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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 757 records · Page 42
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Factorization and resummation for groomed multi-prong jet shapes

Observables which distinguish boosted topologies from QCD jets are playing an increasingly important role at the Large Hadron Collider (LHC). These observables are often used in conjunction with jet grooming algorithms, which reduce contamination from both theoretical and experimental sources. In this paper we derive factorization formulae for groomed multi-prong substructure observables, focusing in particular on the groomed D 2 observable, which is used to identify boosted hadronic decays of electroweak bosons at the LHC. Our factorization formulae allow systematically improvable calculations of the perturbative D 2 distribution and the resummation of logarithmically enhanced terms in all regions of phase space using renormalization group evolution. They include a novel factorization for the production of a soft subjet in the presence of a grooming algorithm, in which clustering effects enter directly into the hard matching. We use these factorization formulae to draw robust conclusions of experimental relevance regarding the universality of the D 2 distribution in both e+e- and pp collisions. In particular, we show that the only process dependence is carried by the relative quark vs. gluon jet fraction in the sample, no non-global logarithms from event-wide correlations are present in the distribution, hadronization corrections are controlled by the perturbative mass of the jet, and all global color correlations are completely removed by grooming, making groomed D 2 a theoretically clean QCD observable even in the LHC environment. Lastly, we compute all ingredients to one-loop accuracy, and present numerical results at next-to-leading logarithmic accuracy for e + e - collisions, comparing with parton shower Monte Carlo simulations. Results for pp collisions, as relevant for phenomenology at the LHC, are presented in a companion paper.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2011

THE IMPACT OF GALAXY INTERACTIONS ON ACTIVE GALACTIC NUCLEUS ACTIVITY IN zCOSMOS

Close encounters between galaxies are expected to be a viable mechanism, as predicted by numerical simulations, by which accretion onto supermassive black holes can be initiated. To test this scenario, we construct a sample of 562 galaxies (M{sub *} > 2.5 Multiplication-Sign 10{sup 10} M{sub Sun }) in kinematic pairs over the redshift range 0.25 < z < 1.05 that are more likely to be interacting than a well-matched control sample of 2726 galaxies not identified as being in a pair, both from the zCOSMOS 20k spectroscopic catalog. Galaxies that harbor an active galactic nucleus (AGN) are identified on the basis of their X-ray emission (L{sub 0.5-10keV} > 2 Multiplication-Sign 10{sup 42} erg s{sup -1}) detected by Chandra. We find a higher fraction of an AGN in galaxies in pairs relative to isolated galaxies of similar stellar mass. Our result is primarily due to an enhancement of AGN activity, by a factor of 1.9 (observed) and 2.6 (intrinsic), for galaxies in pairs of projected separation less than 75 kpc and line-of-sight velocity offset less than 500 km s{sup -1}. This study demonstrates that close kinematic pairs are conducive environments for black hole growth, either indicating a causal physical connection or an inherent relation, such as, to enhanced star formation. In the Appendix, we describe a method for estimating the intrinsic fractions of galaxies (either in pairs or the field) hosting an AGN with confidence intervals, and an excess fraction in pairs. We estimate that 17.8{sup +8.4}{sub -7.4}% of all moderate-luminosity AGN activity takes place within galaxies undergoing early stages of interaction that leaves open the question as to what physical processes are responsible for fueling the remaining {approx}80% that may include late-stage mergers.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

On the reach of perturbative methods for dark matter density fields

We study the mapping from Lagrangian to Eulerian space in the context of the Effective Field Theory (EFT) of Large Scale Structure. We compute Lagrangian displacements with Lagrangian Perturbation Theory (LPT) and perform the full non-perturbative transformation from displacement to density. When expanded up to a given order, this transformation reproduces the standard Eulerian Perturbation Theory (SPT) at the same order. However, the full transformation from displacement to density also includes higher order terms. These terms explicitly resum long wavelength motions, thus making the resulting density field better correlated with the true non-linear density field. As a result, the regime of validity of this approach is expected to extend that of the Eulerian EFT, and match that of the IR-resummed Eulerian EFT. This approach thus effectively enables a test of the IR-resummed EFT at the field level. We estimate the size of stochastic, non-perturbative contributions to the matter density power spectrum. We find that in our highest order calculation, at redshift z = 0 the power spectrum of the density field is reproduced with an accuracy of 1% (10%) up to k = 0.25 hMpc{sup −1} (k = 0.46 hMpc{sup −1}). We believe that the dominant source of the remaining error is the stochastic contribution. Unfortunately, on these scales the stochastic term does not yet scale as k{sup 4} as it does in the very low k regime. Thus, modeling this contribution might be challenging.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2010

Color-singlet relativistic correction to inclusive J/{psi} production associated with light hadrons at B factories

We study the first-order relativistic correction to the associated production of J/{psi} with light hadrons at B factory experiments at {radical}(s)=10.58 GeV, in the context of nonrelativistic QCD (NRQCD) factorization. We employ a strategy for NRQCD expansion that slightly deviates from the orthodox doctrine, in that the matching coefficients are not truly of a ''short-distance'' nature, but explicitly depend upon physical kinematic variables rather than partonic ones. Our matching method, with validity guaranteed by the Gremm-Kapustin relation, is particularly suited for the inclusive quarkonium production and decay processes with involved kinematics, exemplified by the process e{sup +}e{sup -}{yields}J/{psi}+gg considered in this work. Despite some intrinsic ambiguity affiliated with the order-v{sup 2} NRQCD matrix element, if we choose its value as what has been extracted from a recent Cornell-potential-model-based analysis, including the relative order-v{sup 2} effect is found to increase the lowest-order prediction for the integrated J/{psi} cross section by about 30%, and exert a modest impact on J/{psi} energy, angular and polarization distributions except near the very upper end of the J/{psi} energy. The order-v{sup 2} contribution to the energy spectrum becomes logarithmically divergent at the maximum of J/{psi} energy. A consistent analysis may require that these large end-point logarithms be resummed to all orders in {alpha}{sub s}.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS2008

Data Assimilation Cycling for Weather Analysis

This software package runs the atmospheric model MM5 in data assimilation cycling mode to produce an optimized weather analysis, including the ability to insert or adjust a hurricane vortex. The program runs MM5 through a cycle of short forecasts every three hours where the vortex is adjusted to match the observed hurricane location and storm intensity. This technique adjusts the surrounding environment so that the proper steering current and environmental shear are achieved. MM5cycle uses a Cressman analysis to blend observation into model fields to get a more accurate weather analysis. Quality control of observations is also done in every cycle to remove bad data that may contaminate the analysis. This technique can assimilate and propagate data in time from intermittent and infrequent observations while maintaining the atmospheric field in a dynamically balanced state. The software consists of a C-shell script (MM5cycle.driver) and three FORTRAN programs (splitMM5files.F, comRegrid.F, and insert_vortex.F), and are contained in the pre-processor component of MM5 called "Regridder." The model is first initialized with data from a global model such as the Global Forecast System (GFS), which also provides lateral boundary conditions. These data are separated into single-time files using splitMM5.F. The hurricane vortex is then bogussed in the correct location and with the correct wind field using insert_vortex.F. The modified initial and boundary conditions are then recombined into the model fields using comRegrid.F. The model then makes a three-hour forecast. The three-hour forecast data from MM5 now become the analysis for the next short forecast run, where the vortex will again be adjusted. The process repeats itself until the desired time of analysis is achieved. This code can also assimilate observations if desired.

Tran, Nam↗
DOE OSTI2014

Autonomous Metabolomics for Rapid Metabolite Identification in Global Profiling

An autonomous metabolomic workflow combining mass spectrometry analysis with tandem mass spectrometry data acquisition was designed to allow for simultaneous data processing and metabolite characterization. Although previously tandem mass spectrometry data have been generated on the fly, the experiments described herein combine this technology with the bioinformatic resources of XCMS and METLIN. We can analyze large profiling datasets and simultaneously obtain structural identifications, as a result of this unique integration. Furthermore, validation of the workflow on bacterial samples allowed the profiling on the order of a thousand metabolite features with simultaneous tandem mass spectra data acquisition. The tandem mass spectrometry data acquisition enabled automatic search and matching against the METLIN tandem mass spectrometry database, shortening the current workflow from days to hours. Overall, the autonomous approach to untargeted metabolomics provides an efficient means of metabolomic profiling, and will ultimately allow the more rapid integration of comparative analyses, metabolite identification, and data analysis at a systems biology level.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

An evaluation of GPT models for phenotype concept recognition

Clinical deep phenotyping and phenotype annotation play a critical role in both the diagnosis of patients with rare disorders as well as in building computationally-tractable knowledge in the rare disorders field. These processes rely on using ontology concepts, often from the Human Phenotype Ontology, in conjunction with a phenotype concept recognition task (supported usually by machine learning methods) to curate patient profiles or existing scientific literature. With the significant shift in the use of large language models (LLMs) for most NLP tasks, we examine the performance of the latest Generative Pre-trained Transformer (GPT) models underpinning ChatGPT as a foundation for the tasks of clinical phenotyping and phenotype annotation. The experimental setup of the study included seven prompts of various levels of specificity, two GPT models (gpt-3.5-turbo and gpt-4.0) and two established gold standard corpora for phenotype recognition, one consisting of publication abstracts and the other clinical observations. The best run, using in-context learning, achieved 0.58 document-level F1 score on publication abstracts and 0.75 document-level F1 score on clinical observations, as well as a mention-level F1 score of 0.7, which surpasses the current best in class tool. Without in-context learning, however, performance is significantly below the existing approaches. Our experiments show that gpt-4.0 surpasses the state of the art performance if the task is constrained to a subset of the target ontology where there is prior knowledge of the terms that are expected to be matched. While the results are promising, the non-deterministic nature of the outcomes, the high cost and the lack of concordance between different runs using the same prompt and input make the use of these LLMs challenging for this particular task.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2011

Heavy-Quark Mass and Heavy-Meson Decay Constants from QCD Sum Rules

We present a sum-rule extraction of decay constants of heavy mesons from the two-point correlator of heavy-light pseudoscalar currents. Our primary concern is to control the uncertainties of the decay constants, induced by both input QCD parameters and limited accuracy of the sum-rule method. Gaining this control is possible by applying our novel procedure for the extraction of hadron observables utilizing Borel-parameter-depending dual thresholds. For the charmed mesons, we obtain f{sub D} (206.2{+-}7.3{sub (OPE){+-}}5.1{sub (syst)}) MeV and f{sub D{sub s}} (245.3{+-}15.7{sub (OPE){+-}}4.5{sub (syst)}) MeV. In the case of the beauty mesons, the decay constants prove to be extremely sensitive to the exact value of the b-quark MS mass m-bar{sub b}(m-bar{sub b}). By matching our sum-rule prediction for f{sub B} to the lattice outcomes, the very accurate b-mass value m-bar{sub b}(m-bar{sub b}) = (4.245{+-}0.025) GeV is found, which yields f{sub B} = (193.4{+-}12.3{sub (OPE){+-}}4.3{sub (syst)}) MeV and f{sub B{sub s}} (232.5{+-}18.6{sub (OPE){+-}}2.4{sub (syst)}) MeV.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2013

PIV Uncertainty Methodologies for CFD Code Validation at the MIR Facility

Currently, computational fluid dynamics (CFD) is widely used in the nuclear thermal hydraulics field for design and safety analyses. To validate CFD codes, high quality multi dimensional flow field data are essential. The Matched Index of Refraction (MIR) Flow Facility at Idaho National Laboratory has a unique capability to contribute to the development of validated CFD codes through the use of Particle Image Velocimetry (PIV). The significance of the MIR facility is that it permits non intrusive velocity measurement techniques, such as PIV, through complex models without requiring probes and other instrumentation that disturb the flow. At the heart of any PIV calculation is the cross-correlation, which is used to estimate the displacement of particles in some small part of the image over the time span between two images. This image displacement is indicated by the location of the largest peak. In the MIR facility, uncertainty quantification is a challenging task due to the use of optical measurement techniques. Currently, this study is developing a reliable method to analyze uncertainty and sensitivity of the measured data and develop a computer code to automatically analyze the uncertainty/sensitivity of the measured data. The main objective of this study is to develop a well established uncertainty quantification method for the MIR Flow Facility, which consists of many complicated uncertainty factors. In this study, the uncertainty sources are resolved in depth by categorizing them into uncertainties from the MIR flow loop and PIV system (including particle motion, image distortion, and data processing). Then, each uncertainty source is mathematically modeled or adequately defined. Finally, this study will provide a method and procedure to quantify the experimental uncertainty in the MIR Flow Facility with sample test results.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2014

SU-E-CAMPUS-T-03: Development and Implementation of An Anthropomorphic Pediatric Spine Phantom for the Assessment of Craniospinal Irradiation Procedures in Proton Therapy

Purpose: To design an anthropomorphic pediatric spine phantom for use in the evaluation of proton therapy facilities for clinical trial participation by the Imaging and Radiation Oncology Core (IROC) Houston QA Center (formerly RPC). Methods: This phantom was designed to perform an end-to-end audit of the proton spine treatment process, including simulation, dose calculation by the treatment planning system (TPS), and proton treatment delivery. The design incorporated materials simulating the thoracic spinal column of a pediatric patient, along with two thermoluminescent dosimeter (TLD)-100 capsules and radiochromic film embedded in the phantom for dose evaluation. Fourteen potential materials were tested to determine relative proton stopping power (RSP) and Hounsfield unit (HU) values. Each material was CT scanned at 120kVp, and the RSP was obtained from depth ionization scans using the Zebra multilayer ion chamber (MLIC) at two energies: 160 MeV and 250 MeV. To determine tissue equivalency, the measured RSP for each material was compared to the RSP calculated by the Eclipse TPS for a given HU. Results: The materials selected as bone, tissue, and cartilage substitutes were Techron HPV Bearing Grade (Boedeker Plastics, Inc.), solid water, and blue water, respectively. The RSP values did not differ by more than 1.8% between the two energies. The measured RSP for each selected material agreed with the RSP calculated by the Eclipse TPS within 1.2%. Conclusion: An anthropomorphic pediatric proton spine phantom was designed to evaluate proton therapy delivery. The inclusion of multiple tissue substitutes increases heterogeneity and the level of difficulty for institutions to successfully treat the phantom. The following attributes will be evaluated: absolute dose agreement, distal range, field width, junction match and right/left dose profile alignment. The phantom will be tested at several institutions using a 5% dose agreement criterion, and a 5%/3mm gamma analysis criterion for the film planes. Work supported by grants CA10953, CA059267, and CA81647 (NCI, DHHS)

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2026

Public Reference Data for Megawatt-Scale Hydrogen Electrolysis - NLR Historical Wind

The U.S. Department of Energy and the National Laboratory of the Rockies (NLR) demonstrate hydrogen electrolysis from variable sources, hydrogen compression and storage, and hydrogen fuel cell power production using megawatt-scale equipment at NLR’s Flatirons Campus as part of the Advanced Research on Integrated Energy Systems (ARIES) initiative. This dataset represents part of that effort and is intended for academic, national laboratory, industrial, and other stakeholders to plan, design, and validate models of megawatt-scale hydrogen technologies and diverse energy infrastructure nationwide. These data provide a baseline for how existing hydrogen electrolysis technologies perform when coupled with various energy technologies. Future datasets will demonstrate how existing hydrogen fuel cell technologies can provide controllable, dispatchable, and variable power output for artificial intelligence (AI) data centers and other variable loads. This dataset entry describes hydrogen production by conducting a statistical analysis of historical wind data over a five-year period (2020-2025) from a single 1.5MW turbine manufactured by General Electric (GE) located at NLR’s Flatirons Campus, to generate an experimental test profile that was deployed on a 1.25-MW proton exchange membrane type MC250 electrolyzer system manufactured by Nel Hydrogen . [1] While the electrolyzer balance-of-plant supports up to 2.5 MW of electrolysis, NLR only has a single 1.25-MW electrolysis stack. The historical wind data provided several metrics, however, the analysis particularly focused on the measured power output by the wind turbine. The power output time series of data for each day was categorized by total energy generation and standard deviation, and the day that represented the highest combination of these two metrics was chosen – December 25th, 2022. This process was then repeated for a moving four-hour window within this day to identify the most statistically variable period. Finally, this four-hour period was scaled by 65% to match the 1.25 MW electrolyzer. The electrolysis system controls hydrogen production by varying DC current applied to the stack, from a maximum of 3000 A to a minimum safe operation of 300 A, or 10%. Because the current – voltage characteristic changes as the stack ages and efficiency degrades, the actual minimum safe operating power changes over time. The historical wind profiles were translated from power (kilowatts) to current (amperes) using a curve fit with calibration data and sent to the electrolyzer power supply at 1 Hz frequency. For more details on the statistical analysis process, see the presentation labeled “ Public Reference Data for Megawatt-Scale Hydrogen Electrolysis” provided with each data entry. These datasets report relevant hydrogen balance-of-plant and system data, all captured at 1 Hz, including hydrogen mass production measured with an Emerson Coriolis flow meter. Each .zip file represents a single wind turbine electrolysis experiment and is formatted as follows: {technology}_{scaling factor}-{electrolyzer ramp rate in amperes/second} For instance, “wind-GE1.5MW_0.65-400.zip” represents the hour-long experiment using historical data from the wind-GE1.5MW turbine, scaled to 65%, with the electrolyzer power supply set to a maximum ramp rate (gain and slew) of 400 A/s. Each .zip folder contains the following files: A .csv file containing raw data An .xlsx file explaining all the fields in the raw data. A .png plot showing the time series of hydrogen production, electrolysis power consumption, and wind power input. A PDF file detailing the historical wind data statistical analysis used to generate the wind profile. An experiment labeled “characterization_200.zip” demonstrates the MC250 electrolyzer steady-state response with 30-minute load steps for a total duration of 5 hours. Finally, a .csv file is provided with all simulated wind experiments combined into one dataset labeled "combined_historical_wind_experiments.csv". NLR also built an AI/machine-learning predictive model based on these datasets. The model ingests the electrolyzer current command in amperes, as well as various pressures and temperatures across the system, and predicts hydrogen output in kilograms per hour. The complete model can be found at https://huggingface.co/NatLabRockies/ptmelt-hydrogen-electrolysis [1] nelhydrogen.com/product/mc-series-electrolyser .

08 HYDROGEN↗
DOE OSTI2020

Distributed fiber sensing systems for 3D combustion temperature field monitoring in coal-fired boilers using optically generated acoustic waves (Final Report)

In this project, we have developed and tested three kinds of fiber optic sensing systems for real time monitoring of temperature variations within an industrial scale boiler furnace. The fiber optic sensing systems target spatial and temporal distributions of high temperature profiles in a boiler furnace in fossil power plants. The reconstructed temperature profile will provide critical input for the control mechanisms to optimize the combustion process. This temperature profile will address the essential problem for fossil power plants in achieving higher efficiency and fewer pollutant emissions. Acoustic pyrometer systems have been used to reconstruct temperature field of power plant boilers based on measuring TOF (times-of-flight) of sound waves along some straight paths in a 2D cross-section of the boiler. In this project, optically generated acoustic signals from a fiber optic sensing system have replaced the acoustic signals generated from an electrical transducer. A 3D reconstruction algorithm replaced the previous 2D model. In this project, three kinds of fiber optic sensing systems have been developed and tested. They are fiber optic sensing system I, fiber optic sensing system II (Distributed Sensing System I) and fiber optic sensing system III (Distributed Sensing System II). For fiber optic sensing system I, the fiber optic ultrasound generator acts as a signal generator. A microphone, hydrophone or other electronic devices serve as a signal receiver. In this system, there are one generator and one receiver. Distance test, water temperature test, air temperature test, air temperature reconstruction, and GE ISBF pilot test were performed by Fiber optic sensing system I. The fiber optic sensing system I successfully detected temperature in all these tests. We got 2D temperature reconstruction results by using the fiber optic sensing system I and it matched the reference data. The fiber optic sensing system I successfully survived in GE ISBF boiler environment (480 °F). For fiber optic sensing system II (Distributed Sensing System I), it is an all optical ultrasound system. The fiber optic ultrasound generator acts as a signal generator. Fiber Bragg Grating (FBG) and Fabry-Perot (FP) sensor act as a signal receiver. In this system, there is one generator and one receiver. Aluminum plate temperature test, furnace high temperature test, and GE ISBF pilot test were performed by the fiber optic sensing system II. Fiber optic sensing system II successfully detected the temperature in all these tests. The fiber optic sensing system II successfully survived at up to 700 °C furnace environment and 320 °C GE ISBF boiler environment. For fiber optic sensing system III (Distributed Sensing System II), it is also an all optical ultrasound system. The fiber optic ultrasound generator acts as a signal generator. Multiple FP fiber sensors act as signal receivers. In this system, there is one generator and three receivers. Three GE ISBF pilot tests were performed by fiber optic sensing system III. The fiber optic sensing system III survived in the cold flow tests in GE’s ISBF pilot test facility. However, we didn’t get high temperature data by using this system since the nanosecond laser issues. During the period of the project, test trials, data simulation and algorithm optimization was performed successfully. For real time temperature field construction, the sampling rate must be fast enough to capture the field variations. The technology of Code-division multiple access (CDMA) is well studied which could allow parallel multiplexing, even if signals overlap in time or frequencies. Moreover, it has been known that extending the length of signal significantly improves SNR. For acoustic signals, these multiplexing techniques have also been widely used, mainly for sonar and acoustic communications. The CDMA modulation technique has been proposed and studied to guarantee high network throughput, low channel access delay and low energy consumption. We have studied the temperature field reconstruction using Gaussian Radial Basis Functions (GRBF)-based approximation approach. Reconstruction of 3D temperature field using Neural Networks with measured TOF and known propagation paths is feasible. 2D and 3D temperature field reconstruction simulation results are achieved. The milestone status is shown in Table 1. We finished milestone 1-8 and milestone 10. For milestone 9, we did three pilot tests by using the fiber optic sensing system III (Distributed Sensing System II) at GE Power. However, due to the failure of the ns laser, we did not get the temperature results. We conducted some additional tasks that were not originally proposed: 1) We fabricated a fiber optic sensing system I and did a pilot test based on this system. 2) In the proposal, we proposed two pilot tests at GE Power. In reality, we finished at least seven pilot tests at GE Power. GE Power has made a lot of efforts for supporting the pilot tests. 3) We got a simulation results based on CDMA. In summary, most of the tasks have been accomplished. The outcome of this project removed a few barriers that hinder the achievement of the final product of the distributed sensing systems. With the successful accomplishment of this project, a prototype of the fiber optic sensing system can be fabricated to attract more interests from companies and other funding agencies.

47 OTHER INSTRUMENTATION↗
NASA NTRS2008

Column Grid Array Rework for High Reliability

Due to requirements for reduced size and weight, use of grid array packages in space applications has become common place. To meet the requirement of high reliability and high number of I/Os, ceramic column grid array packages (CCGA) were selected for major electronic components used in next MARS Rover mission (specifically high density Field Programmable Gate Arrays). ABSTRACT The probability of removal and replacement of these devices on the actual flight printed wiring board assemblies is deemed to be very high because of last minute discoveries in final test which will dictate changes in the firmware. The questions and challenges presented to the manufacturing organizations engaged in the production of high reliability electronic assemblies are, Is the reliability of the PWBA adversely affected by rework (removal and replacement) of the CGA package? and How many times can we rework the same board without destroying a pad or degrading the lifetime of the assembly? To answer these questions, the most complex printed wiring board assembly used by the project was chosen to be used as the test vehicle, the PWB was modified to provide a daisy chain pattern, and a number of bare PWB s were acquired to this modified design. Non-functional 624 pin CGA packages with internal daisy chained matching the pattern on the PWB were procured. The combination of the modified PWB and the daisy chained packages enables continuity measurements of every soldered contact during subsequent testing and thermal cycling. Several test vehicles boards were assembled, reworked and then thermal cycled to assess the reliability of the solder joints and board material including pads and traces near the CGA. The details of rework process and results of thermal cycling are presented in this paper.

high reliability↗
DOE OSTI2023

Jet-veto resummation at N 3 LL p + NNLO in boson production processes

Vetoing energetic jet activity is a crucial tool for suppressing backgrounds and enabling new physics searches at the LHC, but the introduction of a veto scale can introduce large logarithms that may need to be resummed. We present an implementation of jet-veto resummation for color-singlet processes at the level of N 3 LL p matched to fixed-order NNLO predictions. Our public code MCFM allows for predictions of a single boson, such as Z/γ*, W ± or H, or with a pair of vector bosons, such as W + W – , W ± Z or ZZ. The implementation relies on recent calculations of the soft and beam functions in the presence of a jet veto over all rapidities, with jets defined using a sequential recombination algorithm with jet radius R. However one of the ingredients that is required to reach full N 3 LL accuracy is only known approximately, hence N 3 LL p . We describe in detail our formalism and compare with previous public codes that operate at the level of NNLL. Our higher-order predictions improve significantly upon NNLL calculations by reducing theoretical uncertainties. We demonstrate this by comparing our predictions with ATLAS and CMS results.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2018

Unordinary Ferromagnetic Phase Transitions in Mn- and Fe-doped Half-Heusler CoTiSb

Unordinary ferromagnetic character and high Curie temperature around 900 K have been detected for CoTi {sub 1−x}M{sub x}Sb (M = Mn and Fe, x = 0.1) multiphases systems. The synthesis process was carried out at high temperature in evacuated quartz tubes. The x-ray powder diffraction analysis through Rietveld method was applied to refine the crystal structure. By manipulating the search match program, three nanocrystalline phases of CoTiSb (64.5%), CoSb (15.5%), and TiSb{sub 2} (20.5%) for Mn-doped system and CoTiSb (33%), Ti{sub 3}Sb (35.3%), and CoTi{sub 2} (30.7%) for Fe-doped system were recognized. The term “phase” was used to address the coexistence of different stable chemical compositions for the same half-Heusler alloy. The scanning electron microscope (SEM) and the high-resolution transmission electron microscope (HR-TEM) were applied to characterize the morphology, size, shape, crystallinity and lattice spacing. Good matching was detected between the obtained d values using electron diffraction data and those calculated from x-ray analysis. Well defined nanocrystalline structure with average interatomic distances equaling 0.229 nm, 0.286 nm together with many successive rings with sharp diffraction spots characterized the Fe-doped system. In contrast, partially distorted structured planes and smeared halo surrounded by weak rings were detected in the Mn-doped system. Thermo-magnetic measurements (M-T) were performed for both systems. In addition to Curie transition, many magnetic phase transitions were detected and confirmed through the ΔM/ ΔT vs. T relationship. The field-dependence magnetization (M-H) was measured at different temperatures. The M-H hysteresis loops showed the ferromagnetic character for both systems. Tentative magnetic phase diagrams are suggested as a guide for future research.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Local-scale heterogeneity of soil thermal dynamics and controlling factors in a discontinuous permafrost region

In permafrost regions, the strong spatial and temporal variability in soil temperature cannot be explained by the weather forcing only. Understanding the local heterogeneity of soil thermal dynamics and their controls is essential to understand how permafrost systems respond to climate change and to develop process-based models or remote sensing products for predicting soil temperature. In this study, we analyzed soil temperature dynamics and their controls in a discontinuous permafrost region on the Seward Peninsula, Alaska. We acquired one-year temperature time series at multiple depths (at 5 or 10 cm intervals up to 85 cm depth) at 45 discrete locations across a 2.3 km 2 watershed. We observed a larger spatial variability in winter temperatures than that in summer temperatures at all depths, with the former controlling most of the spatial variability in mean annual temperatures. We also observed a strong correlation between mean annual ground temperature at a depth of 85 cm and mean annual or winter season ground surface temperature across the 45 locations. We demonstrate that soils classified as cold, intermediate, or warm using hierarchical clustering of full-year temperature data closely match their co-located vegetation (graminoid tundra, dwarf shrub tundra, and tall shrub tundra, respectively). We show that the spatial heterogeneity in soil temperature is primarily driven by spatial heterogeneity in snow cover, which induces variable winter insulation and soil thermal diffusivity. These effects further extend to the subsequent summer by causing variable latent heat exchanges. Finally, we discuss the challenges of predicting soil temperatures from snow depth and vegetation height alone by considering the complexity observed in the field data and reproduced in a model sensitivity analysis.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

SU-F-T-114: A Novel Anatomically Predictive Extension Model of Computational Human Phantoms for Dose Reconstruction in Retrospective Epidemiological Studies of Second Cancer Risks in Radiotherapy Patients

Purpose: Recent advances in cancer treatments have greatly increased the likelihood of post-treatment patient survival. Secondary malignancies, however, have become a growing concern. Epidemiological studies determining secondary effects in radiotherapy patients require assessment of organ-specific dose both inside and outside the treatment field. An essential input for Monte Carlo modeling of particle transport is radiological images showing full patient anatomy. However, in retrospective studies it is typical to only have partial anatomy from CT scans used during treatment planning. In this study, we developed a multi-step method to extend such limited patient anatomy to full body anatomy for estimating dose to normal tissues located outside the CT scan coverage. Methods: The first step identified a phantom from a library of body size-dependent computational human phantoms by matching the height and weight of patients. Second, a Python algorithm matched the patient CT coverage location in relation to the whole body phantom. Third, an algorithm cut the whole body phantom and scaled them to match the size of the patient. Then, merged the two anatomies into one whole body. We entitled this new approach, Anatomically Predictive Extension (APE). Results: The APE method was examined by comparing the original chest-abdomen-pelvis CT images of the five patients with the APE phantoms developed from only the chest part of the CAP images and whole body phantoms. We achieved average percent differences of tissue volumes of 25.7%, 34.2%, 16.5%, 26.8%, and 31.6% with an average of 27% across all patients. Conclusion: Our APE method extends the limited CT patient anatomy to whole body anatomy by using image processing and computational human phantoms. Our ongoing work includes evaluating the accuracy of these APE phantoms by comparing normal tissue doses in the APE phantoms and doses calculated for the original full CAP images under generic radiotherapy simulations. This research was supported by the NIH Intramural Research Program.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2020

FOSSIL—Finding Our Cosmic Roots

FOSSIL (Fragments from the Origins of the Solar System and our Interstellar Locale) is a concept to explore the largest solar system object visible to the unaided eye—the zodiacal cloud. The cloud’s many dust particles are each a tiny time capsule from a comet or asteroid. The FOSSIL concept is for the in situ compositional analysis of interplanetary dust particles, and also of the particles passing through the solar system from interstellar space. By measuring the zodiacal and interstellar particles’ velocity vectors and compositions, the approach resolves fundamental questions about the solar system’s origins. The FOSSIL concept is to: (1) Discover whether today’s local interstellar dust matches the composition of the feedstock from which the solar system formed; (2) Determine whether comets’ fine-grained component preserves unprocessed pre-solar dust or shows signs of processing in the early solar system; and (3) Learn whether comets’ and asteroids’ organic material share a common source or formed from distinct reservoirs. The FOSSIL concept is based on the use of a Dust Telescope (DT) with the capability to measure the composition and the velocity vector of dust particles to unambiguously separate interstellar from interplanetary particles, and identify a subset of zodiacal particles that are exclusively cometary. In the DT, particles pass through the trajectory sensor unharmed and impact a target plate, where they are vaporized and partially ionized. The ions are electrostatically focused onto a detector where the time-of-flight mass spectrum is recorded, enabling measurement of the composition of the interstellar solids, detection of cometary minerals altered by high temperatures or exposure to liquid water in the early solar system, and the characterization of the organic materials from the comets and asteroids that are still being delivered to the Earth today. FOSSIL’s objectives crosscut several disciplines with planetary science. Astrophysics interests lie in understanding interstellar solar matter and the only debris disk accessible in situ. Heliophysics interest is in the verification of large-scale heliospheric magnetic field models by the measured effect on the motion of electrically charged interstellar dust. Reporting the makeup of interplanetary dust that ablates in our atmosphere is valuable to Earth sciences. FOSSIL’s DT is scalable and can be accommodated to a variety of mission opportunities, without restriction on launch dates, and for a large number of possible orbits.

Turner, Neal↗