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DOE OSTI2023

Polarized Resonant X-ray Scattering to Measure Molecular Orientation and Conformation in Organic Nanostructures

The ordering of organic (carbon-based) molecules into nanostructures drives useful materials properties for applications such as organic light emitting diodes, flexible batteries, and polymer nanocarriers. However, there is a current lack of techniques to measure this ordering. X-ray scattering techniques involving molecular resonances have shown promise in identifying molecular types, locations, and orientation. However, resonant soft X-ray scattering (RSoXS) techniques have not been developed even lacking basic optical models. The objectives achieved by this research were the development of methods, models, and analysis techniques that harness these resonant phenomena in X-ray scattering measurements to quantitatively probe ordering of organic molecules within devices and nanostructures. This award resulted in 11 peer reviewed publications with two others soon to be submitted. New physical models for X-ray scattering that accurately describe these complex molecular resonances enable measurements of how molecules assemble, orient and conform at the nanometer scale. These new techniques were applied to both organic electronic devices and aqueous nanoparticles being developed for hydrocarbon sequestration. This new measurement capability will enable characterization of structure-property relationships that lead to disruptive technologies of printable, stretchable, and biocompatible devices based on organic materials.

14 SOLAR ENERGY↗

NASA NTRS1979

Advanced development of atmospheric models

A set of atmospheric analysis and prediction models was developed in support of the SEASAT Program existing objective analysis models which utilize a 125x125 polar stereographic grid of the Northern Hemisphere, which were modified in order to incorporate and assess the impact of (real or simulated) satellite data in the analysis of a two-day meteorological scenario in January 1979. Program/procedural changes included: (1) a provision to utilize winds in the sea level pressure and multi-level height analyses (1000-100 MBS); (2) The capability to perform a pre-analysis at two control levels (1000 MBS and 250 MBS); (3) a greater degree of wind- and mass-field coupling, especially at these controls levels; (4) an improved facility to bogus the analyses based on results of the preanalysis; and (5) a provision to utilize (SIRS) satellite thickness values and cloud motion vectors in the multi-level height analysis.

Kesel, P. G.↗

NASA NTRS1992

Near-infrared observations of the proto-planetary nebula AFGL 618

Near-IR images and spectroscopy of the bipolar protoplanetary nebula AFGL 618 are presented. Emission from molecular hydrogen is detected in the 0.90-1.34-micron spectrum. A visual extinction of 3.4 +4.0/-2.0 mag to the H2-emitting region is derived from molecular hydrogen line ratios. Models of collisionally excited and fluorescent H2 emission are compared with the data: the near-IR H2 spectrum is found to be dominated by emission from collisionally excited molecules at Tex of about 2000 K, but a component of fluorescent emission is also present. It is shown that this type of near-IR spectrum is an excellent tool for discriminating relatively low levels of fluorescent H2 emission from a strong collisionally excited component. Images in the H- and K-bandpasses are analyzed using models which assume single scattering of photons from the central objects. The models indicate that the bipolar axis is inclined to the plane of the sky by about 45 deg. The emission in the H- and K-bands is found to be consistent with single scattering of photons by dust with a distribution such that the dust density increases with increasing stellar latitude and is nearly zero at the poles.

Latter, William B.↗

NASA NTRS1993

Parallel runway requirement analysis study. Volume 1: The analysis

The correlation of increased flight delays with the level of aviation activity is well recognized. A main contributor to these flight delays has been the capacity of airports. Though new airport and runway construction would significantly increase airport capacity, few programs of this type are currently underway, let alone planned, because of the high cost associated with such endeavors. Therefore, it is necessary to achieve the most efficient and cost effective use of existing fixed airport resources through better planning and control of traffic flows. In fact, during the past few years the FAA has initiated such an airport capacity program designed to provide additional capacity at existing airports. Some of the improvements that that program has generated thus far have been based on new Air Traffic Control procedures, terminal automation, additional Instrument Landing Systems, improved controller display aids, and improved utilization of multiple runways/Instrument Meteorological Conditions (IMC) approach procedures. A useful element to understanding potential operational capacity enhancements at high demand airports has been the development and use of an analysis tool called The PLAND_BLUNDER (PLB) Simulation Model. The objective for building this simulation was to develop a parametric model that could be used for analysis in determining the minimum safety level of parallel runway operations for various parameters representing the airplane, navigation, surveillance, and ATC system performance. This simulation is useful as: a quick and economical evaluation of existing environments that are experiencing IMC delays, an efficient way to study and validate proposed procedure modifications, an aid in evaluating requirements for new airports or new runways in old airports, a simple, parametric investigation of a wide range of issues and approaches, an ability to tradeoff air and ground technology and procedures contributions, and a way of considering probable blunder mechanisms and range of blunder scenarios. This study describes the steps of building the simulation and considers the input parameters, assumptions and limitations, and available outputs. Validation results and sensitivity analysis are addressed as well as outlining some IMC and Visual Meteorological Conditions (VMC) approaches to parallel runways. Also, present and future applicable technologies (e.g., Digital Autoland Systems, Traffic Collision and Avoidance System II, Enhanced Situational Awareness System, Global Positioning Systems for Landing, etc.) are assessed and recommendations made.

Ebrahimi, Yaghoob S.↗

NASA NTRS1993

Dynamic stall of an oscillating wing. Part 1: Evaluation of turbulence models

Unsteady flowfields of a two-dimensional oscillating wing are calculated using an implicit, finite-difference, Navier-Stokes numerical scheme using five widely used turbulence models. The objective of this study is to identify an appropriate turbulence model for accurate simulation of three-dimensional dynamic stall. Three unsteady flow conditions corresponding to attached flow, light-stall, and deep-stall of an oscillating wing experiment were chosen as test cases for computations. Results of unsteady airload hysteresis curves, harmonics of unsteady pressures, and instantaneous flow pictures are presented. Comparison of unsteady airloads with experiment show that all models are deficient in some sense and not a single model predicts all airloads consistently and in agreement with experiment for all flow conditions. For the attached flow condition, the Renormalization Group Theory (RNG), the Johnoson-King (J-K), and the Spalart-Allmaras (S-A) models have better performance. The Baldwin-Lomax (B-L) and the Baldwin-Barth (B-B) models fair poorly. At the light-stall condition, the results for the RNG, the J-K, and S-A models are in agreement with experiment for the upstroke but they all over predict the separation shown by the experiment and therefore have bigger hysteresis loops than experimental results. The B-B model results are also in good agreement for upstroke but have poor lift hysteresis for downstroke. It has superior drag and pitching-moment predictions. For deep-stall conditions, the airloads for the RNG, the B -B, and the S-A models have fair agreement with experiment, but the B-B model performed better at the extreme deep-stall condition. Overall, the RNG model provides significant improvement over the B-L model in all flow regimes with no additional computational cost. The Baldwin-Barth model is the most expensive of the models considered here, costing about 2.5 times that of the Baldwin-Lomax model. Finally, a brief discussion of the effects of grid density, time-step size, and numerical dissipation on the unsteady solutions are also presented.

Srinivasan, G. R.↗

NASA NTRS2014

Aviation Safety Risk Modeling: Lessons Learned From Multiple Knowledge Elicitation Sessions

Aviation safety risk modeling has elements of both art and science. In a complex domain, such as the National Airspace System (NAS), it is essential that knowledge elicitation (KE) sessions with domain experts be performed to facilitate the making of plausible inferences about the possible impacts of future technologies and procedures. This study discusses lessons learned throughout the multiple KE sessions held with domain experts to construct probabilistic safety risk models for a Loss of Control Accident Framework (LOCAF), FLightdeck Automation Problems (FLAP), and Runway Incursion (RI) mishap scenarios. The intent of these safety risk models is to support a portfolio analysis of NASA's Aviation Safety Program (AvSP). These models use the flexible, probabilistic approach of Bayesian Belief Networks (BBNs) and influence diagrams to model the complex interactions of aviation system risk factors. Each KE session had a different set of experts with diverse expertise, such as pilot, air traffic controller, certification, and/or human factors knowledge that was elicited to construct a composite, systems-level risk model. There were numerous "lessons learned" from these KE sessions that deal with behavioral aggregation, conditional probability modeling, object-oriented construction, interpretation of the safety risk results, and model verification/validation that are presented in this paper.

Luxhoj, J. T.↗

NASA NTRS1993

A model-based approach for detection of objects in low resolution passive millimeter wave images

A model-based vision system to assist the pilots in landing maneuvers under restricted visibility conditions is described. The system was designed to analyze image sequences obtained from a Passive Millimeter Wave (PMMW) imaging system mounted on the aircraft to delineate runways/taxiways, buildings, and other objects on or near runways. PMMW sensors have good response in a foggy atmosphere, but their spatial resolution is very low. However, additional data such as airport model and approximate position and orientation of aircraft are available. These data are exploited to guide our model-based system to locate objects in the low resolution image and generate warning signals to alert the pilots. Also analytical expressions were derived from the accuracy of the camera position estimate obtained by detecting the position of known objects in the image.

Kasturi, Rangachar↗

NASA NTRS1990

A knowledge base architecture for distributed knowledge agents

A tuple space based object oriented model for knowledge base representation and interpretation is presented. An architecture for managing distributed knowledge agents is then implemented within the model. The general model is based upon a database implementation of a tuple space. Objects are then defined as an additional layer upon the database. The tuple space may or may not be distributed depending upon the database implementation. A language for representing knowledge and inference strategy is defined whose implementation takes advantage of the tuple space. The general model may then be instantiated in many different forms, each of which may be a distinct knowledge agent. Knowledge agents may communicate using tuple space mechanisms as in the LINDA model as well as using more well known message passing mechanisms. An implementation of the model is presented describing strategies used to keep inference tractable without giving up expressivity. An example applied to a power management and distribution network for Space Station Freedom is given.

Riedesel, Joel↗

DOE OSTI2022

Modelica-based modeling and simulation of district cooling systems: A case study

While equation-based object-oriented modeling language Modelica can evaluate practical energy improvements for district cooling systems, few have adopted Modelica for this type of large-scale thermo-fluid system. Further, to our best knowledge, district cooling modeling studies have yet to include hydraulics in piping networks alongside plant models featuring realistic mechanical systems and controls. These are critical details to include when looking to make energy and control improvements in many physical system installations. To fill these gaps, this study released new open-source district cooling models at the Modelica Buildings Library and leveraged these models for a real-world case study at the University of Colorado Boulder. Here, the site includes six buildings connected to a central chiller plant featuring a waterside economizer. Several energy saving strategies are pursued based on the validated model, including control setpoint optimization, equipment modification, and pump setpoint adjustments. Results indicate that a combination of the studied measures can save the campus annually 84.6 MWh of energy, 8.9% of electricity costs, 58.0 metric tons of carbon dioxide emissions, while the waterside economizer cuts down chillers’ run times by 201 days/year, reducing maintenance costs and extending chiller life.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

NASA NTRS1995

A relational metric, its application to domain analysis, and an example analysis and model of a remote sensing domain

An objective and quantitative method has been developed for deriving models of complex and specialized spheres of activity (domains) from domain-generated verbal data. The method was developed for analysis of interview transcripts, incident reports, and other text documents whose original source is people who are knowledgeable about, and participate in, the domain in question. To test the method, it is applied here to a report describing a remote sensing project within the scope of the Earth Observing System (EOS). The method has the potential to improve the designs of domain-related computer systems and software by quickly providing developers with explicit and objective models of the domain in a form which is useful for design. Results of the analysis include a network model of the domain, and an object-oriented relational analysis report which describes the nodes and relationships in the network model. Other products include a database of relationships in the domain, and an interactive concordance. The analysis method utilizes a newly developed relational metric, a proximity-weighted frequency of co-occurrence. The metric is applied to relations between the most frequently occurring terms (words or multiword entities) in the domain text, and the terms found within the contexts of these terms. Contextual scope is selectable. Because of the discriminating power of the metric, data reduction from the association matrix to the network is simple. In addition to their value for design. the models produced by the method are also useful for understanding the domains themselves. They can, for example, be interpreted as models of presence in the domain.

Mcgreevy, Michael W.↗

DOE OSTI2020

Oxidation kinetic modelling of Fe-based oxygen carriers for chemical looping applications: Impact of the topochemical effect

Chemical looping is a promising technology for fossil fuel utilization due to its high fuel conversion efficiency with in-situ CO 2 capture capability. Metal oxide are used as oxygen carriers (OCs) and circulate between a fuel reactor and an air reactor to perform reduction and oxidation reactions, respectively. In general, OC exiting the fuel reactor is not reduced fully to its metallic state due to many factors including carbon deposition and OC deactivation. Therefore, the effect of the initial reduction state on the OC oxidation in the air reactor is a significant parameter for consideration in developing the oxidation kinetic model. The objective of this work is to develop a physically significant kinetic model that applies to the oxidation of both initially fully and partially reduced OC with air. For this study, 1.5 mm Fe-based OC particle supported with TiO 2 was used as the model OC particle due to its complex multistep reaction nature. The oxidation kinetics were experimentally investigated in a thermogravimetric analyzer (TGA). Results indicate a significant difference in the oxidation rate profile for the OCs when oxidized from an initially fully reduced compared to an initially partially reduced state. Elemental mapping via energy-dispersive X-ray spectroscopy (EDS) reveals a shrinking-core type topochemical pattern across the OC particle, which was identified to be the cause of the dependency of kinetics on the initial reduction state. A generalized kinetic model was developed based on the observed shrinking-core behavior without presuming any rate-determining steps and experimentally validated over a broad range of temperatures (800–1000 °C) and oxygen concentrations (5, 7, 10, and 15 mol%). Impacts of particle porosity, size, and core-shell structure on the OC oxidation kinetics were analyzed in the developed oxidation kinetic model to suggest methods of improving the oxidation rate of the OC without modifying the chemical composition.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Null Space Monte Carlo Evaluation of the Plateau to River Model

The Plateau to River Groundwater Model (P2R Model) is a groundwater flow and contaminant fate and transport (F&T) simulation model used to support remedial activities conducted by CH2M HILL Plateau Remediation Company at the Hanford Site in Washington State. Figure 1-1 illustrates the P2R Model extents, discretization, and boundary conditions. The P2R Model provides a computational framework to simulate the F&T of contaminants in groundwater associated with the 200-PO-1, 200-UP-1, 200-BP-5, and 200-ZP-1 Groundwater Operable Units (OUs) in the Hanford Site Central Plateau. In addition, the model includes adjacent areas and facilities (e.g., the State Approved Land Disposal Site). Intended and anticipated uses of the model include calculating water levels, hydraulic gradients, and groundwater flows throughout the model domain (encompassing the 200 West and 200 East Areas) for use in subsequent F&T calculations for contaminants of concern and developing scale-appropriate, telescopic-mesh refinement models for detailed evaluation of areas within the model domain where required. The overall objective of the modeling effort is to provide a basis for making informed remedial action decisions based on descriptions of current and expected future contaminant concentrations in groundwater at decision points within the OU boundaries. The objective for the model development phase is to create a common modeling platform that can be used for investigations of the Central Plateau groundwater OUs and areas downgradient toward the Columbia River. The P2R Model calibration to historical data observed at the Hanford Site is documented in CP-57037, Model Package Report for the Plateau to River Model Version 8.3. The purpose of this environmental calculation is to describe a null space Monte Carlo (NSMC) evaluation was conducted with the historic calibration of the P2R model. Use of numerical groundwater models is always accompanied with uncertainty in the results produced by a model because models are approximations of reality. Thus, by definition, lack the detail to fully represent observed behavior. Use of numerical techniques, such as a NSMC analysis, can help in identifying and quantifying the potential uncertainties associated with a numerical model such as the P2R Model. Use of the NSMC approach results in 100 groundwater flow models that are variants of the calibrated P2R Model. These variant models can be used to evaluate uncertainty in model predictions made by the calibrated P2R Model for other analyses. A secondary purpose of the environmental calculation is to establish these variant models for use with other applications.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

NASA NTRS1982

A NASTRAN Model of a Large Flexible Swing-Wing Bomber. Volume 1: NASTRAN Model Plane

A review was conducted of B-1 aircraft no. 2 (A/C-2) internal loads models to determine the minimum model complexity necessary to fulfill all of the airloads research study objectives. Typical model sizings were tabulated at selected vehicle locations, and scale layouts were prepared of the NASTRAN structural analysis model.

Mock, W. D.↗

NASA NTRS2009

Modeling Languages Refine Vehicle Design

Cincinnati, Ohio s TechnoSoft Inc. is a leading provider of object-oriented modeling and simulation technology used for commercial and defense applications. With funding from Small Business Innovation Research (SBIR) contracts issued by Langley Research Center, the company continued development on its adaptive modeling language, or AML, originally created for the U.S. Air Force. TechnoSoft then created what is now known as its Integrated Design and Engineering Analysis Environment, or IDEA, which can be used to design a variety of vehicles and machinery. IDEA's customers include clients in green industries, such as designers for power plant exhaust filtration systems and wind turbines.

Source record↗

DOE OSTI2021

Machine Learning and Economic Models to Enable Risk-Informed Condition Based Maintenance of a Nuclear Plant Asset

The primary objective of this research is to address challenges in the implementation of risk-informed, condition-based predictive maintenance (PdM), which reduces operating costs while still maintaining the safety and reliability of commercial nuclear power plants (NPPs). To achieve the objective, risk models are being developed by taking advantage of advancements in data analytics, deep learning, machine learning (ML), and artificial intelligence (AI). The notable outcomes presented in the report include ? Development of a ML models using heterogeneous plant process and vibration data collected at different spatial and temporal resolutions from the Salem?s CWS to diagnose a circulating water pump (CWP) failure based on salient fault signatures. The developed diagnostic models are extendable to other faults associated with CWPs and CWP motors given associated fault signatures. ? Development of a natural language processing (NLP) technique to automatically classify the WO data into different categories. The developed NLP technique was validated on independent WO data. This automates the tedious and time-consuming activity of mining and classifying WOs by subject matter experts. ? Estimation of mean time between downtime (i.e., time duration between time instances when 1 or more CWPs are not available) and developed an approach to establish reliability of CWS components using unstructured WO data along with CWS plant process data. ? Formulation of economic model based on Markov chain models. The parameters of associated with the transition rate between different states of Markov chain models were estimated using WO data. The economic model formulation and discussion captures both time-independent and time-dependent parameter variation, leading to risk-informed decision-making.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

NASA NTRS2013

The Ocean Colour Climate Change Initiative: III. A Round-Robin Comparison on In-Water Bio-Optical Algorithms

Satellite-derived remote-sensing reflectance (Rrs) can be used for mapping biogeochemically relevant variables, such as the chlorophyll concentration and the Inherent Optical Properties (IOPs) of the water, at global scale for use in climate-change studies. Prior to generating such products, suitable algorithms have to be selected that are appropriate for the purpose. Algorithm selection needs to account for both qualitative and quantitative requirements. In this paper we develop an objective methodology designed to rank the quantitative performance of a suite of bio-optical models. The objective classification is applied using the NASA bio-Optical Marine Algorithm Dataset (NOMAD). Using in situ Rrs as input to the models, the performance of eleven semianalytical models, as well as five empirical chlorophyll algorithms and an empirical diffuse attenuation coefficient algorithm, is ranked for spectrally-resolved IOPs, chlorophyll concentration and the diffuse attenuation coefficient at 489 nm. The sensitivity of the objective classification and the uncertainty in the ranking are tested using a Monte-Carlo approach (bootstrapping). Results indicate that the performance of the semi-analytical models varies depending on the product and wavelength of interest. For chlorophyll retrieval, empirical algorithms perform better than semi-analytical models, in general. The performance of these empirical models reflects either their immunity to scale errors or instrument noise in Rrs data, or simply that the data used for model parameterisation were not independent of NOMAD. Nonetheless, uncertainty in the classification suggests that the performance of some semi-analytical algorithms at retrieving chlorophyll is comparable with the empirical algorithms. For phytoplankton absorption at 443 nm, some semi-analytical models also perform with similar accuracy to an empirical model. We discuss the potential biases, limitations and uncertainty in the approach, as well as additional qualitative considerations for algorithm selection for climate-change studies. Our classification has the potential to be routinely implemented, such that the performance of emerging algorithms can be compared with existing algorithms as they become available. In the long-term, such an approach will further aid algorithm development for ocean-colour studies.

Phytoplankton↗

NASA NTRS2013

Assessments of a Turbulence Model Based on Menter's Modification to Rotta's Two-Equation Model

The main objective of this paper is to construct a turbulence model with a more reliable second equation simulating length scale. In the present paper, we assess the length scale equation based on Menter s modification to Rotta s two-equation model. Rotta shows that a reliable second equation can be formed in an exact transport equation from the turbulent length scale L and kinetic energy. Rotta s equation is well suited for a term-by-term modeling and shows some interesting features compared to other approaches. The most important difference is that the formulation leads to a natural inclusion of higher order velocity derivatives into the source terms of the scale equation, which has the potential to enhance the capability of Reynolds-averaged Navier-Stokes (RANS) to simulate unsteady flows. The model is implemented in the PAB3D solver with complete formulation, usage methodology, and validation examples to demonstrate its capabilities. The detailed studies include grid convergence. Near-wall and shear flows cases are documented and compared with experimental and Large Eddy Simulation (LES) data. The results from this formulation are as good or better than the well-known SST turbulence model and much better than k-epsilon results. Overall, the study provides useful insights into the model capability in predicting attached and separated flows.

Abdol-Hamid, Khaled S.↗

DOE OSTI2021

Pushing automated morphological classifications to their limits with the Dark Energy Survey

ABSTRACT We present morphological classifications of ∼27 million galaxies from the Dark Energy Survey (DES) Data Release 1 (DR1) using a supervised deep learning algorithm. The classification scheme separates: (a) early-type galaxies (ETGs) from late-type galaxies (LTGs); and (b) face-on galaxies from edge-on. Our convolutional neural networks (CNNs) are trained on a small subset of DES objects with previously known classifications. These typically have mr ≲ 17.7 mag; we model fainter objects to mr < 21.5 mag by simulating what the brighter objects with well-determined classifications would look like if they were at higher redshifts. The CNNs reach 97 per cent accuracy to mr < 21.5 on their training sets, suggesting that they are able to recover features more accurately than the human eye. We then used the trained CNNs to classify the vast majority of the other DES images. The final catalogue comprises five independent CNN predictions for each classification scheme, helping to determine if the CNN predictions are robust or not. We obtain secure classifications for ∼87 per cent and 73 per cent of the catalogue for the ETG versus LTG and edge-on versus face-on models, respectively. Combining the two classifications (a) and (b) helps to increase the purity of the ETG sample and to identify edge-on lenticular galaxies (as ETGs with high ellipticity). Where a comparison is possible, our classifications correlate very well with Sérsic index (n), ellipticity (ϵ), and spectral type, even for the fainter galaxies. This is the largest multiband catalogue of automated galaxy morphologies to date.

79 ASTRONOMY AND ASTROPHYSICS↗