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At least 307 records · Page 17

Near-wall turbine closure for curved flows

At present, turbulence closures for curved flows only account for curvature effects in the fully turbulent region where the Reynolds number is large. The justification is that, near a wall, viscous effects dominate and curvature effects are only of secondary importance. Recent direct simulation data show that this assumption is not valid, even for simple two-dimensional fully developed turbulent curved channel flows. This paper presents an approach to develop a near-wall turbulence closure for wall-bounded curved flows. The curved channel direct simulation data is used as a guide to held develop such a closure. The proposed closure has the unique property of approaching conventional high-Reynolds-number Reynolds-stress closures far away from the wall. Hence, curvature effects in both the near-wall and the fully turbulent parts of the flow are accounted for properly. Validations of the closure are carried out with a set of low-Reynolds-number simulation data and with experimental measurements at high Reynolds number. Good agreement is obtained in both cases; in particular, the anisotropic behavior of the normal stresses and the shear stress behavior near the convex and concave walls.

So, R. M. C.↗

A simple model for estimating changes in rainfall erosivity caused by variations in rainfall patterns

Highlights: • A simple relationship was developed for predicting daily erosivity in changing climates. • The relationship depends on precipitation amount and maximum 0.5-h intensity I{sub 0.5} . • The relationship was calibrated using measured climate data and had a R{sup 2} of 0.99. • Simulated daily and annual erosivities were predicted with a R{sup 2} of 0.99 using the relationship. • The relationship was tested using I{sub 24}, showing a R{sup 2} of 0.78 for the simulated data. A major challenge when coupling soil loss models with precipitation forecasts from Global Circulation Models (GCMs) is that their time resolutions do not generally agree. Precipitation forecasts from GCM must be scaled down; however, the distribution of the rainfall intensity, which can affect soil loss as much as precipitation amounts, is usually not considered in this process. Therefore, the objective of this study was to develop a statistical equation for computing event-based rainfall erosivity under changing precipitation patterns using the least amount of information possible. For this purpose, an empirical equation for predicting event-based rainfall erosivity was developed using the product of the total precipitation P and the maximum 0.5-h rainfall intensity, I{sub 0.5}. This equation was calibrated using measured precipitation data from 28 sites in Central Chile and then tested with simulated data with different rainfall patterns from the CLIGEN (CLImate GENerator) weather generator. More than 53,000 rainfall events were analyzed, where the equation consistently provided R{sup 2} values of 0.99 for every dataset used, revealing its robustness when used in potential climate change scenarios in the study site. However, because computing I{sub 0.5} requires estimating precipitation at a high time resolution, the relationship was recalibrated and tested using 1 through 24-h maximum rainfall intensities. Using these intensities, the equation provided erosivity estimates with R{sup 2} ranging from 0.78 to 0.99, where better results were obtained as the resolution of the data increased. This study provides the methodology for building and testing the proposed equation and discusses its advantages and limitations.

54 ENVIRONMENTAL SCIENCES↗

Lightning observations from space shuttle

The experimental program of the Earth Sciences and Applications Division at NASA/MSFC includes development of the Lightning Imaging Sensor (LIS) for the NOAA Earth Observing System (EOS) Polar Platform. The research plan is to use existing lightning information to generate simulated data for the LIS experiment. Navigation algorithms were used to transform pixel locations to latitude and longitude values. The simulated data would then be used to test and develop algorithms for the analysis of LIS data. Individual frames of video imagery obtained from Space Shuttle Missions provide the raw data for the simulation. Individual video frames were digitized to get the pixel locations of lightning flashes. The pixel locations will be used to locate the geographical position of the event. Because of a lack of detailed knowledge of camera orientation with respect to the Space Shuttle, video scenes that contain identifiable city lights were chosen for analysis. A method for locating the payload bay camera axis was developed and tested. Two measurements are needed: the pixel location of the apparent horizon and a timed siting of a known location passing the principal line of the image. Individual video frames were navigated and lightning illuminated clouds were located on the map. Satisfactory agreement in location was achieved for cities and LLP lightning locations. Ground truth measurements were compared to satellite observations. A vertical lightning event was identified on the horizon. Very low frequency (VLF) transmission on this particular occassion shows a strong response to negative cloud to cloud flashes.

Boeck, William L.↗

Myna: Connecting powder bed fusion build data to simulation tools for digital twin applications

Additive manufacturing (AM), as a digital process, can generate a detailed digital thread linking a part’s design and manufacturing to its operational performance. As AM systems advance, an increasing amount of process data is stored in manufacturing databases. In principle, this data can be utilized by simulation-based digital twin approaches, such as real-time process control and asynchronous post-processing guidance. However, few tools currently exist for systematically integrating digital thread data with computational tools. Here, in this study, we propose a software package, called Myna, for connecting data from powder bed fusion processes to simulation tools. The utility of such a platform is demonstrated using build data from the Oak Ridge National Laboratory Manufacturing Demonstration Facility “Peregrine v2023-10” public dataset to automatically configure and run 54 semi-analytical 3DThesis melt pool simulations, 78 numerical Additive FOAM melt pool simulations, and 3 ExaCA microstructure simulations. The simulated, spatially registered microstructures are then compared directly with electron backscatter diffraction characterization of the corresponding as-built part locations. The resulting simulated microstructure showed variation as a function of process parameters, particularly stripe width; however, the experimental data had little variation between the microstructure texture and grain size resulting from different processing conditions. Analysis of the discrepancies suggest that it is possible a two-phase ferritic-austenitic solidification model is needed to accurately predict grain size and texture for certain stainless steel 316L feedstock compositions under powder bed fusion conditions, providing direction for future research. As illustrated here, due to the number and complexity of the simulations involved in AM process-structure–property predictions, automated methods to connect process data and simulations will remain necessary tools for testing hypotheses and implementing digital twin applications.

Knapp, Gerald L. [Oak Ridge National Laboratory (O↗

Simulations and Data analysis for the 35 ton Liquid Argon detector as a prototype for the DUNE experiment

The Deep Underground Neutrino Experiment (DUNE) is a next-generation neutrino experiment which will be built at the Sanford Underground Research Facility (SURF), and will receive a wide-band neutrino beam from Fermilab, 1300~km away. At this baseline DUNE will be able to study many of the properties of neutrino mixing, including the neutrino mass hierarchy and the value of the CP-violating complex phase ($\delta_{CP}$). DUNE will utilise Liquid Argon (LAr) Time Projection Chamber (TPC) (LArTPC) technology, and the Far Detector (FD) will consist of four modules, each containing 17.1~kt of LAr with a fiducial mass of around 10~kt. Each of these FD modules represents around an order of magnitude increase in size, when compared to existing LArTPC experiments. \\ The 35 ton detector is the first DUNE prototype for the single (LAr) phase design of the FD. There were two running periods, one from November 2013 to February 2014, and a second from November 2015 to March 2016. During t he second running period, a system of TPCs was installed, and cosmic-ray data were collected. A method of particle identification was developed using simulations, though this was not applied to the data due to the higher than expected noise level. A new method of determining the interaction time of a track, using the effects of longitudinal diffusion, was developed using the cosmic-ray data. A camera system was also installed in the detector for monitoring purposes, and to look for high voltage breakdowns. \\ Simulations concerning the muon-induced background rate to nucleon decay are performed, following the incorporation of the MUon Simulations UNderground (MUSUN) generator into the DUNE software framework. A series of cuts which are based on Monte Carlo truth information is developed, designed to reject simulated background events, whilst preserving simulated signal events in the $n \rightarrow K^{+} + e^{-}$ decay channel. No background events are seen to survive the app lication of these cuts in a sample of 2~$\times$~10$^9$ muon! s, representing 401.6~years of detector live time. This corresponds to an annual background rate of <~0.44~events$\cdot$Mt$^{-1}\cdot$year$^{-1}$ at 90\% confidence, using a fiducial mass of 13.8~kt.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Deeply learning deep inelastic scattering kinematics

We study the use of deep learning techniques to reconstruct the kinematics of the neutral current deep inelastic scattering (DIS) process in electron–proton collisions. In particular, we use simulated data from the ZEUS experiment at the HERA accelerator facility, and train deep neural networks to reconstruct the kinematic variables Q 2 and x. Our approach is based on the information used in the classical construction methods, the measurements of the scattered lepton, and the hadronic final state in the detector, but is enhanced through correlations and patterns revealed with the simulated data sets. We show that, with the appropriate selection of a training set, the neural networks sufficiently surpass all classical reconstruction methods on most of the kinematic range considered. Rapid access to large samples of simulated data and the ability of neural networks to effectively extract information from large data sets, both suggest that deep learning techniques to reconstruct DIS kinematics can serve as a rigorous method to combine and outperform the classical reconstruction methods.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

HOMOLOGOUS HELICAL JETS: OBSERVATIONS BY IRIS, SDO, AND HINODE AND MAGNETIC MODELING WITH DATA-DRIVEN SIMULATIONS

We report on observations of recurrent jets by instruments on board the Interface Region Imaging Spectrograph, Solar Dynamics Observatory (SDO), and Hinode spacecraft. Over a 4 hr period on 2013 July 21, recurrent coronal jets were observed to emanate from NOAA Active Region 11793. Far-ultraviolet spectra probing plasma at transition region temperatures show evidence of oppositely directed flows with components reaching Doppler velocities of ±100 km s{sup −1}. Raster Doppler maps using a Si iv transition region line show all four jets to have helical motion of the same sense. Simultaneous observations of the region by SDO and Hinode show that the jets emanate from a source region comprising a pore embedded in the interior of a supergranule. The parasitic pore has opposite polarity flux compared to the surrounding network field. This leads to a spine-fan magnetic topology in the coronal field that is amenable to jet formation. Time-dependent data-driven simulations are used to investigate the underlying drivers for the jets. These numerical experiments show that the emergence of current-carrying magnetic field in the vicinity of the pore supplies the magnetic twist needed for recurrent helical jet formation.

79 ASTRONOMY AND ASTROPHYSICS↗

The utility of Bayesian data reconciliation for separations

Data reconciliation methods for separation processes typically rely on classical statistical approaches to generate estimates of true mass flow rates from measurements. Knowledge regarding the uncertainty of these estimates has value in decision making, but is often not acquired. Bayesian approaches intrinsically quantify uncertainty; however, literature for Bayesian data reconciliation of separation processes is scarce. This publication outlines two Bayesian data reconciliation models and provides details for how the models were implemented for the BayesMassBal (V 1.0.0) software package written in R. To demonstrate the advantages of this approach for data reconciliation, the models were first applied to simulated data and then compared to a classical model through a Monte Carlo experiment. In this example, the Bayesian models were found to provide more accurate estimates of the simulated data, while also providing quantitative information on the estimate uncertainty. To demonstrate the use of the technique in a practical problem, the models were also applied to real data collected from a pilot-scale rare earth solvent extraction process. Here, this publication provides a small window into how Bayesian methods can be used for data reconciliation, but findings suggest Bayesian data reconciliation models for separation processes have distinct advantages over classical alternatives.

01 COAL, LIGNITE, AND PEAT↗

Simulating Secure Data Exchange and Storage for Urban Air Mobility Environments

In this paper I give some background on UAM, the need for security in UAM, as well as blockchain. Then I discuss how blockchain can facilitate a secure exchange and storage of data in a UAM environment, focusing on a simulation we developed to that simulates a UAM environment. Specifically, the simulation focuses on the negotiation between UAM operators, PSUs, and the DSS when two operators want to claim the same airspace. We discuss how this process, as well as the subsequent vehicle telemetry data, is captured in the blockchain.

UAM↗

LHC hadronic jet generation using convolutional variational autoencoders with normalizing flows

Abstract In high energy physics, one of the most important processes for collider data analysis is the comparison of collected and simulated data. Nowadays the state-of-the-art for data generation is in the form of Monte Carlo (MC) generators. However, because of the upcoming high-luminosity upgrade of the Large Hadron Collider (LHC), there will not be enough computational power or time to match the amount of needed simulated data using MC methods. An alternative approach under study is the usage of machine learning generative methods to fulfill that task. Since the most common final-state objects of high-energy proton collisions are hadronic jets, which are collections of particles collimated in a given region of space, this work aims to develop a convolutional variational autoencoder (ConVAE) for the generation of particle-based LHC hadronic jets. Given the ConVAE’s limitations, a normalizing flow (NF) network is coupled to it in a two-step training process, which shows improvements on the results for the generated jets. The ConVAE+NF network is capable of generating a jet in 18.30 ± 0.04 μ s , making it one of the fastest methods for this task up to now.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Farpoint: A High-resolution Cosmology Simulation at the Gigaparsec Scale

Abstract In this paper we introduce the Farpoint simulation, the latest member of the Hardware/Hybrid Accelerated Cosmology Code (HACC) gravity-only simulation family. The domain covers a volume of (1000 h −1 Mpc) 3 and evolves close to two trillion particles, corresponding to a mass resolution of m p ∼ 4.6 × 10 7 h −1 M ⊙ . These specifications enable comprehensive investigations of the galaxy–halo connection, capturing halos down to small masses. Further, the large volume resolves scales typical of modern surveys with good statistical coverage of high-mass halos. The simulation was carried out on the GPU-accelerated system Summit, one of the fastest supercomputers currently available. We provide specifics about the Farpoint run and present an initial set of results. The high mass resolution facilitates precise measurements of important global statistics, such as the halo concentration–mass relation and the correlation function down to small scales. Selected subsets of the simulation data products are publicly available via the HACC Simulation Data Portal.

79 ASTRONOMY AND ASTROPHYSICS↗

Flight simulator for hypersonic vehicle and a study of NASP handling qualities

The research goal of the Human-Machine Systems Engineering Group was to study the existing handling quality studies in aircraft with sonic to supersonic speeds and power in order to understand information requirements needed for a hypersonic vehicle flight simulator. This goal falls within the NASA task statements: (1) develop flight simulator for hypersonic vehicle; (2) study NASP handling qualities; and (3) study effects of flexibility on handling qualities and on control system performance. Following the above statement of work, the group has developed three research strategies. These are: (1) to study existing handling quality studies and the associated aircraft and develop flight simulation data characterization; (2) to develop a profile for flight simulation data acquisition based on objective statement no. 1 above; and (3) to develop a simulator and an embedded expert system platform which can be used in handling quality experiments for hypersonic aircraft/flight simulation training.

Ntuen, Celestine A.↗

An Observation Data Driven Simulation and Analysis Framework for Early Stage C. elegans Embryogenesis

Recent developments in cutting-edge live microscopy and image analysis provide a unique opportunity to systematically investigate individual cell’s dynamics as well as simulation-based hypothesis testing. After a summary of data generation and analysis in the observation and modeling efforts related to C. elegans embryogenesis, we develop a systematic approach to model the basic behaviors of individual cells. Next, we present our ideas to model cell fate, division, and movement using 3D time-lapse images within an agent-based modeling framework. Then, we summarize preliminary result and discuss efforts in cell fate, division, and movement modeling. Finally, we discuss the ongoing efforts and future directions for C. elegans embryo modeling, including an inferred developmental landscape for cell fate, a quasi-equilibrium model for cell division, and multi-agent, deep reinforcement learning for cell movement.

3D live images↗

Variance Analysis of Unevenly Spaced Time Series Data

We have investigated the effect of uneven data spacing on the computation of delta (sub chi)(gamma). Evenly spaced simulated data sets were generated for noise processes ranging from white phase modulation (PM) to random walk frequency modulation (FM). Delta(sub chi)(gamma) was then calculated for each noise type. Data were subsequently removed from each simulated data set using typical two-way satellite time and frequency transfer (TWSTFT) data patterns to create two unevenly spaced sets with average intervals of 2.8 and 3.6 days. Delta(sub chi)(gamma) was then calculated for each sparse data set using two different approaches. First the missing data points were replaced by linear interpolation and delta (sub chi)(gamma) calculated from this now full data set. The second approach ignored the fact that the data were unevenly spaced and calculated delta(sub chi)(gamma) as if the data were equally spaced with average spacing of 2.8 or 3.6 days. Both approaches have advantages and disadvantages, and techniques are presented for correcting errors caused by uneven data spacing in typical TWSTFT data sets.

Hackman, Christine↗

A statistical analysis of the dependency of closure assumptions in cumulus parameterization on the horizontal resolution

Simulated data from the UCLA cumulus ensemble model are used to investigate the quasi-universal validity of closure assumptions used in existing cumulus parameterizations. A closure assumption is quasi-universally valid if it is sensitive neither to convective cloud regimes nor to horizontal resolutions of large-scale/mesoscale models. The dependency of three types of closure assumptions, as classified by Arakawa and Chen, on the horizontal resolution is addressed in this study. Type I is the constraint on the coupling of the time tendencies of large-scale temperature and water vapor mixing ratio. Type II is the constraint on the coupling of cumulus heating and cumulus drying. Type III is a direct constraint on the intensity of a cumulus ensemble. The macroscopic behavior of simulated cumulus convection is first compared with the observed behavior in view of Type I and Type II closure assumptions using 'quick-look' and canonical correlation analyses. It is found that they are statistically similar to each other. The three types of closure assumptions are further examined with simulated data averaged over selected subdomain sizes ranging from 64 to 512 km. It is found that the dependency of Type I and Type II closure assumptions on the horizontal resolution is very weak and that Type III closure assumption is somewhat dependent upon the horizontal resolution. The influences of convective and mesoscale processes on the closure assumptions are also addressed by comparing the structures of canonical components with the corresponding vertical profiles in the convective and stratiform regions of cumulus ensembles analyzed directly from simulated data. The implication of these results for cumulus parameterization is discussed.

Xu, Kuan-Man↗

Real-time simulation of F100-PW-100 turbofan engine using the hybrid computer

A real-time hybrid computer simulation of the F100-PW-100 augmented turbofan is presented. The digital portion of the hybrid computer is used to perform the bivariate function generation associated with modeling the performance of the engine's rotating components. The remaining calculations are performed on the analog computer. Steady state simulation data along with sea level, static, transient data are presented to show that the real-time simulation matches baseline digital simulation results over a wide range of power settings and flight conditions. Steady state simulation data are compared with sea level, experimental data to show that the real-time hybrid and baseline digital simulations do adequately predict the performance of the actual engine. FORTRAN listings and analog patching diagrams are provided.

Szuch, J. R.↗

Commercial Building Planning and Retrofitting Strategy for Grid Services

The increasing integration of distributed energy resources (DERs) plays an important role in improving energy consumption efficiency. In September 2020, the Federal Energy Regulatory Commission (FERC) approved Order 2222 which opens wholesale electricity markets to small capacity DERs. The benefit of this new FERC Order 2222 is that DERs, such as rooftop solar panels and batteries, will be able to participate in regional electricity markets and provide grid services. Meanwhile, the planning and operation strategies of DERs are facing new challenges to account for the impact of the wholesale market with numerous uncertainty factors. Therefore, in this paper, we propose a new planning and retrofitting model for long-term commercial buildings that considers both DER investment and market participation. Specifically, we explore the capability of implementing DERs for grid services. The effectiveness of the proposed model is validated using real-world data. Simulation results also validate that participating in grid services can significantly increase revenues through appropriate building energy management and shorten the payback period of DER investments.

building energy management↗

Utilizing the SACADA system to collect simulator training data to inform human reliability analyses - 169

Lack of appropriate human performance data for the development of human reliability analysis (HRA) methods has been identified as a key issue contributing to the method-to-method variability among the HRA methods. The United States Nuclear Regulatory Commission (NRC) worked with domain experts to develop the Scenario Authoring, Characterization, and Debriefing Application (SACADA) system to collect nuclear power plants' licensed operator simulator training and examination data to inform HRA. In the past two decades, significant improvements in understanding and modelling human performance in HRA have affected the perspectives of the types of data to be collected for HRA. A significant change is that human performance is strongly dependent on the context of the tasks to be performed. To incorporate this understanding, the SACADA data taxonomy collects the context and actual performance information of the training objective elements (TOEs) in nuclear plant operator simulator training. This provides a framework consistent with HRA to use context to estimate human error probabilities. It is recognized that measuring crew performance is equally important as improving operator training. SACADA is designed to support the nuclear trainers in capturing this important information that is used to identify training weaknesses and drive continuous improvement. This paper discusses the SACADA taxonomy, the SACADA system's functions, and the supporting software design to enable the SACADA system to be practically implemented in the nuclear power plants' operator simulator training program to collect data for tracking operator performance and HRA analysis. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗