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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

An Exceptionally Powerful, Radiatively Driven Ultrafast Outflow in the Rapidly Accreting AGN RE J1034+396

We report the analysis of ∼1 Ms of XMM-Newton observations of the rapidly accreting active galactic nucleus RE J1034+396. The 0.3–9 keV EPIC-pn spectra are well described by a model consisting of steep continuum emission from the corona accompanied by relativistically blurred reflection from a highly ionized accretion disk. The source is known to exhibit strong excess soft X-ray emission, which we show is well represented by thermal disk photons Comptonized by a warm plasma spanning the inner accretion flow. Additionally, the EPIC-pn data provide compelling evidence (ΔC ∼ 60 for four additional parameters) for the presence of an ultrafast outflow (UFO) with a line-of-sight velocity v/c = 0.307$^{+0.001}_{-0.005}$, and an emission signature consistent with reflection of the corona from modestly ionized, outflowing gas. The simultaneous 0.5–2.5 keV RGS spectra show clear absorption lines. Modelling of these data confirms the presence of the UFO and constrains its equivalent hydrogen column density, log N H /(atom cm −2 ) = 21.7$^{+0.1}_{-0.2}$. The RGS data also reveal at least two warm absorber components with a modest outflow velocity (1680$^{+40}_{-50}$ km s -1 ). The measured properties and time evolution of the UFO in RE J1034+396 suggest that it is formed from collisionally ionized plasma, launched from the disk surface and accelerated by radiation pressure. The high terminal velocity and substantial absorbing column density imply that the outflow carries sufficient momentum and energy to transform its environment, being capable of driving out essentially all dust and gas it interacts with along the line of sight, even if the AGN were initially surrounded by a Compton-thick absorber.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Argonne Leadership Computing Facility: 2021 Operational Assessment Report

This Operational Assessment Report describes how the Argonne Leadership Computing Facility (ALCF) met or exceeded every one of its goals for calendar year (CY) 2021 as an advanced scientific computing center. In CY 2021, the ALCF operated its production resource, Theta, an Intel-based Cray XC40 system (11.7-petaflops) augmented with 24 NVIDIA DGX A100-based nodes (3.9-petaflops) that supports diverse workloads, integrating data analytics with artificial intelligence (AI) training and learning in a single platform. In 2021, we began deploying Polaris, our newest 40- petaflops system, and augmented this powerful testbed system with an additional 28 nodes to support the integration of real-time experiments and HPC resources. We also deployed our two largest storage systems yet, named Grand and Eagle, that will bring new services to our users and will power data-driven research for years to come. Last year, Theta delivered a total of 20.8 million node-hours to 16 Innovative and Novel Computational Impact on Theory and Experiment (INCITE) projects and 7.2 million node-hours to ASCR Leadership Computing Challenge (ALCC) projects (32 awarded during the 2020–2021 ALCC year and 17 awarded during the 2021–2022 ALCC year), as well as substantial support to Director’s Discretionary (DD) projects (5.5 million node-hours). As Table ES.1 shows, Theta performed exceptionally well in terms of overall availability (95.1 percent), scheduled availability (99.4 percent), and utilization (98.1 percent; Table 2.1). As of the submission date of this document, ALCF’s user community has published 249 papers in high-quality, peer-reviewed journals and technical proceedings. At the 2021 International Conference for High Performance Computing, Networking, Storage and Analysis (SC’21), Argonne researchers won two HPCwire Readers’ Choice Awards and were part of a Gordon Bell Prize finalist team recognized for developing an AI-enabled, multi-resolution simulation framework for studying complex biomolecular machines. Their framework was used to observe the SARS-CoV-2 replication-transcription machinery in action, by directly integrating experimental data. ALCF also provided a comprehensive program of high-performance computing (HPC) support services to help our community make productive use of the facility’s diverse and growing collection of resources. We are now entering the exascale era, with exascale machines being planned for national laboratories across the country, including Aurora at Argonne National Laboratory (Argonne) in 2023. ALCF researchers have been leading and guiding numerous strategic activities that will push the boundaries of what’s possible in computational science and engineering and allow us to deliver science on day one.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Multidimensional dynamic piezoresponse measurements. Unraveling local relaxation behavior in relaxor-ferroelectrics via big data

Compositional and charge disorder in ferroelectric relaxors lies at the heart of the unusual properties of these systems, such as aging and non-ergodicity, polarization rotations, and a host of temperature and field-driven phase transitions. However, much information about the field-dynamics of the polarization in the prototypical ferroelectric relaxor (1-x)Pb(Mg 1/3 Nb 2/3 )O 3-x PbTiO 3 (PMN-xPT) remains unprobed at the mesoscopic level. We use a piezoresponse force microscopy-based dynamic multimodal relaxation spectroscopy technique, enabling the study of ferroelectric switching and polarization relaxation at mesoscopic length scales, and carry out measurements on a PMN-0.28PT sample with minimal polishing. Results indicate that beyond a threshold DC bias the average relaxation increases as the system attempts to relax to the previous state. Phenomenological fitting reveals the presence of mesoscale heterogeneity in relaxation amplitudes and clearly suggests the presence of two distinct amplitudes. Independent component analysis reveals the presence of a disorder component of the relaxation, which is found to be strongly anti-correlated with the maximum piezoresponse at that location, suggesting smaller disorder effects where the polarization reversal is large and vice versa. The disorder in the relaxation amplitudes is postulated to arise from rhombohedral and field-induced tetragonal phase in the crystal, with each phase associated with its own relaxation amplitude. As a result, these studies highlight the crucial importance of the mixture of ferroelectric phases in the compositions in proximity of the morphotropic phase boundary in governing the local response and further highlight the ability of PFM voltage and time spectroscopies, in conjunction with big-data multivariate analyses, to locally map disorder and correlate it with parameters governing the dynamic behavior.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Aerodynamic Sensitivity of a Novel Data-Driven Airfoil Shape Representation Framework

We explore the aerodynamic implications of a novel data-driven separable shape tensor framework used to represent discrete airfoil shapes. In this study, we construct a data-driven parameter space defined by separable shape tensors and informed by tens of thousands of distinct airfoils. We use this design space to generate new airfoil designs to study parametric sensitivities with respect to various aerodynamic responses. We use a HAM2D RANS solver to approximate the lift, drag, and moment coefficients for the generated airfoils at two different angles-of-attack. We analyze the robustness and sensitivities of using the separable shape tensor design space by examining the coverage of the aerodynamic response space, uncovering low-dimensional polynomial ridge approximations, and computing various sensitivity metrics. The results show that the data-driven design space produce significant variation in target aerodynamic quantities and facilitate highly accurate approximations (R^2 > 0.96) of one- and two-dimensional structures in each aerodynamic response. This further reduces the effective dimension to enable simplified design and optimization tasks.

aerodynamics↗
DOE OSTI2014

SU-E-J-04: A Data-Driven, Response-Based, Multi-Criteria Decision Support System for Personalized Lung Radiation Treatment Planning

Purpose: To develop a decision support tool to predict a patient's potential overall survival (OS) and radiation induced toxicity (RIT) based on clinical factors and responses during the course of radiotherapy, and suggest appropriate radiation dose adjustments to improve therapeutic effect. Methods: Important relationships between a patient's basic information and their clinical features before and during the radiation treatment are identified from historical clinical data by using statistical learning and data mining approaches. During each treatment period, a data analysis (DA) module predicts radiotherapy features such as time to local progression (TTLP), time to distant metastases (TTDM), radiation toxicity to different organs, etc., under possible future treatment plans based on patient specifics or responses. An information fusion (IF) module estimates intervals for a patient's OS and the probabilities of RIT from a treatment plan by integrating the outcomes of module DA. A decision making (DM) module calculates “satisfaction” with the predicted radiation outcome based on trade-offs between OS and RIT, and finds the best treatment plan for the next time period via multi-criteria optimization. Results: Using physical and biological data from 130 lung cancer patients as our test bed, we were able to train and implement the 3 modules of our decision support tool. Examples demonstrate how it can help predict a new patient's potential OS and RIT with different radiation dose plans along with how these combinations change with dose, thus presenting a range of satisfaction/utility for use in individualized decision support. Conclusion: Although the decision support tool is currently developed from a small patient sample size, it shows the potential for the improvement of each patient's satisfaction in personalized radiation therapy. The radiation treatment outcome prediction and decision making model needs to be evaluated with more patients and demonstrated for use in radiation treatments for other cancers. P01-CA59827;R01CA142840.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Scenario analysis for techno-economic model development of U.S. offshore wind support structures

Challenging bathymetry and soil conditions of future US offshore wind power plants might promote the use of multimember, fixed-bottom structures (or 'jackets') in place of monopiles. Support structures affect costs associated with the balance of system and operation and maintenance. Understanding the link between these costs and the main environmental design drivers is crucial in the quest for a lower levelized cost of energy, and it is the main rationale for this work. Actual cost and engineering data are still scarce; hence, we evaluated a simplified engineering approach to tie key site and turbine parameters (e.g. water depth, wave height, tower-head mass, hub height and generator rating) to the overall support weight. A jacket-and-tower sizing tool, part of the National Renewable Energy Laboratory's system engineering software suite, was utilized to achieve mass-optimized support structures for 81 different configurations. This tool set provides preliminary sizing of all jacket components. Results showed reasonable agreement with the available industry data, and that the jacket mass is mainly driven by water depth, but hub height and tower-head mass become more influential at greater turbine ratings. A larger sensitivity of the structural mass to wave height and target eigenfrequency was observed for the deepest water conditions (>40 m). Thus, techno-economic analyses using this model should be based on accurate estimates of actual metocean conditions and turbine parameters especially for deep waters. Finally, the relationships derived from this study will inform National Renewable Energy Laboratory's offshore balance of system cost model, and they will be used to evaluate the impact of changes in technology on offshore wind lower levelized cost of energy.

17 WIND ENERGY↗
DOE OSTI2017

Reforming EIA systems: A critical review of proposals in Brazil

Environmental Impact Assessment (EIA) systems are under pressure in many countries, driven by a call for efficiency and streamlining. Such a phenomenon is particularly clear in Brazil, where, in the past few years, a number of influential associations put forward documents proposing significant changes to environmental licensing and impact assessment regulations. So far, there is no publicly available information about any initiative towards scrutinizing those proposals. The objective of this study was to critically review the merits and drawbacks of the changes proposed in those documents. The analysis triangulated content analysis, focus group and online survey data. The focus group included ten seasoned Brazilian EIA specialists; the survey, based on Likert-scale and open-ended questions, resulted in 322 valid responses from EIA professionals. Results show that the proposals generally agree that the current EIA system, while playing a key role in mitigating impacts and enhancing project design, needs many changes. Nonetheless, the proposals neither offered solutions to overcome political, technical and budget barriers, nor established a sense of priority of the most urgent issues. Findings from the focus group and the survey signaled that a number of proposed actions might face public outcry, and that those changes that do not depend on legislative action are more likely to be implementable. Previous studies about EIA reform focused mostly on the context of developed countries after changes had taken place. This study, while addressing the perspective of a large developing country in a “before-reform” stage, shows that capacity-building is a key requirement in EIA reform. - Highlights: • Brazil's EIA system is under strong pressure for change. • Findings corroborate ineffectiveness in current system. • There are tensions as to the best approaches to overcome problems. • Exact effects of proposals are uncertain. • Low institutional capacity can play strong role in driving EIA reform.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Predicting Large‐Scale Systematic Missing Pipe Attributes in Water Distribution Networks

Water distribution network (WDN) models are an essential tool used by water utilities for hydraulic analysis. Unfortunately, missing data and insufficient resources often make creating and maintaining these models unfeasible. Existing methods to address missing pipe properties, like sequential imputation for missing values and reconstruction using graph metrics, are designed to accommodate random patterns of missing information and require a significant percentage of the system's attributes to be known. However, these data completeness assumptions do not always align with real‐world scenarios where large sections of the WDN model have missing data. To address this challenge, this study proposes a data‐driven approach for estimating pipe diameter when considering different spatial patterns and degrees of data completeness (i.e., 0%–90%). Using data from 16 WDNs in Kentucky, this study compares the use of machine learning (ML) using topological and geospatial features against an existing deterministic approach. Results demonstrate that WDN models with pipe diameters predicted by the proposed ML method had comparable hydraulic performance to the ground truth models. Moreover, results showed that ML method performance varies between WDNs of differing topological classification. Insights from this study help advance the ability to leverage partial data to create and maintain WDN models amid uncertainty and inadequate resources.

Poff, Jason W. [Oregon State Univ., Corvallis, OR ↗
DOE OSTI2015

Conformational sampling enhancement of replica exchange molecular dynamics simulations using swarm particle intelligence

In this paper, we present a new method based on swarm particle social intelligence for use in replica exchange molecular dynamics simulations. In this method, the replicas (representing the different system configurations) are allowed communicating with each other through the individual and social knowledge, in additional to considering them as a collection of real particles interacting through the Newtonian forces. The new method is based on the modification of the equations of motion in such way that the replicas are driven towards the global energy minimum. The method was tested for the Lennard-Jones clusters of N = 4, 5, and 6 atoms. Our results showed that the new method is more efficient than the conventional replica exchange method under the same practical conditions. In particular, the new method performed better on optimizing the distribution of the replicas among the thermostats with time and, in addition, ergodic convergence is observed to be faster. We also introduce a weighted histogram analysis method allowing analyzing the data from simulations by combining data from all of the replicas and rigorously removing the inserted bias.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Fast Evaluation of Aircraft Icing Severity Using Machine Learning Based on XGBoost

Aircraft icing represents a serious hazard in aviation which has caused a number of fatal accidents over the years. In addition, it can lead to substantial increase in drag and weight, thus reducing the aerodynamics performance of the airplane. The process of ice accretion on a solid surface is a complex interaction of aerodynamic and environmental variables. The complex relationship makes machine learning-based methods an attractive alternative to traditional numerical simulation-based approaches. In this study, we introduce a purely data-driven approach to find the complex pattern between different flight conditions and aircraft icing severity prediction. The supervised learning algorithm Extreme Gradient Boosting (XGBoost) is applied to establish the prediction framework which makes prediction based on any set of observations. The input flight conditions for the proposed prediction framework are liquid water content, droplet diameter and exposure time. The proposed approach is demonstrated in three cases: maximum ice thickness prediction, icing area prediction and icing severity level evaluation. Performance comparison studies and error analysis are also conducted to verify the effectiveness and performance of the proposed method. Results show that the proposed method has reasonable capability in evaluating aircraft icing severity.

Li, Sibo (ORCID:000000021705844X)↗
NASA NTRS2002

Flight Performance Evaluation of Three GPS Receivers for Sounding Rocket Tracking

In preparation for the European Space Agency Maxus-4 mission, a sounding rocket test flight was carried out at Esrange, near Kiruna, Sweden on February 19, 2001 to validate existing ground facilities and range safety installations. Due to the absence of a dedicated scientific payload, the flight offered the opportunity to test multiple GPS receivers and assess their performance for the tracking of sounding rockets. The receivers included an Ashtech G12 HDMA receiver, a BAE (Canadian Marconi) Allstar receiver and a Mitel Orion receiver. All of them provide C/A code tracking on the L1 frequency to determine the user position and make use of Doppler measurements to derive the instantaneous velocity. Among the receivers, the G12 has been optimized for use under highly dynamic conditions and has earlier been flown successfully on NASA sounding rockets. The Allstar is representative of common single frequency receivers for terrestrial applications and received no particular modification, except for the disabling of the common altitude and velocity constraints that would otherwise inhibit its use for space application. The Orion receiver, finally, employs the same Mitel chipset as the Allstar, but has received various firmware modifications by DLR to safeguard it against signal losses and improve its tracking performance. While the two NASA receivers were driven by a common wrap-around antenna, the DLR experiment made use of a switchable antenna system comprising a helical antenna in the tip of the rocket and two blade antennas attached to the body of the vehicle. During the boost a peak acceleration of roughly l7g's was achieved which resulted in a velocity of about 1100 m/s at the end of the burn. At apogee, the rocket reached an altitude of over 80 km. A detailed analysis of the attained flight data is given together with a evaluation of different receiver designs and antenna concepts.

Bull, Barton↗
NASA NTRS2018

Characterization of CO Thermochemistry in Incident Shockwaves

Incident shock waves in pure CO have been characterized in the Electric Arc ShockTube facility at NASA Ames Research Center. Spectrally and spatially resolved emissionspectra characterize radiative signatures from CO in the VUV and mid-infrared and atomiccarbon and C2 in the visible. CO absorption of a single vibrational line is also measuredwith a tunable diode laser. The experimental data analyzed here are at a pressure of 0.25Torr in the driven section and span a shock velocity range from 3.4-9.5 km/s. The emissionand absorption signals are analyzed to extract temperature relaxation behind the shockwhich is used to derive the rate of CO dissociation. The emission spectra are compared toresults using different kinetic parameters for CO dissociation and C2 dissociation andexchange. Different rates from the literature are found to match the data from 3.4-6.6 km/sand 6.6-9.5 km/s. Areas for improvement in CO and C2 radiation modeling are suggested onthe basis of the analysis.

CO↗
DOE OSTI2018

Transcriptome-driven integrative exploration of functional state of ureter tissue affected by CAKUT

Aims: (1) to identify the most dysregulated genes in ureter tissue affected by congenital anomalies of the kidney and urinary tract (CAKUT) and to extract the biological meaning of these markers; (2) to describe the key molecular networks in CAKUT and to provide expression validation of the genes selected from these networks. Main methods: Transcriptome data was obtained from ureter samples of CAKUT patients and controls by Illumina iScan microarray. Identification of differentially expressed genes was coupled with subsequent bioinformatics analyses. Expression of candidate genes was validated by qRT-PCR. Key findings: Analysis of the transcriptome led to the identification of 78 commonly dysregulated genes in CAKUT tissue compared to controls. Integrative bioinformatic analyses of differentially expressed genes identified 7 major networks. The targets for qRT-PCR validation were selected as members of the major molecular networks in CAKUT, which had both, the significant high fold change and biological relevance for CAKUT. By qRT-PCR the substantial increase of LCN2, PROM1, SOSTDC1, and decrease of INA, RASD1 and TAC3 mRNA levels was confirmed. Significance: Since CAKUT is a leading cause of end-stage renal disease in children, the search for molecular targets for postnatal therapy is of particular interest. Data described in this study represents the gene expression profile and significant molecular networks specific to human ureter affected by CAKUT. The discovery of impaired molecular factors and processes is the step towards the uncovering of the key mechanisms that reflect CAKUT postnatally and could lead to the affected tissue deterioration and end organ damage. © 2018 Elsevier Inc.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2019

Certification Gap Analysis

This report describes a generic method for addressing any new technology to its associated set of regulations and certification criteria. The result is a framework under which a detailed assessment can be conducted. Using just such a framework, the report maps the detailed updated regulations and evolving ASTM standards to the particular technology planning and tests. As a result, a roadmap of NASA technology is documented that shows clear transfer of technology data to industry (standards developers, as well as technology developers) and the FAA regulatory policy and certification staff upon whom certification and policy will be data-driven. A clear description of benefits and gaps are identified, as well.

Herbert Schlickenmaier↗
DOE OSTI2025

Chapter 4 - Recent Advances in Identification of Differential Equations from Noisy Data: IDENT Review

Differential equations and numerical methods are extensively used to model various real-world phenomena in science and engineering. With modern developments, we aim to find the underlying differential equation from a single observation of time-dependent data. If we assume that the differential equation is a linear combination of various linear and nonlinear differential terms, then the identification problem can be formulated as solving a linear system. The goal then reduces to finding the optimal coefficient vector that best represents the time derivative of the given data. We review some recent works on the identification of differential equations. We find some common themes for the improved accuracy: (i) The formulation of linear system with proper denoising is important, (ii) how to utilize sparsity and model selection to find the correct coefficient support needs careful attention, and (iii) there are ways to improve the coefficient recovery. We present an overview and analysis of recent developments on the topic.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Automated model generation and parameter estimation of building energy models using an ontology-based framework

This study presents a methodology for automated model generation and parameter estimation of building energy models using semantic modeling and Bayesian estimation. Semantic modeling techniques are used to represent the system components and their interactions, facilitating the automatic generation of a simulation model from dynamic component models. The proposed approach is applied to a case study of a ventilation system where a simulation model is generated, calibrated, and assessed through different performance metrics. These metrics demonstrate the accuracy and reliability of both model point estimates and probabilistic prediction intervals across all model outputs. Overall, the proposed methodology offers a systematic and automated approach to model development and calibration in building energy systems, with potential applications in building performance analysis, monitoring, and optimization.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

From Count Rates to Quantifying Isotopic Activities – Field Analysis of Radiation Monitoring Data

The Nevada National Security Site (NNSS) provides a comprehensive bicoastal radiological and nuclear emergency response to United States Department of Energy/National Nuclear Security Administration. A major part of the support is to provide systematic radiological search for lost or stolen sources, Radiological search is a core competency of the NNSS with its origin dating back to nuclear weapons test era. Search operations from multiple platforms is the common thread among the various NNSS assets, which include Aerial Measuring System (AMS), Maritime Support Team (MST), National Capitol Response (NCR), National Search Team (NST) and Radiological Assistance Program (RAP). Information collected and analyzed during search operations add to the actionable intelligence for the law enforcement agencies and provide valuable guidance for the tactical resolution of a nuclear or radiological crisis. Search is an intelligence and situational awareness driven operation and most often called upon during a radiological emergency, however it can be brought into play to thwart a potential threat by providing monitoring and surveillance support. The Office of Nuclear Incident Response (NA-84) serves as the technical leader in responding to and resolving nuclear and radiological threats worldwide and integrates its efforts with other NNSA stakeholders (e.g., NNSA office of Defense Nuclear Non-proliferation NA-22). The response includes expertise in the areas of radiological search, render safe, and consequence management. This article will discuss the methodologies, tools, procedures, and techniques to extract maximum radiological characterization information (isotopic composition, activities for individual isotopes, threat assessment etc.) from field monitoring or Search operation data.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2017

Light-curve Analysis of Ordinary Type IIP Supernovae Based on Neutrino-driven Explosion Simulations in Three Dimensions

Type II-plateau supernovae (SNe IIP) are the most numerous subclass of core-collapse SNe originating from massive stars. In the framework of the neutrino-driven explosion mechanism, we study the properties of the SN outburst for a red supergiant progenitor model and compare the corresponding light curves with observations of the ordinary Type IIP SN 1999em. Three-dimensional (3D) simulations of (parametrically triggered) neutrino-driven explosions are performed with the (explicit, finite-volume, Eulerian, multifluid hydrodynamics) code Prometheus, using a presupernova model of a 15 M {sub ⊙} star as initial data. On approaching homologous expansion, the hydrodynamic and composition variables of the 3D models are mapped to a spherically symmetric configuration, and the simulations are continued with the (implicit, Lagrangian, radiation hydrodynamics) code Crab to follow the evolution of the blast wave during the SN outburst. Our 3D neutrino-driven explosion model with an explosion energy of about 0.5×10{sup 51} erg produces {sup 56}Ni in rough agreement with the amount deduced from fitting the radioactively powered light-curve tail of SN 1999em. The considered presupernova model, 3D explosion simulations, and light-curve calculations can explain the basic observational features of SN 1999em, except for those connected to the presupernova structure of the outer stellar layers. Our 3D simulations show that the distribution of {sup 56}Ni-rich matter in velocity space is asymmetric with a strong dipole component that is consistent with the observations of SN 1999em. The monotonic decline in luminosity from the plateau to the radioactive tail in ordinary SNe IIP is a manifestation of the intense turbulent mixing at the He/H composition interface.

79 ASTRONOMY AND ASTROPHYSICS↗