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At least 1,045 records · Page 58

Generalizable, fast, and accurate DeepQSPR with fastprop

Abstract Quantitative Structure–Property Relationship studies (QSPR), often referred to interchangeably as QSAR, seek to establish a mapping between molecular structure and an arbitrary target property. Historically this was done on a target-by-target basis with new descriptors being devised to specifically map to a given target. Today software packages exist that calculate thousands of these descriptors, enabling general modeling typically with classical and machine learning methods. Also present today are learned representation methods in which deep learning models generate a target-specific representation during training. The former requires less training data and offers improved speed and interpretability while the latter offers excellent generality, while the intersection of the two remains under-explored. This paper introduces , a software package and general Deep-QSPR framework that combines a cogent set of molecular descriptors with deep learning to achieve state-of-the-art performance on datasets ranging from tens to tens of thousands of molecules. provides both a user-friendly Command Line Interface and highly interoperable set of Python modules for the training and deployment of feedforward neural networks for property prediction. This approach yields improvements in speed and interpretability over existing methods while statistically equaling or exceeding their performance across most of the tested benchmarks. is designed with Research Software Engineering best practices and is free and open source, hosted at github.com/jacksonburns/fastprop.

Burns, Jackson W. (ORCID:0000000206579426)↗

Approximate inference for constructing astronomical catalogs from images

Here, we present a new, fully generative model for constructing astronomical catalogs from optical telescope image sets. Each pixel intensity is treated as a random variable with parameters that depend on the latent properties of stars and galaxies. These latent properties are themselves modeled as random. We compare two procedures for posterior inference. One procedure is based on Markov chain Monte Carlo (MCMC) while the other is based on variational inference (VI). The MCMC procedure excels at quantifying uncertainty, while the VI procedure is 1000 times faster. On a supercomputer, the VI procedure efficiently uses 665,000 CPU cores to construct an astronomical catalog from 50 terabytes of images in 14.6 minutes, demonstrating the scaling characteristics necessary to construct catalogs for upcoming astronomical surveys.

59 BASIC BIOLOGICAL SCIENCES↗

Charged-particle distributions in s = 13 TeV p p interactions measured with the ATLAS detector at the LHC

CERN-LHC. Measurements of charged particle distributions in proton-proton collisions at a centre-of-mass energy of 13 TeV. A data sample of nearly 9 million events recorded by the ATLAS detector during a special LHC fill with low beam currents, and thus giving a low expected mean number of interactions, is used. The charged-particle multiplicity, its dependence on transverse momentum and pseudorapidity and the dependence of the mean transverse momentum on the charged-particle multiplicity are presented. The measurements are performed with charged particles with transverse momentum greater than 500 MeV and absolute pseudorapidity less than 2.5, in events with at least one charged particle satisfying these kinematic requirements. Events with charged particles with transverse momentum greater than 500 MeV and absolute pseudorapidity less than 0.8 are also measured. The results are corrected for detector effects, presented as particle-level distributions and are compared to various Monte Carlo event generator models.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

High-dimensional maximum-entropy phase space tomography

Reconstructing 4D or 6D phase space distributions from 1D or 2D measurements is a challenging inverse problem encountered in particle accelerators. Entropy maximization is an established method to incorporate prior information in the reconstruction, but it is typically infeasible in high-dimensional spaces. In this paper, I review two recent approaches to high-dimensional entropy maximization. The first approach utilizes differentiable simulations and a class of generative models known as normalizing flows, whereas the second approach employs the method of Lagrange multipliers and Markov Chain Monte Carlo (MCMC) sampling. My aim is to provide a short explanation of each method using a common notation. I conclude by mentioning several unsolved problems in phase space tomography.

Hoover, Austin [ORNL] (ORCID:0000000153136962)↗

Chalcogenide Glass Radiation Sensor; Materials Development, Design and Device Testing

For many decades, various radiation detecting material have been extensively researched, to find a better material or mechanism for radiation sensing. Recently, there is a growing need for a smaller and effective material or device that can perform similar functions of bulkier Geiger counters and other measurement options, which fail the requirement for easy, cheap and accurate radiation dose measurement. Here arises the use of thin film chalcogenide glass, which has unique properties of high thermal stability along with high sensitivity towards short wavelength radiation. The unique properties of chalcogenide glasses are attributed to the lone pair p-shell electrons, which provide some distinctive optical properties when compared to crystalline material. These qualities are derived from the energy band diagram and the presence of localized states in the band gap. Chalcogenide glasses have band tail states and localized states, along with the two band states. These extra states are primarily due to the lone pair electrons as well as the amorphous structure of the glasses. The localized states between the conductance band (CB) and valence band (VB) are primarily due to the presence of the lone pair electrons, while the band tail states are attributed to the Van der Waal's forces between layers of atoms. Localized states are trap locations within the band gap where electrons from the valence band can hop into, in their path towards the conduction band. Tail states on the other hand are locations near the band gap edges and are known as Urbach tail states (E u ). These states are occupied with many electrons that can participate in the various transformations due to interaction with photons. According to Y. Utsugi et. al., the electron-phonon interactions are responsible for the generation of the Urbach tails. These states are responsible for setting the absorption edge for these glasses and photons with energy near the band gap affect these states. We have studied the effect of x-rays and γ-rays, on thin film chalcogenide glasses and applied them in conjunction with film incorporating a silver source in a new type of radiation sensor for which we have an US patent application. In this report, we give data about our studies regarding our designed radiation sensor along with the testing and performance at various radiation doses. These studies have been preceded by materials characterization research related to the compositional and structural characteristics of the active materials used in the radiation sensor design. During the work on the project, we collected a large volume of material since every experiment was repeated many times to verify the results. We conducted a comprehensive material research, analysis and discussion with the aim to understand the nature of the occurring effects, design different structures to harness these effects, generated models to aid in the understanding the effects, built different device structures and collected data to quantify device performance. These various aspects of our investigation have been detailed in previous quarterly reports. In this report, we present our main results and emphasize on the results pertaining to the core project goals materials development, sensor design and testing and with an emphasis on classifying the appropriate material and design for the optimal application. The report has three main parts: (i) Presentation of the main data; (ii) Bulleted summary of the most important results; (iii) List of the patent, journal publications, conference proceedings and conferences participation, occurring as a result of working on the project.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Revisiting the Long-Term Hedge Value of Wind Power in an Era of Low Natural Gas Prices

Expanding production of the United States’ vast shale gas reserves in recent years has put the country on a path towards greater energy independence, enhanced economic prosperity, and (potentially) reduced emissions of greenhouse gases and other pollutants. The corresponding expansion of gas-fired generation in the power sector – driven primarily by lower natural gas prices – has also made it easier and cheaper to integrate large amounts of variable renewable generation, such as wind power, into the grid. At the same time, however, low natural gas prices have suppressed wholesale power prices across the nation, making it harder for wind and other renewable power technologies to compete on cost alone – even despite their recent cost and performance improvements. A near-term softening in policy-driven demand from state-level renewable energy mandates, coupled with a possible phase-out of a key federal tax incentive over time, may exacerbate wind’s challenge in the coming years. As wind power finds it more difficult to compete with gas-fired generation on the basis of near-term cost, it will increasingly need to rely on other attributes, such as its “portfolio” or “hedge” value, as justification for inclusion in the power mix. This article investigates the degree to which wind power can still serve as a cost-effective hedge against rising natural gas prices, given the significant reduction in gas prices in recent years, coupled with expectations that prices will remain low for many years to come. It does so by drawing upon a rich sample of long-term power purchase agreements (“PPAs”) between existing wind generators and electric utilities in the U.S., and comparing the contracted prices at which utilities will be buying wind power from these existing projects for decades to come to a variety of long-term projections of the fuel costs of gas-fired generation modeled by the Energy Information Administration (“EIA”).

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Assessment of Industrial Load for Demand Response across U.S. Regions of the Western Interconnect

Demand response has the ability to both increase power grid reliability and potentially reduce operating system costs. Understanding the role of demand response in grid modeling has been difficult due to complex nature of the load characteristics compared to the modeled generation and the variation in load types. This is particularly true of industrial loads, where hundreds of different industries exist with varying availability for demand response. We present a framework considering industrial loads for the development of availability profiles for demand response that can provide more regional understanding and can be inserted into analysis software for further study.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Preliminary Two-Phase Terry Turbine Nozzle Models for RCIC Off-Design Operation Conditions

This report presents the effort to extend the single-phase analytical Terry turbine model to cover two-phase off-design conditions. The work includes: (1) adding well-established two-phase choking models – the Isentropic Homogenous Equilibrium Model (IHEM) and Moody’s model, and (2) theoretical development and implementation of a two-phase nozzle expansion model. The two choking models provide bounding cases for the two-phase choking mass flow rate. The new two-phase Terry turbine model uses the choking models to calculate the mass flow rate, the critical pressure at the nozzle throat, and steam quality. In the divergent stage, we only consider the vapor phase with a similar model for the single-phase case by assuming that the liquid phase would slip along the wall with a much slower speed and will not contribute the impulse on the rotor. We also modify the stagnation conditions according to two-phase choking conditions at the throat and the cross-section areas for steam flow at the nozzle throat and at the nozzle exit. The new two-phase Terry turbine model was benchmarked with the same steam nozzle test as for the single-phase model. Better agreement with the experimental data is observed than from the single-phase model. We also repeated the Terry turbine nozzle benchmark work against the Sandia CFD simulation results with the two-phase model for the pure steam inlet nozzle case. The RCIC start-up tests were simulated and compared with the single-phase model. Similar results are obtained. Finally, we designed a new RCIC system test case to simulate the self-regulated Terry turbine behavior observed in Fukushima accidents. In this test, a period inlet condition for the steam quality varying from 1 to 0 is applied. For the high quality inlet period, the RCIC system behaves just like the normal operation condition with a high pump injection flow rate and a nominal steam release rate through the turbine, with the net addition of water to the primary system; for the low quality inlet period, the RCIC turbine shaft work dramatically decreases and results in a much reduced pump injection flow rate, and the mixture flow rate through the turbine increases due to the high liquid phase flow rate. The net effect for this period is net removal of coolant from the primary loop. With the periodic addition and removal of coolant to the primary loop, the self-regulation mode of the RCIC system can be maintained for a quite long time. Both the IHEM and Moody’s models generate similar phenomena; however noticeable differences can be observed.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Measuring Plasma Formation Field Strength and Current Loss in Pulsed Power Diodes

This LDRD investigated plasma formation, field strength, and current loss in pulsed power diodes. In particular the Self-Magnetic Pinch (SMP) e-beam diode was studied on the RITS-6 accelerator. Magnetic fields of a few Tesla and electric fields of several MV/cm were measured using visible spectroscopy techniques. The magnetic field measurements were then used to determine the current distribution in the diode. This distribution showed that significant beam current extends radially beyond the few millimeter x-ray focal spot diameter. Additionally, shielding of the magnetic field due to dense electrode surface plasmas was observed, quantified, and found to be consistent with the calculated Spitzer resistivity. In addition to the work on RITS, measurements were also made on the Z-machine looking to quantify plasmas within the power flow regions. Measurements were taken in the post-hole convolute and final feed gap regions on Z. Dopants were applied to power flow surfaces and measured spectroscopically. These measurements gave species and density/temperature estimates. Preliminary B-field measurements in the load region were attempted as well. Finally, simulation work using the EMPHASIS, electromagnetic particle in cell code, was conducted using the Z MITL conditions. The purpose of these simulations was to investigate several surface plasma generations models under Z conditions for comparison with experimental data.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Automated Clean Chemistry for Bulk Analysis of Environmental Swipe Samples – Final Report

Sample preparation methods for mass spectrometry are being automated using commercial-off-the-shelf (COTS) equipment to shorten lengthy and costly manual chemical purification procedures. This development addresses a serious need in the International Atomic Energy Agency’s (IAEA) Network of Analytical Laboratories (NWAL) to increase efficiency in the Bulk Analysis of Environmental Samples for Safeguards program with a method that allows unattended, overnight operation. In collaboration with Elemental Scientific Inc. (ESI), the prepFAST-MC2 was designed based on COTS equipment. It was modified for uranium/plutonium separations using renewable columns packed with Eichrom TEVA® and UTEVA® resins, with a chemical separation method based on the Oak Ridge National Laboratory (ORNL) NWAL chemical procedure. Initial verification of individual columns yielded small elution volumes with consistent elution profiles and good recovery. Combined column calibration demonstrated ample separation without crosscontamination of the eluent. Automated packing and unpacking of the built-in columns initially showed >15% deviation in resin loading by weight, which can lead to inconsistent separations. Optimization of the packing and unpacking methods led to a reduction in the variability of the packed resin to less than 5% daily. Based on the initial experience at ORNL with the prepFAST-MC2, a second-generation model, the prepFAST-SR, was built by ESI. The newly designed prepFAST-SR has several upgrades compared with the original prepFAST-MC2. The upgrades largely addressed issues with the reliability of unpacking the Eichrom columns and with ventilation to ensure adequate removal of acid vapors. Both systems are currently installed in the Ultra-Trace Forensics Science Center at ORNL. Separations of mixed uranium and plutonium samples containing certified reference materials were analyzed by multi-collector inductively coupled plasma mass spectrometry and yielded good results. Current efforts have demonstrated a wider applicability of the prepFAST system. Near-quantitative removal of metal interferences was achieved with the system in both uranium and plutonium separated fractions. Successful system validation was completed with several archived samples. Isotopic results from archived samples and certified reference materials were well within data quality limits for the IAEA NWAL. Additional COTS equipment has been evaluated for its potential to aid the prepFAST-SR system in reducing the time allotments and cleanroom infrastructure requirements for accurate separations. Overall, these efforts help ensure continued efficient and effective operation of the NWAL. Comparison of the amount of personnel time necessary for successful manual vs. automated chemical separations showed a significant decrease in hands-on time from 9.8 hours to 35 minutes for seven samples, respectively. This documented time savings and reduced labor translates to a significant cost savings per sample. Overall, the system will enable faster sample reporting times at reduced cost by limiting personnel hours dedicated to the chemical separation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

High-Resolution Regional Wave Hindcast for the U.S. Alaska Coast

Regional long-term wave hindcast with state-of-art third-generation models is essential for characterization of regional wave resources. This report summarizes modeling efforts for the simulation of the wave climate along southern Alaska, which used an unstructured, nested-grid modeling approach that incorporates a global-regional nested grid using WAVEWATCH III ® and the high-resolution SWAN (Simulating Waves Nearshore) model. Wave resource and wave bulk parameters were simulated for a 32-year period from 1979 to 2010 and were subsequently validated with wave buoy data in the model domain. Error statistics of model skills were calculated at all buoy stations. Overall, model results, both resource and bulk parameters, match observations well. The model hindcast was able to reproduce the seasonal variation of the sea state with large waves that occur in the winter and early spring months when wind forcing is strong and the calm sea state during the summer when wind forcing is weak. The hindcast also considers the effect of sea ice on wave growth, which affects the southern Bering Sea. The hindcast results, including resource and bulk parameters, were archived at every model grid point for the entire model domain at three-hour intervals. In addition, spectral results were saved at National Data Buoy Center buoy stations and selected virtual buoy locations at hourly intervals. The nested-grid modeling framework employed in this study provides a powerful and efficient modeling approach for accurately simulating wave climate at regional and long-term temporal scales with sufficiently fine resolutions in the nearshore region.

54 ENVIRONMENTAL SCIENCES↗

A Parallel-in-Time Multigrid Approach to Constrained Optimization

Valuable computer simulations such as weather prediction, traffic flow, and resource allocation are time dependent problems. One such example is the viscous Burgers’ equation which can model various systems such as fluids and traffic flow. Further, many of these models require optimization routines to meet the needs of many businesses. Unfortunately, traditional sequential-in-time algorithms have become bottlenecks in solution model generation. This is because computer architectures have begun to rely more and more on concurrency (parallel processing) as opposed to processor power to provide greater performance. To avoid this bottleneck, many researchers use parallelization methods to take advantage of the increasing number of processors in computers. This approach allows for variables in a problem to be solved for simultaneously. As such, parallelization is a crucial requirement to achieve high-performance computing.

97 MATHEMATICS AND COMPUTING↗

Monte Carlo Simulation of Background and Source Measurements with CSG and CAD Geometries

Detecting radioactive sources in an urban environment is difficult due to the large magnitude and variability of the background radiation. To support the search mission of the National Nuclear Security Administration, a project was undertaken to determine if first-principles modeling and simulation could be used to accurately predict the response of radiation detectors in urban environments. This study demonstrates that the simulated detector responses to photon radiation from both an isotopic source and the background compare well to benchmark-quality measurements in a large urban-like test environment. Simulation results using a traditional combinatorial solid geometry and a CAD model generated from LiDAR measurements gave very similar detector responses. With this validation, further simulations could be used to predict detector responses for various situations in real urban settings.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

SWP Summary Report for Individual Legacy Well Leakage Risk Analysis at Farnsworth Unit Site: Open Well Scenario

This report summarizes results of the individual legacy well leakage risk analysis of the Farnsworth Unit site (FWU) for Open Well scenario. NRAP tools Integrated Assessment Model for Carbon Storage (NRAP-IAM-CS) and Reservoir Reduced-Order Model Generator (RROMGen) were used (Dilmore et al., 2016; Pawar et al., 2016; King, 2016). This is part one of the additional analysis addressing SWP BP4 Subtask 7.4.1.2: Extend quantitative brine and CO2 leakage calculations (Chu et al., 2020).

58 GEOSCIENCES↗

Considerations for Developing a Regulatory Roadmap for Distributed Energy Resource (DER) Integration in Colombia

The USAID-NREL Partnership in Colombia, in conjunction with SURE and USEA, selected four action plan teams from the Young Professionals Leadership Program to receive tailored NREL technical assistance to support action plan implementation. The four plans selected represent various aspects associated with planning for the efficient integration of DERs, including electric mobility, residential and commercial energy applications, distributed generation modeling, and regulatory considerations. In response to national grid modernization, decentralization, digitalization, and electrification trends, CREG is looking to update Colombia's electric distribution code, with an emphasis on the integration of electric vehicles and charging stations, but also energy storage systems, non-conventional sources of renewable energy, and other distributed energy resources (DERs). CREG aims to establish the general steps that must be carried out to update the distribution code for the integration of DERs, with a view to the design and development of new markets. The objective of the TA provided to CREG was to support them in identifying and outlining the general processes and approaches to consider when updating Colombia's distribution code for the integration of electric vehicles, distributed renewable energy systems, and energy storage systems, with a view to the design and development of new markets.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Artificial Intelligence for Accelerating Nuclear Applications, Science, and Technology

Artificial intelligence (AI) and machine learning (ML) methods have had significant impacts in science and technology in recent years. These methods for generating models from datasets or logic-based algorithms that emulate aspects of human performance can similarly accelerate the fields of nuclear applications, science, and technology toward the IAEA goals of contributing to peace, health, and prosperity. In order to accomplish advances with AI in general and ML in particular across these fields, IAEA can play a significant role by establishing, hosting and curating centralised resources, including databases, adhering to FAIR (findable, accessible, interoperable and reusable) principles and Open Science best practices, providing stewardship of data sharing, supporting training efforts and development of relevant workforces, as well as enabling connections among the scientific, technology, mathematics, AI and ethics communities. Many areas can benefit from the use of AI in the realm of nuclear applications. In human health, these areas include clinical research, epidemiology, nutrition, medical imaging, radiotherapy and education of health professionals. AI-based tools are also being used to facilitate different clinical tasks in imaging, computer-assisted diagnosis in mammography and lung cancer screening programmes, and dose prediction in nuclear medicine procedures. ML methods in particular may also increase the efficiency and accuracy of the analysis of computerised tomography and dual-energy absorptiometry scans for body composition and bone analysis. The application of AI methods to nuclear and related technologies in food and agriculture can lead to significant advances and improved efficiency in the optimisation of agricultural production, food product development, management of supply chains, food safety and food authenticity control. In the water and environmental sector, AI can help inform policies to mitigate the world’s water problems. The application of AI techniques to hydrology and environmental sciences is expected to improve patterns identification and enable model predictions under a changing climate.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Initial OpenStudio Profiling Results

OpenStudio’s performance has not historically been an area of much work, but as it has successfully replaced ad hoc model generation solutions, the performance of the software is more and more central to continuing success. This report describes an initial effort to profile OpenStudio, describes the problems encountered, the solutions to those problems, and some early recommendations for further work should funding become available. The approach taken here is to use special software, referred to as profilers, to assess the code and how it executes. This approach is more appropriate for this kind of software than the checkpoint-style timing that is often done with numerical codes. Profiling was most successful on the MacOS platform, where Apple’s Instruments software was able to decipher the complexities of OpenStudio’s command line execution of a workflow. Even with the limited exploration of performance done here, the team quickly ran into limitations imposed on the code by the stateless architecture, and the team recommends an evaluation of this architecture as a good next step to improve performance.

97 MATHEMATICS AND COMPUTING↗

Results from an Aeromagnetic Survey to Detect Steel-Cased Wells at a Marcellus Shale Well Site in Washington County, Pennsylvania

Pennsylvania has a 150-year history of oil and gas production—the longest of any state—and this enduring activity has resulted in the drilling of more than 300,000 recorded wells. However, unknown wells likely exist because innumerable wells were drilled during Pennsylvania’s intense early oil and gas history when incomplete records were kept of well locations. There is concern that early wells are likely to be ineffectively sealed because there were no laws that required plugging when the wells were abandoned. Today, many undocumented and unplugged wells are thought to be in areas of emerging shale gas and shale oil development where open wellbores can provide a pathway for undesired upward migration of fluids and gas from hydraulically fractured reservoirs. Due to this concern, Pennsylvania regulators have asked operators to locate orphaned and abandoned wells within a 1,000-ft buffer of proposed new wells. The objective of this report is to demonstrate that high-resolution aeromagnetic surveys, historic air photos, and Light Detection and Ranging (LiDAR) imagery can be rapid and effective methods to reconnoiter large, forested areas of moderate terrain for the presence of abandoned wells. These well-finding methods were evaluated at a proposed Marcellus Shale gas drilling site in Washington County, Pennsylvania, where the methods collectively located 18 confirmed wells: 15 wells were identified from aeromagnetic surveys, two wells were identified from inspection of historical air photos, and one well was identified by evaluation of state-wide LiDAR imagery. Only six wells were previously known, and their locations, as recorded in Pennsylvania’s statewide oil and gas wells database (PA/IRIS/WIS), were often too inaccurate for the wells to be found in the dense underbrush. Twelve wells identified in this study were abandoned, unmarked, and undocumented. Aeromagnetic surveys locate wells by detecting the unique magnetic signature of vertical, steel well casing, which is depicted on magnetic maps as a “bull’s eye” type anomaly that is centered directly over the well. However, when wells were drilled and found to be sub-economic, their casing was sometimes pulled and salvaged for reuse. Such wellbores provide no magnetic response and go undetected if all casing was removed. Oftentimes attempts to retrieve well casing were not 100% successful. For example, historical records for one well in the study area indicate that the well was completed in 1902 as a dry hole and that, to the extent possible, the casing was pulled for reuse. However, a section of 10-in. diameter steel casing was not recovered and remains at an unknown depth in the wellbore. This well was easily detected by the aeromagnetic survey although only deep casing remained in the well. To mitigate for the likelihood that wellbores exist where most or all casing has been removed, this study augmented aeromagnetic data with historic air photos and digital terrain models generated from LiDAR datasets—both databases are publicly available at no cost for areas within Pennsylvania. These complementary methods located three wells where the aeromagnetic anomaly, although present, was subtle and overlooked. Together, these methods determined accurate locations for six known wells within the study area and located 12 previously unknown wells. Although it is not certain that these methods successfully located all wells in the study area, the application of these methods does represent a significant improvement over relying on existing databases for well locations. For the Appendix to the report, see: https://www.netl.doe.gov/energy-analysis/details?id=b46c417a-7c9e-4d25-b810-e6248b0217f4</p>

04 OIL SHALES AND TAR SANDS↗