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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 559 records · Page 31
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Seabird distribution is better predicted by abundance of prey than oceanography. A case study in the Gulf of Cadiz (SW, Iberian Peninsula)

Abstract Quantifying factors that influence marine predator distributions is essential to understanding the current and future change in marine biodiversity. Here, we test whether marine predator distribution relates to prey, or is better predicted by other specific habitat features. We examine the correlation between spatial distribution of three seabird species and their prey, as well as environmental proxies (oceanographic characteristics) in the Gulf of Cadiz, NE Atlantic. We modeled the at-sea distribution of Cory's shearwater, Balearic shearwater and Northern gannet, based on: (i) pelagic fish abundance according to acoustic surveys, and (ii) a forecast-model of remotely sensed environmental variables (productivity, sea surface temperature, and salinity). In general, seabird distributions were better predicted by abundance of fish than by environmental variables at the habitat scale. We obtained consistent correlations between seabird presence and the abundance of medium-sized (10–20 cm) sardines, anchovies and Mediterranean horse mackerel, providing information on their preferred prey. Additionally, oceanographic productivity variables moderately contributed to seabird distribution models, with better predictive value for the critically endangered Balearic shearwater and Northern gannet in the summer, whilst the model for Cory's shearwater's produced poorer predictions. Predator–prey combined studies may represent essential tools for an efficient ecosystem-based management of marine environments.

de la Cruz, Andrés (ORCID:0000000203632498)↗
NASA NTRS2018

Infrared Computer-Generated Holograms: Design and Application for the WFIRST Grism Using Wavelength-Tuning Interferometry

Interferometers using computer-generated holograms (CGHs) have become the industry standard to accurately measure aspheric optics. The CGH is a diffractive optical element that can create a phase or amplitude distribution and can be manufactured with low uncertainty using modern lithographic techniques. However, these CGHs have conventionally been used with visible light and piezo-shifting interferometers. Testing the performance of transmissive optics in the infrared requires infrared CGHs and an infrared interferometer. Such an instrument is used in this investigation, which introduces its phase shift via wavelength-tuning. A procedure on how to design and manufacture infrared CGHs and how these were successfully used to model and measure the Wide-Field Infrared Survey Telescope grism elements is provided. Additionally, the paper provides a parametric model, simulation results, and calculations of the errors and measurements that come about when interferometers introduce a phase variation via wavelength-tuning interferometry to measure precision aspheres.

Communication↗
NASA NTRS2019

High-Resolution Mid-Infrared Molecular Line Survey of the Orion Hot Core

The basic building blocks of life are synthesized in space as part of the natural stellar evolutionary cycle, whereby elements ejected into the interstellar medium by dying stars are incorporated back into the dense clouds, which form the next generation of stars and planets. The formation of stars and planets are fundamental to the evolution of matter in the Universe as complex molecules are created and destroyed during this step. Understanding these processes will allow us to answer “What is the relation between the molecules we see in the ISM and the molecular inventory of Earth and the terrestrial planets in the Solar System?” Measuring and cataloging the inventory of organic molecules and understanding their evolution requires observations over a broad wavelength range (IR, MIR, FIR, (sub)mm, and radio) to cover all stages of this evolutionary cycle needed to link interstellar material to that delivered to planets. High-resolution molecular line surveys provide chemical inventories for star forming regions and are essential for studying their chemistry, kinematics and physical conditions. Previous high spectral resolution surveys have been limited to radio, sub-mm and FIR wavelengths; however, Mid-infrared observations are the only way to study symmetric molecules that have no dipole moment and thus cannot be detected in the (sub)mm line surveys from ALMA. Past midinfrared missions such as ISO and Spitzer had low to moderate resolving power that were only able to link broad features with particular molecular bands and could not resolve the individual rovibrational transitions. JWST will provide exceptional sensitivity in the MIR, but will also not have sufficient spectral resolution, which can lead to confusion in identifying the contribution from strong to moderate strength molecular species. We present new results from an on-going high resolution (R ~ 60,000) line survey of the Orion hot core between 12.5 - 28.3 μm and 7 - 8 μm, using the EXES instrument on the SOFIA airborne observatory. SOFIA's higher-resolution and smaller beam compared to ISO allows us to spatially and spectrally isolate the emission towards the hot core. This survey will provide the best infrared measurements (to date) of molecular column densities and physical conditions, providing strong constraints on the current chemical network models for star forming regions. This survey will greatly enhance the inventory of resolved line features in the MIR, making it an invaluable reference to be used by the JWST and ALMA scientific communities.

Rangwala, Naseem↗
DOE OSTI2021

Understanding Type Ia Supernova Distance Biases by Simulating Spectral Variations

In the next decade, transient searches from the Vera C. Rubin Observatory and the Nancy Grace Roman Space Telescope will increase the sample of known Type Ia supernovae (SNe Ia) from ~10 3 to 10 5 . With this reduction of statistical uncertainties on cosmological measurements, new methods are needed to reduce systematic uncertainties. Here, characterizing the underlying spectroscopic evolution of SN Ia remains a major systematic uncertainty in current cosmological analyses, motivating a new simulation tool for the next era of SN Ia cosmology: Build Your Own Spectral Energy Distribution (byosed). byosed is used within the SNANA framework to simulate light curves by applying spectral variations to model SEDs, enabling flexible testing of possible systematic shifts in SN Ia distance measurements. We test the framework by comparing a nominal Roman SN Ia survey simulation using a baseline SED model to simulations using SEDs perturbed with byosed, and investigating the impact of ignoring specific SED features in the analysis. These features include semiempirical models of two possible, predicted relationships: between SN ejecta velocity and light-curve observables, and a redshift-dependent relationship between SN Hubble residuals and host-galaxy mass. We analyze each byosed simulation using the SALT2 and BEAMS with Bias Corrections framework, and estimate changes in the measured value of the dark-energy equation-of-state parameter, w. We find a difference of Δw = –0.023 for SN velocity and Δw = 0.021 for redshift-evolving host mass when compared to simulations without these features. By using byosed for SN Ia cosmology simulations, future analyses (e.g., the Rubin and Roman SN Ia samples) will have greater flexibility to constrain or reduce such SN Ia modeling uncertainties.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2010

The Herschel ATLAS

The Herschel ATLAS is the largest open-time key project that will be carried out on the Herschel Space Observatory. It will survey 570 sq deg of the extragalactic sky, 4 times larger than all the other Herschel extragalactic surveys combined, in five far-infrared and submillimeter bands. We describe the survey, the complementary multiwavelength data sets that will be combined with the Herschel data, and the six major science programs we are undertaking. Using new models based on a previous submillimeter survey of galaxies, we present predictions of the properties of the ATLAS sources in other wave bands.

Eales, S.↗
DOE OSTI2022

DeepAdversaries: examining the robustness of deep learning models for galaxy morphology classification

With increased adoption of supervised deep learning methods for work with cosmological survey data, the assessment of data perturbation effects (that can naturally occur in the data processing and analysis pipelines) and the development of methods that increase model robustness are increasingly important. In the context of morphological classification of galaxies, we study the effects of perturbations in imaging data. In particular, we examine the consequences of using neural networks when training on baseline data and testing on perturbed data. We consider perturbations associated with two primary sources: (a) increased observational noise as represented by higher levels of Poisson noise and (b) data processing noise incurred by steps such as image compression or telescope errors as represented by one-pixel adversarial attacks. We also test the efficacy of domain adaptation techniques in mitigating the perturbation-driven errors. We use classification accuracy, latent space visualizations, and latent space distance to assess model robustness in the face of these perturbations. For deep learning models without domain adaptation, we find that processing pixel-level errors easily flip the classification into an incorrect class and that higher observational noise makes the model trained on low-noise data unable to classify galaxy morphologies. On the other hand, we show that training with domain adaptation improves model robustness and mitigates the effects of these perturbations, improving the classification accuracy up to 23% on data with higher observational noise. Domain adaptation also increases up to a factor of ${\approx}2.3$ the latent space distance between the baseline and the incorrectly classified one-pixel perturbed image, making the model more robust to inadvertent perturbations. Successful development and implementation of methods that increase model robustness in astronomical survey pipelines will help pave the way for many more uses of deep learning for astronomy.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

The Separation and Hα Contrasts of Massive Accreting Planets in the Gaps of Transitional Disks: Predicted Hα Protoplanet Yields for Adaptive Optics Surveys

We present a massive accreting gap planet model that ensures large gaps in transitional disks are kept dust free by the scattering action of three coplanar quasi-circular planets in a 1:2:4 mean motion resonance (MMR). This model uses the constraint of the observed gap size, and the dust-free nature of the gap, to determine within ∼10% the possible orbits for three massive planets in an MMR. Calculated orbits are consistent with the observed orbits and Hα emission (the brightest line to observe these planets) for LkCa 15 b, PDS 70 b, and PDS 70 c within observational errors. Moreover, the model suggests that the scarcity of detected Hα planets is likely a selection effect of the current limitations of non-coronagraphic, low (<10%) Strehl, Hα imaging with adaptive optics (AO) systems used in past Hα surveys. We predict that as higher Strehl AO systems (with high-performance custom coronagraphs; like the 6.5 m Magellan Telescope MagAO-X system) are utilized at Hα, the number of detected gap planets will substantially increase by more than tenfold. For example, we show that >25 ± 5 new Hα “gap planets” are potentially discoverable by a survey of the best 19 transitional disks with MagAO-X. Detections of these accreting protoplanets will significantly improve our understanding of planet formation, planet growth and accretion, solar system architectures, and planet–disk interactions.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

OGLE-2018-BLG-0567Lb and OGLE-2018-BLG-0962Lb: Two Microlensing Planets through the Planetary-caustic Channel

We present the analyses of two microlensing events, OGLE-2018-BLG-0567 and OGLE-2018-BLG-0962. In both events, the short-lasting anomalies were densely and continuously covered by two high-cadence surveys. The light-curve modeling indicates that the anomalies are generated by source crossings over the planetary caustics induced by planetary companions to the hosts. The estimated planet/host separation (scaled to the angular Einstein radius θ {sub E}) and mass ratio are (s, q × 10{sup 3}) = (1.81 ± 0.02, 1.24 ± 0.07) and (s, q × 10{sup 3}) = (1.25 ± 0.03, 2.38 ± 0.08), respectively. From Bayesian analyses, we estimate the host and planet masses as (M{sub h},M{sub p})=(0.25{sub −0.13}{sup +0.27} M{sub ⊙},0.32{sub −0.17}{sup +0.34} M{sub J}) and (M{sub h},M{sub p})=(0.54{sub −0.28}{sup +0.33} M{sub ⊙},1.34{sub −0.70}{sup +0.82} M{sub J}), respectively. These planetary systems are located at a distance of 7.06{sub −1.15}{sup +0.93} kpc for OGLE-2018-BLG-0567 and 6.50{sub −1.75}{sup +1.06} kpc for OGLE-2018-BLG-0962, suggesting that they are likely to be near the Galactic bulge. The two events prove the capability of current high-cadence surveys for finding planets through the planetary-caustic channel. We find that most published planetary-caustic planets are found in Hollywood events in which the source size strongly contributes to the anomaly cross-section relative to the size of the caustic.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS2000

Analysis of Complexity Evolution Management and Human Performance Issues in Commercial Aircraft Automation Systems

Autoflight systems in the current generation of aircraft have been implicated in several recent incidents and accidents. A contributory aspect to these incidents may be the manner in which aircraft transition between differing behaviours or 'modes.' The current state of aircraft automation was investigated and the incremental development of the autoflight system was tracked through a set of aircraft to gain insight into how these systems developed. This process appears to have resulted in a system without a consistent global representation. In order to evaluate and examine autoflight systems, a 'Hybrid Automation Representation' (HAR) was developed. This representation was used to examine several specific problems known to exist in aircraft systems. Cyclomatic complexity is an analysis tool from computer science which counts the number of linearly independent paths through a program graph. This approach was extended to examine autoflight mode transitions modelled with the HAR. A survey was conducted of pilots to identify those autoflight mode transitions which airline pilots find difficult. The transitions identified in this survey were analyzed using cyclomatic complexity to gain insight into the apparent complexity of the autoflight system from the perspective of the pilot. Mode transitions which had been identified as complex by pilots were found to have a high cyclomatic complexity. Further examination was made into a set of specific problems identified in aircraft: the lack of a consistent representation of automation, concern regarding appropriate feedback from the automation, and the implications of physical limitations on the autoflight systems. Mode transitions involved in changing to and leveling at a new altitude were identified across multiple aircraft by numerous pilots. Where possible, evaluation and verification of the behaviour of these autoflight mode transitions was investigated via aircraft-specific high fidelity simulators. Three solution approaches to concerns regarding autoflight systems, and mode transitions in particular, are presented in this thesis. The first is to use training to modify pilot behaviours, or procedures to work around known problems. The second approach is to mitigate problems by enhancing feedback. The third approach is to modify the process by which automation is designed. The Operator Directed Process forces the consideration and creation of an automation model early in the design process for use as the basis of the software specification and training.

Vakil, Sanjay S.↗
NASA NTRS2009

Probabilistic Models for Solar Particle Events

Probabilistic Models of Solar Particle Events (SPEs) are used in space mission design studies to provide a description of the worst-case radiation environment that the mission must be designed to tolerate.The models determine the worst-case environment using a description of the mission and a user-specified confidence level that the provided environment will not be exceeded. This poster will focus on completing the existing suite of models by developing models for peak flux and event-integrated fluence elemental spectra for the Z>2 elements. It will also discuss methods to take into account uncertainties in the data base and the uncertainties resulting from the limited number of solar particle events in the database. These new probabilistic models are based on an extensive survey of SPE measurements of peak and event-integrated elemental differential energy spectra. Attempts are made to fit the measured spectra with eight different published models. The model giving the best fit to each spectrum is chosen and used to represent that spectrum for any energy in the energy range covered by the measurements. The set of all such spectral representations for each element is then used to determine the worst case spectrum as a function of confidence level. The spectral representation that best fits these worst case spectra is found and its dependence on confidence level is parameterized. This procedure creates probabilistic models for the peak and event-integrated spectra.

Adams, James H., Jr.↗
NASA NTRS1989

Weight and cost forecasting for advanced manned space vehicles

A mass and cost estimating computerized methology for predicting advanced manned space vehicle weights and costs was developed. The user friendly methology designated MERCER (Mass Estimating Relationship/Cost Estimating Relationship) organizes the predictive process according to major vehicle subsystem levels. Design, development, test, evaluation, and flight hardware cost forecasting is treated by the study. This methodology consists of a complete set of mass estimating relationships (MERs) which serve as the control components for the model and cost estimating relationships (CERs) which use MER output as input. To develop this model, numerous MER and CER studies were surveyed and modified where required. Additionally, relationships were regressed from raw data to accommodate the methology. The models and formulations which estimated the cost of historical vehicles to within 20 percent of the actual cost were selected. The result of the research, along with components of the MERCER Program, are reported. On the basis of the analysis, the following conclusions were established: (1) The cost of a spacecraft is best estimated by summing the cost of individual subsystems; (2) No one cost equation can be used for forecasting the cost of all spacecraft; (3) Spacecraft cost is highly correlated with its mass; (4) No study surveyed contained sufficient formulations to autonomously forecast the cost and weight of the entire advanced manned vehicle spacecraft program; (5) No user friendly program was found that linked MERs with CERs to produce spacecraft cost; and (6) The group accumulation weight estimation method (summing the estimated weights of the various subsystems) proved to be a useful method for finding total weight and cost of a spacecraft.

Williams, Raymond↗
NASA NTRSDate not supplied

A Survey of ISS and Visiting Vehicle Returned Surfaces for Environmental Characterization and Computer Model Development

The Orbital Debris Engineering Model (ORDEM) developed by the NASA Orbital Debris Program Office (ODPO) is a data-driven model — extensive radar, optical, laboratory, and in situ measurement data sets have been used to build the model since its earliest versions. A salient aspect of professional software development is the verification and validation (V&V) process. Verification answers the question “Is the model built correctly?” while validation addresses the question “Did we build the correct model?” Less extensive, reserved, or independent data sets serve the validation requirement. Due to the dynamic nature of the orbital debris environment, it is critical to use contemporaneous data sources that represent the current environment to support ORDEM development and validation. ORDEM has utilized in situ data collected from Space Shuttle and Hubble Space Telescope surface inspections, now over a decade old. This historical dataset is fundamental for providing baseline in situ measurement data for sizes between 10 to 300 microns, but new data sources are being evaluated using returned surfaces from or near the International Space Station (ISS). This paper reviews a general microscopic survey of ISS soft goods, the Pressurized Mating Adapter 2 (PMA-2) blanket, and a limited-scope feasibility study conducted on the Space Exploration Technologies Corporation (SpaceX) Dragon capsule’s Thermal Protection System (TPS) material. The PMA-2 blanket, exposed to the space environment between 09 July 2013 and 25 February 2015, is an approximately 3.7 m2-area blanket composed of a betacloth outer layer and multiple ballistic fabric inner layers. The SpaceX Cargo Dragon capsule regularly visited the ISS from 2012 through 2020 and potentially provides a timely and well-characterized source of data for modeling purposes. The capsule’s lateral surfaces use SpaceX Proprietary Ablative Material (SPAM) TPS material, a syntactic foam, for thermal management during all mission phases. Seven SPAM extracted samples have been analyzed to date. This paper will provide an overview of the characterization completed for impact features by size, depth, impactor diameter, and the impactor residues chemical analyses, allowing a differentiation between micrometeoroids and orbital debris and a categorization by mass density and density class. Impactor diameter is estimated using damage equations generated from ground-based hypervelocity impact testing. The orbital debris impactors are compared to the current ORDEM 3.2 model of the environment at ISS altitudes. We briefly discuss the meteoroid impactors, including constituents and mass densities, in the general context of current models.

Phillip Anz-meador↗
NASA NTRSDate not supplied

A Survey of ISS and Visiting Vehicle Returned Surfaces for Environmental Characterization and Computer Model Development

The Orbital Debris Engineering Model (ORDEM) developed by the NASA Orbital Debris Program Office (ODPO) is a data-driven model — extensive radar, optical, laboratory, and in situ measurement data sets have been used to build the model since its earliest versions. A salient aspect of professional software development is the verification and validation (V&V) process. Verification answers the question “Is the model built correctly?” while validation addresses the question “Did we build the correct model?” Less extensive, reserved, or independent data sets serve the validation requirement. Due to the dynamic nature of the orbital debris environment, it is critical to use contemporaneous data sources that represent the current environment to support ORDEM development and validation. ORDEM has utilized in situ data collected from Space Shuttle and Hubble Space Telescope surface inspections, now over a decade old. This historical dataset is fundamental for providing baseline in situ measurement data for sizes between 10 to 300 microns, but new data sources are being evaluated using returned surfaces from or near the International Space Station (ISS). This paper reviews a general microscopic survey of ISS soft goods, the Pressurized Mating Adapter 2 (PMA-2) blanket, and a limited-scope feasibility study conducted on the Space Exploration Technologies Corporation (SpaceX) Dragon capsule’s Thermal Protection System (TPS) material. The PMA-2 blanket, exposed to the space environment between 09 July 2013 and 25 February 2015, is an approximately 3.7 m2-area blanket composed of a betacloth outer layer and multiple ballistic fabric inner layers. The SpaceX Cargo Dragon capsule regularly visited the ISS from 2012 through 2020 and potentially provides a timely and well-characterized source of data for modeling purposes. The capsule’s lateral surfaces use SpaceX Proprietary Ablative Material (SPAM) TPS material, a syntactic foam, for thermal management during all mission phases. Seven SPAM extracted samples have been analyzed to date. This paper will provide an overview of the characterization completed for impact features by size, depth, impactor diameter, and the impactor residues chemical analyses, allowing a differentiation between micrometeoroids and orbital debris and a categorization by mass density and density class. Impactor diameter is estimated using damage equations generated from ground-based hypervelocity impact testing. The orbital debris impactors are compared to the current ORDEM 3.2 model of the environment at ISS altitudes. We briefly discuss the meteoroid impactors, including constituents and mass densities, in the general context of current models.

Phillip Anz-Meador↗
DOE OSTI2021

A systematic comparison of machine learning methods for modeling of dynamic processes applied to combustion emission rate modeling

Ten established, data-driven dynamic algorithms are surveyed and a practical guide for understanding these methods generated. Existing Python programming packages for implementing each algorithm are acknowledged, and the model equations necessary for prediction are presented. A case study on a coal-fired power plant’s NO x emission rates is performed, directly comparing each modeling method’s performance on a mutual system. Each model is evaluated by its root mean squared error (RMSE) on out-of-sample future horizon predictions. Optimal hyperparameters are identified using either an exhaustive search or genetic algorithm. The top five model structures of each method are used to recursively predict future NO x emission rates over a 60-step time horizon. The RMSE at each future timestep is determined, and the recursive output prediction trends compared against measurements in time. The GRU neural network is identified as the best candidate for representing the system, demonstrating accurate and stable predictions across the future horizon by all considered models, while satisfactory performance was observed in several of the ARX/NARX formulations. Finally, these efforts have contributed 1) a concise resource of multiple proven dynamic machine learning methods, 2) a practical guide explaining the use of these methods, effectively lowering the “barrier-to-entry” of deploying such models in control systems, 3) a comparison study evaluating each method’s performance on a mutual system, 4) demonstration of accurate multi-timestep emissions modeling suitable for systems-level control, and 5) generalizable results demonstrating the suitability of each method for prediction over a multi-step future horizon to other complex dynamic systems.

42 ENGINEERING↗
NASA NTRS1970

System identification - A survey

System identification, considering input signals classification, model structure, linear/nonlinear systems identifying and on-line/real time techniques

Astroem, K.-J.↗