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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Developing Efficient Perovskite/Silicon Tandem Devices

This project aims at developing highly efficient perovskite/silicon tandem solar cells by developing efficient perovskite top cells, silicon bottom cells, and monolithically integrating the subcells for highly efficient tandem solar cells. The project focused on increasing the efficiency of perovskite solar cells to 20% and understanding related materials science and device physics, as well as developing a compatible bottom high-efficiency c-Si solar cell. The perovskite cells with a wide bandgap of 1.61 eV and 1.84 eV are fabricated by a low-cost, low-temperature, scalable solution process on lower bandgap silicon bottom cells. The bandgaps of perovskite top cells have been tuned between 1.61 eV and 1.84 eV by composition engineering mainly through controlling the halide mixing ratio in perovskite materials. The efficiencies of the wide bandgap perovskite solar cells have been improved to an excellent efficiency of 21.0% for perovskites with a bandgap of 1.63 eV with increased grain size, reduced energy disorder at cathode contact, and defect passivation. We invented a solvent annealing approach with solvent vapor during thermal annealing to enlarge grain size of perovskite film which reduces the charge trap density and improves the device efficiency. Moreover, we discovered that the non-wetting surface could further increase the grain size for perovskite films, because non-wetting surface could prevent the formation of too dense nuclei from heterogeneous nucleation process. We proposed to reduce the energy disorder of organic charge extraction layer to reduce the power loss in perovskite cells. We pioneered defect passivation concept and techniques to suppress the charge non-radiative recombination in perovskite solar cells to boost the efficiency. For the silicon bottom cell development, different from the conventional silicon cell work under full illumination, the light available for the silicon bottom cell in tandem structure is mainly NIR region. We developed a NIR enhanced silicon cell with efficiency of 21.2% by applying a double-layer antireflection coating at the front side and a MgF2 back reflector layer at the rear side. For the perovskite/silicon tandem device, we achieved a highest reported power conversion efficiency of 25.4% in 2018, and further increased the efficiency up to 26.0% in 2019. The research on tandem solar cells focused on reducing reflection loss to <5% at spectrum of 300-1100 nm by antireflection layer, tuning the bandgap of perovskite film for matched current density between sub-cells, and utilizing a ITO layer between perovskite top cell and silicon bottom cell as interconnect layer without Voc loss. Finally, we developed a blading technique to fabricate perovskite films which produces perovskite solar cells with comparable or even superior efficiency to those made by non-scalable spin coating method. This paves the way for scaling up perovskite/silicon tandem solar cells using solution approach.

14 SOLAR ENERGY↗
DOE OSTI2021

Bayesian learning of orthogonal embeddings for multi-fidelity Gaussian Processes

Uncertainty propagation in complex engineering systems often poses significant computational challenges related to modeling and quantifying probability distributions of model outputs, as those emerge as the result of various sources of uncertainty that are inherent in the system under investigation. Gaussian Processes regression (GPs) is a robust meta-modeling technique that allows for fast model prediction and exploration of response surfaces. Multi-fidelity variations of GPs further leverage information from cheap and low fidelity model simulations in order to improve their predictive performance on the high fidelity model. In order to cope with the high volume of data required to train GPs in high dimensional design spaces, a common practice is to introduce latent design variables that are typically projections of the original input space to a lower dimensional subspace, and therefore substitute the problem of learning the initial high dimensional mapping, with that of training a GP on a low dimensional space. Here in this paper, we present a Bayesian approach to identify optimal transformations that map the input points to low dimensional latent variables. The \projection" mapping consists of an orthonormal matrix that is considered a priori unknown and needs to be inferred jointly with the GP parameters, conditioned on the available training data. The proposed Bayesian inference scheme relies on a two-step iterative algorithm that samples from the marginal posteriors of the GP parameters and the projection matrix respectively, both using Markov Chain Monte Carlo (MCMC) sampling. In order to take into account the orthogonality constraints imposed on the orthonormal projection matrix, a Geodesic Monte Carlo sampling algorithm is employed, that is suitable for exploiting probability measures on manifolds. We extend the proposed framework to multi-fidelity models using GPs including the scenarios of training multiple outputs together. We validate our framework on three synthetic problems with a known lower-dimensional subspace. The benefits of our proposed framework, are illustrated on the computationally challenging aerodynamic optimization of a last-stage blade for an industrial gas turbine, where we study the effect of an 85-dimensional shape parameterization of a three-dimensional airfoil on two output quantities of interest, specifically on the aerodynamic efficiency and the degree of reaction

42 ENGINEERING↗
DOE OSTI2022

Attributes of Bi-Directional Turbomachinery for Pumped Thermal Energy Storage

Abstract In this paper, we (i) present a methodology for determining the aerodynamic performance of bi-directional turbomachines for pumped thermal energy storage, i.e., turbomachines designed to operate as a compressor in one direction, and then as a turbine in the opposite direction, (ii) carry out performance computations for such turbomachines, and (iii) propose principles for conceptual design of these devices. Focus is placed on using the energy storage cycle not only to identify the novel requirements placed on bi-directional turbomachines but also to estimate the effect of these requirements on the efficiency of the energy storage process. In particular, the difference between aerodynamic loading in forward and in backward operation causes the blading to work at incidences leading to the performance below maximum efficiency, resulting in a lower round-trip efficiency. The description of the design principles includes determination of the number of stages, definition of nondimensional parameters for blading selection, and optimization of two-dimensional blading for bi-directional operation. The assessment of stage count shows the relationship between relative Mach number, pressure ratio, and round-trip efficiency. The nondimensional parameters are assessed through a bi-directional analogue to existing “Smith charts,” for the efficiency of single-direction turbomachines, as a function of camber and stagger. The blade shape evaluation and optimization show how the blade profile can be modified to address the requirements of a bi-directional turbomachine, enabling an increase in round-trip efficiency of two percentage points compared to a baseline double circular arc configuration.

Engineering↗
DOE OSTI2021

Accomplishments and Year-End Performance Report; Wind Energy Program: Fiscal Year 2021

The National Wind Technology Center (NWTC), located at the U.S. Department of Energy's (DOE's) National Renewable Energy Laboratory (NREL) Flatirons Campus, has been a driving force in advancing wind energy technology research worldwide since its designation as a DOE national research center in 1992. Enabled by the Flatirons Campus's world-class facilities, scientists, engineers, analysts, and researchers are pushing the frontiers of science to pursue wind energy innovation. In Fiscal Year (FY) 2021, NREL continued to provide the technical expertise, research capabilities, and industry understanding to support DOE's ambitious climate action and research goals by advancing technology, addressing market and deployment barriers, and driving down costs with more efficient, reliable, and predictable wind energy systems. One of several highlights, NREL received an R&D 100 Special Recognition Award for its Thermoplastic Resin System for Wind Turbine Blades. This breakthrough in the wind turbine manufacturing process will enable the production of recyclable blades that are stronger, longer, and less expensive, while increasing energy capture, decreasing energy and transportation costs, and increasing blade reliability. In a year when the entire U.S. economy struggled to address workforce gaps, an NREL study compared wind industry needs, training programs, and hiring practices with perspectives from students and recent college graduates. Researchers hope that, by pinpointing areas of disconnect, the expectations of employers who have difficulty filling entry-level jobs can better align with the preparation of the potential applicants who find it hard to break into the field. The lab also made numerous new data and modeling resources available in FY 2021. Recent NREL releases include a modeling tool for predicting the power performance and structural loads of wind turbines within a wind farm (FAST.Farm), a computational framework for modeling golden eagle behavior near wind farms, and 20 years of offshore wind data. Updates were also made to the widely used Wind Plant Integrated Systems Design and Engineering Model (WISDEM), which couples engineering and cost models to examine system-level trade-offs. Now, bolstered by a renewed national commitment to tackle climate change and revitalize the U.S. economy through increased investment in clean energy - particularly in offshore wind energy - NREL stands poised to lead the way to a sustainable future that powers the United States with significant levels of reliable, low-cost, accessible wind energy. This report provides an overview of the achievements NREL made on behalf of DOE's Wind Energy Technologies Office (WETO) and other partners during FY 2021 (between Oct. 1, 2020, and Sept. 30, 2021).

Flatirons Campus↗
DOE OSTI2023

Green-Solvent Processed Blade-Coating Organic Solar Cells with an Efficiency Approaching 19% Enabled by Alkyl-Tailored Acceptors

Power-conversion-efficiencies (PCEs) of organic solar cells (OSCs) in laboratory, normally processed by spin-coating technology with toxic halogenated solvents, have reached over 19%. However, there is usually a marked PCE drop when the blade-coating and/or green-solvents toward large-scale printing are used instead, which hampers the practical development of OSCs. Here, a new series of N-alkyl-tailored small molecule acceptors named YR-SeNF with a same molecular main backbone are developed by combining selenium-fused central-core and naphthalene-fused end-group. Thanks to the N-alkyl engineering, NIR-absorbing YR-SeNF series show different crystallinity, packing patterns, and miscibility with polymeric donor. The studies exhibit that the molecular packing, crystallinity, and vertical distribution of active layer morphologies are well optimized by introducing newly designed guest acceptor associated with tailored N-alkyl chains, providing the improved charge transfer dynamics and stability for the PM6:L8-BO:YR-SeNF-based OSCs. As a result, a record-high PCE approaching 19% is achieved in the blade-coating OSCs fabricated from a green-solvent o-xylene with high-boiling point. Notably, ternary OSCs offer robust operating stability under maximum-power-point tracking and well-keep > 80% of the initial PCEs for even over 400 h. Our alkyl-tailored guest acceptor strategy provides a unique approach to develop green-solvent and blade-coating processed high-efficiency and operating stable OSCs, which paves a way for industrial development.

14 SOLAR ENERGY↗
DOE OSTI2022

Defect engineering in wide-bandgap perovskites for efficient perovskite–silicon tandem solar cells

Wide-bandgap (WBG) mixed-halide perovskites show promise of realizing efficient tandem solar cells but at present suffer from large open-circuit voltage loss and the mechanism is still unclear. Here we show that WBG perovskites with iodide–bromide compositions have an increased concentration of deep traps induced by iodide interstitials, which limits performance of WBG perovskite cells. We employ tribromide ions to suppress the iodide interstitial formation and thus reduce charge recombination in bladed WBG perovskite films of Cs 0.1 FA 0.2 MA 0.7 Pb(I 0.85 Br 0.15 )3. The 1-µm-thick opaque WBG perovskite solar cells have an efficiency of 21.9%, a small open-circuit voltage deficit of 0.40 V and a large fill factor of 83%. The efficiency of the best-performing monolithic perovskite–silicon tandem cell using this perovskite reaches 28.6%. Furthermore, the tribromide addition also suppresses light-induced phase segregation in WBG perovskites and thus enhance device stability. Encapsulated tandem cells maintain 93% of their initial efficiency after operation for 550 h.

14 SOLAR ENERGY↗
DOE OSTI2022

Modeling deformation and failure in AlSi-polyester abradable sealcoating material using microstructure-based finite element simulation

A plasma-sprayed aluminum-silicon (AlSi)/polyester coating is applied in modern gas turbine engines as an abradable sealcoating to maintain tight clearances between the rotating blades and the static casing. While running the engine, the rotating blades “rub” with the abradable coating, which results in extreme strain rate (up to 10 6 ) dynamics and a high-temperature environment. Due to the difficulty of collecting direct measurements, predictive computational models are important for analyzing the deformation and failure of the abradable material, to help meet the design target of avoiding damage to the blade tip and maintaining high fuel efficiency. In this research, a microstructure-based finite element (FE) computational model was developed to capture the complex mechanical behavior of the AlSi/polyester microstructure. The model is based on a virtual representative-volume-element (RVE) of a metal-polymer microstructure, reconstructed from x-ray computed tomography. It models the plastic deformation of, and damage to, each AlSi and polyester constituents, as well as the failure at their interface. The model was calibrated and validated with uniaxial tension and compression experiments, conducted at two temperatures (298 K and 533 K) at an applied strain rate of 10 3 - 10 4 s -1 . The material exhibited strongly asymmetric tension-compression behavior and a sensitivity to temperature, which was well captured by the model. The model was further applied to investigate changes in mechanical behavior due to variations in constituents’ volume fractions, which provides guidance to the microstructural design of AlSi/polyester abradable materials. The model is expected to facilitate the development of improved abradable materials by bypassing the conventional trial-and-error approach and extensive testing requirements.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Current state and future trends in boundary layer control on lifting surfaces

Successful flow control may bring numerous benefits, such as flow stabilization, flow reattachment, separation delay, drag reduction, lift increase, aerodynamic performance improvement, energy efficiency increase, shock delay or weakening, noise reduction, etc. For these purposes, many different flow control devices, which can be classified as passive, semi-active and active, have been designed and tested. This review paper aims to highlight the most promising and commonly employed boundary layer control methods as well as outline their potential in specific applications in aerospace and energy engineering. Referenced studies, performed on various geometries (flat plates, channels, airfoils, wings, blades, cylinders), are primarily numerical or experimental. Although enhanced aerodynamic performance is achieved in many cases, further research is required to draw general conclusions. This paper aims to demonstrate that, in the future, we may expect further developments of flow control actuators, as well as their increased application.

42 ENGINEERING↗
DOE OSTI2020

Characterization of Rare-earth Doped Thermal Barrier Coatings for Phosphor Thermometry

Thermal Barrier Coatings have been extensively used to protect and insulate the metallic components in turbine engines from extreme environments to achieve higher turbine inlet temperatures, resulting in an increase in combined engine cycle efficiency, lowering NOx emissions and fuel consumption. Additionally, as the major failure mechanisms determining lifetime are thermally activated during engine operation, uncertainty in temperature measurements affects lifetime prediction. Early detection of Thermal Barrier Coatings spallation symptoms, associated with local delamination induced temperature changes, can reduce forced engine outages. Further improvements are envisioned with the development of more reliable measurement techniques. For this purpose, Phosphor Thermometry has been considered a promising method for precision monitoring of turbine blade coatings that contain embedded phosphor dopants. In this work, a modified four-flux Kubelka-Munk model for luminescent rare-earth doped Thermal Barrier Coating configurations supported the design and the fabrication of viable sensing coatings for potential industrial implementation. Phosphor Thermometry instrumentation was developed with the objective of expanding capabilities of the technique, using a synchronized acquisition method on sensing coatings. Experiments on an innovative Erbium-Europium co-doped Yttria-Stabilized Zirconia coating have demonstrated the effectiveness of this advanced Phosphor Thermometry instrument with enhanced sensitivity and extended temperature range. Delamination progression monitoring was achieved for the first time using a Thermal Barrier Coating configuration subjected to indentation that includes a thin luminescent layer deposited on the surface and associating the multi-layer configuration with a predictive model that evaluates the advancement of the degradation of the coatings. To further ensure the integrity of the phosphor doped coatings, synchrotron X-ray diffraction was performed to characterize the specific residual strains and thermal expansion of the materials, determining mechanical robustness and compatibility with state-of-the-art Thermal Barrier Coatings. The outcomes of this work pave the way for in-situ temperature measurements on phosphor-doped turbine blade coatings with increased performance and accuracy.

Fouliard, Quentin↗
DOE OSTI2024

Design and Cooling Performance of Additively Manufactured Ceramic Turbine Vanes

Ceramic materials are of significant interest in aviation and power generation gas turbine engines due to their low density and ability to withstand high temperatures. Increased cycle thermal efficiency and higher specific power output is possible by incorporating ceramic components that enable high turbine inlet temperatures and lower required cooling airflow levels. However, ceramics can be difficult and costly to form into the complex shapes used in gas turbine components, often requiring specialized multi-step processes. Furthermore, ceramic components in the hottest areas of a gas turbine, such as vanes or blade shroud seals, will still likely require cooling which is challenging to implement in conventional ceramic manufacturing approaches. Therefore, this study presents a multidisciplinary approach that investigates the design, fabrication, and overall cooling effectiveness evaluation of additively manufactured (AM), polymer derived ceramic (PDC) turbine vanes. A thermo-mechanically optimized vane design was generated, ceramic additive manufacturing of the complex cooling configuration was developed, and quantification of the increase in overall cooling effectiveness was performed in a 1X scale, high-speed facility using infrared thermography. This study produced a PDC AM process, capable of printing complex internal cooling schemes in 1X scale turbine vanes. Furthermore, it was found that the optimized vane more than doubled the overall cooling effectiveness observed in the baseline design, which reasonably agreed with thermomechanical optimization model predictions. Additionally, the optimized ceramic vane outperformed an identical metal vane, in terms of area averaged cooling effectiveness, suggesting that the ceramic vane could operate at reduced coolant flowrates to achieve comparable levels of cooling performance.

Reynolds number↗
DOE OSTI2023

Design and Cooling Performance of Additively Manufactured Ceramic Turbine Vanes

Ceramic materials are of significant interest in aviation and power generation gas turbine engines due to their low density and ability to withstand high temperatures. Increased cycle thermal efficiency and higher specific power output is possible by incorporating ceramic components that enable high turbine inlet temperatures and lower required cooling airflow levels. However, ceramics can be difficult and costly to form into the complex shapes used in gas turbine components, often requiring specialized multi-step processes. Furthermore, ceramic components in the hottest areas of a gas turbine, such as vanes or blade shroud seals, will still likely require cooling which is challenging to implement in conventional ceramic manufacturing approaches. Therefore, this study presents a multidisciplinary approach that investigates the design, fabrication and overall cooling effectiveness evaluation of additively manufactured (AM), polymer derived ceramic (PDC) turbine vanes. A thermo-mechanically optimized vane design was generated, ceramic additive manufacturing of the complex cooling configuration was developed, and quantification of the increase in overall cooling effectiveness was performed in a 1X scale, high-speed facility using infrared thermography. This study produced a PDC AM process, capable of printing complex internal cooling schemes in 1X scale turbine vanes. It was found that the optimized vane more than doubled the overall cooling effectiveness observed in the baseline design, which reasonably agreed with thermomechanical optimization model predictions. Additionally, the optimized ceramic vane outperformed an identical metal vane, in terms of area averaged cooling effectiveness, suggesting that the ceramic vane could operate at reduced coolant flow rates to achieve comparable levels of cooling performance.

Fox, Andrew↗
DOE OSTI2026

Molecular Additive Engineering for Process-Humidity Robustness and Reproducible Fabrication of Perovskite Solar Cells and Modules

The commercialization of perovskite solar cells (PSCs) faces significant challenges due to their sensitivity to environmental humidity, which compromises film crystallization and device stability. Here, we introduce diphenylvinylphosphine (DPVP) as a Lewis base additive that enhances the performance and reproducibility of PSCs fabricated under ambient-air conditions. DPVP suppresses moisture-induced defect formation and stabilizes crystallization within realistic process-humidity ranges (20–40% relative humidity) commonly encountered in laboratory and pilot-scale manufacturing environments. It improves film uniformity, reduces trap densities, and yields highly reproducible device performance, enabling champion PCEs of 24.2% in small-area devices and 20.5% in blade-coated 12 cm 2 mini-modules. Furthermore, DPVP-assisted modules exhibit enhanced stability, retaining over 85% of their initial efficiency after 900 h of maximum power point tracking (MPPT) at 65 °C. This study demonstrates a humidity-resilient and scalable additive strategy for ambient-air perovskite photovoltaic manufacturing.

defect passivation↗
DOE OSTI2021

Process for retrofitting an industrial gas turbine engine for increased power and efficiency

A process for retrofitting an industrial gas turbine engine of a power plant where an old industrial engine with a high spool has a new low spool with a low pressure turbine that drives a low pressure compressor using exhaust gas from the high pressure turbine, and where the new low pressure compressor delivers compressed air through a new compressed air line to the high pressure compressor through a new inlet added to the high pressure compressor. The old electric generator is replaced with a new generator having around twice the electrical power production. One or more stages of vanes and blades are removed from the high pressure compressor to optimally match a pressure ratio split. Closed loop cooling of one or more new stages of vanes and blades in the high pressure turbine is added and the spent cooling air is discharged into the combustor.

Jones, Russell B.↗
DOE OSTI2022

CAMERA: A method for cost-aware, adaptive, multifidelity, efficient reliability analysis

Estimating probability of failure in aerospace systems is a critical requirement for flight certification and qualification. Failure probability estimation involves resolving tails of probability distributions, and Monte Carlo sampling methods are intractable when expensive high-fidelity simulations have to be queried. Here, we propose a method to use models of multiple fidelities that trade accuracy for computational efficiency. Specifically, we propose the use of multifidelity Gaussian process models to efficiently fuse models at multiple fidelity, thereby offering a cheap surrogate model that emulates the original model at all fidelities. Furthermore, we propose a novel sequential acquisition function based experiment design framework that can automatically select samples from appropriate fidelity models to make predictions about quantities of interest at the highest fidelity. We use our proposed approach in an importance sampling setting and demonstrate our method on the failure level set and probability estimation on synthetic test functions and two real-world applications, namely, the reliability analysis of a gas turbine engine blade using a finite element method and a transonic aerodynamic wing test case using Reynolds-averaged Navier-Stokes equations. We show that our method predicts the failure boundary and probability more accurately and at a fraction of the computational cost compared with using just a single expensive high-fidelity model. Finally, we show that our sequential approach is guaranteed to asymptotically converge to the true failure boundary with high probability.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Utilizing the unique charge extraction properties of antimony tin oxide nanoparticles for efficient and stable organic photovoltaics

Simultaneously enhancing device performance and longevity, as well as balancing the requirements on cost, scalability, and simplification of processing, is the goal of interface engineering of organic solar cells (OSCs). In our work, we strategically introduce antimony (Sb 3+ ) cations into an efficient and generic n-type SnO 2 nanoparticles (NPs) host during the scalable flame spray pyrolysis synthesis. Accordingly, a significant switch of conduction property from an n-type character to a p-type character is observed, with a corresponding shift in the work function (WF) from 4.01 ± 0.02 eV for pristine SnO 2 NPs to 5.28 ± 0.02 eV for SnO 2 NPs with 20 mol. % Sb content (ATO). Both pristine SnO 2 and ATO NPs with fine-tuned optoelectronic properties exhibit remarkable charge carrier extraction properties, excellent UV resistance and photo-stability being compatible with various state-of-the-art OSCs systems. The reliable and scalable pristine SnO 2 and ATO NPs processed by doctor-blading in air demand no complex post-treatment. Our work offers a simple but unique approach to accelerate the development of advanced interfacial materials, which could circumvent the major existing interfacial problems in solution-processed OSCs.

14 SOLAR ENERGY↗
DOE OSTI2024

Percheron Power Archimedes Screw Turbine Analysis (Abstract)

The development of the Percheron Power (Percheron) composite Archimedes screw turbine (AST) is based upon employing newly developed theoretical mathematical models for optimizing the water volume carried through the AST for a given diameter, combined with minimizing efficiency losses due to bypass flow and friction. The key feasibility issues associated with producing the composite blades will be to understand the strength, fatigue, and wear performance of the AST blades and associated components, and how these factors change along the length of the turbine. To get to this understanding of material property requirements, Percheron needs free-surface computational fluid dynamics (CFD) models of the AST designs and to perform interactive modeling between the turbine blade optimization and component design based on finite element method stress analysis (FEA). The workscope and analyses requested by Percheron in the Small Business Voucher (SBV) program are well aligned with PNNL capability and recent work experience in performing CFD and FEA analysis for hydropower and marine energy turbines. The CFD analysis will provide estimates of power, efficiency, and surface forces on the blades. The forces on the blade will be transferred to the FEA analysis that will be used to evaluate the material stresses. The CFD and FEA analyses will be repeated for different AST designs provided to PNNL by Percheron. The work conducted in this SBV project will complement the existing Percheron FOA project by providing better defined parameters for design and material selection for the turbine unit prior to manufacture of initial test units.

42 ENGINEERING↗
DOE OSTI2023

CFD-based design optimization of ducted hydrokinetic turbines

Abstract Hydrokinetic turbines extract kinetic energy from moving water to generate renewable electricity, thus contributing to sustainable energy production and reducing reliance on fossil fuels. It has been hypothesized that a duct can accelerate and condition the fluid flow passing the turbine blades, improving the overall energy extraction efficiency. However, no substantial evidence has been provided so far for hydrokinetic turbines. To investigate this problem, we perform a CFD-based optimization study with a blade-resolved Reynolds-averaged Navier–Stokes (RANS) solver to explore the design of a ducted hydrokinetic turbine that maximizes the efficiency of energy extraction. A gradient-based optimization approach is utilized to effectively deal with the high-dimensional design space of the blade and duct geometry, with gradients being calculated through the adjoint method. The final design is re-evaluated through higher-fidelity unsteady RANS (URANS) simulations. Our optimized ducted turbine achieves an efficiency of about 54% over a range of operating conditions, higher than the typical 46% efficiency of unducted turbines.

13 HYDRO ENERGY↗