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At least 1,027 records · Page 57
All sourcesNASA NTRSDOE OSTI
NASA NTRS2000

Real Time Intelligent Target Detection and Analysis with Machine Vision

We present an algorithm for detecting a specified set of targets for an Automatic Target Recognition (ATR) application. ATR involves processing images for detecting, classifying, and tracking targets embedded in a background scene. We address the problem of discriminating between targets and nontarget objects in a scene by evaluating 40x40 image blocks belonging to an image. Each image block is first projected onto a set of templates specifically designed to separate images of targets embedded in a typical background scene from those background images without targets. These filters are found using directed principal component analysis which maximally separates the two groups. The projected images are then clustered into one of n classes based on a minimum distance to a set of n cluster prototypes. These cluster prototypes have previously been identified using a modified clustering algorithm based on prior sensed data. Each projected image pattern is then fed into the associated cluster's trained neural network for classification. A detailed description of our algorithm will be given in this paper. We outline our methodology for designing the templates, describe our modified clustering algorithm, and provide details on the neural network classifiers. Evaluation of the overall algorithm demonstrates that our detection rates approach 96% with a false positive rate of less than 0.03%.

Howard, Ayanna↗
NASA NTRS1983

Validation of structural analysis methods using burner liner cyclic rig test data

The objectives of the hot section technology (HOST) burner liner cyclic rig test program are basically threefold: (1) to assist in developing predictive tools needed to improve design analyses and procedures for the efficient and accurate prediction of burner liner structural response; (2) to calibrate, evaluate and validate these predictive tools by comparing the predicted results with the experimental data generated in the tests; and (3) to evaluate existing as well as advanced temperature and strain measurement instrumentation, both contact and noncontact, in a simulated engine cycle environment. The data generated will include measurements of the thermal environment (metal surface temperatures) as well as structural (strain) and life (fatigue) responses of simulated burner liners and specimens under controlled boundary and operating conditions. These data will be used to calibrate, compare and validate analytical theories, methodologies and design procedures, as well as improvements in them, for predicting liner temperatures, stress-strain responses and cycles to failure. Comparison of predicted results with experimental data will be used to show where the predictive theories, etc. need improvements. In addition, as the predictive tools, as well as the tests, test methods, and data acquisition and reduction techniques, are developed and validated, a proven, integrated analysis/experiment method will be developed to determine the cyclic life of a simulated burner liner.

Thompson, R.↗
DOE OSTI2020

Metal-embedded fiber optic sensor packaging and signal demodulation scheme towards high-frequency dynamic measurements in harsh environments

Optical fiber-based sensors are commonly used for industrial monitoring and control processes due to their small size, resistance to electromagnetic interference, and ability to perform a wide variety of high-precision measurements. However, implementing optical fiber sensors in harsh environments is challenging because they are small and fragile. Proper packaging of fiber-optic sensors could extend their use to harsh environments, including at high temperature and under high radiation. Furthermore, conventional fiber optic-based measurement systems often use computationally expensive signal processing algorithms which hinder their use in high-frequency dynamic applications. This work reports on the design of an optical fiber-pressure sensor system based on low-coherence interferometry that uses a metal-embedded optical fiber to provide a robust sensor package. Additionally, a novel phase demodulation scheme is proposed to extract length changes from the deformation of a thin diaphragm within a Fabry–Pérot cavity to measure pressure. The sensor has been tested to ±100 kPa, has a theoretical linear response over a 270 kPa dynamic range (24 dB maximum signal-to-noise ratio), and can resolve pressure transients up to 3910 kPa/s. Sampling at 100 kHz, the present sensor can resolve 2 kPa dynamic pressures at frequencies up to 2 kHz. Faster transients on the order of tens to hundreds of kHz can theoretically be resolved at the expense of decreasing the maximum resolvable amplitude. A methodology for designing a LCI pressure sensor for a given application is outlined based on the limitations imposed by the Nyquist criterion, the diaphragm's resonant frequency, the LCI optoelectronics, and the phase demodulation scheme. The sensor is the first to implement a low-coherence light source and a Fabry–Pérot interferometer designed to provide real-time high-fidelity pressure measurements using a metal-embedded optical fiber. The demonstrated sensor provides a platform for sensing in harsh conditions such as in nuclear and energy applications.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

A modular methodology for time-domain stochastic seismic wave propagation

Presented here is a modular methodology for time-domain stochastic seismic wave propagation analysis. Presented methodology is designed to analyse uncertain seismic motions as an input, propagating through uncertain material. Traditional approach for uncertain wave propagation relies on models that include deep bedrock, local soil site, and their random process and random field information. Such models can become quite large and computationally intractable. The modular approach proposed herein features two step approach that allows separate consideration of the deep bedrock and local site along with corresponding random field information. In this work, the first step considers an auxiliary stochastic motions problem in the bedrock. Stochastic local site response can then be simulated in a reduced domain within certain depth from the surface. Application of uncertain seismic motions at depth, for local uncertain site response is done using stochastic effective forces developed through the Domain Reduction Method. By using Hermite polynomial chaos expansion to represent the non-Gaussian random field of material parameters and non-stationary random process of seismic motion, the proposed modular methodology is formulated using intrusive stochastic Galerkin approach, as seen in the Stochastic Elastic–Plastic Finite Element Method (SEPFEM). Developed modular methodology is illustrated using a 1-D stochastic seismic wave propagation analysis with three cases, and simulation results are also verified with results from conventional approach.

58 GEOSCIENCES↗
NASA NTRS2018

A Common Probe Design for Multiple Planetary Destinations

Atmospheric probes have been successfully flown to planets and moons in the solar system to conduct in situ measurements. They include the Pioneer Venus multi-probes, the Galileo Jupiter probe, and Huygens probe. Probe mission concepts to five destinations, including Venus, Jupiter, Saturn, Uranus, and Neptune, have all utilized similar-shaped aeroshells and concept of operations, namely a 45-degree sphere cone shape with high density heatshield material and parachute system for extracting the descent vehicle from the aeroshell. Each concept designed its probe to meet specific mission requirements and to optimize mass, volume, and cost. At the 2017 International Planetary Probe Workshop (IPPW), NASA Headquarters postulated that a common aeroshell design could be used successfully for multiple destinations and missions. This "common probe" design could even be assembled with multiple copies, properly stored, and made available for future NASA missions, potentially realizing savings in cost and schedule and reducing the risk of losing technologies and skills difficult to sustain over decades. Thus the NASA Planetary Science Division funded a study to investigate whether a common probe design could meet most, if not all, mission needs to the five planetary destinations with extreme entry environments. The Common Probe study involved four NASA Centers and addressed these issues, including constraints and inefficiencies that occur in specifying a common design. Study methodology: First, a notional payload of instruments for each destination was defined based on priority measurements from the Planetary Science Decadal Survey. Steep and shallow entry flight path angles (EFPA) were defined for each planet based on qualification and operational g-load limits for current, state-of-the-art instruments. Interplanetary trajectories were then identified for a bounding range of EFPA. Next, 3-degrees-of-freedom simulations for entry trajectories were run using the entry state vectors from the interplanetary trajectories. Aeroheating correlations were used to generate stagnation point convective and radiative heat flux profiles for several aeroshell shapes and entry masses. High fidelity thermal response models for various Thermal Protection System (TPS) materials were used to size stagnation-point thicknesses, with margins based on previous studies. Backshell TPS masses were assumed based on scaled heat fluxes from the heatshield and also from previous mission concepts. Presentation: We will present an overview of the study scope, highlights of the trade studies and design driver analyses, and the final recommendations of a common probe design and assembly. We will also indicate limitations that the common probe design may have for the different destinations. Finally, recommended qualification approaches for missions will be presented.

Hwang, H. H.↗
DOE OSTI2022

Surface Charge and Nanoparticle Chromophore Coupling to Achieve Fast Exciton Quenching and Efficient Charge Separation in Photoacoustic Imaging (PAI) and Photothermal therapy (PTT)

Abstract An organic semiconductor nanoparticle (OSN) with surface charge strategy is proposed, which displays excellent photothermal conversion performance. The donor–acceptor hybrid organic semiconductor Y6 is selected as a photothermal chromophore into nanoparticle by self‐assembly, which affords long wavelength absorption, sub‐bandgap emission, and high photon‐to‐thermal conversion. Y6 in OSN adopts closed packing comparing to that in single crystal. The surface charge in OSN causes super‐quenching of the photon excitons, which enhances the nonradiative transition to improve photothermal effect. Lower energy level electronic states are created, which breaks up the bandgap limit and leads to long wavelength emission over 1100 nm. Photothermal therapy and photoacoustic imaging are applied successfully, indicating the success of the new methodology in designing photothermal conversion materials.

Pharmacology & Pharmacy↗
DOE OSTI2024

Programmable bionanocomposite coated fertilizers for prolonged controlled release of nitrogen

Controlled-release fertilizers (CRFs) present a promising solution for alleviating food and nutrient scarcity. However, their development has been mainly hindered by both rapid and unsynchronized nutrient release and unsustainable coating materials. In this study, we address this issue by developing a new coating layer for CRFs using a programmable biopolyurethane nanocomposite. This nanocomposite is prepared from diphenylmethane diisocyanate (MDI)-functionalized bentonite nanoclay (BNT-MDI) and a biopolyol from biomass waste. The results show that the BNT-MDI-doped CRFs (BCRFs) exhibit an impressive nitrogen (N)-release longevity of approximately 120 days at a 4 wt% coating ratio, surpassing previous CRF formulations. In a 30-day snap bean cultivation study, BCRF significantly improved root length (1000%), leaf length (257%), leaf width (400%), and plant height (1400%) compared to the control. The superior performance of BCRF is attributed to the PU-nanoclay biocomposite film, with full nano-exfoliation, controllable porosity, and high crosslinking density. Furthermore, we introduce a new dynamic release mechanism and establish a quantitative relationship between the nanostructure, property, and release performance of BCRF by combining the multiplicative and diffusion models for porous materials. Finally, this study provides a theoretical framework and a straightforward methodology for designing programmable nanocomposite structures for future biobased CRFs.

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

Turbine scale and siting considerations in wind plant layout optimization and implications for capacity density

Improvements in wind energy technology, reduced costs, and ambitious clean energy goals have led to projections of high wind contribution in coming years. Developing methodologies to design wind plants with a variety of siting constraints and turbine sizes helps enable high wind penetration, and gain a better understanding of how wind plants are sensitive to setback constraints and turbine design. In this paper, we present a two-step optimization method to simultaneously determine the optimal number of turbines and their locations in a wind plant domain divided into many small, discrete parcels. We present the optimized performance metrics of a wind plant optimized with different turbine sizes and ratings, and with different siting restrictions within the wind plant. Our results indicate that taller and larger turbines are more sensitive to increasing siting constraints. We also compare the optimal wind plant layouts and performance for wind plants optimized for minimum COE and maximum profit. Wind plants optimized for profit had 130%-190% of the capacity of plants optimized for COE, which demonstrates that the optimal results are greatly affected by the objective function, which should be carefully considered. Finally, in this paper we demonstrate the effect of increasing siting constraints on wind plant capacity density, and how the results change when different land areas are used to calculate capacity density. When using the entire wind plant boundary area to determine capacity density, increasing siting constraints decreases the capacity density. However, when we only use the available area (the area left after removing the siting constraints) to calculate the capacity density, increasing the siting constraints increases capacity density. This is a critical insight because of how capacity density is typically defined and used in research, and has important implications for assessment of technical potential and capacity expansion modeling, as well as future wind deployment potential.

17 WIND ENERGY↗
DOE OSTI2020

Symmetric fielding of the largest diamond capsule implosions on the NIF

We present results for the largest diamond capsule implosions driven symmetrically on the National Ignition Facility (NIF) (inner radius of ~1050 μm) without the use of cross beam transfer in cylindrical Hohlraums. We show that the methodology of designing Hohlraum parameters in a semi-empirical way using an extensive database resulted in a round implosion. In addition, we show that the radiation flux symmetry is well controlled during the foot of the pulse and that swings in P2 symmetry between the inflight dense shell and hot spot are within ±4 μm and that swings around peak compression are also within the symmetry specification of ±4 μm. We observed a stronger dependence of symmetry on the capsule scale than previously observed and also observed enhanced inner beam propagation for experiments using a gas fill density of 0.3 mg/cm 3 and 1000 μm inner radius capsules. We have observed sufficient symmetry and mass remaining at near full NIF power and energy, up to 480 TW and 1.9 MJ, with little laser–plasma interactions (low laser backscattered light) and predict that this design could support extended NIF energy of up to 2.1 MJ.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Vertically assembled nanosheet networks for high-density thick battery electrodes

As one of the prevailing energy storage systems, lithium-ion batteries (LIBs) have become an essential pillar in electric vehicles (EVs) during the past decade, contributing significantly to a carbon-neutral future. However, the complete transition to electric vehicles requires LIBs with yet higher energy and power densities. Here, we propose an effective methodology via controlled nanosheet self-assembly to prepare low-tortuosity yet high-density and high-toughness thick electrodes. By introducing a delicate densification in a three-dimensionally interconnected nanosheet network to maintain its vertical architecture, facile electron and ion transports are enabled despite their high packing density. This dense and thick electrode is capable of delivering a high volumetric capacity >1,600 mAh cm −3 , with an areal capacity up to 32 mAh cm −2 , which is among the best reported in the literature. The high-performance electrodes with superior mechanical and electrochemical properties demonstrated in this work provide a potentially universal methodology in designing advanced battery electrodes with versatile anisotropic properties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Techno-Economic Analysis of Gas-Liquid Contactors for Tritium Extraction from Lead-Lithium

To enable a sustainable fuel cycle, any deuterium-tritium fusion reactor must breed its tritium fuel onsite. Lead-lithium (PbLi), a eutectic metal, is a leading liquid breeder material for tritium generation. One challenge with PbLi blanket technology is the extraction of tritium from the molten eutectic. Three technologies are the focus of worldwide research: the vacuum permeator, the vacuum sieve tray, and the gas-liquid contactor (GLC). The present work offers a methodology for designing, sizing, optimizing, and costing a trickle-bed GLC. Here, we analyzed tritium extraction from PbLi using MELODIE experimental data by applying traditional packed bed mass transfer efficiency models along with supplementary models, like film theory. Our analysis revealed that traditional packed bed mass transfer efficiency models do not fit the MELODIE loop experimental data. Moreover, uncertainty in PbLi solubility resulted in a 325-fold increase in required gas flow rates when comparing identical packing heights. The film theory liquid mass transfer coefficient, Delt-Olujic wettability model, and Reiter tritium solubility values fit the MELODIE data best and were used both in the design and to conduct the economic analysis. Techno-economic analysis of the GLC was performed to evaluate three design sizes, all achieving a minimum extraction efficiency of 90 [%] for a total tritium extraction of 31 [kg/yr].

Fusion Fuel Cycle↗
DOE OSTI2024

Evaluation of Converter Performance Considering Static and Dynamic Device Part-to-Part Variability

This paper presents a methodology to incorporate and analyze the impact of semiconductor device part-to-part variation on power converter performance. By integrating extensive static and dynamic device characterization data with an automated compact model generation process that reflects manufacturing variability, device models with inherent variability features are utilized in converter simulations for a comprehensive assessment of performance impacts. The traditional converter performance evaluation process typically yields fixed efficiency values, often dismissing the inherent part-to-part variability caused by the manufacturing process of semiconductor devices. To address this limitation, a large population of devices was characterized to capture variations in static parameters-such as transfer, output, and capacitance characteristics-as well as dynamic behaviors, including switching losses. This data-driven approach enables the development of individual compact models, which were then integrated into converter simulations to evaluate efficiency ranges rather than single point estimated values. The converter simulation results show that part-to-part component variation can lead to significant efficiency deviations, exceeding several percentage points in high-power conversion applications. By offering a more accurate representation of converter behavior under real-world manufacturing conditions, this methodology enables designers to anticipate performance variability, improving the robustness of power converter designs.

device characterization↗
DOE OSTI2022

Next-Cycle Optimal Dilute Combustion Control via Online Learning of Cycle-to-Cycle Variability Using Kernel Density Estimators

Dilute combustion using exhaust gas recirculation (EGR) presents a cost-effective method for increasing the efficiency of spark-ignition (SI) engines. However, the maximum amount of EGR that can be used at a given condition is limited by a rapid increment of cycle-to-cycle variability (CCV). This study describes a methodology to design a model-based stochastic optimal controller to adjust the cycle-to-cycle fuel injection quantity in order to reduce CCV and further extend the dilute limit. Given the complexity and chaotic nature of combustion events, the controller was enhanced with online learning in order to identify the statistical properties of combustion efficiency, which are needed to generate predictions for next-cycle events. This study showed that a kernel density estimator (KDE) can be used to learn the combustion properties in real time and can be incorporated into the feedback policy in order to calculate the optimal control command. Experimental results suggested that the dilute limit can be extended from 18.5% to 21% EGR fraction at an operating condition relevant for highway cruising. Additionally, the proposed controller can achieve a large CCV reduction with less fuel enrichment compared to previous methods, overall contributing to an increase in 0.2% indicated fuel conversion efficiency.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

Reimagining Disassembly Interfaces With Visualization: Combining Instruction Tracing and Control Flow With DisViz

In applications where efficiency is critical, developers may examine their compiled binaries, seeking to understand how the compiler transformed their source code and what performance implications that transformation may have. This analysis is challenging due to the vast number of disassembled binary instructions and the many-to-many mappings between them and the source code. These problems are exacerbated as source code size increases, giving the compiler more freedom to map and disperse binary instructions across the disassembly space. Interfaces for disassembly typically display instructions as an unstructured listing or sacrifice the order of execution. Here, we design a new visual interface for disassembly code that combines execution order with control flow structure, enabling analysts to both trace through code and identify familiar aspects of the computation. Central to our approach is a novel layout of instructions grouped into basic blocks that displays a looping structure in an intuitive way. We add to this disassembly representation a unique block-based mini-map that leverages our layout and shows context across thousands of disassembly instructions. Finally, we embed our disassembly visualization in a web-based tool, DisViz, which adds dynamic linking with source code across the entire application. DizViz was developed in collaboration with program analysis experts following design study methodology and was validated through evaluation sessions with ten participants from four institutions. Participants successfully completed the evaluation tasks, hypothesized about compiler optimizations, and noted the utility of our new disassembly view. Our evaluation suggests that our new integrated view helps application developers in understanding and navigating disassembly code.

Computer science↗
DOE OSTI2021

Learning Forecasts of Rare Stratospheric Transitions from Short Simulations

Abstract Rare events arising in nonlinear atmospheric dynamics remain hard to predict and attribute. We address the problem of forecasting rare events in a prototypical example, sudden stratospheric warmings (SSWs). Approximately once every other winter, the boreal stratospheric polar vortex rapidly breaks down, shifting midlatitude surface weather patterns for months. We focus on two key quantities of interest: the probability of an SSW occurring, and the expected lead time if it does occur, as functions of initial condition. These optimal forecasts concretely measure the event’s progress. Direct numerical simulation can estimate them in principle but is prohibitively expensive in practice: each rare event requires a long integration to observe, and the cost of each integration grows with model complexity. We describe an alternative approach using integrations that are short compared to the time scale of the warming event. We compute the probability and lead time efficiently by solving equations involving the transition operator, which encodes all information about the dynamics. We relate these optimal forecasts to a small number of interpretable physical variables, suggesting optimal measurements for forecasting. We illustrate the methodology on a prototype SSW model developed by Holton and Mass and modified by stochastic forcing. While highly idealized, this model captures the essential nonlinear dynamics of SSWs and exhibits the key forecasting challenge: the dramatic separation in time scales between a single event and the return time between successive events. Our methodology is designed to fully exploit high-dimensional data from models and observations, and has the potential to identify detailed predictors of many complex rare events in meteorology.

Finkel, Justin↗
DOE OSTI2023

Evaluation of printability methodologies and feasibility to down select LBPF steel and other materials for nuclear applications

In this work, new research is underway to produce alloys beyond well-known alloys with modified compositions that are better suited to be produced with additive manufacturing. These alloys can only possess improved radiation tolerance but also improved high temperature strength, creep resistance while also using elements that reduce the amount of activation after irradiation. This work package supports the vision and goals of the Advanced Materials and Manufacturing Technology (AMMT) program relevant to accelerate the development and deployment of advanced manufacturing processes. This work focuses on evaluating the methodology for designing alloys best suited for AM processes based on “printability”, literature research to evaluate and down select steel alloy systems. In this work, microstructural characterization and testing activities have been performed on certain steel alloys to support the efforts from collaborating laboratories during the evaluation and printing of the test articles. The final recommendation will be performed by all four participating laboratories.

316L↗
DOE OSTI2025

High-Speed and High-Quality Field Welding Repair Based on Advanced Non-Destructive Evaluation and Numerical Modeling

Creep strength-enhanced ferritic (CSEF) steels such as Grade 91 (9Cr-1Mo-V) and Grade 92 (Fe-9Cr-2W-0.5Mo) steels are widely used in the fossil-fuel-fired and nuclear power plants. The weld integrity of these steels is crucial for power plants' safe and reliable operations. Due to harsh service conditions, the steel weld can become susceptible to environmental degradation. Field welding repair is used to restore the degraded weld’s performance where a controlled temper-bead welding technique is commonly used to temper the freshly formed martensite during welding. However, knowledge of weld repairability is limited and experimental trial and error optimization to achieve desired microstructure and joint properties is expensive and time-consuming. Many existing computational models, e.g., finite element models, are limited to solving heat conduction equation and ignoring convective heat transfer due to molten metal flow. These models can result in over-prediction of peak temperatures of weld pool and heat-affected zone (HAZ), which in turn can affect the accuracy of tempering prediction. Moreover, these finite element models require an input of the deposit profiles in advance and thus limits the usability of these models. Here, a molten pool-based, multi-pass multi-layer model has been developed based on computational fluid dynamics (CFD) approach with the Volume of Fluid (VOF) method. The model calculates the bead formation, thereby eliminating the need for pre-determined bead profiles required by finite element models. For computational efficiency, a coordinate system attached to the moving heat source is utilized. A subroutine is developed to convert the temperature profiles in the reference frame stationary to the heat source to that stationary to the workpiece. The converted thermal cycles are then imported into a microstructure model to compute the tempering kinetics and resultant hardness using a Johnson-Mehl-Avrami-Kolmogorov (JMAK), and modified Grange-Baughman parameter. The modeling approach is first developed and validated on single- and multi-pass deposition of stainless steel filler metal onto a SA-533 high strength steel substrate. The models are then applied to a multi-pass V-groove repair weld of Grade 91 steel plate as well as directed energy deposition of Grade 92 steel. Non-destructive characterization of microstructures was performed on Grade 91 and 92 steel welds. Two welding processes, cold metal transfer (CMT) and flux-cored arc welding (FCAW), were investigated for the Grade 91 steel weld samples. For the Grade 92 weld samples, three different heat inputs (low, medium, and high) of gas tungsten arc welding (GTAW) were utilized to replicate traditional field welding processes. The non-destructive evaluation (NDE) method used for this research was immersion ultrasonic testing (UT) using a micro-resolution ultrasonic imaging methodology specifically designed to operate in the through-transmission configuration operating at 20 MHz of frequency. The system used a focused ultrasonic beam spot size diameter between 250-300 μm, and a 6 μm laser vibrometer spot size for detection, to produce highly defined images with longitudinal and mode-converted shear waves. From the micro-resolution ultrasonic C-scan images, three microstructural regions, i.e., weld metal (WM), HAZ, and base metal (BM), were clearly identifiable. Various levels of ultrasonic amplitudes distributed over the three regions were correlated with electron beam backscattered diffraction (EBSD) images using grain size, grain boundaries, and dislocation densities. The results showed that areas with relatively higher ultrasonic amplitude levels were associated with smaller grains and higher dislocation densities, while areas with lower amplitude levels were associated with larger grains and lower dislocation densities. In addition, ultrasonic velocity data obtained across the three different weld microstructural regions of Grade 91 test samples were correlated with optical metallographic images and hardness measurements. The results showed distinctive decreases in ultrasonic velocity and hardness over the HAZ region, where weld failures often occur during service.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Hardware-in-the-Loop Efficiency Analysis of Tidal Power Systems

Marine renewable energy presents an opportunity for sustainable power in areas located near and in the marine environment. In particular, tidal energy offers a consistent and reliable resource. However, tidal energy harvesting systems seeking to take advantage of this resource face challenges associated with power electronics. Power conversion electronics struggle with low efficiencies, lack of off-the-shelf options for small-scale energy harvesting systems, and limited opportunities for testing with deployed turbines. This work demonstrates a hardware-in-the-loop experimental design and methodology for characterizing efficiency of tidal turbine power electronics and control methods. The suggested method removes barriers to testing these power electronics by eliminating the need for a physical tidal turbine and generator to produce accurate harvested tidal power profiles.

tidal turbine, hardware-in-the-loop, energy conver↗