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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Retrieval of the sea spray aerosol mode from submicron particle size distributions and supermicron scattering during LASIC

Abstract. Improved quantification of sea spray aerosol concentration and size is important for determining aerosol effects on clouds and the climate, though attempts to accurately capture the size distribution of the sea spray mode remain limited by the availability of supermicron size distributions. In this work, we introduce a new approach to retrieving lognormal mode fit parameters for a sea spray aerosol mode by combining submicron size distributions with supermicron scattering measurements using a Mie inversion. Submicron size distributions were measured by an ultra-high-sensitivity aerosol spectrometer (UHSAS), and supermicron scattering was taken as the difference between <10 µm and <1 µm three-wavelength integrating nephelometer measurements (NEPH). This UHSAS-NEPH method was applied during background marine periods of the Department of Energy Atmospheric Radiation Measurement Layered Atlantic Smoke Interactions with Clouds (LASIC) campaign on Ascension Island (November 2016–May 2017), when the contribution of sea spray aerosol was expected to represent a large fraction of the aerosol mass and total scattering. Lognormal sea spray modal parameters were retrieved from comparisons between nephelometer measurements and a lookup table of Mie theory-simulated scattering coefficients for low-error solutions that minimized the 0.4–1 µm residual in the UHSAS size distribution. We evaluated the UHSAS-NEPH method with a set of clean marine measurements in the North Atlantic that included supermicron size and chemical measurements, showing that measured supermicron size distributions are needed to constrain the sea spray number concentration but that mass concentration was reasonably characterized using supermicron scattering. For LASIC, the UHSAS-NEPH method retrieved sea spray mode properties for approximately 88 % of the background marine times when the scattering variability and total particle concentration were low (<± 5 Mm−1 and <400 cm−3, respectively), with mass mean diameter ranging from 0.6 to 1.9 µm (1.47 ± 0.17 µm), modal width ranging from 1.1 to 3.97 (2.4±0.3), and mass concentration ranging from 0.18 to 23.0 µg m−3 (8.37. ± 4.1 µg m−3). The measured nephelometer scattering at three wavelengths was found to constrain the mode width marginally at the largest particle sizes in the absence of additional size and chemical measurements for defining parameters for the Mie solutions. Comparing UHSAS-NEPH retrievals to those of a fitting algorithm applied only to the submicron UHSAS number size distribution showed that correlations between retrieved mass concentration and the available mass-based sea spray tracers (coarse scattering, wind speed, and chloride) are low when supermicron measurements are not considered. This work demonstrates the added value of supermicron scattering measurements for retrieving reasonable sea spray mass concentrations, providing the best-available observationally constrained estimate of the sea spray mode properties when supermicron size distribution measurements are not available.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2012

Multicriteria VMAT optimization

Purpose: To make the planning of volumetric modulated arc therapy (VMAT) faster and to explore the tradeoffs between planning objectives and delivery efficiency. Methods: A convex multicriteria dose optimization problem is solved for an angular grid of 180 equi-spaced beams. This allows the planner to navigate the ideal dose distribution Pareto surface and select a plan of desired target coverage versus organ at risk sparing. The selected plan is then made VMAT deliverable by a fluence map merging and sequencing algorithm, which combines neighboring fluence maps based on a similarity score and then delivers the merged maps together, simplifying delivery. Successive merges are made as long as the dose distribution quality is maintained. The complete algorithm is called VMERGE. Results: VMERGE is applied to three cases: a prostate, a pancreas, and a brain. In each case, the selected Pareto-optimal plan is matched almost exactly with the VMAT merging routine, resulting in a high quality plan delivered with a single arc in less than 5 min on average. Conclusions: VMERGE offers significant improvements over existing VMAT algorithms. The first is the multicriteria planning aspect, which greatly speeds up planning time and allows the user to select the plan, which represents the most desirable compromise between target coverage and organ at risk sparing. The second is the user-chosen epsilon-optimality guarantee of the final VMAT plan. Finally, the user can explore the tradeoff between delivery time and plan quality, which is a fundamental aspect of VMAT that cannot be easily investigated with current commercial planning systems.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2014

SU-E-T-69: Cloud-Based Monte Carlo Patient-Specific Quality Assurance (QA) Method for Volumetric Modulated Arc Therapy (VMAT)

Purpose: Patient-specific QA for VMAT is incapable of providing full 3D dosimetric information and is labor intensive in the case of severe heterogeneities or small-aperture beams. A cloud-based Monte Carlo dose reconstruction method described here can perform the evaluation in entire 3D space and rapidly reveal the source of discrepancies between measured and planned dose. Methods: This QA technique consists of two integral parts: measurement using a phantom containing array of dosimeters, and a cloud-based voxel Monte Carlo algorithm (cVMC). After a VMAT plan was approved by a physician, a dose verification plan was created and delivered to the phantom using our Varian Trilogy or TrueBeam system. Actual delivery parameters (i.e., dose fraction, gantry angle, and MLC at control points) were extracted from Dynalog or trajectory files. Based on the delivery parameters, the 3D dose distribution in the phantom containing detector were recomputed using Eclipse dose calculation algorithms (AAA and AXB) and cVMC. Comparison and Gamma analysis is then conducted to evaluate the agreement between measured, recomputed, and planned dose distributions. To test the robustness of this method, we examined several representative VMAT treatments. Results: (1) The accuracy of cVMC dose calculation was validated via comparative studies. For cases that succeeded the patient specific QAs using commercial dosimetry systems such as Delta- 4, MAPCheck, and PTW Seven29 array, agreement between cVMC-recomputed, Eclipse-planned and measured doses was obtained with >90% of the points satisfying the 3%-and-3mm gamma index criteria. (2) The cVMC method incorporating Dynalog files was effective to reveal the root causes of the dosimetric discrepancies between Eclipse-planned and measured doses and provide a basis for solutions. Conclusion: The proposed method offers a highly robust and streamlined patient specific QA tool and provides a feasible solution for the rapidly increasing use of VMAT treatments in the clinic.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

DAVIS: A direct algorithm for velocity-map imaging system

Here, we report a direct (non-iterative) algorithm to reconstruct the three-dimensional (3D) momentum-space picture of any charged particles collected with a velocity-map imaging system from the two-dimensional (2D) projected image captured by a position-sensitive detector. The technique consists of fitting the measured image with the 2D projection of a model 3D velocity distribution defined by the physics of the light-matter interaction. The meaningful angle-correlated information is first extracted from the raw data by expanding the image with a complete set of Legendre polynomials. Both the particle’s angular and energy distributions are then directly retrieved from the expansion coefficients. The algorithm is simple, easy to implement, fast, and explicitly takes into account the pixelization effect in the measurement.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2024

A Hierarchical OPF Algorithm with Improved Gradient Evaluation in Three-Phase Networks

Linear approximation commonly used in solving alternating-current optimal power flow (AC-OPF) simplifies the system models but incurs accumulated voltage errors in large power networks. Such errors will make the primal-dual type gradient algorithms converge to solutions with voltage violation. In this paper, we improve a recent hierarchical OPF algorithm that rested on primal-dual gradients evaluated with a linearized distribution power flow model. Specifically, we propose a more accurate gradient evaluation method based on an unbalanced three-phase nonlinear distribution power flow model to mitigate the errors arising from linearization. The resultant gradients feature a blocked structure that enables our development of an improved hierarchical primal-dual algorithm to solve the OPF problem. Numerical results on the IEEE 123-bus test feeder and a 4,518-node test feeder show that the proposed method can enhance voltage safety at comparable computational efficiency with the linearized algorithm.

approximation algorithms↗
DOE OSTI2022

Safety-assured, real-time neural active fault management for resilient microgrids integration

Federated-learning-based active fault management (AFM) is devised to achieve real-time safety assurance for microgrids and the main grid during faults. AFM was originally formulated as a distributed optimization problem. Here, federated learning is used to train each microgrid's network with training data achieved from distributed optimization. The main contribution of this work is to replace the optimization-based AFM control algorithm with a learning-based AFM control algorithm. The replacement transfers computation from online to offline. With this replacement, the control algorithm can meet real-time requirements for a system with dozens of microgrids. By contrast, distributed-optimization-based fault management can output reference values fast enough for a system with several microgrids. More microgrids, however, lead to more computation time with optimization-based method. Distributed-optimization-based fault management would fail real-time requirements for a system with dozens of microgrids. Controller hardware-in-the-loop real-time simulations demonstrate that learning-based AFM can output reference values within 10 ms irrespective of the number of microgrids.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

A Closed-Loop Distribution System Restoration Tool for Natural Disaster Recovery. Final CRADA report

We propose to continue the development of the restoration algorithms and the tool’s user interface, both of which have been developed under the GMLC-0131 project. This project aims to develop a distribution restoration decision support tool that will assist utilities in performing distribution restoration after extreme weather events in an optimal and efficient manner. The tool will integrate the weather information/forecasts and system fragility assessment together with the field measurement data to improve the situational awareness and estimate the system damage status. Advanced optimization models will be leveraged to dispatch repair crews and associated resources. New resources (e.g., automatic switches and distributed generators (DGs)) enabled by distribution automation and smart grid development will be utilized to reconfigure distribution grids and pick up loads promptly to reduce the outage sizes and durations. The closed-loop feature of the tool will make the tool adaptive to the evolving weather events and varying restoration capabilities. In this CRADA, we will collaborate with S&C Electric Company (S&C) to refine ANL-1060 (07/17/2019) the restoration algorithms that can be potentially applicable for any utility systems and vendor products, including: 1) Customizable information from both utility users and vendor users; 2) User interface design.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

A COUPLED 2 × 2D BABCOCK–LEIGHTON SOLAR DYNAMO MODEL. II. REFERENCE DYNAMO SOLUTIONS

In this paper we complete the presentation of a new hybrid 2 × 2D flux transport dynamo (FTD) model of the solar cycle based on the Babcock–Leighton mechanism of poloidal magnetic field regeneration via the surface decay of bipolar magnetic regions (BMRs). This hybrid model is constructed by allowing the surface flux transport (SFT) simulation described in Lemerle et al. to provide the poloidal source term to an axisymmetric FTD simulation defined in a meridional plane, which in turn generates the BMRs required by the SFT. A key aspect of this coupling is the definition of an emergence function describing the probability of BMR emergence as a function of the spatial distribution of the internal axisymmetric magnetic field. We use a genetic algorithm to calibrate this function, together with other model parameters, against observed cycle 21 emergence data. We present a reference dynamo solution reproducing many solar cycle characteristics, including good hemispheric coupling, phase relationship between the surface dipole and the BMR-generating internal field, and correlation between dipole strength at cycle maximum and peak amplitude of the next cycle. The saturation of the cycle amplitude takes place through the quenching of the BMR tilt as a function of the internal field. The observed statistical scatter about the mean BMR tilt, built into the model, acts as a source of stochasticity which dominates amplitude fluctuations. The model thus can produce Dalton-like epochs of strongly suppressed cycle amplitude lasting a few cycles and can even shut off entirely following an unfavorable sequence of emergence events.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

Seismicity studies at Moluccas area based on the result of hypocenter relocation using HypoDD

The precise hypocenter was determined location using double difference method around subduction zone in Moluccas area eastern part of Indonesia. The initial hypocenter location from MCGA data catalogue of 1,945 earthquake events. Basically the principle of double-difference algorithm assumes if the distance between two earthquake hypocenter distribution is very small compared to the distance between the station to the earthquake source, the ray path can be considered close to both earthquakes. The results show the initial earthquakes with a certain depth (fix depth 10 km) relocated and can be interpreted more reliable in term of seismicity and geological setting. The relocation of the intra slab earthquakes beneath Banda Arc are also clearly observed down to depth of about 400 km. The precise relocated hypocenter will give invaluable seismicity information for other seismological and tectonic studies especially for seismic hazard analysis in this region.

58 GEOSCIENCES↗
DOE OSTI2019

Large-Scale Grid Models: Synthetic Data and Co-Simulation

Power grid modernization and wide-spread distributed energy resource (DER) integration are driving an explosion of interest in advanced algorithms and new optimization schemes. However, there has historically been a lack of open-access realistically sized and detailed datasets-particularly for the distribution system-and simulation tools able to model these systems. This talk will present recent advances with very large-scale (>>1M nodes) distribution data sets and the use of co-simulation to tractably model large integrated transmission-distribution grids and their interactions with new controls/optimization.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Rare Events via Cross-Entropy Population Monte Carlo

Rare events are events that happen with very low frequency. Estimating rare event probabilities using Monte Carlo techniques is computationally expensive, often to the point of intractability, and special methods are required. Importance sampling (IS) is a well known technique that uses a proposal distribution in place of a target distribution to lower the variance of the estimator. Key to the success of IS methods is the choice of a proposal distribution, or the parameters governing the distribution. Adaptive importance sampling improves the parameters of a family or population of proposal distributions iteratively through trials. We present a novel cross-entropy population Monte Carlo algorithm, which adapts the parameters of proposals through the cross-entropy method. The proposed method stands apart from previous work in that we are not optimizing a mixture distribution. Instead, we leverage deterministic mixture weights and optimize the distributions individually through a reinterpretation of the typical derivation of the cross-entropy method. Demonstrations on rare event examples show that the algorithm can outperform existing resampling based population Monte Carlo methods, especially for higher-dimensional problems. Finally, we also demonstrate efficacy on a conjunction analysis problem.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

THE HERSCHEL EXPLOITATION OF LOCAL GALAXY ANDROMEDA (HELGA). VI. THE DISTRIBUTION AND PROPERTIES OF MOLECULAR CLOUD ASSOCIATIONS IN M31

In this paper we present a catalog of giant molecular clouds (GMCs) in the Andromeda (M31) galaxy extracted from the Herschel Exploitation of Local Galaxy Andromeda (HELGA) data set. GMCs are identified from the Herschel maps using a hierarchical source extraction algorithm. We present the results of this new catalog and characterize the spatial distribution and spectral energy properties of its clouds based on the radial dust/gas properties found by Smith et al. A total of 326 GMCs in the mass range 10{sup 4}-10{sup 7} M {sub ☉} are identified; their cumulative mass distribution is found to be proportional to M {sup –2.34}, in agreement with earlier studies. The GMCs appear to follow the same correlation of cloud mass to L {sub CO} observed in the Milky Way. However, comparison between this catalog and interferometry studies also shows that the GMCs are substructured below the Herschel resolution limit, suggesting that we are observing associations of GMCs. Following Gordon et al., we study the spatial structure of M31 by splitting the observed structure into a set of spiral arms and offset rings. We fit radii of 10.3 and 15.5 kpc to the two most prominent rings. We then fit a logarithmic spiral with a pitch angle of 8.°9 to the GMCs not associated with either ring. Last, we comment on the effects of deprojection on our results and investigate the effect different models for M31's inclination will have on the projection of an unperturbed spiral arm system.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

SDSS-IV eBOSS emission-line galaxy pilot survey

The Sloan Digital Sky Survey IV extended Baryonic Oscillation Spectroscopic Survey (SDSS-IV/eBOSS) will observe 195,000 emission-line galaxies (ELGs) to measure the Baryonic Acoustic Oscillation standard ruler (BAO) at redshift 0.9. To test different ELG selection algorithms, 9,000 spectra were observed with the SDSS spectrograph as a pilot survey based on data from several imaging surveys. First, using visual inspection and redshift quality flags, we show that the automated spectroscopic redshifts assigned by the pipeline meet the quality requirements for a reliable BAO measurement. We also show the correlations between sky emission, signal-to-noise ratio in the emission lines, and redshift error. Then we provide a detailed description of each target selection algorithm we tested and compare them with the requirements of the eBOSS experiment. As a result, we provide reliable redshift distributions for the different target selection schemes we tested. Lastly, we determine an target selection algorithms that is best suited to be applied on DECam photometry because they fulfill the eBOSS survey efficiency requirements.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Computing water flow through complex landscapes – Part 3: Fill–Spill–Merge: flow routing in depression hierarchies

Abstract. Depressions – inwardly draining regions – are common to many landscapes. When there is sufficient moisture, depressions take the form of lakes and wetlands; otherwise, they may be dry. Hydrological flow models used in geomorphology, hydrology, planetary science, soil and water conservation, and other fields often eliminate depressions through filling or breaching; however, this can produce unrealistic results. Models that retain depressions, on the other hand, are often undesirably expensive to run. In previous work we began to address this by developing a depression hierarchy data structure to capture the full topographic complexity of depressions in a region. Here, we extend this work by presenting the Fill–Spill–Merge algorithm that utilizes our depression hierarchy data structure to rapidly process and distribute runoff. Runoff fills depressions, which then overflow and spill into their neighbors. If both a depression and its neighbor fill, they merge. We provide a detailed explanation of the algorithm and results from two sample study areas. In these case studies, the algorithm runs 90–2600 times faster (with a reduction in compute time of 2000–63 000 times) than the commonly used Jacobi iteration and produces a more accurate output. Complete, well-commented, open-source code with 97 % test coverage is available on GitHub and Zenodo.

58 GEOSCIENCES↗
DOE OSTI2014

MO-G-18C-03: Evaluation of Deformable Image Registration for Lung Motion Estimation Using Hyperpolarized Gas Tagging MRI

Purpose: Hyperpolarized gas (HP) tagging MRI is a novel imaging technique for direct measurement of lung motion during breathing. This study aims to quantitatively evaluate the accuracy of deformable image registration (DIR) in lung motion estimation using HP tagging MRI as references. Methods: Three healthy subjects were imaged using the HP MR tagging, as well as a high-resolution 3D proton MR sequence (TrueFISP) at the end-of-inhalation (EOI) and the end-of-exhalation (EOE). Ground truth of lung motion and corresponding displacement vector field (tDVF) was derived from HP tagging MRI by manually tracking the displacement of tagging grids between EOI and EOE. Seven different DIR methods were applied to the high-resolution TrueFISP MR images (EOI and EOE) to generate the DIR-based DVFs (dDVF). The DIR methods include Velocity (VEL), MIM, Mirada, multi-grid B-spline from Elastix (MGB) and 3 other algorithms from DIRART toolbox (Double Force Demons (DFD), Improved Lucas-Kanade (ILK), and Iterative Optical Flow (IOF)). All registrations were performed by independent experts. Target registration error (TRE) was calculated as tDVF – dDVF. Analysis was performed for the entire lungs, and separately for the upper and lower lungs. Results: Significant differences between tDVF and dDVF were observed. Besides the DFD and IOF algorithms, all other dDVFs showed similarity in deformation magnitude distribution but away from the ground truth. The average TRE for entire lung ranged 2.5−23.7mm (mean=8.8mm), depending on the DIR method and subject's breathing amplitude. Larger TRE (13.3–23.7mm) was found in subject with larger breathing amplitude of 45.6mm. TRE was greater in lower lung (2.5−33.9 mm, mean=12.4mm) than that in upper lung (2.5−11.9 mm, mean=5.8mm). Conclusion: Significant differences were observed in lung motion estimation between the HP gas tagging MRI method and the DIR methods, especially when lung motion is large. Large variation among different DIR methods was also observed.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Exact and efficient hybrid Monte Carlo algorithm for accelerated Bayesian inference of gene expression models from snapshots of single-cell transcripts

Single cells exhibit a significant amount of variability in transcript levels, which arises from slow, stochastic transitions between gene expression states. Elucidating the nature of these states and understanding how transition rates are affected by different regulatory mechanisms require state-of-the-art methods to infer underlying models of gene expression from single cell data. A Bayesian approach to statistical inference is the most suitable method for model selection and uncertainty quantification of kinetic parameters using small data sets. However, this approach is impractical because current algorithms are too slow to handle typical models of gene expression. To solve this problem, we first show that time-dependent mRNA distributions of discrete-state models of gene expression are dynamic Poisson mixtures, whose mixing kernels are characterized by a piecewise deterministic Markov process. Here, we combined this analytical result with a kinetic Monte Carlo algorithm to create a hybrid numerical method that accelerates the calculation of time-dependent mRNA distributions by 1000-fold compared to current methods. We then integrated the hybrid algorithm into an existing Monte Carlo sampler to estimate the Bayesian posterior distribution of many different, competing models in a reasonable amount of time. We demonstrate that kinetic parameters can be reasonably constrained for modestly sampled data sets if the model is known a priori. If there are many competing models, Bayesian evidence can rigorously quantify the likelihood of a model relative to other models from the data. We demonstrate that Bayesian evidence selects the true model and outperforms approximate metrics typically used for model selection.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Fiber optic computing using distributed feedback

Abstract The widespread adoption of machine learning and other matrix intensive computing algorithms has renewed interest in analog optical computing, which has the potential to perform large-scale matrix multiplications with superior energy scaling and lower latency than digital electronics. However, most optical techniques rely on spatial multiplexing, requiring a large number of modulators and detectors, and are typically restricted to performing a single kernel convolution operation per layer. Here, we introduce a fiber-optic computing architecture based on temporal multiplexing and distributed feedback that performs multiple convolutions on the input data in a single layer. Using Rayleigh backscattering in standard single mode fiber, we show that this technique can efficiently apply a series of random nonlinear projections to the input data, facilitating a variety of computing tasks. The approach enables efficient energy scaling with orders of magnitude lower power consumption than GPUs, while maintaining low latency and high data-throughput.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2011

Dijet invariant mass distribution in top quark hadronic decay with QCD corrections

The dijet invariant mass distributions from the hadronic decay of unpolarized top quark (t{yields}bW{sup +} followed by W{sup +}{yields}ud) are calculated, including the next-to-leading order QCD radiative corrections. We treat the top decay in the complex mass scheme due to the existence of the intermediate state W boson. Our analytical expressions are also available in different dimensional regularization schemes and {gamma}{sub 5} strategies. Finally, in order to construct the jets, we use different jet algorithms to compare their influences on our results. The obtained dijet mass distributions from the top quark decay are useful to distinguish these dijets from those produced via other sources and to clarify the issue about the recent CDF Collaboration's Wjj anomaly.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗