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At least 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

1995 OKI Household Activity and Travel Report Survey

The OKI Household Activity and Travel Report Survey 1995, conducted by Market Opinion Research, gathered household activity and travel data from 3,000 households within the OKI region (Ohio, Kentucky, and Indiana Council of Governments' service area). The region covers over 2,615 square miles and is home to 697,468 households (over 1.75 million people). The primary purpose of this study was to provide OKI with a new database of travel patterns and behavior to assist in updating the region's transportation models. Respondents were asked to report their activities for a 24-hour period from 3:00 a.m. to 3:00 a.m. on an assigned activity day. The survey included weekday assignments only from October 4, 1995, to November 30, 1995.

1Hz data↗
DOE OSTI2023

Predictive models of long COVID

Background: The cause and symptoms of long COVID are poorly understood. It is challenging to predict whether a given COVID-19 patient will develop long COVID in the future. Methods: We used electronic health record (EHR) data from the National COVID Cohort Collaborative to predict the incidence of long COVID. We trained two machine learning (ML) models — logistic regression (LR) and random forest (RF). Features used to train predictors included symptoms and drugs ordered during acute infection, measures of COVID-19 treatment, pre-COVID comorbidities, and demographic information. We assigned the ‘long COVID’ label to patients diagnosed with the U09.9 ICD10-CM code. The cohorts included patients with (a) EHRs reported from data partners using U09.9 ICD10-CM code and (b) at least one EHR in each feature category. We analysed three cohorts: all patients (n = 2,190,579; diagnosed with long COVID = 17,036), inpatients (149,319; 3,295), and outpatients (2,041,260; 13,741). Findings: LR and RF models yielded median AUROC of 0.76 and 0.75, respectively. Ablation study revealed that drugs had the highest influence on the prediction task. The SHAP method identified age, gender, cough, fatigue, albuterol, obesity, diabetes, and chronic lung disease as explanatory features. Models trained on data from one N3C partner and tested on data from the other partners had average AUROC of 0.75. Interpretation: ML-based classification using EHR information from the acute infection period is effective in predicting long COVID. SHAP methods identified important features for prediction. Cross-site analysis demonstrated the generalizability of the proposed methodology.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Practical galaxy morphology tools from deep supervised representation learning

Astronomers have typically set out to solve supervised machine learning problems by creating their own representations from scratch. We show that deep learning models trained to answer every Galaxy Zoo DECaLS question learn meaningful semantic representations of galaxies that are useful for new tasks on which the models were never trained. We exploit these representations to outperform several recent approaches at practical tasks crucial for investigating large galaxy samples. The first task is identifying galaxies of similar morphology to a query galaxy. Given a single galaxy assigned a free text tag by humans (e.g. ‘#diffuse’), we can find galaxies matching that tag for most tags. The second task is identifying the most interesting anomalies to a particular researcher. Our approach is 100 per cent accurate at identifying the most interesting 100 anomalies (as judged by Galaxy Zoo 2 volunteers). The third task is adapting a model to solve a new task using only a small number of newly labelled galaxies. Models fine-tuned from our representation are better able to identify ring galaxies than models fine-tuned from terrestrial images (ImageNet) or trained from scratch. We solve each task with very few new labels; either one (for the similarity search) or several hundred (for anomaly detection or fine-tuning). This challenges the longstanding view that deep supervised methods require new large labelled data sets for practical use in astronomy. To help the community benefit from our pretrained models, we release our fine-tuning code zoobot. Zoobot is accessible to researchers with no prior experience in deep learning.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Using spin alignment of inelastically excited nuclei in fast beams to assign spins: The spectroscopy of 13 O as a test case

Excited states in O 13 were investigated using inelastic scattering of an E / A = 69.5 MeV O 13 beam off of a Be 9 target. The excited states were identified in the invariant-mass spectra of the decay products. Both single-proton and sequential two-proton decays of the excited states were examined. Furthermore, for a number of the excited states, the protons were emitted with strong anisotropy where emissions transverse to the beam axis are favored. The measured proton-decay angular distributions were compared to predictions from distorted-wave Born-approximation calculations of the spin alignment which was shown to be largely independent of the excitation mechanism. The deduced O 13 level scheme is compared to ab initio no-core shell model with continuum predictions. The lowest-energy excited states decay isotropically consistent with predictions of strong proton 1 s 1 / 2 structure. Above these states in the level scheme, we observed a number of higher-spin states not predicted within the model. Possibly these are associated with rotational bands built on deformed cluster configurations predicted by antisymmetrized molecular dynamics calculations. The spin alignment mechanism is shown to be useful for making spin assignments and may have widespread use.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Multi-objective Eco-Routing Model Development and Evaluation for Battery Electric Vehicles

This paper develops a multi-objective eco-routing algorithm (eco- and travel time-optimum routing) for battery electric vehicles (BEVs) and internal combustion engine vehicles (ICEVs) and investigates the network-wide impacts of the proposed multi-objective Nash optimum (user equilibrium) traffic assignment on a large-scale network. Unlike ICEVs, BEVs are more energy efficient on low-speed arterial trips compared with highway trips. Different energy consumption patterns require different eco-routing strategies for ICEVs and BEVs. This study found that single-objective eco-routing could significantly reduce the energy consumption of BEVs but also significantly increase their average travel time. Consequently, the study developed a multi-objective routing model (eco- and travel time-routing) to improve both energy and travel time measures. The model introduced a link cost function that uses the specification of the value of time and the cost of fuel/energy. The simulation study found that multi-objective routing could reduce BEV energy consumption by 13.5%, 14.2%, 12.9%, and 10.7%, as well as ICEV fuel consumption by 0.1%, 4.3%, 3.4%, and 10.6% for “not congested, “slightly congested,”“moderately congested,” and “highly congested” conditions, respectively. The study also found that multi-objective user equilibrium routing reduced the average vehicle travel time by up to 10.1% compared with the standard user equilibrium traffic assignment for highly congested conditions, producing a solution closer to the system optimum traffic assignment. The results indicate that the proposed multi-objective eco-routing strategy can reduce vehicle fuel/energy consumption effectively with minimum impacts on travel times for both BEVs and ICEVs.

Engineering↗
DOE OSTI2024

Time-resolved quantification of key species and mechanistic insights in low-temperature tetrahydrofuran oxidation

Here, we investigate the kinetics and report the time-resolved concentrations of key chemical species in the oxidation of tetrahydrofuran (THF) at 7500 torr and 450–675 K. Experiments are carried out using high-pressure multiplexed photoionization mass spectrometry (MPIMS) combined with tunable vacuum ultraviolet radiation from the Berkely Lab Advanced Light Source. Intermediates and products are quantified using reference photoionization (PI) cross sections, when available, and constrained by a global carbon balance tracking approach at all experimental temperatures simultaneously for the species without reference cross sections. From carbon balancing, we determine time-resolved concentrations for the ROO˙ and ˙OOQOOH radical intermediates, butanedial, and the combined concentration of ketohydroperoxide (KHP) and unsaturated hydroperoxide (UHP) products stemming from the ˙QOOH + O 2 reaction. Furthermore, we quantify a product that we tentatively assign as fumaraldehyde, which arises from UHP decomposition via H 2 O or ˙OH + H loss. The experimentally derived species concentrations are compared with model predictions using the most recent literature THF oxidation mechanism of Fenard et al., (Combust. Flame, 2018, 191, 252–269). Our results indicate that the literature mechanism significantly overestimates THF consumption and the UHP + KHP concentration at our conditions. The model predictions are sensitive to the rate coefficient for the ROO˙ isomerization to ˙QOOH, which is the gateway for radical chain propagating and branching pathways. Comparisons with our recent results for cyclopentane (Demireva et al., Combust. Flame, 2023, 257, 112506) provide insights into the effect of the ether group on reactivity and highlight the need to determine accurate rate coefficients of ROO˙ isomerization and subsequent reactions.

Demireva, Maria↗
DOE OSTI2025

Reviewing Incident Neutron Energy assignments in 238 U(n,f) Fission Yield Data

Fission yield evaluations rely not only on precise measurements, but also on clear documentation of experimental conditions especially the energy of incident neutrons inducing fission. In the EXFOR database, following the convention adopted in past evaluations, the incident neutron energy has traditionally been divided in only three energy groups: thermal, fast and 14 MeV. The information is stored in the EN-DUMMY field, which often serves as a placeholder in the presence of broad-spectrum or reactor-based sources. This work reviews 238 U(n,f) entries in EXFOR that use EN-DUMMY, identifying cases where better energy estimates can be made based on the original publications, facility characteristics, or reconstructed neutron spectra. We assign new cross-section-weighted average energies where possible. The revised independent and cumulative fission yield data are compiled for future use in model development and evaluation efforts.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Model-Free Building Temperature Control and Power Allocation Under Measurement Time Delays

Taking a step towards a greener planet has created an increased need for a higher integration of renewable energy resources into the electric grid. Nonetheless, the intermittency and uncertainty associated with renewable generation have slowed down this integration. Demand response (DR) has been recently adopted to address this challenge by utilizing demand side flexibility and enabling the participation of many grid-interactive efficient buildings (GEBs). However, existing DR methods require significant modeling and/or training efforts and are computationally expensive. To address the aforementioned issues, we propose a model-free control (MFC)-based strategy that is robust to the time delays in the temperature measurements of the thermostatically controlled loads (TCLs). It assigns to each GEB a local controller to maintain the TCLs’ temperatures within desired comfort levels, while the load aggregator (LA) allocates the assigned reference power provided by the distribution system operator (DSO) to support a specific grid service, such as demand peak reduction, load shifting, balancing supply and demand, and consuming the solar photovoltaic power locally. We investigate the effects of such loss of information on the local control action as well as on meeting the power allocation constraint. We conclude that, for an appropriate choice of design parameters, the proposed MFC controller is satisfactorily robust to measurement time delays.

Telsang, Bhagyashri↗
DOE OSTI2023

Uncertain characterization of reservoir fluids due to brittleness of equation of state regression

Equations of state (EoS) play a central role in modeling the phase equilibrium of fluid mixtures. Their parameterization involves fitting a model to experimental data, i.e., solving a nonlinear, non-convex, multivariate optimization problem. The latter requires one to select design variables, domains of definition for each variable, and weights assigned to individual measurements. We demonstrate that subjective choices of an optimization algorithm and an initial guess also impact the regression process. Consequently, EoS predictions are fundamentally uncertain even after the EoS tuning to a limited set of experimental data points. We demonstrate this observation for two hydrocarbon reservoir fluids, in which five properties of the heaviest carbon fraction are treated as design variables. While all the optimization algorithms and initial guesses match experimental data for the gas and liquid properties, the resulting EoS parameterizations lead to dramatically different predictions of the fluid’s thermophysical behavior in the unsampled pressure and temperature regions. In conclusion, we propose the probabilistic treatment of design variables to quantify the predictive uncertainty of the resulting fluid models.

15 GEOTHERMAL ENERGY↗
DOE OSTI2022

Exploring ENSO-Induced Anomalies over North America in Historical and Future Climate Simulations That Use HadGEM2-ESM Output to Drive WRF

Projected changes to the El Niño Southern Oscillation (ENSO) climate mode have been explored using global Earth system models (ESMs). Regional expressions of such changes have yet to be fully advanced and may require the use of regional downscaling. Here, we employ regional climate modeling (RCM) using the Weather Research and Forecasting (WRF) model at convection-permitting resolution and nested in output from the HadGEM2 ESM. We quantify ENSO teleconnections to temperature and precipitation anomalies in historical and future climate scenarios over eastern North America. Two paired simulations are run, a strong El Niño (positive ENSO phase) and a weak La Niña (negative ENSO phase), for the historical and future years. The HadGEM2 direct output and HadGEM2-WRF simulation output are compared to the anomalies derived from the NOAA ENSO Climate Normals dataset. The near-surface temperature and precipitation differences by ENSO phase, as represented by the HadGEM2-WRF historical simulations, show a poor degree of association with the NOAA ENSO Climate Normals, in part because of the large biases in the HadGEM2 model. Downscaling with the WRF model does improve the agreement with the observations, and large discrepancies remain. The model chain HadGEM2-WRF reverses the sign of the ENSO phase response over eastern North America under simulations of the future climate with high greenhouse gas forcing, but due to the poor agreement with the NOAA ENSO Climate Normals it is difficult to assign confidence to this prediction.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Towards understanding the formation of internal fragments generated by collisionally activated dissociation for top-down mass spectrometry

Top-down mass spectrometry (TD-MS) generates fragment ions that returns information on the polypeptide amino acid sequence. In addition to terminal fragments, internal fragments that result from multiple cleavage events can also be formed. Traditionally, internal fragments are largely ignored due to a lack of available software to reliably assign them, mainly caused by a poor understanding of their formation mechanism. To accurately assign internal fragments, their formation process needs to be better understood. Here we applied a statistical method to compare fragmentation patterns of internal and terminal fragments of peptides and proteins generated by collisionally activated dissociation (CAD). Internal fragments share similar fragmentation propensities with terminal fragments (e.g., enhanced cleavages N-terminal to proline and C-terminal to acidic residues), suggesting that their formation follows conventional CAD pathways. Internal fragments should be generated by subsequent cleavages of terminal fragments and their formation can be explained by the well-known mobile proton model. Additionally, internal fragments can be coupled with terminal fragments to form complementary product ions that span the entire protein sequence. These enhance our understanding of internal fragment formation and can help improve sequencing algorithms to accurately assign internal fragments, which will ultimately lead to more efficient and comprehensive TD-MS analysis of proteins and proteoforms.

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

FRISM (FReight Integrated Simulation Model) [SWR-24-40]

FRISM simulates day-to-day freight activities including end-consumer shopping, distribution channel, and carrier operation with e-commerce dynamics between passenger and freight travel. It outputs an assignment of different shipments to carriers and tour plans of the carriers' vehicles to transport shipments from their origins to their destinations.

Ugirumurera, Juliette↗
DOE OSTI2021

Multi-objective Eco-Routing Model Development and Evaluation for Battery Electric Vehicles.

This paper develops a multi-objective eco-routing algorithm (combined eco- and travel time-optimum routing) for battery electric vehicles (BEVs) and internal combustion engine vehicles (ICEVs) and investigates the network-wide impacts of the proposed multi-objective Nash optimum (user equilibrium) traffic assignment on a large-scale network. Eco-routing is a technique that finds the most energy efficient route. ICEV and BEV energy consumption patterns are significantly different with regard to their sensitivity to driving cycles. Unlike ICEVs, BEVs are more energy efficient on low-speed arterial trips compared to highway trips. Different energy consumption patterns require different eco-routing strategies for ICEVs and BEVs. This study found that single objective eco-routing could significantly reduce the energy consumption of BEVs but also significantly increase their average travel time. Consequently, the study developed a multi-objective routing model (eco- and travel time-routing) to improve both energy and travel time measures. The model introduced a link cost function that uses the specification of the value of time and the cost of fuel/energy. The simulation study found that multi-objective routing could reduce the BEV energy consumption by 13.5%, 14.2%, 12.9%, and 10.7%, as well as ICEV fuel consumption by 0.1%, 4.3%, 3.4%, and 10.6% for “not congested, “slightly congested,” “moderately congested,” and “highly congested” conditions, respectively. The study also found that multi-objective user equilibrium routing reduced the average vehicle travel time by up to 10.1% compared to the standard user equilibrium traffic assignment for highly congested conditions, producing a solution closer to the system optimum traffic assignment. The results indicate that the proposed multi-objective eco-routing strategy can reduce vehicle fuel/energy consumption effectively with minimum impacts on travel times for both BEVs and ICEVs.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

CODEX clusters

Context: Large area catalogs of galaxy clusters constructed from ROSAT All-Sky Survey provide the basis for our knowledge of the population of clusters thanks to long-term multiwavelength efforts to follow up observations of these clusters. Aims: The advent of large area photometric surveys superseding previous, in-depth all-sky data allows us to revisit the construction of X-ray cluster catalogs, extending the study to lower cluster masses and higher redshifts and providing modeling of the selection function. Methods: We performed a wavelet detection of X-ray sources and made extensive simulations of the detection of clusters in the RASS data. We assigned an optical richness to each of the 24 788 detected X-ray sources in the 10 382 square degrees of the Baryon Oscillation Spectroscopic Survey area using red sequence cluster finder redMaPPer version 5.2 run on Sloan Digital Sky Survey photometry. We named this survey COnstrain Dark Energy with X-ray (CODEX) clusters. Results: We show that there is no obvious separation of sources on galaxy clusters and active galactic nuclei (AGN) based on the distribution of systems on their richness. This is a combination of an increasing number of galaxy groups and their selection via the identification of X-ray sources either by chance or by groups hosting an AGN. To clean the sample, we use a cut on the optical richness at the level corresponding to the 10% completeness of the survey and include it in the modeling of the cluster selection function. We present the X-ray catalog extending to a redshift of 0.6. Conclusions: The CODEX suvey is the first large area X-ray selected catalog of northern clusters reaching fluxes of 10 –13 ergs s –1 cm –2 . We provide modeling of the sample selection and discuss the redshift evolution of the high end of the X-ray luminosity function (XLF). Our results on z < 0.3 XLF agree with previous studies, while we provide new constraints on the 0.3 < z < 0.6 XLF. We find a lack of strong redshift evolution of the XLF, provide exact modeling of the effect of low number statistics and AGN contamination, and present the resulting constraints on the flat ΛCDM.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Spectroscopy of states in 136 Ba using the 138 Ba(p,t) reaction

Background: The 136 Ba isotope is the daughter nucleus in 136 Xe $ββ$ decay. It also lies in a shape transitional region of the nuclear chart, making it a suitable candidate to test a variety of nuclear models. Purpose: To obtain spectroscopic information on states in 136 Ba, which will allow a better understanding of its low-lying structure. These data may prove useful to constrain future 136 Xe → 136 Ba neutrinoless $ββ$ decay matrix element calculations. Methods: Here, a 138 Ba(p, t) reaction was used to populate states in 136 Ba up to approximately 4.6 MeV in excitation energy. The tritons were detected using a high-resolution Q3D magnetic spectrograph. A distorted wave Born approximation analysis was performed for the measured triton angular distributions. Results: 102 excited states in 136 Ba were observed, out of which 52 are reported for the first time. Definite spin-parity assignments are made for 26 newly observed states, while previously ambiguous assignments for ten other states are resolved. Together with other available data, the results are used to determine level densities in 136 Ba. These were compared with theory predictions, obtained using shell model calculations with Hamiltonians previously used for 136 Xe neutrinoless $ββ$ decay matrix element evaluations. Conclusions: The shell model predicted level densities agree reasonably well for the two Hamiltonians. However the results for theory and experiment are found to agree only at lower energies, diverging from one another for the higher lying states, with the discrepancy increasing with energy. This is presumably because of lower production cross sections for a majority of the higher-lying predicted states and the experimental limitations in resolving a large number of nearly degenerate states predicted by the theory.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Dark Energy Survey Year 3 Results: Galaxy mock catalogs for BAO analysis

The calibration and validation of scientific analysis in simulations is a fundamental tool to ensure unbiased and robust results in observational cosmology. In particular, mock galaxy catalogs are a crucial resource to achieve these goals in the measurement of baryon acoustic oscillation (BAO) in the clustering of galaxies. Here we present a set of 1952 galaxy mock catalogs designed to mimic the Dark Energy Survey Year 3 BAO sample over its full photometric redshift range 0.6 < zphoto < 1.1. The mocks are based upon 488 ICE-COLA fast N-body simulations of full-sky light cones and were created by populating halos with galaxies, using a hybrid halo occupation distribution – halo abundance matching model. This model has ten free parameters, which were determined, for the first time, using an automatic likelihood minimization procedure. We also introduced a novel technique to assign photometric redshift for simulated galaxies, following a two-dimensional probability distribution with VIMOS Public Extragalactic Redshift Survey data. The calibration was designed to match the observed abundance of galaxies as a function of photometric redshift, the distribution of photometric redshift errors, and the clustering amplitude on scales smaller than those used for BAO measurements. An exhaustive analysis was done to ensure that the mocks reproduce the input properties. Finally, mocks were tested by comparing the angular correlation function w(θ), angular power spectrum Cℓ, and projected clustering ξp(r⊥) to theoretical predictions and data. The impact of volume replication in the estimate of the covariance is also investigated. The success in accurately reproducing the photometric redshift uncertainties and the galaxy clustering as a function of redshift render this mock creation pipeline as a benchmark for future analyses of photometric galaxy surveys.Key words: catalogs / large-scale structure of Universe / galaxies: distances and redshifts / Galaxy: halo / methods: numerical

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Uncertainty-aware Continuous Implicit Neural Representations for Remote Sensing Object Counting

Many existing object counting methods rely on density map estimation (DME) of the discrete grid representation by decoding extracted image semantic features from designed convolutional neural networks (CNNs). Relying on discrete density maps not only leads to information loss dependent on the original image resolution, but also has a scalability issue when analyzing high-resolution images with cubically increasing memory complexity. Furthermore, none of the existing methods can offer reliable uncertainty quantification (UQ) for the derived count estimates. To overcome these limitations, we design UNcertainty-aware, hypernetwork-based Implicit neural representations for Counting (UNIC) to assign probabilities and the corresponding counting confidence over continuous spatial coordinates. We derive a sampling-based Bayesian counting loss function and develop the corresponding model training algorithm. UNIC outperforms existing methods on the Remote Sensing Object Counting (RSOC) dataset with reliable UQ and improved interpretability of the derived count estimates. Our code is available at https://github.com/SiyuanXu-tamu/UNIC.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Gaussian mixture model clustering algorithms for the analysis of high-precision mass measurements

The development of the phase-imaging ion-cyclotron resonance (PI-ICR) technique for use in Penning trap mass spectrometry (PTMS) increased the speed and precision with which PTMS experiments can be carried out. In PI-ICR, data sets of the locations of individual ion hits on a detector are created showing how ions cluster together into spots according to their cyclotron frequency. Ideal data sets would consist of a single, 2D-spherical spot with no other noise, but in practice data sets typically contain multiple spots, non-spherical spots, or significant noise, all of which can make determining the locations of spot centers non-trivial. A method for assigning groups of ions to their respective spots and determining the spot centers is therefore essential for further improving precision and confidence in PI-ICR experiments. Here, we present the class of Gaussian mixture model (GMM) clustering algorithms as an optimal solution. We show that on simulated PI-ICR data, several types of GMM clustering algorithms perform better than other clustering algorithms over a variety of typical scenarios encountered in PI-ICR. The mass spectra of 163Gd, 163 mGd, 162 Tb, and 162 mTb measured using PI-ICR at the Canadian Penning trap mass spectrometer were checked using GMMs, producing results that were in close agreement with the previously published values.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗