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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 1,639 records · Page 91
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DOE OSTI2015

SU-E-I-57: Estimating the Occupational Eye Lens Dose in Interventional Radiology Using Active Personal Dosimeters Worn On the Chest

Purpose: To provide a general formalism for determination of occupational eye lens dose based on the response of an active personal dosimeter (APD) worn at chest level above the radiation protection apron. Methods: The formalism consists of three factors: (1) APD conversion factor converting the reading at chest level (APDchest) to the corresponding personal dose equivalent at eye level, (2) Dose conversion factor transferring the measured dose quantity, Hp(10), into a dose quantity relevant for the eye lens dose, (3) Correction factor accounting for differences in exposure of the eye(s) compared to the exposure at chest level (e.g., due to protective lead glasses).The different factors were investigated and evaluated based on phantom and clinical measurements performed in an x-ray angiography suite for interventional cardiology. Results: The eye lens dose can be conservatively estimated by assigning an appropriate numerical value to each factor entering the formalism that in most circumstances overestimates the dose. Doing so, the eye lens dose to the primary operator and assisting staff was estimated in this work as D-eye,primary = 2.0 APDchest and D-eye,assisting = 1.0 APDchest, respectively.The annual eye lens dose to three nurses and one cardiologist was estimated to be 2, 2, 2, and 13 mSv (Hp(0.07)), respectively, using a TLD dosimeter worn at eye level. In comparison, using the formalism and APDchest measurements, the respective doses were 2, 2, 2, and 16 mSv (Hp(3)). Conclusion: The formalism outlined in this work can be used to estimate the occupational eye lens dose from the response of an APD worn on the chest. The formalism is general and could be applied also to other types of dosimeters. However, the numerical value of the different factors may differ from those obtained with the APD’s used in this work due to differences in dosimeter properties.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-I-65: Estimation of Tagging Efficiency in Pseudo-Continuous Arterial Spin Labeling (pCASL) MRI

Purpose: pCASL was recommended as a potent approach for absolute cerebral blood flow (CBF) quantification in clinical practice. However, uncertainties of tagging efficiency in pCASL remain an issue. This study aimed to estimate tagging efficiency by using short quantitative pulsed ASL scan (FAIR-QUIPSSII) and compare resultant CBF values with those calibrated by using 2D Phase Contrast (PC) MRI. Methods: Fourteen normal volunteers participated in this study. All images, including whole brain (WB) pCASL, WB FAIR-QUIPSSII and single-slice 2D PC, were collected on a 3T clinical MRI scanner with a 8-channel head coil. DeltaM map was calculated by averaging the subtraction of tag/control pairs in pCASL and FAIR-QUIPSSII images and used for CBF calculation. Tagging efficiency was then calculated by the ratio of mean gray matter CBF obtained from pCASL and FAIR-QUIPSSII. For comparison, tagging efficiency was also estimated with 2D PC, a previously established method, by contrast WB CBF in pCASL and 2D PC. Feasibility of estimation from a short FAIR-QUIPSSII scan was evaluated by number of averages required for obtaining a stable deltaM value. Setting deltaM calculated by maximum number of averaging (50 pairs) as reference, stable results were defined within ±10% variation. Results: Tagging efficiencies obtained by 2D PC MRI (0.732±0.092) were significantly lower than which obtained by FAIRQUIPPSSII (0.846±0.097) (P<0.05). Feasibility results revealed that four pairs of images in FAIR-QUIPPSSII scan were sufficient to obtain a robust calibration of less than 10% differences from using 50 pairs. Conclusion: This study found that reliable estimation of tagging efficiency could be obtained by a few pairs of FAIR-QUIPSSII images, which suggested that calibration scan in a short duration (within 30s) was feasible. Considering recent reports concerning variability of PC MRI-based calibration, this study proposed an effective alternative for CBF quantification with pCASL.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-J-92: Validating Dose Uncertainty Estimates Produced by AUTODIRECT, An Automated Program to Evaluate Deformable Image Registration Accuracy

Purpose: Deformable image registration (DIR) is a powerful tool with the potential to deformably map dose from one computed-tomography (CT) image to another. Errors in the DIR, however, will produce errors in the transferred dose distribution. We have proposed a software tool, called AUTODIRECT (automated DIR evaluation of confidence tool), which predicts voxel-specific dose mapping errors on a patient-by-patient basis. This work validates the effectiveness of AUTODIRECT to predict dose mapping errors with virtual and physical phantom datasets. Methods: AUTODIRECT requires 4 inputs: moving and fixed CT images and two noise scans of a water phantom (for noise characterization). Then, AUTODIRECT uses algorithms to generate test deformations and applies them to the moving and fixed images (along with processing) to digitally create sets of test images, with known ground-truth deformations that are similar to the actual one. The clinical DIR algorithm is then applied to these test image sets (currently 4) . From these tests, AUTODIRECT generates spatial and dose uncertainty estimates for each image voxel based on a Student’s t distribution. This work compares these uncertainty estimates to the actual errors made by the Velocity Deformable Multi Pass algorithm on 11 virtual and 1 physical phantom datasets. Results: For 11 of the 12 tests, the predicted dose error distributions from AUTODIRECT are well matched to the actual error distributions within 1–6% for 10 virtual phantoms, and 9% for the physical phantom. For one of the cases though, the predictions underestimated the errors in the tail of the distribution. Conclusion: Overall, the AUTODIRECT algorithm performed well on the 12 phantom cases for Velocity and was shown to generate accurate estimates of dose warping uncertainty. AUTODIRECT is able to automatically generate patient-, organ- , and voxel-specific DIR uncertainty estimates. This ability would be useful for patient-specific DIR quality assurance.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

MO-DE-210-05: Improved Accuracy of Liver Feature Motion Estimation in B-Mode Ultrasound for Image-Guided Radiation Therapy

Purpose: In similarity-measure based motion estimation incremental tracking (or template update) is challenging due to quantization, bias and accumulation of tracking errors. A method is presented which aims to improve the accuracy of incrementally tracked liver feature motion in long ultrasound sequences. Methods: Liver ultrasound data from five healthy volunteers under free breathing were used (15 to 17 Hz imaging rate, 2.9 to 5.5 minutes in length). A normalised cross-correlation template matching algorithm was implemented to estimate tissue motion. Blood vessel motion was manually annotated for comparison with three tracking code implementations: (i) naive incremental tracking (IT), (ii) IT plus a similarity threshold (ST) template-update method and (iii) ST coupled with a prediction-based state observer, known as the alpha-beta filter (ABST). Results: The ABST method produced substantial improvements in vessel tracking accuracy for two-dimensional vessel motion ranging from 7.9 mm to 40.4 mm (with mean respiratory period: 4.0 ± 1.1 s). The mean and 95% tracking errors were 1.6 mm and 1.4 mm, respectively (compared to 6.2 mm and 9.1 mm, respectively for naive incremental tracking). Conclusions: High confidence in the output motion estimation data is required for ultrasound-based motion estimation for radiation therapy beam tracking and gating. The method presented has potential for monitoring liver vessel translational motion in high frame rate B-mode data with the required accuracy. This work is support by Cancer Research UK Programme Grant C33589/A19727.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

WE-D-303-05: Dosimetric Accuracy of CBCT Images Estimated by a Motion Modeling and Free-Form Deformation Technique for Radiotherapy of Lung Cancer

Purpose: To investigate the dosimetric accuracy of CBCTs estimated by a motion modeling and free-form deformation(MM-FD) technique for radiotherapy of lung cancer. Methods: Various inter-fractional variations featuring patient motion pattern change, tumor size change and tumor average position change were simulated from planning-CT to on-board images using both digital and physical motion phantoms. The doses calculated on the planning-CT (planned doses), the on-board CBCT estimated by MM-FD (MM-FD doses) and the on-board CBCT reconstructed by the conventional Feldkamp-Davis-Kress(FDK) algorithm (FDK doses) were compared to the on-board dose calculated on the ‘gold-standard’ on-board images (gold-standard doses). The absolute deviations of minimum dose (dDmin), maximum dose (dDmax), mean dose (dDmean) and dose coverage (dV100%) of PTV were evaluated. In addition, 4D on-board dose accumulations were performed using the 4D-CBCT images estimated by MM-FD. The accumulated doses were compared to measurements using OSL detectors and radiochromic films. Results: Of all the 50 scenarios simulated, the average(± standard deviation) dDmin, dDmax, dDmean and dV100% (values normalized by the prescription dose or the PTV volume) between the planned and the gold-standard PTV doses were 34.8% (± 29.2%), 3.2% (± 3.8%), 3.5% (± 3.5%) and 13.0% (± 11.4%), respectively. The corresponding values of FDK PTV doses were 3.1% (± 3.7%), 1.4% (± 1.1%), 2.1% (± 0.8%) and 14.5% (± 14.2%), respectively. In contrast, the corresponding values of MM-FD PTV doses were 0.4% (± 0.5%), 0.9% (± 0.7%), 0.6% (± 0.4%) and 0.9% (± 0.8%), respectively.For the 4D dose accumulation study, the average(± standard deviation) absolute dose deviation (normalized by local doses) between the accumulated doses and the OSL measured doses was 3.0% (± 2.4%). The average gamma pass-rate(3%/3mm) between the accumulated doses and the radiochromic film measured doses was 96.1%. Conclusion: MM-FD estimated CBCT enables accurate on-board dose calculation and accumulation for lung radiation therapy. The research was funded by the National Institutes of Health Grant No. R01-CA184173 and a grant from Varian Medical Systems.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Dosimetric verification of lung cancer treatment using the CBCTs estimated from limited-angle on-board projections

Purpose: Lung cancer treatment is susceptible to treatment errors caused by interfractional anatomical and respirational variations of the patient. On-board treatment dose verification is especially critical for the lung stereotactic body radiation therapy due to its high fractional dose. This study investigates the feasibility of using cone-beam (CB)CT images estimated by a motion modeling and free-form deformation (MM-FD) technique for on-board dose verification. Methods: Both digital and physical phantom studies were performed. Various interfractional variations featuring patient motion pattern change, tumor size change, and tumor average position change were simulated from planning CT to on-board images. The doses calculated on the planning CT (planned doses), the on-board CBCT estimated by MM-FD (MM-FD doses), and the on-board CBCT reconstructed by the conventional Feldkamp-Davis-Kress (FDK) algorithm (FDK doses) were compared to the on-board dose calculated on the “gold-standard” on-board images (gold-standard doses). The absolute deviations of minimum dose (ΔD{sub min}), maximum dose (ΔD{sub max}), and mean dose (ΔD{sub mean}), and the absolute deviations of prescription dose coverage (ΔV{sub 100%}) were evaluated for the planning target volume (PTV). In addition, 4D on-board treatment dose accumulations were performed using 4D-CBCT images estimated by MM-FD in the physical phantom study. The accumulated doses were compared to those measured using optically stimulated luminescence (OSL) detectors and radiochromic films. Results: Compared with the planned doses and the FDK doses, the MM-FD doses matched much better with the gold-standard doses. For the digital phantom study, the average (± standard deviation) ΔD{sub min}, ΔD{sub max}, ΔD{sub mean}, and ΔV{sub 100%} (values normalized by the prescription dose or the total PTV) between the planned and the gold-standard PTV doses were 32.9% (±28.6%), 3.0% (±2.9%), 3.8% (±4.0%), and 15.4% (±12.4%), respectively. The corresponding values of FDK PTV doses were 1.6% (±1.9%), 1.2% (±0.6%), 2.2% (±0.8%), and 17.4% (±15.3%), respectively. In contrast, the corresponding values of MM-FD PTV doses were 0.3% (±0.2%), 0.9% (±0.6%), 0.6% (±0.4%), and 1.0% (±0.8%), respectively. Similarly, for the physical phantom study, the average ΔD{sub min}, ΔD{sub max}, ΔD{sub mean}, and ΔV{sub 100%} of planned PTV doses were 38.1% (±30.8%), 3.5% (±5.1%), 3.0% (±2.6%), and 8.8% (±8.0%), respectively. The corresponding values of FDK PTV doses were 5.8% (±4.5%), 1.6% (±1.6%), 2.0% (±0.9%), and 9.3% (±10.5%), respectively. In contrast, the corresponding values of MM-FD PTV doses were 0.4% (±0.8%), 0.8% (±1.0%), 0.5% (±0.4%), and 0.8% (±0.8%), respectively. For the 4D dose accumulation study, the average (± standard deviation) absolute dose deviation (normalized by local doses) between the accumulated doses and the OSL measured doses was 3.3% (±2.7%). The average gamma index (3%/3 mm) between the accumulated doses and the radiochromic film measured doses was 94.5% (±2.5%). Conclusions: MM-FD estimated 4D-CBCT enables accurate on-board dose calculation and accumulation for lung radiation therapy. It can potentially be valuable for treatment quality assessment and adaptive radiation therapy.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Improved accuracy of quantitative parameter estimates in dynamic contrast-enhanced CT study with low temporal resolution

Purpose: A previously proposed method to reduce radiation dose to patient in dynamic contrast-enhanced (DCE) CT is enhanced by principal component analysis (PCA) filtering which improves the signal-to-noise ratio (SNR) of time-concentration curves in the DCE-CT study. The efficacy of the combined method to maintain the accuracy of kinetic parameter estimates at low temporal resolution is investigated with pixel-by-pixel kinetic analysis of DCE-CT data. Methods: The method is based on DCE-CT scanning performed with low temporal resolution to reduce the radiation dose to the patient. The arterial input function (AIF) with high temporal resolution can be generated with a coarsely sampled AIF through a previously published method of AIF estimation. To increase the SNR of time-concentration curves (tissue curves), first, a region-of-interest is segmented into squares composed of 3 × 3 pixels in size. Subsequently, the PCA filtering combined with a fraction of residual information criterion is applied to all the segmented squares for further improvement of their SNRs. The proposed method was applied to each DCE-CT data set of a cohort of 14 patients at varying levels of down-sampling. The kinetic analyses using the modified Tofts’ model and singular value decomposition method, then, were carried out for each of the down-sampling schemes between the intervals from 2 to 15 s. The results were compared with analyses done with the measured data in high temporal resolution (i.e., original scanning frequency) as the reference. Results: The patients’ AIFs were estimated to high accuracy based on the 11 orthonormal bases of arterial impulse responses established in the previous paper. In addition, noise in the images was effectively reduced by using five principal components of the tissue curves for filtering. Kinetic analyses using the proposed method showed superior results compared to those with down-sampling alone; they were able to maintain the accuracy in the quantitative histogram parameters of volume transfer constant [standard deviation (SD), 98th percentile, and range], rate constant (SD), blood volume fraction (mean, SD, 98th percentile, and range), and blood flow (mean, SD, median, 98th percentile, and range) for sampling intervals between 10 and 15 s. Conclusions: The proposed method of PCA filtering combined with the AIF estimation technique allows low frequency scanning for DCE-CT study to reduce patient radiation dose. The results indicate that the method is useful in pixel-by-pixel kinetic analysis of DCE-CT data for patients with cervical cancer.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2016

SU-G-JeP3-04: Estimating 4D CBCT from Prior Information and Extremely Limited Angle Projections Using Structural PCA and Weighted Free-Form Deformation

Purpose: To investigate the feasibility of using structure-based principal component analysis (PCA) motion-modeling and weighted free-form deformation to estimate on-board 4D-CBCT using prior information and extremely limited angle projections for potential 4D target verification of lung radiotherapy. Methods: A technique for lung 4D-CBCT reconstruction has been previously developed using a deformation field map (DFM)-based strategy. In the previous method, each phase of the 4D-CBCT was generated by deforming a prior CT volume. The DFM was solved by a motion-model extracted by global PCA and a free-form deformation (GMM-FD) technique, using data fidelity constraint and the deformation energy minimization. In this study, a new structural-PCA method was developed to build a structural motion-model (SMM) by accounting for potential relative motion pattern changes between different anatomical structures from simulation to treatment. The motion model extracted from planning 4DCT was divided into two structures: tumor and body excluding tumor, and the parameters of both structures were optimized together. Weighted free-form deformation (WFD) was employed afterwards to introduce flexibility in adjusting the weightings of different structures in the data fidelity constraint based on clinical interests. XCAT (computerized patient model) simulation with a 30 mm diameter lesion was simulated with various anatomical and respirational changes from planning 4D-CT to onboard volume. The estimation accuracy was evaluated by the Volume-Percent-Difference (VPD)/Center-of-Mass-Shift (COMS) between lesions in the estimated and “ground-truth” on board 4D-CBCT. Results: Among 6 different XCAT scenarios corresponding to respirational and anatomical changes from planning CT to on-board using single 30° on-board projections, the VPD/COMS for SMM-WFD was reduced to 10.64±3.04%/1.20±0.45mm from 21.72±9.24%/1.80±0.53mm for GMM-FD. Using 15° orthogonal projections, the VPD/COMS was further reduced to 1.91±0.86%/0.31±0.42mm based on SMM-WFD. Conclusion: Compared to GMM-FD technique, the SMM-WFD technique can substantially improve the 4D-CBCT estimation accuracy using extremely small scan angles to provide ultra-fast 4D verification. This work was supported by the National Institutes of Health under Grant No. R01-CA184173 and a research grant from Varian Medical Systems.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

TU-FG-BRB-03: Basis Vector Model Based Method for Proton Stopping Power Estimation From Experimental Dual Energy CT Data

Purpose: This work aims at reducing the uncertainty in proton stopping power (SP) estimation by a novel combination of a linear, separable basis vector model (BVM) for stopping power calculation (Med Phys 43:600) and a statistical, model-based dual-energy CT (DECT) image reconstruction algorithm (TMI 35:685). The method was applied to experimental data. Methods: BVM assumes the photon attenuation coefficients, electron densities, and mean excitation energies (I-values) of unknown materials can be approximated by a combination of the corresponding quantities of two reference materials. The DECT projection data for a phantom with 5 different known materials was collected on a Philips Brilliance scanner using two scans at 90 kVp and 140 kVp. The line integral alternating minimization (LIAM) algorithm was used to recover the two BVM coefficient images using the measured source spectra. The proton stopping powers are then estimated from the Bethe-Bloch equation using electron densities and I-values derived from the BVM coefficients. The proton stopping powers and proton ranges for the phantom materials estimated via our BVM based DECT method are compared to ICRU reference values and a post-processing DECT analysis (Yang PMB 55:1343) applied to vendorreconstructed images using the Torikoshi parametric fit model (tPFM). Results: For the phantom materials, the average stopping power estimations for 175 MeV protons derived from our method are within 1% of the ICRU reference values (except for Teflon with a 1.48% error), with an average standard deviation of 0.46% over pixels. The resultant proton ranges agree with the reference values within 2 mm. Conclusion: Our principled DECT iterative reconstruction algorithm, incorporating optimal beam hardening and scatter corrections, in conjunction with a simple linear BVM model, achieves more accurate and robust proton stopping power maps than the post-processing, nonlinear tPFM based DECT analysis applied to conventional reconstructions of low and high energy scans. Funding Support: NIH R01CA 75371; NCI grant R01 CA 149305.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

TH-AB-202-10: Quantifying the Accuracy and Precision of Six Degree-Of-Freedom Motion Estimation for Use in Real-Time Tumor Motion Monitoring During Radiotherapy

Purpose: Kilovoltage intrafraction monitoring (KIM) scheme has been successfully used to simultaneously monitor 3D tumor motion during radiotherapy. Recently, an iterative closest point (ICP) algorithm was implemented in KIM to also measure rotations about three axes, enabling real-time tracking of tumor motion in six degrees-of-freedom (DoF). This study aims to evaluate the accuracy of the six DoF motion estimates of KIM by comparing it with the corresponding motion (i) measured by the Calypso; and (ii) derived from kV/MV triangulation. Methods: (i) Various motions (static and dynamic) were applied to a CIRS phantom with three embedded electromagnetic transponders (Calypso Medical) using a 5D motion platform (HexaMotion) and a rotating treatment couch while both KIM and Calypso were used to concurrently track the phantom motion in six DoF. (ii) KIM was also used to retrospectively estimate six DoF motion from continuous sets of kV projections of a prostate, implanted with three gold fiducial markers (2 patients with 80 fractions in total), acquired during the treatment. Corresponding motion was obtained from kV/MV triangulation using a closed form least squares method based on three markers’ positions. Only the frames where all three markers were present were used in the analysis. The mean differences between the corresponding motion estimates were calculated for each DoF. Results: Experimental results showed that the mean of absolute differences in six DoF phantom motion measured by Calypso and KIM were within 1.1° and 0.7 mm. kV/MV triangulation derived six DoF prostate tumor better agreed with KIM estimated motion with the mean (s.d.) difference of up to 0.2° (1.36°) and 0.2 (0.25) mm for rotation and translation, respectively. Conclusion: These results suggest that KIM can provide an accurate six DoF intrafraction tumor during radiotherapy.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

A method for estimating the amplitude response of smartphone built-in microphone sensors below 4 kHz

A method for estimating the amplitude response of built-in smartphone microphone sensors is pre- sented. The method is intended to be accessible to the general public, and comparison calibration measurements are performed in a non-isolated environment using conventional consumer products. A double reference sensor scheme is set up, consisting of a MB3 digital microbarometer (reference over the 0.5–2 Hz octave bands) and the iPrecisionMic smartphone microphone (reference above the 2 Hz octave band). The amplitude response of the iPrecisionMic sensor is first evaluated over the 1–2000 Hz octave bands. The amplitude response of three Samsung Galaxy S8 built-in smart- phone microphone sensors is then measured over the 0.5–2000 Hz octave bands. The Redvox Infrasound Recorder application (app) for Android is used to measure acoustic signals with the built-in smartphone microphone sensors. Amplitude response models in terms of digital gain are estimated for the test sensors based on the results. Last, self-noise levels for the iPrecisionMic and Samsung Galaxy S8 microphones are estimated and compared to infrasound ambient noise models. Results show an experimental capability for estimating the amplitude response of built-in smartphone microphone sensors in a non-isolated environment with conventional consumer products.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Fast estimation of the look-elsewhere effect using Gaussian random fields

Abstract We discuss the use of Gaussian random fields to estimate the look-elsewhere effect correction. We show that Gaussian random fields can be used to model the null-hypothesis significance maps from a large set of statistical problems commonly encountered in physics, such as template matching and likelihood ratio tests. Some specific examples are searches for dark matter using pixel arrays, searches for astronomical transients, and searches for fast-radio bursts. Gaussian random fields can be sampled efficiently in the frequency domain, and the excursion probability can be fitted with these samples to extend any estimation of the look-elsewhere effect to lower p values. In addition, in cases where the Gaussian random field is stationary and the parameter space is Euclidean, the look-elsewhere effect correction can be computed analytically. We demonstrate these methods using two example template matching problems. Finally, we apply these methods to estimate the trial factor of a $$4^3$$ 4 3 accelerometer array for the detection of dark matter tracks in the Windchime project. When a global significance of $$3\sigma $$ 3 σ is required, the estimated trial factor for such an accelerometer array is $$10^{14}$$ 10 14 for a one-second search, and $$10^{22}$$ 10 22 for a 1-year search.

Qin, Juehang (ORCID:0000000182288949)↗
DOE OSTI2022

Parameter Estimation for Electrode Degradation: Learning in the Face of Model-Experiment Discrepancies

Use of physics-based models to interpret battery degradation data over the course of cycling can provide deeper physical insight into the internal states of the system and how they evolve. We present a neural network trained on simulations generated by a previously published physics-based model for a lithium trivanadate (LVO) cathode to estimate parameters that evolve over the course of cycling. We focus on the robustness of the neural network through two case studies that probe different kinds of discrepancies between model and experiment: nonideal data and imperfect model. In the former, the experimental protocols do not meet the assumption made in the training data generated by the physics-based model, while in the latter, the physics-based model fails to describe all of the measured cathode behavior even under ideal conditions. When there is total model-experiment agreement, a neural network estimates parameters with improved accuracy compared to a maximum likelihood analysis using the same set of simulations. However, in both types of model-experiment discrepancy, the neural network returned biased parameter estimates. We introduce a data augmentation procedure into the neural network training to mitigate these effects and improve robustness, and employ it to estimate parameters for a cycling LVO cathode.

Mayilvahanan, Karthik S. (ORCID:0000000316282332)↗
DOE OSTI2019

Plant density and enhanced plant vigor estimation for high-resolution images v1

The package contains algorithms for the estimation of sprout/plant density and the corresponding enhanced plant vigor from remotely sensed (RS) images. These algorithms aim to improve the plant characterization and monitoring in the early season when the soil component is significant compared to the plant spatial coverage. In such a scenario, the identification of sprouts (or plants) and the estimation of plant vegetation indexes can be performed only using UAV-acquired images. Additionally, because of the extremely high resolution, gridding becomes necessary to improve visualization and provide more informative maps. However, to capture the real range of values of the VIs, it is important to avoid the inclusion of those pixels belonging to the soil component. The sprout/plant density estimation algorithm takes in input a classification map and uses the vegetation class to estimates the plant density within a user-defined grid using a floating window. Similarly, the enhanced plant vigor algorithm takes in input the vegetation index and the classification map. The enhanced vegetation index is computed for each pixel as the average value among those pixels that belong to the vegetation class within a floating window. The software is developed for the MATLAB environment.

Falco, Nicola↗
DOE OSTI2019

Ubiquitous Traffic Volume Estimation System

The Ubiquitous Traffic Volume Estimation System uses Machine Learning (ML) algorithms to provide accurate estimates of number vehicles on the roadway (ubiquitous traffic volume) based on inputs such as commercial probe traffic data that includes average vehicle speed and probe counts, roadway characteristics, weather, time of day, and day of week, and reference volume counts from a limited number of automatic traffic recorder stations. The Ubiquitous Traffic Volume Estimation System estimates traffic volumes 24 hours a day, 7 days a week, and 365 days a year on all major corridors and freeways in Denver metropolitan area and is being expanded to the whole state of Colorado. The methodology and code developed in this effort can be easily customized to other states and cities where similar data is available.

Young, Stanley↗
DOE OSTI2022

Master State Distributed Estimator (masde)

The MSE technology provides a distributed state estimation scheme for power utilities by making it a real time dynamic system, versus the static snapshot method used today. This will allow utilities to verify power grid readings and identify false data on the communication network. The prevailing method of estimation takes all the data from the system into a single load flow equation at the utilities command center. This becomes a large algorithm that is very time consuming to solve, providing the engineers only snap shots of the system. The MFD distributes an algorithm to devises that are already installed at various locations on the power grid. This allows for much faster computer times because the algorithms contain magnitudes less data. When each distributed estimator completes its calculation, it sends the results back to the master device to check against all other distributed estimators.

Reen, DylanW.↗
DOE OSTI2014

Reservoir Temperature Estimator

The Reservoir Temperature Estimator (RTEst) is a program that can be used to estimate deep geothermal reservoir temperature and chemical parameters such as CO2 fugacity based on the water chemistry of shallower, cooler reservoir fluids. This code uses the plugin features provided in The Geochemist's Workbench (Bethke and Yeakel, 2011) and interfaces with the model-independent parameter estimation code Pest (Doherty, 2005) to provide for optimization of the estimated parameters based on the minimization of the weighted sum of squares of a set of saturation indexes from a user-provided mineral assemblage.

Palmer, CarlD.↗
DOE OSTI2014

Ensemble-Based Parameter Estimation in a Coupled GCM Using the Adaptive Spatial Average Method

Ensemble-based parameter estimation for a climate model is emerging as an important topic in climate research. And for a complex system such as a coupled ocean–atmosphere general circulation model, the sensitivity and response of a model variable to a model parameter could vary spatially and temporally. An adaptive spatial average (ASA) algorithm is proposed to increase the efficiency of parameter estimation. Refined from a previous spatial average method, the ASA uses the ensemble spread as the criterion for selecting “good” values from the spatially varying posterior estimated parameter values; these good values are then averaged to give the final global uniform posterior parameter. In comparison with existing methods, the ASA parameter estimation has a superior performance: faster convergence and enhanced signal-to-noise ratio.

54 ENVIRONMENTAL SCIENCES↗