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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS1981

The two-dimensional diagnostic model for tropospheric OH - An uncertainty analysis

Tropospheric OH is believed to play a major role in atmospheric photochemistry, and, via its chemical interactions OH ultimately may affect the climate, stratospheric ozone levels, and the pH of rain. A valuable tool for predicting the global OH abundance as a function of latitude and altitude is the two-dimensional diagnostic model for tropospheric OH. This model can also be applied to budget studies of species which interact with OH, such as CH4, CO, and O3. In addition to laboratory-obtained kinetic data, important variables include the rate constants for several reactions, the rate of heterogeneous removal of soluble species, and the global abundance and spatial variability in H2O, O3, CO, and NOx. The uncertainties in these parameters imply over a factor of 3 variability in the calculated global OH concentration as well as significant uncertainties in the latitudinal and vertical OH distribution.

Chameides, W. L.↗
NASA NTRS2011

Climate Model Diagnostic and Evaluation: With a Focus on Satellite Observations

Each year, we host a summer school that brings together the next generation of climate scientists - about 30 graduate students and postdocs from around the world - to engage with premier climate scientists from the Jet Propulsion Laboratory and elsewhere. Our yearly summer school focuses on topics on the leading edge of climate science research. Our inaugural summer school, held in 2011, was on the topic of "Using Satellite Observations to Advance Climate Models," and enabled students to explore how satellite observations can be used to evaluate and improve climate models. Speakers included climate experts from both NASA and the National Oceanic and Atmospheric Administration (NOAA), who provided updates on climate model diagnostics and evaluation and remote sensing of the planet. Details of the next summer school will be posted here in due course.

climate↗
DOE OSTI2020

Advancing Diagnostic Model Evaluation to Better Understand Water Shortage Mechanisms in Institutionally Complex River Basins

Abstract Water resources systems models enable valuable inferences on consequential system stressors by representing both the geophysical processes determining the movement of water and the human elements distributing it to its various competing uses. This study contributes a diagnostic evaluation framework that pairs exploratory modeling with global sensitivity analysis to enhance our ability to make inferences on water scarcity vulnerabilities in institutionally complex river basins. Diagnostic evaluation of models representing institutionally complex river basins with many stakeholders poses significant challenges. First, it needs to exploit a large and diverse suite of simulations to capture important human‐natural system interactions as well as institutionally aware behavioral mechanisms. Second, it needs to have performance metrics that are consequential and draw on decision‐relevant model outputs that adequately capture the multisector concerns that emerge from diverse basin stakeholders. We demonstrate the proposed model diagnostic framework by evaluating how potential interactions between changing hydrologic conditions and human demands influence the frequencies and durations of water shortages of varying magnitudes experienced by hundreds of users in a subbasin of the Colorado River. We show that the dominant factors shaping these effects vary both across users and, for an individual user, across percentiles of shortage magnitude. These differences hold even for users sharing diversion locations, demand levels or water right seniority. Our findings underline the importance of detailed institutional representation for such basins, as institutions strongly shape how dominant factors of stakeholder vulnerabilities propagate through the complex network of users.

Hadjimichael, Antonia↗
DOE OSTI2016

Hierarchical mixture of experts and diagnostic modeling approach to reduce hydrologic model structural uncertainty

In most water resources applications, a single model structure might be inadequate to capture the dynamic multi-scale interactions among different hydrological processes. Calibrating single models for dynamic catchments, where multiple dominant processes exist, can result in displacement of errors from structure to parameters, which in turn leads to over-correction and biased predictions. An alternative to a single model structure is to develop local expert structures that are effective in representing the dominant components of the hydrologic process and adaptively integrate them based on an indicator variable. In this study, the Hierarchical Mixture of Experts (HME) framework is applied to integrate expert model structures representing the different components of the hydrologic process. Various signature diagnostic analyses are used to assess the presence of multiple dominant processes and the adequacy of a single model, as well as to identify the structures of the expert models. The approaches are applied for two distinct catchments, the Guadalupe River (Texas) and the French Broad River (North Carolina) from the Model Parameter Estimation Experiment (MOPEX), using different structures of the HBV model. Furthermore, the results show that the HME approach has a better performance over the single model for the Guadalupe catchment, where multiple dominant processes are witnessed through diagnostic measures. Whereas, the diagnostics and aggregated performance measures prove that French Broad has a homogeneous catchment response, making the single model adequate to capture the response.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Diagnostic Models for Wind Turbine Gearbox Components Using SCADA Time Series Data: Preprint

This paper presents a scalable, autonomous framework for diagnostics of wind turbine gearbox failures using a multi-feature supervisory control and data acquisition data set spanning multiple years. Because of the size of the data set studied, all algorithms were constructed to be scalable using a Spark-Hadoop data framework. An unsupervised approach was used to detect significant failures based on predetermined criteria. The initial criteria selected were an abnormal spike in turbine component temperature followed by a turbine power off, which helps reduce the number of potential false alarms. To detect abnormal spikes in component temperature, a model was introduced to adjust the temperature data for effects caused by ambient temperature and normal temperature increases when loaded. This study evaluates methods for normalizing temperature sensor data to identify anomalies. The models that performed the best were a linear regression and a multivariate polynomial regression. The proposed process for finding failures has tunable parameters that can be adjusted to be more or less sensitive. The combination of sensor data normalization and application of these criteria is successful in finding turbine failures resulting in downtime. The proposed methods can operate without failure or maintenance logs and can be utilized for offline analysis of large high-resolution data sets.

17 WIND ENERGY↗
DOE OSTI2020

Convective Transition Statistics over Tropical Oceans for Climate Model Diagnostics: GCM Evaluation

To assess deep convective parameterizations in a variety of GCMs and examine the fast-time-scale convective transition, a set of statistics characterizing the pickup of precipitation as a function of column water vapor (CWV), PDFs and joint PDFs of CWV and precipitation, and the dependence of the moisture–precipitation relation on tropospheric temperature is evaluated using the hourly output of two versions of the GFDL Atmospheric Model, version 4 (AM4), NCAR CAM5 and superparameterized CAM (SPCAM). The 6-hourly output from the MJO Task Force (MJOTF)/GEWEX Atmospheric System Study (GASS) project is also analyzed. Contrasting statistics produced from individual models that primarily differ in representations of moist convection suggest that convective transition statistics can substantially distinguish differences in convective representation and its interaction with the large-scale flow, while models that differ only in spatial–temporal resolution, microphysics, or ocean–atmosphere coupling result in similar statistics. Most of the models simulate some version of the observed sharp increase in precipitation as CWV exceeds a critical value, as well as that convective onset occurs at higher CWV but at lower column RH as temperature increases. While some models quantitatively capture these observed features and associated probability distributions, considerable intermodel spread and departures from observations in various aspects of the precipitation–CWV relationship are noted. For instance, in many of the models, the transition from the low-CWV, nonprecipitating regime to the moist regime for CWV around and above critical is less abrupt than in observations. Additionally, some models overproduce drizzle at low CWV, and some require CWV higher than observed for strong precipitation. For many of the models, it is particularly challenging to simulate the probability distributions of CWV at high temperature.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2012

Diagnostic modeling of dimethylsulfide production in coastal water west of the Antarctic Peninsula

The rate of gross biological dimethylsulfide (DMS) production at two coastal sites west of the Antarctic Peninsula, off Anvers Island, near Palmer Station, was estimated using a diagnostic approach that combined field measurements from 1 January 2006 through 1 March 2006 and a one-dimensional physical model of ocean mixing. The average DMS production rate in the upper water column (0-60 m) was estimated to be 3.1 +/- 0.6 nM/d at station B (closer to shore) and 2.7 +/- 0.6 nM/d1 at station E (further from shore). The estimated DMS replacement time was on the order of 1 d at both stations. DMS production was greater in the mixed layer than it was below the mixed layer. The average DMS production normalized to chlorophyll was 0.5 +/- nM/d)/(mg cubic m) at station B and 0.7 +/- 0.2 (nM/d)/(mg/cubic m3) at station E. When the diagnosed production rates were normalized to the observed concentrations of total dimethylsulfoniopropionate (DMSPt, the biogenic precursor of DMS), we found a remarkable similarity between our estimates at stations B and E (0.06 +/- 0.02 and 0.04 +/- 0.01 (nM DMS / d1)/(nM DMSP), respectively) and the results obtained in a previous study from a contrasting biogeochemical environment in the North Atlantic subtropical gyre (0.047 =/- 0.006 and 0.087 +/- 0.014 (nM DMS d1)/(nM DMSP) in a cyclonic and anticyclonic eddy, respectively).We propose that gross biological DMS production normalized to DMSPt might be relatively independent of the biogeochemical environment, and place our average estimate at 0.06 +/- 0.01 (nM DMS / d)/(nM DMSPt). The significance of this finding is that it can provide a means to use DMSPt measurements to extrapolate gross biological DMS production, which is extremely difficult to measure experimentally under realistic in situ conditions.

Dimethylsulfide↗
DOE OSTI2014

Error field and magnetic diagnostic modeling for W7-X

The prediction, detection, and compensation of error fields for the W7-X device will play a key role in achieving a high beta (Β = 5%), steady state (30 minute pulse) operating regime utilizing the island divertor system [1]. Additionally, detection and control of the equilibrium magnetic structure in the scrape-off layer will be necessary in the long-pulse campaign as bootstrapcurrent evolution may result in poor edge magnetic structure [2]. An SVD analysis of the magnetic diagnostics set indicates an ability to measure the toroidal current and stored energy, while profile variations go undetected in the magnetic diagnostics. An additional set of magnetic diagnostics is proposed which improves the ability to constrain the equilibrium current and pressure profiles. However, even with the ability to accurately measure equilibrium parameters, the presence of error fields can modify both the plasma response and diverter magnetic field structures in unfavorable ways. Vacuum flux surface mapping experiments allow for direct measurement of these modifications to magnetic structure. The ability to conduct such an experiment is a unique feature of stellarators. The trim coils may then be used to forward model the effect of an applied n = 1 error field. This allows the determination of lower limits for the detection of error field amplitude and phase using flux surface mapping. *Research supported by the U.S. DOE under Contract No. DE-AC02-09CH11466 with Princeton University.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2018

NMR-based serum metabolomics study reveals a innovative diagnostic model for missed abortion

A missed abortion (MA) is an in-utero death of the embryo or fetus before the 20th week of gestation with retained products of conception. In order to discover novel biomarkers for MA, a {sup 1}H NMR spectroscopy-based metabolomics approach was applied to detect human MA serum metabolic profiles. Serum samples were obtained from patients with MA (n = 15) and healthy controls (n = 9) for study. The NOESYPR1D spectrum combined with multi-variate pattern recognition analysis was used to cluster the groups and establish a disease-specific metabolites phenotype. Principal component analysis (PCA) and orthogonal partial least-squares discriminant analysis (OPLS-DA) models were capable of distinguishing MA patients from healthy subjects. The results revealed that 24 metabolites altered in MA patients compared with the control population. Metabolomic pathway analysis demonstrated that alanine, aspartate and glutamate metabolism, citrate cycle (TCA cycle), taurine and hypotaurine metabolism were significantly altered in MA. The results indicated that serum NMR-based metabolomic profiling method is sensitive and specific enough to distinguish MA and from healthy controls, this method could be developed as a clinically useful diagnostic tool for MA. The finding from the MA serum metabolic profiling shed a new light on further understanding of MA disease mechanisms.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Convective Transition Statistics over Tropical Oceans for Climate Model Diagnostics: Observational Baseline

Convective transition statistics, which describe the relation between column-integrated water vapor (CWV) and precipitation, are compiled over tropical oceans using satellite and ARM site measurements to quantify the temperature and resolution dependence of the precipitation–CWV relation at fast time scales relevant to convection. At these time scales, and for precipitation especially, uncertainties associated with observational systems must be addressed by examining features with a variety of instrumentation and identifying robust behaviors versus instrument sensitivity at high rain rates. Here the sharp pickup in precipitation as CWV exceeds a certain critical threshold is found to be insensitive to spatial resolution, with convective onset occurring at higher CWV but at lower column relative humidity as bulk tropospheric temperature increases. Mean tropospheric temperature profiles conditioned on precipitation show vertically coherent structure across a wide range of temperature, reaffirming the use of a bulk temperature measure in defining the convective transition statistics. The joint probability distribution of CWV and precipitation develops a peak probability at low precipitation for CWV above critical, with rapidly decreasing probability of high precipitation below and near critical, and exhibits systematic changes under spatial averaging. The precipitation pickup with CWV is reasonably insensitive to time averaging up to several hours but is smoothed at daily time scales. This work demonstrates that CWV relative to critical serves as an effective predictor of precipitation with only minor geographic variations in the tropics, quantifies precipitation-related statistics subject to different spatial–temporal resolution, and provides a baseline for model comparison to apply these statistics as observational constraints on precipitation processes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Combining diagnostics, modeling, and control systems for automated alignment of the TES beamline

X-ray beamlines are essential components of all synchrotron light sources. Practical operations involve frequent variation in beamline component positions and orientation, particularly when photon beam parameters shift due to experimental needs, or due to variations in the incoming photon beam. The alignment process can be time consuming and takes away from valuable beam time for experimental data collection. We describe progress in the automation of certain alignment tasks on the tender-energy X-ray spectroscopy (TES) beamline at the National Synchrotron Light Source II (NSLS-II). The beamline is controlled using the BlueSky software in which high level experimental plans guide the beamline components during an experiment. Numerous software packages exist for beamline modeling, and they may be tied to the beamline control system using a package we are continuing to develop called Sirepo-Bluesky. The photon beam distribution may be measured with fluorescent screens, and a relation between beam and machine state can be found by varying the mirror and aperture settings over a multi-dimensional range. We describe the results of such parameter varying measurements and how we are combining Sirepo-Bluesky with machine learning methods and reduced models to automate mirror alignment on the TES beamline.

36 MATERIALS SCIENCE↗
NASA NTRS1981

A diagnostic model for studying daytime urban air quality trends

A single cell Eulerian photochemical air quality simulation model was developed and validated for selected days of the 1976 St. Louis Regional Air Pollution Study (RAPS) data sets; parameterizations of variables in the model and validation studies using the model are discussed. Good agreement was obtained between measured and modeled concentrations of NO, CO, and NO2 for all days simulated. The maximum concentration of O3 was also predicted well. Predicted species concentrations were relatively insensitive to small variations in CO and NOx emissions and to the concentrations of species which are entrained as the mixed layer rises.

Brewer, D. A.↗
NASA NTRS1985

A two-layer diagnostic model of the long-term physical evolution of warm-core ring 82B

The present shipboard data in the 1982 time series on a single Gulf Stream warm core ring are composited on a cylindrical coordinate system following ring motion; 10 C-isotherm depth measurements are used in a two-layer model of the ring's structure to compute gradient current, kinetic energy, available potential energy (APE), and potential vorticity. The ring's evolution can be divided into two periods: April-late June, while the ring is isolated from strong Gulf Stream interaction, during which the ring loses APE at a low rate, and from July onward, following ring interactions with the Gulf Stream and topography with much higher energy loss. Within measurement errors, the potential vorticity at the center of the ring is conserved from April through August, implying nearly inviscid dynamics.

Olson, D. B.↗
NASA NTRS1999

Tropospheric Diagnostic Modeling Studies of PEM-Tropics Field Data: Investigation of the HO(x)/NO(x)/O3 Photochemical System and Its Coupling to Sulfur and Halogen Chemistry

Over the time period of this NASA grant the PI has helped plan and execute in the PEM-Tropics A field program. He has also helped organize and co-chair three data workshops which have focused on the detailed analysis of PEM-Tropics A data. His direct participation in these analyses has led to his major involvement in 10 manuscripts, 5 of which are in print, 3 in press, and 2 submitted. A complete list of papers is included in the report.

Davis, Douglas D.↗
NASA NTRS2001

Tropospheric Diagnostic Modeling Studies of PEM-Tropics B Field Data: Investigation of the HOx/NOx/O3 Photochemical System and its Coupling to Sulfur Chemistry

Over the time period of this NASA grant the PI has helped plan and execute the PEM-Tropics B field program. He has also helped organize and co-chair two data workshops which have focused on the detailed analysis of PEM-Tropics B data. His direct participation in these analyses has led to his involvement in 13 manuscripts, nine of which are in print, two in press, and two submitted. A complete list of papers is given.

Davis, Douglas D.↗