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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS1945

Summary of Airfoil Data

Recent airfoil data for both flight and wind-tunnel tests have been collected and correlated insofar as possible. The flight data consist largely of drag measurements made by the wake-survey method. Most of the data on airfoil section characteristics were obtained in the Langley two-dimensional low-turbulence pressure tunnel. Detail data necessary for the application of NACA 6-serles airfoils to wing design are presented in supplementary figures, together with recent data for the NACA 24-, 44-, and 230-series airfoils. The general methods used to derive the basic thickness forms for NACA 6- and 7-series airfoils and their corresponding pressure distributions are presented. Data and methods are given for rapidly obtaining the approximate pressure distributions for NACA four-digit, five-digit, 6-, and 7-series airfoils. The report includes an analysis of the lift, drag, pitching-moment, and critical-speed characteristics of the airfoils, together with a discussion of the effects of surface conditions. Available data on high-lift devices are presented. Problems associated with lateral-control devices, leading-edge air intakes, and interference are briefly discussed. The data indicate that the effects of surface condition on the lift and drag characteristics are at least as large as the effects of the airfoil shape and must be considered in airfoil selection and the prediction of wing characteristics. Airfoils permitting extensive laminar flow, such as the NACA 6-series airfoils, have much lower drag coefficients at high speed and cruising lift coefficients than earlier types-of airfoils if, and only if, the wing surfaces are sufficiently smooth and fair. The NACA 6-series airfoils also have favorable critical-speed characteristics and do not appear to present unusual problems associated with the application of high-lift and lateral-control devices. Much of the data given in the NACA Advance Confidential Report entitled "Preliminary Low-Drag-Airfoil and Flap Data from Tests at Large Reynolds Number and Low Turbulence," by Eastman N. Jacobs, Ira R. Abbott, and Milton Davidson, March 1942 has been corrected and included in the present paper, which supersedes the previously published paper.

LOW-DRAG↗
DOE OSTI2023

Optimization of operational strategies for rich gas enhanced oil recovery based on a pilot test in the Bakken tight oil reservoir

Horizontal well drilling and multistage hydraulic fracturing have been demonstrated as effective approaches for stimulating oil production in the Bakken tight oil reservoir. However, after multiple years of production, primary oil recovery in the Bakken is generally less than 10% of the estimated original oil in place. Gas huff ‘n’ puff (HnP) has been tested in the Bakken Formation as an enhanced oil recovery (EOR) method; however, most field pilot test results showed no significant incremental oil production. One of the factors affecting HnP EOR performance is premature gas breakthrough, which is one of the most critical issues observed in the field because of the presence of interwell fractures. Consequently, injected gas rapidly reaches adjacent production wells without contacting reservoir rock and increasing oil recovery. Proper conformance control is therefore needed to avoid early gas breakthrough and improve EOR performance. In this study, a rich gas EOR pilot in the Bakken was carefully analyzed to collect the essential reservoir and operational data. A simulation model with 16 wells was then developed to reproduce the production history and predict the EOR performance with and without conformance control. EOR operational strategies, including single- and multiple-well HnP, with different gas injection constraints were investigated. The simulation results of single-well HnP without conformance control showed that a rich gas injection rate of at least 10 MMscfd was needed to yield meaningful incremental oil production. The strategy of conformance control via water injection could significantly improve oil production in the HnP well, but injecting an excessive amount of water also leads to water breakthrough and loss of oil production in the offset wells. By analyzing the production performance of the wells individually, the arrangement of wells was optimized for multiple-well HnP EOR. The multiwell results showed that rich gas EOR could improve oil production up to 7.4% by employing conformance control strategies. Furthermore, replacing rich gas with propane as the injection gas could result in 14% of incremental oil production.

02 PETROLEUM↗
DOE OSTI2023

Creating large Fock states and massively squeezed states in optics using systems with nonlinear bound states in the continuum

The quantization of the electromagnetic field leads directly to the existence of quantum mechanical states, called Fock states, with an exact integer number of photons. Despite these fundamental states being long-understood, and despite their many potential applications, generating them is largely an open problem. For example, at optical frequencies, it is challenging to deterministically generate Fock states of order two and beyond. Here, we predict the existence of an effect in nonlinear optics, which enables the deterministic generation of large Fock states at arbitrary frequencies. The effect, which we call an n-photon bound state in the continuum, is one in which a photonic resonance (such as a cavity mode) becomes lossless when a precise number of photons n is inside the resonance. Based on analytical theory and numerical simulations, we show that these bound states enable a remarkable phenomenon in which a coherent state of light, when injected into a system supporting this bound state, can spontaneously evolve into a Fock state of a controllable photon number. This effect is also directly applicable for creating (highly) squeezed states of light, whose photon number fluctuations are (far) below the value expected from classical physics (i.e., shot noise). In conclusion, we suggest several examples of systems to experimentally realize the effects predicted here in nonlinear nanophotonic systems, showing examples of generating both optical Fock states with large n (n > 10), as well as more macroscopic photonic states with very large squeezing, with over 90% less noise (10 dB) than the classical value associated with shot noise.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Effective point-charge analysis of crystal fields: Application to rare-earth pyrochlores and tripod kagome magnets 𝑅 ⁢3⁢ Mg⁢ 2 ⁢Sb⁢ 3⁢ O⁢ 14

An indispensable step to understand collective magnetic phenomena in rare-earth compounds is the determination of spatially anisotropic single-ion properties resulting from spin-orbit coupling and crystal field (CF). The CF Hamiltonian has a discrete energy spectrum—accessible to spectroscopic probes such as neutron scattering—controlled by a number of independent parameters reflecting the point symmetry of the magnetic sites. Determining these parameters in low-symmetry systems is often challenging. Here, we describe a general method to analyze CF excitation spectra using adjustable effective point-charges. We benchmark our method to existing neutron-scattering measurements on pyrochlore rare-earth oxides and obtain a universal point-charge model that describes a large family of related materials. We adapt this model to the newly discovered tripod kagome magnets (𝑅 3 ⁢Mg 2 ⁢Sb 3 ⁢O 14 , 𝑅 = Tb, Ho, Er, Yb) for which we report broadband inelastic neutron-scattering spectra. Analysis of these data using adjustable point-charges yields the CF wave functions for each compound. From this, we calculate thermomagnetic properties that accurately reflect our measurements on powder samples and predict the effective gyromagnetic tensor for pseudospin degrees of freedom—a crucial step to understand the exotic collective properties of these kagome magnets at low temperature. We present further applications of our method to other tripod kagome materials and triangular rare-earth compounds 𝑅⁢MgGaO 4 (𝑅 =Yb, Tm). Overall, this study establishes a widely applicable methodology to predict CF and single-ion properties of rare-earth compounds based on interpretable and adjustable models of effective point charges.

Crystal-field theory↗
DOE OSTI2023

A General Spatiotemporal Imputation Framework for Missing Sensor Data

Many applications from precision agriculture, environmental monitoring and transportation networks rely on data collected across space and time over a large geographic area. Missing data poses a significant challenge for any data-driven inference and control tasks. Data imputation or the estimation of missing data can help fill these gaps by utilizing inherent spatial relationships and temporal patterns. A variety of spatiotemporal imputation models have been developed to address missing data in spatiotemporal datasets. However, these classical methods rely on the assumption that the underlying data follows a smooth trend and fail to provide accurate estimates when there is a large number of missing points in the data. Even though there are machine learning driven tensor completion approaches such as convolutional neural network based tensor completion (CoSTCo) that capture the non-linear relationships in the dataset, the transductive nature makes the algorithm less scalable. Thus, existing approaches for estimating the missing information do not effectively capture all dimensions of the spatiotemporal data structure, resulting in erroneous predictions and poor performance. The main contributions of this paper are: (1) We propose a novel inductive framework (G-LSTM) for missing data imputation that integrates a graph neural network with LSTMs to effectively capture both spatial and temporal dependencies. (2) Experimental results on a traffic dataset demonstrate that the proposed GNN integrated with an LSTM framework achieves improved imputation and maintains steady performance even when there are extreme missing conditions in comparison with the state-of-the-art imputation framework (i.e, CoSTCo). (3) The simulation results on a traffic network show up to 69% reduction in mean absolute error and 61% reduction in root mean square error when compared to CoSTCo.

Tharzeen, Aabila↗
NASA NTRS2005

Martian Atmospheric Circulation and Climate

This project was submitted with four work tasks. The reviews recommended focusing on the following three, with an appropriately reduced budget: 1. In the first, we proposed to use Thermal Emission Spectrometer (TES) data to examine the general circulation of the atmosphere and to better constrain and validate a Mars General Circulation Model (GCM). 2. In the second, we proposed to examine processes responsible for the injection of dust into the atmosphere. We will conduct a global, seasonal survey of dust lifting events, and specifically of dust devil activity, using MGS MOC, MGS TES, and Odyssey THEMIS data. The results of this survey will be compared with model predictions of dust devil and other dust lifting processes. It is expected that some of the observational results will motivate specific simulations with the GCM and mesoscale models. 3. In the third task, we proposed to extract seasonal and spatial near-surface wind information from aeolian streaks. Detailed analysis will focus on streaks in the polar regions and in regions of large topography (such as Tharsis). The streak information will be used along with the mesoscale model to examine the processes that control local and regional scale flow patterns.

Richardson, Mark I.↗
DOE OSTI2023

High-Performance Accelerator Modeling: Toward Improving Controls and Diagnostics for High-Brightness Beams in Experiment

One of the main charges of beam physics is to improve the overall beam quality delivered to experiments and applications, which is generally quantified by the beam brightness. High brightness beams have numerous applications, including x-ray free electron lasers and ultrafast electron diffraction (UED). To these ends, this thesis details efforts to use high-performance models --- high-fidelity models that execute quickly --- for controls and diagnostics. To demonstrate the generality of these techniques, this thesis focuses on three of the most successful photoinjector designs currently used worldwide: the UCLA/SLAC/BNL-type high-gradient S-band gun, the continuous-wave high-repetition rate VHF APEX gun and the L-band DESY-PITZ-type gun. Work will be shown from Pegasus (UCLA), HiRES (LBNL) and FAST (FNAL).Specifically, data-driven models for online virtual diagnostics are presented, in this case, in the context of UED at HiRES, leading to a temporal resolution improvement. Methods for improving the fidelity of physics-based models are discussed, with examples at HiRES, Pegasus and FAST. Markov-chain Monte Carlo analysis is applied to match simulations, in the context of photocathode studies at HiRES and Pegasus. Lastly, the augmentation of online model-based predictions with model-independent optimization is explored in a fluctuating environment at Pegasus and HiRES. A central theme of this dissertation is working with parameter fluctuations when modeling an accelerator beamline. Long-term drifts and shot-to-shot jitter exist in every accelerator to a varying degree and therefore play an important role in every chapter of this dissertation. This thesis attempts to address the issues associated with these fluctuations when trying to develop faithful model representations of the system.

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

Simulation-Based Recovery Action Analysis Using the EMRALD Dynamic Risk Assessment Tool

A recovery action is defined as the action that prevents deviant conditions from producing unwanted effects. It generally indicates a kind of countermeasure performed in response to a failure of human action. The recovery actions especially play an important role in complex systems like nuclear power plants (NPPs), which consist of highly sophisticated controllers to ensure that desired performance and safety must be achieved and maintained. This is because a combination of human error and its recovery failure may be able to cause a catastrophic effect on a system. Analyzing recovery actions has been a critical part of HRA, which is a technique to evaluate human errors and provide human error probabilities (HEPs) for application in probabilistic safety assessment (PSA). If recovery actions are not adequately analyzed and applied to PSA models, the PSA results may be under-estimated or be not able to reasonably account for the failure of human actions in the context of PSA. For this reason, some regulatory documents such as ASME/ANS RA-Sb-2013 by the American Society for Mechanical Engineers and the American Nuclear Society and NUREG-1792 by U.S. Nuclear Regulatory Commission have emphasized the importance of recovery analysis within the HRA. A couple of existing HRA methods, such as the Technique for Human Error-Rate Prediction (THERP), the Cause-Based Decision Tree (CBDT), and the Korean Standard HRA (K-HRA), have respectively suggested their own approaches to the HRA recovery analysis. However, there are a couple of limitations to treating recovery actions using only the current HRA methods available. The biggest limitation is that the existing recovery analysis does not explicitly consider a variety of recovery action types and recovery sequences as they occur in actual NPPs. To handle the limitations of existing recovery analysis, this study proposes a simulation-based recovery analysis method using the Event Modeling Risk Assessment Using Linked Diagram (EMRALD) software. The EMRALD software is a dynamic simulation tool for PSA. It supports realistic and dynamic modeling of human actions as they would be performed at NPPs. It is also favorable to simultaneously model the specific moment at which an action is performed, the time it takes to perform the action, and the failure probability of that action. In this paper, a detailed methodology for modeling recovery actions in the simulation platform is proposed with a couple of examples. Then, outputs from the simulation are discussed as reviewing if this novel approach can complement the challenges of existing recovery analyses.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2024

QC-GN 2 oMS 2 : a Graph Neural Net for High Resolution Mass Spectra Prediction

Predicting the mass spectrum of a molecular ion is often accomplished via three generalized approaches: rules-based methods for bond breaking, deep learning, or quantum chemical (QC) modeling. Rules-based approaches are often limited by the conditions for different chemical subspaces and perform poorly under chemical regimes with few defined rules. QC modeling is theoretically robust but requires significant amounts of computational time to produce a spectrum for a given target. Among deep learning techniques, graph neural networks (GNNs) have performed better than previous work with fingerprint-based neural networks in mass spectra prediction. To explore this technique further, we investigate the effects of including quantum chemically derived information as edge features in the GNN to increase predictive accuracy. The models we investigated include categorical bond order, bond force constants derived from extended tight-binding (xTB) quantum chemistry, and acyclic bond dissociation energies. Throughout this work, we evaluated these models against a control GNN with no edge features in the input graphs. Bond dissociation enthalpies yielded the best improvement with a cosine similarity score of 0.462 relative to the baseline model (0.437). In this work we also apply dynamic graph attention which improves performance on benchmark problems and supports the inclusion of edge features. Between implementations, we investigate the nature of the molecular embedding for spectra prediction and discuss the recognition of fragment topographies in distinct chemistries for further development in tandem mass spectrometry prediction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Materials Characterization, Prediction, and Control Project: Characterization of 316L Stainless Steel after Solid Phase Processing using Ultrasonic NDE Method

The Pacific Northwest National Laboratory undertook the Materials Characterization, Prediction, and Control Laboratory Directed Research and Development Project to advance understanding of nuclear material processing and enable multifold acceleration in the development and qualification of new material systems produced via advanced manufacturing methods, such as solid phase processing, for use in national security and advanced energy applications (Smith 2021). A motivation of the Materials Characterization, Prediction, and Control Project was to demonstrate ultrasonic testing as a nondestructive evaluation method to complement traditional destructive methods for characterizing material microstructure with emphasis on grain size determination using a method that may have future applications for real-time inline process monitoring. The objective of the work described in this report is to establish the process and an analysis method for measuring grain sizes of polycrystalline metals with ultrafine grains using ultrasonic shear wave backscattering, building on prior studies on coarser-grained material. The work involves five tasks: Measured ultrasonic backscattering experimentally for a series of 316L stainless steel specimens with various grain sizes made by friction stir processing. Calculated ultrasonic backscattering coefficients from experimental data based on a physical measurement model. Measured ground truth grain sizes of the specimens from electron backscatter diffraction grain boundary images using a generalization of the ASTM E112 (ASTM 2021) intercept method. Built a curve of ultrasonic backscattering coefficients versus the ground truth intercept-based grain sizes to determine the correlation between mean grain sizes and ultrasonic measurements. Demonstrated the ability of using the correlation curve to deduce grain sizes with measured ultrasonic backscattering coefficients for a few 316L stainless steel specimens whose grain sizes were unknown beforehand but were targeted to be an extrapolation to larger grain sizes than used to formulate the correlation curves. Experimental procedures and computational algorithms are developed and validated for these tasks. This work establishes an ultrasonic technique for characterizing material microstructure with ultrafine grains that are often resulted by solid-phase processing. The technique is nondestructive, and it has the potential to be used for real time inline process monitoring. This work successfully demonstrates the viability of an ultrasonic nondestructive evaluation method for microstructural characterization of material having ultrafine grain structure (as small as 1?mm) and produced by an advanced manufacturing method. This includes a demonstration of the method to extrapolate to other conditions. While not demonstrated here, the method is expected to be viable for in-line, or near-inline, process monitoring in advanced manufacturing applications with suitable consideration for access of instrumentation to the material being manufactured.

316 L Stainless Steel↗
NASA NTRS1987

A study of methods to predict and measure the transmission of sound through the walls of light aircraft. Numerical method for analyzing the optimal performance of active noise controllers

An optimal active noise controller is formulated and analyzed for three different active noise control problems. The first problem formulated is the active control of enclosed or partially enclosed harmonic sound fields where the noise source strengths and enclosure boundary description are known. The enclosure boundary is described by either pressure, velocity, or impedance boundary conditions. The second problem formulated is the active control of the free field power radiated from a distributed noise source with a known time harmonic surface velocity. The third problem formulated is the active control of enclosed or partially enclosed harmonic sound field where the noise source strengths of enclosure boundary description may not be known. All three formulations are derived using an indirect boundary element technique. Formulation and verification of an indirect boundary element method is presented. The active noise controller formulations for enclosures are capable of analyzing systems with generalized enclosure shapes, point noise sources, and/or locally reacting impedance boundary conditions. For each formulation, representative results of optimal active noise controller case studies are presented, and some general conclusions are drawn.

Mollo, Christopher G.↗
DOE OSTI2023

Effect of Framework Composition and NH 3 on the Diffusion of Cu + in Cu-CHA Catalysts Predicted by Machine-Learning Accelerated Molecular Dynamics

Cu-exchanged zeolites rely on mobile solvated Cu + cations for their catalytic activity, but the role of the framework composition in transport is not fully understood. Ab initio molecular dynamics simulations can provide quantitative atomistic insight but are too computationally expensive to explore large length and time scales or diverse compositions. We report a machine-learning interatomic potential that accurately reproduces ab initio results and effectively generalizes to allow multinanosecond simulations of large supercells and diverse chemical compositions. Biased and unbiased simulations of [Cu(NH 3 ) 2 ] + mobility show that aluminum pairing in eight-membered rings accelerates local hopping and demonstrate that increased NH 3 concentration enhances long-range diffusion. The probability of finding two [Cu(NH 3 ) 2 ] + complexes in the same cage, which is key for SCR-NOx reaction, increases with Cu content and Al content but does not correlate with the long-range mobility of Cu + . Supporting experimental evidence was obtained from reactivity tests of Cu-CHA catalysts with a controlled chemical composition.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

New Developments and Capabilities Within WEC-Sim

WEC-Sim is an open-source software for simulating wave energy converters and has been actively developed and applied since its initial release in 2014 to simulate a wide variety of device archetypes. WEC-Sim is developed jointly by the National Renewable Energy Laboratory and Sandia National Laboratories within the MATLAB/SIMULINK environment. A general wave-to-wire model begins with a deployment site resource characterization, which is used to complete the hydrodynamic simulation of wave energy converters (WEC), with the power generation profile imported to a grid simulator to understand the influence on the local electrical network. While modeling the entire wave-to-wire is difficult and encompasses multiple time scales and physics, WEC-Sim is focused on the hydrodynamics simulation to predict, analyze, and optimize WEC dynamics and power performance. WEC-Sim simulations are performed in the time domain based on the radiation and diffraction method using hydrodynamics coefficients derived from boundary element method (BEM)-based frequency-domain potential flow solvers (e.g., WAMIT, NEMOH, Capytaine, or ANSYS-AQWA). With this level of modeling fidelity, WEC-Sim can handle floating body hydrodynamics, mechanical and electrical power generation methods, advanced control implementation, mooring systems, and other unique applications such as desalination. Additional WEC-Sim functionalities include pre-built Simulink blocks and MATLAB scripts that can simulate a wide range of floating systems and the corresponding auxiliary subsystems. The developers of WEC-Sim continue to release new versions of the software, at least annually, with the latest release in September 2022. These releases include bug fixes, updates to software documentation, as well as new features to expand WEC-Sim's capabilities to model a wide range of WEC concepts. This publication will highlight the new features added to WEC-Sim between versions 4.1.0 to 5.0.1, which spans a 2-year period from June 2020 to September 2022. New features described here include topics such as continuous integration checks, revised Morison Element and nonlinear hydro implementations, run directly from Simulink (required for hardware-in-the-loop execution), BEMIO updates to import Capytaine BEM hydrodynamics, addition of cable blocks, and new wave visualization features.

TIDAL AND WAVE POWER↗
NASA NTRS2005

Solar Cycle/Seasonal Variations of H, D, H2 and He Distributions and Escape on Mars as Determined by the Mars Thermosphere Global Circulation Model (MTGCM)

The Mars Thermosphere General Circulation Model (MTGCM) was exercised for Ls = 90 (aphelion) solar minimum, and Ls = 270 perihelion) solar maximum conditions. Simulated MTGCM outputs (i.e. helium density distributions) were compared to those previously observed for Earth and Venus. Winter polar night bulges of helium are predicted on Mars, similar to those observed on the nightside of Venus and in the winter polar regions of Earth. A poster on this research was presented at the European Geophysical Society Meeting (EGS) in 2003. This research paves the way for what might be expected in the polar night regions of Mars during upcoming aerobraking and mapping Campaigns. Lastly, Mars thermosphere (approx. 100-130 km) winter polar warming was observed at high Northern latitudes during the perihelion season, but not at high Southern latitudes during the opposite aphelion season. Presumably, the Mars thermospheric circulation is responsible for the dynamically controlled heating needed to warm polar night temperatures above radiative equilibrium values. Again, MTGCM simulations were conducted for Ls = 90 and Ls = 270 conditions; polar temperatures were examined and found to be much warmer at Northern high latitudes (perihelion) than at Southern high latitudes (aphelion), similar to Mars aerobraking datasets. The Mars thermospheric circulation is found to be stronger during perihelion solstice conditions than during aphelion conditions, owing to both stronger seasonal solar and dust heating during Mars perihelion. An invited talk was given at the Spring AGU 2004 on this research. A forthcoming GRL paper was drafted on this same topic, but not submitted before the termination of this 1-year grant.

Bougher, Stephen↗
NASA NTRS2019

Cloud Influence on ERA5 and AMPS Surface Downwelling Longwave Radiation Biases in West Antarctica

The surface downwelling longwave radiation component (LW[down arrow]) is crucial for the determination of the surface energy budget and has significant implications for the resilience of ice surfaces in the polar regions. Accurate model evaluation of this radiation component requires knowledge about the phase, vertical distribution, and associated temperature of water in the atmosphere, all of which control the LW[down arrow] signal measured at the surface. In this study, we examine the LW[down arrow] model errors found in the Antarctic Mesoscale Prediction System (AMPS) operational forecast model and the ERA5 reanalysis model relative to observations from the AWARE campaign at McMurdo Station and the West Antarctic Ice Sheet (WAIS) Divide. The errors are calculated separately for observed clear-sky conditions, ice-cloud occurrences, and liquid-bearing cloud layer (LBCL) occurrences. The analysis results show a tendency in both models at each site to underestimate the LW[down arrow] during clear sky conditions, high error variability (standard deviations > 20 W/m[exp2]) during any type of cloud occurrence, and negative LW biases when LBCLs are observed (bias magnitudes > 15 W/m[exp2] in tenuous LBCL cases; > 43 W/m[exp2] in optically thick/opaque LBCLs instances). We suggest that a generally dry and liquid-deficient atmosphere responsible for the identified LW[down arrow] biases in both models is the result of excessive ice formation and growth, which could stem from model initial and lateral boundary conditions, microphysics scheme, aerosol representation, and/or limited vertical resolution.

Israel Silber↗
DOE OSTI2023

New Developments and Capabilities Within WEC-Sim: Preprint

WEC-Sim is an open-source software for simulating wave energy converters, which has been actively developed and applied since its initial release in 2014 to simulate a wide variety of device archetypes. WEC-Sim is developed jointly by the National Renewable Energy Laboratory (NREL) and Sandia National Laboratories (Sandia) within the MATLAB/SIMULINK environment. A general wave-to-wire model begins with a deployment site resource characterization, which is used to complete the hydrodynamic simulation of wave energy converters (WEC), with the power generation profile imported to a grid simulator to understand the influence on the local electrical network. While modeling the entire wave-to-wire is difficult and encompasses multiple time scales and physics, WEC-Sim is focused on the hydrodynamics simulation to predict, analyze, and optimize WEC dynamics and power performance. WEC-Sim simulations are performed in the time domain based on the radiation and diffraction method using hydrodynamics coefficients derived from boundary element method (BEM)-based frequency-domain potential flow solvers (e.g., WAMIT, NEMOH, Capytaine, or ANSYS-AQWA). With this level of modeling fidelity, WEC-Sim can handle floating body hydrodynamics, mechanical and electrical power generation methods, advanced control implementation, mooring systems, and other unique applications such as desalination. Additional WEC-Sim functionalities include pre-built Simulink blocks and MATLAB scripts that can simulate a wide range of floating systems and the corresponding auxiliary subsystems. The developers of WEC-Sim continue to release new versions of the software, at least annually, with our latest release in September 2022. These releases include bug fixes, updates to software documentation, as well as new features to expand WEC-Sim's capabilities to model a wide range of WEC concepts. This publication will highlight the new features added to WEC-Sim between versions 4.1.0 to 5.0.1 which spans over a two year period from June 2020 to September 2022. New features to be described will include topics such as continuous integration checks, revised Morison Element and nonlinear hydro implementations, run directly from Simulink (required for hardware-in-the-loop execution), BEMIO updates to import Capytaine BEM hydrodynamics, addition of cable blocks, and new wave visualization features.

TIDAL AND WAVE POWER↗
DOE OSTI2024

The Use of Artificial Intelligence in Head and Neck Cancers: A Multidisciplinary Survey

Artificial intelligence (AI) approaches have been introduced in various disciplines but remain rather unused in head and neck (H&N) cancers. This survey aimed to infer the current applications of and attitudes toward AI in the multidisciplinary care of H&N cancers. From November 2020 to June 2022, a web-based questionnaire examining the relationship between AI usage and professionals’ demographics and attitudes was delivered to different professionals involved in H&N cancers through social media and mailing lists. A total of 139 professionals completed the questionnaire. Only 49.7% of the respondents reported having experience with AI. The most frequent AI users were radiologists (66.2%). Significant predictors of AI use were primary specialty (V = 0.455; p < 0.001), academic qualification and age. AI’s potential was seen in the improvement of diagnostic accuracy (72%), surgical planning (64.7%), treatment selection (57.6%), risk assessment (50.4%) and the prediction of complications (45.3%). Among participants, 42.7% had significant concerns over AI use, with the most frequent being the ‘loss of control’ (27.6%) and ‘diagnostic errors’ (57.0%). This survey reveals limited engagement with AI in multidisciplinary H&N cancer care, highlighting the need for broader implementation and further studies to explore its acceptance and benefits.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1988

High-aspect-ratio wings

High-aspect-ratio aircraft include most transport aircraft such as commercial and military transports, business aircraft, and cargo aircraft. Generally, these types of aircraft are designed to cruise over a narrow range of lift coefficients and Mach numbers in the performance of their mission. Emphasis is therefore placed on the cruise performance of transport aircraft and every effort is made to obtain accurate wind-tunnel data to use as a basis for prediction of full-scale cruise performance. However, off-cruise performance is also important and methods were developed for extrapolating wind-tunnel data on buffet and flutter at transonic speed. Transport-type aircraft were tested extensively in various wind tunnels around the world and many different test techniques were developed to simulate higher Reynolds numbers. Methods developed for one tunnel may not be applicable to another tunnel because of differences in size, Reynolds number capability, running time, and test objectives. Many of the methods of boundary-layer control developed in two-dimensional airfoil testing can be applied in tests of transport configurations, but sometimes the three-dimensional flow fields that develop on tranpsort aircraft can make application of the two-dimensional methods difficult or impossible. The discussion is intended to be a representative, but not exhaustive, survey of the various methods of high Reynolds number simulation in the testing of high-aspect-ratio aircraft.

Peterson, John B., Jr.↗