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DOE OSTI2023

WACCM6 Projections of Polar Mesospheric Cloud Abundance Over the 21st Century

Polar mesospheric clouds (PMC), or noctilucent clouds, can be observed over high latitudes with the naked eye from the ground or from space near the summer solstice. PMC are considered a direct and sensitive indicator of climate change and have been reported to appear more frequently in recent decades. How PMC will change in the future under the influence of natural variability and anthropogenic forcing is uncertain. In this study, we utilize model output from the Whole Atmosphere Community Climate Model under several shared socioeconomic pathway (SSP) scenarios and input the water vapor, temperature, and pressure information into a 0-d PMC model to project the trend and variation of PMC over the 21st century, and their relationship to future changes of temperature, water vapor, and the solar cycle. The 0-d model calculations indicate that PMC ice water content (IWC) will increase and PMC will extend to lower latitudes under high SSP scenarios. Under these scenarios, more mesospheric water vapor leads to an increased IWC of PMC over the polar region, and colder mesopause temperature leads to more PMC over the mid-latitudes. There is a significant anti-correlation between the solar cycle and PMC IWC over the 21st century, but the anti-correlation is not always significant on the decadal scale. Finally, methane oxidation in the stratosphere and water vapor entering from the troposphere are both responsible for future changes in mesospheric water vapor and thus PMC.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2014

Highly stable polarization independent Mach-Zehnder interferometer

We experimentally demonstrate optical Mach-Zehnder interferometer utilizing displaced Sagnac configuration to enhance its phase stability. The interferometer with footprint of 27×40 cm offers individually accessible paths and shows phase deviation less than 0.4° during a 250 s long measurement. The phase drift, evaluated by means of Allan deviation, stays below 3° or 7 nm for 1.5 h without any active stabilization. The polarization insensitive design is verified by measuring interference visibility as a function of input polarization. For both interferometer's output ports and all tested polarization states the visibility stays above 93%. The discrepancy in visibility for horizontal and vertical polarization about 3.5% is caused mainly by undesired polarization dependence of splitting ratio of the beam splitter used. The presented interferometer device is suitable for quantum-information and other sensitive applications where active stabilization is complicated and common-mode interferometer is not an option as both the interferometer arms have to be accessible individually.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2017

Carbon cycle confidence and uncertainty: Exploring variation among soil biogeochemical models

Emerging insights into factors responsible for soil organic matter stabilization and decomposition are being applied in a variety of contexts, but new tools are needed to facilitate the understanding, evaluation, and improvement of soil biogeochemical theory and models at regional to global scales. To isolate the effects of model structural uncertainty on the global distribution of soil carbon stocks and turnover times we developed a soil biogeochemical testbed that forces three different soil models with consistent climate and plant productivity inputs. The models tested here include a first-order, microbial implicit approach (CASA-CNP), and two recently developed microbially explicit models that can be run at global scales (MIMICS and CORPSE). When forced with common environmental drivers, the soil models generated similar estimates of initial soil carbon stocks (roughly 1,400 Pg C globally, 0–100 cm), but each model shows a different functional relationship between mean annual temperature and inferred turnover times. Subsequently, the models made divergent projections about the fate of these soil carbon stocks over the 20th century, with models either gaining or losing over 20 Pg C globally between 1901 and 2010. Single-forcing experiments with changed inputs, temperature, and moisture suggest that uncertainty associated with freeze-thaw processes as well as soil textural effects on soil carbon stabilization were larger than direct temperature uncertainties among models. Finally, the models generated distinct projections about the timing and magnitude of seasonal heterotrophic respiration rates, again reflecting structural uncertainties that were related to environmental sensitivities and assumptions about physicochemical stabilization of soil organic matter. Here, by providing a computationally tractable and numerically consistent framework to evaluate models we aim to better understand uncertainties among models and generate insights about factors regulating the turnover of soil organic matter.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

AI-Batt (Autonomous Identification of Battery Life Models) [SWR 21-36]

Autonomous Identification of Battery Life Models (AI-Batt) AI-Batt is a MATLAB code base for developing lifetime models for batteries from accelerated aging data. The code base provides many functions for processing, visualizing, and modeling battery aging data, making the data processing, exploration, and modeling workflow substantially faster. These tools are tailored for working with battery aging data sets, which usually consist of many separate time-series for each cell, with many test conditions and possible replicates at each condition, which makes it difficult to simply process or visualize the data set. Complex modeling tasks, such as cross-validation, sensitivity analysis, and uncertainty quantification have been implemented to enable thorough statistical investigation of model predictions. Additionally, several machine-learning algorithms are implemented to autonomously identify suitable models via symbolic regression. Data processing functions automatically cast data from the struct data type, which is commonly used to store experimental data, but is not an acceptable input for most algorithms, to the table data type, which can be easily used as input to any optimization algorithm. Also, the data can be separated into time-invariant and time-variant data tables, which is helpful for exploring the data set as well as developing separate models for time-variant and time-invariant aging mechanisms. For example, in aging tests with constant temperature, temperature is a time-invariant experimental condition. Visualization tools enable plotting of data, model fits, and model simulations possible with single-line function calls, empowering data exploration of complex data sets with both time-varying and time-invariant trends. Plots can be automatically generated for the whole data set, or separated by data group (groups of test replicates) or individual data series. Data points or data series can be automatically colored by the value of a variable with a variety of color maps, and model predictions can also be colored by the value of a fit statistic. Comparisons between data sets and the predictions/simulations of different models on the same data set can be easily plotted as well. Distributions of parameter values from bootstrap resampling can be plotted to visualize the reliability of parameter estimation, or determine any correlations between parameters. Modeling tools handle the complex task of creating and parsing symbolic equations for modeling battery lifetime. Equations are parsed to grab relevant data variables, parameter values, or specified sub-models for input into optimization, evaluation, or simulation functions. Models can be optimized locally (one set of parameters for each data series), bi-level (some parameters shared across the data set), or globally (single set of parameters for all data). Functions implementing symbolic regression algorithms help users to discover effective model equations, even in poorly sampled, high-dimensional data.

Smith, Kandler↗

DOE OSTI2019

(U) LNK3DNT Capability in SENSMG

The SENSMG multigroup neutron sensitivity code has been extended to read materials and geometry from redoin and lnk3dnt files written by the PARTISN multigroup discrete ordinates code or the MCNP6 Monte Carlo code. This report describes the user interface for this capability and the code verification that was done. Not all of the capability of SENSMG is available for redoin/lnk3dnt inputs. The only responses allowed are k eff or α eigenvalues. Fixed-source problems are not allowed, and there is no mechanism to input reaction rates or reaction-rate ratios. The next section of this report describes the user interface. Section III describes the verification of the capability. Section IV is a summary and conclusions. The input files used for verification are listed in the appendix.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2015

MELCOR Computer Code Manuals Volume 3: MELCOR Assessment Problems [Draft]

MELCOR is a fully integrated, engineering-level computer code that models the progression of severe accidents in light-water reactor nuclear power plants. MELCOR is being developed at Sandia National Laboratories (SNL) for the U.S. Nuclear Regulatory Commission (NRC) as a second-generation plant risk assessment tool and the successor to the Source Term Code package. A broad spectrum of severe accident phenomena in both boiling and pressurized water reactors is treated in MELCOR in a unified framework. These include thermal-hydraulic response in the reactor coolant system (RCS), reactor cavity, containment, and confinement buildings; core heatup, degradation, and relocation; core-concrete attack; hydrogen production, transport, and combustion; and fission product release and transport behavior. Current uses of MELCOR include estimation of severe accident source terms and their sensitivities and uncertainties in a variety of applications. This publication of the MELCOR computer code manuals corresponds to MELCOR 2.0, released to users in September 2008. Volume 1 contains a primer that describes MELCOR's phenomenological scope, organization (by package), and documentation. The remainder of Volume 1 contains the MELCOR User's Guides, which provide the input instructions and guidelines for each package. Volume 2 contains the MELCOR Reference Manuals, which describe the phenomenological models that have been implemented in each package. Volume 3, MELCOR Assessment Problems, presents a portfolio of test and sample problems consisting of both analyses of experiments and of full plant problems. These analyses will be repeated with future releases of MELCOR in order to provide a metric on code predictions as new versions are released.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2023

Nuclear Matrix Elements for Neutrinoless Double-Beta Decay from Lattice QCD

Neutrinoless double-beta decay (0vbb) is a hypothetical nuclear decay that is only possible if the neutrino is a Majorana fermion. Experimental searches for this process with ever-increasing sensitivity have placed strong constraints on the 0vbb half-lives of relevant isotopes. Relating these experimental half-lives to the underlying particle physics -- the effective Majorana mass of the neutrino -- requires understanding of the nuclear matrix elements for the transition. These matrix elements can be computed within a nuclear effective field theory framework, but input from lattice QCD is necessary to constrain low-energy constants relevant for the decay. This talk will discuss calculations of these matrix elements using lattice QCD and the implications for determination of nuclear EFT parameters.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2020

A machine learning approach to emulation and biophysical parameter estimation with the Community Land Model, version 5

Abstract. Land models are essential tools for understanding and predicting terrestrial processes and climate–carbon feedbacks in the Earth system, but uncertainties in their future projections are poorly understood. Improvements in physical process realism and the representation of human influence arguably make models more comparable to reality but also increase the degrees of freedom in model configuration, leading to increased parametric uncertainty in projections. In this work we design and implement a machine learning approach to globally calibrate a subset of the parameters of the Community Land Model, version 5 (CLM5) to observations of carbon and water fluxes. We focus on parameters controlling biophysical features such as surface energy balance, hydrology, and carbon uptake. We first use parameter sensitivity simulations and a combination of objective metrics including ranked global mean sensitivity to multiple output variables and non-overlapping spatial pattern responses between parameters to narrow the parameter space and determine a subset of important CLM5 biophysical parameters for further analysis. Using a perturbed parameter ensemble, we then train a series of artificial feed-forward neural networks to emulate CLM5 output given parameter values as input. We use annual mean globally aggregated spatial variability in carbon and water fluxes as our emulation and calibration targets. Validation and out-of-sample tests are used to assess the predictive skill of the networks, and we utilize permutation feature importance and partial dependence methods to better interpret the results. The trained networks are then used to estimate global optimal parameter values with greater computational efficiency than achieved by hand tuning efforts and increased spatial scale relative to previous studies optimizing at a single site. By developing this methodology, our framework can help quantify the contribution of parameter uncertainty to overall uncertainty in land model projections.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1971

Satellite tracking by combined optimal estimation and control techniques.

Combined optimal estimation and control techniques are applied for the first time to satellite tracking systems. Both radio antenna and optical tracking systems of NASA are considered. The optimal estimation is accomplished using an extended Kalman filter resulting in an estimated state of the satellite and of the tracking system. This estimated state constitutes an input to the optimal controller. The optimal controller treats a linearized system with a quadratic performance index. The maximum principle is applied and a steady-state approximation to the resulting Riccati equation is obtained. A computer program, RATS, implementing this algorithm is described. A feasibility study of real-time implementation, tracking simulations, and parameter sensitivity studies are also reported.

Dressler, R. M.↗

NASA NTRS1984

Vestibulospinal reflexes as a function of microgravity

Data from previous manned space flights suggest that an exposure to microgravity produces significant alterations in vestibular, neuromuscular, and related sensory system functions. It is possible that the observed changes are a function of adaptation induced by altered otolith input. An experiment in Spacelab 1 was conducted with the aim to study this adaptation as it occurred in flight and after flight, and to relate the observed changes to mechanisms underlying space motion sickness. The concept was explored by making use of the anatomic pathway which links the otolith organs and spinal motoneurons. The overall sensitivity of the spinal motoneurons was tested by two related methods. One method involves the electrical excitation of neural tissue and the recording of vestibulospinal reflexes in conjunction with a brief linear acceleration. The second method is concerned with measurements of dynamic postural ataxia. Results suggest that more than a single time constant may be involved in man's ability to return to baseline values.

Reschke, M. F.↗

NASA NTRS1984

Analysis of the uncertainties in velocity measurements with triple hot-wire probes

A detailed computerized sensitivity analysis of the triple hot-wire equations has been performed in order to delineate the uncertainties associated with measurements of the velocity components. Absolute and relative uncertainties for the instantaneous hot-wire outputs are calculated as functions of roll and pitch angles, based on a constant probability combination of the uncertainties in the inputs. From the results, it is concluded that the small inherent difficulties associated with the triple hot-wire data do not reflect artifacts introduced by the data processing. Fixed errors present in the V and W channels of the output are due to the nonzero measuring volume of the triple wire probe, and are entirely predictable.

Frota, M. N.↗

NASA NTRS1987

Fiber-optic photoelastic pressure sensor with fiber-loss compensation

A new fiber-optic pressure sensor is described that has high immunity to the effects of fiber-loss variations. This device uses the photoelastic effect to modulate the proportion of the light from each of two input fibers that is coupled into each of two output fibers. This four-fiber link permits two detectors to be used to measure the sensor's responses to the light from each of two independently controlled sources. These four detector outputs are processed to yield a loss-compensated signal that is a stable and sensitive pressure indicator.

Beheim, G.↗

NASA NTRS2002

Ultrasonic Characterization of Fatigue Cracks in Composite Materials

Microcracking in composite structures due to combined fatigue and cryogenic loading can cause leakage and failure of the structure and can be difficult to detect in-service. In aerospace systems, these leaks may lead to loss of pressure/propellant, increased risk of explosion and possible cryo-pumping. The success of nondestructive evaluation to detect intra-ply microcracking in unlined pressure vessels fabricated from composite materials is critical to the use of composite structures in future space systems. The work presented herein characterizes measurements of intraply fatigue cracking through the thickness of laminated composite material by means of correlation with ultrasonic resonance. Resonant ultrasound spectroscopy provides measurements which are sensitive to both the microscopic and macroscopic properties of the test article. Elastic moduli, acoustic attenuation, and geometry can all be probed. The approach is based on the premise of half-wavelength resonance. The method injects a broadband ultrasonic wave into the test structure using a swept frequency technique. This method provides dramatically increased energy input into the test article, as compared to conventional pulsed ultrasonics. This relative energy increase improves the ability to measure finer details in the materials characterization, such as microcracking and porosity. As the microcrack density increases, more interactions occur with the higher frequency (small wavelength) components of the signal train causing the spectrum to shift toward lower frequencies. Several methods are under investigation to correlate the degree of microcracking from resonance ultrasound measurements on composite test articles including self organizing neural networks, chemometric techniques used in optical spectroscopy and other clustering algorithms.

Workman, Gary L.↗

NASA NTRS2004

Integrated Modeling Activities for the James Webb Space Telescope (JWST): Structural-Thermal-Optical Analysis

This is a continuation of a series of papers on modeling activities for JWST. The structural-thermal- optical, often referred to as "STOP", analysis process is used to predict the effect of thermal distortion on optical performance. The benchmark STOP analysis for JWST assesses the effect of an observatory slew on wavefront error. The paper begins an overview of multi-disciplinary engineering analysis, or integrated modeling, which is a critical element of the JWST mission. The STOP analysis process is then described. This process consists of the following steps: thermal analysis, structural analysis, and optical analysis. Temperatures predicted using geometric and thermal math models are mapped to the structural finite element model in order to predict thermally-induced deformations. Motions and deformations at optical surfaces are input to optical models and optical performance is predicted using either an optical ray trace or WFE estimation techniques based on prior ray traces or first order optics. Following the discussion of the analysis process, results based on models representing the design at the time of the System Requirements Review. In addition to baseline performance predictions, sensitivity studies are performed to assess modeling uncertainties. Of particular interest is the sensitivity of optical performance to uncertainties in temperature predictions and variations in metal properties. The paper concludes with a discussion of modeling uncertainty as it pertains to STOP analysis.

Johnston, John D.↗

NASA NTRS2004

Development of Thermally Stable and Highly Fluorescent IR Dyes

Fluorophores are the core component in various optical applications such as sensors and probes. Fluorphores with low-energy or long wavelength emission, in particular, in NIR region, possess advantages of low interference and high sensitivity. In this study, we has explored several classes of imidazole-based compounds for NIR fluorescent properties and concluded: (1) thiazole-based imidazole compounds are fluorescent; (2) emission energy is tunable by additional donor groups; (3) they also possess impressive two- photon absorption properties; and (4) fluorescence emission can be induced by two- photon input. This report summarizes (1) synthesis of new series of fluorophore; (2) impact of electron-withdrawing groups on fluorescent property; (3) unique property of two-photon absorption; and (4) on-going development.

Bu, Xiu R.↗

NASA NTRS2012

Measuring Segmented Primary Mirror WFE in the Presence of Vibration and Thermal Drift on the Light-Weighted JWST

The light-weighted design of the Optical Telescope Element (OTE) of the James Webb Telescope (JWST) leads to additional sensitivity to vibration from the ground - an important consideration to the measurement uncertainty of the wavefront error (WFE) in the primary mirror. Furthermore, segmentation of the primary mirror leads to rigid-body movements of segment areas in the WFE. The ground vibrations are minimized with modifications to the test facility, and by the architecture of the equipment supporting the load. Additional special test equipment (including strategically placed isolators, tunable mass dampers, and cryogenic magnetic dampers) mitigates the vibration and the response sensitivity before reaching the telescope. A multi-wavelength interferometer is designed and operated to accommodate the predicted residual vibration. Thermal drift also adds to the measurement variation. Test results of test equipment components, measurement theory, and finite element analysis combine to predict the test uncertainty in the future measurement of the primary mirror. The vibration input to the finite element model comes from accelerometer measurements of the facility with the environmental control pumps operating. One of the isolators have been built and tested to validate the dynamic performance. A preliminary model of the load support equipment and the OTE with the Integrated Science Instrument Module (ISIM) is complete. The performance of the add-on dampers have been established in previous applications. And operation of the multi-wavelength interferometer was demonstrated on a scaled hardware version of the JWST in an environment with vibration and thermal drift.

Whitman, Tony L.↗

NASA NTRS2023

WACCM6 Projections of Polar Mesospheric Cloud Abundance Over the 21st Century

Polar Mesospheric Clouds↗

NASA NTRS1998

Choosing Meteorological Input for the Global Modeling Initiative Assessment of High Speed Aircraft

The Global Modeling Initiative (GMI) science team is developing a three dimensional chemistry and transport model (CTM) to be used in assessment of the atmospheric effects of aviation. Requirements are that this model be documented, be validated against observations, use a realistic atmospheric circulation, and contain numerical transport and photochemical modules representing atmospheric processes. The model must also retain computational efficiency to be tractable to use for multiple scenarios and sensitivity studies. To meet these requirements, a facility model concept was developed in which the different components of the CTM are evaluated separately. The first use of the GMI model will be to evaluate the impact of the exhaust of supersonic aircraft on the stratosphere. The assessment calculations will depend strongly on the wind and temperature fields used by the CTM. Three meteorological data sets for the stratosphere are available to GMI: the National Center for Atmospheric Research Community Climate Model (CCM2), the Goddard Earth Observing System Data Assimilation System (GEOS DAS), and the Goddard Institute for Space Studies general circulation model (GISS). Objective criteria were established by the GMI team to identify the data set which provides the best representation of the stratosphere. Simulations of gases with simple chemical control were chosen to test various aspects of model transport. The three meteorological data sets were evaluated and graded based on their ability to simulate these aspects of stratospheric measurements. This paper describes the criteria used in grading the meteorological fields. The meteorological data set which has the highest score and therefore was selected for GMI is CCM2. This type of objective model evaluation establishes a physical basis for interpretation of differences between models and observations. Further, the method provides a quantitative basis for defining model errors, for discriminating between different models, and for ready re-evaluation of improved models. These in turn will lead to a higher level of confidence in assessment calculations.

Douglas, A. R.↗