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At least 145 records · Page 8

A Simple Criterion for Feasibility of Heat Integration between Distillation Streams Based on Relative Volatilities

In a multicomponent distillation configuration, there are numerous sources and sinks of heat, and a potential way to reduce the heat duty requirement is to perform heat integration. Unfortunately, an algorithmic search of the optimal heat integration opportunities is intractable when the required temperatures of intermediate streams are computed via complex models. Instead, in this work, we introduce pressure-scaled pseudo relative volatility, a new metric to compare stream temperatures. Here, we justify the use of pseudo relative volatility by proving that this variable is a monotonically increasing function of the liquid fraction in a saturated mixture stream. Using this metric, we derive a shortcut criterion to check the feasibility of various heat integration opportunities, such as thermal coupling via heat transfer (TCH). The advantage of this approach is that it circumvents the need for explicit temperatures and instead relies on composition, component relative volatilities, and pressure—quantities that are readily available in shortcut models for optimization of distillation configurations. Leveraging this fact, we propose a new optimization framework that identifies feasible TCHs that we consider within the formulation while minimizing the total heat duty of a distillation configuration. We demonstrate, on a few examples, that our formulation can identify heat duty efficient configurations, some of which are multieffect configurations. Using this methodology, we discover configurations that are not only simpler than the fully thermally coupled (FTC) configuration but also have a much lower heat duty.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Real-time nuclear activation detectors for measuring neutron angular distributions at the National Ignition Facility (invited)

The Real Time Nuclear Activation Detector (RTNAD) array at NIF measures the distribution of 14 MeV neutrons emitted by deuterium-tritium (DT) fueled inertial confinement fusion implosions. The uniformity of the neutron distribution is an important indication of implosion symmetry and DT shell integrity. The array consists of 48 LaBr 3 (Ce) crystal gamma-ray spectrometers mounted outside the NIF target chamber, which continuously monitor the slow decay of the 909 keV gamma-ray line from activated 89 Zr located in Zr cups surrounding each crystal. The measured decay rate dramatically increases during a DT implosion in proportion to the number of 14 MeV neutrons striking each Zr cup. The neutrons produce activated 89 Zr through an (n, 2n) reaction on 90 Zr, which is insensitive to low energy neutrons. The neutron flux along the detector line-of-sight at shot time is determined by extrapolating the fitted 909 keV decay curve back to shot time. Automatic analysis algorithms were developed to handle the non-stop data stream. The large number of detectors and the high statistical accuracy of the array enable the spherical harmonic modes of the neutron angular distribution to be measured up to L ≤ 4 to provide a better understanding of implosion dynamics. In addition, these data combined with measurements of the down-scattered neutrons can be used to derive fuel areal density distributions. This paper will describe the RTNAD hardware and analysis procedures.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Simulation of an inductively coupled plasma with a two-dimensional Darwin particle-in-cell code

A two-dimensional particle-in-cell code for the simulation of low-frequency electromagnetic processes in laboratory plasmas has been developed. The code uses the Darwin method omitting the electromagnetic wave propagation. The Darwin method separates the electric field into solenoidal and irrotational parts. The solenoidal electric field is calculated with a new algorithm based on the equation for the electric field vorticity. The system of linear equations in the new algorithm is readily solved using a standard iterative method. The irrotational electric field is the electrostatic field calculated with the direct implicit algorithm. The code is verified by reproducing the two-stream instability, electron electromagnetic waves, and shear Alfvén waves. The code is applied to simulate an inductively coupled plasma with the driving current flowing around the plasma region. In this simulation, a ring of dense plasma forms at the initial stage but then the density becomes maximal in the center and decays monotonically toward the walls. The skin effect is in the transitional mode between local and non-local, and the electron velocity distribution function is non-Maxwellian.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Online Voltage Event Detection Using Synchrophasor Data with Structured Sparsity-Inducing Norms

This paper develops an accurate and computationally efficient data-driven framework to detect voltage events from PMU data streams. It develops an innovative Proximal Bilateral Random Projection (PBRP) algorithm to quickly decompose the PMU data matrix into a low-rank matrix, a row-sparse event-pattern matrix and a noise matrix. Here, the row-sparse pattern matrix significantly distinguishes events from normal behavior. These matrices are then fed into a clustering algorithm to separate voltage events from normal operating conditions. Large-scale numerical study results on real-world PMU data show that the proposed algorithm is computationally more efficient and achieves higher F scores than state-of-the-art benchmarks.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Basic data requirements for microwave radiometer systems

Microwave radiometry has emerged over the last two decades to become an integral part of the field of environmental remote sensing. Numerous investigations were conducted to evaluate the use of microwave radiometry for atmospheric, oceanographic, hydrological, and geological applications. Remote sensing of the earth using microwave radiometry began in 1968 by the Soviet satellite Cosmos 243, which included four microwave radiometers (Ulably, 1981). Since then, microwave radiometers were included onboard many spacecraft, and were used to infer many physical parameters. Some of the basic concepts of radiometric emission and measurement will be discussed. Several radiometer systems are presented and an overview of their operation is discussed. From the description of the radiometer operation the data stream required from the radiometer and the general type of algorithm required for the measurement is discussed.

Lawrence, R. W.↗

Data Mining at NASA: From Theory to Applications

This slide presentation demonstrates the data mining/machine learning capabilities of NASA Ames and Intelligent Data Understanding (IDU) group. This will encompass the work done recently in the group by various group members. The IDU group develops novel algorithms to detect, classify, and predict events in large data streams for scientific and engineering systems. This presentation for Knowledge Discovery and Data Mining 2009 is to demonstrate the data mining/machine learning capabilities of NASA Ames and IDU group. This will encompass the work done re cently in the group by various group members.

Srivastava, Ashok N.↗

Computation of Domain-Averaged Shortwave Irradiance by a One-Dimensional Algorithm Incorporating Correlations between Optical Thickness and Direct Incident Radiation

A one-dimensional radiative transfer algorithm that accounts for correlations between the optical thickness and the incident direct solar radiation is developed to compute the domain-averaged shortwave irradiance profile. It divides the direct irradiance into four components and treats the direct irradiance in two separate, clear and cloudy columns to account for the fact that clouds attenuate the direct irradiance more than clear-sky. The horizontal inhomogeneity of clouds in the cloudy column is treated by the gamma weighted two-stream approximation, which assumes that the optical thickness of clouds follows a gamma distribution. The algorithm inputs the cloud fraction, cumulative cloud fraction as a function of height, and a parameter expressing the shape of the probability density function of the cloud optical thickness distribution in addition to inputs required for a two-stream radiative transfer model. These cloud property inputs can be obtained using ground- and satellite-based instruments. Therefore, the algorithm can treat realistic cloud overlap features and horizontal inhomogeneity of clouds in a framework of one- dimensional radiative transfer. Heating rates computed by the algorithm using cloud fields generated by cloud resolving models agree with those computed with a Monte Carlo model. If optical properties in computational layers that divide a vertically extensive cloud are correlated, the irradiance profile computed by the algorithm further improves.

Kato, S.↗

Quantification of Lanthanides in a Molten Salt Reactor Surrogate Off-Gas Stream Using Laser-Induced Breakdown Spectroscopy

To enable the deployment of molten salt reactor technology, the development of off-gas treatment systems and advanced monitoring tools capable of operating with high temperatures and radiation fields while delivering near real-time information is necessary. Here, we aim to fulfill this requirement and proposes laser-induced breakdown spectroscopy (LIBS) for monitoring molten salt aerosol streams. A sheath gas measuring method was developed to protect optical elements from aerosol particles and to ensure a relatively constant aerosol stream for measurement. An aqueous system was studied to demonstrate the utility of LIBS for monitoring possible fission products in an aerosol stream: Gd, Nd, and Sm up to 2000 parts per million (ppm). A calibration model was built using partial least squares (PLS) regression with five, six, and nine latent variables for Gd, Nd, and Sm, respectively. This calibration model successfully estimated the concentrations of three test samples, which were validated with inductively charged plasma optical emission spectroscopy measurements at a 99.9% confidence interval. To enhance these models, a genetic algorithm was used to filter the spectra before entering the PLS model, thereby limiting the spectral features being regressed to those with greater correlations to concentration. This allowed for the number of latent variables used in the PLS models to be reduced to four, three, and three for Gd, Nd, and Sm, respectively. Finally, the genetic algorithm-filtered PLS models were used to predict the concentrations of the aerosol stream on a real-time dataset and resulted in a 73%, 18%, and 25% improvement in root mean squared error of prediction compared to the original PLS models developed.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Random Forest Regressor-Based Approach for Detecting Fault Location and Duration in Power Systems

Power system failures or outages due to short-circuits or “faults” can result in long service interruptions leading to significant socio-economic consequences. It is critical for electrical utilities to quickly ascertain fault characteristics, including location, type, and duration, to reduce the service time of an outage. Existing fault detection mechanisms (relays and digital fault recorders) are slow to communicate the fault characteristics upstream to the substations and control centers for action to be taken quickly. Fortunately, due to availability of high-resolution phasor measurement units (PMUs), more event-driven solutions can be captured in real time. In this paper, we propose a data-driven approach for determining fault characteristics using samples of fault trajectories. A random forest regressor (RFR)-based model is used to detect real-time fault location and its duration simultaneously. This model is based on combining multiple uncorrelated trees with state-of-the-art boosting and aggregating techniques in order to obtain robust generalizations and greater accuracy without overfitting or underfitting. Four cases were studied to evaluate the performance of RFR: 1. Detecting fault location (case 1), 2. Predicting fault duration (case 2), 3. Handling missing data (case 3), and 4. Identifying fault location and length in a real-time streaming environment (case 4). A comparative analysis was conducted between the RFR algorithm and state-of-the-art models, including deep neural network, Hoeffding tree, neural network, support vector machine, decision tree, naive Bayesian, and K-nearest neighborhood. Experiments revealed that RFR consistently outperformed the other models in detection accuracy, prediction error, and processing time.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Online Event Detection in Synchrophasor Data with Graph Signal Processing

Online detection of anomalies is crucial to enhancing the reliability and resiliency of power systems. We propose a novel data-driven online event detection algorithm with synchrophasor data using graph signal processing. In addition to being extremely scalable, our proposed algorithm can accurately capture and leverage the spatio-temporal correlations of the streaming PMU data. This paper also develops a general technique to decouple spatial and temporal correlations in multiple time series. Finally, we develop a unique framework to construct a weighted adjacency matrix and graph Laplacian for product graph. Case studies with real-world, large-scale synchrophasor data demonstrate the scalability and accuracy of our proposed event detection algorithm. Compared to the state-of-the-art benchmark, the proposed method not only achieves higher detection accuracy but also yields higher computational efficiency.

Event detection↗

Online Event Detection in Synchrophasor Data with Graph Signal Processing

Online detection of anomalies is crucial to enhancing the reliability and resiliency of power systems. We propose a novel data-driven online event detection algorithm with synchrophasor data using graph signal processing. In addition to being extremely scalable, our proposed algorithm can accurately capture and leverage the spatio-temporal correlations of the streaming PMU data. This paper also develops a general technique to decouple spatial and temporal correlations in multiple time series. Finally, we develop a unique framework to construct a weighted adjacency matrix and graph Laplacian for product graph. Case studies with real-world, large-scale synchrophasor data demonstrate the scalability and accuracy of our proposed event detection algorithm. Compared to the state-of-the-art benchmark, the proposed method not only achieves higher detection accuracy but also yields higher computational efficiency.

24 POWER TRANSMISSION AND DISTRIBUTION↗

The continuous readout stream of the MicroBooNE liquid argon time projection chamber for detection of supernova burst neutrinos

The MicroBooNE continuous readout stream is a parallel readout of the MicroBooNE liquid argon time projection chamber (LArTPC) which enables detection of non-beam events such as those from a supernova neutrino burst. The low energies of the supernova neutrinos and the intense cosmic-ray background flux due to the near-surface detector location makes triggering on these events very challenging. Instead, MicroBooNE relies on a delayed trigger generated by SNEWS (the Supernova Early Warning System) for detecting supernova neutrinos. The continuous readout of the LArTPC generates large data volumes, and requires the use of real-time compression algorithms (zero suppression and Huffman compression) implemented in an FPGA (field-programmable gate array) in the readout electronics. In this paper we present the results of the optimization of the data reduction algorithms, and their operational performance. To demonstrate the capability of the continuous stream to detect low-energy electrons, a sample of Michel electrons from stopping cosmic-ray muons is reconstructed and compared to a similar sample from the lossless triggered readout stream.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Support for the Harvard University Water Vapor and Total Water Instruments for the 2004 NASA WB57 Middle Latitude Cirrus Experiment

In order to improve our understanding of the role clouds play in the climate system, NASA is investing considerable effort in characterizing clouds with instruments ranging from passive remote sensors on board the EOS platforms, to the forthcoming active remote sensors on Cloudsat and Calipso. These missions, when taken together, have the capacity to advance our understanding of the coupling between various components of the hydrologic cycle and the atmospheric circulation, and hold the additional potential of leading to significant improvements in the characterization of cloud feedbacks in global models. This is especially true considering that several of these platforms will be flown in an identical orbit within several minutes of one another-a constellation of satellites known as the A-Train. The algorithms that are being implemented and developed to convert these new data streams from radiance and reflectivity measurements into geophysical parameters invariably rely on some set of simplifymg assumptions and empirical constants. Uncertainties in these relationships lead to poorly understood random and systematic errors in the retrieved properties. This lack of understanding introduces ambiguity in interpreting the data and in using the global data sets for their intended purposes. In light of this, a series of flights with the W57F was proposed to address certain specific issues related to the basic properties of mid latitude cirrus clouds: the NASA WE357 Middle Latitude Cirrus Experiment ("MidCiX"). The science questions addressed are: 1) Can cloud property retrieval algorithms developed for A-Train active and passive remote sensing measurements accurately characterize the microphysical properties of synoptic and convectively generated cirrus cloud systems? 2) What are the relationships between the cirrus particle mass, projected area, and particle size spectrum in various genre of cirrus clouds? 3) Does the present compliment of state of the art in situ cloud probes provide the level of precision and accuracy needed to develop and validate algorithms and to contribute to our understanding of the characteristics and microphysical processes operating in cirrus clouds?

Anderson, James G.↗

PvaPy streaming framework for real-time data processing

User facility upgrades, new measurement techniques, advances in data analysis algorithms as well as advances in detector capabilities result in an increasing amount of data collected at X-ray beamlines. Some of these data must be analyzed and reconstructed on demand to help execute experiments dynamically and modify them in real time. In turn, this requires a computing framework for real-time processing capable of moving data quickly from the detector to local or remote computing resources, processing data, and returning results to users. In this paper, we discuss the streaming framework built on top of PvaPy, a Python API for the EPICS pvAccess protocol. We describe the framework architecture and capabilities, and discuss scientific use cases and applications that benefit from streaming workflows implemented on top of this framework. We also illustrate the framework's performance in terms of achievable data-processing rates for various detector image sizes.

EPICS pvAccess↗

Mu2e DAQ and slow control systems

The Mu2e experiment at the Fermilab Muon Campus will search for the coherent neutrinoless conversion of a muon into an electron in the feld of an aluminum nucleus with a sensitivity improvement by a factor of 10,000 over existing limits. The Mu2e Trigger and Data Acquisition System (TDAQ) uses otsdaq as the online Data Acquisition System (DAQ) solution. Developed at Fermilab, otsdaq integrates both the artdaq DAQ and the art analysis frameworks for event transfer, fltering, and processing. otsdaq is an online DAQ software suite with a focus on fexibility and scalability and provides a multiuser, web-based, interface accessible through a web browser. The data stream from the detector subsystems is read by a software flter algorithm that selects events which are combined with the data fux coming from a Cosmic Ray Veto System. The Detector Control System (DCS) has been developed using the Experimental Physics and Industrial Control System (EPICS) open source platform for monitoring, controlling, alarming, and archiving. The DCS System has been integrated into otsdaq. A prototype of the TDAQ and the DCS systems has been built at Fermilab’s Feynman Computing Center. In this paper, we report on the progress of the integration of this prototype in the online otsdaq software.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

MHD mode tracking using high-speed cameras and deep learning

Abstract We present a new algorithm to track the amplitude and phase of rotating magnetohydrodynamic (MHD) modes in tokamak plasmas using high speed imaging cameras and deep learning. This algorithm uses a convolutional neural network (CNN) to predict the amplitudes of the n = 1 sine and cosine mode components using solely optical measurements from one or more cameras. The model was trained and tested on an experimental dataset consisting of camera frame images and magnetic-based mode measurements from the High Beta Tokamak - Extended Pulse (HBT-EP) device, and it outperformed other, more conventional, algorithms using identical image inputs. The effect of different input data streams on the accuracy of the model’s predictions is also explored, including using a temporal frame stack or images from two cameras viewing different toroidal regions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Data acquisition and slow control interface for the Mu2e experiment

The Mu2e experiment at the Fermilab Muon Campus will search for the coherent neutrinoless conversion of a muon into an electron in the field of an aluminum nucleus with a sensitivity improvement by a factor of 10000 over existing limits. The Mu2e Trigger and Data Acquisition System (TDAQ) uses otsdaq as the online Data Acquisition System (DAQ) solution. Developed at Fermilab, otsdaq integrates both the artdaq DAQ and the art analysis frameworks for event transfer, filtering, and processing. otsdaq is an online DAQ software suite with a focus on flexibility and scalability and provides a multi-user, web-based, interface accessible through a web browser. The data stream from the detector subsystems is read by a software filter algorithm that selects events which are combined with the data flux coming from a cosmic ray veto system. The Detector Control System (DCS) has been developed using the Experimental Physics and Industrial Control System (EPICS) open source platform for monitoring, controlling, alarming, and archiving. The DCS system has been integrated into otsdaq. A prototype of the TDAQ and the DCS systems has been built at Fermilab's Feynman Computing Center. In this study, we report on the progress of the integration of this prototype in the online otsdaq software.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Probing the Galactic halo with RR Lyrae stars – II. The substructures of the Milky Way

ABSTRACT We identify substructures of the Galactic halo using 3003 type ab RR Lyrae stars with six-dimensional position–velocity information from the Sloan Digital Sky Survey, the Large Sky Area Multi-Object Fiber Spectroscopic Telescope and the Gaia Early Data Release 3. Based on this information, we define the separation of any two of the stars in the integrals of motion space and we identify substructures by utilizing the friends-of-friends algorithm. We identify members belonging to several known substructures: the Sagittarius stream, the Gaia-Enceladus-Sausage (GES), the Sequoia and the Helmi streams. In addition to these known substructures, there are three other substructures possibly associated with globular clusters NGC 5272, 6656 and 5024, respectively. Finally, we also find three remaining unknown substructures, one of which has large angular momentum and a mean metallicity −2.13 dex, which may be a new substructure. As for the GES, we find that it accounts for a large part of substructures in the inner halo and the apocentre distance is in the range 10–34 kpc, which suggests that the GES is mainly distributed in the inner halo. The near one-third proportion of the GES and the peak value of 20 kpc of the apocentre distance suggest that the GES could account for the break in the density profile of the Galactic halo at the Galactocentric distance ~20–25 kpc. The similarity when comparing the kinematic properties of the GES with the Hercules–Aquila Cloud and Virgo Overdensity suggests that the three substructures may have similar origins.

79 ASTRONOMY AND ASTROPHYSICS↗