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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 1,243 records · Page 69
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

SU-F-T-104: Determining the NTCP Parameters of Pharyngeal Constrictors and Proximal Esophagus for Radiation Induced Swallowing Problems Recorded Six Months After Radiation Therapy for Head and Neck Tumors

Purpose: To estimate the radiobiological parameters of four NTCP models that describe the dose-response relations of pharyngeal constrictors and proximal esophagus regarding the severity of patient reported swallowing problems 6 months post chemo-radiotherapy. To identify the section/structure that best correlates with the manifestation of the clinical endpoints. Finally, to compare the goodness-of-fit of those models. Methods: Forty-three patients were treated on a prospective multi-institutional phase II study for oropharyngeal squamous cell carcinoma. All the patients received 60 Gy IMRT and they reported symptoms using the novel patient reported outcome version of the CTCAE. We derived the individual patient dosimetric data of superior, medium and inferior sections of pharyngeal constrictors (SPC, MPC and IPC), superior and inferior sections of esophagus (SES and IES) as separate structures as well as combinations. The Lyman-Kutcher-Burman (LKB), Relative Seriality (RS), Logit and Relative Logit (RL) NTCP models were used to fit the patient data. The fitting of the different models was assessed through the area under the receiver operating characteristic curve (AUC) and the Odds Ratio methods. Results: The AUC values were highest for the SPC for Grade ≥ 2 (0.719 for the RS and RL models, and 0.716 for LKB and Logit). For Grade ≥ 1, the respective values were 0.699 for RS, LKB and Logit and 0.676 for RL. For MPC the AUC values varied between 0.463–0.477, for IPC between 0.396–0.458, for SES between 0.556–0.613 and for IES between 0.410–0.519. The Odds Ratio for the SPC was 15.6 (1.7–146.4) for RS, LKB and Logit for NTCP of 55%. Conclusion: All the examined NTCP models could fit the clinical data with similar accuracy. The SPC appear to correlate best with the clinical endpoints of swallowing problems. A prospective study could establish the use of NTCP values of SPC as a constraint in treatment planning.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Electron energy partition in the ‘above-the-looptop’ solar hard X-ray sources

The presentation begins by considering the non-thermal fraction of electron energies (R ε ) in 'above-the-looptop' (ALT). Several spectral models area considered: isothermal model, power-law, and the newly derived kappa distribution. Technically, all 3 non-thermal models can fit the data. In the discussion of flare scenario, energy partition, energization mechanism, and collisionality are considered. It is concluded that the kappa distribution works (R ε ≲ 50%), magnetic reconnection scenario works, and Coulomb collisions may reduce the non-thermal fraction of electron energies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2012

THE NATURE OF THE UV/OPTICAL EMISSION OF THE ULTRALUMINOUS X-RAY SOURCE IN HOLMBERG II

We report on UV and X-ray spectroscopy and broadband optical observations of the ultraluminous X-ray source in Holmberg II. Fitting various stellar spectral models to the combined, non-simultaneous data set, we find that normal metallicity stellar spectra are ruled out by the data, while low-metallicity, Z = 0.1 Z{sub Sun }, late O-star spectra provide marginally acceptable fits, if we allow for the fact that X-ray ionization from the compact object may reduce or eliminate UV absorption/emission lines from the stellar wind. By contrast, an irradiated disk model fits both UV and optical data with {chi}{sup 2}/dof = 175.9/178, and matches the nebular extinction with a reddening of E(B - V) = 0.05{sup +0.05}{sub -0.04}. These results suggest that the UV/optical flux of Holmberg II X-1 may be dominated by X-ray irradiated disk emission.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Better practices for inferring ecosystem water use strategy from eddy covariance data

Eddy covariance data are critical for inferring ecosystem water use strategies. Yet, such inferences are sensitive to a range of assumptions applied across studies, hindering our understanding of water use strategies within and across eddy covariance sites. A recent analysis across 151 FLUXNET2015 and AmeriFlux-FLUXNET datasets found that poor model performance was the key driver of non-robust inferences of ecosystem water use strategies. Here, we leverage this previous analysis to (i) identify the specific assumptions that improve inference model performance across most sites, (ii) explain the mechanisms behind the performance improvements, and (iii) check whether better performance improves water use inference. We find that the common practice of fitting a model to canopy conductance (G c ) derived from the evapotranspiration (ET) observations, rather than to observed ET itself, artificially amplifies data errors and degrades the model performance. Next, accounting for vegetation dynamics by applying a growing season filter or incorporating satellite LAI data improves performance, but the former practice may remove soil water stress periods. Lastly, using the leaf-to-air vapor pressure deficit (VPD l ) derived from ET observations as a model input may artificially inflate performance. Based on these results, we recommend selecting observed ET (rather than derived G c ) as the response variable, carefully accounting for vegetation dynamics, and avoiding derived VPD l as a model input; these best practices improve model performance by c. 20% and robustness by c. 80% across all eddy covariance sites. Nevertheless, the performance improvements do not always correspond to more robust inference of water use strategies, as model parameter selection and surface energy budget closure corrections still strongly influence the ecosystem water use parameter estimation in a site-specific manner.

AmeriFlux↗
DOE OSTI2022

Bridging the Gap between the X-ray Absorption Spectroscopy and the Computational Catalysis Communities in Heterogeneous Catalysis: A Perspective on the Current and Future Research Directions

X-ray absorption spectroscopy (XAS) [extended X-ray absorption fine structure (EXAFS) and X-ray absorption near-edge structure (XANES)] is a key technique within the heterogeneous catalysis community to probe the structure and properties of the active site(s) for a diverse range of catalytic materials. Furthermore, the interpretation of the raw experimental data to derive an atomistic picture of the catalyst requires modeling and analysis; the EXAFS data are compared to a model, and a goodness of fit parameter is used to judge the best fit. This EXAFS modeling can often be nontrivial and time-consuming; overcoming or improving these limitations remains a central challenge for the community. Considering these limitations, this Perspective highlights how recent developments in analysis software, increased availability of reliable computational models, and application of data science tools can be used to improve the speed, accuracy, and reliability of EXAFS interpretation. In particular, we emphasize the advantages of combining theory and EXAFS as a unified technique that should be treated as a standard (when applicable) to identify catalytic sites and not two separate complementary methods. Building on the recent trends in the computational catalysis community, we also present a community-driven approach to adopt FAIR Guiding Principles for the collection, analysis, dissemination, and storage of XAS data. Written with both the experimental and theory audience in mind, we provide a unified roadmap to foster collaborations between the two communities.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Rapid early gas accretion for the inner Galactic disc: A case for short accretion timescale

Recent observations of the Milky Way and galaxies at high redshifts suggest that galaxy discs were already in place soon after the Big Bang. While the gas infall history of the Milky Way in the inner disc has long been assumed to be characterised by a short accretion timescale, this has not been directly constrained using observations. Using data for the inner regions of the Milky Way recently produced by APOGEE and Gaia and of unprecedented quantity and quality, we aim to derive strong constraints on the infall history of the inner (< 6 kpc) Galaxy (with a focus on stars between 4 and 6 kpc, which we show is an appropriate proxy for the entire inner disc). We implemented gas infall into a chemical evolution model of the Galaxy disc, and used a Schmidt–Kennicutt law to connect the infall to the star formation. We explore a number of models, and two different formulations of the infall law. In one formulation, the infall is non-parametric, and in the other the infall has an explicitly exponential form. We fit the model parameters to the time–[Si/Fe] distribution of solar vicinity stars, and the metallicity and [Si/Fe] distribution function of stars with a galactocentric radius of between 4 and 6 kpc from APOGEE. Our results point to a fast, early gas accretion, and an upper limit on the accretion timescale of around 2 Gyr in the inner disc of the Milky Way. This suggests that at least half the baryons were in place within 2–3 Gyr of the Big Bang, and that half the stars of the inner disc formed within the first 5 Gyr, during the thick disc formation phase. This implies that the stellar mass of the inner disc is dominated by the thick disc, supporting our previous work, and that the gas accretion onto the inner disc was rapid and early.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Transferability of data-driven, many-body models for CO 2 simulations in the vapor and liquid phases

Here, extending on the previous work by Riera et al. [J. Chem. Theory Comput. 16, 2246–2257 (2020)], we introduce a second generation family of data-driven many-body MB-nrg models for CO 2 and systematically assess how the strength and anisotropy of the CO 2 –CO 2 interactions affect the models’ ability to predict vapor, liquid, and vapor–liquid equilibrium properties. Building upon the many-body expansion formalism, we construct a series of MB-nrg models by fitting one-body and two-body reference energies calculated at the coupled cluster level of theory for large monomer and dimer training sets. Advancing from the first generation models, we employ the charge model 5 scheme to determine the atomic charges and systematically scale the two-body energies to obtain more accurate descriptions of vapor, liquid, and vapor–liquid equilibrium properties. Challenges in model construction arise due to the anisotropic nature and small magnitude of the interaction energies in CO 2 , calling for the necessity of highly accurate descriptions of the multidimensional energy landscape of liquid CO 2 . These findings emphasize the key role played by the training set quality in the development of transferable, data-driven models, which, accurately representing high-dimensional many-body effects, can enable predictive computer simulations of molecular fluids across the entire phase diagram.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

The Latent Dirichlet Allocation model applied to airborne LiDAR data: A case study on mapping forest degradation associated with fragmentation and fire in the Amazon region

1. LiDAR data are being increasingly used to provide a detailed characterization of the vertical profile of forests. This characterization enables the generation of new insights on the influence of environmental drivers and anthropogenic disturbances on forest structure as well as on how forest structure influences important ecosystem functions and services. Unfortunately, extracting information from LiDAR data in a way that enables the spatial visualization of forest structure, as well as its temporal changes, is challenging due to the high dimensionality of these data. 2. In this study, we show how the Latent Dirichlet Allocation model applied to LiDAR data (LidarLDA) can be used to identify forest structural types and how the relative abundance of these forest types changes throughout the landscape. The code to fit this model is made available through the open-source r package LidarLDA in github. We illustrate the use of LidarLDA both with simulated data and data from a large-scale fire experiment in the Brazilian Amazon region. 3. Using simulated data, we demonstrate that LidarLDA accurately identifies the number of forest types as well as their spatial distribution and absorptance probabilities. For the empirical data, we found that LidarLDA detects both landscape-level patterns in forest structure as well as the strong interacting effect of fire and forest fragmentation on forest structure based on the experimental fire plots. More specifically, LidarLDA reveals that proximity to forest edge exacerbates the impact of fires, and that burned forests remain structurally different from unburned areas for at least 7 years, even when burned only once. Importantly, LidarLDA generates insights on the 3D structure of forest that cannot be obtained using more standard approaches that just focus on top-of-the-canopy information (e.g. canopy height models based on LiDAR data). 4. By enabling the mapping of forest structure and its temporal changes, we believe that LidarLDA will be of broad utility to the ecological research community.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Light output measurements and computational models of microcolumnar CsI scintillators for x-ray imaging

Purpose: The authors report on measurements of light output and spatial resolution of microcolumnar CsI:Tl scintillator detectors for x-ray imaging. In addition, the authors discuss the results of simulations aimed at analyzing the results of synchrotron and sealed-source exposures with respect to the contributions of light transport to the total light output. Methods: The authors measured light output from a 490-μm CsI:Tl scintillator screen using two setups. First, the authors used a photomultiplier tube (PMT) to measure the response of the scintillator to sealed-source exposures. Second, the authors performed imaging experiments with a 27-keV monoenergetic synchrotron beam and a slit to calculate the total signal generated in terms of optical photons per keV. The results of both methods are compared to simulations obtained with hybridMANTIS, a coupled x-ray, electron, and optical photon Monte Carlo transport package. The authors report line response (LR) and light output for a range of linear absorption coefficients and describe a model that fits at the same time the light output and the blur measurements. Comparing the experimental results with the simulations, the authors obtained an estimate of the absorption coefficient for the model that provides good agreement with the experimentally measured LR. Finally, the authors report light output simulation results and their dependence on scintillator thickness and reflectivity of the backing surface. Results: The slit images from the synchrotron were analyzed to obtain a total light output of 48 keV{sup −1} while measurements using the fast PMT instrument setup and sealed-sources reported a light output of 28 keV{sup −1}. The authors attribute the difference in light output estimates between the two methods to the difference in time constants between the camera and PMT measurements. Simulation structures were designed to match the light output measured with the camera while providing good agreement with the measured LR resulting in a bulk absorption coefficient of 5 × 10{sup −5} μm{sup −1}. Conclusions: The combination of experimental measurements for microcolumnar CsI:Tl scintillators using sealed-sources and synchrotron exposures with results obtained via simulation suggests that the time course of the emission might play a role in experimental estimates. The procedure yielded an experimentally derived linear absorption coefficient for microcolumnar Cs:Tl of 5 × 10{sup −5} μm{sup −1}. To the author’s knowledge, this is the first time this parameter has been validated against experimental observations. The measurements also offer insight into the relative role of optical transport on the effective optical yield of the scintillator with microcolumnar structure.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

People who inject drugs in metropolitan Chicago: A meta-analysis of data from 1997-2017 to inform interventions and computational modeling toward hepatitis C microelimination

Progress toward hepatitis C virus (HCV) elimination in the United States is not on track to meet targets set by the World Health Organization, as the opioid crisis continues to drive both injection drug use and increasing HCV incidence. A pragmatic approach to achieving this is using a microelimination approach of focusing on high-risk populations such as people who inject drugs (PWID). Computational models are useful in understanding the complex interplay of individual, social, and structural level factors that might alter HCV incidence, prevalence, transmission, and treatment uptake to achieve HCV microelimination. However, these models need to be informed with realistic sociodemographic, risk behavior and network estimates on PWID. We conducted a meta-analysis of research studies spanning 20 years of research and interventions with PWID in metropolitan Chicago to produce parameters for a synthetic population for realistic computational models (e.g., agent-based models). We then fit an exponential random graph model (ERGM) using the network estimates from the meta-analysis in order to develop the network component of the synthetic population.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

A measurement of the proton’s spin structure function g2 at low Q2

JLab E08-027, a measurement of g2p and the longitudinal-transverse (LT) spin polarizability, successfully collected data from March to May, 2012. Nucleon spin structure study has been an active research area, which has attracted a very large effort from both experimentalists and theorists. The spin structure study for the last 2 decades has provided us with many exciting and often surprising results. Recently, new precision results in the low-to-intermediate momentum transfer Q2 region from JLab have provided extensive information on the nucleon structure in the confinement region and the transition region between asymptotic free to confinement. In particular, the extensive comparisons of experimental results with Chiral Perturbation Theory (the effective theory of QCD at low energy) calculations show general good agreements, but strong disagreement in the case of the neutron LT spin polarizability. This experiment completed the measurements of gp2 and the LT spin polarizability on the proton in the low-to-intermediate Q2 region. The experiment used a polarized proton (NH3) target for the first time in Hall A. Scattered electrons were detected by a pair of Hall A high resolution spectrometer (HRS) with a pair of septum magnets. To avoid too much depolarization of the target, beam current was limited to 50-100 nA during the experiment. Since the existing beam current monitors (BCMs), beam position monitors (BPMs) and calibration methods did not work at such a low current range, new BPM and BCM receivers were designed and used for current condition. A pair of super-harps and a tungsten calorimeter were installed to calibrate the BPMs and BCMs. To compensate for the effect of the 2.5/5T transverse magnet field, two chicane dipole magnets were installed. A pair of slow rasters were installed for the first time in Hall A, combining with a pair of fast raster. The standard Hall A DAQ system and the improved high resolution DAQ system were used to record the detector information and the helicity dependent beam information, respectively. In order to achieve the required accuracy of the beam position and angle and reconstruct them event by event at the target location, the data of the BPMs and harps were carefully analyzed. The final uncertainty of BCM after the calibration using the tungsten calorimeter is below 1%, which is important for the asymmetry extraction. Before the acceptance and the dilution factor are available, the models from fitting to the world data were used instead to extract the unpolarized cross section and the dilution factor. The longitudinal and transverse physics asymmetries were extracted and compared with the model, with the study of the radiative correction. The preliminary g1 and g2 results were then extracted using the measured asymmetry and the model.

Zhu, Pengjia↗
DOE OSTI2024

DECOVALEX-2023: Task C Final Report

The Full-scale Emplacement (FE) heater experiment at the Mont Terri Underground Rock Laboratory (URL) was designed and conducted by Nagra to replicate an emplacement tunnel of Nagra’s reference repository design at 1:1 scale. Alongside testing the technical feasibility of constructing disposal tunnels, emplacing waste containers in the tunnels and then backfilling them, the main goals of the FE experiment are (1) to obtain a better understanding of the coupled effects of induced thermo-hydro-mechanical (THM) processes that may occur and (2) to validate existing coupled THM models (Müller et al., 2017). A key aspect of ensuring safety for repositories located in low-permeability rock involves minimizing any damage to the rock itself, thereby preserving its integrity and promoting a stable environment Amongst a number of processes that could damage the rock is the increase in pore pressure due to thermal loading caused by heat emitted from the waste. To reduce the potential damage of the rock, it is important to analyse the evolution of heat over time due to the heat load of the containers and assess possible consequences by coupled THM models. The aim of Task C of DECOVALEX-2023 was to build 3D numerical models of the FE experiment, focussing in particular on the heating induced pore pressure change in the Opalinus Clay. Data from a large number of sensors were available from the FE experiment for model comparison. These sensors measured temperature and relative humidity in the bentonite around the heaters, and temperature, pressure and displacement/strain in the surrounding Opalinus clay. Data were available from the start of excavation (April 2012) up to August 2020 for most sensors (more than 5 years from the start of heating in December 2014). To fulfil the overall aim of the task, the work was broken down into a number of steps, starting with simpler models to build confidence in each team’s approach and then moving to more complex models that better represent the FE experiment. Step 0 consisted of 2D benchmark models, gradually increasing the number of processes that are represented from thermal (T) only models in Step 0a, to coupled thermal hydraulic (TH) models in Step 0b with a representation of changing porosity, to coupled thermo-hydro-mechanical (THM) models in Step 0c, where porosity changes are calculated by the mechanical model. A detailed specification of processes, parameters, initial and boundary conditions was provided for this step, with the ambition that all teams would work towards close agreement in their model results, thus building confidence in the model implementations. vi It was not straightforward to achieve agreement between the teams, so additional steps (Step 0b2, 0b3, 0c2, 0c3) were added along with derivation of some analytical solutions against which the models could be compared. The reasons for the differences between teams were investigated and found to be caused primarily by different conceptual model assumptions (including temperature dependence of the thermal expansion of water), different model formulations (including porosity evolution) and differences in modelled domain sizes, boundary conditions and grid discretisation. This demonstrates that comparisons between multiple modelling teams and/or comparison with analytical results and experimental data are highly beneficial in providing an indication of uncertainty in model predictions. At the conclusion of Step 0, almost all teams had achieved a close agreement in model results and those that had not achieved an agreement knew the reason for this. Step 1 moved from 2D models to 3D models of the FE experiment without adding technical features like shotcrete or EDZ, and only considering the heating phase. Initially the 3D model was tightly specified to continue to build confidence in the model implementations (Step 1a). The results of Step 1a were compared to the data from the FE-experiment without the teams seeing the data. The teams were then provided with a sub-set of the data from the FE-experiment and invited to consider how best to use the large dataset for model comparison (Step 1b). Teams were then asked to use the data provided to calibrate their models, only changing material property values rather than adding features or processes to their models (Step 1c). In Step 1, teams were asked to only model the heating phase of the experiment, so pressure in the Opalinus Clay was reported as change in pressure since the initial conditions were specified rather than modelled. The change from 2D to 3D models was accompanied by an increase in the dispersion of results between the teams. Some of this was resolved during the task, but some remained and is potentially due to model discretisation. Calibration of parameters was useful in improving the fit of the models to the data but the remaining differences indicated that the models were missing features or processes. In Step 2, the teams were asked to update their models with additional features and processes as well as calibrating parameters to try and improve the fit of the models to the data. Teams were encouraged to represent ventilation of the open FE tunnel prior to backfilling with heaters and bentonite and in Step 2, the absolute pressure in the Opalinus Clay was compared between the teams. Teams took different approaches, but there was consideration of adding shotcrete and an EDZ into the model, representing stress change during excavation and different approaches to modelling ventilation of the FE tunnel. Overall, the documented results showed a very good agreement for temperature. The results for porewater pressure evolution showed a significant improvement for most teams compared to Step 1c with a good agreement to the measurements for several teams whereas some teams overpredicted the pressure increase and others overpredicted the drainage effect especially for the sensors close to the heater. Step 3 was an opportunity for teams to use the models developed in Step 1 and Step 2 to make predictions about the temperature and pressure changes that will be expected at the FE experiment over the next few years in light of the planned changes in thermal output of the heaters.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2014

Comparison of atmospheric parameters determined from spectroscopy and photometry for DA white dwarfs in the Sloan Digital Sky Survey

We present a comparative analysis of atmospheric parameters obtained with the so-called photometric and spectroscopic techniques. Photometric and spectroscopic data for 1360 DA white dwarfs from the Sloan Digital Sky Survey (SDSS) are used, as well as spectroscopic data from the Villanova White Dwarf Catalog. We first test the calibration of the ugriz photometric system by using model atmosphere fits to observed data. Our photometric analysis indicates that the ugriz photometry appears well calibrated when the SDSS to AB{sub 95} zeropoint corrections are applied. The spectroscopic analysis of the same data set reveals that the so-called high-log g problem can be solved by applying published correction functions that take into account three-dimensional hydrodynamical effects. However, a comparison between the SDSS and the White Dwarf Catalog spectra also suggests that the SDSS spectra still suffer from a small calibration problem. We then compare the atmospheric parameters obtained from both fitting techniques and show that the photometric temperatures are systematically lower than those obtained from spectroscopic data. This systematic offset may be linked to the hydrogen line profiles used in the model atmospheres. We finally present the results of an analysis aimed at measuring surface gravities using photometric data only.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Assessing and Managing the Current and Future Pest Risk from Water Hyacinth, (Eichhornia crassipes), an Invasive Aquatic Plant Threatening the Environment and Water Security

Understanding and managing the biological invasion threats posed by aquatic plants under current and future climates is a growing challenge for biosecurity and land management agencies worldwide. Eichhornia crassipes is one of the world’s worst aquatic weeds. Presently, it threatens aquatic ecosystems, and hinders the management and delivery of freshwater services in both developed and developing parts of the world. A niche model was fitted using CLIMEX, to estimate the potential distribution of E. crassipes under historical and future climate scenarios. Under two future greenhouse gas emission scenarios for 2080 simulated with three Global Climate Models, the area with a flavourable temperature regime appears set to shift polewards. The greatest potential for future range expansion lies in Europe. Elsewhere in the northern hemisphere temperature gradients are too steep for significant geographical range expansion under the climate scenarios explored here. In the Southern Hemisphere, the southern range boundary for E. crassipes is set to expand southwards in Argentina, Australia and New Zealand; under current climate conditions it is already able to invade the southern limits of Africa. The opportunity exists to prevent its spread into the islands of Tasmania in Australia and the South Island of New Zealand, both of which depend upon hydroelectric facilities that would be threatened by the presence of E. crassipes. In Europe, efforts to slow or stop the spread of E. crassipes will face the challenge of limited internal biosecurity capacity. The modelling technique demonstrated here is the first application of niche modelling for an aquatic weed under historical and projected future climates. It provides biosecurity agencies with a spatial tool to foresee and manage the emerging invasion threats in a manner that can be included in the international standard for pest risk assessments. It should also support more detailed local and regional management.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Fermilab Booster loss modelling and rebalancing using Bayesian methods

Fermilab Booster is being upgraded for the PIP-II project to support 20Hz ramp rate at higher intensities. Loss trip limits determine the achievable peak power. To meet PIP-II requirements, losses need to be halved as compared to current levels. Losses primarily occur at injection and transition crossing, with both gradually increasing and threshold-like intensity-dependent behaviors. The existing simulation models are not yet good enough for quantitative loss predictions. In practice, it will be necessary to tune up the Booster using iterative methods and operator intuition. In this paper we present an effort to systematically model Booster losses using active learning (Bayesian exploration) techniques, and subsequently to rebalance them for higher trip limit margins. We first created several sets of spatially and temporally isolated orbit and optics knobs, and trained Gaussian process models for each beam loss monitor as well as beam current. This is a complex task due to safety and timing requirements – we discuss mitigations such as uncertainty constraints and approximate fitting. Once models are stable, we perform large-scale single and multi-objective tuning using scalarized objectives made up of critical beam loss locations. Our results demonstrate significant rebalancing of losses, increasing trip margins, as well as an overall improvement in beam transmission efficiency. We are exploring how to combine existing simulations with experimental data and automate the collection procedure so that more advanced surrogate models can be created over time.

Kuklev, Nikita [Fermilab]↗
DOE OSTI2023

Data to Accompany: PM2.5 is insufficient to explain personal PAH exposure

Fine particulate matter (PM2.5) air quality index (AQI) data from outdoor stationary monitors and Hazard Mapping System (HMS) smoke density data from satellites are often used as proxies for personal chemical exposure. Silicone wristbands can quantify more individualized exposure data than stationary air monitors or smoke satellites. However, it is not understood how these proxy measurements compare to chemical data measured from wristbands. We hypothesized that predictive models for personal chemical exposure would be significantly improved by expanding beyond stationary PM2.5 AQI data or satellite HMS data to also include environmental and behavioral information. In Eugene, Oregon, participants wore daily wristbands, carried a phone that recorded locations, and answered daily questionnaires for a seven-day period in multiple seasons. We gathered publicly available daily PM2.5 AQI data and HMS data. We analyzed wristbands for 94 organic chemicals, including 53 polycyclic aromatic hydrocarbons (PAHs). Wristband chemical detections and concentrations, behavioral variables (e.g., time spent indoors), and environmental conditions (e.g., PM2.5 AQI) significantly differed between seasons. Machine learning models were fit to predict personal chemical exposure using PM2.5 AQI only, HMS only, and a multivariate feature set including PM2.5 AQI, HMS, and other environmental and behavioral information. On average, the multivariate models increased predictive accuracy by approximately 70% compared to either the AQI model or the HMS model for all chemicals modeled. This study provides evidence that PM2.5 AQI data alone or HMS data alone is insufficient to explain personal chemical exposures. Our results identify additional key predictors of personal chemical exposure.

Bramer, Lisa M↗
DOE OSTI2023

Investigating the impact of environmental factors on West Nile virus human case prediction in Ontario, Canada

West Nile virus is the most common mosquito borne disease in North America and the leading cause of viral encephalitis. West Nile virus is primarily transmitted between birds and mosquitoes while humans are incidental, dead-end hosts. Climate change may increase the risk of human infections as climatic variables have been shown to affect the mosquito life cycle, biting rate, incubation period of the disease in mosquitoes, and bird migration patterns. We develop a zero-inflated Poisson model to investigate how human West Nile virus case counts vary with respect to mosquito abundance and infection rates, bird abundance, and other environmental covariates. We use a Bayesian paradigm to fit our model to data from 2010–2019 in Ontario, Canada. Our results show mosquito infection rate, temperature, precipitation, and crow abundance are positively correlated with human cases while NDVI and robin abundance are negatively correlated with human cases. We find the inclusion of spatial random effects allows for more accurate predictions, particularly in years where cases are higher. Our model is able to accurately predict the magnitude and timing of yearly West Nile virus outbreaks and could be a valuable tool for public health officials to implement prevention strategies to mitigate these outbreaks.

60 APPLIED LIFE SCIENCES↗