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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 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Simulating nonlinear cosmological structure formation with massive neutrinos

We present a new method for simulating cosmologies that contain massive particles with thermal free streaming motion, such as massive neutrinos or warm/hot dark matter. This method combines particle and fluid descriptions of the thermal species to eliminate the shot noise known to plague conventional N-body simulations. We describe this method in detail, along with results for a number of test cases to validate our method, and check its range of applicability. Using this method, we demonstrate that massive neutrinos can produce a significant scale-dependence in the large-scale biasing of deep voids in the matter field. We show that this scale-dependence may be quantitatively understood using an extremely simple spherical expansion model which reproduces the behavior of the void bias for different neutrino parameters.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

A new calibration method for charm jet identification validated with proton-proton collision events at $\sqrt{s}$ =13 TeV

Many measurements at the LHC require efficient identification of heavy-flavour jets, i.e. jets originating from bottom (b) or charm (c) quarks. An overview of the algorithms used to identify c jets is described and a novel method to calibrate them is presented. This new method adjusts the entire distributions of the outputs obtained when the algorithms are applied to jets of different flavours. It is based on an iterative approach exploiting three distinct control regions that are enriched with either b jets, c jets, or light-flavour and gluon jets. Results are presented in the form of correction factors evaluated using proton-proton collision data with an integrated luminosity of 41.5 fb$^{-1}$ at √s = 13 TeV, collected by the CMS experiment in 2017. The closure of the method is tested by applying the measured correction factors on simulated data sets and checking the agreement between the adjusted simulation and collision data. Furthermore, a validation is performed by testing the method on pseudodata, which emulate various mismodelling conditions. The calibrated results enable the use of the full distributions of heavy-flavour identification algorithm outputs, e.g. as inputs to machine-learning models. Thus, they are expected to increase the sensitivity of future physics analyses.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2018

Void lensing as a test of gravity

We propose a consistency test of gravity based on the weak lensing signal of cosmic voids. For a given void profile, as traced by galaxies, the lensing signal can vary in different gravity theories. Thus the comparison of the lensing shear profile of such voids with the general relativistic prediction can test for deviations from general relativity (GR). For concreteness, we calculate the expected lensing signal in two gravity theories involving scalar fields with derivative couplings. We find that the scalar field has the potential to boost the tangential shear both within and outside the void radius. Reversing the method, one can infer the void central density parameter from the lensing signal, and compare to the value estimated independently using the galaxy tracer profiles of voids. Hence, one can check for consistency between the behavior of light and matter under the assumption of GR. We use voids traced by luminous red galaxies in SDSS to demonstrate our methodology, finding that the void central density parameter can shift from its GR value by up to 20% in some Galileon gravity models. Although Galileon gravity is now disfavored as a source of cosmic acceleration by other data sets, the methods we demonstrate here can be used to test for more general fifth force effects with upcoming void lensing data.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

The Radius of PSR J0740+6620 from NICER with NICER Background Estimates

We report a revised analysis for the radius, mass, and hot surface regions of the massive millisecond pulsar PSR J0740+6620, studied previously with joint fits to NICER and XMM-Newton data by Riley et al. (2021) and Miller et al. (2021). We perform a similar Bayesian estimation for the pulse-profile model parameters, except that instead of fitting simultaneously the XMM-Newton data, we use the best available NICER background estimates to constrain the number of photons detected from the source. This approach eliminates any potential issues in the cross-calibration between these two instruments, providing thus an independent check of the robustness of the analysis. The obtained neutron star parameter constraints are compatible with the already published results, with a slight dependence on how conservative the imposed background limits are. A tighter lower limit causes the inferred radius to increase, and a tighter upper limit causes it to decrease. We also extend the study of the inferred emission geometry to examine the degree of deviation from antipodality of the hot regions. We show that there is a significant offset to an antipodal spot configuration, mainly due to the non-half-cycle azimuthal separation of the two emitting spots. The offset angle from the antipode is inferred to be above 25° with 84% probability. This seems to exclude a centered-dipolar magnetic field in PSR J0740+6620.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

COVID-19 global pandemic planning: Performance and electret charge of N95 respirators after recommended decontamination methods

Shortages of N95 respirators for use by medical personnel have driven consideration of novel conservation strategies, including decontamination for reuse and extended use. Decontamination methods listed as promising by the Centers for Disease Control and Prevention (CDC) (vaporous hydrogen peroxide (VHP), wet heat, ultraviolet irradiation (UVI)) and several methods considered for low resource environments (bleach, isopropyl alcohol and detergent/soap) were studied for two commonly used surgical N95 respirators (3M™ 1860 and 1870+ Aura™). Although N95 filtration performance depends on the electrostatically charged electret filtration layer, the impact of decontamination on this layer is largely unexplored. As such, respirator performance following decontamination was assessed based on the fit, filtration efficiency, and pressure drop, along with the relationship between (1) surface charge of the electret layer, and (2) elastic properties of the straps. Decontamination with VHP, wet heat, UVI, and bleach did not degrade fit and filtration performance or electret charge. Isopropyl alcohol and soap significantly degraded fit, filtration performance, and electret charge. Pressure drop across the respirators was unchanged. Modest degradation of N95 strap elasticity was observed in mechanical fatigue testing, a model for repeated donnings and doffings. CDC recommended decontamination methods including VHP, wet heat, and UV light did not degrade N95 respirator fit or filtration performance in these tests. Extended use of N95 respirators may degrade strap elasticity, but a loss of face seal integrity should be apparent during user seal checks. NIOSH recommends performing user seal checks after every donning to detect loss of appropriate fit. Decontamination methods which degrade electret charge such as alcohols or detergents should not be used on N95 respirators. The loss of N95 performance due to electret degradation would not be apparent to a respirator user or evident during a negative pressure user seal check.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Anomaly Detection in Seismic Data with Deep Learning: Application for Instrument Failure Detection and Forecasting

Seismic data quality assessment (QA) is the first and one of the most important steps before conducting any further data analysis. Traditional methods involve checking various metrics, such as spike detection and power spectral density, by setting strict thresholds or comparing data against synthetic benchmarks. However, these approaches often rely on pre-existing knowledge and assumptions about data anomalies, leading to potential misclassification of unusual cases. Here, in this study, we propose a deep autoencoder model, an unsupervised learning approach that evaluates data quality without making assumptions about normal and anomalous data, which can be used to identify deviations in recorded data that may indicate nascent instrument failure. We test the model with the U.S. International Monitoring System (IMS) seismic stations and demonstrate the capability of detecting anomalies on a monthly scale. This could prompt station operators to examine potential problems early, allowing sufficient time for instrument maintenance to prevent data outages. In addition, we use a new manually selected testing dataset to compare our model performance against two supervised machine learning (ML) approaches and a standard QA package, as baseline models. When applied to the dataset containing known data anomalies, performance of the supervised and unsupervised ML approaches is similar, with an accuracy of 88.1% for our model compared to ∼90% for the supervised ML approach and 78.2% for the standard QA package. Our model outperforms the baseline models when applied to new stations, where new types of data anomalies can be station-specific and not included in the training dataset. Finally, we show model transferability by training the model with data from the Global Seismograph Network only and applying it to the IMS network data. The results suggest that our model is generalizable and can be applied to new stations with good accuracy.

Lin, Jiun-Ting [Lawrence Livermore National Labora↗
DOE OSTI2013

Functional Bounding Content Envelope for Gamma and Neutron Emitting Isotopes in the Model 9977 Packaging

The contents approved for shipment in a Type B radioactive material transportation package have historically been descriptions of discrete items, or groupings of well-defined similar items, in the package safety basis documentation. The need for a comprehensive functional content envelope of both gamma and neutron emitting nuclides compliant with regulatory limits has become necessary as the DOE complex requires shipments of unique mixtures of radionuclides and impurities. Recent publications have presented a calculational model and a corresponding content envelope intended to be compliant with federal regulatory external radiation limits as well as design decay heat limits based on the Model 9977 Packaging. The methodology used to develop this content envelope consisted of determining the external radiation dose rates based on one gram of a given isotope combined, in the case of actinides, with various levels of light element impurities and determining the allowable mass to the regulatory limits based on these dose rates. The method of ratioing from these calculations to the masses that meet the regulatory limits fails in the case of some combinations of actinides and light element impurities because of the effect of subcritical multiplication, resulting in non-conservative and non-compliant dose rates in some cases. This is particularly true for many actinides combined with beryllium, boron, fluorine, lithium, and sodium. In this study, the source was modeled as a sphere with the appropriate dimensions based on the actinide or gamma source density and placed at the bottom of the containment vessel for maximum conservatism. The results presented in this report rectify the above-noted deficiencies by adjusting the previously determined mass limits so that the resulting dose rates are compliant with regulatory limits. Some amount of iteration was required in some instances to adjust the masses for dose compliance. In some instances the masses were increased since they were too conservative. In addition, the method of ratioing the masses when applied to several gamma emitting isotopes also resulted in either non-conservative or overly conservative data. The mass imits presented here are for bare sources and are complaint with the design decay heat limit of 19W. The masses are based on package surface dose rates (the limiting dose rate) that fall in the range 185-195 mrem/h, thus giving an additional margin of between 7.5% and 2.5% to the regulatory limit of 200 mrem/h. This report presents a revised set of mass limits (i.e., content envelope) for several neutron emitting actinides with varying levels of light element impurities compliant with both external radiation and design decay heat limits. In addition, revised limits for gamma sources are also presented. The neutron emitter mass limits are in Tables 1 through 9 and the gamma emitter mass limits are in Table 10. The revised content envelope covering a wide range of materials present in the DOE complex, was developed for the Model 9977 Packaging, providing conservative limits for other commonly-used Type B Packagings such as the Models 9975 and 9978. It should be noted that for the Model 9977 package, shipment is also possible with three shielded containers – lead or tungsten for gamma sources and polyethylene for neutron emitters. The design decay heat limits for these are as follows: 19W for tungsten, 6W for lead and 3W for polyethylene. The limits presented in this report would need to be checked against the lower decay heat limits for the lead and polyethylene and adjusted as required for compliance. Criticality safety is not factored into these limits and should be evaluated on a case by case basis.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Physics-guided Deep Learning for Power System State Estimation

In the past decade, dramatic progress has been made in the field of machine learning. This paper explores the possibility of applying deep learning in power system state estimation. Traditionally, physics-based models are used including weighted least square (WLS) or weighted least absolute value (WLAV). These models typically consider a single snapshot of the system without capturing temporal correlations of system states. In this paper, a physics-guided deep learning (PGDL) method is proposed. Specifically, inspired by autoencoders, deep neural networks (DNNs) are used to learn the temporal correlations. The estimated system states from DNNs are then checked against physics laws by running through a set of power flow equations. Hence, the proposed PGDL is both data-driven and physics-guided. The accuracy and robustness of the proposed PGDL method are compared with traditional methods in standard IEEE cases. Simulations show promising results and the applicability is further discussed.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2015

Three-family particle physics models from global F-theory compactifications

We construct four-dimensional, globally consistent F-theory models with three chiral generations, whose gauge group and matter representations coincide with those of the Minimal Supersymmetric Standard Model, the Pati-Salam Model and the Trinification Model. These models result from compactification on toric hypersurface fibrations X with the choice of base $\mathbb P^{3}$. We observe that the F-theory conditions on the G 4 -flux restrict the number of families to be at least three. We comment on the phenomenology of the models, and for Pati-Salam and Trinification models discuss the Higgsing to the Standard Model. A central point of this work is the construction of globally consistent G 4 -flux. For this purpose we compute the vertical cohomology H V (2,2) (X) in each case and solve the conditions imposed by matching the M- and F-theoretical 3D Chern-Simons terms. Finally, we explicitly check that the expressions found for the G 4 -flux allow for a cancelation of D3-brane tadpoles. We also use the integrality of 3D Chern-Simons terms to ensure that our G 4 -flux solutions are adequately quantized.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2014

Multicolor photometry of the merging galaxy cluster A2319: Dynamics and star formation properties

Asymmetric X-ray emission and a powerful cluster-scale radio halo indicate that A2319 is a merging cluster of galaxies. This paper presents our multicolor photometry for A2319 with 15 optical intermediate filters in the Beijing-Arizona-Taiwan-Connecticut (BATC) system. There are 142 galaxies with known spectroscopic redshifts within the viewing field of 58' × 58' centered on this rich cluster, including 128 member galaxies (called sample I). A large velocity dispersion in the rest frame, 1622{sub −70}{sup +91} km s{sup –1}, suggests merger dynamics in A2319. The contour map of projected density and localized velocity structure confirm the so-called A2319B substructure, at ∼10' northwest to the main concentration A2319A. The spectral energy distributions (SEDs) of more than 30,000 sources are obtained in our BATC photometry down to V ∼ 20 mag. A u-band (∼3551 Å) image with better seeing and spatial resolution, obtained with the Bok 2.3 m telescope at Kitt Peak, is taken to make star-galaxy separation and distinguish the overlapping contamination in the BATC aperture photometry. With color-color diagrams and photometric redshift technique, 233 galaxies brighter than h {sub BATC} = 19.0 are newly selected as member candidates after an exclusion of false candidates with contaminated BATC SEDs by eyeball-checking the u-band Bok image. The early-type galaxies are found to follow a tight color-magnitude correlation. Based on sample I and the enlarged sample of member galaxies (called sample II), subcluster A2319B is confirmed. The star formation properties of cluster galaxies are derived with the evolutionary synthesis model, PEGASE, assuming a Salpeter initial mass function and an exponentially decreasing star formation rate (SFR). A strong environmental effect on star formation histories is found in the manner that galaxies in the sparse regions have various star formation histories, while galaxies in the dense regions are found to have shorter SFR time scales, older stellar ages, and higher interstellar medium metallicities. For the merging cluster A2319, local surface density is a better environmental indicator rather than the cluster-centric distance. Compared with the well-relaxed cluster A2589, a higher fraction of star-forming galaxies is found in A2319, indicating that the galaxy-scale turbulence stimulated by the subcluster merger might have played a role in triggering the star formation activity.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

SU-F-T-139: Meeting the Challenges of Quality Control in the TOPAS Monte Carlo Simulation Toolkit for Proton Therapy

Purpose: Monte Carlo particle transport simulation (MC) codes have become important tools in proton therapy and biology, both for research and practice. TOPAS is an MC toolkit serving users worldwide (213 licensed users at 95 institutions in 21 countries). It provides unprecedented ease in 4D placement of geometry components, beam sources and scoring through its user-friendly and reproducible parameter file interface. Quality control (QC) of stochastic simulation software is inherently difficult, and the versatility of TOPAS introduces additional challenges. But QC is vital as the TOPAS development team implements new features, addresses user feedback and reacts to upgrades of underlying software (i.e. Geant4). Methods: Whenever code is committed to our repository, over 50 separate module tests are automatically triggered via a continuous integration service. They check that the various module options execute successfully and that their results are statistically consistent with previous reference values. Prior to each software release, longer end-to-end tests automatically validate TOPAS against experimental data and a TOPAS benchmark. These include simulating multiple properties of spread-out Bragg peaks, validating nuclear models, and searching for differences in patient simulations. Results: Continuous integration has proven effective in catching regressions at the time they are introduced, particularly when implementing new features that involve refactoring code (e.g. multithreading and ntuple output). Code coverage statistics highlight untested portions of code and guide development of new tests. The various end-to-end tests demonstrate that TOPAS accurately describes the physics of proton therapy within clinical tolerances. Conclusion: The TOPAS QC strategy of frequent short tests and pre-release long tests has led to a more reliable tool. However, the versatility of TOPAS makes it difficult to predict how users might combine different modules, and so QC ultimately remains a partnership between the developer and the user. This work was funded by National Cancer Institute grant R01 CA 140735.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-T-494: A Multi-Institutional Study of Independent Dose Verification Using Golden Beam Data

Purpose: In general, beam data of individual linac is measured for independent dose verification software program and the verification is performed as a secondary check. In this study, independent dose verification using golden beam data was compared to that using individual linac’s beam data. Methods: Six institutions were participated and three different beam data were prepared. The one was individual measured data (Original Beam Data, OBD) .The others were generated by all measurements from same linac model (Model-GBD) and all linac models (All-GBD). The three different beam data were registered to the independent verification software program for each institute. Subsequently, patient’s plans in eight sites (brain, head and neck, lung, esophagus, breast, abdomen, pelvis and bone) were analyzed using the verification program to compare doses calculated using the three different beam data. Results: 1116 plans were collected from six institutes. Compared to using the OBD, the results shows the variation using the Model-GBD based calculation and the All-GBD was 0.0 ± 0.3% and 0.0 ± 0.6%, respectively. The maximum variations were 1.2% and 2.3%, respectively. The plans with the variation over 1% shows the reference points were located away from the central axis with/without physical wedge. Conclusion: The confidence limit (2SD) using the Model-GBD and the All-GBD was within 0.6% and 1.2%, respectively. Thus, the use of golden beam data may be feasible for independent verification. In addition to it, the verification using golden beam data provide quality assurance of planning from the view of audit. This research is partially supported by Japan Agency for Medical Research and Development(AMED)

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Gas Puff Imaging Diagnostics of Edge Plasma Turbulence in Magnetic Fusion Devices

Gas puff imaging (GPI) is a diagnostic of plasma turbulence which usesa puff of neutral gas at the plasma edge to increase the local visiblelight emission for improved space-time resolution of plasmafluctuations. This paper reviews gas puff imaging diagnostics of edgeplasma turbulence in magnetic fusion research, with a focus on theinstrumentation, diagnostic cross-checks, and interpretationissues. The gas puff imaging hardware, optics, and detectors aredescribed for about 10 GPI systems implemented over the past ~15years. Comparison of GPI results with other edge turbulence diagnosticresults are described and many common features are observed. Severalissues in the interpretation of GPI measurements are discussed, andpotential improvements in hardware and modeling are suggested.

Gas puff imaging↗
DOE OSTI2018

Fission TPC FY2018 Report

The primary motivation for the fission TPC experiment is to provide highly precise, accurate data for evaluation of the 239 Pu(n,f) cross section. As with any precision measurement careful validation of the results and rigorous quantification of the uncertainties is required. Our approach has been to make multiple experimental configuration changes and to use several analysis techniques to test both data correction models and detector performance. This report will focus one efforts during FY18 to validate the preliminary 239 Pu/ 235 U results that were released in FY17 and to make a preliminary measurement of the 238 U/ 239 Pu ratio. These validation efforts have led to the conclusion that further investigation and cross-checking is required before final results can be published

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2017

Environmental impact of electricity relocation: A quasi-natural experiment from interregional electricity transmission

Pollutants such as sulfur would concentrate in the source regions and thus the localized impacts are more obvious. Local balance of electricity by transporting coal has resulted in dense concentration of coal-fired power plants in load centers and caused severe environmental problems. Electricity relocation through interregional transmission is another choice for energy transportation to achieve electricity balance across regions and pollution mitigation. Using interregional electricity transmission (IRET) lines in China as a quasi-natural experiment, this paper assesses the environmental impact of electricity relocation. In the assessment, the grid organization of “province as executor” in China is considered because it affects the sphere of IRET's influence on pollution mitigation. Here we show the environmental benefits of electricity relocation. We find that, electricity relocation through interregional transmission leads to the growth rate of sulfur dioxide (SO{sub 2}) emission decreasing 7% in landing areas and Sichuan province benefits most from electricity relocation. It is interesting that there is no significant increase of SO{sub 2} emission growth rate in sending areas compared to counterfactuals if there had no IRET due to more integration of clean energy and improved emission efficiency in sending areas. Placebo study and robustness check show that the results are quite convincing. Therefore, IRET provides an appealing choice for China's environmental control in eastern region, and it is not necessarily at the cost of pollution in western region. The methodology can be applied to assess the environmental impacts of other program or policy elsewhere. - Highlights: •Proposing a model to assess the environmental impact of electricity relocation •Interregional electricity transmission in China provides a quasi-natural experiment. •Grid organization of “province as executor” is considered that affects sphere of IRET. •Providing insight about environmental necessity of IRET using China as a case study •The model can be used to assess environmental impacts of other program or policy.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Use of machine learning for a helium line intensity ratio method in Magnum-PSI

Optical emission spectroscopy (OES) of helium (He) line intensities has been used to measure the electron density, ne, and temperature, Te, in various plasma devices. In this study, a neural network with five hidden layers is introduced to model the relation between the OES data and ne/Te from laser Thomson scattering in the linear plasma device Magnum-PSI and compared to multiple regression analysis. It is shown that the neural network reduces the residual errors of prediction values (ne and Te) less than half those of the multiple regression analysis. We checked two different data splitting methods for training and validation data, i.e., with and without considering the unit of discharge. A comparison of the splitting methods suggests that the residual error will decrease to ~10% even for a new discharge data when accumulating a sufficient data set.

Kajita, Shin↗
DOE OSTI2014

A full-dimensional multilayer multiconfiguration time-dependent Hartree study on the ultraviolet absorption spectrum of formaldehyde oxide

Employing the multilayer multiconfiguration time-dependent Hartree (ML-MCTDH) method in conjunction with the multistate multimode vibronic coupling Hamiltonian (MMVCH) model, we perform a full dimensional (9D) quantum dynamical study on the simplest Criegee intermediate, formaldehyde oxide, in five lower-lying singlet electronic states. The ultraviolet (UV) spectrum is then simulated by a Fourier transform of the auto-correlation function. The MMVCH model is built based on extensive MRCI(8e,8o)/aug-cc-pVTZ calculations. To ensure a fast convergence of the final calculations, a large number of ML-MCTDH test calculations is performed to find an appropriate multilayer separations (ML-trees) of the ML-MCTDH nuclear wave functions, and the dynamical calculations are carefully checked to ensure that the calculations are well converged. To compare the computational efficiency, standard MCTDH simulations using the same Hamiltonian are also performed. A comparison of the MCTDH and ML-MCTDH calculations shows that even for the present not-too-large system (9D here) the ML-MCTDH calculations can save a considerable amount of computational resources while producing identical spectra as the MCTDH calculations. Furthermore, the present theoretical B{sup ~} {sup 1}A{sup ′}←X{sup ~} {sup 1}A{sup ′} UV spectral band and the corresponding experimental measurements [J. M. Beames, F. Liu, L. Lu, and M. I. Lester, J. Am. Chem. Soc. 134, 20045–20048 (2012); L. Sheps, J. Phys. Chem. Lett. 4, 4201–4205 (2013); W.-L. Ting, Y.-H. Chen, W. Chao, M. C. Smith, and J. J.-M. Lin, Phys. Chem. Chem. Phys. 16, 10438–10443 (2014)] are discussed. To the best of our knowledge, this is the first theoretical UV spectrum simulated for this molecule including nuclear motion beyond an adiabatic harmonic approximation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗