should be either non-destructively recovered for reuse or be recycled. The framework optimally determines the depth of disassembly for a given product, taking into account economic considerations. On this basis, it embeds all relevant cost elements to be included in the decision-making process, such as recovered materials and (depreciated) parts/components, labor costs, energy consumption, equipment depreciation, quality control and warehousing. This tool can be part of the strategic decision-making process in order to maximize profitability or minimize end-of-life management costs. A case study to demonstrate the models’ applicability is presented for a typical electronic product in terms of structure and material composition. Taking into account the market values of the pilot product’s components, the manual disassembly is proven profitable with the marginal revenues from recovered reusable materials to be estimated at 2.93–23.06 €, depending on the level of disassembly.« less

Development of a multiobjective optimization tool for the selection and placement of best management practices for nonpoint source pollution control

NASA Astrophysics Data System (ADS)

Maringanti, Chetan; Chaubey, Indrajeet; Popp, Jennie

2009-06-01

Best management practices (BMPs) are effective in reducing the transport of agricultural nonpoint source pollutants to receiving water bodies. However, selection of BMPs for placement in a watershed requires optimization of the available resources to obtain maximum possible pollution reduction. In this study, an optimization methodology is developed to select and place BMPs in a watershed to provide solutions that are both economically and ecologically effective. This novel approach develops and utilizes a BMP tool, a database that stores the pollution reduction and cost information of different BMPs under consideration. The BMP tool replaces the dynamic linkage of the distributed parameter watershed model during optimization and therefore reduces the computation time considerably. Total pollutant load from the watershed, and net cost increase from the baseline, were the two objective functions minimized during the optimization process. The optimization model, consisting of a multiobjective genetic algorithm (NSGA-II) in combination with a watershed simulation tool (Soil Water and Assessment Tool (SWAT)), was developed and tested for nonpoint source pollution control in the L'Anguille River watershed located in eastern Arkansas. The optimized solutions provided a trade-off between the two objective functions for sediment, phosphorus, and nitrogen reduction. The results indicated that buffer strips were very effective in controlling the nonpoint source pollutants from leaving the croplands. The optimized BMP plans resulted in potential reductions of 33%, 32%, and 13% in sediment, phosphorus, and nitrogen loads, respectively, from the watershed.

Advanced Nuclear Technology. Using Technology for Small Modular Reactor Staff Optimization, Improved Effectiveness, and Cost Containment, 3002007071

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

Loflin, Leonard

Through this grant, the U.S. Department of Energy (DOE) will review several functional areas within a nuclear power plant, including fire protection, operations and operations support, refueling, training, procurement, maintenance, site engineering, and others. Several functional areas need to be examined since there appears to be no single staffing area or approach that alone has the potential for significant staff optimization at new nuclear power plants. Several of the functional areas will require a review of technology options such as automation, remote monitoring, fleet wide monitoring, new and specialized instrumentation, human factors engineering, risk informed analysis and PRAs, component andmore » system condition monitoring and reporting, just in time training, electronic and automated procedures, electronic tools for configuration management and license and design basis information, etc., that may be applied to support optimization. Additionally, the project will require a review key regulatory issues that affect staffing and could be optimized with additional technology input. Opportunities to further optimize staffing levels and staffing functions by selection of design attributes of physical systems and structures need also be identified. A goal of this project is to develop a prioritized assessment of the functional areas, and R&D actions needed for those functional areas, to provide the best optimization« less

Final Report

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

Hollingsworth, Jeff

2014-07-31

The purpose of this project was to develop tools and techniques to improve the ability of computational scientists to investigate and correct problems (bugs) in their programs. Specifically, the University of Maryland component of this project focused on the problems associated with the finite number of bits available in a computer to represent numeric values. In large scale scientific computation, numbers are frequently added to and multiplied with each other billions of times. Thus even small errors due to the representation of numbers can accumulate into big errors. However, using too many bits to represent a number results in additionalmore » computation, memory, and energy costs. Thus it is critical to find the right size for numbers. This project focused on several aspects of this general problem. First, we developed a tool to look for cancelations, the catastrophic loss of precision in numbers due to the addition of two numbers whose actual values are close to each other, but whose representation in a computer is identical or nearly so. Second, we developed a suite of tools to allow programmers to identify exactly how much precision is required for each operation in their program. This tool allows programmers to both verify that enough precision is available, but more importantly find cases where extra precision could be eliminated to allow the program to use less memory, computer time, or energy. These tools use advanced binary modification techniques to allow the analysis of actual optimized code. The system, called Craft, has been applied to a number of benchmarks and real applications.« less

Optimization design of submerged propeller in oxidation ditch by computational fluid dynamics and comparison with experiments.

PubMed

Zhang, Yuquan; Zheng, Yuan; Fernandez-Rodriguez, E; Yang, Chunxia; Zhu, Yantao; Liu, Huiwen; Jiang, Hao

The operating condition of a submerged propeller has a significant impact on flow field and energy consumption of the oxidation ditch. An experimentally validated numerical model, based on the computational fluid dynamics (CFD) tool, is presented to optimize the operating condition by considering two important factors: flow field and energy consumption. Performance demonstration and comparison of different operating conditions were carried out in a Carrousel oxidation ditch at the Yingtang wastewater treatment plants in Anhui Province, China. By adjusting the position and rotating speed together with the number of submerged propellers, problems of sludge deposit and the low velocity in the bend could be solved in a most cost-effective way. The simulated results were acceptable compared with the experimental data and the following results were obtained. The CFD model characterized flow pattern and energy consumption in the full-scale oxidation ditch. The predicted flow field values were within -1.28 ± 7.14% difference from the measured values. By determining three sets of propellers under the rotating speed of 6.50 rad/s with one located 5 m from the first curved wall, after numerical simulation and actual measurement, not only the least power density but also the requirement of the flow pattern could be realized.

Simulation of diurnal thermal energy storage systems: Preliminary results

NASA Astrophysics Data System (ADS)

Katipamula, S.; Somasundaram, S.; Williams, H. R.

1994-12-01

This report describes the results of a simulation of thermal energy storage (TES) integrated with a simple-cycle gas turbine cogeneration system. Integrating TES with cogeneration can serve the electrical and thermal loads independently while firing all fuel in the gas turbine. The detailed engineering and economic feasibility of diurnal TES systems integrated with cogeneration systems has been described in two previous PNL reports. The objective of this study was to lay the ground work for optimization of the TES system designs using a simulation tool called TRNSYS (TRaNsient SYstem Simulation). TRNSYS is a transient simulation program with a sequential-modular structure developed at the Solar Energy Laboratory, University of Wisconsin-Madison. The two TES systems selected for the base-case simulations were: (1) a one-tank storage model to represent the oil/rock TES system; and (2) a two-tank storage model to represent the molten nitrate salt TES system. Results of the study clearly indicate that an engineering optimization of the TES system using TRNSYS is possible. The one-tank stratified oil/rock storage model described here is a good starting point for parametric studies of a TES system. Further developments to the TRNSYS library of available models (economizer, evaporator, gas turbine, etc.) are recommended so that the phase-change processes is accurately treated.

Procedures and Standards for Residential Ventilation System Commissioning: An Annotated Bibliography

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

Stratton, J. Chris; Wray, Craig P.

2013-04-01

Beginning with the 2008 version of Title 24, new homes in California must comply with ANSI/ASHRAE Standard 62.2-2007 requirements for residential ventilation. Where installed, the limited data available indicate that mechanical ventilation systems do not always perform optimally or even as many codes and forecasts predict. Commissioning such systems when they are installed or during subsequent building retrofits is a step towards eliminating deficiencies and optimizing the tradeoff between energy use and acceptable IAQ. Work funded by the California Energy Commission about a decade ago at Berkeley Lab documented procedures for residential commissioning, but did not focus on ventilation systems.more » Since then, standards and approaches for commissioning ventilation systems have been an active area of work in Europe. This report describes our efforts to collect new literature on commissioning procedures and to identify information that can be used to support the future development of residential-ventilation-specific procedures and standards. We recommend that a standardized commissioning process and a commissioning guide for practitioners be developed, along with a combined energy and IAQ benefit assessment standard and tool, and a diagnostic guide for estimating continuous pollutant emission rates of concern in residences (including a database that lists emission test data for commercially-available labeled products).« less

Pressure Mapping and Efficiency Analysis of an EPPLER 857 Hydrokinetic Turbine

NASA Astrophysics Data System (ADS)

Clark, Tristan

A conceptual energy ship is presented to provide renewable energy. The ship, driven by the wind, drags a hydrokinetic turbine through the water. The power generated is used to run electrolysis on board, taking the resultant hydrogen back to shore to be used as an energy source. The basin efficiency (Power/thrust*velocity) of the Hydrokinetic Turbine (HTK) plays a vital role in this process. In order to extract the maximum allowable power from the flow, the blades need to be optimized. The structural analysis of the blade is important, as the blade will undergo high pressure loads from the water. A procedure for analysis of a preliminary Hydrokinetic Turbine blade design is developed. The blade was designed by a non-optimized Blade Element Momentum Theory (BEMT) code. Six simulations were run, with varying mesh resolution, turbulence models, and flow region size. The procedure was developed that provides detailed explanation for the entire process, from geometry and mesh generation to post-processing analysis tools. The efficiency results from the simulations are used to study the mesh resolution, flow region size, and turbulence models. The results are compared to the BEMT model design targets. Static pressure maps are created that can be used for structural analysis of the blades.

Implementation of a Low-Thrust Trajectory Optimization Algorithm for Preliminary Design

NASA Technical Reports Server (NTRS)

Sims, Jon A.; Finlayson, Paul A.; Rinderle, Edward A.; Vavrina, Matthew A.; Kowalkowski, Theresa D.

2006-01-01

A tool developed for the preliminary design of low-thrust trajectories is described. The trajectory is discretized into segments and a nonlinear programming method is used for optimization. The tool is easy to use, has robust convergence, and can handle many intermediate encounters. In addition, the tool has a wide variety of features, including several options for objective function and different low-thrust propulsion models (e.g., solar electric propulsion, nuclear electric propulsion, and solar sail). High-thrust, impulsive trajectories can also be optimized.

A genetic algorithm approach in interface and surface structure optimization

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

Zhang, Jian

The thesis is divided into two parts. In the first part a global optimization method is developed for the interface and surface structures optimization. Two prototype systems are chosen to be studied. One is Si[001] symmetric tilted grain boundaries and the other is Ag/Au induced Si(111) surface. It is found that Genetic Algorithm is very efficient in finding lowest energy structures in both cases. Not only existing structures in the experiments can be reproduced, but also many new structures can be predicted using Genetic Algorithm. Thus it is shown that Genetic Algorithm is a extremely powerful tool for the materialmore » structures predictions. The second part of the thesis is devoted to the explanation of an experimental observation of thermal radiation from three-dimensional tungsten photonic crystal structures. The experimental results seems astounding and confusing, yet the theoretical models in the paper revealed the physics insight behind the phenomena and can well reproduced the experimental results.« less

Gaussian processes with optimal kernel construction for neuro-degenerative clinical onset prediction

NASA Astrophysics Data System (ADS)

Canas, Liane S.; Yvernault, Benjamin; Cash, David M.; Molteni, Erika; Veale, Tom; Benzinger, Tammie; Ourselin, Sébastien; Mead, Simon; Modat, Marc

2018-02-01

Gaussian Processes (GP) are a powerful tool to capture the complex time-variations of a dataset. In the context of medical imaging analysis, they allow a robust modelling even in case of highly uncertain or incomplete datasets. Predictions from GP are dependent of the covariance kernel function selected to explain the data variance. To overcome this limitation, we propose a framework to identify the optimal covariance kernel function to model the data.The optimal kernel is defined as a composition of base kernel functions used to identify correlation patterns between data points. Our approach includes a modified version of the Compositional Kernel Learning (CKL) algorithm, in which we score the kernel families using a new energy function that depends both the Bayesian Information Criterion (BIC) and the explained variance score. We applied the proposed framework to model the progression of neurodegenerative diseases over time, in particular the progression of autosomal dominantly-inherited Alzheimer's disease, and use it to predict the time to clinical onset of subjects carrying genetic mutation.

The MCUCN simulation code for ultracold neutron physics

NASA Astrophysics Data System (ADS)

Zsigmond, G.

2018-02-01

Ultracold neutrons (UCN) have very low kinetic energies 0-300 neV, thereby can be stored in specific material or magnetic confinements for many hundreds of seconds. This makes them a very useful tool in probing fundamental symmetries of nature (for instance charge-parity violation by neutron electric dipole moment experiments) and contributing important parameters for the Big Bang nucleosynthesis (neutron lifetime measurements). Improved precision experiments are in construction at new and planned UCN sources around the world. MC simulations play an important role in the optimization of such systems with a large number of parameters, but also in the estimation of systematic effects, in benchmarking of analysis codes, or as part of the analysis. The MCUCN code written at PSI has been extensively used for the optimization of the UCN source optics and in the optimization and analysis of (test) experiments within the nEDM project based at PSI. In this paper we present the main features of MCUCN and interesting benchmark and application examples.

Topology and boundary shape optimization as an integrated design tool

NASA Technical Reports Server (NTRS)

Bendsoe, Martin Philip; Rodrigues, Helder Carrico

1990-01-01

The optimal topology of a two dimensional linear elastic body can be computed by regarding the body as a domain of the plane with a high density of material. Such an optimal topology can then be used as the basis for a shape optimization method that computes the optimal form of the boundary curves of the body. This results in an efficient and reliable design tool, which can be implemented via common FEM mesh generator and CAD type input-output facilities.

Energy, variability and weather finance engineering

NASA Astrophysics Data System (ADS)

Roussis, Dimitrios; Parara, Iliana; Gournari, Panagiota; Moustakis, Yiannis; Dimitriadis, Panayiotis; Iliopoulou, Theano; Koutsoyiannis, Demetris; Karakatsanis, Georgios

2017-04-01

Most types of renewable energies are characterized by intense intermittency, causing significant instabilities to the grid; further requiring additional infrastructure (e.g. pumped-storage) for buffering hydrometeorological uncertainties, as well as complex operational rules for load balancing. In addition, most intermittent renewable units are subsidized, creating significant market inefficiencies. Weather derivatives comprise mature financial tools for integrating successfully the intermittent-load and base-load components into a unified hybrid energy system and establish their operation within a generalized uncertainty management market. With a growing global market share and 46% utilization of this financial tool by the energy industry and 12% by agriculture (that partially concerns biofuel resources), weather derivatives are projected to constitute a critical subsystem of many grids for buffering frequent hydrometeorological risks of low and medium impacts -which are not covered by standard insurance contracts that aim exclusively at extreme events and high financial damages. In this context, we study the attributes of hydrometeorological time series in a remote and small island in Greece, powered by an autonomous hybrid energy system. Upon the results we choose the optimal underlying index and we further compose and engineer a weather derivative with features of a typical option contract -which we consider most flexible and appropriate for the case- to test our assumptions on its beneficiary effects for both the budget of private energy producers and the island's public administration. Acknowledgement: This research is conducted within the frame of the undergraduate course "Stochastic Methods in Water Resources" of the National Technical University of Athens (NTUA). The School of Civil Engineering of NTUA provided moral support for the participation of the students in the Assembly.

Supporting Building Portfolio Investment and Policy Decision Making through an Integrated Building Utility Data Platform

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

Aziz, Azizan; Lasternas, Bertrand; Alschuler, Elena

The American Recovery and Reinvestment Act stimulus funding of 2009 for smart grid projects resulted in the tripling of smart meters deployment. In 2012, the Green Button initiative provided utility customers with access to their real-time1 energy usage. The availability of finely granular data provides an enormous potential for energy data analytics and energy benchmarking. The sheer volume of time-series utility data from a large number of buildings also poses challenges in data collection, quality control, and database management for rigorous and meaningful analyses. In this paper, we will describe a building portfolio-level data analytics tool for operational optimization, businessmore » investment and policy assessment using 15-minute to monthly intervals utility data. The analytics tool is developed on top of the U.S. Department of Energy’s Standard Energy Efficiency Data (SEED) platform, an open source software application that manages energy performance data of large groups of buildings. To support the significantly large volume of granular interval data, we integrated a parallel time-series database to the existing relational database. The time-series database improves on the current utility data input, focusing on real-time data collection, storage, analytics and data quality control. The fully integrated data platform supports APIs for utility apps development by third party software developers. These apps will provide actionable intelligence for building owners and facilities managers. Unlike a commercial system, this platform is an open source platform funded by the U.S. Government, accessible to the public, researchers and other developers, to support initiatives in reducing building energy consumption.« less

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.

Using Optimization to Improve Test Planning

DTIC Science & Technology

2017-09-01

friendly and to display the output differently, the test and evaluation test schedule optimization model would be a good tool for the test and... evaluation schedulers. 14. SUBJECT TERMS schedule optimization, test planning 15. NUMBER OF PAGES 223 16. PRICE CODE 17. SECURITY CLASSIFICATION OF...make the input more user-friendly and to display the output differently, the test and evaluation test schedule optimization model would be a good tool

OPTIMAL WELL LOCATOR (OWL): A SCREENING TOOL FOR EVALUATING LOCATIONS OF MONITORING WELLS

EPA Science Inventory

The Optimal Well Locator ( OWL) program was designed and developed by USEPA to be a screening tool to evaluate and optimize the placement of wells in long term monitoring networks at small sites. The first objective of the OWL program is to allow the user to visualize the change ...

Kinetic compensation effect in logistic distributed activation energy model for lignocellulosic biomass pyrolysis.

PubMed

Xu, Di; Chai, Meiyun; Dong, Zhujun; Rahman, Md Maksudur; Yu, Xi; Cai, Junmeng

2018-06-04

The kinetic compensation effect in the logistic distributed activation energy model (DAEM) for lignocellulosic biomass pyrolysis was investigated. The sum of square error (SSE) surface tool was used to analyze two theoretically simulated logistic DAEM processes for cellulose and xylan pyrolysis. The logistic DAEM coupled with the pattern search method for parameter estimation was used to analyze the experimental data of cellulose pyrolysis. The results showed that many parameter sets of the logistic DAEM could fit the data at different heating rates very well for both simulated and experimental processes, and a perfect linear relationship between the logarithm of the frequency factor and the mean value of the activation energy distribution was found. The parameters of the logistic DAEM can be estimated by coupling the optimization method and isoconversional kinetic methods. The results would be helpful for chemical kinetic analysis using DAEM. Copyright © 2018 Elsevier Ltd. All rights reserved.

Leveraging OpenStudio's Application Programming Interfaces: Preprint

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

Long, N.; Ball, B.; Goldwasser, D.

2013-11-01

OpenStudio development efforts have been focused on providing Application Programming Interfaces (APIs) where users are able to extend OpenStudio without the need to compile the open source libraries. This paper will discuss the basic purposes and functionalities of the core libraries that have been wrapped with APIs including the Building Model, Results Processing, Advanced Analysis, UncertaintyQuantification, and Data Interoperability through Translators. Several building energy modeling applications have been produced using OpenStudio's API and Software Development Kits (SDK) including the United States Department of Energy's Asset ScoreCalculator, a mobile-based audit tool, an energy design assistance reporting protocol, and a portfolio scalemore » incentive optimization analysismethodology. Each of these software applications will be discussed briefly and will describe how the APIs were leveraged for various uses including high-level modeling, data transformations from detailed building audits, error checking/quality assurance of models, and use of high-performance computing for mass simulations.« less

The role of CSP in Brazil: A multi-model analysis

NASA Astrophysics Data System (ADS)

Soria, Rafael; Lucena, André F. P.; Tomaschek, Jan; Fichter, Tobias; Haasz, Thomas; Szklo, Alexandre; Schaeffer, Roberto; Rochedo, Pedro; Fahl, Ulrich; Kern, Jürgen; Hoffmann, Susanne

2016-05-01

MESSAGE, TIMES and REMIX-CEM are potential tools for modelling a larger penetration of variable renewable energy (VRE) into the Brazilian power system. They also allow devising the opportunities that concentrated solar power (CSP) plants offer to the power system and to the wider energy system. There are different opportunities for CSP in Brazil in the short and medium term, consolidating this technology as a feasible alternative for greenhouse gas (GHG) mitigation in Brazil. This work verified that CSP is a cost-effective option only under very stringent mitigation scenarios (4DS and 2DS) and when carbon capture and storage (CCS) is not available. Still, according to the findings of REMIX-CEM-B, CSP can provide firm energy and dispatchable capacity in the Northeast region of Brazil, optimally complementing wind and PV generation. Moreover, CSP can offer additional flexibility to the Northeast power system, especially during winter and after 2030.

A novel method for predicting the power outputs of wave energy converters

NASA Astrophysics Data System (ADS)

Wang, Yingguang

2018-03-01

This paper focuses on realistically predicting the power outputs of wave energy converters operating in shallow water nonlinear waves. A heaving two-body point absorber is utilized as a specific calculation example, and the generated power of the point absorber has been predicted by using a novel method (a nonlinear simulation method) that incorporates a second order random wave model into a nonlinear dynamic filter. It is demonstrated that the second order random wave model in this article can be utilized to generate irregular waves with realistic crest-trough asymmetries, and consequently, more accurate generated power can be predicted by subsequently solving the nonlinear dynamic filter equation with the nonlinearly simulated second order waves as inputs. The research findings demonstrate that the novel nonlinear simulation method in this article can be utilized as a robust tool for ocean engineers in their design, analysis and optimization of wave energy converters.

A wireless soil moisture sensor powered by solar energy.

PubMed

Jiang, Mingliang; Lv, Mouchao; Deng, Zhong; Zhai, Guoliang

2017-01-01

In a variety of agricultural activities, such as irrigation scheduling and nutrient management, soil water content is regarded as an essential parameter. Either power supply or long-distance cable is hardly available within field scale. For the necessity of monitoring soil water dynamics at field scale, this study presents a wireless soil moisture sensor based on the impedance transform of the frequency domain. The sensor system is powered by solar energy, and the data can be instantly transmitted by wireless communication. The sensor electrodes are embedded into the bottom of a supporting rod so that the sensor can measure soil water contents at different depths. An optimal design with time executing sequence is considered to reduce the energy consumption. The experimental results showed that the sensor is a promising tool for monitoring moisture in large-scale farmland using solar power and wireless communication.

A method to evaluate hydraulic fracture using proppant detection.

PubMed

Liu, Juntao; Zhang, Feng; Gardner, Robin P; Hou, Guojing; Zhang, Quanying; Li, Hu

2015-11-01

Accurate determination of the proppant placement and propped fracture height are important for evaluating and optimizing stimulation strategies. A technology using non-radioactive proppant and a pulsed neutron gamma energy spectra logging tool to determine the placement and height of propped fractures is proposed. Gd2O3 was incorporated into ceramic proppant and a Monte Carlo method was utilized to build the logging tools and formation models. Characteristic responses of the recorded information of different logging tools to fracture widths, proppant concentrations and influencing factors were studied. The results show that Gd capture gamma rays can be used to evaluate propped fractures and it has higher sensitivity to the change of fracture width and traceable proppant content compared with the exiting non-radioactive proppant evaluation techniques and only an after-fracture measurement is needed for the new method; The changes in gas saturation and borehole size have a great impact on determining propped fractures when compensated neutron and pulsed neutron capture tool are used. A field example is presented to validate the application of the new technique. Copyright © 2015 Elsevier Ltd. All rights reserved.

A modeling tool to support decision making in future hydropower development in Chile

NASA Astrophysics Data System (ADS)

Vicuna, S.; Hermansen, C.; Cerda, J. P.; Olivares, M. A.; Gomez, T. I.; Toha, E.; Poblete, D.; Mao, L.; Falvey, M. J.; Pliscoff, P.; Melo, O.; Lacy, S.; Peredo, M.; Marquet, P. A.; Maturana, J.; Gironas, J. A.

2017-12-01

Modeling tools support planning by providing transparent means to assess the outcome of natural resources management alternatives within technical frameworks in the presence of conflicting objectives. Such tools, when employed to model different scenarios, complement discussion in a policy-making context. Examples of practical use of this type of tool exist, such as the Canadian public forest management, but are not common, especially in the context of developing countries. We present a tool to support the selection from a portfolio of potential future hydropower projects in Chile. This tool, developed by a large team of researchers under the guidance of the Chilean Energy Ministry, is especially relevant in the context of evident regionalism, skepticism and change in societal values in a country that has achieved a sustained growth alongside increased demands from society. The tool operates at a scale of a river reach, between 1-5 km long, on a domain that can be defined according to the scale needs of the related discussion, and its application can vary from river basins to regions or other spatial configurations that may be of interest. The tool addresses both available hydropower potential and the existence (inferred or observed) of other ecological, social, cultural and productive characteristics of the territory which are valuable to society, and provides a means to evaluate their interaction. The occurrence of each of these other valuable characteristics in the territory is measured by generating a presence-density score for each. Considering the level of constraint each characteristic imposes on hydropower development, they are weighted against each other and an aggregate score is computed. With this information, optimal trade-offs are computed between additional hydropower capacity and valuable local characteristics over the entire domain, using the classical knapsack 0-1 optimization algorithm. Various scenarios of different weightings and hydropower development targets are tested and compared. The results illustrate the capabilities of the tool to identify promising hydropower development strategies and to aid public policy discussions aimed at establishing incentives and regulations, and therefore provide decision makers with supporting material allowing a more informed discussion.

Indoor Multi-Sensor Acquisition System for Projects on Energy Renovation of Buildings.

PubMed

Armesto, Julia; Sánchez-Villanueva, Claudio; Patiño-Cambeiro, Faustino; Patiño-Barbeito, Faustino

2016-05-28

Energy rehabilitation actions in buildings have become a great economic opportunity for the construction sector. They also constitute a strategic goal in the European Union (EU), given the energy dependence and the compromises with climate change of its member states. About 75% of existing buildings in the EU were built when energy efficiency codes had not been developed. Approximately 75% to 90% of those standing buildings are expected to remain in use in 2050. Significant advances have been achieved in energy analysis, simulation tools, and computer fluid dynamics for building energy evaluation. However, the gap between predictions and real savings might still be improved. Geomatics and computer science disciplines can really help in modelling, inspection, and diagnosis procedures. This paper presents a multi-sensor acquisition system capable of automatically and simultaneously capturing the three-dimensional geometric information, thermographic, optical, and panoramic images, ambient temperature map, relative humidity map, and light level map. The system integrates a navigation system based on a Simultaneous Localization and Mapping (SLAM) approach that allows georeferencing every data to its position in the building. The described equipment optimizes the energy inspection and diagnosis steps and facilitates the energy modelling of the building.

Indoor Multi-Sensor Acquisition System for Projects on Energy Renovation of Buildings

PubMed Central

Armesto, Julia; Sánchez-Villanueva, Claudio; Patiño-Cambeiro, Faustino; Patiño-Barbeito, Faustino

2016-01-01

Energy rehabilitation actions in buildings have become a great economic opportunity for the construction sector. They also constitute a strategic goal in the European Union (EU), given the energy dependence and the compromises with climate change of its member states. About 75% of existing buildings in the EU were built when energy efficiency codes had not been developed. Approximately 75% to 90% of those standing buildings are expected to remain in use in 2050. Significant advances have been achieved in energy analysis, simulation tools, and computer fluid dynamics for building energy evaluation. However, the gap between predictions and real savings might still be improved. Geomatics and computer science disciplines can really help in modelling, inspection, and diagnosis procedures. This paper presents a multi-sensor acquisition system capable of automatically and simultaneously capturing the three-dimensional geometric information, thermographic, optical, and panoramic images, ambient temperature map, relative humidity map, and light level map. The system integrates a navigation system based on a Simultaneous Localization and Mapping (SLAM) approach that allows georeferencing every data to its position in the building. The described equipment optimizes the energy inspection and diagnosis steps and facilitates the energy modelling of the building. PMID:27240379

Process Performance of Optima XEx Single Wafer High Energy Implanter

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

Kim, J. H.; Yoon, Jongyoon; Kondratenko, S.

2011-01-07

To meet the process requirements for well formation in future CMOS memory production, high energy implanters require more robust angle, dose, and energy control while maintaining high productivity. The Optima XEx high energy implanter meets these requirements by integrating a traditional LINAC beamline with a robust single wafer handling system. To achieve beam angle control, Optima XEx can control both the horizontal and vertical beam angles to within 0.1 degrees using advanced beam angle measurement and correction. Accurate energy calibration and energy trim functions accelerate process matching by eliminating energy calibration errors. The large volume process chamber and UDC (upstreammore » dose control) using faraday cups outside of the process chamber precisely control implant dose regardless of any chamber pressure increase due to PR (photoresist) outgassing. An optimized RF LINAC accelerator improves reliability and enables singly charged phosphorus and boron energies up to 1200 keV and 1500 keV respectively with higher beam currents. A new single wafer endstation combined with increased beam performance leads to overall increased productivity. We report on the advanced performance of Optima XEx observed during tool installation and volume production at an advanced memory fab.« less

Energy harvesting concepts for small electric unmanned systems

NASA Astrophysics Data System (ADS)

Qidwai, Muhammad A.; Thomas, James P.; Kellogg, James C.; Baucom, Jared N.

2004-07-01

In this study, we identify and survey energy harvesting technologies for small electrically powered unmanned systems designed for long-term (>1 day) time-on-station missions. An environmental energy harvesting scheme will provide long-term, energy additions to the on-board energy source. We have identified four technologies that cover a broad array of available energy sources: solar, kinetic (wind) flow, autophagous structure-power (both combustible and metal air-battery systems) and electromagnetic (EM) energy scavenging. We present existing conceptual designs, critical system components, performance, constraints and state-of-readiness for each technology. We have concluded that the solar and autophagous technologies are relatively matured for small-scale applications and are capable of moderate power output levels (>1 W). We have identified key components and possible multifunctionalities in each technology. The kinetic flow and EM energy scavenging technologies will require more in-depth study before they can be considered for implementation. We have also realized that all of the harvesting systems require design and integration of various electrical, mechanical and chemical components, which will require modeling and optimization using hybrid mechatronics-circuit simulation tools. This study provides a starting point for detailed investigation into the proposed technologies for unmanned system applications under current development.

PubChem3D: Conformer generation

PubMed Central

2011-01-01

Background PubChem, an open archive for the biological activities of small molecules, provides search and analysis tools to assist users in locating desired information. Many of these tools focus on the notion of chemical structure similarity at some level. PubChem3D enables similarity of chemical structure 3-D conformers to augment the existing similarity of 2-D chemical structure graphs. It is also desirable to relate theoretical 3-D descriptions of chemical structures to experimental biological activity. As such, it is important to be assured that the theoretical conformer models can reproduce experimentally determined bioactive conformations. In the present study, we investigate the effects of three primary conformer generation parameters (the fragment sampling rate, the energy window size, and force field variant) upon the accuracy of theoretical conformer models, and determined optimal settings for PubChem3D conformer model generation and conformer sampling. Results Using the software package OMEGA from OpenEye Scientific Software, Inc., theoretical 3-D conformer models were generated for 25,972 small-molecule ligands, whose 3-D structures were experimentally determined. Different values for primary conformer generation parameters were systematically tested to find optimal settings. Employing a greater fragment sampling rate than the default did not improve the accuracy of the theoretical conformer model ensembles. An ever increasing energy window did increase the overall average accuracy, with rapid convergence observed at 10 kcal/mol and 15 kcal/mol for model building and torsion search, respectively; however, subsequent study showed that an energy threshold of 25 kcal/mol for torsion search resulted in slightly improved results for larger and more flexible structures. Exclusion of coulomb terms from the 94s variant of the Merck molecular force field (MMFF94s) in the torsion search stage gave more accurate conformer models at lower energy windows. Overall average accuracy of reproduction of bioactive conformations was remarkably linear with respect to both non-hydrogen atom count ("size") and effective rotor count ("flexibility"). Using these as independent variables, a regression equation was developed to predict the RMSD accuracy of a theoretical ensemble to reproduce bioactive conformations. The equation was modified to give a minimum RMSD conformer sampling value to help ensure that 90% of the sampled theoretical models should contain at least one conformer within the RMSD sampling value to a "bioactive" conformation. Conclusion Optimal parameters for conformer generation using OMEGA were explored and determined. An equation was developed that provides an RMSD sampling value to use that is based on the relative accuracy to reproduce bioactive conformations. The optimal conformer generation parameters and RMSD sampling values determined are used by the PubChem3D project to generate theoretical conformer models. PMID:21272340

A benchmarking tool to evaluate computer tomography perfusion infarct core predictions against a DWI standard.

PubMed

Cereda, Carlo W; Christensen, Søren; Campbell, Bruce Cv; Mishra, Nishant K; Mlynash, Michael; Levi, Christopher; Straka, Matus; Wintermark, Max; Bammer, Roland; Albers, Gregory W; Parsons, Mark W; Lansberg, Maarten G

2016-10-01

Differences in research methodology have hampered the optimization of Computer Tomography Perfusion (CTP) for identification of the ischemic core. We aim to optimize CTP core identification using a novel benchmarking tool. The benchmarking tool consists of an imaging library and a statistical analysis algorithm to evaluate the performance of CTP. The tool was used to optimize and evaluate an in-house developed CTP-software algorithm. Imaging data of 103 acute stroke patients were included in the benchmarking tool. Median time from stroke onset to CT was 185 min (IQR 180-238), and the median time between completion of CT and start of MRI was 36 min (IQR 25-79). Volumetric accuracy of the CTP-ROIs was optimal at an rCBF threshold of <38%; at this threshold, the mean difference was 0.3 ml (SD 19.8 ml), the mean absolute difference was 14.3 (SD 13.7) ml, and CTP was 67% sensitive and 87% specific for identification of DWI positive tissue voxels. The benchmarking tool can play an important role in optimizing CTP software as it provides investigators with a novel method to directly compare the performance of alternative CTP software packages. © The Author(s) 2015.

Towards resiliency with micro-grids: Portfolio optimization and investment under uncertainty

NASA Astrophysics Data System (ADS)

Gharieh, Kaveh

Energy security and sustained supply of power are critical for community welfare and economic growth. In the face of the increased frequency and intensity of extreme weather conditions which can result in power grid outage, the value of micro-grids to improve the communities' power reliability and resiliency is becoming more important. Micro-grids capability to operate in islanded mode in stressed-out conditions, dramatically decreases the economic loss of critical infrastructure in power shortage occasions. More wide-spread participation of micro-grids in the wholesale energy market in near future, makes the development of new investment models necessary. However, market and price risks in short term and long term along with risk factors' impacts shall be taken into consideration in development of new investment models. This work proposes a set of models and tools to address different problems associated with micro-grid assets including optimal portfolio selection, investment and financing in both community and a sample critical infrastructure (i.e. wastewater treatment plant) levels. The models account for short-term operational volatilities and long-term market uncertainties. A number of analytical methodologies and financial concepts have been adopted to develop the aforementioned models as follows. (1) Capital budgeting planning and portfolio optimization models with Monte Carlo stochastic scenario generation are applied to derive the optimal investment decision for a portfolio of micro-grid assets considering risk factors and multiple sources of uncertainties. (2) Real Option theory, Monte Carlo simulation and stochastic optimization techniques are applied to obtain optimal modularized investment decisions for hydrogen tri-generation systems in wastewater treatment facilities, considering multiple sources of uncertainty. (3) Public Private Partnership (PPP) financing concept coupled with investment horizon approach are applied to estimate public and private parties' revenue shares from a community-level micro-grid project over the course of assets' lifetime considering their optimal operation under uncertainty.

Watershed Management Optimization Support Tool (WMOST) v1: User Manual and Case Study Examples

EPA Science Inventory

The Watershed Management Optimization Support Tool (WMOST) is intended to be used as a screening tool as part of an integrated watershed management process such as that described in EPA’s watershed planning handbook (EPA 2008).1 The objective of WMOST is to serve as a public-doma...

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

Zhou, S; Fan, Q; Lei, Y

Purpose: In-Water-Output-Ratio (IWOR) plays a significant role in linac-based radiotherapy treatment planning, linking MUs to delivered radiation dose. For an open rectangular field, IWOR depends on both its width and length, and changes rapidly when one of them becomes small. In this study, a universal functional form is proposed to fit the open field IWOR tables in Varian TrueBeam representative datasets for all photon energies. Methods: A novel Generalized Mean formula is first used to estimate the Equivalent Square (ES) for a rectangular field. The formula’s weighting factor and power index are determined by collapsing all data points as muchmore » as possible onto a single curve in IWOR vs. ES plot. The result is then fitted with a novel universal function IWOR=1+b*Log(ES/10cm)/(ES/10cm)^c via a least-square procedure to determine the optimal values for parameters b and c. The maximum relative residual error in IWOR over the entire two-dimensional measurement table with field sizes between 3cm and 40cm is used to evaluate the quality of fit for the function. Results: The two-step fitting strategy works very well in determining the optimal parameter values for open field IWOR of each photon energies in the Varian data-set. Relative residual error ≤0.71% is achieved for all photon energies (including Flattening-Filter-Free modes) with field sizes between 3cm and 40cm. The optimal parameter values change smoothly with regular photon beam quality. Conclusion: The universal functional form fits the Varian TrueBeam open field IWOR measurement tables accurately with small relative residual errors for all photon energies. Therefore, it can be an excellent choice to represent IWOR in absolute dose and MU calculations. The functional form can also be used as a QA/commissioning tool to verify the measured data quality and consistency by checking the IWOR data behavior against the function for new photon energies with arbitrary beam quality.« less

Comparative study of coated and uncoated tool inserts with dry machining of EN47 steel using Taguchi L9 optimization technique

NASA Astrophysics Data System (ADS)

Vasu, M.; Shivananda, Nayaka H.

2018-04-01

EN47 steel samples are machined on a self-centered lathe using Chemical Vapor Deposition of coated TiCN/Al2O3/TiN and uncoated tungsten carbide tool inserts, with nose radius 0.8mm. Results are compared with each other and optimized using statistical tool. Input (cutting) parameters that are considered in this work are feed rate (f), cutting speed (Vc), and depth of cut (ap), the optimization criteria are based on the Taguchi (L9) orthogonal array. ANOVA method is adopted to evaluate the statistical significance and also percentage contribution for each model. Multiple response characteristics namely cutting force (Fz), tool tip temperature (T) and surface roughness (Ra) are evaluated. The results discovered that coated tool insert (TiCN/Al2O3/TiN) exhibits 1.27 and 1.29 times better than the uncoated tool insert for tool tip temperature and surface roughness respectively. A slight increase in cutting force was observed for coated tools.

Urban-Climate Adaptation Tool: Optimizing Green Infrastructure

NASA Astrophysics Data System (ADS)

Fellows, J. D.; Bhaduri, B. L.

2016-12-01

Cities have an opportunity to become more resilient to future climate change and green through investments made in urban infrastructure today. However, most cities lack access to credible high-resolution climate change projection and other environmental information needed to assess and address potential vulnerabilities from future climate variability. Therefore, we present an integrated framework for developing an urban climate adaptation tool (Urban-CAT). The initial focus of Urban-CAT is to optimize the placement of green infrastructure (e.g., green roofs, porous pavements, retention basins, etc.) to be better control stormwater runoff and lower the ambient urban temperature. Urban-CAT consists of four modules. Firstly, it provides climate projections at different spatial resolutions for quantifying urban landscape. Secondly, this projected data is combined with socio-economic and other environmental data using leading and lagging indicators for assessing landscape vulnerability to climate extremes (e.g., urban flooding). Thirdly, a neighborhood scale modeling approach is presented for identifying candidate areas for adaptation strategies (e.g., green infrastructure as an adaptation strategy for urban flooding). Finally, all these capabilities are made available as a web-based tool to support decision-making and communication at the neighborhood and city levels. This presentation will highlight the methods that drive each of the modules, demo some of the capabilities using Knoxville Tennessee as a case study, and discuss the challenges of working with communities to incorporate climate change into their planning. Next steps on Urban-CAT is to additional capabilities to create a comprehensive climate adaptation tool, including energy, transportation, health, and other key urban services.

A hybrid optimization approach in non-isothermal glass molding

NASA Astrophysics Data System (ADS)

Vu, Anh-Tuan; Kreilkamp, Holger; Krishnamoorthi, Bharathwaj Janaki; Dambon, Olaf; Klocke, Fritz

2016-10-01

Intensively growing demands on complex yet low-cost precision glass optics from the today's photonic market motivate the development of an efficient and economically viable manufacturing technology for complex shaped optics. Against the state-of-the-art replication-based methods, Non-isothermal Glass Molding turns out to be a promising innovative technology for cost-efficient manufacturing because of increased mold lifetime, less energy consumption and high throughput from a fast process chain. However, the selection of parameters for the molding process usually requires a huge effort to satisfy precious requirements of the molded optics and to avoid negative effects on the expensive tool molds. Therefore, to reduce experimental work at the beginning, a coupling CFD/FEM numerical modeling was developed to study the molding process. This research focuses on the development of a hybrid optimization approach in Non-isothermal glass molding. To this end, an optimal configuration with two optimization stages for multiple quality characteristics of the glass optics is addressed. The hybrid Back-Propagation Neural Network (BPNN)-Genetic Algorithm (GA) is first carried out to realize the optimal process parameters and the stability of the process. The second stage continues with the optimization of glass preform using those optimal parameters to guarantee the accuracy of the molded optics. Experiments are performed to evaluate the effectiveness and feasibility of the model for the process development in Non-isothermal glass molding.

Beyond cost-of-energy, the value-of-energy metric and value-centric approaches to design, operations, and maintenance of wind turbines

NASA Astrophysics Data System (ADS)

Fernandes, Kevin

This thesis is oriented toward developers, owners, operators and investors of renewable energy projects. With increasing demand of renewables, our energy dependence comes down to reducing costs associated with this sector so as to compete with the existing sources. One way of valuing investment potential is to determine and then compare the overall value derived by investing in a particular project. Several engineering and financial levers, one of which is operation and maintenance, affect this value. This thesis provides a useful visual aid to owners and operators by which they can operate and maintain their wind farm so as to achieve maximum value throughout its lifetime. All the necessary components that go into developing a business model of a wind farm project will be discussed. Finally, this tool is valid within the assumptions that are explicitly stated. Real world data and trends are used to provide a practical approach to the optimization.

Closing data gaps for LCA of food products: estimating the energy demand of food processing.

PubMed

Sanjuán, Neus; Stoessel, Franziska; Hellweg, Stefanie

2014-01-21

Food is one of the most energy and CO2-intensive consumer goods. While environmental data on primary agricultural products are increasingly becoming available, there are large data gaps concerning food processing. Bridging these gaps is important; for example, the food industry can use such data to optimize processes from an environmental perspective, and retailers may use this information for purchasing decisions. Producers and retailers can then market sustainable products and deliver the information demanded by governments and consumers. Finally, consumers are increasingly interested in the environmental information of foods in order to lower their consumption impacts. This study provides estimation tools for the energy demand of a representative set of food process unit operations such as dehydration, evaporation, or pasteurization. These operations are used to manufacture a variety of foods and can be combined, according to the product recipe, to quantify the heat and electricity demand during processing. In combination with inventory data on the production of the primary ingredients, this toolbox will be a basis to perform life cycle assessment studies of a large number of processed food products and to provide decision support to the stakeholders. Furthermore, a case study is performed to illustrate the application of the tools.

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

NASA Astrophysics Data System (ADS)

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

2014-10-01

Consistently collecting the earth's climate signatures remains a priority for world governments and international scientific organizations. Architecting a solution requires transforming scientific missions into an optimized robust `operational' constellation that addresses the needs of decision makers, scientific investigators and global users for trusted data. The application of new tools offers pathways for global architecture collaboration. Recent (2014) rulebased decision engine modeling runs that targeted optimizing the intended NPOESS architecture, becomes a surrogate for global operational climate monitoring architecture(s). This rule-based systems tools provide valuable insight for Global climate architectures, through the comparison and evaluation of alternatives considered and the exhaustive range of trade space explored. A representative optimization of Global ECV's (essential climate variables) climate monitoring architecture(s) is explored and described in some detail with thoughts on appropriate rule-based valuations. The optimization tools(s) suggest and support global collaboration pathways and hopefully elicit responses from the audience and climate science shareholders.

Preliminary Development of an Object-Oriented Optimization Tool

NASA Technical Reports Server (NTRS)

Pak, Chan-gi

2011-01-01

The National Aeronautics and Space Administration Dryden Flight Research Center has developed a FORTRAN-based object-oriented optimization (O3) tool that leverages existing tools and practices and allows easy integration and adoption of new state-of-the-art software. The object-oriented framework can integrate the analysis codes for multiple disciplines, as opposed to relying on one code to perform analysis for all disciplines. Optimization can thus take place within each discipline module, or in a loop between the central executive module and the discipline modules, or both. Six sample optimization problems are presented. The first four sample problems are based on simple mathematical equations; the fifth and sixth problems consider a three-bar truss, which is a classical example in structural synthesis. Instructions for preparing input data for the O3 tool are presented.

Comparative analysis for various redox flow batteries chemistries using a cost performance model

NASA Astrophysics Data System (ADS)

Crawford, Alasdair; Viswanathan, Vilayanur; Stephenson, David; Wang, Wei; Thomsen, Edwin; Reed, David; Li, Bin; Balducci, Patrick; Kintner-Meyer, Michael; Sprenkle, Vincent

2015-10-01

The total energy storage system cost is determined by means of a robust performance-based cost model for multiple flow battery chemistries. Systems aspects such as shunt current losses, pumping losses and various flow patterns through electrodes are accounted for. The system cost minimizing objective function determines stack design by optimizing the state of charge operating range, along with current density and current-normalized flow. The model cost estimates are validated using 2-kW stack performance data for the same size electrodes and operating conditions. Using our validated tool, it has been demonstrated that an optimized all-vanadium system has an estimated system cost of < 350 kWh-1 for 4-h application. With an anticipated decrease in component costs facilitated by economies of scale from larger production volumes, coupled with performance improvements enabled by technology development, the system cost is expected to decrease to 160 kWh-1 for a 4-h application, and to 100 kWh-1 for a 10-h application. This tool has been shared with the redox flow battery community to enable cost estimation using their stack data and guide future direction.

Visual prosthesis wireless energy transfer system optimal modeling.

PubMed

Li, Xueping; Yang, Yuan; Gao, Yong

2014-01-16

Wireless energy transfer system is an effective way to solve the visual prosthesis energy supply problems, theoretical modeling of the system is the prerequisite to do optimal energy transfer system design. On the basis of the ideal model of the wireless energy transfer system, according to visual prosthesis application condition, the system modeling is optimized. During the optimal modeling, taking planar spiral coils as the coupling devices between energy transmitter and receiver, the effect of the parasitic capacitance of the transfer coil is considered, and especially the concept of biological capacitance is proposed to consider the influence of biological tissue on the energy transfer efficiency, resulting in the optimal modeling's more accuracy for the actual application. The simulation data of the optimal model in this paper is compared with that of the previous ideal model, the results show that under high frequency condition, the parasitic capacitance of inductance and biological capacitance considered in the optimal model could have great impact on the wireless energy transfer system. The further comparison with the experimental data verifies the validity and accuracy of the optimal model proposed in this paper. The optimal model proposed in this paper has a higher theoretical guiding significance for the wireless energy transfer system's further research, and provide a more precise model reference for solving the power supply problem in visual prosthesis clinical application.

Visual prosthesis wireless energy transfer system optimal modeling

PubMed Central

2014-01-01

Background Wireless energy transfer system is an effective way to solve the visual prosthesis energy supply problems, theoretical modeling of the system is the prerequisite to do optimal energy transfer system design. Methods On the basis of the ideal model of the wireless energy transfer system, according to visual prosthesis application condition, the system modeling is optimized. During the optimal modeling, taking planar spiral coils as the coupling devices between energy transmitter and receiver, the effect of the parasitic capacitance of the transfer coil is considered, and especially the concept of biological capacitance is proposed to consider the influence of biological tissue on the energy transfer efficiency, resulting in the optimal modeling’s more accuracy for the actual application. Results The simulation data of the optimal model in this paper is compared with that of the previous ideal model, the results show that under high frequency condition, the parasitic capacitance of inductance and biological capacitance considered in the optimal model could have great impact on the wireless energy transfer system. The further comparison with the experimental data verifies the validity and accuracy of the optimal model proposed in this paper. Conclusions The optimal model proposed in this paper has a higher theoretical guiding significance for the wireless energy transfer system’s further research, and provide a more precise model reference for solving the power supply problem in visual prosthesis clinical application. PMID:24428906

OPTIMAL WELL LOCATOR (OWL): A SCREENING TOOL FOR EVALUATING LOCATIONS OF MONITORING WELLS: USER'S GUIDE VERSION 1.2

EPA Science Inventory

The Optimal Well Locator ( OWL) program was designed and developed by USEPA to be a screening tool to evaluate and optimize the placement of wells in long term monitoring networks at small sites. The first objective of the OWL program is to allow the user to visualize the change ...

Metabolic engineering tools in model cyanobacteria.

PubMed

Carroll, Austin L; Case, Anna E; Zhang, Angela; Atsumi, Shota

2018-03-26

Developing sustainable routes for producing chemicals and fuels is one of the most important challenges in metabolic engineering. Photoautotrophic hosts are particularly attractive because of their potential to utilize light as an energy source and CO 2 as a carbon substrate through photosynthesis. Cyanobacteria are unicellular organisms capable of photosynthesis and CO 2 fixation. While engineering in heterotrophs, such as Escherichia coli, has result in a plethora of tools for strain development and hosts capable of producing valuable chemicals efficiently, these techniques are not always directly transferable to cyanobacteria. However, recent efforts have led to an increase in the scope and scale of chemicals that cyanobacteria can produce. Adaptations of important metabolic engineering tools have also been optimized to function in photoautotrophic hosts, which include Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)-Cas9, 13 C Metabolic Flux Analysis (MFA), and Genome-Scale Modeling (GSM). This review explores innovations in cyanobacterial metabolic engineering, and highlights how photoautotrophic metabolism has shaped their development. Copyright © 2018 International Metabolic Engineering Society. Published by Elsevier Inc. All rights reserved.

Energy-optimal path planning in the coastal ocean

NASA Astrophysics Data System (ADS)

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

2017-05-01

We integrate data-driven ocean modeling with the stochastic Dynamically Orthogonal (DO) level-set optimization methodology to compute and study energy-optimal paths, speeds, and headings for ocean vehicles in the Middle-Atlantic Bight (MAB) region. We hindcast the energy-optimal paths from among exact time-optimal paths for the period 28 August 2006 to 9 September 2006. To do so, we first obtain a data-assimilative multiscale reanalysis, combining ocean observations with implicit two-way nested multiresolution primitive-equation simulations of the tidal-to-mesoscale dynamics in the region. Second, we solve the reduced-order stochastic DO level-set partial differential equations (PDEs) to compute the joint probability of minimum arrival time, vehicle-speed time series, and total energy utilized. Third, for each arrival time, we select the vehicle-speed time series that minimize the total energy utilization from the marginal probability of vehicle-speed and total energy. The corresponding energy-optimal path and headings are obtained through the exact particle-backtracking equation. Theoretically, the present methodology is PDE-based and provides fundamental energy-optimal predictions without heuristics. Computationally, it is 3-4 orders of magnitude faster than direct Monte Carlo methods. For the missions considered, we analyze the effects of the regional tidal currents, strong wind events, coastal jets, shelfbreak front, and other local circulations on the energy-optimal paths. Results showcase the opportunities for vehicles that intelligently utilize the ocean environment to minimize energy usage, rigorously integrating ocean forecasting with optimal control of autonomous vehicles.

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

NASA Astrophysics Data System (ADS)

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

2014-05-01

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

Exploring How Technology Growth Limits Impact Optimal Carbon dioxide Mitigation Pathways

EPA Science Inventory

Energy system optimization models prescribe the optimal mix of technologies and fuels for meeting energy demands over a time horizon, subject to energy supplies, demands, and other constraints. When optimizing, these models will, to the extent allowed, favor the least cost combin...

Energy-optimal electrical excitation of nerve fibers.

PubMed

Jezernik, Saso; Morari, Manfred

2005-04-01

We derive, based on an analytical nerve membrane model and optimal control theory of dynamical systems, an energy-optimal stimulation current waveform for electrical excitation of nerve fibers. Optimal stimulation waveforms for nonleaky and leaky membranes are calculated. The case with a leaky membrane is a realistic case. Finally, we compare the waveforms and energies necessary for excitation of a leaky membrane in the case where the stimulation waveform is a square-wave current pulse, and in the case of energy-optimal stimulation. The optimal stimulation waveform is an exponentially rising waveform and necessitates considerably less energy to excite the nerve than a square-wave pulse (especially true for larger pulse durations). The described theoretical results can lead to drastically increased battery lifetime and/or decreased energy transmission requirements for implanted biomedical systems.

Flyby Geometry Optimization Tool

NASA Technical Reports Server (NTRS)

Karlgaard, Christopher D.

2007-01-01

The Flyby Geometry Optimization Tool is a computer program for computing trajectories and trajectory-altering impulsive maneuvers for spacecraft used in radio relay of scientific data to Earth from an exploratory airplane flying in the atmosphere of Mars.

Data and Tools | Concentrating Solar Power | NREL

Science.gov Websites

download. Solar Power tower Integrated Layout and Optimization Tool (SolarPILOT(tm)) The SolarPILOT is code rapid layout and optimization capability of the analytical DELSOL3 program with the accuracy and

Watershed Management Optimization Support Tool (WMOST) Webinar

EPA Science Inventory

This webinar will highlight version 3 of EPA’s Watershed Management Optimization Support Tool (WMOST). WMOST facilitates implementation of integrated water management by communities, utilities, watershed management organizations, consultants, and others. There can be many o...

Alternative Fuel Transportation Optimization Tool : Description, Methodology, and Demonstration Scenarios.

DOT National Transportation Integrated Search

2015-09-01

This report describes an Alternative Fuel Transportation Optimization Tool (AFTOT), developed by the U.S. Department of Transportation (DOT) Volpe National Transportation Systems Center (Volpe) in support of the Federal Aviation Administration (FAA)....

Integration of Dakota into the NEAMS Workbench

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

Swiler, Laura Painton; Lefebvre, Robert A.; Langley, Brandon R.

2017-07-01

This report summarizes a NEAMS (Nuclear Energy Advanced Modeling and Simulation) project focused on integrating Dakota into the NEAMS Workbench. The NEAMS Workbench, developed at Oak Ridge National Laboratory, is a new software framework that provides a graphical user interface, input file creation, parsing, validation, job execution, workflow management, and output processing for a variety of nuclear codes. Dakota is a tool developed at Sandia National Laboratories that provides a suite of uncertainty quantification and optimization algorithms. Providing Dakota within the NEAMS Workbench allows users of nuclear simulation codes to perform uncertainty and optimization studies on their nuclear codes frommore » within a common, integrated environment. Details of the integration and parsing are provided, along with an example of Dakota running a sampling study on the fuels performance code, BISON, from within the NEAMS Workbench.« less

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

An optimized method to calculate error correction capability of tool influence function in frequency domain

NASA Astrophysics Data System (ADS)

Wang, Jia; Hou, Xi; Wan, Yongjian; Shi, Chunyan

2017-10-01

An optimized method to calculate error correction capability of tool influence function (TIF) in certain polishing conditions will be proposed based on smoothing spectral function. The basic mathematical model for this method will be established in theory. A set of polishing experimental data with rigid conformal tool is used to validate the optimized method. The calculated results can quantitatively indicate error correction capability of TIF for different spatial frequency errors in certain polishing conditions. The comparative analysis with previous method shows that the optimized method is simpler in form and can get the same accuracy results with less calculating time in contrast to previous method.

Perceptual attraction in tool use: evidence for a reliability-based weighting mechanism.

PubMed

Debats, Nienke B; Ernst, Marc O; Heuer, Herbert

2017-04-01

Humans are well able to operate tools whereby their hand movement is linked, via a kinematic transformation, to a spatially distant object moving in a separate plane of motion. An everyday example is controlling a cursor on a computer monitor. Despite these separate reference frames, the perceived positions of the hand and the object were found to be biased toward each other. We propose that this perceptual attraction is based on the principles by which the brain integrates redundant sensory information of single objects or events, known as optimal multisensory integration. That is, 1 ) sensory information about the hand and the tool are weighted according to their relative reliability (i.e., inverse variances), and 2 ) the unisensory reliabilities sum up in the integrated estimate. We assessed whether perceptual attraction is consistent with optimal multisensory integration model predictions. We used a cursor-control tool-use task in which we manipulated the relative reliability of the unisensory hand and cursor position estimates. The perceptual biases shifted according to these relative reliabilities, with an additional bias due to contextual factors that were present in experiment 1 but not in experiment 2 The biased position judgments' variances were, however, systematically larger than the predicted optimal variances. Our findings suggest that the perceptual attraction in tool use results from a reliability-based weighting mechanism similar to optimal multisensory integration, but that certain boundary conditions for optimality might not be satisfied. NEW & NOTEWORTHY Kinematic tool use is associated with a perceptual attraction between the spatially separated hand and the effective part of the tool. We provide a formal account for this phenomenon, thereby showing that the process behind it is similar to optimal integration of sensory information relating to single objects. Copyright © 2017 the American Physiological Society.

Energy services in the information age: The convergence of energy, communications, and information technologies

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

Centolella, P.A.

1998-07-01

Most of the economic efficiency benefits of electric restructuring--consumer choice based on price and risk preferences, efficient capacity utilization, capacity expansion that reflects marketability, and innovative products--depend upon consumer access to information and opportunities to respond to time- and location-specific prices and customized products. Information and communications technologies from back-room data management centers to intelligent consumer gateways will play an essential role in marketing energy services in a retail access environment. This paper describes the role of information and communications technology in electric industry restructuring and retailing of energy services. It includes a survey of economic analyses on the likelymore » variability in competitive generation prices and consumer responses if such prices are effectively communicated. The paper describes the potential benefits and cost savings associated with flexible consumer responses to price variability. It identifies consumer loads and preferences. Finally, the paper describes the building blocks of information systems being developed to facilitate price-responsive energy management and provide a range of other energy services. Intelligent gateways, analytical tools for facility load prediction and optimizing energy management responses, and electronic commerce applications are discussed.« less

Process and Energy Optimization Assessment, Rock Island Arsenal, IL

DTIC Science & Technology

2004-09-01

Approved for public release; distribution is unlimited. ER D C /C ER L TR -0 4- 17 Process and Energy Optimization Assessment Rock Island... Optimization Assessment: Rock Island Arsenal, IL Mike C.J. Lin, Alexander M. Zhivov, and Veera M. Boddu, Construction Engineering Research...and Energy Optimization Assessment (PEOA) was conducted at Rock Island Arsenal (RIA), IL to identify process, energy, and environmental opportunities

Using Delft3D to Simulate Current Energy Conversion

NASA Astrophysics Data System (ADS)

James, S. C.; Chartrand, C.; Roberts, J.

2015-12-01

As public concern with renewable energy increases, current energy conversion (CEC) technology is being developed to optimize energy output and minimize environmental impact. CEC turbines generate energy from tidal and current systems and create wakes that interact with turbines located downstream of a device. The placement of devices can greatly influence power generation and structural reliability. CECs can also alter the ecosystem process surrounding the turbines, such as flow regimes, sediment dynamics, and water quality. Software is needed to investigate specific CEC sites to simulate power generation and hydrodynamic responses of a flow through a CEC turbine array. This work validates Delft3D against several flume experiments by simulating the power generation and hydrodynamic response of flow through a turbine or actuator disc(s). Model parameters are then calibrated against these data sets to reproduce momentum removal and wake recovery data with 3-D flow simulations. Simulated wake profiles and turbulence intensities compare favorably to the experimental data and demonstrate the utility and accuracy of a fast-running tool for future siting and analysis of CEC arrays in complex domains.

On use of ZPR research reactors and associated instrumentation and measurement methods for reactor physics studies

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

Chauvin, J.P.; Blaise, P.; Lyoussi, A.

2015-07-01

The French atomic and alternative energies -CEA- is strongly involved in research and development programs concerning the use of nuclear energy as a clean and reliable source of energy and consequently is working on the present and future generation of reactors on various topics such as ageing plant management, optimization of the plutonium stockpile, waste management and innovative systems exploration. Core physics studies are an essential part of this comprehensive R and D effort. In particular, the Zero Power Reactor (ZPR) of CEA: EOLE, MINERVE and MASURCA play an important role in the validation of neutron (as well photon) physicsmore » calculation tools (codes and nuclear data). The experimental programs defined in the CEA's ZPR facilities aim at improving the calculation routes by reducing the uncertainties of the experimental databases. They also provide accurate data on innovative systems in terms of new materials (moderating and decoupling materials) and new concepts (ADS, ABWR, new MTR (e.g. JHR), GENIV) involving new fuels, absorbers and coolant materials. Conducting such interesting experimental R and D programs is based on determining and measuring main parameters of phenomena of interest to qualify calculation tools and nuclear data 'libraries'. Determining these parameters relies on the use of numerous and different experimental techniques using specific and appropriate instrumentation and detection tools. Main ZPR experimental programs at CEA, their objectives and challenges will be presented and discussed. Future development and perspectives regarding ZPR reactors and associated programs will be also presented. (authors)« less

Real-time Crystal Growth Visualization and Quantification by Energy-Resolved Neutron Imaging

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

Tremsin, Anton S.; Perrodin, Didier; Losko, Adrian S.

Energy-resolved neutron imaging is investigated as a real-time diagnostic tool for visualization and in-situ measurements of "blind" processes. This technique is demonstrated for the Bridgman-type crystal growth enabling remote and direct measurements of growth parameters crucial for process optimization. The location and shape of the interface between liquid and solid phases are monitored in real-time, concurrently with the measurement of elemental distribution within the growth volume and with the identification of structural features with a ~100 μm spatial resolution. Such diagnostics can substantially reduce the development time between exploratory small scale growth of new materials and their subsequent commercial production.more » This technique is widely applicable and is not limited to crystal growth processes.« less

Logistics in a low carbon concept: Connotation and realization way

NASA Astrophysics Data System (ADS)

Zheng, Chaocheng; Qiu, Xiaoying; Mao, Jiarong

2017-01-01

Low-carbon logistics has become a trend for the logistics industry-as a high-energy consumption industry, continuation of its previous operating mode has been significantly behind the times. So logistics industry must release lower carbon emissions. This paper sort out the literature home and abroad from three aspects, that is, the definition of low-carbon logistics, low-carbon logistics implementation mechanisms or measures, and low carbon design quantitative models. The research shows: low-carbon logistics needed to implemented both in enterprise' macro and micro level, which means the government should provide relevant policy support and micro enterprises should be actively sought from all sectors of the logistics in energy saving. In practice, low-carbon logistics optimization models are effective tools for enterprises to implement emission reduction.

Additive Manufacturing of a Microbial Fuel Cell—A detailed study

PubMed Central

Calignano, Flaviana; Tommasi, Tonia; Manfredi, Diego; Chiolerio, Alessandro

2015-01-01

In contemporary society we observe an everlasting permeation of electron devices, smartphones, portable computing tools. The tiniest living organisms on Earth could become the key to address this challenge: energy generation by bacterial processes from renewable stocks/waste through devices such as microbial fuel cells (MFCs). However, the application of this solution was limited by a moderately low efficiency. We explored the limits, if any, of additive manufacturing (AM) technology to fabricate a fully AM-based powering device, exploiting low density, open porosities able to host the microbes, systems easy to fuel continuously and to run safely. We obtained an optimal energy recovery close to 3 kWh m−3 per day that can power sensors and low-power appliances, allowing data processing and transmission from remote/harsh environments. PMID:26611142

Real-time Crystal Growth Visualization and Quantification by Energy-Resolved Neutron Imaging

DOE PAGES

Tremsin, Anton S.; Perrodin, Didier; Losko, Adrian S.; ...

2017-04-20

Energy-resolved neutron imaging is investigated as a real-time diagnostic tool for visualization and in-situ measurements of "blind" processes. This technique is demonstrated for the Bridgman-type crystal growth enabling remote and direct measurements of growth parameters crucial for process optimization. The location and shape of the interface between liquid and solid phases are monitored in real-time, concurrently with the measurement of elemental distribution within the growth volume and with the identification of structural features with a ~100 μm spatial resolution. Such diagnostics can substantially reduce the development time between exploratory small scale growth of new materials and their subsequent commercial production.more » This technique is widely applicable and is not limited to crystal growth processes.« less

Additive Manufacturing of a Microbial Fuel Cell—A detailed study

NASA Astrophysics Data System (ADS)

Calignano, Flaviana; Tommasi, Tonia; Manfredi, Diego; Chiolerio, Alessandro

2015-11-01

In contemporary society we observe an everlasting permeation of electron devices, smartphones, portable computing tools. The tiniest living organisms on Earth could become the key to address this challenge: energy generation by bacterial processes from renewable stocks/waste through devices such as microbial fuel cells (MFCs). However, the application of this solution was limited by a moderately low efficiency. We explored the limits, if any, of additive manufacturing (AM) technology to fabricate a fully AM-based powering device, exploiting low density, open porosities able to host the microbes, systems easy to fuel continuously and to run safely. We obtained an optimal energy recovery close to 3 kWh m-3 per day that can power sensors and low-power appliances, allowing data processing and transmission from remote/harsh environments.

An Automated Treatment Plan Quality Control Tool for Intensity-Modulated Radiation Therapy Using a Voxel-Weighting Factor-Based Re-Optimization Algorithm.

PubMed

Song, Ting; Li, Nan; Zarepisheh, Masoud; Li, Yongbao; Gautier, Quentin; Zhou, Linghong; Mell, Loren; Jiang, Steve; Cerviño, Laura

2016-01-01

Intensity-modulated radiation therapy (IMRT) currently plays an important role in radiotherapy, but its treatment plan quality can vary significantly among institutions and planners. Treatment plan quality control (QC) is a necessary component for individual clinics to ensure that patients receive treatments with high therapeutic gain ratios. The voxel-weighting factor-based plan re-optimization mechanism has been proved able to explore a larger Pareto surface (solution domain) and therefore increase the possibility of finding an optimal treatment plan. In this study, we incorporated additional modules into an in-house developed voxel weighting factor-based re-optimization algorithm, which was enhanced as a highly automated and accurate IMRT plan QC tool (TPS-QC tool). After importing an under-assessment plan, the TPS-QC tool was able to generate a QC report within 2 minutes. This QC report contains the plan quality determination as well as information supporting the determination. Finally, the IMRT plan quality can be controlled by approving quality-passed plans and replacing quality-failed plans using the TPS-QC tool. The feasibility and accuracy of the proposed TPS-QC tool were evaluated using 25 clinically approved cervical cancer patient IMRT plans and 5 manually created poor-quality IMRT plans. The results showed high consistency between the QC report quality determinations and the actual plan quality. In the 25 clinically approved cases that the TPS-QC tool identified as passed, a greater difference could be observed for dosimetric endpoints for organs at risk (OAR) than for planning target volume (PTV), implying that better dose sparing could be achieved in OAR than in PTV. In addition, the dose-volume histogram (DVH) curves of the TPS-QC tool re-optimized plans satisfied the dosimetric criteria more frequently than did the under-assessment plans. In addition, the criteria for unsatisfied dosimetric endpoints in the 5 poor-quality plans could typically be satisfied when the TPS-QC tool generated re-optimized plans without sacrificing other dosimetric endpoints. In addition to its feasibility and accuracy, the proposed TPS-QC tool is also user-friendly and easy to operate, both of which are necessary characteristics for clinical use.

Nonlinear Shaping Architecture Designed with Using Evolutionary Structural Optimization Tools

NASA Astrophysics Data System (ADS)

Januszkiewicz, Krystyna; Banachowicz, Marta

2017-10-01

The paper explores the possibilities of using Structural Optimization Tools (ESO) digital tools in an integrated structural and architectural design in response to the current needs geared towards sustainability, combining ecological and economic efficiency. The first part of the paper defines the Evolutionary Structural Optimization tools, which were developed specifically for engineering purposes using finite element analysis as a framework. The development of ESO has led to several incarnations, which are all briefly discussed (Additive ESO, Bi-directional ESO, Extended ESO). The second part presents result of using these tools in structural and architectural design. Actual building projects which involve optimization as a part of the original design process will be presented (Crematorium in Kakamigahara Gifu, Japan, 2006 SANAA“s Learning Centre, EPFL in Lausanne, Switzerland 2008 among others). The conclusion emphasizes that the structural engineering and architectural design mean directing attention to the solutions which are used by Nature, designing works optimally shaped and forming their own environments. Architectural forms never constitute the optimum shape derived through a form-finding process driven only by structural optimization, but rather embody and integrate a multitude of parameters. It might be assumed that there is a similarity between these processes in nature and the presented design methods. Contemporary digital methods make the simulation of such processes possible, and thus enable us to refer back to the empirical methods of previous generations.

Application of the advanced engineering environment for optimization energy consumption in designed vehicles

NASA Astrophysics Data System (ADS)

Monica, Z.; Sękala, A.; Gwiazda, A.; Banaś, W.

2016-08-01

Nowadays a key issue is to reduce the energy consumption of road vehicles. In particular solution one could find different strategies of energy optimization. The most popular but not sophisticated is so called eco-driving. In this strategy emphasized is particular behavior of drivers. In more sophisticated solution behavior of drivers is supported by control system measuring driving parameters and suggesting proper operation of the driver. The other strategy is concerned with application of different engineering solutions that aid optimization the process of energy consumption. Such systems take into consideration different parameters measured in real time and next take proper action according to procedures loaded to the control computer of a vehicle. The third strategy bases on optimization of the designed vehicle taking into account especially main sub-systems of a technical mean. In this approach the optimal level of energy consumption by a vehicle is obtained by synergetic results of individual optimization of particular constructional sub-systems of a vehicle. It is possible to distinguish three main sub-systems: the structural one the drive one and the control one. In the case of the structural sub-system optimization of the energy consumption level is related with the optimization or the weight parameter and optimization the aerodynamic parameter. The result is optimized body of a vehicle. Regarding the drive sub-system the optimization of the energy consumption level is related with the fuel or power consumption using the previously elaborated physical models. Finally the optimization of the control sub-system consists in determining optimal control parameters.

2D and 3D registration methods for dual-energy contrast-enhanced digital breast tomosynthesis

NASA Astrophysics Data System (ADS)

Lau, Kristen C.; Roth, Susan; Maidment, Andrew D. A.

2014-03-01

Contrast-enhanced digital breast tomosynthesis (CE-DBT) uses an iodinated contrast agent to image the threedimensional breast vasculature. The University of Pennsylvania is conducting a CE-DBT clinical study in patients with known breast cancers. The breast is compressed continuously and imaged at four time points (1 pre-contrast; 3 postcontrast). A hybrid subtraction scheme is proposed. First, dual-energy (DE) images are obtained by a weighted logarithmic subtraction of the high-energy and low-energy image pairs. Then, post-contrast DE images are subtracted from the pre-contrast DE image. This hybrid temporal subtraction of DE images is performed to analyze iodine uptake, but suffers from motion artifacts. Employing image registration further helps to correct for motion, enhancing the evaluation of vascular kinetics. Registration using ANTS (Advanced Normalization Tools) is performed in an iterative manner. Mutual information optimization first corrects large-scale motions. Normalized cross-correlation optimization then iteratively corrects fine-scale misalignment. Two methods have been evaluated: a 2D method using a slice-by-slice approach, and a 3D method using a volumetric approach to account for out-of-plane breast motion. Our results demonstrate that iterative registration qualitatively improves with each iteration (five iterations total). Motion artifacts near the edge of the breast are corrected effectively and structures within the breast (e.g. blood vessels, surgical clip) are better visualized. Statistical and clinical evaluations of registration accuracy in the CE-DBT images are ongoing.

Optimization of Shipboard Manning Levels Using Imprint Pro Forces Module

DTIC Science & Technology

2015-09-01

NPS-OR-15-008 NAVAL POSTGRADUATE SCHOOL MONTEREY, CALIFORNIA OPTIMIZATION OF SHIPBOARD MANNING LEVELS USING IMPRINT PRO...Optimization of Shipboard Manning Levels Using IMPRINT Pro Forces Module 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER...ABSTRACT The Improved Performance Research Integration Tool ( IMPRINT ) is a dynamic, stochastic, discrete-event modeling tool used to develop a model

Hull Form Design and Optimization Tool Development

DTIC Science & Technology

2012-07-01

global minimum. The algorithm accomplishes this by using a method known as metaheuristics which allows the algorithm to examine a large area by...further development of these tools including the implementation and testing of a new optimization algorithm , the improvement of a rapid hull form...under the 2012 Naval Research Enterprise Intern Program. 15. SUBJECT TERMS hydrodynamic, hull form, generation, optimization, algorithm

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

PubMed

Zhang, Lilong; Cao, Tong; Liu, Da

2017-04-01

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

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.

Blended near-optimal tools for flexible water resources decision making

NASA Astrophysics Data System (ADS)

Rosenberg, David

2015-04-01

State-of-the-art systems analysis techniques focus on efficiently finding optimal solutions. Yet an optimal solution is optimal only for the static modelled issues and managers often seek near-optimal alternatives that address un-modelled or changing objectives, preferences, limits, uncertainties, and other issues. Early on, Modelling to Generate Alternatives (MGA) formalized near-optimal as performance within a tolerable deviation from the optimal objective function value and identified a few maximally-different alternatives that addressed select un-modelled issues. This paper presents new stratified, Monte Carlo Markov Chain sampling and parallel coordinate plotting tools that generate and communicate the structure and full extent of the near-optimal region to an optimization problem. Plot controls allow users to interactively explore region features of most interest. Controls also streamline the process to elicit un-modelled issues and update the model formulation in response to elicited issues. Use for a single-objective water quality management problem at Echo Reservoir, Utah identifies numerous and flexible practices to reduce the phosphorus load to the reservoir and maintain close-to-optimal performance. Compared to MGA, the new blended tools generate more numerous alternatives faster, more fully show the near-optimal region, help elicit a larger set of un-modelled issues, and offer managers greater flexibility to cope in a changing world.

Habitat Design Optimization and Analysis

NASA Technical Reports Server (NTRS)

SanSoucie, Michael P.; Hull, Patrick V.; Tinker, Michael L.

2006-01-01

Long-duration surface missions to the Moon and Mars will require habitats for the astronauts. The materials chosen for the habitat walls play a direct role in the protection against the harsh environments found on the surface. Choosing the best materials, their configuration, and the amount required is extremely difficult due to the immense size of the design region. Advanced optimization techniques are necessary for habitat wall design. Standard optimization techniques are not suitable for problems with such large search spaces; therefore, a habitat design optimization tool utilizing genetic algorithms has been developed. Genetic algorithms use a "survival of the fittest" philosophy, where the most fit individuals are more likely to survive and reproduce. This habitat design optimization tool is a multi-objective formulation of structural analysis, heat loss, radiation protection, and meteoroid protection. This paper presents the research and development of this tool.

Advanced Structural Optimization Under Consideration of Cost Tracking

NASA Astrophysics Data System (ADS)

Zell, D.; Link, T.; Bickelmaier, S.; Albinger, J.; Weikert, S.; Cremaschi, F.; Wiegand, A.

2014-06-01

In order to improve the design process of launcher configurations in the early development phase, the software Multidisciplinary Optimization (MDO) was developed. The tool combines different efficient software tools such as Optimal Design Investigations (ODIN) for structural optimizations, Aerospace Trajectory Optimization Software (ASTOS) for trajectory and vehicle design optimization for a defined payload and mission.The present paper focuses to the integration and validation of ODIN. ODIN enables the user to optimize typical axis-symmetric structures by means of sizing the stiffening designs concerning strength and stability while minimizing the structural mass. In addition a fully automatic finite element model (FEM) generator module creates ready-to-run FEM models of a complete stage or launcher assembly.Cost tracking respectively future improvements concerning cost optimization are indicated.

Hybrid ABC Optimized MARS-Based Modeling of the Milling Tool Wear from Milling Run Experimental Data

PubMed Central

García Nieto, Paulino José; García-Gonzalo, Esperanza; Ordóñez Galán, Celestino; Bernardo Sánchez, Antonio

2016-01-01

Milling cutters are important cutting tools used in milling machines to perform milling operations, which are prone to wear and subsequent failure. In this paper, a practical new hybrid model to predict the milling tool wear in a regular cut, as well as entry cut and exit cut, of a milling tool is proposed. The model was based on the optimization tool termed artificial bee colony (ABC) in combination with multivariate adaptive regression splines (MARS) technique. This optimization mechanism involved the parameter setting in the MARS training procedure, which significantly influences the regression accuracy. Therefore, an ABC–MARS-based model was successfully used here to predict the milling tool flank wear (output variable) as a function of the following input variables: the time duration of experiment, depth of cut, feed, type of material, etc. Regression with optimal hyperparameters was performed and a determination coefficient of 0.94 was obtained. The ABC–MARS-based model's goodness of fit to experimental data confirmed the good performance of this model. This new model also allowed us to ascertain the most influential parameters on the milling tool flank wear with a view to proposing milling machine's improvements. Finally, conclusions of this study are exposed. PMID:28787882

Hybrid ABC Optimized MARS-Based Modeling of the Milling Tool Wear from Milling Run Experimental Data.

PubMed

García Nieto, Paulino José; García-Gonzalo, Esperanza; Ordóñez Galán, Celestino; Bernardo Sánchez, Antonio

2016-01-28

Milling cutters are important cutting tools used in milling machines to perform milling operations, which are prone to wear and subsequent failure. In this paper, a practical new hybrid model to predict the milling tool wear in a regular cut, as well as entry cut and exit cut, of a milling tool is proposed. The model was based on the optimization tool termed artificial bee colony (ABC) in combination with multivariate adaptive regression splines (MARS) technique. This optimization mechanism involved the parameter setting in the MARS training procedure, which significantly influences the regression accuracy. Therefore, an ABC-MARS-based model was successfully used here to predict the milling tool flank wear (output variable) as a function of the following input variables: the time duration of experiment, depth of cut, feed, type of material, etc . Regression with optimal hyperparameters was performed and a determination coefficient of 0.94 was obtained. The ABC-MARS-based model's goodness of fit to experimental data confirmed the good performance of this model. This new model also allowed us to ascertain the most influential parameters on the milling tool flank wear with a view to proposing milling machine's improvements. Finally, conclusions of this study are exposed.

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

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

Zhou, Nan; Marnay, Chris; Firestone, Ryan

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

Design and Control of Integrated Systems for Hydrogen Production and Power Generation

NASA Astrophysics Data System (ADS)

Georgis, Dimitrios

Growing concerns on CO2 emissions have led to the development of highly efficient power plants. Options for increased energy efficiencies include alternative energy conversion pathways, energy integration and process intensification. Solid oxide fuel cells (SOFC) constitute a promising alternative for power generation since they convert the chemical energy electrochemically directly to electricity. Their high operating temperature shows potential for energy integration with energy intensive units (e.g. steam reforming reactors). Although energy integration is an essential tool for increased efficiencies, it leads to highly complex process schemes with rich dynamic behavior, which are challenging to control. Furthermore, the use of process intensification for increased energy efficiency imposes an additional control challenge. This dissertation identifies and proposes solutions on design, operational and control challenges of integrated systems for hydrogen production and power generation. Initially, a study on energy integrated SOFC systems is presented. Design alternatives are identified, control strategies are proposed for each alternative and their validity is evaluated under different operational scenarios. The operational range of the proposed control strategies is also analyzed. Next, thermal management of water gas shift membrane reactors, which are a typical application of process intensification, is considered. Design and operational objectives are identified and a control strategy is proposed employing advanced control algorithms. The performance of the proposed control strategy is evaluated and compared with classical control strategies. Finally SOFC systems for combined heat and power applications are considered. Multiple recycle loops are placed to increase design flexibility. Different operational objectives are identified and a nonlinear optimization problem is formulated. Optimal designs are obtained and their features are discussed and compared. The results of the dissertation provide a deeper understanding on the design, operational and control challenges of the above systems and can potentially guide further commercialization efforts. In addition to this, the results can be generalized and used for applications from the transportation and residential sector to large--scale power plants.

OPTIMIZING BMP PLACEMENT AT WATERSHED-SCALE USING SUSTAIN

EPA Science Inventory

Watershed and stormwater managers need modeling tools to evaluate alternative plans for environmental quality restoration and protection needs in urban and developing areas. A watershed-scale decision-support system, based on cost optimization, provides an essential tool to suppo...

Physical Modeling of Contact Processes on the Cutting Tools Surfaces of STM When Turning

NASA Astrophysics Data System (ADS)

Belozerov, V. A.; Uteshev, M. H.

2016-08-01

This article describes how to create an optimization model of the process of fine turning of superalloys and steel tools from STM on CNC machines, flexible manufacturing units (GPM), machining centers. Creation of the optimization model allows you to link (unite) contact processes simultaneously on the front and back surfaces of the tool from STM to manage contact processes and the dynamic strength of the cutting tool at the top of the STM. Established optimization model of management of the dynamic strength of the incisors of the STM in the process of fine turning is based on a previously developed thermomechanical (physical, heat) model, which allows the system thermomechanical approach to choosing brands STM (domestic and foreign) for cutting tools from STM designed for fine turning of heat resistant alloys and steels.

Spinoff 2009

NASA Technical Reports Server (NTRS)

2009-01-01

Topics covered include: Image-Capture Devices Extend Medicine's Reach; Medical Devices Assess, Treat Balance Disorders; NASA Bioreactors Advance Disease Treatments; Robotics Algorithms Provide Nutritional Guidelines; "Anti-Gravity" Treadmills Speed Rehabilitation; Crew Management Processes Revitalize Patient Care; Hubble Systems Optimize Hospital Schedules; Web-based Programs Assess Cognitive Fitness; Electrolyte Concentrates Treat Dehydration; Tools Lighten Designs, Maintain Structural Integrity; Insulating Foams Save Money, Increase Safety; Polyimide Resins Resist Extreme Temperatures; Sensors Locate Radio Interference; Surface Operations Systems Improve Airport Efficiency; Nontoxic Resins Advance Aerospace Manufacturing; Sensors Provide Early Warning of Biological Threats; Robot Saves Soldier's Lives Overseas (MarcBot); Apollo-Era Life Raft Saves Hundreds of Sailors; Circuits Enhance Scientific Instruments and Safety Devices; Tough Textiles Protect Payloads and Public Safety Officers; Forecasting Tools Point to Fishing Hotspots; Air Purifiers Eliminate Pathogens, Preserve Food; Fabrics Protect Sensitive Skin from UV Rays; Phase Change Fabrics Control Temperature; Tiny Devices Project Sharp, Colorful Images; Star-Mapping Tools Enable Tracking of Endangered Animals; Nanofiber Filters Eliminate Contaminants; Modeling Innovations Advance Wind Energy Industry; Thermal Insulation Strips Conserve Energy; Satellite Respondent Buoys Identify Ocean Debris; Mobile Instruments Measure Atmospheric Pollutants; Cloud Imagers Offer New Details on Earth's Health; Antennas Lower Cost of Satellite Access; Feature Detection Systems Enhance Satellite Imagery; Chlorophyll Meters Aid Plant Nutrient Management; Telemetry Boards Interpret Rocket, Airplane Engine Data; Programs Automate Complex Operations Monitoring; Software Tools Streamline Project Management; Modeling Languages Refine Vehicle Design; Radio Relays Improve Wireless Products; Advanced Sensors Boost Optical Communication, Imaging; Tensile Fabrics Enhance Architecture Around the World; Robust Light Filters Support Powerful Imaging Devices; Thermoelectric Devices Cool, Power Electronics; Innovative Tools Advance Revolutionary Weld Technique; Methods Reduce Cost, Enhance Quality of Nanotubes; Gauging Systems Monitor Cryogenic Liquids; Voltage Sensors Monitor Harmful Static; and Compact Instruments Measure Heat Potential.

Spinoff 2010

NASA Technical Reports Server (NTRS)

2010-01-01

Topics covered include: Burnishing Techniques Strengthen Hip Implants; Signal Processing Methods Monitor Cranial Pressure; Ultraviolet-Blocking Lenses Protect, Enhance Vision; Hyperspectral Systems Increase Imaging Capabilities; Programs Model the Future of Air Traffic Management; Tail Rotor Airfoils Stabilize Helicopters, Reduce Noise; Personal Aircraft Point to the Future of Transportation; Ducted Fan Designs Lead to Potential New Vehicles; Winglets Save Billions of Dollars in Fuel Costs; Sensor Systems Collect Critical Aerodynamics Data; Coatings Extend Life of Engines and Infrastructure; Radiometers Optimize Local Weather Prediction; Energy-Efficient Systems Eliminate Icing Danger for UAVs; Rocket-Powered Parachutes Rescue Entire Planes; Technologies Advance UAVs for Science, Military; Inflatable Antennas Support Emergency Communication; Smart Sensors Assess Structural Health; Hand-Held Devices Detect Explosives and Chemical Agents; Terahertz Tools Advance Imaging for Security, Industry; LED Systems Target Plant Growth; Aerogels Insulate Against Extreme Temperatures; Image Sensors Enhance Camera Technologies; Lightweight Material Patches Allow for Quick Repairs; Nanomaterials Transform Hairstyling Tools; Do-It-Yourself Additives Recharge Auto Air Conditioning; Systems Analyze Water Quality in Real Time; Compact Radiometers Expand Climate Knowledge; Energy Servers Deliver Clean, Affordable Power; Solutions Remediate Contaminated Groundwater; Bacteria Provide Cleanup of Oil Spills, Wastewater; Reflective Coatings Protect People and Animals; Innovative Techniques Simplify Vibration Analysis; Modeling Tools Predict Flow in Fluid Dynamics; Verification Tools Secure Online Shopping, Banking; Toolsets Maintain Health of Complex Systems; Framework Resources Multiply Computing Power; Tools Automate Spacecraft Testing, Operation; GPS Software Packages Deliver Positioning Solutions; Solid-State Recorders Enhance Scientific Data Collection; Computer Models Simulate Fine Particle Dispersion; Composite Sandwich Technologies Lighten Components; Cameras Reveal Elements in the Short Wave Infrared; Deformable Mirrors Correct Optical Distortions; Stitching Techniques Advance Optics Manufacturing; Compact, Robust Chips Integrate Optical Functions; Fuel Cell Stations Automate Processes, Catalyst Testing; Onboard Systems Record Unique Videos of Space Missions; Space Research Results Purify Semiconductor Materials; and Toolkits Control Motion of Complex Robotics.

Bacterial cell-free expression technology to in vitro systems engineering and optimization.

PubMed

Caschera, Filippo

2017-06-01

Cell-free expression system is a technology for the synthesis of proteins in vitro . The system is a platform for several bioengineering projects, e.g. cell-free metabolic engineering, evolutionary design of experiments, and synthetic minimal cell construction. Bacterial cell-free protein synthesis system (CFPS) is a robust tool for synthetic biology. The bacteria lysate, the DNA, and the energy module, which are the three optimized sub-systems for in vitro protein synthesis, compose the integrated system. Currently, an optimized E. coli cell-free expression system can produce up to ∼2.3 mg/mL of a fluorescent reporter protein. Herein, I will describe the features of ATP-regeneration systems for in vitro protein synthesis, and I will present a machine-learning experiment for optimizing the protein yield of E. coli cell-free protein synthesis systems. Moreover, I will introduce experiments on the synthesis of a minimal cell using liposomes as dynamic containers, and E. coli cell-free expression system as biochemical platform for metabolism and gene expression. CFPS can be further integrated with other technologies for novel applications in environmental, medical and material science.

OPTIMAL AIRCRAFT TRAJECTORIES FOR SPECIFIED RANGE

NASA Technical Reports Server (NTRS)

Lee, H.

1994-01-01

For an aircraft operating over a fixed range, the operating costs are basically a sum of fuel cost and time cost. While minimum fuel and minimum time trajectories are relatively easy to calculate, the determination of a minimum cost trajectory can be a complex undertaking. This computer program was developed to optimize trajectories with respect to a cost function based on a weighted sum of fuel cost and time cost. As a research tool, the program could be used to study various characteristics of optimum trajectories and their comparison to standard trajectories. It might also be used to generate a model for the development of an airborne trajectory optimization system. The program could be incorporated into an airline flight planning system, with optimum flight plans determined at takeoff time for the prevailing flight conditions. The use of trajectory optimization could significantly reduce the cost for a given aircraft mission. The algorithm incorporated in the program assumes that a trajectory consists of climb, cruise, and descent segments. The optimization of each segment is not done independently, as in classical procedures, but is performed in a manner which accounts for interaction between the segments. This is accomplished by the application of optimal control theory. The climb and descent profiles are generated by integrating a set of kinematic and dynamic equations, where the total energy of the aircraft is the independent variable. At each energy level of the climb and descent profiles, the air speed and power setting necessary for an optimal trajectory are determined. The variational Hamiltonian of the problem consists of the rate of change of cost with respect to total energy and a term dependent on the adjoint variable, which is identical to the optimum cruise cost at a specified altitude. This variable uniquely specifies the optimal cruise energy, cruise altitude, cruise Mach number, and, indirectly, the climb and descent profiles. If the optimum cruise cost is specified, an optimum trajectory can easily be generated; however, the range obtained for a particular optimum cruise cost is not known a priori. For short range flights, the program iteratively varies the optimum cruise cost until the computed range converges to the specified range. For long-range flights, iteration is unnecessary since the specified range can be divided into a cruise segment distance and full climb and descent distances. The user must supply the program with engine fuel flow rate coefficients and an aircraft aerodynamic model. The program currently includes coefficients for the Pratt-Whitney JT8D-7 engine and an aerodynamic model for the Boeing 727. Input to the program consists of the flight range to be covered and the prevailing flight conditions including pressure, temperature, and wind profiles. Information output by the program includes: optimum cruise tables at selected weights, optimal cruise quantities as a function of cruise weight and cruise distance, climb and descent profiles, and a summary of the complete synthesized optimal trajectory. This program is written in FORTRAN IV for batch execution and has been implemented on a CDC 6000 series computer with a central memory requirement of approximately 100K (octal) of 60 bit words. This aircraft trajectory optimization program was developed in 1979.

HyPEP FY06 Report: Models and Methods

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

DOE report

2006-09-01

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

Parametric study of transport beam lines for electron beams accelerated by laser-plasma interaction

NASA Astrophysics Data System (ADS)

Scisciò, M.; Lancia, L.; Migliorati, M.; Mostacci, A.; Palumbo, L.; Papaphilippou, Y.; Antici, P.

2016-03-01

In the last decade, laser-plasma acceleration of high-energy electrons has attracted strong attention in different fields. Electrons with maximum energies in the GeV range can be laser-accelerated within a few cm using multi-hundreds terawatt (TW) lasers, yielding to very high beam currents at the source (electron bunches with up to tens-hundreds of pC in a few fs). While initially the challenge was to increase the maximum achievable electron energy, today strong effort is put in the control and usability of these laser-generated beams that still lack of some features in order to be used for applications where currently conventional, radio-frequency (RF) based, electron beam lines represent the most common and efficient solution. Several improvements have been suggested for this purpose, some of them acting directly on the plasma source, some using beam shaping tools located downstream. Concerning the latter, several studies have suggested the use of conventional accelerator magnetic devices (such as quadrupoles and solenoids) as an easy implementable solution when the laser-plasma accelerated beam requires optimization. In this paper, we report on a parametric study related to the transport of electron beams accelerated by laser-plasma interaction, using conventional accelerator elements and tools. We focus on both, high energy electron beams in the GeV range, as produced on petawatt (PW) class laser systems, and on lower energy electron beams in the hundreds of MeV range, as nowadays routinely obtained on commercially available multi-hundred TW laser systems. For both scenarios, our study allows understanding what are the crucial parameters that enable laser-plasma accelerators to compete with conventional ones and allow for a beam transport. We show that suitable working points require a tradeoff-combination between low beam divergence and narrow energy spread.

Accelerated development of Zr-containing new generation ferritic steels for advanced nuclear reactors

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

Tan, Lizhen; Yang, Ying; Sridharan, K.

2015-12-01

The mission of the Nuclear Energy Enabling Technologies (NEET) program is to develop crosscutting technologies for nuclear energy applications. Advanced structural materials with superior performance at elevated temperatures are always desired for nuclear reactors, which can improve reactor economics, safety margins, and design flexibility. They benefit not only new reactors, including advanced light water reactors (LWRs) and fast reactors such as the sodium-cooled fast reactor (SFR) that is primarily designed for management of high-level wastes, but also life extension of the existing fleet when component exchange is needed. Developing and utilizing the modern materials science tools (experimental, theoretical, and computationalmore » tools) is an important path to more efficient alloy development and process optimization. The ultimate goal of this project is, with the aid of computational modeling tools, to accelerate the development of Zr-bearing ferritic alloys that can be fabricated using conventional steelmaking methods. The new alloys are expected to have superior high-temperature creep performance and excellent radiation resistance as compared to Grade 91. The designed alloys were fabricated using arc-melting and drop-casting, followed by hot rolling and conventional heat treatments. Comprehensive experimental studies have been conducted on the developed alloys to evaluate their hardness, tensile properties, creep resistance, Charpy impact toughness, and aging resistance, as well as resistance to proton and heavy ion (Fe 2+) irradiation.« less

Home | BEopt

Science.gov Websites

BEopt - Building Energy Optimization BEopt NREL - National Renewable Energy Laboratory Primary Energy Optimization) software provides capabilities to evaluate residential building designs and identify sequential search optimization technique used by BEopt: Finds minimum-cost building designs at different

Energy and Process Optimization Assessment, Fort Stewart, GA

DTIC Science & Technology

2006-04-01

ER D C/ CE R L TR -0 6 -8 Energy and Process Optimization Assessment Fort Stewart, GA John L. Vavrin, Alexander M. Zhivov, William T...distribution is unlimited. ERDC/CERL TR-06-8 April 2006 Energy and Process Optimization Assessment Fort Stewart, GA John L. Vavrin, Alexander...U.S. Army Corps of Engineers Washington, DC 20314-1000 Under Work Unit 33143 ERDC/CERL TR-06-8 ii Abstract: An Energy and Process Optimization

Topology Optimization for Energy Management in Underwater Sensor Networks

DTIC Science & Technology

2015-02-01

1 To appear in International Journal of Control as a regular paper Topology Optimization for Energy Management in Underwater Sensor Networks ⋆ Devesh...K. Jha1 Thomas A. Wettergren2 Asok Ray1 Kushal Mukherjee3 Keywords: Underwater Sensor Network , Energy Management, Pareto Optimization, Adaptation...Optimization for Energy Management in Underwater Sensor Networks 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d

CNV detection method optimized for high-resolution arrayCGH by normality test.

PubMed

Ahn, Jaegyoon; Yoon, Youngmi; Park, Chihyun; Park, Sanghyun

2012-04-01

High-resolution arrayCGH platform makes it possible to detect small gains and losses which previously could not be measured. However, current CNV detection tools fitted to early low-resolution data are not applicable to larger high-resolution data. When CNV detection tools are applied to high-resolution data, they suffer from high false-positives, which increases validation cost. Existing CNV detection tools also require optimal parameter values. In most cases, obtaining these values is a difficult task. This study developed a CNV detection algorithm that is optimized for high-resolution arrayCGH data. This tool operates up to 1500 times faster than existing tools on a high-resolution arrayCGH of whole human chromosomes which has 42 million probes whose average length is 50 bases, while preserving false positive/negative rates. The algorithm also uses a normality test, thereby removing the need for optimal parameters. To our knowledge, this is the first formulation for CNV detecting problems that results in a near-linear empirical overall complexity for real high-resolution data. Copyright © 2012 Elsevier Ltd. All rights reserved.

From Zero Energy Buildings to Zero Energy Districts

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

Polly, Ben; Kutscher, Chuck; Macumber, Dan

Some U.S. cities are planning advanced districts that have goals for zero energy, water, waste, and/or greenhouse gas emissions. From an energy perspective, zero energy districts present unique opportunities to cost-effectively achieve high levels of energy efficiency and renewable energy penetration across a collection of buildings that may be infeasible at the individual building scale. These high levels of performance are accomplished through district energy systems that harness renewable and wasted energy at large scales and flexible building loads that coordinate with variable renewable energy supply. Unfortunately, stakeholders face a lack of documented processes, tools, and best practices to assistmore » them in achieving zero energy districts. The National Renewable Energy Laboratory (NREL) is partnering on two new district projects in Denver: the National Western Center and the Sun Valley Neighborhood. We are working closely with project stakeholders in their zero energy master planning efforts to develop the resources needed to resolve barriers and create replicable processes to support future zero energy district efforts across the United States. Initial results of these efforts include the identification and description of key zero energy district design principles (maximizing building efficiency, solar potential, renewable thermal energy, and load control), economic drivers, and master planning principles. The work has also resulted in NREL making initial enhancements to the U.S. Department of Energy's open source building energy modeling platform (OpenStudio and EnergyPlus) with the long-term goal of supporting the design and optimization of energy districts.« less

10 CFR 434.606 - Simulation tool.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 10 Energy 3 2010-01-01 2010-01-01 false Simulation tool. 434.606 Section 434.606 Energy DEPARTMENT OF ENERGY ENERGY CONSERVATION ENERGY CODE FOR NEW FEDERAL COMMERCIAL AND MULTI-FAMILY HIGH RISE RESIDENTIAL BUILDINGS Building Energy Compliance Alternative § 434.606 Simulation tool. 606.1 The criteria...

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

NASA Astrophysics Data System (ADS)

Fernandez, J.

2015-06-01

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

Application of simulation models for the optimization of business processes

NASA Astrophysics Data System (ADS)

Jašek, Roman; Sedláček, Michal; Chramcov, Bronislav; Dvořák, Jiří

2016-06-01

The paper deals with the applications of modeling and simulation tools in the optimization of business processes, especially in solving an optimization of signal flow in security company. As a modeling tool was selected Simul8 software that is used to process modeling based on discrete event simulation and which enables the creation of a visual model of production and distribution processes.

Enforcing elemental mass and energy balances for reduced order models

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

Ma, J.; Agarwal, K.; Sharma, P.

2012-01-01

Development of economically feasible gasification and carbon capture, utilization and storage (CCUS) technologies requires a variety of software tools to optimize the designs of not only the key devices involved (e., g., gasifier, CO{sub 2} adsorber) but also the entire power generation system. High-fidelity models such as Computational Fluid Dynamics (CFD) models are capable of accurately simulating the detailed flow dynamics, heat transfer, and chemistry inside the key devices. However, the integration of CFD models within steady-state process simulators, and subsequent optimization of the integrated system, still presents significant challenges due to the scale differences in both time and length,more » as well the high computational cost. A reduced order model (ROM) generated from a high-fidelity model can serve as a bridge between the models of different scales. While high-fidelity models are built upon the principles of mass, momentum, and energy conservations, ROMs are usually developed based on regression-type equations and hence their predictions may violate the mass and energy conservation laws. A high-fidelity model may also have the mass and energy balance problem if it is not tightly converged. Conservations of mass and energy are important when a ROM is integrated to a flowsheet for the process simulation of the entire chemical or power generation system, especially when recycle streams are connected to the modeled device. As a part of the Carbon Capture Simulation Initiative (CCSI) project supported by the U.S. Department of Energy, we developed a software framework for generating ROMs from CFD simulations and integrating them with Process Modeling Environments (PMEs) for system-wide optimization. This paper presents a method to correct the results of a high-fidelity model or a ROM such that the elemental mass and energy are conserved perfectly. Correction factors for the flow rates of individual species in the product streams are solved using a minimization algorithm based on Lagrangian multiplier method. Enthalpies of product streams are also modified to enforce the energy balance. The approach is illustrated for two ROMs, one based on a CFD model of an entrained-flow gasifier and the other based on the CFD model of a multiphase CO{sub 2} adsorber.« less

A simulation-optimization-based decision support tool for mitigating traffic congestion.

DOT National Transportation Integrated Search

2009-12-01

"Traffic congestion has grown considerably in the United States over the past twenty years. In this paper, we develop : a robust decision support tool based on simulation optimization to evaluate and recommend congestion-mitigation : strategies to tr...

Spatial optimization of cropping pattern for sustainable food and biofuel production with minimal downstream pollution.

PubMed

Femeena, P V; Sudheer, K P; Cibin, R; Chaubey, I

2018-04-15

Biofuel has emerged as a substantial source of energy in many countries. In order to avoid the 'food versus fuel competition', arising from grain-based ethanol production, the United States has passed regulations that require second generation or cellulosic biofeedstocks to be used for majority of the biofuel production by 2022. Agricultural residue, such as corn stover, is currently the largest source of cellulosic feedstock. However, increased harvesting of crops residue may lead to increased application of fertilizers in order to recover the soil nutrients lost from the residue removal. Alternatively, introduction of less-fertilizer intensive perennial grasses such as switchgrass (Panicum virgatum L.) and Miscanthus (Miscanthus x giganteus Greef et Deu.) can be a viable source for biofuel production. Even though these grasses are shown to reduce nutrient loads to a great extent, high production cost have constrained their wide adoptability to be used as a viable feedstock. Nonetheless, there is an opportunity to optimize feedstock production to meet bioenergy demand while improving water quality. This study presents a multi-objective simulation optimization framework using Soil and Water Assessment Tool (SWAT) and Multi Algorithm Genetically Adaptive Method (AMALGAM) to develop optimal cropping pattern with minimum nutrient delivery and minimum biomass production cost. Computational time required for optimization was significantly reduced by loose coupling SWAT with an external in-stream solute transport model. Optimization was constrained by food security and biofuel production targets that ensured not more than 10% reduction in grain yield and at least 100 million gallons of ethanol production. A case study was carried out in St. Joseph River Watershed that covers 280,000 ha area in the Midwest U.S. Results of the study indicated that introduction of corn stover removal and perennial grass production reduce nitrate and total phosphorus loads without compromising on food and biofuel production. Optimization runs yielded an optimal cropping pattern with 32% of watershed area in stover removal, 15% in switchgrass and 2% in Miscanthus. The optimal scenario resulted in 14% reduction in nitrate and 22% reduction in total phosphorus from the baseline. This framework can be used as an effective tool to take decisions regarding environmentally and economically sustainable strategies to minimize the nutrient delivery at minimal biomass production cost, while simultaneously meeting food and biofuel production targets. Copyright © 2018 Elsevier Ltd. All rights reserved.

Development of optimal grinding and polishing tools for aspheric surfaces

NASA Astrophysics Data System (ADS)

Burge, James H.; Anderson, Bill; Benjamin, Scott; Cho, Myung K.; Smith, Koby Z.; Valente, Martin J.

2001-12-01

The ability to grind and polish steep aspheric surfaces to high quality is limited by the tools used for working the surface. The optician prefers to use large, stiff tools to get good natural smoothing, avoiding small scale surface errors. This is difficult for steep aspheres because the tools must have sufficient compliance to fit the aspheric surface, yet we wish the tools to be stiff so they wear down high regions on the surface. This paper presents a toolkit for designing optimal tools that provide large scale compliance to fit the aspheric surface, yet maintain small scale stiffness for efficient polishing.

An optimization tool for satellite equipment layout

NASA Astrophysics Data System (ADS)

Qin, Zheng; Liang, Yan-gang; Zhou, Jian-ping

2018-01-01

Selection of the satellite equipment layout with performance constraints is a complex task which can be viewed as a constrained multi-objective optimization and a multiple criteria decision making problem. The layout design of a satellite cabin involves the process of locating the required equipment in a limited space, thereby satisfying various behavioral constraints of the interior and exterior environments. The layout optimization of satellite cabin in this paper includes the C.G. offset, the moments of inertia and the space debris impact risk of the system, of which the impact risk index is developed to quantify the risk to a satellite cabin of coming into contact with space debris. In this paper an optimization tool for the integration of CAD software as well as the optimization algorithms is presented, which is developed to automatically find solutions for a three-dimensional layout of equipment in satellite. The effectiveness of the tool is also demonstrated by applying to the layout optimization of a satellite platform.

On a computational model of building thermal dynamic response

NASA Astrophysics Data System (ADS)

Jarošová, Petra; Vala, Jiří

2016-07-01

Development and exploitation of advanced materials, structures and technologies in civil engineering, both for buildings with carefully controlled interior temperature and for common residential houses, together with new European and national directives and technical standards, stimulate the development of rather complex and robust, but sufficiently simple and inexpensive computational tools, supporting their design and optimization of energy consumption. This paper demonstrates the possibility of consideration of such seemingly contradictory requirements, using the simplified non-stationary thermal model of a building, motivated by the analogy with the analysis of electric circuits; certain semi-analytical forms of solutions come from the method of lines.

Analysis of the prospective energy interconnections in Northeast Asia and development of the data portal

NASA Astrophysics Data System (ADS)

Churkin, Andrey; Bialek, Janusz

2018-01-01

Development of power interconnections in Northeast Asia becomes not only engineering but also a political issue. More research institutes are involved in the Asian Super Grid initiative discussion, as well as more politicians mention power interconnection opportunities. UNESCAP started providing a platform for intragovernmental discussion of the issue. However, there are still a lack of comprehensive modern research of the Asian Super Grid. Moreover, there is no unified data base and no unified power routes concept. Therefore, this article discusses a tool for optimal power routes selection and suggest a concept of the unified data portal.

A Data Driven Pre-cooling Framework for Energy Cost Optimization in Commercial Buildings

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

Vishwanath, Arun; Chandan, Vikas; Mendoza, Cameron

Commercial buildings consume significant amount of energy. Facility managers are increasingly grappling with the problem of reducing their buildings’ peak power, overall energy consumption and energy bills. In this paper, we first develop an optimization framework – based on a gray box model for zone thermal dynamics – to determine a pre-cooling strategy that simultaneously shifts the peak power to low energy tariff regimes, and reduces both the peak power and overall energy consumption by exploiting the flexibility in a building’s thermal comfort range. We then evaluate the efficacy of the pre-cooling optimization framework by applying it to building managementmore » system data, spanning several days, obtained from a large commercial building located in a tropical region of the world. The results from simulations show that optimal pre-cooling reduces peak power by over 50%, energy consumption by up to 30% and energy bills by up to 37%. Next, to enable ease of use of our framework, we also propose a shortest path based heuristic algorithmfor solving the optimization problemand show that it has comparable erformance with the optimal solution. Finally, we describe an application of the proposed optimization framework for developing countries to reduce the dependency on expensive fossil fuels, which are often used as a source for energy backup.We conclude by highlighting our real world deployment of the optimal pre-cooling framework via a software service on the cloud platform of a major provider. Our pre-cooling methodology, based on the gray box optimization framework, incurs no capital expense and relies on data readily available from a building management system, thus enabling facility managers to take informed decisions for improving the energy and cost footprints of their buildings« less

NREL's Energy Storage and REopt Teams Awarded $525k from TCF to Study

Science.gov Websites

Commercial Viability of Optimal, Reliable Building-Integrated Energy Storage | News | NREL NREL's Energy Storage and REopt Teams Awarded $525k from TCF to Study Commercial Viability of Optimal Study Commercial Viability of Optimal, Reliable Building-Integrated Energy Storage November 14, 2017

Economic optimization of operations for hybrid energy systems under variable markets

DOE PAGES

Chen, Jen; Garcia, Humberto E.

2016-05-21

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