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At least 163 records · Page 9

A TOPAS model for lens-based proton radiography

Abstract Objective. Proton Radiography can be used in conjunction with proton therapy for patient positioning, real-time estimates of stopping power, and adaptive therapy in regions with motion. The modeling capability shown here can be used to evaluate lens-based radiography as an instantaneous proton-based radiographic technique. The utilization of user-friendly Monte Carlo program TOPAS enables collaborators and other users to easily conduct medical- and therapy- based simulations of the Los Alamos Neutron Science Center (LANSCE). The resulting transport model is an open-source Monte Carlo package for simulations of proton and heavy ion therapy treatments and concurrent particle imaging. Approach. The four-quadrupole, magnetic lens system of the 800-MeV proton beamline at LANSCE is modeled in TOPAS. Several imaging and contrast objects were modelled to assess transmission at energies from 230–930 MeV and different levels of particle collimation. At different proton energies, the strength of the magnetic field was scaled according to βγ, the inverse product of particle relativistic velocity and particle momentum. Main results. Materials with high atomic number, Z, (gold, gallium, bone-equivalent) generated more contrast than materials with low-Z (water, lung-equivalent, adipose-equivalent). A 5-mrad collimator was beneficial for tissue-to-contrast agent contrast, while a 10-mrad collimator was best to distinguish between different high-Z materials. Assessment with a step-wedge phantom showed water-equivalent path length did not scale directly according to predicted values but could be mapped more accurately with calibration. Poor image quality was observed at low energies (230 MeV), but improved as proton energy increased, with sub-mm resolution at 630 MeV. Significance. Proton radiography becomes viable for shallow bone structures at 330 MeV, and for deeper structures at 630 MeV. Visibility improves with use of high-Z contrast agents. This modality may be particularly viable at carbon therapy centers with accelerators capable of delivering high energy protons and could be performed with carbon therapy.

60 APPLIED LIFE SCIENCES↗

Real-time Simulation Model of a Vanadium Redox Flow Battery Energy Storage System with Power Electronics Integration

This paper presents a real-time (RT) model of a 20 kW multi-stack vanadium redox flow battery (VRFB) system including power electronics converters in a single real-time framework. Implemented on a Typhoon HIL 604 device, this model is designed to simulate the operation of the flow battery with system-level controls. To provide a realistic overview of a VRFB system, the model incorporates a closed-loop control system for managing the speeds of two centrifugal pumps and an electro-thermal model of the battery stacks, enabling realtime temperature estimation. Furthermore, a two-stage power electronics topology and associated control solution are presented, operating with distinct strategies for interfacing the battery model with the main grid and a local load. Results from simulations demonstrate that the VRFB model is well suited for RT environment, and system can manage power during both charging and discharging cycles, while a SCADA monitor is used to display critical variables for safe, efficient, and reliable operation of the VRFB systems.

Rezende Da Costa Reis Kimpara, Renata [ORNL] (ORCI↗

Quantifying radiation quality for space relevant radiation types: Fitting excess risk models to three combined HZE-irradiated mouse datasets

Radiation health risks are predominantly derived from low linear energy transfer (LET) terrestrial exposures; however, space radiation includes exposure to high-LET and high-charge, high-energy (HZE) particles. Accurately quantifying the differences in radiation quality between the space and terrestrial radiation environments is important for assessing and predicting health risks for astronauts. Weil et al. 2009 and 2014 used two different inbred mouse strains to study differences in hepatocellular carcinoma (HCC) tumorigenesis after exposures to low- and high- LET radiation. More recently, Edmundson et al. 2020 provided valuable new tumor data in outbred mice that were exposed to low- and high-LET radiation. The present study aims to rigorously investigate a relative biological effectiveness (RBE) factor by leveraging the HCC tumor data from Weil et al. 2009, Weil et al. 2014, and Edmundson et al. 2020. The three experiments were similarly designed, allowing the raw data to be combined into a pooled dataset to estimate excess relative risk (ERR) and excess absolute risk (EAR) models using Bayesian Poisson regression. These effect estimates from the pooled data provide greater power to calculate a data driven RBE. Extensive sensitivity analyses test the robustness of RBE estimates to various model assumptions. The following questions will be explored through the sensitivity analyses: • Is the shape of the dose response different for low-LET radiation and HZE radiation, indicating that RBE is a function of dose? • Does attained age modify the effect estimates differently for low-LET radiation and HZE radiation, indicating RBE is a function of attained age? • Are the effect estimates and RBE estimates different for inbred mouse strains and outbred mouse strains? • Do assumptions about differences in ERR models and EAR models change the estimated RBE? Additional studies would be needed to validate the findings from these exploratory analyses.

Lori J. Chappell↗

An Adaptive-Importance-Sampling-Enhanced Bayesian Approach for Topology Estimation in an Unbalanced Power Distribution System

The reliable operation of a power distribution system relies on a good prior knowledge of its topology and its system state. Although crucial, due to the lack of direct monitoring devices on the switch statuses, the topology information is often unavailable or outdated for the distribution system operators for real-time applications. Apart from the limited observability of the power distribution system, other challenges are the nonlinearity of the model, the complicated, unbalanced structure of the distribution system, and the scale of the system. To overcome the above challenges, we, in this paper, propose a Bayesian-inference framework that allows us to simultaneously estimate the topology and the state of a three-phase, unbalanced power distribution system. Specifically, by using the very limited number of measurements available that are associated with the forecast load data, we efficiently recover the full Bayesian posterior distributions of the system topology under both normal and outage operation conditions. This is performed through an adaptive importance sampling procedure that greatly alleviates the computational burden of the traditional Monte-Carlo (MC)-sampling-based approach while maintaining a good estimation accuracy. The simulations conducted on the IEEE 123-bus test system and an unbalanced 1282-bus system reveal the excellent performances of the proposed method.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Analytic Neural Network Gaussian Process Enabled Chance-Constrained Voltage Regulation for Active Distribution Systems with PVs, Batteries and EVs

This paper proposes an analytic neural network Gaussian process (NNGP)-based chance-constrained real-time voltage regulation method for active distribution systems with photovoltaics (PVs), batteries, and electric vehicles (EVs). NNGP can utilize historical measurement data to achieve real-time probabilistic node voltage estimation through Bayesian inference. Then, NNGP is fully analytically embedded into the optimal power flow model to perform voltage regulation and adapt to various topological changes. The uncertainties of voltage estimations are easily considered via the chance constraint, and it has been shown that the adoption of this chance constraint can significantly improve the reliability of voltage regulation under various scenarios. The comparison results with other methods, carried out on a real 759-node distribution system located in western Colorado, U.S., show that the proposed method can achieve accurate voltage estimation across different topologies and reliably perform voltage regulation considering PVs, batteries, and EVs.

active distribution systems↗

System and Method for Modeling the Flow Performance Features of an Object

The method and apparatus includes a neural network for generating a model of an object in a wind tunnel from performance data on the object. The network is trained from test input signals (e.g., leading edge flap position, trailing edge flap position, angle of attack, and other geometric configurations, and power settings) and test output signals (e.g., lift, drag, pitching moment, or other performance features). In one embodiment, the neural network training method employs a modified Levenberg-Marquardt optimization technique. The model can be generated 'real time' as wind tunnel testing proceeds. Once trained, the model is used to estimate performance features associated with the aircraft given geometric configuration and/or power setting input. The invention can also be applied in other similar static flow modeling applications in aerodynamics, hydrodynamics, fluid dynamics, and other such disciplines. For example, the static testing of cars, sails, and foils, propellers, keels, rudders, turbines, fins, and the like, in a wind tunnel, water trough, or other flowing medium.

Jorgensen, Charles↗

The Atacama Cosmology Telescope: Cosmological Parameters from the 2008 Power Spectrum

We present cosmological parameters derived from the angular power spectrum of the cosmic microwave background (CMB) radiation observed at 148 GHz and 218 GHz over 296 deg(exp 2) with the Atacama Cosmology Telescope (ACT) during its 2008 season. ACT measures fluctuations at scales 500 < l < 10,000. We fit a model for the lensed CMB, Sunyaev-Zel'dovich (SZ), and foreground contribution to the 148 GHz and 218 GHz power spectra, including thermal and kinetic SZ, Poisson power from radio and infrared point sources, and clustered power from infrared point sources. At l = 3000, about half the power at 148 GHz comes from primary CMB after masking bright radio sources. The power from thermal and kinetic SZ is estimated to be Beta(sub 3000) is identical to 6.8 +/- 2.9 mu K (exp 2), where Beta (sub l) is identical to l(l + 1) C(sub l)/2pi. The IR Poisson power at 148 GHz is Bewta(sub 3000) 7.8 +/- 0.7 muK(exp 2) (C(sub l) = 5.5 +/- 0.5 nK(exp 2)), and a clustered IR component is required with Beta (sub 3000) = 4.6 +/- 0.9 muK(exp 2), assuming an analytic model for its power spectrum shape. At 218 GHz only about 15% of the power, approximately 27 mu K(exp 2), is CMB anisotropy at l = 3000. The remaining 85% is attributed to IR sources (approximately 50% Poisson and 35% clustered), with spectral index alpha = 3.69 +/- 0.14 for flux scaling as S(nu) varies as nu(sup alpha). We estimate primary cosmological parameters from the less contaminated 148 GHz spectrum, marginalizing over SZ and source power. The ACDM cosmological model is a good fit to the data (chi square/dof = 29/46), and ACDM parameters estimated from ACT+Wilkinson Microwave Anisotropy Probe (WMAP) are consistent with the seven-year WMAP limits, with scale invariant n(sub s) = 1 excluded at 99.7% confidence level (CL) (3 sigma). A model with no CMB lensing is disfavored at 2.8 sigma. By measuring the third to seventh acoustic peaks, and probing the Silk damping regime, the ACT data improve limits on cosmological parameters that affect the small-scale CMB power. The ACT data combined with WMAP give a 6 sigma detection of primordial helium, with Y(sub p) = 0.313 +/- 0.044, and a 4 sigma detection of relativistic species, assumed to be neutrinos, with N(sub eff) = 5.3 +/- 1.3 (4.6 +/- 0.8 with BAO+H(sub 0) data). From the CMB alone the running of the spectral index is constrained to be d(sub s) / d ln k = -0,034 +/- 0,018, the limit on the tensor-to-scalar ratio is r < 0,25 (95% CL), and the possible contribution of Nambu cosmic strings to the power spectrum is constrained to string tension G(sub mu) < 1.6 x 10(exp -7) (95% CL),

Dunkley, J.↗

Power System Options Evaluated for the Radiation and Technology Demonstration Mission

The Radiation and Technology Demonstration (RTD) Mission is under joint study by three NASA Centers: the NASA Johnson Space Center, the NASA Goddard Space Flight Center, and the NASA Glenn Research Center at Lewis Field. This Earth-orbiting mission, which may launch on a space shuttle in the first half of the next decade, has the primary objective of demonstrating high-power electric thruster technologies. Secondary objectives include better characterization of Earth's Van Allen trapped-radiation belts, measurement of the effectiveness of the radiation shielding for human protection, measurement of radiation effects on advanced solar cells, and demonstration of radiation-tolerant microelectronics. During the mission, which may continue up to 1 year, the 2000-kg RTD spacecraft will first spiral outward from the shuttle-deployed, medium-inclination, low Earth orbit. By the phased operation of a 10-kW Hall thruster and a 10-kW Variable Specific Impulse Magneto-Plasma Rocket, the RTD spacecraft will reach a low-inclination Earth orbit with a radius greater than five Earth radii. This will be followed by an inward spiraling orbit phase when the spacecraft deploys 8 to 12 microsatellites to map the Van Allen belts. The mission will conclude in low Earth orbit with the possible retrieval of the spacecraft by the space shuttle. A conceptual RTD spacecraft design showing two photovoltaic (PV) array wings, the Hall thruster with propellant tanks, and stowed microsatellites is presented. Early power system studies assessed five different PV array design options coupled with a 120-Vdc power management and distribution system (PMAD) and secondary lithium battery energy storage. Array options include (1) state-of-the-art 10-percent efficient three-junction amorphous SiGe thin-film cells on thin polymer panels deployed with an inflatable (or articulated) truss, (2) SCARLET array panels, (3) commercial state-of-the-art, planar PV array rigid panels with 25-percent efficient, three-junction GaInP2/GaAs/Ge solar cells, (4) rigid panels with 25-percent efficient, three-junction GaInP2/GaAs/Ge solar cells, in a 2 -concentrator trough configuration, and (5) thin polymer panels with 25-percent efficient, three-junction GaInP2/GaAs/Ge solar cells deployed with an inflatable (or articulated) truss. To assess the relative merits of these PV array design options, the study group developed a dedicated Fortran code to predict power system performance and estimate system mass. This code also modeled Earth orbital environments important for accurately predicting PV array performance. The most important environmental effect, solar cell radiation degradation, was calculated from electron-proton fluence input from the industry standard AE8/AP8 trapped radiation models and the concept of damage equivalence. Power systems were sized to provide 10 kW of thruster power and approximately 1 kW of spacecraft power at end of life. Of the five PV array design options, the option 1 (thin-film cells) power system was the most massive 590 kg, whereas the option 4 (trough concentrator) power system was the lightest 260 kg. Arguably, the lowest cost would come from the option 3 (commercial array panels) power system with an acceptable, albeit greater, system mass of 320 kg. Predicted power system performance during the spiral-out mission phase is shown the preceding graph for the option 5 (flexible-panel) array. From the results, the radiation-induced power loss over time is evident as the spacecraft slowly spirals outward through the trapped proton belt. The importance of the spiral trip time is also evident in the two curves representing 74-day and 182-day spiral-out periods. The longer spiral time introduces a beginning-of-life power oversizing penalty greater than 1 kW. Future studies will analyze power system performance and mass with a 50-Vdc power management and distribution architecture favorable to the VASIMR thruster and longer missions.

Kerslake, Thomas W.↗

Updated Oregon Floating Offshore Wind Cost Modeling [Slides]

The study provides heat maps showing updated estimates of the levelized cost of energy (LCOE) for floating offshore wind energy off the coast of Oregon. This project builds on a 2019 National Renewable Energy Laboratory (NREL) floating offshore wind power cost study in Oregon (Musial et al. 2019) and a recent NREL California cost analysis (Beiter et al. 2020). Floating wind power cost data, modeling methodology, and resource data are updated and LCOE is estimated through 2032 using 2019 as a reference year. Comparisons are made to the previous offshore wind energy cost studies (Musial et al. 2019; Beiter et al. 2020). The study does not prioritize specific sites or make judgments about marine spatial planning viability.

17 WIND ENERGY↗

Thermal Analysis of the Advanced Technology Large Aperture Space Telescope (ATLAST) 8 Meter Primary Mirror

The Advanced Technology Large Aperture Space Telescope (ATLAST) preliminary design concept consists of an 8 meter diameter monolithic primary mirror enclosed in an insulated, optical tube with stray light baffles and a sunshade. ATLAST will be placed in orbit about the Sun-Earth L2 and will experience constant exposure to the sun. The insulation on the optical tube and sunshade serve to cold bias the telescope which helps to minimize thermal gradients. The primary mirror will be maintained at 280K with an active thermal control system. The geometric model of the primary mirror, optical tube, sun baffles, and sunshade was developed using Thermal Desktop(R) SINDA/FLUINT(R) was used for the thermal analysis and the radiation environment was analyzed using RADCAD(R). A XX node model was executed in order to characterize the static performance and thermal stability of the mirror during maneuvers. This is important because long exposure observations, such as extra-solar terrestrial planet finding and characterization, require a very stable observatory wave front. Steady state thermal analyses served to predict mirror temperatures for several different sun angles. Transient analyses were performed in order to predict thermal time constant of the primary mirror for a 20 degree slew or 30 degree roll maneuver. This paper describes the thermal model and provides details of the geometry, thermo-optical properties, and the environment which influences the thermal performance. All assumptions that were used in the analysis are also documented. Parametric analyses are summarized for design parameters including primary mirror coatings and sunshade configuration. Estimates of mirror heater power requirements are reported. The thermal model demonstrates results for the primary mirror heated from the back side and edges using a heater system with multiple independently controlled zones.

Hornsby, Linda↗

Evaluating Impacts of the Inflation Reduction Act and Bipartisan Infrastructure Law on the U.S. Power System

The Inflation Reduction Act of 2022 (IRA) and the Infrastructure Investment and Jobs Act of 2021, commonly referred to as the 'Bipartisan Infrastructure Law (BIL),' collectively represent the largest commitment of the U.S. Federal Government to invest in the modernization and decarbonization of the U.S. energy system. The Congressional Budget Office (CBO) estimates that total support for the broad range of climate and clean energy programs, tax credits, and other incentives authorized through the two laws will exceed $430 billion from 2022 through 2031 (CRS 2022; CBO 2021, 2022). While the climate and clean energy provisions are numerous and have the potential to impact all aspects of the U.S. energy system from fuel and electricity production to final consumption in industry, transportation, and buildings, the provisions relevant to the electricity sector - in particular the suite of tax credits for clean generation, storage, and carbon dioxide ( CO 2 ) capture and storage - are expected to be some of the most consequential in terms of emissions reduction and clean energy deployment (Larsen et al. 2022; Jenkins, Mayfield, et al. 2022; Mahajan et al. 2022; Zhao et al. 2022). In this report, we detail the methods and results of a study estimating the potential impacts of key provisions of IRA and BIL on the contiguous U.S. power sector from present day through 2030. The analysis employs an advanced power system planning model, the Regional Energy Deployment System (ReEDS), to evaluate how major provisions from both laws impact investment in and operation of utility-scale generation, storage, and transmission, and, in turn, how those changes impact power system costs, emissions, and climate and health damages. While not exhaustive in capturing every provision, the analysis estimates the possible scale of power-sector impacts that could result from the modeled provisions in IRA and BIL. The study is structured around two scenarios to evaluate the potential impacts of both laws on the power sector: 1) No New Policy: A counter-factual scenario that reflects all Federal and state policies enacted as of September 2022, with exception to IRA and BIL, and assumes load growth consistent with the Energy Information Administration's Annual Energy Outlook 2022 (AEO22) Reference case (EIA 2022a); 2) IRA-BIL: A scenario reflecting all Federal and state policies enacted as of September 2022, including key IRA and BIL provisions, most notably the investment and production tax credits for zero-carbon emitting electricity generation and storage (ITC and PTC), the tax credit for CO 2 capture and storage (45Q), and the tax credit for existing nuclear plants (described further in Section 2.3). To account for the impacts of IRA and BIL on electrification, assumes increased load growth consistent with a scaled version of the Medium Electrification scenario from the Electrification Futures Study (Mai et al. 2018). These scenarios are simulated across seven sets of assumptions with varying projected future electricity market conditions, including technology costs and performance, natural gas prices, and the degree of availability, feasibility, and cost of development of renewable resources, electricity transmission, and CO 2 pipeline, injection, and storage infrastructure. In addition, we simulate two sensitivities on the 'policy' treatment in which we vary key assumptions pertaining to the realized value of the clean electricity ITC and PTC: 1) the cost of monetization of tax credits, and 2) the level of bonus crediting realized by project developers. We demonstrate that IRA and BIL have the collective potential to drive substantial growth in clean electricity by 2030, while reducing costs for consumers, mitigating climate change, and decreasing the human health impacts of power sector emissions. However, we also demonstrate that if expected cost improvements of clean technologies are not realized and/or constraints on deployment driven by factors such as supply-chain challenges, regulatory hurdles, and the social acceptability of energy infrastructure development limit the rate of clean energy and associated infrastructure deployment (such as transmission), then the share of clean generation achieved and the associated emissions benefits realized may be substantively reduced.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Trace Element Sampling and Partitioning Modeling to Estimate Wastewater Composition and Treatment Performance at Coal Generators

The coal combusted at coal-fired power plants (CFPPs) contains several trace elements that impact human heath if released to the environment. Effective combinations of air pollution control devices (APCDs) and water pollution control devices (WPCDs) are critical to reducing these impacts. This work sampled pulverized CFPPs owned and operated by Louisville Gas & Electricity – Kentucky Utilities (LGE-KU) during baseload and cycling conditions. Next, an open-source and easy-to-implement trace element partitioning model was developed using publicly available datasets, literature studies of trace element partitioning, and sampling data to estimate trace element partitioning in APCDs to the gas, liquid, and solid phases exiting CFPPs. These estimates of the liquid phase trace element concentration in FGD wastewater were then used to estimate trace element behavior in WPCDs and evaluate treated wastewater effluent concentrations for compliance with the Effluent Limitation Guidelines (ELG) for the Steam Electric Generating Sector. Finally, cost estimates were developed for established and emerging wastewater treatment trains to identify the most cost-effective approaches for ELG compliance.

01 COAL, LIGNITE, AND PEAT↗

AC Power Flow Based DLMP Calculation and Decomposition Method to Smooth Power Fluctuation of Distributed Renewable Energy Sources

As the penetration of renewable energy sources increases, the growing renewable power variability brings ramping issues to power systems. Meanwhile, the development of distributed energy resources (DERs) makes the distribution systems to provide both energy and ancillary services. To incentivise individual resources and customers to alleviate ramping issues on the demand side, a two-stage distribution locational marginal price (DLMP) calculation and decomposition method is developed to formulate the marginal power ramping price for DERs. In the first stage of the proposed method, a distribution system operator market scheduling model based on AC optimal power flow is designed to estimate the optimal operating point of the distribution system. Subsequently, the voltage and power flow constraints are linearised in stage two to calculate DLMP. Finally, based on the Lagrange function and sensitivity factors, DLMP is decomposed to the marginal costs for active/reactive power, voltage management, power loss and power variability. Case studies demonstrate that the proposed model can effectively smooth the power fluctuation and reduce the ramping flexibility requirements of distribution systems.

AC optimal power flow↗

Transient Efficiency Flexibility and Reliability Optimization of Coal-Fired Power Plants: Model-Predictive Control Library Development (Report)

This document pertains to the reporting requirements of DOE contract FE-0031767. The document covers the development of a model predictive control (MPC) library for implementing MPC for a general dynamic system. The library is implemented in a standardized manner in Matlab/Simulink, where core functions on model prediction, linearization and formulation and solution of a quadratic programming (QP) optimization problem is done in the core library - independent of the specific application. The user can provide the application-specific dynamic model in continuous and discrete time, to rapidly implement and test the MPC performance in a desktop simulation. The MPC optimization objective and constraints are also easily configured via an Excel file to allow iterative refinement as needed. Finally, the MPC library enables a rapid deployment to a target environment through auto C-code generation and containerization. The MPC library works seamlessly with the model based estimation (MBE) library to obtain the overall output feedback control solution. In this program, the reduced order model (ROM) of a coal-fired power plant (CFPP) is used to implement and test the MPC solution.

01 COAL, LIGNITE, AND PEAT↗

A High-Accuracy Power Loss Model of SiC MOSFETs in Current Source Inverter Considering Current Commutation and Parasitic Parameters

Power loss estimation of power electronic devices is important to the efficiency optimization of motor drives used in many applications. However, most existing simplified power loss models of silicon carbide (SiC) MOSFETs are not sufficiently accurate due to their neglect of parasitic parameters in the current commutation loop. In addition, the loss model of the voltage source inverter (VSI) cannot be directly applied to the current source inverter (CSI) because of differences between their commutation loops. First, the commutation processes for VSIs and CSIs are compared. The voltage and current trajectories of SiC MOSFETs in the switching transition of a CSI-based motor drive system are analyzed in detail. Based on these results, the conduction and switching losses of SiC MOSFETs in CSIs are modeled considering the current commutation details. In addition, the proposed analytical model includes parasitic inductances and capacitances in the current commutation loop. Experimental results have verified that the proposed power loss model delivers higher accuracy loss predictions than the conventional loss model.

current commutation, current source inverter, powe↗

DC Arc Incident Energy in Photovoltaic Systems: Methods for Evaluation

Renewable energy systems continue to be one of the fastest growing segments of the energy industry. This article focuses on the understanding of how photovoltaic (PV) technology behaves under dc arc conditions. Emphasis is placed on the electrical safety aspect of dc arc-flash incident energy (IE) evaluation. Because of the fast proliferation of PV systems and lack of formal equivalent calculation guidelines, such as IEEE 1584 for ac systems, it has been necessary to rely on different equations and models presented by various researchers over the last few years. This article discusses the behavior of PV systems under arc conditions and presents the results of the available methods to estimate the dc arc-flash IE. It provides a comparative analysis of a proposed arc-flash IE calculation method against different laboratory tests, including those performed for this article at the National Renewable Energy Laboratory (NREL). Detailed explanations are provided regarding the effect of the PV module current-voltage (I-V) and power-voltage (P-V) curves under arcing conditions. Examples of the application of the proposed calculation method to the test measurements are included.

arc discharges↗

Thrust stand evaluation of engine performance improvement algorithms in an F-15 airplane

An investigation is underway to determine the benefits of a new propulsion system optimization algorithm in an F-15 airplane. The performance seeking control (PSC) algorithm optimizes the quasi-steady-state performance of an F100 derivative turbofan engine for several modes of operation. The PSC algorithm uses an onboard software engine model that calculates thrust, stall margin, and other unmeasured variables for use in the optimization. As part of the PSC test program, the F-15 aircraft was operated on a horizontal thrust stand. Thrust was measured with highly accurate load cells. The measured thrust was compared to onboard model estimates and to results from posttest performance programs. Thrust changes using the various PSC modes were recorded. Those results were compared to benefits using the less complex highly integrated digital electronic control (HIDEC) algorithm. The PSC maximum thrust mode increased intermediate power thrust by 10 percent. The PSC engine model did very well at estimating measured thrust and closely followed the transients during optimization. Quantitative results from the evaluation of the algorithms and performance calculation models are included with emphasis on measured thrust results. The report presents a description of the PSC system and a discussion of factors affecting the accuracy of the thrust stand load measurements.

Conners, Timothy R.↗

Influence of Time and Frequency Domain Wave Forcing on the Power Estimation of a Wave Energy Converter Array

Industry-specific tools for analyzing and optimizing the design of wave energy converters (WECs) and associated power systems are essential to advancing marine renewable energy. This study aims to quantify the influence of phase information on the device power output of a virtual WEC array. We run the phase-resolving wave model FUNWAVE-TVD (Total Variation Diminishing) to generate directional waves at the PacWave South site offshore from Newport, Oregon, where future WECs are expected to be installed for testing. The two broad cases presented correspond to mean wave climates during warm months (March–August) and cold months (September–February). FUNWAVE-TVD time series of sea-surface elevation are then used in WEC-Sim, a time domain numerical model, to simulate the hydrodynamic response of each device in the array and estimate their power output. For comparison, WEC-Sim is also run with wave energy spectra calculated from the FUNWAVE-TVD simulations, which do not retain phase information, and with wave spectra computed using the phase-averaged model Simulating WAves Nearshore (SWAN). The use of spectral data in WEC-Sim requires a conversion from frequency to time domain by means of random superposition of wave components, which are not necessarily consistent because of the linear assumption implicit in this method. Thus, power response is characterized by multiple realizations of the wave climates.

13 HYDRO ENERGY↗