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DOE OSTI2020

Spectral solar irradiance on inclined surfaces: A fast Monte Carlo approach

Estimating spectral plane-of-array (POA) solar irradiance on inclined surfaces is an important step in the design and performance evaluation of both photovoltaic and concentrated solar plants. This work introduces a fast, line-by-line spectral, Monte Carlo (MC) radiative transfer model approach to simulate anisotropic distributions of shortwave radiation through the atmosphere as photon bundles impinge on inclined surfaces. This fast Monte Carlo approach reproduces the angular distribution of solar irradiance without the undesirable effects of spatial discretization and thus computes detailed POA irradiance values on surfaces at any orientation and also when surfaces are subjected to the anisotropic ground and atmospheric scattering. Polarization effects are also easily incorporated into this approach that can be considered as direct numerical simulation of the physics involved. Here, we compare our Monte Carlo radiative transfer model with the most widely used empirical transposition model, Perez4, under various conditions. The results show that the Perez4 model reproduces the more detailed Monte Carlo simulations with less than 10% deviation under clear skies for all relevant surface tilt and azimuth angles. When optically thin clouds are present, observed deviations are larger, especially when the receiving surface is strongly tilted. Deviations are also observed for large azimuth angle differences between the receiving surface and the solar position. When optically thick clouds are present, the two models agree within 15% deviation for nearly all surface orientation and tilt angles. The overall deviations are smaller when compared with cases for optically thin clouds. The Perez4 model performs very well (6.0% deviation) in comparison with the detailed MC simulations for all cases, thus validating its widespread use for practical solar applications. When detailed atmospheric profiles and cloud optical properties are available, the proposed fast Monte Carlo radiative model reproduces accurate spectral and angular POA irradiance levels for various atmospheric and cloud cover conditions, surface orientations, and different surface and ground properties.

42 ENGINEERING↗

DOE OSTI2013

ExacTrac Snap Verification: A New Tool for Ensuring Quality Control for Lung Stereotactic Body Radiation Therapy

Purpose: The intrafraction verification provided by ExacTrac X-ray 6D Snap Verification (ET-SV) allows the tracking of potential isocenter displacements throughout patient position and treatment. The aims of this study were (1) to measure the intrafraction variations of the isocenter position (random errors); (2) to study the amplitude of the variation related to the fraction duration; and (3) to assess the impact of the table movement on positioning uncertainties. Methods and Materials: ET-SV uses images acquired before or during treatment delivery or both to detect isocenter displacement. Twenty patients treated with stereotactic body radiation therapy (SBRT) for lung tumors underwent SV before or during each beam. Noncoplanar beams were sometimes necessary. The time between the setup of the patient and each SV was noted, and values of deviations were compiled for 3 SV time groups: SV performed at {<=}10 min (group 1), between 11 and 20 min (group 2), and {>=}21 min (group 3). Random errors in positioning during the use of noncoplanar fields were noted. Results: The mean isocenter deviation {+-}SD was 2 {+-} 0.5 mm (range, 1-8 mm). The average deviations {+-}SD increased significantly from 1.6 {+-} 0.5 mm to 2.1 {+-} 0.8 mm and 2.2 {+-} 0.6 mm for groups 1, 2, and 3 (P=.002), respectively. Percentages of deviation {>=}3 mm were 7.06%, 22.83%, and 28.07% and 1.08%, 4.15%, and 8.4% for {>=}5 mm (P<.0001). For 11 patients, table rotation was necessary. The mean isocenter deviation {+-}SD increased significantly from 1.9 {+-} 0.5 mm before table rotation to 2.7 {+-} 0.5 mm (P=.001) for the first beam treated after rotation. Conclusions: SV detects isocenter deviations, which increase in amplitude and frequency with the fraction duration, and enables intrafraction verification for SBRT (taking into account clinical condition and technical issues). SV gives accurate targeting at any time during irradiation and may raise confidence to escalate the dose. SV appears to be an important tool for ensuring the quality control of SBRT.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2012

EXACTRAC x-ray and beam isocenters--What's the difference?

Purpose: To evaluate the geometric accuracy of the isocenter of an image-guidance system, as implemented in the exactrac system from brainlab, relative to the linear accelerator radiation isocenter. Subsequently to correct the x-ray isocenter of the exactrac system for any geometric discrepancies between the two isocenters. Methods: Five Varian linear accelerators all equipped with electronic imaging devices and exactrac with robotics from brainlab were evaluated. A commercially available Winston-Lutz phantom and an in-house made adjustable base were used in the setup. The electronic portal imaging device of the linear accelerators was used to acquire MV-images at various gantry angles. Stereoscopic pairs of x-ray images were acquired using the exactrac system. The deviation between the position of the external laser isocenter and the exactrac isocenter was evaluated using the commercial software of the exactrac system. In-house produced software was used to analyze the MV-images and evaluate the deviation between the external laser isocenter and the radiation isocenter of the linear accelerator. Subsequently, the deviation between the radiation isocenter and the isocenter of the exactrac system was calculated. A new method of calibrating the isocenter of the exactrac system was applied to reduce the deviations between the radiation isocenter and the exactrac isocenter. Results: To evaluate the geometric accuracy a 3D deviation vector was calculated for each relative isocenter position. The 3D deviation between the external laser isocenter and the isocenter of the exactrac system varied from 0.21 to 0.42 mm. The 3D deviation between the external laser isocenter and the linac radiation isocenter ranged from 0.37 to 0.83 mm. The 3D deviation between the radiation isocenter and the isocenter of the exactrac system ranged from 0.31 to 1.07 mm. Using the new method of calibrating the exactrac isocenter the 3D deviation of one linac was reduced from 0.90 to 0.23 mm. The results were complicated due to routine maintenance of the linac, including laser calibration. It was necessary to repeat the measurements in order to perform the calibration of the exactrac isocenter. Conclusions: The deviations between the linac radiation isocenter and the exactrac isocenter were of an order that may have clinical relevance. An alternative method of calibrating the isocenter of the exactrac system was applied and reduced the deviations between the two isocenters.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

NASA NTRS2004

In-Flight Assessment of a Pursuit Guidance Display Format for Manually Flown Precision Instrument Approaches

In-flight evaluations of a pursuit guidance display system for manually flown precision instrument approaches were performed. The guidance system was integrated into the RASCAL JUH-60A Black Hawk helicopter. The applicability of the pursuit guidance disp1aFs to the operation of Runway Independent Aircraft (RIA) is made evident because the displays allow the pilot to fly a complex, multi-segment, descending, decelerating approach trajectory. The complex trajectory chosen for this in-flight assessment began from a downwind abeam position at 110 knots and was hand-flown to a 50 ft decision altitude at 40 knots using a rate-command/attitude-hold plus turn-coordination control system. The elements of the pursuit guidance format displayed on a 10-inch liquid crystal display (LCD) flat panel consisted of a flightpath vector and a "leader" aircraft as the pursuit guidance element. Approach guidance was based primarily on carrier-phase differential Global Positioning System (GPS) navigation, and secondarily on both medium accuracy inertial navigation unit states and air data computer states. Required Navigation Performance (RNP) concepts were applied to the construction of display elements such as lateral/vertical deviation indicators and a tunnel that indicated to the pilot, in real-time, the performance with respect to RNP error bounds. The results of the flight evaluations of the guidance display show that precise path control for operating within tight RNP boundaries (RNP 0.007NM/24ft for initial approach, RNP 0.008NM/19ft for intermediate approach, and RNP 0.002NM/9ft for final approach) is attainable with minimal to moderate pilot workload.

Moralez, Ernesto, III↗

DOE OSTI2011

Optical Rotation Calculated with Time-Dependent Density Functional Theory: The OR45 Benchmark

Time-dependent density functional theory (TDDFT) computations are performed for 42 organic molecules and 3 transition metal complexes, with experimental molar optical rotations ranging from 2 to 2 x 10{sup 4} deg cm{sup 2} dmol{sup -1}. The performance of the global hybrid functionals B3LYP, PBE0, and BHLYP, and of the range-separated functionals CAM-B3LYP and LR-PBE0 (the latter being fully long-range corrected), are investigated. The performance of different basis sets is studied. When compared to liquid-phase experimental data, the range-separated functionals do, on average, not perform better than B3LYP and PBE0. Median relative deviations between calculations and experiment range from 25 to 29%. A basis set recently proposed for optical rotation calculations (LPol-ds) on average does not give improved results compared to aug-cc-pVDZ in TDDFT calculations with B3LYP. Individual cases are discussed in some detail, among them norbornenone for which the LR-PBE0 functional produced an optical rotation that is close to available data from coupled-cluster calculations, but significantly smaller in magnitude than the liquid-phase experimental value. Range-separated functionals and BHLYP perform well for helicenes and helicene derivatives. Metal complexes pose a challenge to first-principles calculations of optical rotation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2019

Investigating the Impact of Connected Vehicle Market Share on the Performance of Reinforcement-Learning Based Traffic Signal Control

We aim to understand and explore the performance of reinforcement learning based signal control algorithms in a mixed environment with less than 100% market share of connected and automated vehicles (CAVs). Within a simulation environment, we have considered partial connectivity—less than 100% market share of CAVs—in the network and investigated the impact on the performance of the signal control algorithm. Two test networks including a four-intersection arterial in Lankershim Boulevard, CA, and a portion of downtown Springfield, IL, with 20 intersections. The first network is calibrated in the micro-simulator PTV Vissim with the US DOT provided NGSIM datasets. The results provide insights regarding the impact of the connectivity and sensing technologies on the practical implementation of traffic signal control algorithms that leverage the data sharing capability of a connected environment. For scenarios with 40% or more market share of CAVs, we observed improvement in the performance metrics—travel time, queue time, and energy consumption—with the increase in market share. Results from our experiments do not indicate any clear trend when the networks have low (less than 40%) market share of CAVs. The higher standard deviations as obtained from the statistical analyses of the performance metrics at low market share may indicate the instability of the RL controller arising from the partial (if not zero) observability of the traffic states. Further, we have conducted simplified scenario analyses to explore the impact of the market share of battery electric vehicles (BEVs) on energy consumption due to the regenerative braking feature. Our results and findings will be the foundation for the future reinforcement learning based control algorithm development that accounts for partial connectivity—less than 100% CAV market share, and the presence of BEVs in a network of connected and automated signalized intersections.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2022

Efficient Loads Surrogates for Waked Turbines in an Array

Accurately and efficiently predicting wind turbine structural loading is a crucial step in wind farm design. Without considering structural loading, wind farm optimization could negatively impact turbine fatigue and ultimate loads, especially for waked and partially waked turbines, which could result in higher maintenance costs and reduced turbine lifetime. However, predicting turbine loads throughout an array is a costly step, as these quantities require time-accurate results across long time histories, which is often intractable for large array optimization. Therefore, surrogate models that link array spacing to load outputs are often used, but the surrogates are then unique to the inflow conditions and array configurations in the training library. This work develops surrogate models for many wind turbine load outputs based solely on rotor plane velocity measurements, with no required input about array configuration or freestream inflow parameters. Surrogate models were constructed for many turbine quantities of interest (QoI), considering mean, standard deviation, ultimate, and fatigue loads. In general, most QoI statistics were accurately captured, as measured by predicted vs. actual correlation coefficient, confirming the suitability of the approach. Temporal mean values of the QoI required only temporal mean measurements of the rotor plane inflow velocity. However, accurate prediction of temporal standard deviation, ultimate, and fatigue values of QoI also required temporal standard deviations of the rotor plane velocity field. Poor surrogate performance was observed when too many correlated inputs were used, such as multiple velocity components. If the fewest inflow parameters are used to construct the surrogates, the average correlation coefficient value for all output QoI statistics is 0.89. Surrogates for standard deviations and damage equivalent loads (DELs) of turbine QoIs generally had lower accuracy and tower-base and shaft load channels posed the most difficult to capture accurately. The results suggest that these surrogates could be easily paired with analytic wake models, which are frequently used for pre-construction wind farm array optimization, to account for turbine loading in addition to power production. By including the optimal inflow conditions, the surrogate accuracy can improve to an average correlation coefficient value for all output QoI statistics of 0.92. This work has established the ability to build accurate surrogates for mean, standard deviation, ultimate load, and DEL turbine QoI values based on the rotor plane inflow velocity, and identified which inflow conditions lead to greater surrogate accuracy.

17 WIND ENERGY↗

DOE OSTI2026

Enhancing segmentation fairness through curriculum learning and progressive loss: a centralized and federated perspective on radiograph analysis

Bias in medical image segmentation can lead to unequal performance across demographic subgroups, raising concerns about fairness and reliability in clinical AI systems. While deep learning models have achieved high segmentation accuracy, ensuring equitable performance across race and gender remains a significant challenge, particularly in privacy-sensitive healthcare environments. This study investigates fairness-aware medical image segmentation for hip and knee radiographs using deep learning models evaluated in both centralized and Federated Learning (FL) settings. We introduce Curriculum Learning (CL) strategies and Progressive Loss (PL) functions to regulate sample difficulty during training. In addition, we propose two novel fairness-oriented federated learning algorithms, Federated Intersection over Union (FedIoU) and Federated Intersection over Union with Outlier Analysis (FedIoUoutlier). Experiments are conducted using multiple segmentation backbones and simulated multi-site data partitions derived from the Osteoarthritis Initiative dataset. Model performance is evaluated using Intersection over Union (IoU), IoU standard deviation, Skewed Error Ratio (SER), and Min-Max Disparity across race and gender subgroups. Statistical significance was verified using paired t-tests to compare per-sample IoU performance against baseline configurations. Across both hip and knee segmentation tasks, curriculum learning and progressive loss strategies consistently improved segmentation accuracy and reduced demographic performance disparities in centralized training. In federated settings, fairness-aware aggregation further enhanced performance. Notably, FedIoUoutlier combined with balanced curriculum learning and tiered progressive loss achieved the highest mean IoU while yielding the lowest SER and Min-Max Disparity, indicating improved fairness without sacrificing accuracy. In several configurations, federated models matched or exceeded the performance of optimized centralized models, with statistically significant improvements in per-sample IoU over baseline configurations. The results demonstrate that structured training strategies and fairness-aware federated aggregation can jointly improve accuracy, stability, and demographic fairness in medical image segmentation. By integrating curriculum learning, progressive loss, and novel FL algorithms, this work provides a practical pathway toward equitable and privacy-preserving AI systems for medical imaging.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Offshore wind energy forecasting sensitivity to sea surface temperature input in the Mid-Atlantic

Abstract. As offshore wind farm development expands, accurate wind resource forecasting over the ocean is needed. One important yet relatively unexplored aspect of offshore wind resource assessment is the role of sea surface temperature (SST). Models are generally forced with reanalysis data sets, which employ daily SST products. Compared with observations, significant variations in SSTs that occur on finer timescales are often not captured. Consequently, shorter-lived events such as sea breezes and low-level jets (among others), which are influenced by SSTs, may not be correctly represented in model results. The use of hourly SST products may improve the forecasting of these events. In this study, we examine the sensitivity of model output from the Weather Research and Forecasting model (WRF) 4.2.1 to different SST products. We first evaluate three different data sets: the Multiscale Ultrahigh Resolution (MUR25) SST analysis, a daily, 0.25∘ × 0.25∘ resolution product; the Operational Sea Surface Temperature and Ice Analysis (OSTIA), a daily, 0.054∘ × 0.054∘ resolution product; and SSTs from the Geostationary Operational Environmental Satellite 16 (GOES-16), an hourly, 0.02∘ × 0.02∘ resolution product. GOES-16 is not processed at the same level as OSTIA and MUR25; therefore, the product requires gap-filling using an interpolation method to create a complete map with no missing data points. OSTIA and GOES-16 SSTs validate markedly better against buoy observations than MUR25, so these two products are selected for use with model simulations, while MUR25 is at this point removed from consideration. We run the model for June and July of 2020 and find that for this time period, in the Mid-Atlantic, although OSTIA SSTs overall validate better against in situ observations taken via a buoy array in the area, the two products result in comparable hub-height (140 m) wind characterization performance on monthly timescales. Additionally, during hours-long flagged events (< 30 h each) that show statistically significant wind speed deviations between the two simulations, both simulations once again demonstrate similar validation performance (differences in bias, earth mover's distance, correlation, and root mean square error on the order of 10−1 or less), with GOES-16 winds validating nominally better than OSTIA winds. With a more refined GOES-16 product, which has been not only gap-filled but also assimilated with in situ SST measurements in the region, it is likely that hub-height winds characterized by GOES-16-informed simulations would definitively validate better than those informed by OSTIA SSTs.

17 WIND ENERGY↗

NASA NTRS2010

Verify MesoNAM Performance

The AMU conducted an objective analysis of the MesoNAM forecasts compared to observed values from sensors at specified KSC/CCAFS wind towers by calculating the following statistics to verify the performance of the model: 1) Bias (mean difference), 2) Standard deviation of Bias, 3) Root Mean Square Error (RMSE), and 4) Hypothesis test for Bias = O. The 45 WS LWOs use the MesoNAM to support launch weather operations. However, the actual performance of the model at KSC and CCAFS had not been measured objectively. The analysis compared the MesoNAM forecast winds, temperature and dew point to the observed values from the sensors on wind towers. The data were stratified by tower sensor, month and onshore/offshore wind direction based on the orientation of the coastline to each tower's location. The model's performance statistics were then calculated for each wind tower based on sensor height and model initialization time. The period of record for the data used in this task was based on the operational start of the current MesoNAM in mid-August 2006 and so the task began with the first full month of data, September 2006, through May 2010. The analysis of model performance indicated: a) The accuracy decreased as the forecast valid time from the model initialization increased, b) There was a diurnal signal in T with a cool bias during the late night and a warm bias during the afternoon, c) There was a diurnal signal in Td with a low bias during the afternoon and a high bias during the late night, and d) The model parameters at each vertical level most closely matched the observed parameters at heights closest to those vertical levels. The AMU developed a GUI that consists of a multi-level drop-down menu written in JavaScript embedded within the HTML code. This tool allows the LWO to easily and efficiently navigate among the charts and spreadsheet files containing the model performance statistics. The objective statistics give the LWOs knowledge of the model's strengths and weaknesses and the GUI allows quick access to the data which will result in improved forecasts for operations.

Bauman, William H., III↗

DOE OSTI2018

Bayesian approach to model-based extrapolation of nuclear observables

Here, we considered 10 global models based on nuclear density functional theory with realistic energy density functionals as well as two more phenomenological mass models. The emulators of two-neutron separation energy residuals and Bayesian confidence intervals defining theoretical error bars were constructed using Bayesian Gaussian processes and Bayesian neural networks. By establishing statistical methodology and parameters, we carried out extrapolations toward the two-neutron dripline. While both Gaussian processes (GP) and Bayesian neural networks reduce the root-mean-square (rms) deviation from experiment significantly, GP offers a better and much more stable performance. The increase in the predictive power of microscopic models aided by the statistical treatment is quite astonishing: The resulting rms deviations from experiment on the testing dataset are similar to those of more phenomenological models. The estimated credibility intervals on predictions make it possible to evaluate predictive power of individual models and also make quantified predictions using groups of models. The proposed robust statistical approach to extrapolation of nuclear model results can be useful for assessing the impact of current and future experiments in the context of model developments. The new Bayesian capability to evaluate residuals is also expected to impact research in the domains where experiments are currently impossible, for instance, in simulations of the astrophysical r process.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

NASA NTRS2008

Wide-Band Radar for Measuring Thickness of Sea Ice

A wide-band penetrating radar system for measuring the thickness of sea ice is under development. The need for this or a similar system arises as follows: Spatial and temporal variations in the thickness of sea ice are important indicators of heat fluxes between the ocean and atmosphere and, hence, are important indicators of climate change in polar regions. A remote-sensing system that could directly measure the thickness of sea ice over a wide thickness range from aboard an aircraft or satellite would be of great scientific value. Obtaining thickness measurements over a wide region at weekly or monthly time intervals would contribute significantly to understanding of changes in the spatial distribution and of the mass balance of sea ice. A prototype of the system was designed on the basis of computational simulations directed toward understanding what signal frequencies are needed to satisfy partly competing requirements to detect both bottom and top ice surfaces, obtain adequate penetration despite high attenuation in the lossy sea-ice medium, and obtain adequate resolution, all over a wide thickness range. The prototype of the system is of the frequency-modulation, continuous-wave (FM-CW) type. At a given time, the prototype functions in either of two frequency-band/operational-mode combinations that correspond to two thickness ranges: a lower-frequency (50 to 250 MHz) mode for measuring thickness greater than about 1 m, and a higher frequency (300 to 1,300 MHz) mode for measuring thickness less than about 1 m. The bandwidth in the higher-frequency (lesser-thickness) mode is adequate for a thickness resolution of 15 cm; the bandwidth in the lower-frequency (greater-thickness) mode is adequate for a thickness resolution of 75 cm. Although a thickness resolution of no more than 25 cm is desired for scientific purposes, the 75-cm resolution was deemed acceptable for the purpose of demonstrating feasibility. The prototype was constructed as a modified version of a 500-to-2,000-MHz FM-CW radar system developed previously for mapping near-surface internal layers of the Greenland ice sheet. The prototype included two sets of antennas: one for each frequency-band/mode. For Arctic and Antarctic field tests, the prototype was mounted on a sled that was towed across the ice. The Arctic field test was performed in the lower-frequency mode on ice ranging in thickness from 1 to 4 m. In the analysis of the results of the Arctic field test, a comparison of the radar-determined ice thicknesses with actual ice thicknesses yielded an overall mean difference of 14 cm and standard deviation of 30 cm. The Antarctic field test was performed in the higher-frequency mode; analysis of the results led to the conclusion that this mode is useful for measuring thicknesses between 0.5 and 1 m. Several modifications have been conceived for implementation in further development toward an improved practical system: The system would function in a single frequency-band/mode (100 to 1,200 MHz) that would afford a resolution of about 15 cm. There would be a single antenna system that would be optimized for the entire 100-to-1,000-MHz frequency band. To enable ice-thickness surveys over larger areas, the system would be made capable of operating aboard a low-flying aircraft that could be either piloted or robotic. Data-processing techniques to deconvolve the system response have been developed on the basis of impulse-response measurements over a calm ocean. Implementation of these techniques in the system would enable correction for imperfections of the system and would thereby increase the effective sensitivity of the system.

Gogineni, Prasad↗

DOE OSTI2015

A general framework of noise suppression in material decomposition for dual-energy CT

Purpose: As a general problem of dual-energy CT (DECT), noise amplification in material decomposition severely reduces the signal-to-noise ratio on the decomposed images compared to that on the original CT images. In this work, the authors propose a general framework of noise suppression in material decomposition for DECT. The method is based on an iterative algorithm recently developed in their group for image-domain decomposition of DECT, with an extension to include nonlinear decomposition models. The generalized framework of iterative DECT decomposition enables beam-hardening correction with simultaneous noise suppression, which improves the clinical benefits of DECT. Methods: The authors propose to suppress noise on the decomposed images of DECT using convex optimization, which is formulated in the form of least-squares estimation with smoothness regularization. Based on the design principles of a best linear unbiased estimator, the authors include the inverse of the estimated variance–covariance matrix of the decomposed images as the penalty weight in the least-squares term. Analytical formulas are derived to compute the variance–covariance matrix for decomposed images with general-form numerical or analytical decomposition. As a demonstration, the authors implement the proposed algorithm on phantom data using an empirical polynomial function of decomposition measured on a calibration scan. The polynomial coefficients are determined from the projection data acquired on a wedge phantom, and the signal decomposition is performed in the projection domain. Results: On the Catphan{sup ®}600 phantom, the proposed noise suppression method reduces the average noise standard deviation of basis material images by one to two orders of magnitude, with a superior performance on spatial resolution as shown in comparisons of line-pair images and modulation transfer function measurements. On the synthesized monoenergetic CT images, the noise standard deviation is reduced by a factor of 2–3. By using nonlinear decomposition on projections, the authors’ method effectively suppresses the streaking artifacts of beam hardening and obtains more uniform images than their previous approach based on a linear model. Similar performance of noise suppression is observed in the results of an anthropomorphic head phantom and a pediatric chest phantom generated by the proposed method. With beam-hardening correction enabled by their approach, the image spatial nonuniformity on the head phantom is reduced from around 10% on the original CT images to 4.9% on the synthesized monoenergetic CT image. On the pediatric chest phantom, their method suppresses image noise standard deviation by a factor of around 7.5, and compared with linear decomposition, it reduces the estimation error of electron densities from 33.3% to 8.6%. Conclusions: The authors propose a general framework of noise suppression in material decomposition for DECT. Phantom studies have shown the proposed method improves the image uniformity and the accuracy of electron density measurements by effective beam-hardening correction and reduces noise level without noticeable resolution loss.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2023

Power System Event Detection Using the Energy Detector: A Performance Analysis

As the grid becomes smarter, the need to accurately detect, predict, and classify waveform phenomena is growing. When it comes to detecting high-frequency behaviors, i.e. transients, it is especially important to employ an event detection system that is able to accurately uncover these types of disturbances that would otherwise be lost with traditional hardware. In this paper, we first present the energy detector; a waveform event detection system that adaptively monitors a signal's energy and picks out high-frequency events that deviate from the nominal state. Secondly, we evaluate the performance of this detector against waveform data that have been corrupted by sensor irregularities. Using Oak Ridge National Laboratory's sensor testbed, we are able to show the results of the detector's performance against events that have been corrupted by three distinct sensor types, and examine how these results change with multiple trials. The results show excellent performance when detecting the beginning of an anomalous event with an average of less than 1% error.

Ekti, Ali Riza↗

DOE OSTI2021

Polyferrocenylsilane Semicrystalline Polymer Additive for Solution-Processed p-Channel Organic Thin Film Transistors

In this study, we demonstrated for the first time that a metal-containing semicrystalline polymer was used as an additive to mediate the thin film morphology of solution-grown, small-molecule organic semiconductors. By mixing polyferrocenylsilane (PFS) with an extensively-studied organic semiconductor 6,13-bis(triisopropylsilylethynyl) pentacene (TIPS pentacene), PFS as a semicrystalline polymer independently forms nucleation and crystallization while simultaneously ameliorating diffusivity of the blend system and tuning the surface energies as a result of its partially amorphous property. We discovered that the resultant blend film exhibited a 6-fold reduction in crystal misorientation angle and a 3-fold enlargement in average grain width. Enhanced crystal orientation considerably reduces mobility variation, while minimized defects and trap centers located at grain boundaries lessen the adverse impact on the charge transport. Consequently, bottom-gate, top-contact organic thin film transistors (OTFTs) based on the TIPS pentacene/PFS mixture yielded a 40% increase in performance consistency (represented by the ratio of average mobility to the standard deviation of mobility). The PFS semicrystalline polymer-controlled crystallization can be used to regulate the thin film morphology of other high-performance organic semiconductors and shed light on applications in organic electronic devices.

36 MATERIALS SCIENCE↗

NASA NTRS1994

Effects of expected-value information and display format on recognition of aircraft subsystem abnormalities

This study identifies improved methods to present system parameter information for detecting abnormal conditions and to identify system status. Two workstation experiments were conducted. The first experiment determined if including expected-value-range information in traditional parameter display formats affected subject performance. The second experiment determined if using a nontraditional parameter display format, which presented relative deviation from expected value, was better than traditional formats with expected-value ranges included. The inclusion of expected-value-range information onto traditional parameter formats was found to have essentially no effect. However, subjective results indicated support for including this information. The nontraditional column deviation parameter display format resulted in significantly fewer errors compared with traditional formats with expected-value-ranges included. In addition, error rates for the column deviation parameter display format remained stable as the scenario complexity increased, whereas error rates for the traditional parameter display formats with expected-value ranges increased. Subjective results also indicated that the subjects preferred this new format and thought that their performance was better with it. The column deviation parameter display format is recommended for display applications that require rapid recognition of out-of-tolerance conditions, especially for a large number of parameters.

Palmer, Michael T.↗

NASA NTRS1972

Systematic two-dimensional cascade tests. Volume 3: Slotted double circular-arc hydrofoils

Performance parameters are presented for cascades of slotted double circular-arc hydrofoils tested over a range of systematically introduced variables in a rectilinear cascade tunnel which uses water as the test medium. Cascade configurations included various combinations of an inlet flow angle of 50, 60 and 70 deg; a cascade solidity of 0.75, 1.00 and 1.50; a hydrofoil camber angle of 20, 30, 40 and 45 deg; and angles of incidence between positive and negative stall. The slot was positioned at the 45 percent chord station and the slot exit width was 0.047-in. Tests were also performed with the slot positioned at the 35 percent chord station and with slot widths of 0.63 and 0.094-in. These data were correlated to indicate the effects of slot location and slot width on minimum loss incidence and deviation angles. In addition, a comparison is presented of the performance parameters for cascades of slotted and unslotted hydrofoils.

Columbo, R. M.↗

NASA NTRS1994

A neural network controller for automated composite manufacturing

At McDonnell Douglas Aerospace (MDA), an artificial neural network based control system has been developed and implemented to control laser heating for the fiber placement composite manufacturing process. This neurocontroller learns an approximate inverse model of the process on-line to provide performance that improves with experience and exceeds that of conventional feedback control techniques. When untrained, the control system behaves as a proportional plus integral (PI) controller. However after learning from experience, the neural network feedforward control module provides control signals that greatly improve temperature tracking performance. Faster convergence to new temperature set points and reduced temperature deviation due to changing feed rate have been demonstrated on the machine. A Cerebellar Model Articulation Controller (CMAC) network is used for inverse modeling because of its rapid learning performance. This control system is implemented in an IBM compatible 386 PC with an A/D board interface to the machine.

Lichtenwalner, Peter F.↗