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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 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Assessment of task‐based performance from five clinical DBT systems using an anthropomorphic breast phantom

Purpose Digital breast tomosynthesis (DBT) is a limited‐angle tomographic breast imaging modality that can be used for breast cancer screening in conjunction with full‐field digital mammography (FFDM) or synthetic mammography (SM). Currently, there are five commercial DBT systems that have been approved by the U.S. FDA for breast cancer screening, all varying greatly in design and imaging protocol. Because the systems are different in technical specifications, there is a need for a quantitative approach for assessing them. In this study, the DBT systems are assessed using a novel methodology with an inkjet‐printed anthropomorphic phantom and four alternative forced choice (4AFC) study scheme. Method A breast phantom was fabricated using inkjet printing and parchment paper. The phantom contained 5‐mm spiculated masses fabricated with potassium iodide (KI)‐doped ink and microcalcifications (MCs) made with calcium hydroxyapatite. Images of the phantom were acquired on all five systems with DBT, FFDM, and SM modalities where available using beam settings under automatic exposure control. A 4AFC study was conducted to assess reader performance with each signal under each modality. Statistical analysis was performed on the data to determine proportion correct (PC), standard deviations, and levels of significance. Results For masses, overall detection was highest with DBT. The difference in PC was statistically significant between DBT and SM for most systems. A relationship was observed between increasing PC and greater gantry span. For MCs, performance was highest with DBT and FFDM compared to SM. The difference between PC of DBT and PC of SM was statistically significant for all manufacturers. Conclusions This methodology represents a novel approach for evaluating systems. This study is the first of its kind to use an inkjet‐printed anthropomorphic phantom with realistic signals to assess performance of clinical DBT imaging systems.

Ikejimba, Lynda C.↗
DOE OSTI2025

ATTNChecker: Highly-Optimized Fault Tolerant Attention for Large Language Model Training

Large Language Models (LLMs) have demonstrated remarkable performance in various natural language processing tasks. However, the training of these models is computationally intensive and susceptible to faults, particularly in the attention mechanism, which is a critical component of transformer-based LLMs. In this paper, we investigate the impact of faults on LLM training, focusing on INF, NaN, and near-INF values in the computation results with systematic fault injection experiments. We observe the propagation patterns of these errors, which can trigger non-trainable states in the model and disrupt training, forcing the procedure to load from checkpoints. To mitigate the impact of these faults, we propose ATTNChecker, the first Algorithm-Based Fault Tolerance (ABFT) technique tailored for the attention mechanism in LLMs. ATTNChecker is designed based on fault propagation patterns of LLM and incorporates performance optimization to adapt to both system reliability and model vulnerability while providing lightweight protection for fast LLM training. Evaluations on four LLMs show that ATTNChecker on average incurs on average 7% overhead on training while detecting and correcting all extreme errors. Compared with the state-of-the-art checkpoint/restore approach, ATTNChecker reduces recovery overhead by up to 49×.

Liang, Yuhang [University of Alabama - Birmingham]↗
DOE OSTI2016

A high-fidelity method to analyze perturbation evolution in turbulent flows

Small perturbation propagation in fluid flows is usually examined by linearizing the governing equations about a steady basic state. It is often useful, however, to study perturbation evolution in the unsteady evolving turbulent environment. Such analyses can elucidate the role of perturbations in the generation of coherent structures or the production of noise from jet turbulence. The appropriate equations are still the linearized Navier–Stokes equations, except that the linearization must be performed about the instantaneous evolving turbulent state, which forms the coefficients of the linearized equations. This is a far more difficult problem since in addition to the turbulent state, its rate of change and the perturbation field are all required at each instant. In this paper, we develop and use a novel technique for this problem by using a pair (denoted “baseline” and “twin”) of simultaneous synchronized Large-Eddy Simulations (LES). At each time-step, small disturbances whose propagation characteristics are to be studied, are introduced into the twin through a forcing term. At subsequent time steps, the difference between the two simulations is shown to be equivalent to solving the forced Navier–Stokes equations, linearized about the instantaneous turbulent state. The technique does not put constraints on the forcing, which could be arbitrary, e.g., white noise or other stochastic variants. We consider, however, “native” forcing having properties of disturbances that exist naturally in the turbulent environment. The method then isolates the effect of turbulence in a particular region on the rest of the field, which is useful in the study of noise source localization. The synchronized technique is relatively simple to implement into existing codes. In addition to minimizing the storage and retrieval of large time-varying datasets, it avoids the need to explicitly linearize the governing equations, which can be a very complicated task for viscous terms or turbulence closures. The method is illustrated by application to a well-validated Mach 1.3 jet. Specifically, the effects of turbulence on the jet lipline and core collapse regions on the near-acoustic field are isolated. The properties of the method, including linearity and effect of initial transients, are discussed. The results provide insight into how turbulence from different parts of the jet contribute to the observed dominance of low and high frequency content at shallow and sideline angles, respectively.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

X-ray verification of sol-gel resist shrinkage in substrate-conformal imprint lithography for a replicated blazed reflection grating

Surface-relief gratings fabricated through nanoimprint lithography (NIL) are prone to topographic distortion induced by resist shrinkage. Characterizing the impact of this effect on blazed diffraction efficiency is particularly important for applications in astrophysical spectroscopy at soft x-ray wavelengths ( λ ≈ 0.5 − 5 nm) that call for the mass-production of large-area grating replicas with sub-micron, sawtooth surface-relief profiles. A variant of NIL that lends itself well for this task is substrate-conformal imprint lithography (SCIL), which uses a flexible, composite stamp formed from a rigid master template to imprint nanoscale features in an inorganic resist that cures thermodynamically through a silica sol-gel process. While SCIL enables the production of several hundred imprints before stamp degradation and avoids many of the detriments associated with large-area imprinting in NIL, the sol-gel resist suffers shrinkage dependent on the post-imprint cure temperature. Through atomic force microscopy and diffraction-efficiency testing at beamline 6.3.2 of the Advanced Light Source, the impact of this effect on blaze response is constrained for a ∼160-nm-period grating replica cured at 90 ° C. Results demonstrate a ∼2 ° reduction in blaze angle relative to the master grating, which was fabricated by anisotropic wet etching in 〈311〉-oriented silicon to yield a facet angle close to 30 ° .

McCoy, Jake A. (ORCID:0000000216057517)↗
DOE OSTI2020

PANNA: Properties from Artificial Neural Network Architectures

We report prediction of material properties from first principles is often a computationally expensive task. Recently, artificial neural networks and other machine learning approaches have been successfully employed to obtain accurate models at a low computational cost by leveraging existing example data. Here, we present a software package “Properties from Artificial Neural Network Architectures” (PANNA) that provides a comprehensive toolkit for creating neural network models for atomistic systems following the Behler–Parrinello topology. Besides the core routines for neural network training, it includes data parser, descriptor builder for Behler–Parrinello class of symmetry functions and force-field generator suitable for integration within molecular dynamics packages. PANNA offers a variety of activation and cost functions, regularization methods, as well as the possibility of using fully-connected networks with custom size for each atomic species. PANNA benefits from the optimization and hardware-flexibility of the underlying TensorFlow engine which allows it to be used on multiple CPU/GPU/TPU systems, making it possible to develop and optimize neural network models based on large datasets.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2013

Multifunctional Nanowire/film Composites based Bi-modular Sensors for In-situ and Real-time High Temperature Gas Detection

This final report to the Department of Energy/National Energy Technology Laboratory for DE-FE0000870 covers the period from 2009 to June, 2013 and summarizes the main research accomplishments, which can be divided in sensing materials innovation, bimodular sensor demonstration, and new understanding and discoveries. As a matter of fact, we have successfully completed all the project tasks in June 1, 2013, and presented the final project review presentation on the 9th of July, 2013. Specifically, the major accomplishments achieved in this project include: 1) Successful development of a new class of high temperature stable gas sensor nanomaterials based on composite nano-array strategy in a 3D or 2D fashion using metal oxides and perovskite nanostructures. 2) Successful demonstration of bimodular nanosensors using 2D nanofibrous film and 3D composite nanowire arrays using electrical resistance mode and electrochemical electromotive force mode. 3) Series of new discoveries and understandings based on the new composite nanostructure platform toward enhancing nanosensor performance in terms of stability, selectivity, sensitivity and mass flux sensing. In this report, we highlight some results toward these accomplishments.

47 OTHER INSTRUMENTATION↗
DOE OSTI2026

Mechanism-Resolved PFM of Ferroionic and Ferroelectric Responses in Thickness-Gradient Hf 0.5 Zr 0.5 O 2 Libraries

Resolving growth mechanisms and thickness evolution of functional properties is one of the key tasks in materials discovery and optimization involving thin-film materials, traditionally requiring significant experimental budgets. Here we introduce the combination of thickness-gradient libraries and automated scanning probe microscopy as a systematic pathway to elucidate growth modes and disentangle ferroelectric and electrochemical contributions in ferroelectric thin films. As a model system, we explore the Hf 0.5 Zr 0.5 O 2 (HZO) gradient thin films grown on La x Sr 1-x MnO 3 (LSMO) bottom electrode thin films. Automated piezoresponse force microscopy, spectroscopy, and lithography reveals that irreversible topographic deformation arises from electrochemical activity at the LSMO surface, whereas reversible phase inversion in HZO reflects ferroelectric switching. Automated topography height-map scans are used to further quantify nucleation density, particle-size evolution, and roughness correlations across the thickness-gradient, demonstrating that improved plume stabilization during growth suppresses interfacial reactions and promotes dense, fine-grained HZO conducive to ferroelectric phase formation. This combined materials-engineering and automated-SPM framework establishes a platform for high-throughput, mechanism-resolved characterization of ferroionic and ferroelectric responses in complex oxide films.

FOS: Physical sciences↗
DOE OSTI2013

A GLOBAL MAGNETIC TOPOLOGY MODEL FOR MAGNETIC CLOUDS. II

In the present work, we extensively used our analytical approach to the global magnetic field topology of magnetic clouds (MCs), introduced in a previous paper, in order to show its potential and to study its physical consistency. The model assumes toroidal topology with a non-uniform (variable maximum radius) cross-section along them. Moreover, it has a non-force-free character and also includes the expansion of its cross-section. As is shown, the model allows us, first, to analyze MC magnetic structures-determining their physical parameters-with a variety of magnetic field shapes, and second, to reconstruct their relative orientation in the interplanetary medium from the observations obtained by several spacecraft. Therefore, multipoint spacecraft observations give the opportunity to infer the structure of this large-scale magnetic flux rope structure in the solar wind. For these tasks, we use data from Helios (A and B), STEREO (A and B), and Advanced Composition Explorer. We show that the proposed analytical model can explain quite well the topology of several MCs in the interplanetary medium and is a good starting point for understanding the physical mechanisms under these phenomena.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Kelvin Probe Force Microscopy Imaging of Plasticity in Hydrogenated Perovskite Nickelate Multilevel Neuromorphic Devices

Ion drift in nanoscale electronically inhomogeneous semiconductors is among the most important mechanisms being studied for designing neuromorphic computing hardware. However, nondestructive imaging of the ion drift in operando devices directly responsible for multiresistance states and synaptic memory represents a formidable challenge. Here, we present Kelvin probe force microscopy imaging of hydrogen-doped perovskite nickelate device channels subject to high-speed electric field pulses to directly visualize proton distribution by monitoring surface potential changes spatially, which is also supported with finite element-based electric field distribution studies. First-principles calculations provide mechanistic insights into the origin of surface potential changes as a function of hydrogen donor doping that serves as the contrast mechanism. We demonstrate 128 (7-bit) nonvolatile conductance levels in such devices relevant to in-memory computing applications. The synaptic plasticity measurements are implemented in spiking neural networks and show promising results for classification (SciKit Learn’s Iris and Wine data sets) and control (OpenAI’s CartPole-v1 and BipedalWalker-v3) simulation tasks.

Kelvin probe force microscopy↗
DOE OSTI2021

High Energy Physics Network Requirements Review (Final Report, July-October 2020)

Throughout 2020, ESnet and the Office of High Energy Physics (HEP) of the DOE SC organized an ESnet requirements review of HEP-supported activities. Preparation for this event included identification of key stakeholders: program and facility management, research groups, technology providers, and a number of external observers. These individuals were asked to prepare formal case study documents about their relationship to the HEP program to build a complete understanding of the current, near-term, and long-term status, expectations, and processes that will support the science going forward. A series of pre-planning meetings better prepared case study authors for this task, along with guidance on how the review would proceed in a virtual fashion.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2014

A Large-Scale, High-Resolution Hydrological Model Parameter Data Set for Climate Change Impact Assessment for the Conterminous US

To extend geographical coverage, refine spatial resolution, and improve modeling efficiency, a computation- and data-intensive effort was conducted to organize a comprehensive hydrologic dataset with post-calibrated model parameters for hydro-climate impact assessment. Several key inputs for hydrologic simulation—including meteorologic forcings, soil, land class, vegetation, and elevation—were collected from multiple best-available data sources and organized for 2107 hydrologic subbasins (8-digit hydrologic units, HUC8s) in the conterminous United States at refined 1/24° (~4 km) spatial resolution. Using high-performance computing for intensive model calibration, a high-resolution parameter dataset was prepared for the macro-scale Variable Infiltration Capacity (VIC) hydrologic model. The VIC simulation was driven by DAYMET daily meteorological forcing and was calibrated against USGS WaterWatch monthly runoff observations for each HUC8. The results showed that this new parameter dataset may help reasonably simulate runoff at most US HUC8 subbasins. Based on this exhaustive calibration effort, it is now possible to accurately estimate the resources required for further model improvement across the entire conterminous United States. We anticipate that through this hydrologic parameter dataset, the repeated effort of fundamental data processing can be lessened, so that research efforts can emphasize the more challenging task of assessing climate change impacts. The pre-organized model parameter dataset will be provided to interested parties to support further hydro-climate impact assessment.

Oubeidillah, Abdoul A.↗
DOE OSTI2018

Capturing the spatial variability of noise levels based on a short-term monitoring campaign and comparing noise surfaces against personal exposures collected through a panel study

Highlights: • A Generalized Additive Model (GAM) was developed to generate noise exposure surfaces. • Noise data were collected based on short-term measurements in Toronto, Canada. • Various model specifications were tested in terms of the resulting predictions. • Predictions were validated against data from a panel and from a long-term campaign. • Models that involved manual adjustments resulted in more realistic surfaces. Environmental noise can cause important cardiovascular effects, stress and sleep disturbance. The development of appropriate methods to estimate noise exposure within a single urban area remains a challenging task, due to the presence of various transportation noise sources (road, rail, and aircraft). In this study, we developed a land-use regression (LUR) approach using a Generalized Additive Model (GAM) for LA{sub eq} (equivalent noise level) to capture the spatial variability of noise levels in Toronto, Canada. Four different model formulations were proposed based on continuous 20-min noise measurements at 92 sites and a leave one out cross-validation (LOOCV). Models where coefficients for variables considered as noise sources were forced to be positive, led to the development of more realistic exposure surfaces. Three different measures were used to assess the models; adjusted R{sup 2} (0.44–0.64), deviance (51−72%) and Akaike information criterion (AIC) (469.2–434.6). When comparing exposures derived from the four approaches to personal exposures from a panel study, we observed that all approaches performed very similarly, with values for the Fractional mean bias (FB), normalized mean square error (NMSE), and normalized absolute difference (NAD) very close to 0. Finally, we compared the noise surfaces with data collected from a previous campaign consisting of 1-week measurements at 200 fixed sites in Toronto and observed that the strongest correlations occurred between our predictions and measured noise levels along major roads and highway collectors. Our validation against long-term measurements and panel data demonstrates that manual modifications brought to the models were able to reduce bias in model predictions and achieve a wider range of exposures, comparable with measurement data.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Computational capacity in hydrodynamic real-time hybrid simulation applied to simulate the dynamic response of floating offshore wind turbines

Real-time hybrid simulation (RTHS) mitigates similitude distortions in model-scale tests of floating offshore wind turbines (FOWTs) by coupling physical experiments with numerical models in real time. The coupling requires faster-than-real-time numerical computations to satisfy temporal similitude with the physical experiment, presenting a bottleneck for using more complex numerical models in RTHS. This paper presents a hydrodynamic-RTHS (hydro-RTHS) framework for FOWTs that simulates the hydrodynamics physically and the aerodynamics numerically with sensor feedback from the physical testing. The framework adapts the three-loop hardware architecture to leverage greater computational resources and mitigate strict temporal requirements, enabling more computationally demanding numerical analyses in hydro-RTHS. The three-loop hardware architecture integrates multiple machines, each dedicated to either numerical analysis or RTHS controls, with a rate-transition algorithm to synchronize the tasks executed across the different machine processors. Virtual and physical tests verified and validated the hydro-RTHS framework, respectively. The ”virtual” tests, which approximates the physical domain numerically, verified the RTHS framework with respect to a numerical full-scale complete FOWT model simulated in the open-source software, OpenFAST. The virtual tests were able to maintain comparable control signals while enabling greater computational resources for the numerical calculations. Real-world physical tests demonstrated that the hydro-RTHS framework computes aerodynamic forces similar to the complete OpenFAST model, validating the hydro-RTHS framework using the three-loop hardware architecture. Findings show that the hydro-RTHS framework with the three-loop hardware architecture is computationally efficient, with reserve capacity to simulate more complex problems due to the customized software, hardware, and rate-transition algorithm.

17 WIND ENERGY↗
DOE OSTI2023

GATE Center of Excellence in Innovative Drivetrains in Electric Automotive Technology Education (IDEATE) (Final Report)

The IDEATE project recognized that this is a critical point in history where advanced engineering solutions are required to propel the U.S. automotive industry irrevocably to the next level: the electrified drivetrain. The existing workforce is not sufficient to this task. It is imperative that automotive engineers with traditional backgrounds focused on internal-combustion and mechanical-drivetrain technologies be retrained with the most current advanced solutions in battery controls and vehicle power electronics. For the long-term success of the U.S. automakers, it is even more important that a future workforce be developed that has both broad and deep comprehension of the issues involved and the most advanced solutions known to these problems. Two campuses of the University of Colorado system joined forces to establish the GATE Center of Excellence in Innovative Drivetrains in Electric Automotive Technology Education (IDEATE). The University of Colorado Boulder (CU-Boulder) is widely regarded as having one of the top graduate programs in power electronics in the country; the University of Colorado Colorado Springs (UCCS) has unrivaled expertise in algorithms for automotive battery control. By collaborating, IDEATE built on our team’s proven strengths to develop innovative curricula and to initiate courses and programs that have provided (and continue to provide) students with a unique opportunity for holistic and specialty education in electric drivetrain technology (part-way through the project, we invited Utah State University to join the project, adding to our strength in power electronics for battery application).

42 ENGINEERING↗
DOE OSTI2014

PREPARATION AND TESTING OF CORROSIONAND SPALLATION-RESISTANT COATINGS

This Energy & Environmental Research Center (EERC) project is designed to determine if plating APMT®, a specific highly oxidation-resistant oxide dispersion-strengthened FeCrAl alloy made by Kanthal, onto nickel-based superalloy turbine parts is a viable method for substantially improving the lifetimes and maximum use temperatures of the parts. The method for joining the APMT plate to the superalloys is called evaporative metal bonding and involves placing a thin foil of zinc (Zn) between the plate and the superalloy, clamping them together, and heating in an atmosphere-controlled furnace. Upon heating, the Zn melts and dissolves the oxide skins of the alloys at the bond line, allowing the two alloys to diffuse into each other. The Zn then diffuses through the alloys and evaporates from their surfaces. Laboratory testing to determine the diffusion rate of Zn through the alloys has been completed. However, an analytical solution does not exist to model the diffusion of zinc through the alloys. For this reason, a finite difference algorithm using MATLAB was developed. It makes use of the hopscotch algorithm. The model allows the user to specify the dimensions of the metal parts, the Zn concentration at the bondline, the mesh size, time step, and Zn diffusivity. The experimentally measured values of diffusivity for Zn in APMT and Rene 80/CM 247LC are approximately 2.7 × 10-12 and 4 × 10-14 m2/s, respectively. While the qualitative behavior of the model appears correct, a comparison of the diffusion predictions with the experimental results from earlier in the project indicates that the expected Zn concentration is significantly higher than that measured experimentally. The difference depends on the assumed initial concentration, which is difficult to quantify exactly under experimental conditions for t = 0. In addition to the diffusion work, the coefficients of thermal expansions were determined for each of the alloys as a function of temperature. This information has been entered into a finite element model using ANSYS so that appropriate force-applying structures can be designed for use in joining structures composed of APMT and the nickel alloys. Finite element modeling has been performed to finalize the fabrication geometry for the corrosion-testing phase. The addition of another bolt increases stress uniformity away from the region where the clamping is applied. It appears that a bolt spacing of approximately 25 mm in each jig is appropriate. This will allow the fabrication of 50-mm-wide sections of joints for the corrosion-testing task. Gasifier sampling activities continue to determine what types of trace contaminants may occur in cleaned syngas that could lead to corrosion or deposition in turbines firing coal syngas. The EERC has several pilot-scale gasifiers that are continually used in a variety of test configurations as determined by the needs of the projects that are funding the tests. We are sampling both noncombusted and combusted syngas produced during some of the pilot-scale gasifier tests. This year sampling was performed of both syngas and combusted syngas while the entrained-flow gasifier (EFG) was firing subbituminous coal from the Antelope Mine in Wyoming. Results of scanning electron microscope analyses of the syngas before combustion showed no submicron particles, only flakes of iron oxide that had likely formed on steel surfaces inside the combustor. As shown in the 2013 annual report, soot was also collected from the syngas when the much-lower-temperature fluid-bed gasifier (FBG) was fired, indicating that the much higher temperature of the EFG prevented soot formation. However, particles collected from the combusted syngas consist almost entirely of submicron soot, and little to no vaporized metals made it past the warm-gas filters and scrubbers in the high-temperature EFG system which could then deposit in a turbine system burning a higher hydrogen syngas. These results are consistent with the analyses of the particulates collected from combusted syngas when the lowertemperature FBG system is used.

Electric↗
DOE OSTI2017

Behavior-based approach to misuse detection of a simulated SCADA system - 339

This paper presents the initial findings in applying a behavior-based approach for detection of unauthorized activities in a simulated Supervisory Control and Data Acquisition (SCADA) system. Misuse detection of this type utilizes fault-free system telemetry to develop empirical models that learn normal system behavior. Future monitored telemetry sources that show statistically significant deviations from this learned behavior may indicate an attack or other unwanted actions. The experimental test bed consists of a set of Linux based enterprise servers that were isolated from a larger university research cluster. All servers are connected to a private network and simulate several components and tasks seen in a typical SCADA system. Telemetry sources included kernel statistics, resource usages and internal system hardware measurements. For this study, the Auto Associative Kernel Regression (AAKR) and Auto Associative Multivariate State Estimation Technique (AAMSET) are employed to develop empirical models. Prognostic efficacy of these methods for computer security used several groups of signals taken from available telemetry classes. The Sequential Probability Ratio Test (SPRT) is used along with these models for intrusion detection purposes. The different intrusion types shown include host/network discovery, DoS, brute force login, privilege escalation and malicious exfiltration actions. For this study, all intrusion types tested displayed alterations in the residuals of much of the monitored telemetry and were able to be detected in all signal groups used by both model types. The methods presented can be extended and implemented to industries besides nuclear that use SCADA or business-critical networks. (authors)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2013

Correlation between human observer performance and model observer performance in differential phase contrast CT

Purpose: With the recently expanding interest and developments in x-ray differential phase contrast CT (DPC-CT), the evaluation of its task-specific detection performance and comparison with the corresponding absorption CT under a given radiation dose constraint become increasingly important. Mathematical model observers are often used to quantify the performance of imaging systems, but their correlations with actual human observers need to be confirmed for each new imaging method. This work is an investigation of the effects of stochastic DPC-CT noise on the correlation of detection performance between model and human observers with signal-known-exactly (SKE) detection tasks.Methods: The detectabilities of different objects (five disks with different diameters and two breast lesion masses) embedded in an experimental DPC-CT noise background were assessed using both model and human observers. The detectability of the disk and lesion signals was then measured using five types of model observers including the prewhitening ideal observer, the nonprewhitening (NPW) observer, the nonprewhitening observer with eye filter and internal noise (NPWEi), the prewhitening observer with eye filter and internal noise (PWEi), and the channelized Hotelling observer (CHO). The same objects were also evaluated by four human observers using the two-alternative forced choice method. The results from the model observer experiment were quantitatively compared to the human observer results to assess the correlation between the two techniques.Results: The contrast-to-detail (CD) curve generated by the human observers for the disk-detection experiments shows that the required contrast to detect a disk is inversely proportional to the square root of the disk size. Based on the CD curves, the ideal and NPW observers tend to systematically overestimate the performance of the human observers. The NPWEi and PWEi observers did not predict human performance well either, as the slopes of their CD curves tended to be steeper. The CHO generated the best quantitative agreement with human observers with its CD curve overlapping with that of human observer. Statistical equivalence between CHO and humans can be claimed within 11% of the human observer results, including both the disk and lesion detection experiments.Conclusions: The model observer method can be used to accurately represent human observer performance with the stochastic DPC-CT noise for SKE tasks with sizes ranging from 8 to 128 pixels. The incorporation of the anatomical noise remains to be studied.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2023

OC6 project Phase III: validation of the aerodynamic loading on a wind turbine rotor undergoing large motion caused by a floating support structure

Abstract. This paper provides a summary of the work done within Phase III of the Offshore Code Comparison Collaboration, Continued, with Correlation and unCertainty (OC6) project, under the International Energy Agency Wind Technology Collaboration Programme Task 30. This phase focused on validating the aerodynamic loading on a wind turbine rotor undergoing large motion caused by a floating support structure. Numerical models of the Technical University of Denmark 10 MW reference wind turbine were validated using measurement data from a 1:75 scale test performed during the UNsteady Aerodynamics for FLOating Wind (UNAFLOW) project and a follow-on experimental campaign, both performed at the Politecnico di Milano wind tunnel. Validation of the models was performed by comparing the loads for steady (fixed platform) and unsteady (harmonic motion of the platform) wind conditions. For the unsteady wind conditions, the platform was forced to oscillate in the surge and pitch directions under several frequencies and amplitudes. These oscillations result in a wind variation that impacts the rotor loads (e.g., thrust and torque). For the conditions studied in these tests, the system aerodynamic response was almost steady. Only a small hysteresis in airfoil performance undergoing angle of attack variations in attached flow was observed. During the experiments, the rotor speed and blade pitch angle were held constant. However, in real wind turbine operating conditions, the surge and pitch variations would result in rotor speed variations and/or blade pitch actuations, depending on the wind turbine controller region that the system is operating. Additional simulations with these control parameters were conducted to verify the fidelity of different models. Participant results showed, in general, a good agreement with the experimental measurements and the need to account for dynamic inflow when there are changes in the flow conditions due to the rotor speed variations or blade pitch actuations in response to surge and pitch motion. Numerical models not accounting for dynamic inflow effects predicted rotor loads that were 9 % lower in amplitude during rotor speed variations and 18 % higher in amplitude during blade pitch actuations.

17 WIND ENERGY↗