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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Comparing Numerical Models of the TALOS Wave Energy Converter

In this study, we present the development of a numerical model of the TALOS Wave Energy Converter (WEC) in WEC-Sim and compare it with existing numerical in-house models from Lancaster and results from DNV's Sesam code. The objective of this work is to validate the performance of the TALOS WEC using WEC-Sim and compare the results with those obtained from other numerical models. The TALOS WEC is a promising technology for the generation of clean, renewable energy from ocean waves. The development of a reliable numerical model for the TALOS WEC is crucial for its design and optimization. To achieve this, we have implemented the TALOS WEC in WEC-Sim and compared the results to in-house models from Lancaster and to results from DNV's Sesam code. Our results show good agreement with the results from Lancaster and DNV, demonstrating the accuracy and reliability of the numerical model developed in WEC-Sim. This work advances the field of wave energy conversion by providing a verified numerical model of the TALOS WEC, which can be used for further optimization and design studies.

CFD↗
DOE OSTI2023

Additive Manufacturing for Powering the Blue Economy Applications: A Tidal Turbine Blade Case Study: Preprint

As the marine renewable energy industry continues to expand, innovation in the manufacturing space must grow accordingly to reduce costs and ensure the economic feasibility of new technologies. Additive manufacturing, more commonly known as 3D printing, provides an alternative for rapid prototyping of marine hydrokinetic technologies, particularly supporting Powering the Blue Economy initiatives of the U.S. Department of Energy Water Power Technologies Office. This study explores the application of additive manufacturing in the development of marine hydrokinetic structures, focusing on material and printing method selection, design, and analysis of a 3D-printed spar for an axial-flow tidal turbine blade. Corrosion-resistant metals were deemed ideal due to the loads and harsh marine environment the blade would experience. Laser metal deposition methods were determined to be the most effective and scalable for the considered scale. The designed spar adapts its geometry to the blade - a feature uniquely suited to additive manufacturing - and is intended to serve as the blade's primary structural component. A finite element model was used to study stresses and deformations under loading conditions. The spar was manufactured using 316L stainless steel through direct energy deposition, and defects were assessed and recorded. Future efforts will include mechanical testing of the spar. This research establishes a benchmark process for using additive manufacturing in developing marine hydrokinetic structures, paving the way for future optimization and techno-economic analysis.

additive manufacturing↗
DOE OSTI2024

Feasible Actuator Range Modifier (FARM), a Tool Aiding the Solution of Unit Dispatch Problems for Advanced Energy Systems

Integrated energy systems (IESs) seek to minimize power generating costs in future power grids through the coupling of different energy technologies. To accommodate fluctuations in load demand due to the penetration of renewable energy sources, flexible operation capabilities must be fully exploited, and even power plants that are traditionally considered as base-load units need to be operated according to unconventional paradigms. Thermomechanical loads induced by frequent power adjustments can accelerate the wear and tear. If a unit is flexibly operated without respecting limits on materials, the risk of failures of expensive components will eventually increase, nullifying the additional profits ensured by flexible operation. In addition to the bounds on power variations (explicit constraints),the solution of the unit dispatch problem needs to meet the limits on the variation of key process variables, including temperature, pressure and flow rate (implicit constraints).The FARM (Feasible Actuator Range Modifier) module was developed to enable existing optimization algorithms to identify solutions to the unit dispatch problem that are both economically favorable and technologically sustainable. Thanks to the iterative dispatcher–validator scheme, FARM permits addressing all the imposed constraints without excessively increasing the computational costs. In this work, the algorithms constituting the module are described, and the performance was assessed by solving the unit dispatch problem for an IES composed of three units, i.e., balance of plant, gas turbine, and high-temperature steam electrolysis. Finally, the FARM module provides dedicated tools for visualizing the response of the constrained variables of interest during operational transients and a tool aiding the operator at making decisions. These techniques might represent the first step towards the deployment of an ecological interface design (EID) for IES units.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Optimizing Grid Regulation With Gravity Storage Systems: A Comparative Analysis With Different Motor Inertias: Preprint

The integration of renewable energy sources into power grids necessitates solutions for grid support and stability during fluctuations in electricity generation and demand. Gravity energy storage systems (GESS) are emerging as a promising technology for managing the balance between the energy supply and demand. However, their capacity to optimize energy flow and offer voltage and frequency regulation amid generation-demand imbalances is less reported. This paper investigates the control of GESS for optimizing energy flow during voltage and frequency regulation. The study evaluates the regulation capabilities of GESS with different motor inertias during a Texas grid event: one with a high-speed, low-inertia motor and another with a low-speed, high-inertia motor. Results indicate that both GESS systems provide fast frequency response by converting potential energy into kinetic energy and vice versa, with a response time of 1.5 seconds from the frequency variation. This aligns with grid requirements for primary frequency response from traditional synchronous generators and motors with large inertia. Furthermore, a GESS with a high-inertia motor may be able operate over a broader range of frequency variations whereas a low-inertia system may be limited by thermal constraints of the motor.

frequency regulation↗
DOE OSTI2025

Practical Implementation of GPU-based Computing at the Grid Edge for Resilience Scenarios

This paper presents a practical implementation of GPU-accelerated computing at the grid edge to enhance power system resilience through next-generation smart meters. Advanced Metering Infrastructure (AMI) systems rely predominantly on centralized processing architectures, which limit real-time response capabilities during grid disturbances. This work proposes the integration of GPU-enabled computational platforms directly within smart meter to enable local execution support for power system analytics, fault detection algorithms, and optimization routines. The proposed framework uses the Julia programming language to leverage highperformance parallel computing capabilities while maintaining code portability and development efficiency. We use two experimental scenarios to benchmark the computational feasibility of this approach: sparse linear system solutions representative of power flow analyses, and multi-stage production cost simulations incorporating unit commitment and economic dispatch operations. Results demonstrate that computationally intensive power system algorithms, such as those supporting resilience scenario calculations, can be effectively executed at the distribution edge using commercially available embedded GPU hardware. Keywords—GPU acceleration, edge computing, smart meters, grid resilience, AMI, resilience.

De Souza, Reubun [School of Electrical Engineering↗
NASA NTRS1989

Development of free-piston Stirling engine performance and optimization codes based on Martini simulation technique

A FORTRAN computer code is described that could be used to design and optimize a free-displacer, free-piston Stirling engine similar to the RE-1000 engine made by Sunpower. The code contains options for specifying displacer and power piston motion or for allowing these motions to be calculated by a force balance. The engine load may be a dashpot, inertial compressor, hydraulic pump or linear alternator. Cycle analysis may be done by isothermal analysis or adiabatic analysis. Adiabatic analysis may be done using the Martini moving gas node analysis or the Rios second-order Runge-Kutta analysis. Flow loss and heat loss equations are included. Graphical display of engine motions and pressures and temperatures are included. Programming for optimizing up to 15 independent dimensions is included. Sample performance results are shown for both specified and unconstrained piston motions; these results are shown as generated by each of the two Martini analyses. Two sample optimization searches are shown using specified piston motion isothermal analysis. One is for three adjustable input and one is for four. Also, two optimization searches for calculated piston motion are presented for three and for four adjustable inputs. The effect of leakage is evaluated. Suggestions for further work are given.

Martini, William R.↗
DOE OSTI2021

Flow Redirection and Induction in Steady State (FLORIS) Wind Plant Power Production Data Sets

This dataset contains turbine- and plant-level power outputs for 252,500 cases of diverse wind plant layouts operating under a wide range of yawing and atmospheric conditions. The power outputs were computed using the Gaussian wake model in NREL's FLOw Redirection and Induction in Steady State (FLORIS) model, version 2.3.0. The 252,500 cases include 500 unique wind plants generated randomly by a specialized Plant Layout Generator (PLayGen) that samples randomized realizations of wind plant layouts from one of four canonical configurations: (i) cluster, (ii) single string, (iii) multiple string, (iv) parallel string. Other wind plant layout parameters were also randomly sampled, including the number of turbines (25-200) and the mean turbine spacing (3D-10D, where D denotes the turbine rotor diameter). For each layout, 500 different sets of atmospheric conditions were randomly sampled. These include wind speed in 0-25 m/s, wind direction in 0 deg.-360 deg., and turbulence intensity chosen from low (6%), medium (8%), and high (10%). For each atmospheric inflow scenario, the individual turbine yaw angles were randomly sampled from a one-sided truncated Gaussian on the interval 0 deg.-30 deg. oriented relative to wind inflow direction. This random data is supplemented with a collection of yaw-optimized samples where FLORIS was used to determine turbine yaw angles that maximize power production for the entire plant. To generate this data, a subset of cases were selected (50 atmospheric conditions from 50 layouts each for a total of additional 2,500 cases) for which FLORIS was re-run with wake steering control optimization. The IEA onshore reference turbine, which has a 130 m rotor diameter, a 110 m hub height, and a rated power capacity of 3.4 MW was used as the turbine for all simulations. The simulations were performed using NREL's Eagle high performance computing system in February 2021 as part of the Spatial Analysis for Wind Technology Development project funded by the U.S. Department of Energy Wind Energy Technologies Office. The data was collected, reformatted, and preprocessed for this OEDI submission in May 2023 under the Foundational AI for Wind Energy project funded by the U.S. Department of Energy Wind Energy Technologies Office. This dataset is intended to serve as a benchmark against which new artificial intelligence (AI) or machine learning (ML) tools may be tested. Baseline AI/ML methods for analyzing this dataset have been implemented, and a link to their repository containing those models has been provided. The .h5 data file structure can be found in the GitHub repository under explore_wind_plant_data_h5.ipynb.

AI↗
DOE OSTI2024

Development of an Optimal Variable-Pitch Controller for Floating Axial-Flow Marine Hydrokinetic Turbines

This article discusses the development of an optimal variable-pitch controller for floating, axial-flow marine turbines. Recently, OpenFAST, an open-source wind turbine modeling tool, has been extended to model marine turbines. A controller is necessary to simulate marine turbines for different load cases using OpenFAST, which greatly impacts the performance of the energy system. Previous studies have designed controllers using a linearized model of the marine turbine, which can be time-consuming and require the expertise of a control engineer. In this study, we use an automated approach that uses generic models of the marine turbine to identify the controller gains, which can expedite the process of designing a controller. Using an optimizer to identify the control system parameters can additionally improve the controller's performance. The optimal controller tuned using such an approach results in a 20% reduction in the tower-base damage equivalent loading and better tracking of the rated generator speed and power.

axial flow↗
NASA NTRS1996

An optimized index of human cardiovascular adaptation to simulated weightlessness

Prolonged exposure to weightlessness is known to produce a variety of cardiovascular changes, some of which may influence the astronaut's performance during a mission. In order to find a reliable indicator of cardiovascular adaptation to weightlessness, we analyzed data from nine male subjects after a 24-hour period of normal activity and after a period of simulated weightlessness produced by two hours in a launch position followed by 20 hours of 6 degrees head-down tilt plus pharmacologically induced diuresis (furosemide). Heart rate, arterial pressure, thoracic fluid index, and radial flow were analyzed. Autoregressive spectral estimation and decomposition were used to obtain the spectral components of each variable from the subjects in the supine position during pre- and post-simulated weightlessness. We found a significant decrease in heart rate power and an increase in thoracic fluid index power in the high frequency region (0.2-0.45 Hz) and significant increases in radial flow and arterial pressure powers in the low frequency region (<0.2 Hz) in response to simulated weightlessness. However, due to the variability among subjects, any single variable appeared limited as a dependable index of cardiovascular adaptation to weightlessness. The backward elimination algorithm was then used to select the best discriminatory features from these spectral components. Fisher's linear discriminant and Bayes' quadratic discriminant were used to combine the selected features to obtain an optimal index of adaptation to simulated weightlessness. Results showed that both techniques provided improved discriminant performance over any single variable and thus have the potential for use as an index to track adaptation and prescribe countermeasures to the effects of weightlessness.

NASA Discipline Number 14-10↗
NASA NTRS1978

Canard configured aircraft with 2-D nozzle

A closely-coupled canard fighter with vectorable two-dimensional nozzle was designed for enhanced transonic maneuvering. The HiMAT maneuver goal of a sustained 8g turn at a free-stream Mach number of 0.9 and 30,000 feet was the primary design consideration. The aerodynamic design process was initiated with a linear theory optimization minimizing the zero percent suction drag including jet effects and refined with three-dimensional nonlinear potential flow techniques. Allowances were made for mutual interference and viscous effects. The design process to arrive at the resultant configuration is described, and the design of a powered 2-D nozzle model to be tested in the LRC 16-foot Propulsion Wind Tunnel is shown.

Child, R. D.↗
DOE OSTI2020

Deep Reinforcement Learning Based Volt-VAR Optimization in Smart Distribution Systems

This paper develops a model-free volt-VAR optimization (VVO) algorithm via multi-agent deep reinforcement learning (DRL) in unbalanced distribution systems. This method is novel since we cast the VVO problem in distribution networks to an intelligent deep Q-network (DQN) framework, which avoids solving a specific optimization model directly when facing time-varying operating conditions in the systems. We consider statuses/ratios of switchable capacitors, voltage regulators, and smart inverters installed at distributed generators as the action variables of the agents. A delicately designed reward function guides these agents to interact with the distribution system, in the direction of reinforcing voltage regulation and power loss reduction simultaneously. The forward-backward sweep method for radial three-phase distribution systems provides accurate power flow results within a few iterations to the DRL environment. The proposed method realizes the dual goals for VVO. We test this algorithm on the unbalanced IEEE 13-bus and 123-bus systems. Numerical simulations validate the excellent performance of this method in voltage regulation and power loss reduction.

41 EE - Solar Energy Technologies Office (EE-4S)↗
DOE OSTI2026

Systematic analysis of melt pool dynamics in laser processing of mixed powder feedstocks

Functionally graded materials (FGMs) fabricated via additive manufacturing of blended powders offer the potential to spatially tailor properties for new technologies, such as fusion first-wall systems, turbine blades, and spacecraft. However, processing these materials is difficult due to the multiplicity of processing parameters to optimize, all of which must be changed as substrate material, powder feedstock compositions, and melt pool dynamics evolve. Here, this work systematically evaluates the qualitative and quantitative effects of these variables on the melt pool size, shape, composition, and particle distribution in an exemplar Ti-Ta system, and connects the experimental results to Marangoni flow behavior and phenomena observed in other systems. Increasing laser power linearly increases melt pool size and layer thickness, driving engineering considerations such as part/geometrical tolerances. Decreasing laser velocity changes the melt pool shape from lenticular to convex and reduces chemical homogeneity due to extreme thermal and compositional gradients between the melt pool center and boundaries. Thermophysical property differences between the powder feedstock and substrate material, as well as the directionality of the gradient, affect dilution and melt pool dynamics, which in turn affect the melt pool boundary characteristics, shape, and uniformity. Mixed powder feedstocks of intermediate compositions do not behave according to linear interpolations between single-material endpoints, instead building taller and wider melt pools. As such, it is recommended to quantify process maps for at least one intermediate composition in the FGM or multi-material system of interest to ensure optimized processing parameters, predictable melt pool sizes and shapes, and compositional and spatial precision.

Dissimilar↗
NASA NTRS1982

Tests of a 2-Stage, Axial-Flow, 2-Phase Turbine

A two phase flow turbine with two stages of axial flow impulse rotors was tested with three different working fluid mixtures at a shaft power of 30 kW. The turbine efficiency was 0.55 with nitrogen and water of 0.02 quality and 94 m/s velocity, 0.57 with Refrigerant 22 of 0.27 quality and 123 m/s velocity, and 0.30 with steam and water of 0.27 quality and 457 m/s velocity. The efficiencies with nitrogen and water and Refrigerant 22 were 86 percent of theoretical. At that fraction of theoretical, the efficiencies of optimized two phase turbines would be in the low 60 percent range with organic working fluids and in the mid 50 percent range with steam and water. The recommended turbine design is a two stage axial flow impulse turbine followed by a rotary separator for discharge of separate liquid and gas streams and recovery of liquid pressure.

Elliott, D. G.↗
DOE OSTI2022

E-transit-bench: simulation platform for analyzing electric public transit bus fleet operations

When electrified transit systems make grid aware choices, improved social welfare is achieved by reducing grid stress, reducing system loss, and minimizing power quality issues. Electrifying transit fleet has numerous challenges like non availability of buses during charging, varying charging costs and so on, that are related the electric grid behavior. However, transit systems do not have access to the information about the co-evolution of the grid's power flow and therefore cannot account for the power grid's needs in its day-to-day operation. In this paper we propose a framework of transportation-grid co-simulation, analyzing the spatio-temporal interaction between the transit operations with electric buses and the power distribution grid. Real-world data for a day's traffic from Chattanooga city's transit system is simulated in SUMO and integrated with a realistic distribution grid simulation (using GridLAB-D) to understand the grid impact due to transit electrification. Charging information is obtained from the transportation simulation to feed into grid simulation to assess the impact of charging. We also discuss the impact to the grid with higher degree of transit electrification that further necessitates such an integrated transportation-grid co-simulation to operate the integrated system optimally. Our future work includes extending the platform for optimizing the charging and trip assignment operations.

Sen, Rishav↗
NASA NTRS1993

Preconditioning for the Navier-Stokes equations with finite-rate chemistry

The extension of Van Leer's preconditioning procedure to generalized finite-rate chemistry is discussed. Application to viscous flow is begun with the proper preconditioning matrix for the one-dimensional Navier-Stokes equations. Eigenvalue stiffness is resolved and convergence-rate acceleration is demonstrated over the entire Mach-number range from nearly stagnant flow to hypersonic. Specific benefits are realized at the low and transonic flow speeds typical of complete propulsion-system simulations. The extended preconditioning matrix necessarily accounts for both thermal and chemical nonequilibrium. Numerical analysis reveals the possible theoretical improvements from using a preconditioner for all Mach number regimes. Numerical results confirm the expectations from the numerical analysis. Representative test cases include flows with previously troublesome embedded high-condition-number areas. Van Leer, Lee, and Roe recently developed an optimal, analytic preconditioning technique to reduce eigenvalue stiffness over the full Mach-number range. By multiplying the flux-balance residual with the preconditioning matrix, the acoustic wave speeds are scaled so that all waves propagate at the same rate, an essential property to eliminate inherent eigenvalue stiffness. This session discusses a synthesis of the thermochemical nonequilibrium flux-splitting developed by Grossman and Cinnella and the characteristic wave preconditioning of Van Leer into a powerful tool for implicitly solving two and three-dimensional flows with generalized finite-rate chemistry. For finite-rate chemistry, the state vector of unknowns is variable in length. Therefore, the preconditioning matrix extended to generalized finite-rate chemistry must accommodate a flexible system of moving waves. Fortunately, no new kind of wave appears in the system. The only existing waves are entropy and vorticity waves, which move with the fluid, and acoustic waves, which propagate in Mach number dependent directions. The nonequilibrium vibrational energies and species densities in the unknown state vector act strictly as convective waves. The essential concept for extending the preconditioning to generalized chemistry models is determining the differential variables which symmetrize the flux Jacobians. The extension is then straight-forward. This algorithm research effort will be released in a future version of the production level computational code coined the General Aerodynamic Simulation Program (GASP), developed by Walters, Slack, and McGrory.

Godfrey, Andrew G.↗
NASA NTRS1995

The radiated noise from isotropic turbulence and heated jets

Our understanding of aerodynamic noise has its foundations in the work of Sir James Lighthill (1952), which was the first major advance in acoustics since the pioneering work of Lord Rayleigh in the last century. The combination of Lighthill's theory of aerodynamic noise as applied to turbulent flows and the experimental growing database from the early 1950's was quickly exploited by various jet propulsion engine designers in reducing the noise of jet engines at takeoff and landing to levels marginally acceptable to communities living in the neighborhoods of airports. The success in this noise containment led to the rapid growth of fast economical subsonic civil transport aircraft worldwide throughout the 1960's and has continued to the present day. One important factor in this success story has been the improvements in the engine cycle that have led to both reductions in specific fuel consumption and noise. The second is the introduction of Noise Certification, which specifies the maximum noise levels at takeoff and landing that all aircraft must meet before they can be entered on the Civil Aircraft Register. The growing interest in the development of a new supersonic civil transport to replace 'Concorde' in the early years of the next century has led to a resurgence of interest in the more challenging problem of predicting the noise of hot supersonic jets and developing means of aircraft noise reduction at takeoff and landing to meet the standards now accepted for subsonic Noise Certification. The prediction of aircraft noise to the accuracy required to meet Noise Certification requirements has necessitated reliance upon experimental measurements and empirically derived laws based on the available experimental data bases. These laws have their foundation in the results from Lighthill's theory, but in the case of jet noise, where the noise is generated in the turbulent mixing region with the external ambient fluid, the complexity of the turbulent motion has prevented the full deployment of Lighthill's theory from being achieved. However, the growth of the supercomputer and its applications in the study of the structure of turbulent shear flows in both unbounded and wall bounded flows, which complements and in certain cases extends the work of the few dedicated experimental groups working in this field for the past forty years, provides an opportunity and challenge to accurately predict the noise from jets. Moreover a combination of numerical and laboratory experiments offers the hope that in the not too distant future the physics of noise generation and flow interaction will be better understood and it will then be possible to not only improve the accuracy of noise prediction but also to explore and optimize schemes for noise reduction. The present challenge is to provide time and space accurate numerical databases for heated subsonic and supersonic jets to provide information on the fourth-order space-time covariance of Lighthill's equivalent stress tensor, T(ij), which governs the characteristics of the farfield radiated noise and the total acoustic power. Validation with available experimental databases will establish how close Lighthill's theory is to the accurate prediction of the directivity and spectrum of jet noise and the total acoustic power, and the need, in the applications of the theory, to include the effects of flow-acoustic interaction.

Lilley, G. M.↗
DOE OSTI2024

Flow and Heat Transfer Experimental Study for 3D-Printed Solar Receiving Tubes With Helical Fins at Internal Surface

3D-printing technology was applied to fabricate novel solar thermal collection tubes that have internal heat transfer enhancement fins and external surfaces with high solar absorptivity and low emissivity due to the ability to use different materials in one tube. Helical fins were selected to introduce circumferential flow and thus minimize the circumferential temperature difference of the tube that receives sunlight on one side. The structures of the helical fins were previously optimized from computational fluid dynamics (CFD) analysis with the objective of low entropy production rate by looking for high heat transfer coefficient and relatively lower pressure loss. High-temperature alloy, Inconel-718, was used to 3D print the tubes, which can resist corrosion for the potential application of molten chloride salts as heat transfer fluid. Experimental tests were carried out using water as the heat transfer fluid with the high heat flux provided by a tubular furnace heater. The tested Reynolds number ranges from 3.9 × 10 3 to 6.1 × 10 4 . Heat transfer coefficients of up to 2.8 times that of the smooth tube could be obtained with the expense of increased pressure loss compared to that of the smooth tube. The total system entropy generation can be significantly reduced due to the benefit of heat transfer enhancement that is greater than the expenses of the increased pressure loss. The experimental results of the 3D-printed heat transfer tubes confirmed the CFD-based results of fin optimization. Furthermore, the novel heat transfer tube is recommended for application in concentrating solar power systems.

14 SOLAR ENERGY↗
DOE OSTI2020

Optimization of Archimedes Screw for Use in Hydroelectric Projects

In 2017, the Department of Energy’s (DOE) Water Power Technologies Office (WPTO) made federal funding available to several awardees to investigate and provide innovative technological solutions to reduce capital costs of installed hydroelectric facilities at non-powered dam’s (NPD’s) across the United States, while maintaining a high level of efficiency. Awardees were to develop specific technologies that showed promise of reducing installed capital cost (ICC) by at least 20% over a given baseline and maintain a water-to-wire efficiency of at least 80% at head levels of 50 feet or less and flows of 1000 cubic feet per second (cfs) or less. Canyon Hydro (Canyon) was selected as an awardee for this funding and worked to refine the implementation of the Archimedes screw turbine for use at these site conditions. Canyon and its project partners analyzed several dam inventory datasets to determine the most common head and flow range of current NPD’s in order to best select design conditions for a turbine that would perform successfully at common heads and flows. Computational Fluid Dynamic (CFD) analyses were conducted after site conditions had been selected to optimize the turbine geometry for efficiency. Through this effort we were able to estimate water-to-wire efficiency over a range of flows. Equipment design focused on concepts of modularity and pre-fabricated construction. These methodologies were used where possible to reduce costly on-site construction and shorten deployment timelines. Cost modeling was conducted with input from industry experts in general construction, pre-fabricated concrete construction, and composite fabrication. As a hydroelectric turbine manufacturer of 35 years, Canyon drew upon its own knowledge base in steel fabrication, water-to-wire component specification and ancillary systems to develop the remaining cost matrix for the project. As a result of these efforts, Canyon was able to present findings that indicated a modular Archimedes screw turbine system could be designed that reduced ICC by 23.9% and maintain a maximum water-to-wire efficiency of 82.3%, meeting the goals of the project.

13 HYDRO ENERGY↗