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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Encoding Frequency Constraints in Preventive Unit Commitment Using Deep Learning With Region-of-Interest Active Sampling

With the increasing penetration of renewable energy, frequency response and its security are of significant concerns for reliable power system operations. Frequency-constrained unit commitment (FCUC) is proposed to address this challenge. Despite existing efforts in modeling frequency characteristics in unit commitment (UC), current strategies can only handle oversimplified low-order frequency response models and do not consider wide-range operating conditions. This paper presents a generic data-driven framework for FCUC under high renewable penetration. Here, deep neural networks (DNNs) are trained to predict the frequency response using real data or high-fidelity simulation data. Next, the DNN is reformulated as a set of mixed-integer linear constraints to be incorporated into the ordinary UC formulation. In the data generation phase, all possible power injections are considered, and a region-of-interest active sampling is proposed to include power injection samples with frequency nadirs closer to the UFLC threshold, which enhances the accuracy of frequency constraints in FCUC. The proposed FCUC is investigated on the IEEE 39-bus system. Then, a full-order dynamic model simulation using PSS/E verifies the effectiveness of FCUC in frequency-secure generator commitments.

42 ENGINEERING↗
NASA NTRS2005

Study of Some Planetary Atmospheres Features by Probe Entry and Descent Simulations

Characterization of planetary atmospheres is analyzed by its effects in the entry and descent trajectories of probes. Emphasis is on the most important variables that characterize atmospheres e.g. density profile with altitude. Probe trajectories are numerically determined with ENTRAP, a developing multi-purpose computational tool for entry and descent trajectory simulations capable of taking into account many features and perturbations. Real data from Mars Pathfinder mission is used. The goal is to be able to determine more accurately the atmosphere structure by observing real trajectories and what changes are to expect in probe descent trajectories if atmospheres have different properties than the ones assumed initially.

Gil, P. J. S.↗
NASA NTRSDate not supplied

Validation of A Simulation Environment for Future Space Traffic Management

This study presents initial results of a newly developed simulation environment intendedto explore and assess future Space Traffic Management (STM) scenarios. The number ofnew Resident Space Objects (RSOs) in near-Earth orbit is expected to increase significantlywith the expected future deployment of a number of large constellations. These futurescenarios involve the addition of many tens of thousands of new RSOs, making the analysisinto their impact on collision risk extend beyond what traditional data-mining of present-dayconjunction data can reliably predict. To address this, a robust simulation environment wasdeveloped that implements a full force-model for orbit propagation, and computes continuousall-on-all conjunction statistics for arbitrarily large catalog sizes and simulation timeframes.Collision avoidance and station-keeping maneuvers can be optionally implemented based onconfigurable user inputs including physical characteristics and spacecraft meta-data (e.g.,commercial/government, owner country, etc.). Constellation build-out and de-orbit scenarioswere also implemented and modeled based on real-data analysis. Validation of the simulationresults was a critical component of the simulation development, and was done using the currentcatalog with comparisons against both public and internal NASA data-sets. The comparisonsdemonstrate that, with the appropriate settings, representative levels of conjunction ratesand probabilities can be obtained, providing confidence that the simulation tool can generatemeaningful outcomes for test scenarios. As an initial demonstration of the tool’s capabilities,year-long simulations with station-keeping were conducted to examine conjunction historiesusing both the current object catalog (5800 active satellites) and a hypothetical 60,000 objectscenario involving five potential large constellations. Output metrics include the number ofconjunction events, estimates of collision consequence (fragmentation), delta-V maneuver costs,and the probability of at least one collision occurring. The results highlight the potential thatthe simulation tool has for incorporating and running performance comparisons between, e.g.,various sets of maneuver guidelines, industry norms, and definitions of risk, with the overallobjective of providing actionable data to STM policy makers. The presentation will providean overview of the simulation development and validation efforts, as well as a discussion ofobservations gathered from the initial simulations performed.

conjunction assessment↗
NASA NTRS1994

The real-time display of interferometry data for Goldstone radar astronomy data acquisition

A method for visualizing radar interferometry data in real time has been developed for the Goldstone radar astronomy ranging data-acquisition system. The presentation is similar in appearance to a vector field display or data-based grid. This form was selected to facilitate the recognition of characteristic patterns of local variation in the phase and magnitude of complex elements in a two-dimensional data array. The design emphasized efficiency under the demands of real-time processing and remote monitoring. The interferometry 'phase-magnitude' presentation, as it has come to be called, has been used to monitor radar interferometry experiments on three targets, beginning with the asteroid 4179 Toutatis, and continuing with Mars and Mercury.

Howard, S. D.↗
DOE OSTI2016

in silico Whole Genome Sequencer & Analyzer (iWGS): A Computational Pipeline to Guide the Design and Analysis of de novo Genome Sequencing Studies

The availability of genomes across the tree of life is highly biased toward vertebrates, pathogens, human disease models, and organisms with relatively small and simple genomes. Recent progress in genomics has enabled the de novo decoding of the genome of virtually any organism, greatly expanding its potential for understanding the biology and evolution of the full spectrum of biodiversity. The increasing diversity of sequencing technologies, assays, and de novo assembly algorithms have augmented the complexity of de novo genome sequencing projects in nonmodel organisms. To reduce the costs and challenges in de novo genome sequencing projects and streamline their experimental design and analysis, we developed iWGS (in silico Whole Genome Sequencer and Analyzer), an automated pipeline for guiding the choice of appropriate sequencing strategy and assembly protocols. iWGS seamlessly integrates the four key steps of a de novo genome sequencing project: data generation (through simulation), data quality control, de novo assembly, and assembly evaluation and validation. The last three steps can also be applied to the analysis of real data. iWGS is designed to enable the user to have great flexibility in testing the range of experimental designs available for genome sequencing projects, and supports all major sequencing technologies and popular assembly tools. Three case studies illustrate how iWGS can guide the design of de novo genome sequencing projects, and evaluate the performance of a wide variety of user-specified sequencing strategies and assembly protocols on genomes of differing architectures. iWGS, along with a detailed documentation, is freely available at https://github.com/zhouxiaofan1983/iWGS.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1985

Transport of trace species deduced from LIMS observations

One of the critical problems in the middle atmosphere at this time is understanding the interaction between atmospheric motions and photochemistry, and the way in which these two processes maintain the distributions of photochemically active species such as ozone. Recent work has shown that a great deal can be learned by considering the zonally averaged distributions and transports, i.e., working in the latitude-altitude plane. This 2-dimensional approach has been used in the past in Eulerian formation. Recent work (DUNKERTON, 1978) has shown that formulating the transport problems in terms of the residual mean circulation, which has similarity to the Lagrangian mean motion, results in a more physical picture of the way in which the transport takes place. Here, data from the Limb Infrared Monitor of the Stratosphere (LIMB) experiment are used to investigate how well the residual mean formulation works with real data, in the sense of asking how well the predicted ozone changes match those in regions of the lower stratosphere in which chemical changes may be neglected. This allows a test of the approximations that are made, and of the strengths and weaknesses of this approach to transport calculation.

Gille, J. C.↗
NASA NTRS1992

A new method for recognizing quadric surfaces from range data and its application to telerobotics and automation

Pose and orientation of an object is one of the central issues in 3-D recognition problems. Most of today's available techniques require considerable pre-processing such as detecting edges or joints, fitting curves or surfaces to segment images, and trying to extract higher order features from the input images. We present a method based on analytical geometry, whereby all the rotation parameters of any quadric surface are determined and subsequently eliminated. This procedure is iterative in nature and was found to converge to the desired results in as few as three iterations. The approach enables us to position the quadric surface in a desired coordinate system, and then to utilize the presented shape information to explicitly represent and recognize the 3-D surface. Experiments were conducted with simulated data for objects such as hyperboloid of one and two sheets, elliptic and hyperbolic paraboloid, elliptic and hyperbolic cylinders, ellipsoids, and quadric cones. Real data of quadric cones and cylinders were also utilized. Both of these sets yielded excellent results.

Alvertos, Nicolas↗
NASA NTRS2002

Abstracts for the 2002 Meeting of the AIAA Working Group on Dynamic Space Simulation

Undersampling is sometimes used in order to save memory and reducing digitizing speed requirements for pyroshock data. Many interpolation techniques have been used to estimate the missing peaks due undersampling. The more exotic techniques may not work well when real data that contains noise is used as an input. Various peak interpolation techniques will be evaluated using noisy data in this presentation.

Simpson, Alda D.↗
NASA NTRS2015

Data Recipes: Toward Creating How-To Knowledge Base for Earth Science Data

Both the diversity and volume of Earth science data from satellites and numerical models are growing dramatically, due to an increasing population of measured physical parameters, and also an increasing variety of spatial and temporal resolutions for many data products. To further complicate matters, Earth science data delivered to data archive centers are commonly found in different formats and structures. NASA data centers, managed by the Earth Observing System Data and Information System (EOSDIS), have developed a rich and diverse set of data services and tools with features intended to simplify finding, downloading, and working with these data. Although most data services and tools have user guides, many users still experience difficulties with accessing or reading data due to varying levels of familiarity with data services, tools, and or formats. The data recipe project at Goddard Earth Science Data and Information Services Center (GES DISC) was initiated in late 2012 for enhancing user support. A data recipe is a How-To online explanatory document, with step-by-step instructions and examples of accessing and working with real data (http:disc.sci.gsfc.nasa.govrecipes). The current suite of recipes has been found to be very helpful, especially to first-time-users of particular data services, tools, or data products. Online traffic to the data recipe pages is significant, even though the data recipe topics are still limited. An Earth Science Data System Working Group (ESDSWG) for data recipes was established in the spring of 2014, aimed to initiate an EOSDIS-wide campaign for leveraging the distributed knowledge within EOSDIS and its user communities regarding their respective services and tools. The ESDSWG data recipe group is working on an inventory and analysis of existing data recipes and tutorials, and will provide guidelines and recommendation for writing and grouping data recipes, and for cross linking recipes to data products. This presentation gives an overview of the data recipe activites at GES DISC and ESDSWG. We are seeking requirements and input from a broader data user community to establish a strong knowledge base for Earth science data research and application implementations.

data recipe↗
DOE OSTI2026

Wildfire-Power Grid Interactions: Feedback, Impacts, Monitoring, Modeling, and Mitigation Strategies

Wildfires are increasingly interacting with electric power systems through a two-way hazard chain: fires damage grid assets and trigger cascading outages, while grid faults can ignite new fires under hot, dry, and windy conditions. This review synthesizes the state of knowledge across five domains: (i) physical impacts of flames, heat, and smoke on lines, towers, insulators, and substations; (ii) power-infrastructure-initiated ignitions via conductor clash, high-impedance faults, and corona discharge; (iii) widespread blackouts and disproportionate societal impacts; (iv) multi-scale monitoring spanning laboratory tests, in-situ and grid-integrated sensors, and Earth observation; (v) coupled modeling that links fire behavior with grid operations; and (vi) technological and strategic mitigation pathways spanning prevention, response, and recovery. We integrate these domains into a novel 'feedback-aware' socio-technical framework. Through a longitudinal analysis (2005-2025) of global incidents, we identify that while vegetation contact remains the most frequent ignition source, aging infrastructure failure has emerged as a critical driver of catastrophic 'mega-fires'. We further identify persistent gaps, including limited interoperability of high-frequency grid and environmental data, scarce real-time data assimilation, and under-developed equity metrics for outage management. We conclude by outlining a research agenda to (1) deploy interoperable sensing architectures, (2) advance feedback-coupled fire-grid simulations, and (3) evaluate mitigation portfolios through techno-economic and fairness lenses. Recognizing wildfire-grid interactions as coupled socio-technical systems is essential for protecting infrastructure and communities and for ensuring reliable, sustainable electricity in a changing world.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2011

CIGALEMC: GALAXY PARAMETER ESTIMATION USING A MARKOV CHAIN MONTE CARLO APPROACH WITH CIGALE

We introduce a fast Markov Chain Monte Carlo (MCMC) exploration of the astrophysical parameter space using a modified version of the publicly available code Code Investigating GALaxy Emission (CIGALE). The original CIGALE builds a grid of theoretical spectral energy distribution (SED) models and fits to photometric fluxes from ultraviolet to infrared to put constraints on parameters related to both formation and evolution of galaxies. Such a grid-based method can lead to a long and challenging parameter extraction since the computation time increases exponentially with the number of parameters considered and results can be dependent on the density of sampling points, which must be chosen in advance for each parameter. MCMC methods, on the other hand, scale approximately linearly with the number of parameters, allowing a faster and more accurate exploration of the parameter space by using a smaller number of efficiently chosen samples. We test our MCMC version of the code CIGALE (called CIGALEMC) with simulated data. After checking the ability of the code to retrieve the input parameters used to build the mock sample, we fit theoretical SEDs to real data from the well-known and -studied Spitzer Infrared Nearby Galaxy Survey sample. We discuss constraints on the parameters and show the advantages of our MCMC sampling method in terms of accuracy of the results and optimization of CPU time.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Open Power System Datasets and Open Simulation Engines: A Survey Toward Machine Learning Applications

A major factor behind the success of machine learning (ML) models in multiple domains is the availability and accessibility of large, labeled, and well-organized datasets for training and benchmarking. In comparison, power grid datasets face three major challenges: (i) real-world data is often restricted by regulatory constraints, privacy reasons, or security concerns, making it difficult to obtain and work with; (ii) synthetic datasets, which are created to address these limitations, often have incomplete information and are released using specialized tools, making them inaccessible to the broader community; and, (iii) input-output datasets are difficult to generate through simulation for non-experts because open-source simulators are not known outside the power system community. This survey addresses these challenges by serving as an entry point to publicly available datasets and simulators for researchers venturing in this area. We review the current landscape of open-source power network data, machine models, consumer demand profiles, renewable generation data, and inverter models. We also examine open-source power system simulators, which are crucial for generating high-quality, high-fidelity power grid datasets. We aim to provide a foundation for overcoming data scarcity and advance towards a structured web of datasets and simulators to support the development of ML for power systems.

42 ENGINEERING↗
NASA NTRS2008

Development of Solar Wind Model Driven by Empirical Heat Flux and Pressure Terms

We are developing a time stationary self-consistent 2D MHD model of the solar corona and solar wind as suggested by Sittler et al. (2003). Sittler & Guhathakurta (1999) developed a semiempirical steady state model (SG model) of the solar wind in a multipole 3-streamer structure, with the model constrained by Skylab observations. Guhathakurta et al. (2006) presented a more recent version of their initial work. Sittler et al. (2003) modified the SG model by investigating time dependent MHD, ad hoc heating term with heat conduction and empirical heating solutions. Next step of development of 2D MHD models was performed by Sittler & Ofman (2006). They derived effective temperature and effective heat flux from the data-driven SG model and fit smooth analytical functions to be used in MHD calculations. Improvements of the Sittler & Ofman (2006) results now show a convergence of the 3-streamer topology into a single equatorial streamer at altitudes > 2 R(sub S). This is a new result and shows we are now able to reproduce observations of an equatorially confined streamer belt. In order to allow our solutions to be applied to more general applications, we extend that model by using magnetogram data and PFSS model as a boundary condition. Initial results were presented by Selwa et al. (2008). We choose solar minimum magnetogram data since during solar maximum the boundary conditions are more complex and the coronal magnetic field may not be described correctly by PFSS model. As the first step we studied the simplest 2D MHD case with variable heat conduction, and with empirical heat input combined with empirical momentum addition for the fast solar wind. We use realistic magnetic field data based on NSO/GONG data, and plan to extend the study to 3D. This study represents the first attempt of fully self-consistent realistic model based on real data and including semi-empirical heat flux and semi-empirical effective pressure terms.

Sittler, Edward C., Jr.↗
NASA NTRS1984

Global Scale Diagnosis of FGGE Data

The objective was to perform descriptive global-scale diagnoses of the Goddard Laboratory for Atmospheric Sciences (GLAS) First GARP Global Experiment (GLAS) SOP-1 analyses and to compare these diagnoses against controlled, real-data integrations of the GLAS General Circulation Model (GCM) as well as other data sets. The effects of critical latitudes, the diagnoses of the influence of tropical wind data and latent heating upon the GLAS GCM, investigations of planetary wave structure on various time scales from the diurnal to the monthly, and comparison of the GLAS analyses with other analyses are discussed.

Paegle, J.↗
NASA NTRS2020

Aircraft Engine Run-To-Failure Data Set Under Real Flight Conditions

The generation of data-driven prognostics models requires the availability of datasets with run-to-failure trajectories. In order to contribute to the development of these methods, the dataset provides a new realistic dataset of run-to-failure trajectories for a small fleet of aircraft engines under realistic flight conditions. The damage propagation modelling used for the generation of this synthetic dataset builds on the modelling strategy from previous work [1] and incorporates two new levels of fidelity. First, it considers real flight conditions as recorded on board of a commercial jet [2]. Secondly, it extends the degradation modelling by relating the degradation process to the operation history. The dataset was generated with the Commercial Modular Aero-Propulsion System Simulation (C-MAPSS) dynamical model [3]. More details about the generation process can be found in [4].

CMAPSS↗
NASA NTRS2003

Advanced Observation Operators for GPS Radio Occultation: Validation of the 2D Ray Tracing Approach with CHAMP and SAC-C bending angle and refractivity data - Part 1

Global Positioning System (GPS) Radio Occultations (RO) bending angles and refractivity data characterize mostly the vertical structure of the Earth's atmosphere. We answer the question whether proper simulation of GPS RO data for data assimilation can be obtained with one-dimensional vertical operators, or if accounting also for horizontal atmospheric structures via ray-tracing makes a positive difference when compared with real data. We present a detailed implementation of a geometrical optics multi-plane two-dimensional (2D) ray-tracing as an observation operator to simulate GPS RO bending angles and refractivities within the Finite Volume Data Assimilation System (FVDAS). Comparisons of the outputs of that 2D observation operator with those of simpler ID observation operators are used to generate estimates of errors induced by neglecting tangent point drift (TPD) and horizontal gradients (HG). These error estimates are then confronted with errors estimates derived using 6335 real CHAMP and SAC-C occultations. The agreement for TPD-induced (HG-induced) errors is remarkably positive at altitudes 10-30 km (below 10 km). Comparisons in bending angles O - B STD of the outputs of the multi-plane 2D ray-tracer with those of a vertical Abel transform show reductions of about 8% of the usual O - B bending angle STD due to TPD in the stratosphere (3% due to HG, in the troposphere only). In terms of refractivity, the O - B STD reductions are about 1520% for TPD and 3-5% for HG in the same regions. These reductions are obtained using either 6-hour forecasts or analyses as backgrounds, and using Geometrical Optics (GO) or Canonical Transform (CT) data.

Poli, P.↗
DOE OSTI2023

Simulations and analysis tools for charge-exchange (d, 2 He) reactions in inverse kinematics with the AT-TPC

Charge-exchange (d, 2 He) reactions in inverse kinematics at intermediate energies are a very promising method to investigate the Gamow–Teller transition strength in unstable nuclei. A simulation and analysis software based on the attpcroot package was developed to study this type of reactions with the active-target time projection chamber (AT-TPC). The simulation routines provide a realistic detector response that can be used to understand and benchmark experimental data. Analysis tools and correction routines can be developed and tested from simulations in ATTPCROOT , because they are processed in the same way as the real data. In particular, we study the feasibility of using coincidences with beam-like particles to unambiguously identify the (d, 2 He) reaction channel, and to develop a kinematic fitting routine for future applications. More technically, the impact of space-charge effects in the track reconstruction, and a possible correction method are investigated in detail. Finally, this analysis and simulation package constitutes an essential part of the software development for the fast-beams program with the AT-TPC.

(d,2He)↗
DOE OSTI2023

The entropy of galaxy spectra: how much information is encoded?

Abstract The inverse problem of extracting the stellar population content of galaxy spectra is analysed here from a basic standpoint based on information theory. By interpreting spectra as probability distribution functions, we find that galaxy spectra have high entropy, thus leading to a rather low effective information content. The highest variation in entropy is unsurprisingly found in regions that have been well studied for decades with the conventional approach. We target a set of six spectral regions that show the highest variation in entropy – the 4000 Å break being the most informative one. As a test case with real data, we measure the entropy of a set of high-quality spectra from the Sloan Digital Sky Survey, and contrast entropy-based results with the traditional method based on line strengths. The data are classified into star-forming (SF), quiescent (Q), and active galactic nucleus (AGN) galaxies, and show – independently of any physical model – that AGN spectra can be interpreted as a transition between SF and Q galaxies, with SF galaxies featuring a more diverse variation in entropy. The high level of entanglement complicates the determination of population parameters in a robust, unbiased way, and affects traditional methods that compare models with observations, as well as machine learning (especially deep learning) algorithms that rely on the statistical properties of the data to assess the variations among spectra. Entropy provides a new avenue to improve population synthesis models so that they give a more faithful representation of real galaxy spectra.

Ferreras, Ignacio (ORCID:0000000345843127)↗