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DOE OSTI2013

Ancient light from young cosmic cities: Physical and observational signatures of galaxy proto-clusters

A growing number of galaxy clusters at z = 1-2 is being discovered as part of deep optical, IR, X-ray, and Sunyaev-Zel'dovich effect surveys. For a complete picture of cluster formation, however, it is important that we also start probing the much earlier epoch, between redshifts of about 2 and 7, during which these clusters and their galaxies first began to form. Because the study of these so-called proto-clusters is currently quite limited by small number statistics, widely varying selection techniques, and many assumptions, we have performed a large systematic study of cluster formation utilizing cosmological simulations. We use the Millennium Simulations to track the evolution of dark matter and galaxies in about 3000 clusters from the earliest times to z = 0. We define an effective radius R{sub e} for proto-clusters and characterize their growth in size and mass with cosmic time. We show that the progenitor regions of galaxy clusters (ranging in mass from ∼10{sup 14} to a few times 10{sup 15} M {sub ☉}) can already be identified in galaxy surveys at very early times (at least up to z ∼ 5), provided that the galaxy overdensities are measured on a sufficiently large scale (R{sub e} ∼ 5-10 Mpc comoving) and with sufficient statistics. We present the overdensities in matter, dark matter halos, and galaxies as functions of present-day cluster mass, redshift, bias, and window size that can be used to interpret the wide range of structures found in real surveys. We also derive the probability that a structure having a galaxy overdensity δ{sub gal}, defined by a set of observational selection criteria, is indeed a proto-cluster, and we show how their z = 0 masses can already be estimated long before virialization. We present overdensity profiles as a function of radius, and we further show how the projected surface overdensities of proto-clusters decrease as the uncertainties in redshift measurements increase. We provide a table of proto-cluster candidates selected from the literature and discuss their properties in light of our simulation predictions. This paper provides the general framework that will allow us to extend the study of cluster formation out to much higher redshifts using the large number of proto-clusters that are expected to be discovered in, e.g., the upcoming HETDEX and Hyper Suprime-Cam surveys.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2019

A Novel Statistical Method for Measuring the Temperature–Density Relation in the IGM Using the b – N Hi Distribution of Absorbers in the Ly α Forest

We propose a new method for determining the thermal state of the intergalactic medium based on Voigt profile decomposition of the Lyα forest. The distribution of Doppler parameter and column density (b–N H i distribution) is sensitive to the temperature–density relation T = T 0 (ρ/ρ 0 ) γ-1 , and previous work has inferred T 0 and γ by fitting its low-b cutoff. This approach discards the majority of available data and is susceptible to systematics related to cutoff determination. We introduce an approach that exploits all information encoded in the b – N H i distribution by modeling its entire shape. We apply kernel density estimation to discrete absorption lines to generate model probability density functions, and then we use principal component decomposition to create an emulator that can be evaluated anywhere in thermal parameter space. We introduce a Bayesian likelihood based on these models enabling parameter inference via Markov Chain Monte Carlo. The method's robustness is tested by applying it to a large grid of thermal history simulations. By conducting 160 mock measurements, we establish that our approach delivers unbiased estimates and valid uncertainties for a 2D ( T 0 , γ) measurement. Furthermore, we conduct a pilot study applying this methodology to real observational data at z = 2. Using 200 absorbers, equivalent in path length to a single Lya forest spectrum, we measure $\mathrm{log}{T}_{0}={4.092}_{-0.055}^{+0.050}$ and $\gamma ={1.49}_{-0.074}^{+0.073}$ in excellent agreement with cutoff fitting determinations using the same data. Our method is far more sensitive than cutoff fitting, enabling measurements of log T 0 and γ with precision on $\mathrm{log}{T}_{0}$ (γ) nearly two (three) times higher for current data set sizes.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2017

Time to Amyloid Positivity and Preclinical Changes in Brain Metabolism, Atrophy, and Cognition: Evidence for Emerging Amyloid Pathology in Alzheimer's Disease

Background: Aβ pathology is associated with longitudinal changes of brain metabolism, atrophy, and cognition, in cognitively healthy elders. However, Aβ information is usually measured cross-sectionally and dichotomized to classify subjects as Aβ-positive or Aβ-negative, making it difficult to evaluate when brain and cognitive changes occur with respect to emerging Aβ pathology. In this study, we use longitudinal Aβ information to combine the level and rate of change of Aβ to estimate the time to Aβ-positivity for each subject and test this temporal proximity to significant Aβ pathology for associations with brain structure, metabolism, and cognition. Methods: In 89 cognitively healthy elders with up to 10 years of follow-up, we estimated the points at which rates of fluorodeoxyglucose (FDG) PET, MRI, and cognitive and functional decline begin to accelerate with respect to the time to Aβ-positivity. Points of initial acceleration in rates of decline were estimated using mixed-effects models with penalized regression splines. Results: Acceleration of rates of FDG PET were observed to occur 20+ years before the conventional threshold for Aβ-positivity. Subtle signs of cognitive dysfunction were observed 10+ years before Aβ-positivity. Conclusions: Aβ may have subtle associations with other hallmarks of Alzheimer’s disease before Aβ biomarkers reach conventional thresholds for Aβ-positivity. Therefore, we propose that emerging Aβ pathology occurs many years before cognitively healthy elders reach the current threshold for Aβ positivity (preclinical AD). To allow prevention in the earliest disease stages, AD clinical trials may be designed to also include subjects with Aβ biomarkers in the sub-threshold range.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2011

Data Analysis

Analysis of the material protection, control, and accountability (MPC&A) system is necessary to understand the limits and vulnerabilities of the system to internal threats. A self-appraisal helps the facility be prepared to respond to internal threats and reduce the risk of theft or diversion of nuclear material. The material control and accountability (MC&A) system effectiveness tool (MSET) fault tree was developed to depict the failure of the MPC&A system as a result of poor practices and random failures in the MC&A system. It can also be employed as a basis for assessing deliberate threats against a facility. MSET uses fault tree analysis, which is a top-down approach to examining system failure. The analysis starts with identifying a potential undesirable event called a 'top event' and then determining the ways it can occur (e.g., 'Fail To Maintain Nuclear Materials Under The Purview Of The MC&A System'). The analysis proceeds by determining how the top event can be caused by individual or combined lower level faults or failures. These faults, which are the causes of the top event, are 'connected' through logic gates. The MSET model uses AND-gates and OR-gates and propagates the effect of event failure using Boolean algebra. To enable the fault tree analysis calculations, the basic events in the fault tree are populated with probability risk values derived by conversion of questionnaire data to numeric values. The basic events are treated as independent variables. This assumption affects the Boolean algebraic calculations used to calculate results. All the necessary calculations are built into the fault tree codes, but it is often useful to estimate the probabilities manually as a check on code functioning. The probability of failure of a given basic event is the probability that the basic event primary question fails to meet the performance metric for that question. The failure probability is related to how well the facility performs the task identified in that basic event over time (not just one performance or exercise). Fault tree calculations provide a failure probability for the top event in the fault tree. The basic fault tree calculations establish a baseline relative risk value for the system. This probability depicts relative risk, not absolute risk. Subsequent calculations are made to evaluate the change in relative risk that would occur if system performance is improved or degraded. During the development effort of MSET, the fault tree analysis program used was SAPHIRE. SAPHIRE is an acronym for 'Systems Analysis Programs for Hands-on Integrated Reliability Evaluations.' Version 1 of the SAPHIRE code was sponsored by the Nuclear Regulatory Commission in 1987 as an innovative way to draw, edit, and analyze graphical fault trees primarily for safe operation of nuclear power reactors. When the fault tree calculations are performed, the fault tree analysis program will produce several reports that can be used to analyze the MPC&A system. SAPHIRE produces reports showing risk importance factors for all basic events in the operational MC&A system. The risk importance information is used to examine the potential impacts when performance of certain basic events increases or decreases. The initial results produced by the SAPHIRE program are considered relative risk values. None of the results can be interpreted as absolute risk values since the basic event probability values represent estimates of risk associated with the performance of MPC&A tasks throughout the material balance area (MBA). The RRR for a basic event represents the decrease in total system risk that would result from improvement of that one event to a perfect performance level. Improvement of the basic event with the greatest RRR value produces a greater decrease in total system risk than improvement of any other basic event. Basic events with the greatest potential for system risk reduction are assigned performance improvement values, and new fault tree calculations show the improvement in total system risk. The operational impact or cost-effectiveness from implementing the performance improvements can then be evaluated. The improvements being evaluated can be system performance improvements, or they can be potential, or actual, upgrades to the system. The RIR for a basic event represents the increase in total system risk that would result from failure of that one event. Failure of the basic event with the greatest RIR value produces a greater increase in total system risk than failure of any other basic event. Basic events with the greatest potential for system risk increase are assigned failure performance values, and new fault tree calculations show the increase in total system risk. This evaluation shows the importance of preventing performance degradation of the basic events. SAPHIRE identifies combinations of basic events where concurrent failure of the events results in failure of the top event.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2015

A tutorial introduction to the statistical theory of turbulent plasmas, a half-century after Kadomtsev’s Plasma Turbulence and the resonance-broadening theory of Dupree and Weinstock

In honour of the 50th anniversary of the influential review/monograph on plasma turbulence by B. B. Kadomtsev as well as the seminal works of T. H. Dupree and J. Weinstock on resonance-broadening theory, an introductory tutorial is given about some highlights of the statistical–dynamical description of turbulent plasmas and fluids, including the ideas of nonlinear incoherent noise, coherent damping, and self-consistent dielectric response. The statistical closure problem is introduced. Incoherent noise and coherent damping are illustrated with a solvable model of passive advection. Self-consistency introduces turbulent polarization effects that are described by the dielectric function ${\mathcal{D}}$ . Dupree’s method of using ${\mathcal{D}}$ to estimate the saturation level of turbulence is described; then it is explained why a more complete theory that includes nonlinear noise is required. The general theory is best formulated in terms of Dyson equations for the covariance $C$ and an infinitesimal response function $R$ , which subsumes ${\mathcal{D}}$ . An important example is the direct-interaction approximation (DIA). It is shown how to use Novikov’s theorem to develop an $\boldsymbol{x}$ -space approach to the DIA that is complementary to the original $\boldsymbol{k}$ -space approach of Kraichnan. A dielectric function is defined for arbitrary quadratically nonlinear systems, including the Navier–Stokes equation, and an algorithm for determining the form of ${\mathcal{D}}$ in the DIA is sketched. The independent insights of Kadomtsev and Kraichnan about the problem of the DIA with random Galilean invariance are described. The mixing-length formula for drift-wave saturation is discussed in the context of closures that include nonlinear noise (shielded by ${\mathcal{D}}$ ). The role of $R$ in the calculation of the symmetry-breaking (zonostrophic) instability of homogeneous turbulence to the generation of inhomogeneous mean flows is addressed. The second-order cumulant expansion and the stochastic structural stability theory are also discussed in that context. In conclusion, various historical research threads are mentioned and representative entry points to the literature are given. In addition, some outstanding conceptual issues are enumerated.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2016

Functional renormalization group approach to the Yang-Lee edge singularity

Here, we determine the scaling properties of the Yang-Lee edge singularity as described by a one-component scalar field theory with imaginary cubic coupling, using the nonperturbative functional renormalization group in 3 ≤ d ≤ 6 Euclidean dimensions. We find very good agreement with high-temperature series data in d = 3 dimensions and compare our results to recent estimates of critical exponents obtained with the four-loop ϵ = 6 - d expansion and the conformal bootstrap. The relevance of operator insertions at the corresponding fixed point of the RG β functions is discussed and we estimate the error associated with O(∂ 4 ) truncations of the scale-dependent effective action.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2017

SIDSIM (Sub-Interval Distribution-function in Simulation) [SWR-17-22]

Time-series simulation is a technique used to estimate the energy delivery of a power generation system with output that changes under changing conditions. Such variable resources include photovoltaic energy systems that experience different levels of sunlight or wind farms with changing wind patterns. As distributed generation from these variable resources continues to flourish, having improved software tools to accurately measure, model, and estimate phenomena of interest to grid integration, in addition to energy output, will be crucial for safeguarding smooth integration and operation of these energy systems. Currently, time-series simulations assume conditions and power output are constant over the duration of a time-step (steady-state assumption). NREL researchers improve the accuracy with a new simulation software called SIDSIM (Sub-Interval Distribution Simulation) that replaces this steady value (solar or wind resource) with a distribution function that has a maximum value, a minimum value, and a shape to the curve within each time-step. The distribution function used for modeling varying values in the SIDSIM software is a novel equation and presents advantageous new benefits over the conventional methods. The first advantage comes in the ability to determine maximum instantaneous power within a time-step. This enables better protection of a system from overcurrent issues and it also allows for better forecasting and reservation of transmission capacity; such capabilities are essential for energy system integration. Second, a distribution function helps to determine the amount of energy loss due to “clipping” in cases where the photovoltaic direct current (DC) system capacity exceeds the inverter capacity, the AC interconnect capacity, or any other limiting component or threshold value. It improves estimates of battery throughput by allowing both charge and discharge of a battery within the duration of a time-step. Third, it provides a more refined estimate of utility-bill impacts by considering the delivered power may be higher than the site load or lower than the regular average power estimates that are made using a quasi-steady-state assumption. SEE ALSO OSTI ID 1,361,018

Walker, Andy↗

DOE OSTI2018

Universality of Poisson-driven plasma fluctuations in the Alcator C-Mod scrape-off layer

Large-amplitude, intermittent fluctuations are ubiquitous in the boundary region of magnetically confined plasmas and lead to detrimental plasma-wall interactions in next-generation, high duty cycle fusion power experiments. Using gas puff imaging data time series from the scrape-off layer in the Alcator C-Mod device, it is demonstrated in this work that the large-amplitude fluctuations can be described as a super-position of pulses with a fixed shape and a constant duration. By applying a new deconvolution algorithm on the data time series with a two-sided exponential pulse function, the arrival times and amplitudes of the pulses can be estimated, and the measurement time series can be reconstructed with high accuracy. The pulse amplitudes are shown to follow an exponential distribution. The waiting times between pulses are uncorrelated, their distribution has an exponential tail, and the number of arrivals is a linear function of time. This demonstrates that pulse arrivals follow a homogeneous Poisson process. Identical statistical properties apply to both ohmic and high confinement mode plasmas, clearly demonstrating the universality of the fluctuation statistics in the boundary region of Alcator C-Mod.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2026

Extraction of neutron-capture cross sections on 92 Zr using the charge-exchange Oslo method

The 93 Nb (𝑡, 3 He ) reaction at 115 MeV/nucleon was studied to demonstrate that nuclear level densities and 𝛾-ray strength functions can be extracted from charge-exchange reactions at intermediate energies using the Oslo technique. The matrix of excitation energy in 93 Zr, reconstructed from the (𝑡, 3 He ) reaction, versus the energy of 𝛾 rays emitted by the excited 93 Zr nuclei, was obtained in an experiment with the S800 Spectrograph operated in coincidence with the GRETINA 𝛾 -ray detector. The extracted level density and 𝛾 -ray strength function obtained by applying the Oslo method to this matrix were used to estimate the 92 Zr⁢(𝑛,𝛾) ⁢93 Zr cross section by combining the new results with other experimental data and theoretical calculations for 𝐸⁢1 and 𝑀⁢1 strength functions at higher energies. Good agreement with direct measurements of the 92 Zr⁢(𝑛,𝛾)⁢ 93 Zr cross section was found. The contribution from the upbend in the extracted 𝛾-ray strength function was important to achieve the consistency, as the neutron-capture cross section without this contribution is significantly below the direct measurements otherwise. Since charge-exchange reactions at intermediate energies have long been used for extracting Gamow-Teller strengths, the successful demonstration of the charge-exchange Oslo method enables experiments in which (𝑛,𝛾) cross sections and Gamow-Teller strengths can be measured simultaneously, which is of benefit for astrophysical studies.

90 ≤ A ≤ 149↗

DOE OSTI2014

Reverberation measurements of the inner radius of the dust torus in 17 Seyfert galaxies

We present the results of a dust reverberation survey for 17 nearby Seyfert 1 galaxies, which provides the largest homogeneous data collection for the radius of the innermost dust torus. A delayed response of the K-band light curve after the V-band light curve was found for all targets, and 49 measurements of lag times between the flux variation of the dust emission in the K band and that of the optical continuum emission in the V band were obtained by the cross-correlation function analysis and also by an alternative method for estimating the maximum likelihood lag. The lag times strongly correlated with the optical luminosity in the luminosity range of M{sub V} = –16 to –22 mag, and the regression analysis was performed to obtain the correlation log Δt (days) = –2.11 – 0.2 M{sub V} assuming Δt∝L {sup 0.5}, which was theoretically expected. We discuss the possible origins of the intrinsic scatter of the dust lag-luminosity correlation, which was estimated to be approximately 0.13 dex, and we find that the difference of internal extinction and delayed response of changes in lag times to the flux variations could have partly contributed to intrinsic scatter. However, we could not detect any systematic change of the correlation with the subclass of the Seyfert type or the Eddington ratio. Finally, we compare the dust reverberation radius with the near-infrared interferometric radius of the dust torus and the reverberation radius of broad Balmer emission lines. The interferometric radius in the K band was found to be systematically larger than the dust reverberation radius in the same band by the about a factor of two, which could be interpreted by the difference between the flux-weighted radius and response-weighted radius of the innermost dust torus. The reverberation radius of the broad Balmer emission lines was found to be systematically smaller than the dust reverberation radius by about a factor of four to five, which strongly supports the unified scheme of the Seyfert type of active galactic nuclei (AGNs). Moreover, we examined the radius-luminosity correlations for the hard X-ray (14-195 keV) and the [O IV] λ25.89 μm emission-line luminosities, which would be applicable for obscured AGNs.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2016

Uncertainty as a Function of Time for Subcritical Experiment Parameters Using the Hage-Cifarelli Formalism

When designing critical or subcritical experiments, it is desirable to have an estimate of the measurement uncertainties prior to performing an experiment. In addition, an important goal is to have the smallest measurement uncertainties possible given measurement time constraints. Having well-designed experiments with small uncertainties helps improve nuclear data and therefore has direct impacts on criticality safety. This work shows how the uncertainties in various measurement parameters vary as a function of counting time and provides an approach to estimate measured uncertainties and guides in optimizing the available counting time. The uncertainty in six parameters used in subcritical experiments was investigated as a function of time: singles count rate (R{sub 1}), doubles count rate (R{sub 2}), lifetime (1/λ), leakage multiplication (M{sub L}), spontaneous fission rate (FS), and detector efficiency (ε). A comparison to measured data will be presented at the meeting. The approach and results in this work will be used to optimize measurement time in future subcritical experiments and will be used to help estimate measurement uncertainties during the design phase. Having well-designed experiments with the smallest uncertainties possible can help the criticality safety community through data validation. (authors)

42 ENGINEERING↗

DOE OSTI2011

Light Cone Dynamics and EMC Effects in the Extraction of F{sub 2n} at Large Bjorken x

We discuss theoretical issues related to the extraction of deep inelastic (DIS) structure function of neutron from inclusive DIS scattering off the deuteron at large Bjorken x. Theoretical justification is given to the consideration of only pn component of the deuteron wave function and consistency with both the baryonic number and light-cone momentum conservation sum rules. Next we discuss the EMC type effects and argue that in all cases relevant to the nuclear DIS reactions at large x the main issue is the medium modification of the properties of bound nucleon rather than the non-nucleonic components like pions. We give brief description of the color screening model of EMC and within this model we estimate uncertainties in the extraction of the neutron DIS structure function at large x. We emphasize also that these uncertainties are rather ''model independent'' since any theoretical framework accounting for the medium modification is proportional to the magnitude of the virtuality of bound nucleon which increases with an increase of x.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2022

Adjusting solar-induced fluorescence to nadir-viewing provides a better proxy for GPP

Solar-induced fluorescence (SIF) provides key information for inferring terrestrial gross primary productivity (GPP). However, there is little research on analyzing the performance of nadir-adjusted SIF (SIF nadir ) on GPP, compared to total SIF emitted by all leaves (SIF total ) for reducing the viewing angle effects and estimating GPP. Besides, there have been controversial opinions on whether SIF total is better correlated to GPP than raw SIF observations (SIF obs ). Here we systematically analyzed the relationship between raw/nadir/total SIF (i.e., SIF obs , SIF nadir and SIF total ) and GPP and investigated the underlying mechanism, using multi-angular field measurements and eddy covariance data in wheat and corn crops at sub-daily scale. We further compared the performance of SIF obs , SIF nadir and SIF total in estimating GPP using the TROPOspheric Monitoring Instrument (TROPOMI) SIF and concurrent AmeriFlux measurements at daily scale. Furthermore, the results indicate that diurnal SIF nadir has stronger correlations to GPP than SIF obs for field measurements, with the increase of mean coefficient of determination (R 2 ) by 0.05–0.07 for far-red band and 0.11–0.20 for red band. SIF nadir shows comparable performance with SIF total for both far-red and red bands. Although the viewing angle effects dominate the difference in estimating GPP between SIF nadir and SIF obs , the correlation between light use efficiency (LUE) and fesc further determines the different performance of SIF nadir and SIF total in estimating GPP. TROPOMI-based analysis further confirms that SIF nadir overall has higher correlations to AmeriFlux GPP than SIF obs for different plant functional types and shows similar performance with SIF total . Compared to SIF total , the estimation of SIF nadir independent of viewing angle effects does not require any canopy structure parameters, and thus offers promising potential for reliably estimating regional and global GPP.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2015

Cool core bias in Sunyaev–zel’dovich galaxy cluster surveys

Sunyaev–Zel’dovich (SZ) surveys find massive clusters of galaxies by measuring the inverse Compton scattering of cosmic microwave background off of intra-cluster gas. The cluster selection function from such surveys is expected to be nearly independent of redshift and cluster astrophysics. In this work, we estimate the effect on the observed SZ signal of centrally peaked gas density profiles (cool cores) and radio emission from the brightest cluster galaxy by creating mock observations of a sample of clusters that span the observed range of classical cooling rates and radio luminosities. For each cluster, we make simulated SZ observations by the South Pole Telescope and characterize the cluster selection function, but note that our results are broadly applicable to other SZ surveys. We find that the inclusion of a cool core can cause a change in the measured SPT significance of a cluster between 0.01 and 10% at z>0.3, increasing with cuspiness of the cool core and angular size on the sky of the cluster (i.e., decreasing redshift, increasing mass). We provide quantitative estimates of the bias in the SZ signal as a function of a gas density cuspiness parameter, redshift, mass, and the 1.4 GHz radio luminosity of the central active galactic nuclei. Based on this work, we estimate that, for the Phoenix cluster (one of the strongest cool cores known), the presence of a cool core is biasing the SZ significance high by ∼6%. The ubiquity of radio galaxies at the centers of cool core clusters will offset the cool core bias to varying degrees.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2012

Dynamically accumulated dose and 4D accumulated dose for moving tumors

Purpose: The purpose of this work was to investigate the relationship between dynamically accumulated dose (dynamic dose) and 4D accumulated dose (4D dose) for irradiation of moving tumors, and to quantify the dose uncertainty induced by tumor motion. Methods: The authors established that regardless of treatment modality and delivery properties, the dynamic dose will converge to the 4D dose, instead of the 3D static dose, after multiple deliveries. The bounds of dynamic dose, or the maximum estimation error using 4D or static dose, were established for the 4D and static doses, respectively. Numerical simulations were performed (1) to prove the principle that for each phase, after multiple deliveries, the average number of deliveries for any given time converges to the total number of fractions (K) over the number of phases (N); (2) to investigate the dose difference between the 4D and dynamic doses as a function of the number of deliveries for deliveries of a 'pulsed beam'; and (3) to investigate the dose difference between 4D dose and dynamic doses as a function of delivery time for deliveries of a 'continuous beam.' A Poisson model was developed to estimate the mean dose error as a function of number of deliveries or delivered time for both pulsed beam and continuous beam. Results: The numerical simulations confirmed that the number of deliveries for each phase converges to K/N, assuming a random starting phase. Simulations for the pulsed beam and continuous beam also suggested that the dose error is a strong function of the number of deliveries and/or total deliver time and could be a function of the breathing cycle, depending on the mode of delivery. The Poisson model agrees well with the simulation. Conclusions: Dynamically accumulated dose will converge to the 4D accumulated dose after multiple deliveries, regardless of treatment modality. Bounds of the dynamic dose could be determined using quantities derived from 4D doses, and the mean dose difference between the dynamic dose and 4D dose as a function of number of deliveries and/or total deliver time was also established.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2020

Physics-Informed Deep Neural Networks for Learning Parameters and Constitutive Relationships in Subsurface Flow Problems

In this paper, we present a physics informed deep neural network (DNN) method for estimating parameters and unknown physics (constitutive relationships) in partial differential equation (PDE) models. We use PDEs in addition to measurements to train DNNs to approximate unknown parameters and constitutive relationships as well as states. The proposed approach increases the accuracy of DNN approximations of partially known functions when a limited number of measurements is available and allows for training DNNs when no direct measurements of the functions of interest are available. We employ physics informed DNNs to estimate the unknown space-dependent diffusion coefficient in a linear diffusion equation and an unknown constitutive relationship in a non-linear diffusion equation. For the parameter estimation problem, we assume that partial measurements of the coefficient and states are available and demonstrate that under these conditions, the proposed method is more accurate than state-of-the-art methods. For the non-linear diffusion PDE model with a fully unknown constitutive relationship (i.e., no measurements of constitutive relationship are available), the physics informed DNN method can accurately estimate the non-linear constitutive relationship based on state measurements only. Finally, we demonstrate that the proposed method remains accurate in the presence of measurement noise.

42 ENGINEERING↗

DOE OSTI2016

LOW-METALLICITY YOUNG CLUSTERS IN THE OUTER GALAXY. I. Sh 2-207

To study star formation in low-metallicity environments ([M/H] ∼ −1 dex), we obtained deep near-infrared (NIR) images of Sh 2-207 (S207), which is an H ii region in the outer Galaxy with a spectroscopically determined metallicity of [O/H] ≃ −0.8 dex. We identified a young cluster in the western region of S207 with a limiting magnitude of K{sub S} = 19.0 mag (10σ) that corresponds to a mass detection limit of ≲0.1 M{sub ⊙} and enables the comparison of star-forming properties under low metallicity with those of the solar neighborhood. From the fitting of the K-band luminosity function (KLF), the age and distance of the S207 cluster are estimated at 2–3 Myr and ∼4 kpc, respectively. The estimated age is consistent with the suggestion of small extinctions of stars in the cluster (A{sub V} ∼ 3 mag) and the non-detection of molecular clouds. The reasonably good fit between the observed KLF and the model KLF suggests that the underlying initial mass function (IMF) of the cluster down to the detection limit is not significantly different from the typical IMFs in the solar metallicity. From the fraction of stars with NIR excesses, a low disk fraction (<10%) in the cluster with a relatively young age is suggested, as we had previously proposed.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2020

The Evolving Distribution of Relative Humidity Conditional Upon Daily Maximum Temperature in a Warming Climate

Abstract The impacts of heat waves in a warming climate depend not only on changing temperatures but also on changing humidity. Using 35 simulations from the Community Earth System Model Large Ensemble (CESM LENS), we investigate the long‐term evolution of the joint distribution of summer relative humidity (RH) and daily maximum temperature ( Tmax ) near four U.S. cities (New York City, Chicago, Phoenix, and New Orleans) under the high‐emissions Representative Concentration Pathway (RCP) 8.5. We estimate the conditional quantiles of RH given Tmax with quantile regression models, using functions of temperature for each city in July for three time periods (1990–2005, 2026–2035, and 2071–2080). Quality‐of‐fit diagnostics indicate that these models accurately estimate conditional quantiles for each city. As expected, each quantile of Tmax increases from 1990–2005 to 2071–2080, while mean RH decreases modestly. Conditional upon a fixed quantile of Tmax , the median and high quantiles of RH decrease, while those of the Heat Index (HI) and dew point both increase. This result suggests that, despite a modest decrease in median relative humidity, heat stress measured by metrics considering both humidity and temperature in a warming climate will increase faster than that measured by temperatures alone would indicate. For a fixed Tmax , the high quantiles of RH (and thus of HI and dew point) increase from 1990–2005 to 2071–2080 in all four cities. This result suggests that the heat stress of a day at a given Tmax will increase in a warming climate due to the increase of RH.

Yuan, Jiacan↗