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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Accurate force field for molybdenum by machine learning large materials data

In this work, we present a highly accurate spectral neighbor analysis potential (SNAP) model for molybdenum (Mo) developed through the rigorous application of machine learning techniques on large materials data sets. Despite Mo's importance as a structural metal, existing force fields for Mo based on the embedded atom and modified embedded atom methods still do not provide satisfactory accuracy on many properties. We will show that by fitting to the energies, forces and stress tensors of a large density functional theory (DFT)-computed dataset on a diverse set of Mo structures, a Mo SNAP model can be developed that achieves close to DFT accuracy in the prediction of a broad range of properties, including energies, forces, stresses, elastic constants, melting point, phonon spectra, surface energies, grain boundary energies, etc. We will outline a systematic model development process, which includes a rigorous approach to structural selection based on principal component analysis, as well as a differential evolution algorithm for optimizing the hyperparameters in the model fitting so that both the model error and the property prediction error can be simultaneously lowered. We expect that this newly developed Mo SNAP model will find broad applications in large-scale, long-time scale simulations.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Seasonal Reconfiguration of Electrical Distribution Systems to Mitigate the Impact of Electric Vehicle Charging

Power grids face challenges in their infrastructure related to the integration of electric vehicles (EV). In particular, EV charging stations may induce instability in key system parameters such as substantial voltage drops, active power losses, and transformer overload due to high demand during charging periods. This article presents a seasonal reconfiguration strategy based on the differential evolution (DE) algorithm, aimed at enhancing system performance under highly variable and stochastic load profiles, particularly those driven by EV charging. The DEA algorithm is hybridized with the find-union (FU) algorithm to efficiently ensure network radiality throughout the optimization process. The proposed methodology is validated on a hybrid distribution system composed of the IEEE 33-bus network, a modified IEEE 13-bus system, and a specific 13-bus microgrid. Results have demonstrated that seasonal reconfiguration significantly reduces active power losses and mitigates transformer loading during critical demand hours, thereby quantifiably increasing the system’s performance. As an integral component of the proposed approach, an analysis of CO2 emissions associated with energy losses is included, allowing a contextualized assessment of the environmental benefits of seasonal reconfiguration in various geographical areas.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

A Comparison of Outer Rotor Radial and Axial Flux Machines for Application in Electric Vehicles

Axial flux machines have attracted a lot of interest in the recent years as potential high torque low weight candidates for use as traction motors in electric vehicles (EV). This paper compares axial and radial flux machines for electric vehicle applications. An external rotor radial flux machine with a Halbach array surface permanent magnet rotor and concentrated windings is chosen as a baseline to compare with axial flux designs. Both axial and radial flux motors are sized to meet the EV same requirements. Multi-objective design optimization using differential evolution minimizing loss and volume is carried out for both types of machines. Hundreds of candidate designs for each type of machine are analyzed, pareto fronts are identified and compared. The potential advantages of axial flux machines are evaluated and quantified.

Rallabandi, Vandana↗
DOE OSTI2019

Evaluating Optimization Strategies for Engine Simulations Using Machine Learning Emulators

This work evaluates different optimization algorithms for computational fluid dynamics (CFD) simulations of engine combustion. Due to the computational expense of CFD simulations, emulators built with machine learning algorithms were used as surrogates for the optimizers. Two types of emulators were used: a Gaussian process (GP) and a weighted variety of machine learning methods called SuperLearner (SL). The emulators were trained using a dataset of 2048 CFD simulations that were run concurrently on a supercomputer. The design of experiments (DOE) for the CFD runs was obtained by perturbing nine input parameters using a Monte-Carlo method. The CFD simulations were of a heavy duty engine running with a low octane gasoline-like fuel at a partially premixed compression ignition mode. Ten optimization algorithms were tested, including types typically used in research applications. Each optimizer was allowed 800 function evaluations and was randomly tested 100 times. The optimizers were evaluated for the median, minimum, and maximum merits obtained in the 100 attempts. Some optimizers required more sequential evaluations, thereby resulting in longer wall clock times to reach an optimum. The best performing optimization methods were particle swarm optimization (PSO), differential evolution (DE), GENOUD (an evolutionary algorithm), and micro-genetic algorithm (GA). These methods found a high median optimum as well as a reasonable minimum optimum of the 100 trials. Moreover, all of these methods were able to operate with less than 100 successive iterations, which reduced the wall clock time required in practice. Two methods were found to be effective but required a much larger number of successive iterations: the DIRECT and MALSCHAINS algorithms. A random search method that completed in a single iteration performed poorly in finding optimum designs but was included to illustrate the limitation of highly concurrent search methods. The last three methods, Nelder–Mead, bound optimization by quadratic approximation (BOBYQA), and constrained optimization by linear approximation (COBYLA), did not perform as well.

Probst, Daniel M.↗
DOE OSTI2022

Optimal band selection for target detection with a LWIR multispectral imager

Multispectral imaging can offer many benefits in cost, complexity, resolution, size, weight, and power, relative to hyperspectral imaging. When designing a multispectral system, spectral bandpasses can be selected using optimization algorithms configured to maximally separate target detection scores between target and background regions. A hyperspectral image (HSI) can serve as the source of data from which band groupings can be tested for optimality. The output of an adaptive cosine estimator target detection algorithm is used in an objective function. Three optimization algorithms are compared: particle swarm, dual annealing, and differential evolution. A global optimum is also found using a brute force approach on the Livermore Computing Syrah supercomputer. Three materials are investigated: calcite, gypsum, and limestone. This is done for 3-, 4-, and 5-band systems. The data originate from a longwave infrared HSI of a material display board. The optimization algorithms were run 30 times for every scenario. Performance statistics (maximum, minimum, mean, standard deviation, and median) based on the separation values are given. Additional characterization was performed using receiver operator characteristic (ROC) curves and the area under the ROC curve. While good performance was obtained for the three optimization algorithms, the dual annealing algorithm produced the highest and most consistent detection separation scores on average.

47 OTHER INSTRUMENTATION↗
DOE OSTI2013

Breast Imaging Reporting and Data System (BI-RADS) breast composition descriptors: Automated measurement development for full field digital mammography

Purpose: The Breast Imaging Reporting and Data System (BI-RADS) breast composition descriptors are used for standardized mammographic reporting and are assessed visually. This reporting is clinically relevant because breast composition can impact mammographic sensitivity and is a breast cancer risk factor. New techniques are presented and evaluated for generating automated BI-RADS breast composition descriptors using both raw and calibrated full field digital mammography (FFDM) image data.Methods: A matched case-control dataset with FFDM images was used to develop three automated measures for the BI-RADS breast composition descriptors. Histograms of each calibrated mammogram in the percent glandular (pg) representation were processed to create the new BR{sub pg} measure. Two previously validated measures of breast density derived from calibrated and raw mammograms were converted to the new BR{sub vc} and BR{sub vr} measures, respectively. These three measures were compared with the radiologist-reported BI-RADS compositions assessments from the patient records. The authors used two optimization strategies with differential evolution to create these measures: method-1 used breast cancer status; and method-2 matched the reported BI-RADS descriptors. Weighted kappa (κ) analysis was used to assess the agreement between the new measures and the reported measures. Each measure's association with breast cancer was evaluated with odds ratios (ORs) adjusted for body mass index, breast area, and menopausal status. ORs were estimated as per unit increase with 95% confidence intervals.Results: The three BI-RADS measures generated by method-1 had κ between 0.25–0.34. These measures were significantly associated with breast cancer status in the adjusted models: (a) OR = 1.87 (1.34, 2.59) for BR{sub pg}; (b) OR = 1.93 (1.36, 2.74) for BR{sub vc}; and (c) OR = 1.37 (1.05, 1.80) for BR{sub vr}. The measures generated by method-2 had κ between 0.42–0.45. Two of these measures were significantly associated with breast cancer status in the adjusted models: (a) OR = 1.95 (1.24, 3.09) for BR{sub pg}; (b) OR = 1.42 (0.87, 2.32) for BR{sub vc}; and (c) OR = 2.13 (1.22, 3.72) for BR{sub vr}. The radiologist-reported measures from the patient records showed a similar association, OR = 1.49 (0.99, 2.24), although only borderline statistically significant.Conclusions: A general framework was developed and validated for converting calibrated mammograms and continuous measures of breast density to fully automated approximations for the BI-RADS breast composition descriptors. The techniques are general and suitable for a broad range of clinical and research applications.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2018

PyBioNetFit

Systems biology models written in the BioNetGen language often contain parameters that must be fit based on experimental data. PyBioNetFit is a software tool designed to fit parameters of BioNetGen models. The user is expected to provide a BioNetGen model that contains unknown parameters, along with one or more text files containing experimental data. PyBioNetFit will perform a series of calls to the BioNetGen simulator using different parameter sets, to identify the parameter set that best fits the data. The parameter search is dictated by the user's choice of one of several metaheuristic optimization algorithms, including differential evolution, particle swarm optimization, scatter search, and simulated annealing. The software supports parallelized computing on multi-core computers and on computing clusters. We expect this software to be a useful tool for researchers designing BioNetGen models in collaboration with experimentalists.

Mitra, Eshan↗
DOE OSTI2024

I-V characterization and parameter extraction tool [SWR-24-59]

GPT-crafted control software and graphical user interface for Keithley 2400 Source Measure Units and global optimization algorithm. It contains Numba-compatible self-adaptive differential evolution algorithm for optimization tasks. This software is comprised of two repositories: https://github.com/NREL/Keithley_GPT https://github.com/NREL/DE

Febba, Davi Marcelo↗
DOE OSTI2025

Hyporheic-zone Processes and Stream Oxygen Dynamics: Insights from a Multiscale Reactive Transport Model: Modeling Archive

This archive contains the data and Python scripts required to reproduce the analyses and figures in the study: Gomez-Velez, J. D., Rathore, S. S., Cohen, M. J., & Painter, S. L. (2025). Hyporheic-zone Processes and Stream Oxygen Dynamics: Insights from a Multiscale Reactive Transport Model. Submitted to Water Resources Research. The analysis utilizes the subgrid model Advection Dispersion Equation with Lagrangian Subgrids (ADELS) implemented in the Advanced Terrestrial Simulator (ATS; https://amanzi.github.io/ats/stable/). In this case, the ATS and Amanzi versions are (1) ATS version 1.5.1_f5ba18f8 and (2) Amanzi version 1.6-dev_53444cca4. The repository includes a Jupyter Notebook and the necessary data (Pandas DataFrames stored as pickle files) to generate the figures for the manuscript. Additionally, it contains Python scripts to create ATS input files, run the ATS simulations, and post-process the results. Finally, it provides routines for parameter estimation using the Single-Station Metabolism (SSM) model with the Differential Evolution Adaptive Metropolis (DREAM) Markov Chain Monte Carlo (MCMC) algorithm with ZS enhancements (DREAM-ZS).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Optimization of a cyclone using MFIX and Nodeworks

Video depicting the optimization process of a cyclone on NETL's chemical looping reactor (CLR) using MFIX and Nodeworks. MFIX is used to model the cyclone using PIC. Nodeworks is then used to generate proposed geometry changes using a Latin hypercube. Each design is simulated, with an objective value being computed based on the cyclone efficiency and pressure drop. A Gaussian Process surrogate model is then constructed from the objective values. This surrogate model is then used by a differential evolution optimization algorithm to identify the optimal cyclone design. Details published here: Weber, J., Fullmer, W., Gel, A., and Musser, J. (February 4, 2020). "Optimization of a Cyclone Using Multiphase Flow Computational Fluid Dynamics." ASME. J. Fluids Eng. March 2020; 142(3): 031111. https://doi.org/10.1115/1.4045952 OSTI: https://www.osti.gov/pages/servlets/purl/1763893

cyclone↗
DOE OSTI2024

Codebase release r1.1 for SmoQyDEAC.jl

We introduce the SmoQyDEAC.jl package, a Julia implementation of the Differential Evolution Analytic Continuation (DEAC) algorithm [N. S. Nichols et al., Phys. Rev. E 106, 025312 (2022)] for analytically continuing noisy imaginary time correlation functions to the real frequency axis. Our implementation supports fermionic and bosonic correlation functions on either the imaginary time or Matsubara frequency axes, and treatment of the covariance error in the input data. This paper presents an overview of the DEAC algorithm and the features implemented in the SmoQyDEAC.jl package. It also provides detailed benchmarks of the package’s output against the popular maximum entropy and stochastic analytic continuation methods. The code for this package can be downloaded from our GitHub repository at https://github.com/SmoQySuite/SmoQyDEAC.jl or installed using the Julia package manager. The online documentation, including examples, can be accessed at https://smoqysuite.github.io/SmoQyDEAC.jl/stable/.

Neuhaus, James (ORCID:0000000169048510)↗
DOE OSTI2015

Implement Method for Automated Testing of Markov Chain Convergence into INVERSE for ORNL12-RS-108J: Advanced Multi-Dimensional Forward and Inverse Modeling

The DiffeRential Evolution Adaptive Metropolis (DREAM) method is a powerful optimization/uncertainty quantification tool used to solve inverse transport problems in Los Alamos National Laboratory’s INVERSE code system. The DREAM method has been shown to be adept at accurate uncertainty quantification, but it can be very computationally demanding. Previously, the DREAM method in INVERSE performed a user-defined number of particle transport calculations. This placed a burden on the user to guess the number of calculations that would be required to accurately solve any given problem. This report discusses a new approach that has been implemented into INVERSE, the Gelman-Rubin convergence metric. This metric automatically detects when an appropriate number of transport calculations have been completed and the uncertainty in the inverse problem has been accurately calculated. In a test problem with a spherical geometry, this method was found to decrease the number of transport calculations (and thus time required) to solve a problem by an average of over 90%. In a cylindrical test geometry, a 75% decrease was obtained.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Crosscutting Recombination Metrology for Expediting VOC Engineering

Work carried out under this grant addressed the need for improved materials and device characterization of solar cell designs. This experimental program aimed to develop joint electrical and optical studies of solar cells based on the group-II-VI semiconductor CdTe and the chalcogenide semiconductor Cu(InGa)Se 2 . Electrical measurements focused on temperature (T) and illumination intensity (I) dependence of the open-circuit voltage (VOC), a quantity that plays an important role in conversion efficiency. The VOC depends on temperature and illumination intensity through the energy gap and positions of the quasiFermi levels (QFLs). Optical measurements exploited the illumination and temperature dependence of absolute photoluminescence (PL) intensity (PL-I), a quantity that also depends on the QFL positions. The QFL splitting is a quantity that also depends on recombination rates within the solar cell, including radiative and non-radiative processes. Other factors affect the electrical and optical properties. These include band offsets at both the front and back interfaces of the device active region where electrical contacts are formed. Understanding, locating, and quantifying the recombination properties of the solar cells was the principal goal of this research. Custom simulations were developed to solve continuity and Poisson equations selfconsistently to obtain free-electron and free-hole concentrations. The measurements of temperature and intensity dependent VOC and PL-I allowed the extraction of a number of physical parameters including the conduction band offset, the shunt constant, and the effective capture coefficient for recombination centers, both within the absorber and at the absorber-buffer interface. In addition, the back-contact barrier height is determined from electrical properties. Each of these is discussed in the report. The illumination intensity dependence of VOC and PL-I do not overlap in experiments primarily because PL is not observed in the low-intensity regime where VOC is studied. Absolute PL-I measurements enabled development of an approach directly comparing it with VOC. This in turn allowed development of a simulation capability that would consistently use both measurements, as functions of T and I, for producing a minimization scheme using a differential evolution algorithm. The approach was applied to both CdTe and Cu(InGa)Se 2 solar cells each prepared under various conditions. Shunt conductivity, QFL splitting, recombination were measured. Also extensively studied are current-voltage and frequency-dependent capacitance voltage. Work completed under this grant included studies of magnesium zinc oxide (MZO) buffered CdTe solar cells including the effects of hydroiodic acid (HI) treatment. From these studies the recombination rates were quantified at the buffer/absorber (front) interface. The effect of back-contact barrier height was investigated. CdTe solar cells were prepared with CdSe and CdS buffer layers. Lower grain-boundary potential fluctuation, higher back-contact barrier height, and greater bulk recombination were observed in early devices with CdSe buffer layer. Investigations were also carried out into CdS/Cu(InGa)Se 2 solar cells. A metal-insulatorsemiconductor capacitance-voltage technique was developed to extract recombinationrelevant properties of the absorber interface. From this work the density of interface states D it , their capture cross-section σ, fixed charge at the interface Q f , and surface recombination velocity were all extracted.

14 SOLAR ENERGY↗
DOE OSTI2022

Real-Time Drilling Optimization System for Improved Overall Rate of Penetration and Reduced Cost Per Foot in Geothermal Drilling

The key to success in geothermal drilling is economic feasibility, and a major cost in the development of geothermal resources is the actual drilling of the wells. In this project, a real-time drilling optimization system for geothermal drilling was developed. The system couples three individual components while drilling. The first component is a drill stem vibration analysis model, the second is Mechanical Specific Energy (MSE) analyses, and the third is a detailed PDC Rate of Penetration (ROP) drill bit model for optimum RPM and WOB combinations. The benefit of the coupled system is that the range of WOB and RPM could be selected to avoid drill stem vibrations. Secondly, MSE is used as an efficiency measure and the detailed PDC drill bit model ensures the drill bit does not endure temperatures that exceed the temperature at which the PDC cutters experience accelerated wear. The new detailed PDC bit model is based on rock/bit interaction that physically tracks the PDC cutter wear flats as the bit drills ahead giving the capability to calculate the temperature being generated underneath the worn cutters to better advise on operational parameters to avoid accelerated cutter wear and failure and to ensure that operational parameters are applied so that overall ROP is maximized. By combining the drill stem vibrations and the detailed PDC bit cutter wear and “safe” non-accelerated cutter wear temperature and optimum ranges of operating parameters, it results in higher ROP and lower cost drilling. Single cutter PDC testing performed in different lithologies at Sandia was utilized to verify the PDC cutter forces and depth of cut for new and worn cutters. Based on single cutter PDC temperature modeling, verification using single cutter data from the testing done by National Oilwell Varco (NOV) was performed. Sandia’s Hard-Rock Drilling Facility (HRDF) was utilized to test different drill bit configurations with different cutter designs and wear status with different induced modes of vibration to obtain the critical bit RPM/WOB ranges resulting in ineffective drilling and low ROP. The collected test data were further used to verify and calibrate the full hole PDC ROP model that was developed based on single cutter interaction data. A full coupled drill stem vibration model was formulated and verified with geothermal field data from the Chocolate Mountain Aerial Gunnery Range (CMAGR). A graphical user interface (GUI) was developed using Tkinter library in the computer programming language Python, which integrates all the developed models in one system. The developed system consists mainly of the PDC ROP model, PDC bit wear model, PDC cutter temperature model, Mechanical Specific Energy (MSE) model, and drillstring vibration model integrated into one system. The developed system can be used for both, post well analysis and real-time optimization using different criteria such as ROP maximization or MSE minimization. The software uses Differential Evolution Algorithm (DEA) to find optimum values for operational parameters based on last foot drilled while avoiding the drillstring vibration and cutter temperature critical operating parameters.

15 GEOTHERMAL ENERGY↗
DOE OSTI2023

Quantification of LEU Holdup using gamma ray imaging and inverse transport solver

Holdup is the residual amount of special nuclear material (SNM) remaining in a processing facility after the bulk materials have been cleaned out. In commercial uranium processing facilities, quantification of holdup is a major challenge because of the highly variable shapes and sizes of the deposits. Any method that attempts to generalize and calibrate deposit shapes in order to quantify holdup will be prone to high uncertainties. Uncertainties on the order of ±50% are typical in holdup results. In international safeguards applications, a ±50% uncertainty can result in a large amount of material unaccounted for (MUF) thereby increasing the difficulty of detecting material diversion and facility misuse. An imaging-based methodology has been developed with the objective of significantly reducing this uncertainty by using the true deposit shape, instead of relying on oversimplified geometric assumptions. The project is a collaboration between ORNL, Y-12, and the University of Tennessee, Knoxville, TN. Uranium sources of known masses were measured using the Germanium Gamma-ray Imager (GeGI), a high-resolution imaging spectrometer, creating a pixelated map for each spectral bin. Two different gamma imaging methods are employed in this work: coded aperture imaging and Compton imaging. A validated MonteCarlo model of the detector has been developed using the GEANT4 code for determining the intrinsic response of the detector, its enclosure, and the coded aperture mask. An inverse transport solver based on the Markov Chain Monte-Carlo approach known as Differential Evolution Adaptive Metropolis (DREAM) is employed to use the measurement data from the image pixels (coded aperture or Compton) to solve for the mass of 235 U in the deposit. A reliable method based on the DREAM solver has been developed to flag the infinite thickness condition of a uranium deposit. The project team is working towards improving the image reconstruction for Compton imaging so that a better localization of the source can be achieved. Besides treating the coded aperture and Compton imaging methods independently, the project is also evaluating a combined method that uses the Compton scatter data from a coded aperture measurement. GEANT4 simulations are being performed to evaluate the combined approach. The impact on the DREAM optimization as the source thickness progressively approaches infinite thickness is being evaluated. A number of uranium sources available at ORNL have been measured, and the DREAM results have been tested and validated for the coded aperture imaging. A similar effort will be carried out to validate the Compton based method once the development of algorithms for better localization are complete. The imaging based quantification is very amenable to unattended monitoring of holdup accumulation at key measurement points. A proof of concept measurement has been completed to demonstrate this capability The current work used the high energy resolution imager GeGI. However, the approach and methodologies are applicable to other imagers such as the cadmium zin telluride (CZT) based imager manufactured by H3D, Inc.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2018

Three dimensional optimization for subsonic axial turbines operating at high unsteady inlet Mach number

In this paper, a three dimensional optimization strategy is presented to improve the performance of a subsonic axial turbine exposed to high Mach number unsteady inflows encountered in pressure gain combustors. The optimization aims at altering the stator hub and shroud end wells. A multi-objective differential evolution optimizer was used to enhance specific work and efficiency. The optimization routine consisted of a multi-step approach where in a first step an optimization was carried out where the turbine was subjected to a steady high Mach inflow. The turbine stage was parametrized via an in-house turbine design tool based on Bezier curves. Seven design parameters were selected to contour the stator end walls and rotor hub end wall. The parametrized turbine stage was meshed and the steady Reynolds-Averaged Navier-Stokes equations were solved via the commercial solver CFD++ and calculation time of each stage was around 10 hours. Results of the steady optimization identified three major design parameters of stator end walls, which were taken as inputs for the next phase unsteady optimization. For the unsteady simulations, a large inlet fluctuation was imposed and the turbine was modeled with the mixing plane approach. Total calculation time of each individual was 48 hours. An efficiency improvement of 10% from the steady optimization and 13% from the unsteady optimization was found compared to the baseline case. Finally, full unsteady simulations with two stator and three rotor passages were performed on selected steady and unsteady optimized configurations.

03 NATURAL GAS↗
DOE OSTI2024

Electromagnetic Design Optimization Integrated with Mechanical Stress Analysis of PM-Assisted Synchronous Reluctance Machine Topologies Enabled with a Blend of Magnets

Permanent Magnet-Assisted Synchronous Reluctance Machines (PMASynRM) provide a low-cost alternative to Surface PM Machines due to the use of relatively lower grades of rare-earth (RE) or RE-free magnets, as the performance degradation due to weaker magnets is compensated by the presence of reluctance torque. However, the weaker magnets suffer from a high risk of demagnetization, leading to unreliable motor operation. Using a blend of RE and RE-free magnets has the potential to overcome this issue. This paper proposes to blend different grades of various rare-earth (RE) and rare-earth-free (RE-free) magnets in six different combinations and utilizes them in two-layer and three-layer U-shaped PMASynRM topologies with both eight-pole and six-pole variations. The rotor of the various designs is then optimized using a differential evolution (DE) based optimization algorithm to obtain low-cost designs with reduced RE magnet volume and minimum demagnetization risk. The optimization of each design is also integrated with the evaluation of mechanical stresses in the rotor laminations so as to maintain the stresses below the material yield strength. Furthermore, the various performance metrics, such as toque–speed/power–speed characteristics, demagnetization, and efficiency maps, are evaluated for each of the optimized and mechanically feasible designs. A quantitative comparison of the various optimized designs is also obtained to highlight the various trade-offs. The results indicate the feasibility of meeting the baseline torque requirement across the entire speed range, even with a 100% reduction in RE magnet volume and less than 5% demagnetization risk, while achieving a cost reduction exceeding 50%. Moreover, the two-layer, eight-pole designs exhibit relatively higher performance, whereas the three-layer, eight-pole designs are found to be the most economical option.

design optimization↗
DOE OSTI2020

SCExAO/CHARIS Near-infrared Integral Field Spectroscopy of the HD 15115 Debris Disk

We present new, near-infrared (1.1–2.4 μm) high-contrast imaging of the debris disk around HD 15115 with the Subaru Coronagraphic Extreme Adaptive Optics (SCExAO) system coupled with the Coronagraphic High Angular Resolution Imaging Spectrograph (CHARIS). The SCExAO/CHARIS resolves the disk down to ρ ∼ 0.″2 (r {sub proj} ∼ 10 au), a factor of ∼3–5 smaller than previous recent studies. We derive a disk position angle of PA ∼ 279.°4–280.°5 and an inclination of i ∼ 85.°3–86.2.°. While recent SPHERE/IRDIS imagery of the system could suggest a significantly misaligned two-ring disk geometry, CHARIS imagery does not reveal conclusive evidence for this hypothesis. Moreover, optimizing models of both one- and two-ring geometries using differential evolution, we find that a single ring having a Hong-like scattering phase function matches the data equally well within the CHARIS field of view (ρ ≲ 1″). The disk’s asymmetry, well evidenced at larger separations, is also recovered; the west side of the disk appears, on average, around 0.4 mag brighter across the CHARIS bandpass between 0.″25 and 1″. Comparing Space Telescope Imaging Spectrograph (STIS) 50CCD optical photometry (2000–10500 Å) with CHARIS near-infrared photometry, we find a red (STIS/50CCD−CHARIS broadband) color for both sides of the disk throughout the 0.″4–1″ region of overlap, in contrast to the blue color reported at similar wavelengths for regions exterior to ∼2″. Further, this color may suggest a smaller minimum grain size than previously estimated at larger separations. Finally, we provide constraints on planetary companions and discuss possible mechanisms for the observed inner disk flux asymmetry and color.

79 ASTRONOMY AND ASTROPHYSICS↗