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At least 433 records · Page 24

Correlated Topics in a Scalable Multidimensional Text Cube: Algorithms and Aviation Safety Case Study

As world-wide air traffic continues to grow even at a modest pace, the overall complexity of the system will increase significantly. This increased complexity can lead to a larger number of fatalities per year even if the extremely low fatality rate that we currently enjoy is maintained. One important source of information about the safety of the aviation system is in Aviation Safety Text Reports which are written by members of the flight crew, air traffic controllers, and other parties involved with the aviation system. These anonymized narrative reports contain fixed-field contextual information about the flight but also contain free-form narratives that describe, in the author s own words, the nature of the safety incident and, in many cases, the contributing factors that led to the safety incident. Several thousand such reports are filed each month, each of which is read and analyzed by highly trained experts. However, it is possible that there are emerging safety issues due to the fact that they may be reported very infrequently and in different contexts with different descriptions. The goal of this research paper is to develop correlated topic models which uncover correlations in the subspaces defined by the intersection of numerous fixed fields and discovered correlated topics. This task requires the discovery of latent topics in the text reports and the creation of a topic cube. Furthermore, because the number of potential cells in the topic cube is very large, we discuss novel methods of pruning the search space in the topic cells, thereby making the analysis feasible. We demonstrate the new algorithms on an analysis of pilot fatigue and its contributing factors, as well as the safety incidents that are correlated with this phenomenon.

Zhao, Bo↗

Improving photovoltaic hosting capacity of distribution networks with coordinated inverter control: A case study of the EPRI J1 feeder

Abstract Adding photovoltaic (PV) systems in distribution networks, while desirable for reducing the carbon footprint, can lead to voltage violations under high solar‐low load conditions. The inability of traditional volt‐VAr control in eliminating all the violations is also well‐known. This article presents a novel coordinated inverter control methodology that leverages system‐wide situational awareness to significantly improve hosting capacity (HC). The methodology employs a real‐time voltage‐reactive power (VQ) sensitivity matrix in an iterative linear optimizer to calculate the minimum reactive power intervention from PV inverters needed for mitigating over‐voltage without resorting to active power curtailing or requiring step voltage regulator setting changes. The algorithm is validated using the EPRI J1 feeder under an extensive set of realistic use cases and is shown to provide 3x improvement in HC under all scenarios.

Dalal, Dhaval [School of Electrical, Computer, and↗

Issues in knowledge representation to support maintainability: A case study in scientific data preparation

Scientific data preparation is the process of extracting usable scientific data from raw instrument data. This task involves noise detection (and subsequent noise classification and flagging or removal), extracting data from compressed forms, and construction of derivative or aggregate data (e.g. spectral densities or running averages). A software system called PIPE provides intelligent assistance to users developing scientific data preparation plans using a programming language called Master Plumber. PIPE provides this assistance capability by using a process description to create a dependency model of the scientific data preparation plan. This dependency model can then be used to verify syntactic and semantic constraints on processing steps to perform limited plan validation. PIPE also provides capabilities for using this model to assist in debugging faulty data preparation plans. In this case, the process model is used to focus the developer's attention upon those processing steps and data elements that were used in computing the faulty output values. Finally, the dependency model of a plan can be used to perform plan optimization and runtime estimation. These capabilities allow scientists to spend less time developing data preparation procedures and more time on scientific analysis tasks. Because the scientific data processing modules (called fittings) evolve to match scientists' needs, issues regarding maintainability are of prime importance in PIPE. This paper describes the PIPE system and describes how issues in maintainability affected the knowledge representation used in PIPE to capture knowledge about the behavior of fittings.

Chien, Steve↗

An uncertainty visualization framework for large-scale cardiovascular flow simulations: A case study on aortic stenosis

We present a generalizable uncertainty quantification (UQ) and visualization framework for lattice Boltzmann method simulations of high Reynolds number vascular flows, demonstrated on a patient-specific stenosed aorta. The framework combines EasyVVUQ for parameter sampling with large-eddy simulation turbulence modeling in HemeLB, and executes ensembles on the Frontier exascale supercomputer. Spatially resolved metrics, including entropy and isosurface-crossing probability, are used to map uncertainty in pressure and wall shear stress fields directly onto vascular geometries. Two sources of model variability are examined: inlet peak velocity and the Smagorinsky constant. Inlet velocity variation produces high uncertainty downstream of the stenosis where turbulence develops, while upstream regions remain stable. Smagorinsky constant variation has little effect on the large-scale pressure field but increases WSS uncertainty in localized high-shear regions. In both cases, the stenotic throat manifests low entropy, indicative of robust identification of elevated WSS. By linking quantitative UQ measures to three-dimensional anatomy, the framework improves interpretability over conventional 1D UQ plots and supports clinically relevant decision-making, with broad applicability to vascular flow problems requiring both accuracy and spatial insight.

Hemodynamics↗

The 27-28 October 1986 FIRE cirrus case study: Meteorology and clouds

Detailed descriptions of the rawinsonde resolved meteorological conditions (3 hourly soundings) associated with a succession of five distinct mesoscale cirrus cloud regimes, that were intensively observed over a 36 hour period, are given. The synoptic scale systems in which these features were embedded are described and a brief overview of the experiment is given. Regional analyses of the static stability structure and vertical motion are presented and interpreted with respect to the characteristics of the corresponding cloud fields as deduced from satellite and lidar observations. The cloud fields exhibited a high degree of persistent mesoscale organization on scales of 20 to 500 km reflecting corresponding scales of dynamic and thermodynamic structure/variability as on the synoptic scale. Cloud generation was usually confined to layers less than 1 km deep (typically 0.5 km in depth) and cellular organization was evident in most cases irrespective of the thermal stratification. Multilayered development was prevalent (2 to 3 layers) and was associated with vertical structure of the temperature and moisture fields resulting primarily from vertical gradients in horizontal advection.

Starr, David↗

Hierarchical Resilience Planning for Networked Microgrids: A Case Study of Puerto Rico

Microgrids can be designed to enhance the energy resilience of communities and critical infrastructures, such as hospitals, data centers, and communication networks, which are vulnerable to frequent weather-related disruption. Coordinating multiple microgrids in a network can leverage the geographical diversity of load and generation resources while enabling resilient and cost-effective planning of the distribution system. Designing a networked microgrid is complex, involving intricate technical assessment, cost-benefit analysis, site-specific requirements, and the evaluation of existing resources. Therefore, this paper proposes a hierarchical resilience planning framework and performs an extensive techno-economic analysis for the design of a networked microgrid. Hierarchical resilience planning involves technology sizing at an individual community level to meet the critical load and satisfy resilience criteria, and resource optimization at networked microgrid level to provide a higher level of resilience and energy adequacy. A real-world case of Puerto Rico's cooperative microgrid “Microrred de la Montaña” is investigated considering localized electricity tariffs, site-specific demand profiles, solar generation, and existing hydro resources. Multiple optimization scenarios are developed based on the resiliency requirement to estimate the capacity of solar photovoltaic and battery energy storage (BES) to be installed at each substation. The results provide the optimal sizing for individual community and networked microgrid to withstand 1day and 3-day outages along with the criteria for critical load.

13 - HYDRO ENERGY↗

The Geometric Factor of Electrostatic Plasma Analyzers: A Case Study from the Fast Plasma Investigation for the Magnetospheric Multiscale mission

We report our findings comparing the geometric factor (GF) as determined from simulations and laboratory measurements of the new Dual Electron Spectrometer (DES) being developed at NASA Goddard Space Flight Center as part of the Fast Plasma Investigation on NASA's Magnetospheric Multiscale mission. Particle simulations are increasingly playing an essential role in the design and calibration of electrostatic analyzers, facilitating the identification and mitigation of the many sources of systematic error present in laboratory calibration. While equations for laboratory measurement of the Geometric Factpr (GF) have been described in the literature, these are not directly applicable to simulation since the two are carried out under substantially different assumptions and conditions, making direct comparison very challenging. Starting from first principles, we derive generalized expressions for the determination of the GF in simulation and laboratory, and discuss how we have estimated errors in both cases. Finally, we apply these equations to the new DES instrument and show that the results agree within errors. Thus we show that the techniques presented here will produce consistent results between laboratory and simulation, and present the first description of the performance of the new DES instrument in the literature.

Magnetospheric Multiscale Mission↗

Design-Filter Selection for H2 Control of Microgravity Isolation Systems: A Single-Degree-of-Freedom Case Study

Many microgravity space-science experiments require active vibration isolation, to attain suitably low levels of background acceleration for useful experimental results. The design of state-space controllers by optimal control methods requires judicious choices of frequency-weighting design filters. Kinematic coupling among states greatly clouds designer intuition in the choices of these filters, and the masking effects of the state observations cloud the process further. Recent research into the practical application of H2 synthesis methods to such problems, indicates that certain steps can lead to state frequency-weighting design-filter choices with substantially improved promise of usefulness, even in the face of these difficulties. In choosing these filters on the states, one considers their relationships to corresponding design filters on appropriate pseudo-sensitivity- and pseudo-complementary-sensitivity functions. This paper investigates the application of these considerations to a single-degree-of-freedom microgravity vibration-isolation test case. Significant observations that were noted during the design process are presented. along with explanations based on the existent theory for such problems.

Hampton, R. David↗

What Multilevel Parallel Programs do when you are not Watching: A Performance Analysis Case Study Comparing MPI/OpenMP, MLP, and Nested OpenMP

With the current trend in parallel computer architectures towards clusters of shared memory symmetric multi-processors, parallel programming techniques have evolved that support parallelism beyond a single level. When comparing the performance of applications based on different programming paradigms, it is important to differentiate between the influence of the programming model itself and other factors, such as implementation specific behavior of the operating system (OS) or architectural issues. Rewriting-a large scientific application in order to employ a new programming paradigms is usually a time consuming and error prone task. Before embarking on such an endeavor it is important to determine that there is really a gain that would not be possible with the current implementation. A detailed performance analysis is crucial to clarify these issues. The multilevel programming paradigms considered in this study are hybrid MPI/OpenMP, MLP, and nested OpenMP. The hybrid MPI/OpenMP approach is based on using MPI [7] for the coarse grained parallelization and OpenMP [9] for fine grained loop level parallelism. The MPI programming paradigm assumes a private address space for each process. Data is transferred by explicitly exchanging messages via calls to the MPI library. This model was originally designed for distributed memory architectures but is also suitable for shared memory systems. The second paradigm under consideration is MLP which was developed by Taft. The approach is similar to MPi/OpenMP, using a mix of coarse grain process level parallelization and loop level OpenMP parallelization. As it is the case with MPI, a private address space is assumed for each process. The MLP approach was developed for ccNUMA architectures and explicitly takes advantage of the availability of shared memory. A shared memory arena which is accessible by all processes is required. Communication is done by reading from and writing to the shared memory.

Jost, Gabriele↗

Dragonfly: A Case Study in Dynamic Stability Characterization

Next decade, the Dragonfly probe will enter Titan’s atmosphere on a mission to explore and characterize its unique and complex organic chemistry. In contrast to Mars entry missions, where the challenge is to slow down in its tenuous atmosphere before impacting the surface, Titan’s thick atmosphere provides generous drag. However, Titan has its own unique EDL challenges. Among these challenges is the long time (on the order of 90 minutes!) the vehicle will need to descend unguided through flow regimes where blunt-body entry probes are known to be dynamically unstable. This elongated timeline, both prior to drogue parachute deployment, and during the ensuing descent, has the potential to allow adverse dynamic instability properties to produce large amplitude oscillations in angle-of-attack. This, in-turn may lead to non-compliance in vehicle attitude requirements for EDL events such as parachute deployment, and lander release, or in the most extreme case, tumbling of the aeroshell and near-assured loss of mission.

EDL↗

Dragonfly: A Case Study in Dynamic Stability Characterization

Next decade, the Dragonfly probe will enter Titan’s atmosphere on a mission to explore and characterize its unique and complex organic chemistry. In contrast to Mars entry missions, where the challenge is to slow down in its tenuous atmosphere before impacting the surface, Titan’s thick atmosphere provides generous drag. However, Titan has its own unique EDL challenges. Among these challenges is the long time (on the order of 90 minutes!) the vehicle will need to descend unguided through flow regimes where blunt-body entry probes are known to be dynamically unstable. This elongated timeline, both prior to drogue parachute deployment, and during the ensuing descent, has the potential to allow adverse dynamic instability properties to produce large amplitude oscillations in angle-of-attack. This, in-turn may lead to non-compliance in vehicle attitude requirements for EDL events such as parachute deployment, and lander release, or in the most extreme case, tumbling of the aeroshell and near-assured loss of mission.

EDL↗

Case Study of Solar Wind and IMF Influence on Ionospheric Outflow

We examine ionospheric outflows in the high attitude magnetospheric polar cap during the POLAR satellite's apogee on 04/19/96 using the TIDE instrument. The pass has a fairly constant flux of H+ which is similar to many other passes, but there is a large amount of O+ present. The elevated levels of O+ may be due both to the geophysical conditions during the apogee pass (Kp=5) and prior to the pass. When the outflows for many high altitude polar cap passes are analyzed the O+ density correlates well with the dynamic pressure. There are several aspects of this pass which are interesting besides the abundance of O+ relative to H+. In this pass both the H+ and O+ outflow velocity correlate with both the solar wind speed and Interplanetary Magnetic Field (IMF) Bx. The geophysical conditions are such that the solar wind speed and IMF Bx are highly correlated with each other. For this case the dynamic pressure of the solar wind is fairly constant and has an average value of about 2.5 nPa which is typical for the solar wind, but the average solar wind speed is about 695 km/s which is greater than 450 km/s which is typical for the solar wind at I AU. The ion outflow measurements themselves are interrelated. The H+ density and parallel speed are anticorrelated which results in the constant flux. The 0+ density does not have as large of a anticorrelation with its parallel speed as H+ does with its parallel speed.

Elliott, H. A.↗

NASA Satellites and Data Fusion: A Case Study with Coral Reefs

As the world is experiencing a significant rise in both AI, Climate, and Space start-up companies, we are in a new wave of limitless innovation. NASA's statutory responsibility is to "provide for the widest practicable and appropriate dissemination of information concerning its activities and the results thereof." (51 U.S.C. § 20112) In particular, through machine learning, the public data drawn from NASA’s space assets can provide insights for addressing climate-related problems here on Earth. And many climate start-up companies can benefit from leveraging this data, either for proof of concepts or their own missions. In the Fall of 2021, several scientists from NASA and Coral Vita led a Practicum with the Georgia Institute of Technology Masters in Data Analytics program. The Practicum saw two teams of students develop and implement machine learning models to infer, from CALIPSO satellite imagery, vitality properties upon satellite pass. This kind of capability can lead to real-time mapping of coral health around the world, giving organization an understanding of where to prioritize reef reconstitution.. In this presentation, we will highlight this use case and discuss other concrete applications in which space data is used to solve problems here on Earth.

Earth Sciences↗

Westerly Wind Events in the Eastern Indian Ocean as a Precursor to El Nino: A Case Study for the 2002-03 El Nino

This paper extends the work of our previous study, which showed the potential of using precipitation in the eastern Indian Ocean to predict when an El Nino would begin. The paper begins by showing the successful prediction of the 2002-03 El Nino. However, precipitation is really used as a substitute for wind (storms are usually accompanied by heavy wind), because a popular hypothesis is that winds (especially % winds out of the West) stir up the ocean surface in the western Pacific sending currents of warm waters to the east Pacific where El Ninos form. This paper shows that it is typical for storms that produce strong winds in the western Pacific to have traveled from the Indian Ocean. We begin in the Indian Ocean looking at strong bursts of wind over several days. The number of windy days seems to increase in the months prior to El Nino. We examined these relationships in detail for November 2001 to April 2002, before the recent El Nino, using NASA's TRMM and QuikSCAT data. We found in one case that a warming of the eastern Indian Ocean occurred about 25 days before heavy rainfall formed. As the stormed moved eastward it was followed (6 days later) by strong winds out of the West. The entire storm system (and warming of the sea) moved eastward through a small strip of water between Indonesia and Australia, before reaching the western Pacific. Thus, this paper increases our understanding of the physical processes leading to the formation of El Nino.

Curtis, Scott↗

A multi‐variable framework for selecting WRF physics configurations at convection‐permitting scales: An Amazon wet‐season case study

Tropical convection over rainforests modulates atmospheric circulation and the energy and hydrological cycles across multiple scales. However, the scarcity of observations still limits our understanding of these processes. Although numerical models are utilized to investigate atmospheric physical processes, their performance depends on the choice of parameterizations and grid resolution. Here, in this work, we introduce and apply a multi‐variable, multi‐physics framework to evaluate and rank the Advanced Research Weather Research and Forecasting (WRF–ARW) configurations at 1‐km resolution over the central Amazon during the wet season. A 48‐member ensemble combines three land‐surface models (LSMs), four planetary boundary layer (PBL), and four microphysics (MP) schemes. Model performance for seven convection‐related near‐surface and boundary‐layer variables is assessed using Taylor diagrams and the Taylor skill score (TSS), analysis of variance (ANOVA)‐based sensitivity metrics, and non‐parametric rank tests. We then construct a combined, weighted TSS to identify configurations that are comparatively robust across variables. Results showed that most configurations reproduce near‐surface temperature, sensible and latent heat fluxes, and boundary‐layer height reasonably well, whereas humidity and rainfall remain challenging. LSM choice has the strongest impact on the surface fluxes and a secondary influence on near‐surface temperature and humidity, PBL schemes dominate boundary‐layer height, and MP schemes exert the largest control on rainfall. No single configuration is optimal for all variables, but the combination of Noah (LSM), Yonsei University (PBL), and Morrison (MP) emerges as the most robust configuration for this case, with the WRF single‐moment six‐class scheme (WSM6) providing a competitive, computationally cheaper MP alternative. The framework is general and can be applied to other regions, seasons, and convective regimes.

Amazon rainforest↗

Cirrus microphysics and radiative transfer: A case study

During the Cirrus Intensive Field Operations of FIRE, data collected by the NCAR King Air in the vicinity of Wausau, WI on October 28 were selected to study the influence of cirrus cloud microphysics on radiative transfer and the role of microphysical approximations in radiative transfer models. The instrumentation of the King Air provided, aside from temperature and wind data, up-and downwelling broadband solar and infrared fluxes as well as detailed microphysical data. The aircraft data, supplied every second, are averaged over the 7 legs to represent the properties for that altitude. The resulting vertical profiles, however, suffer from the fact that each leg represents a different cloud column path. Based on the measured microphysical data particle size distributions of equivalent spheres for each cloud level are developed. Accurate radiative transfer calculations are performed, incorporating atmospheric and radiative data from the ground and the stratosphere. Comparing calculated to the measured up- and downwelling fluxes at the seven cloud levels for both the averaged and the three crossover data will help to assess the validity of particle size and shape approximation as they are frequently used to model cirrus clouds. Once agreement is achieved the model results may be applied to determine, in comparison to a cloudfree case, the influence of this particular cirrus on the radiation budget of the earth atmosphere system.

Kinne, Stefan A.↗

Case studies of NOAA 6/TIROS N data impact on numerical weather forecasts

The impact of satellite temperatures from systems which predate the launching of the third generation of vertical sounding instruments aboard TIROS N (13 Oct 1978) and NOAA 6 (27 June 1979) is reported. The first evaluation of soundings from TIROS N found that oceanic, cloudy retrievals over NH mid latitudes show a cold bias in winter. It is confirmed for both satellite systems using a larger data base. It is shown that RMS differences between retrievals and colocated radiosonde observations within the swath 30-60N during the 1979-80 winter were generally 2-3K in clear air and higher for cloudy columns. A positive impact of TIROS N temperatures on the analysis of synoptic weather systems is shown. Analyses prepared from only satellite temperatures seemed to give a better definition to weather systems' thermal structure than that provided by corresponding NMC analyses without satellite data. The results of a set of 14 numerical forecast experiments performed with the PE model of the Israel Meteorological Service (IMS) are summarized; these were designed to test the impact of TIROS N and NOAA 6 temperatures within the IMS analysis and forecast cycle. The satellite data coverage over the NH, the mean area/period S1 and RMS verification scores and the spatial distribution of SAT versus NO SAT forecast differences are discussed and it is concluded that positive forecast impact occurs over ocean areas where the extra data improve the specification which is otherwise available from conventional observations. The forecast impact for three cases from the same set of experiments was examined and it is found that satellite temperatures, observed over the Atlantic Ocean contribute to better forecasts over Iceland and central Europe although a worse result was verified over Spain. It is also shown that the better scores of a forecast based also on satellite data and verified over North America actually represent a mixed impact on the forecast synoptic patterns. A superior 48 hr 500 mb forecast over the western US due to the better initial specification afforded by satellite observed temperatures over the North Pacific Ocean is shown.

Druyan, L. M.↗

Utilization of O4 Slant Column Density to Derive Aerosol Layer Height from a Space-Borne UV-Visible Hyperspectral Sensor: Sensitivity and Case Study

The sensitivities of oxygen-dimer (O4) slant column densities (SCDs) to changes in aerosol layer height are investigated using the simulated radiances by a radiative transfer model, the linearized pseudo-spherical vector discrete ordinate radiative transfer (VLIDORT), and the differential optical absorption spectroscopy (DOAS) technique. The sensitivities of the O4 index (O4I), which is defined as dividing O4 SCD by 10(sup 40) molecules (sup 2) per centimeters(sup -5), to aerosol types and optical properties are also evaluated and compared. Among the O4 absorption bands at 340, 360, 380, and 477 nanometers, the O4 absorption band at 477 nanometers is found to be the most suitable to retrieve the aerosol effective height. However, the O4I at 477 nanometers is significantly influenced not only by the aerosol layer effective height but also by aerosol vertical profiles, optical properties including single scattering albedo (SSA), aerosol optical depth (AOD), particle size, and surface albedo. Overall, the error of the retrieved aerosol effective height is estimated to be 1276, 846, and 739 meters for dust, non-absorbing, and absorbing aerosol, respectively, assuming knowledge on the aerosol vertical distribution shape. Using radiance data from the Ozone Monitoring Instrument (OMI), a new algorithm is developed to derive the aerosol effective height over East Asia after the determination of the aerosol type and AOD from the MODerate resolution Imaging Spectroradiometer (MODIS). About 80 percent of retrieved aerosol effective heights are within the error range of 1 kilometer compared to those obtained from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) measurements on thick aerosol layer cases.

Air Pollution↗