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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Control of ion content and nitrogen species using a mixed chemistry plasma for GaN grown at extremely high growth rates >9 μm/h by plasma-assisted molecular beam epitaxy

Utilizing a modified nitrogen plasma source, plasma assisted molecular beam epitaxy (PAMBE) has been used to achieve higher growth rates in GaN. A higher conductance aperture plate, combined with higher nitrogen flow and added pumping capacity, resulted in dramatically increased growth rates up to 8.4 μm/h using 34 sccm of N{sub 2} while still maintaining acceptably low operating pressure. It was further discovered that argon could be added to the plasma gas to enhance growth rates up to 9.8 μm/h, which was achieved using 20 sccm of N{sub 2} and 7.7 sccm Ar flows at 600 W radio frequency power, for which the standard deviation of thickness was just 2% over a full 2 in. diameter wafer. A remote Langmuir style probe employing the flux gauge was used to indirectly measure the relative ion content in the plasma. The use of argon dilution at low plasma pressures resulted in a dramatic reduction of the plasma ion current by more than half, while high plasma pressures suppressed ion content regardless of plasma gas chemistry. Moreover, different trends are apparent for the molecular and atomic nitrogen species generated by varying pressure and nitrogen composition in the plasma. Argon dilution resulted in nearly an order of magnitude achievable growth rate range from 1 μm/h to nearly 10 μm/h. Even for films grown at more than 6 μm/h, the surface morphology remained smooth showing clear atomic steps with root mean square roughness less than 1 nm. Due to the low vapor pressure of Si, Ge was explored as an alternative n-type dopant for high growth rate applications. Electron concentrations from 2.2 × 10{sup 16} to 3.8 × 10{sup 19} cm{sup −3} were achieved in GaN using Ge doping, and unintentionally doped GaN films exhibited low background electron concentrations of just 1–2 × 10{sup 15} cm{sup −3}. The highest growth rates resulted in macroscopic surface features due to Ga cell spitting, which is an engineering challenge still to be addressed. Nonetheless, the dramatically enhanced growth rates demonstrate great promise for the future of III-nitride devices grown by PAMBE.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Special Nuclear Material Characterization Using Digital 3-D Position Sensitive CdZnTe Detectors and High Purity Germanium Spectrometers

Special nuclear material (SNM) monitoring often requires high resolution gamma-ray spectroscopy for material characterization. Portable systems and rapid deployment are also highly valued for some applications. Deployable gamma-ray imaging spectrometers using pixelated CdZnTe semiconductor detectors have become commercially available within the past three years to meet these requirements. CdZnTe systems have demonstrated room-temperature energy resolutions below 0.5% FWHM at 662 keV using single pixel events and below 0.7% FWHM at 662 keV using all events. The systems are able to go from storage to measurement in less than two minutes. Special nuclear materials were measured at the Y-12 National Security Complex and at the Device Assembly Facility at the Nevada National Security Site. The use of a CdZnTe system to measure uranium enrichment was demonstrated and uranium spectral features were compared to a commercially available high purity germanium (HPGe) spectrometer. The use of passive gamma ray spectroscopy techniques to estimate plutonium grade using CdZnTe detectors was demonstrated for the first time.

CdZnTe detectors, gamma-ray imaging, gamma-ray spe↗
DOE OSTI2013

Novel multimodality segmentation using level sets and Jensen-Rényi divergence

Purpose: Positron emission tomography (PET) is playing an increasing role in radiotherapy treatment planning. However, despite progress, robust algorithms for PET and multimodal image segmentation are still lacking, especially if the algorithm were extended to image-guided and adaptive radiotherapy (IGART). This work presents a novel multimodality segmentation algorithm using the Jensen-Rényi divergence (JRD) to evolve the geometric level set contour. The algorithm offers improved noise tolerance which is particularly applicable to segmentation of regions found in PET and cone-beam computed tomography. Methods: A steepest gradient ascent optimization method is used in conjunction with the JRD and a level set active contour to iteratively evolve a contour to partition an image based on statistical divergence of the intensity histograms. The algorithm is evaluated using PET scans of pharyngolaryngeal squamous cell carcinoma with the corresponding histological reference. The multimodality extension of the algorithm is evaluated using 22 PET/CT scans of patients with lung carcinoma and a physical phantom scanned under varying image quality conditions. Results: The average concordance index (CI) of the JRD segmentation of the PET images was 0.56 with an average classification error of 65%. The segmentation of the lung carcinoma images had a maximum diameter relative error of 63%, 19.5%, and 14.8% when using CT, PET, and combined PET/CT images, respectively. The estimated maximal diameters of the gross tumor volume (GTV) showed a high correlation with the macroscopically determined maximal diameters, with aR{sup 2} value of 0.85 and 0.88 using the PET and PET/CT images, respectively. Results from the physical phantom show that the JRD is more robust to image noise compared to mutual information and region growing. Conclusions: The JRD has shown improved noise tolerance compared to mutual information for the purpose of PET image segmentation. Presented is a flexible framework for multimodal image segmentation that can incorporate a large number of inputs efficiently for IGART.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

Realistic simulation of reduced-dose CT with noise modeling and sinogram synthesis using DICOM CT images

Purpose: Reducing the patient dose while maintaining the diagnostic image quality during CT exams is the subject of a growing number of studies, in which simulations of reduced-dose CT with patient data have been used as an effective technique when exploring the potential of various dose reduction techniques. Difficulties in accessing raw sinogram data, however, have restricted the use of this technique to a limited number of institutions. Here, we present a novel reduced-dose CT simulation technique which provides realistic low-dose images without the requirement of raw sinogram data. Methods: Two key characteristics of CT systems, the noise equivalent quanta (NEQ) and the algorithmic modulation transfer function (MTF), were measured for various combinations of object attenuation and tube currents by analyzing the noise power spectrum (NPS) of CT images obtained with a set of phantoms. Those measurements were used to develop a comprehensive CT noise model covering the reduced x-ray photon flux, object attenuation, system noise, and bow-tie filter, which was then employed to generate a simulated noise sinogram for the reduced-dose condition with the use of a synthetic sinogram generated from a reference CT image. The simulated noise sinogram was filtered with the algorithmic MTF and back-projected to create a noise CT image, which was then added to the reference CT image, finally providing a simulated reduced-dose CT image. The simulation performance was evaluated in terms of the degree of NPS similarity, the noise magnitude, the bow-tie filter effect, and the streak noise pattern at photon starvation sites with the set of phantom images. Results: The simulation results showed good agreement with actual low-dose CT images in terms of their visual appearance and in a quantitative evaluation test. The magnitude and shape of the NPS curves of the simulated low-dose images agreed well with those of real low-dose images, showing discrepancies of less than +/−3.2% in terms of the noise power at the peak height and +/−1.2% in terms of the spatial frequency at the peak height. The magnitudes of the noise measured for 12 different combinations the phantom size, tube current, and reconstruction kernel for the simulated and real low-dose images were very similar, with differences of 0.1 to 4.7%. Thep value for a statistical testing of the difference in the noise magnitude ranged from 0.99 to 0.11, showing that there was no difference statistically between the noise magnitudes of the real and simulated low-dose images using our method. The strength and pattern of the streak noise in an anthropomorphic phantom was also consistent with expectations. Conclusions: A novel reduced-dose CT simulation technique was developed which uses only CT images while not requiring raw sinogram data. Our method can provide realistic simulation results under reduced-dose conditions both in terms of the noise magnitude and the textual appearance. This technique has the potential to promote clinical research for patient dose reductions.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

Validating and improving CT ventilation imaging by correlating with ventilation 4D-PET/CT using {sup 68}Ga-labeled nanoparticles

Purpose: CT ventilation imaging is a novel functional lung imaging modality based on deformable image registration. The authors present the first validation study of CT ventilation using positron emission tomography with{sup 68}Ga-labeled nanoparticles (PET-Galligas). The authors quantify this agreement for different CT ventilation metrics and PET reconstruction parameters. Methods: PET-Galligas ventilation scans were acquired for 12 lung cancer patients using a four-dimensional (4D) PET/CT scanner. CT ventilation images were then produced by applying B-spline deformable image registration between the respiratory correlated phases of the 4D-CT. The authors test four ventilation metrics, two existing and two modified. The two existing metrics model mechanical ventilation (alveolar air-flow) based on Hounsfield unit (HU) change (V{sub HU}) or Jacobian determinant of deformation (V{sub Jac}). The two modified metrics incorporate a voxel-wise tissue-density scaling (ρV{sub HU} and ρV{sub Jac}) and were hypothesized to better model the physiological ventilation. In order to assess the impact of PET image quality, comparisons were performed using both standard and respiratory-gated PET images with the former exhibiting better signal. Different median filtering kernels (σ{sub m} = 0 or 3 mm) were also applied to all images. As in previous studies, similarity metrics included the Spearman correlation coefficient r within the segmented lung volumes, and Dice coefficient d{sub 20} for the (0 − 20)th functional percentile volumes. Results: The best agreement between CT and PET ventilation was obtained comparing standard PET images to the density-scaled HU metric (ρV{sub HU}) with σ{sub m} = 3 mm. This leads to correlation values in the ranges 0.22 ⩽ r ⩽ 0.76 and 0.38 ⩽ d{sub 20} ⩽ 0.68, with r{sup ¯}=0.42±0.16 and d{sup ¯}{sub 20}=0.52±0.09 averaged over the 12 patients. Compared to Jacobian-based metrics, HU-based metrics lead to statistically significant improvements in r{sup ¯} and d{sup ¯}{sub 20} (p < 0.05), with density scaled metrics also showing higher r{sup ¯} than for unscaled versions (p < 0.02). r{sup ¯} and d{sup ¯}{sub 20} were also sensitive to image quality, with statistically significant improvements using standard (as opposed to gated) PET images and with application of median filtering. Conclusions: The use of modified CT ventilation metrics, in conjunction with PET-Galligas and careful application of image filtering has resulted in improved correlation compared to earlier studies using nuclear medicine ventilation. However, CT ventilation and PET-Galligas do not always provide the same functional information. The authors have demonstrated that the agreement can improve for CT ventilation metrics incorporating a tissue density scaling, and also with increasing PET image quality. CT ventilation imaging has clear potential for imaging regional air volume change in the lung, and further development is warranted.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

Determination of prescription dose for Cs-131 permanent implants using the BED formalism including resensitization correction

Purpose: The current widely used biological equivalent dose (BED) formalism for permanent implants is based on the linear-quadratic model that includes cell repair and repopulation but not resensitization (redistribution and reoxygenation). The authors propose a BED formalism that includes all the four biological effects (4Rs), and the authors propose how it can be used to calculate appropriate prescription doses for permanent implants with Cs-131. Methods: A resensitization correction was added to the BED calculation for permanent implants to account for 4Rs. Using the same BED, the prescription doses with Au-198, I-125, and Pd-103 were converted to the isoeffective Cs-131 prescription doses. The conversion factor F, ratio of the Cs-131 dose to the equivalent dose with the other reference isotope (F{sub r}: with resensitization, F{sub n}: without resensitization), was thus derived and used for actual prescription. Different values of biological parameters such as α, β, and relative biological effectiveness for different types of tumors were used for the calculation. Results: Prescription doses with I-125, Pd-103, and Au-198 ranging from 10 to 160 Gy were converted into prescription doses with Cs-131. The difference in dose conversion factors with (F{sub r}) and without (F{sub n}) resensitization was significant but varied with different isotopes and different types of tumors. The conversion factors also varied with different doses. For I-125, the average values of F{sub r}/F{sub n} were 0.51/0.46, for fast growing tumors, and 0.88/0.77 for slow growing tumors. For Pd-103, the average values of F{sub r}/F{sub n} were 1.25/1.15 for fast growing tumors, and 1.28/1.22 for slow growing tumors. For Au-198, the average values of F{sub r}/F{sub n} were 1.08/1.25 for fast growing tumors, and 1.00/1.06 for slow growing tumors. Using the biological parameters for the HeLa/C4-I cells, the averaged value of F{sub r} was 1.07/1.11 (rounded to 1.1), and the averaged value of F{sub n} was 1.75/1.18. F{sub r} of 1.1 has been applied to gynecological cancer implants with expected acute reactions and outcomes as expected based on extensive experience with permanent implants. The calculation also gave the average Cs-131 dose of 126 Gy converted from the I-125 dose of 144 Gy for prostate implants. Conclusions: Inclusion of an allowance for resensitization led to significant dose corrections for Cs-131 permanent implants, and should be applied to prescription dose calculation. The adjustment of the Cs-131 prescription doses with resensitization correction for gynecological permanent implants was consistent with clinical experience and observations. However, the Cs-131 prescription doses converted from other implant doses can be further adjusted based on new experimental results, clinical observations, and clinical outcomes.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2020

Calculating Average Hot Water Mixes of Residential Plumbing Fittings Using the ANSI 301-2019 Hot Water Draw Model and National Residential Data to Estimate Hot Water Use in Showerheads and Lavatory Faucets

Available studies of hot water use percentages may not necessarily be generalized to a national level given regional differences, varying methodological approaches, and limited sample sizes. While some publicly available usage data, reports, and surveys estimate actual household usage, a lack of water use data specific to end uses make more precise savings calculations difficult. Additionally, most hot water draw models tend to focus on overall household use and may not readily estimate lavatory fixture use. However, reviewing more recent studies and standards enables the U.S. Environmental Protection Agency’s WaterSense program to update its estimates for hot water use and consumers’ corresponding energy and monetary savings to better reflect realworld conditions. This report specifically focuses on improving hot water use and savings estimates of lavatory faucets and showerheads. To estimate the hot water use of lavatory faucets and showerheads, we employed the 2015 Residential Energy Consumption Surveys (RECS) microdata alongside the ANSI 301-2019 Hot Water Draw Model. These estimates account for regional differences in hot water use, including regional cold water inlet temperatures. As a result, the refinements presented in this report are more robust, more recent, and better describe the geographic variation than previous inputs used by the WaterSense program. In addition, the approach described in this paper can be updated over time or tailored to regionally specific needs given available inputs. We conclude that hot water percentages for showers and faucets calculated using publicly available national data are close to the percentages found by regional studies and are consistent with household-level models of water use.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2019

Comparison of Wind Farm Layout Optimization Results Using a Simple Wake Model and Gradient-Based Optimization to Large-Eddy Simulations: Preprint

Comparison of wind farm layout optimization results with simulations or wind tunnel tests is important because the models used during optimization use simplifying assumptions that can alter the design space. Some of the characteristics of the simple models may negatively influence the resulting layouts. In this paper we perform wind farm layout optimization and compare the resulting improvements to large eddy simulation (LES) results. We begin by describing the models used, including changes specific for use with gradient-based optimization. We then compare our version of the models with the original versions and large eddy simulation LES) data from previous publications. Using the models described, we performed gradient-based wind farm layout optimization, using exact gradients, and compare the results to LES simulations. The models predicted an improvement in annual energy production (AEP) of 7.4%, while the LES reported an AEP improvement of 9:9%. We conclude that the improvements found by optimizing with the simple models are not just an artifact of the models, but are real improvements.

17 WIND ENERGY↗
DOE OSTI2020

Global rules for translating land-use change (LUH2) to land-cover change for CMIP6 using GLM2

Anthropogenic land-use and land-cover change activities play a critical role in Earth system dynamics through significant alterations to biogeophysical and biogeochemical properties at local to global scales. To quantify the magnitude of these impacts, climate models need consistent land-cover change time series at a global scale, based on land-use information from observations or dedicated land-use change models. However, a specific land-use change cannot be unambiguously mapped to a specific land-cover change. Here, nine translation rules are evaluated based on assumptions about the way land-use change could potentially impact land cover. Utilizing the Global Land-use Model 2 (GLM2), the model underlying the latest Land-Use Harmonization dataset (LUH2), the land-cover dynamics resulting from land-use change were simulated based on multiple alternative translation rules from 850 to 2015 globally. For each rule, the resulting forest cover, carbon density and carbon emissions were compared with independent estimates from remote sensing observations, U.N. Food and Agricultural Organization reports, and other studies. The translation rule previously suggested by the authors of the HYDE 3.2 dataset, that underlies LUH2, is consistent with the results of our examinations at global, country and grid scales. This rule recommends that for CMIP6 simulations, models should (1) completely clear vegetation in land-use changes from primary and secondary land (including both forested and non-forested) to cropland, urban land and managed pasture; (2) completely clear vegetation in land-use changes from primary forest and/or secondary forest to rangeland; (3) keep vegetation inland-use changes from primary non-forest and/or secondary non-forest to rangeland. Our analysis shows that this rule is one of three (out of nine)rules that produce comparable estimates of forest cover, vegetation carbon and emissions to independent estimates and also mitigate the anomalously high carbon emissions from land-use change observed in previous studies in the 1950s. According to the three translation rules, contemporary global forest area is estimated to be 37.42×106 km2, within the range derived from remote sensing products. Likewise, the estimated carbon stock is in close agreement with reference biomass datasets, particularly over regions with more than 50 % forest cover

58 GEOSCIENCES↗
DOE OSTI2019

Modeling Building Use and Population Distribution Opportunity Using Open Geosocial Data in Urban Areas

Knowing where people are and knowing how the land in urban areas is being used is critical for assessing human mobility patterns, monitoring population health, planning for transportation services, and responding to natural disasters and emergency situations. While geophysical phenomena like land cover are more easily observed through remote sensing, social phenomena like how a city block or building is being used by the population is generally unobservable through standard remote sensing practices. Current methods and land use data by their nature are also difficult to scale to national or global levels. While land use data are often available in large cities, there are abundant data gaps globally. Furthermore, land use data can often appear relatively coarse in its spatial and semantic resolution (i.e. 1km grid cells rather than building level, and "commercial" rather than "coffee shop"). In particular, there is a need to harvest scalable data and develop methods to create global land use maps. To this end, in this work we combine building footprints and Points of Interest (POI) to estimate land use at the building level, including its mixed-use intensity. Next, we propose a method for defining semantic temporal zones referring to Morning, Day, Evening, and Night times unique to a region, based on the cumulative hourly change in the POIs' hours of operation. We then use these POIs' hours of operation to estimate non-residential population distribution opportunity and land use change over a 24-hour period. We validate our results through manual checks of randomly sampled individual buildings using multiple sources. Finally, we discuss the impact of our results on identifying population distribution opportunity and the reliability of estimating building use.

Sparks, Kevin↗
DOE OSTI2016

Impact of Using Audit Data to Improve the Evidence-Based Use of Single-Fraction Radiation Therapy for Bone Metastases in British Columbia

Purpose: To assess the impact of a population-based intervention to increase the consistency and use of single-fraction radiation therapy (SFRT) for bone metastases. Methods and Materials: In 2012, an audit of radiation therapy prescriptions for bone metastases in British Columbia identified significant interphysician and -center (26%-73%) variation in the use of SFRT. Anonymous physician-level and identifiable regional cancer center SFRT use data were presented to all radiation oncologists, together with published guidelines, meta-analyses, and recommendations from practice leaders. The use of SFRT for bone metastases from 2007 through 2011 was compared with use of SFRT in 2013, to assess the impact of the audit and educational intervention. Multilevel logistic regression was used to assess the relationship between the usage of SFRT and the timing of the radiation while controlling for potentially confounding variables. Physician and center were included as group effects to account for the clustered structure of the data. Results: A total of 16,898 courses of RT were delivered from 2007 through 2011, and 3200 courses were delivered in 2013. The rates of SFRT use in 2007, 2008, 2009, 2010, 2011, and 2013 were 50.5%, 50.9%, 48.3%, 48.5%, 48.0%, and 59.7%, respectively (P<.001). Use of SFRT increased in each of 5 regional centers: A: 26% to 32%; B: 36% to 56%; C: 39% to 57%; D: 49% to 56%; and E: 73% to 85.0%. Use of SFRT was more consistent; 3 of 5 centers used SFRT for 56% to 57% of bone metastases RT courses. The regression analysis showed strong evidence that the usage of SFRT increased after the 2012 intervention (odds ratio 2.27, 95% confidence interval 2.06-2.50, P<.0001). Conclusion: Assessed on a population basis, an audit-based intervention increased utilization of SFRT for bone metastases. The intervention reversed a trend to decreasing SFRT use, reduced costs, and improved patient convenience. This suggests that dissemination of programmatic quality indicators in oncology can lead to increased utilization of evidence-based practice.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

Using Field-Metered Data to Quantify Annual Energy Use of Portable Air Conditioners

As many regions of the United States experience rising temperatures, consumers have come to rely increasingly on cooling appliances (including portable air conditioners) to provide a comfortable indoor temperature. Home occupants sometimes use a portable air conditioner (PAC) to maintain a desired indoor temperature in a single room or enclosed space. Although PACs in residential use are few compared to centrally installed and room air conditioning (AC) units, the past few years have witnessed an increase of PACs use throughout the United States. There is, however, little information and few research projects focused on the energy consumption and performance of PACs, particularly studies that collect information from field applications of PACs. The operation and energy consumption of PACs may differ among geographic locations and households, because of variations in cooling load, frequency, duration of use, and other user-selected settings. In addition, the performance of building envelope (thermal mass and air leakage) as well as inter-zonal mixing within the building would substantially influence the ability to control and maintain desirable indoor thermal conditions. Lawrence Berkeley National Laboratory (LBNL) conducted an initial field-metering study aimed at increasing the knowledge and data related to PAC operation and energy consumption in the United States. LBNL performed its field-metering study from mid-April to late October 2014. The study, which monitored 19 sites in the Northeastern United States (4 in upstate New York and 15 near Philadelphia), collected real-time data on PAC energy consumption along with information regarding housing characteristics, consumer behavior, and environmental conditions that were expected to affect PAC performance. Given the limited number of test sites, this study was not intended to be statistically representative of PAC users in the United States but rather to understand the system response to the cooling demand and to some extent, the operating hours of the studied units. Specifically, the primary objectives of the field-metering study were to (1) expand knowledge of the installation, energy consumption profiles, consumer patterns of use, and environmental parameters related to PAC use; (2) develop distributions of hours of PAC operation for three operating modes: standby, 1 fan-only, and cooling; and (3) describe how individual consumers’ selection of PAC capacity, the area of the space to be cooled, the temperature set point, and environmental conditions affect energy use. Beginning to understand the energy consumption of PACs operating in American homes and commercial settings will help develop a more accurate energy use profile that characterizes relevant variables. This report on LBNL’s field-metering study of PAC energy use describes: a general definition of a PAC and how it operates (section 2); current practices and sources of data for estimating PAC energy use (section 3); the process LBNL used to select field-metering sites, along with characteristics of the sites and the PACs studied (section 4); data collection methods and instrumentation (section 5); analysis methods (section 6); results and discussion (section 7); and conclusions (section 8).

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2017

Multivariate analysis of gamma spectra to characterize used nuclear fuel

Abstract—The Multi-Isotope Process (MIP) Monitor provides an efficient approach to monitoring the process conditions in used nuclear fuel reprocessing facilities to support process verification and validation. The MIP Monitor applies multivariate analysis to gamma spectroscopy of reprocessing streams in order to detect small changes in the gamma spectrum, which may indicate changes in process conditions. This research extends the MIP Monitor by characterizing a used fuel sample after initial dissolution according to the type of reactor of origin (pressurized or boiling water reactor), initial enrichment, burn up, and cooling time. Simulated gamma spectra were used to develop and test three fuel characterization algorithms. The classification and estimation models employed are based on the partial least squares regression (PLS) algorithm. A PLS discriminate analysis model was developed which perfectly classified reactor type. Locally weighted PLS models were fitted on-the-fly to estimate continuous fuel characteristics. Burn up was predicted within 0.1% root mean squared percent error (RMSPE) and both cooling time and initial enrichment within approximately 2% RMSPE. This automated fuel characterization can be used to independently verify operator declarations of used fuel characteristics and inform the MIP Monitor anomaly detection routines at later stages of the fuel reprocessing stream to improve sensitivity to changes in operational parameters and material diversions.

Multivariate Analysis for Characterization of Used↗
DOE OSTI2019

Residential Electricity End-use Disaggregation Using Whole Home Disaggregation Technologies

To understand whether a novel, cost effective approach can support a national program that reports on residential energy consumption, a two-phase research study was undertaken by a federal statistical agency and a national laboratory to evaluate the latest load disaggregation technologies. This paper will present the results of the first phase of the study, which explored whether load disaggregation technologies have the potential to inform end-use estimates for a national survey on residential energy consumption Historically, residential submetering projects have been implemented using a combination of plug-load and circuit-level monitoring. This approach is expensive, requires extensive onsite installation, and faces limitations in measuring smaller and portable end uses. In recent years, innovative computing technologies have entered the market that use algorithms to analyze electric signals and disaggregate household end uses. If proven sufficiently accurate and reliable, these technologies would simplify the identification and measurement of distinct end uses and improve end-use consumption estimation. The first phase of the study was planned as an initial assessment of the three load disaggregation products with the objective of determining the strongest candidates for further evaluation in the second phase. The load disaggregation products were evaluated based on their ability to measure total electricity for the home, detect end uses, measure electricity consumption of end uses, and perform reliably without burdening participants. If demonstrated as effective, obtaining end-use energy consumption data through load disaggregation technology would provide an invaluable check for the national survey at a minimum, and could potentially offer insight for enhancements.

Disaggregation accuracy↗
DOE OSTI2021

Evaluating Probability of Containment Effectiveness at a GCS Sites using integrated assessment modeling approach with Bayesian decision Networks

Improved scientific and engineering understanding of the behavior of geologic CO2 storage together with established regulatory framework and incentive structures raise the prospects for accelerated, large-scale deployment of this greenhouse gas emissions reduction approach. Incentive structures call for the establishment of appropriate verification and accounting approaches to support claims of the integrity of a geologic storage complex and to justify taking credit for long-term storage. In this study, we present a framework for assessing the probability of containment effectiveness over the lifetime of a geologic carbon storage site (e.g., after 70 years of injection and post-injection site performance) using forward stochastic model realizations based on site characterization data and using a monitoring-informed Bayesian network based on hypothetical detectability from surface seismic surveys over the site injection and post-injection phases. The National Risk Assessment Partnership’s open-source Integrated Assessment Model (NRAP-Open-IAM) was utilized to develop an ensemble of 10,000 a priori stochastic forecasts of CO2 containment. Those simulations were used to train the Bayesian network model to estimate the prior probabilities of the CO2 leakage mass into overlying, monitorable aquifers considering the uncertainties in the reservoir properties, permeability of potentially leaky wells and the overlying aquifers. The conditional probabilities in the Bayesian network were either learned from the NRAP-Open-IAM simulations or derived from the predefined detection thresholds for the monitoring method. Observations obtained from monitoring, over time during the site operation phases were then used to generate updated posterior probabilities of containment (and any loss from containment) in the Bayesian network by propagating the prior probabilities through the conditional probabilities. We demonstrate how to construct and use the Bayesian network for verifying the long-term storage complex effectiveness informed by monitoring based on the NRAP-Open-IAM simulations previously developed for the FutureGen 2.0 site. This approach may have relevance for stake holders to demonstrate secure geologic storage, provide a defensible, probabilistic approach to claim credit for geologic storage, and to estimate the likelihood that any fraction of the claimed credit may need to be refunded to the creditor based on available monitoring information.

Bayesian network, Risk assessment, Monitoring, car↗
DOE OSTI2018

Measurements of b -jet tagging efficiency with the ATLAS detector using $t\overline{t}$ events at $\sqrt{s}=13$ TeV

The efficiency to identify jets containing b-hadrons (b-jets) is measured using a high purity sample of dileptonic top quark-antiquark pairs ($t\bar{t}$) selected from the 36.1 fb -1 of data collected by the ATLAS detector in 2015 and 2016 from proton-proton collisions produced by the Large Hadron Collider at a centre-of-mass energy $\sqrt{s}=13$ TeV. Two methods are used to extract the efficiency from $t\bar{t}$ events, a combinatorial likelihood approach and a tag-and-probe method. A boosted decision tree, not using b-tagging information, is used to select events in which two b-jets are present, which reduces the dominant uncertainty in the modelling of the flavour of the jets. The efficiency is extracted for jets in a transverse momentum range from 20 to 300 GeV, with data-to-simulation scale factors calculated by comparing the efficiency measured using collision data to that predicted by the simulation. In conclusion, the two methods give compatible results, and achieve a similar level of precision, measuring data-to-simulation scale factors close to unity with uncertainties ranging from 2% to 12% depending on the jet transverse momentum.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Investigations of Polymethacrylate Tribochemical Films Using X-Ray Spectroscopy and Optical Profilometry

This study investigates the elemental composition and surface morphology of solid tribochemical films formed on steel surfaces. The reversible addition-fragmentation chain transfer (RAFT) method was used to synthesize nine different metal-free polymers, which were blended into commercial base oils. The polymers were either homopolymers of dodecyl methacrylate and ethylhexyl methacrylate or were co-polymers of these monomers with six polar monomers. After tribological testing at 100 degrees C using the ball-on-flat geometry, the resulting tribochemical films were imaged using scanning electron microscopy (SEM) and optical microscopy. The resulting tribochemical films have thicknesses around 50-100 nm. Two of the films corresponding to small (P1-imidazole-containing copolymer) and large (P3-less polar homopolymer) wear were cross-sectioned using focused ion beam (FIB) and analyzed for elemental composition using energy-dispersive X-Ray (EDX) mapping. Oxygen and nitrogen enrichment was observed, consistent with the relative chemical composition of the precursor polymers. Transmission electron microscopy (TEM) evidence suggests that at the worn surface, some organic elements penetrate or are mixed into the steel substrate giving an interlocking appearance. The two samples examined with TEM showed that P1 tribofilm is diffused or mixed with the steel substrate more so than P3, suggesting a stronger affinity and contact during tribofilm formation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗