Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Using”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

A Bayesian approach to calibrating hydrogen flame kinetics using many experiments and parameters

First-principles Markov Chain Monte Carlo sampling is used to investigate uncertainty quantification and uncertainty propagation in parameters describing hydrogen kinetics. Specifically, we sample the posterior distribution for thirty-one parameters focusing on the H 2 O 2 and HO 2 reactions resulting from conditioning on ninety-one experiments. Established literature values are used for the remaining parameters in the mechanism as well as other thermodynamic and transport data needed to specify fluid properties. The samples are computed using an affine invariant sampler starting with broad, noninformative priors. Autocorrelation analysis shows that O(1M) samples are sufficient to obtain a reasonable sampling of the posterior. The resulting distribution identifies strong positive and negative correlations and several non-Gaussian characteristics. Using samples drawn from the posterior, we investigate the impact of parameter uncertainty on the prediction of two more complex flames: a 2D premixed flame kernel and the ignition of a hydrogen jet issuing into a heated chamber. The former represents a combustion regime similar to the target experiments used to calibrate the mechanism and the latter represents a different combustion regime. For the premixed flame, the net amount of product after a given time interval has a standard deviation of less than 2% whereas the standard deviation of the ignition time for the jet is more than 10%. The samples used for these studies are posted online. These results indicate the degree to which parameters consistent with the target experiments constrain predicted behavior in different combustion regimes. Finally, this process provides a framework for both identifying reactions for further study from candidate mechanisms as well as combining uncertainty quantification and propagation to, ultimately, tie uncertainty in laboratory flame experiments to uncertainty in end-use numerical predictions of more complicated scenarios.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Electrical Fault Detection, Power Quality, Distributed Energy Resource Use Cases, and Cyber Event Applications with the Cyber Grid Guard System Using Distributed Ledger Technology

Electrical utilities continue to deploy more intelligent electronic devices (IEDs) inside and outside electrical substation and are associated with distributed energy resources (DERs). The integrity and confidentiality of data from IEDs is crucial, and distributed ledger technology (DLT) could improve the resilience of microgrids by helping to make these data more secure. The most popular applications using blockchain technology for electrical utilities is in the field is based on energy trading. However, the dynamism of the penetration of customer owned DERs and the deployment of sensors with IEDs have led to the identification of new applications using DLT that are focused on other areas, such as monitoring, operation and management of the grid and its assets. In addition, the majority of studies on electrical grid applications with blockchain were validated with software simulations. Although general monitoring of power systems for using DLT could be evaluated in operational electric grids, other DLT research applications such as defense against cyber-attacks and/or electrical fault detection are not likely to be performed in a real infrastructure because of possible risks to the network/equipment security. This report summarizes the application of power system applications using distributed ledger technology (DLT), providing a secure DLT framework for collecting data from IEDs like power meters and protective relays inside and outside of an electrical substation and/or between two different electrical utilities. In this study, the use case scenarios were created and assessed for different power system application by using DLT. The electrical fault detection for faulted phases (1), power quality monitoring of phase voltage magnitudes, frequency levels and load power factor (2), DERs use case monitoring (3), and cyber-event applications (4) were performed in a test bed with a Cyber-Grid Guard (CGG) system using DLT. It had a real-time simulator with power meters and protective relays in-the-loop. The first section of this report presents a literature review of power system applications using blockchain at research level. The second section shows the theory and equations used on this report. The third section shows the description of the test bed, equipment, architecture, and electrical grid diagrams. The fourth section shows the experimental models and use case scenarios that were performed for the electrical fault detection, power quality, DERs use case, and cyber event applications with the CGG system using DLT. The fifth section shows the results collected from the tests based on comparing the time stamped events of the analog signals from the IEDs, DLT computer and real time simulator. The sixth section performed the discussion of the results for the use case scenarios. Finally, section seven presents the conclusions for this report were presented.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

Determining aromatic and aliphatic carboxylic acids in biomass-derived oil samples using 2,4-dinitrophenylhydrazine and liquid chromatography-electrospray injection-mass spectrometry/mass spectrometry

Converting biomass to a useful fuel commonly incorporates the pyrolysis of the biomass feed stock. The base liquid fraction usually contains high concentrations of ketones, aldehydes and carboxylic acids, of which each can cause detrimental issues related to the storage and upgrading process. Knowing the carbonyl species and the concentration of each will provide value information to the pyrolysis researchers, specifically as that community branches into more targeted end-products such as jet fuel or biogenic-derived oxygenate-containing fuel products. The analysis of aldehydes, ketones and small alkyl carboxylic acids using 2,4-dinitrophenylhydrazine (DNPH) derivation method has been well documented and the method is commonly used the analytical community. By using liquid chromatograph coupled to tandem mass spectrometry, biomass sample analysis can be complete with identification of most carbonyl species. The issue of identifying isobaric ketone and aldehyde compounds can be resolved by utilizing differences in retention time or characteristic fragment ions of ketones and aldehydes. One issue which could not resolved using published methods was identifying aromatic or large non-aromatic carboxylic acids from their corresponding hydroxyl aldehyde or ketone analogs. By modifying the current method for determining carbonyls in biomass samples, carboxylic and hydroxyl-carbonyl can be determined. A careful adjustment of the pH during the extraction procedure and extended heating time of the DNPH solution allowed for the successful derivation of aromatic carboxylic acids. Like other dinitrophenylhydrazones, carboxylic acid derivatives also produce a unique secondary ion pattern, which was useful to distinguish these species from the non-acid analogs.

bio-oil↗
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 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↗