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At least 469 records · Page 26

Reanalyses and Essential Climate Variables

Reanalyses are a potentially powerful climate data collection driven by observations but also subjected to model bias. Additionally, reanalyses can produce and use essential climate variables in a consistent method. For example, snow cover and soil moisture (among other variables) will eventually be assimilated into the reanalyses, but also provide crucial validation data. Sea surface temperature can be prescribed or assimilated in a coupled reanalysis. The strength of reanalysis lies in the ancillary data that is produced from the modeling components but not routinely observed thereby providing more complete Earth system information. The weakness in this concept is that the model derived data can be affected by model bias and may also change relative to the available observing system. Here, we will review the status of existing reanalyses and the ECVs being considered for the workshop. Purpose of Michael Bosilovich's contribution to the workshop: Michael Bosilovich will represent US reanalysis community in this international discussion of Essential Climate Variables (ECVs) and the relative nature of reanalyses to ECVs.

Bosilovich, Michael↗

Ride qualities criteria validation/pilot performance study: Flight test results

Pilot performance during a terrain following flight was studied for ride quality criteria validation. Data from manual and automatic terrain following operations conducted during low level penetrations were analyzed to determine the effect of ride qualities on crew performance. The conditions analyzed included varying levels of turbulence, terrain roughness, and mission duration with a ride smoothing system on and off. Limited validation of the B-1 ride quality criteria and some of the first order interactions between ride qualities and pilot/vehicle performance are highlighted. An earlier B-1 flight simulation program correlated well with the flight test results.

Nardi, L. U.↗

Standardizing Interfaces for External Access to Data and Processing for the NASA Ozone Product Evaluation and Test Element (PEATE)

NASA's traditional science data processing systems have focused on specific missions, and providing data access, processing and services to the funded science teams of those specific missions. Recently NASA has been modifying this stance, changing the focus from Missions to Measurements. Where a specific Mission has a discrete beginning and end, the Measurement considers long term data continuity across multiple missions. Total Column Ozone, a critical measurement of atmospheric composition, has been monitored for'decades on a series of Total Ozone Mapping Spectrometer (TOMS) instruments. Some important European missions also monitor ozone, including the Global Ozone Monitoring Experiment (GOME) and SCIAMACHY. With the U.S.IEuropean cooperative launch of the Dutch Ozone Monitoring Instrument (OMI) on NASA Aura satellite, and the GOME-2 instrumental on MetOp, the ozone monitoring record has been further extended. In conjunction with the U.S. Department of Defense (DoD) and the National Oceanic and Atmospheric Administration (NOAA), NASA is now preparing to evaluate data and algorithms for the next generation Ozone Mapping and Profiler Suite (OMPS) which will launch on the National Polar-orbiting Operational Environmental Satellite System (NPOESS) Preparatory Project (NPP) in 2010. NASA is constructing the Science Data Segment (SDS) which is comprised of several elements to evaluate the various NPP data products and algorithms. The NPP SDS Ozone Product Evaluation and Test Element (PEATE) will build on the heritage of the TOMS and OM1 mission based processing systems. The overall measurement based system that will encompass these efforts is the Atmospheric Composition Processing System (ACPS). We have extended the system to include access to publically available data sets from other instruments where feasible, including non-NASA missions as appropriate. The heritage system was largely monolithic providing a very controlled processing flow from data.ingest of satellite data to the ultimate archive of specific operational data products. The ACPS allows more open access with standard protocols including HTTP, SOAPIXML, RSS and various REST incarnations. External entities can be granted access to various modules within the system, including an extended data archive, metadata searching, production planning and processing. Data access is provided with very fine grained access control. It is possible to easily designate certain datasets as being available to the public, or restricted to groups of researchers, or limited strictly to the originator. This can be used, for example, to release one's best validated data to the public, but restrict the "new version" of data processed with a new, unproven algorithm until it is ready. Similarly, the system can provide access to algorithms, both as modifiable source code (where possible) and fully integrated executable Algorithm Plugin Packages (APPs). This enables researchers to download publically released versions of the processing algorithms and easily reproduce the processing remotely, while interacting with the ACPS. The algorithms can be modified allowing better experimentation and rapid improvement. The modified algorithms can be easily integrated back into the production system for large scale bulk processing to evaluate improvements. The system includes complete provenance tracking of algorithms, data and the entire processing environment. The origin of any data or algorithms is recorded and the entire history of the processing chains are stored such that a researcher can understand the entire data flow. Provenance is captured in a form suitable for the system to guarantee scientific reproducability of any data product it distributes even in cases where the physical data products themselves have been deleted due to space constraints. We are currently working on Semantic Web ontologies for representing the various provenance information. A new web site focusing on consolidating informaon about the measurement, processing system, and data access has been established to encourage interaction with the overall scientific community. We will describe the system, its data processing capabilities, and the methods the community can use to interact with the standard interfaces of the system.

Tilmes, Curt A.↗

Forward Technology Solar Cell Experiment First On-Orbit Data

This paper presents first on orbit measured data from the Forward Technology Solar Cell Experiment (FTSCE). FTSCE is a space experiment housed within the 5th Materials on the International Space Station Experiment (MISSE-5). MISSE-5 was launched aboard the Shuttle return to flight mission (STS-114) on July 26, 2005 and deployed on the exterior of the International Space Station (ISS). The experiment will remain in orbit for nominally one year, after which it will be returned to Earth for post-flight testing and analysis. While on orbit, the experiment is designed to measure a 36 point current vs. voltage (IV) curve on each of the experimental solar cells, and the data is continuously telemetered to Earth. The experiment also measures the solar cell temperature and the orientation of the solar cells to the sun. A range of solar cell technologies are included in the experiment including state-of-the-art triple junction InGaP/GaAs/Ge solar cells from several vendors, thin film amorphous Si and CuIn(Ga)Se2 cells, and next-generation technologies like single-junction GaAs cells grown on Si wafers and metamorphic InGaP/InGaAs/Ge triple-junction cells. In addition to FTSCE, MISSE-5 also contains a Thin-Film Materials experiment. This is a passive experiment that will provide data on the effect of the space environment on more than 200 different materials. FTSCE was initially conceived in response to various on-orbit and ground test anomalies associated with space power systems. The Department of Defense (DoD) required a method of rapidly obtaining on orbit validation data for new space solar cell technologies, and NRL was tasked to devise an experiment to meet this requirement. Rapid access to space was provided by the MISSE Program which is a NASA Langley Research Center program. MISSE-5 is a completely self-contained experiment system with its own power generation and storage system and communications system. The communications system, referred to as PCSat, transmits and receives in the Amateur Radio band providing a node on the Amateur Radio Satellite Service. This paper presents an overview of the various aspects of MISSE-5 and a sample of the first measured on orbit data.

Walters, R. J.↗

Using PAFEC as a preprocessor for COSMIC/NASTRAN

Programs for Automatic Finite Element Calculations (PAFEC) is a general purpose, three dimensional linear and nonlinear finite element program (ref. 1). PAFEC's features include free format input utilizing engineering keywords, powerful mesh generating facilities, sophisticated data base management procedures, and extensive data validation checks. Presented here is a description of a software interface that permits PAFEC to be used as a preprocessor for COSMIC/NASTRAN. This user friendly software, called PAFCOS, frees the stress analyst from the laborious and error prone procedure of creating and debugging a rigid format COSMIC/NASTRAN bulk data deck. By interactively creating and debugging a finite element model with PAFEC, thus taking full advantage of the free format engineering keyword oriented data structure of PAFEC, the amount of time spent during model generation can be drastically reduced. The PAFCOS software will automatically convert a PAFEC data structure into a COSMIC/NASTRAN bulk data deck. The capabilities and limitations of the PAFCOS software are fully discussed in the following report.

Gray, W. H.↗

TESS Science Processing Operations Center Pipeline and Data Products

TESS launched 18 April 2018 to conduct a two-year, near all-sky survey for at least 50 small, nearby exoplanets for which masses can be ascertained and whose atmospheres can be characterized by ground- and space-based follow-on observations. TESS just completed its survey of the southern hemisphere, identifying >600 candidate exoplanets and unveiling a plethora of exciting non-exoplanet astrophysics results, such as asteroseismology, asteroids, and supernova. The TESS Science Processing Operations Center (SPOC) processes the data downlinked every two weeks to generate a range of data products hosted at the Mikulski Archive for Space Telescopes (MAST). For each sector (~1 month) of observations, the SPOC calibrates the image data for both 30-min Full Frame Images (FFIs) and up to 20,000 pre-selected 2-min target star postage stamps. Data products for the 2-min targets include simple aperture photometry and systematic error-corrected flux time series. The SPOC also conducts searches for transiting exoplanets in the 2-min data for each sector and generates Data Validation time series and associated reports for each transit-like feature identified in the search. Multi-sector searches for exoplanets are conducted periodically to discover longer period planets, including those in the James Webb Continuous Viewing Zone (CVZ), which are observed for up to one year. Data products also include co-trending basis vectors (CBVs) and calibration files, such as the Pixel Response Functions across the field of view of each of TESS's four cameras. To maximize the usability, the TESS science data products are modeled after those for Kepler, including Target Pixel Files and Light Curve files.In this talk, I describe the SPOC pipeline and the chief differences between the TESS and the Kepler pipelines, and the major updates to the SPOC pipeline (4.0) available now to the community at MAST. I also discuss the documentation available to the community to help them in properly interpreting and analyzing the TESS data products.The TESS Mission is funded by NASA's Science Mission Directorate as an Astrophysics Explorer Mission.

Jenkins, Jon M.↗

Transport and Chemical Evolution over the Pacific (TRACE-P)Aircraft Mission: Design, Execution, and First Results

The NASA Transport and Chemical Evolution over the Pacific (TRACE-P) aircraft mission was conducted in February-April 2001 over the NW Pacific (1) to characterize the Asian chemical outflow and relate it quantitatively to its sources and (2) to determine its chemical evolution. It used two aircraft, a DC-8 and a P-3B, operating out of Hong Kong and Yokota Air Force Base (near Tokyo), with secondary sites in Hawaii, Wake Island, Guam, Okinawa, and Midway. The aircraft carried instrumentation for measurements of long-lived greenhouse gases, ozone and its precursors, aerosols and their precursors, related species, and chemical tracers. Five chemical transport models (CTMs) were used for chemical forecasting. Customized bottom-up emission inventories for East Asia were generated prior to the mission to support chemical forecasting and to serve as a priori for evaluation with the aircraft data. Validation flights were conducted for the Measurements Of Pollution In The Troposphere (MOPITT) satellite instrument and revealed little bias (6 plus or minus 2%) in the MOPITT measurements of CO columns. A major event of transpacific Asian pollution was characterized through combined analysis of TRACE-P and MOPITT data. The TRACE-P observations showed that cold fronts sweeping across East Asia and the associated warm conveyor belts (WCBs) are the dominant pathway for Asian outflow to the Pacific in spring. The WCBs lift both anthropogenic and biomass burning (SE Asia) effluents to the free troposphere, resulting in complex chemical signatures. The TRACE-P data are in general consistent with a priori emission inventories, lending confidence in our ability to quantify Asian emissions from socioeconomic data and emission factors. However, the residential combustion source in rural China was found to be much larger than the a priori, and there were also unexplained chemical enhancements (HCN, CH3Cl, OCS, alkylnitrates) in Chinese urban plumes. The Asian source of CCl4 was found to be much higher than government estimates. Measurements of HCN and CH3CN indicated a dominant biomass burning source and ocean sink for both gases. Large fractions of sulfate and nitrate were found to be present in dust aerosols. Photochemical activity in the Asian outflow was strongly reduced by aerosol attenuation of UV radiation, with major implications for the concentrations of HOx, radicals. New particle formation, apparently from ternary nucleation involving NH3, was observed in Chinese urban plumes.

Jacob, Daniel J.↗

Advances in Assimilation of Satellite-Based Passive Microwave Observations for Soil-Moisture Estimation

Satellite-based microwave measurements have long shown potential to provide global information about soil moisture. The European Space Agency (ESA) Soil Moisture and Ocean Salinity (SMOS, [1]) mission as well as the future National Aeronautics and Space Administration (NASA) Soil Moisture Active and Passive (SMAP, [2]) mission measure passive microwave emission at L-band frequencies, at a relatively coarse (40 km) spatial resolution. In addition, SMAP will measure active microwave signals at a higher spatial resolution (3 km). These new L-band missions have a greater sensing depth (of -5cm) compared with past and present C- and X-band microwave sensors. ESA currently also disseminates retrievals of SMOS surface soil moisture that are derived from SMOS brightness temperature observations and ancillary data. In this research, we address two major challenges with the assimilation of recent/future satellite-based microwave measurements: (i) assimilation of soil moisture retrievals versus brightness temperatures for surface and root-zone soil moisture estimation and (ii) scale-mismatches between satellite observations, models and in situ validation data.

De Lannoy, Gabrielle J. M.↗

Microwave Radiometer RFI Detection Using Deep Learning

Radio frequency interference (RFI) is a risk for microwave radiometers due to their requirement of very high sensitivity. The Soil Moisture Active Passive (SMAP) mission has an aggressive approach to RFI detection and filtering using dedicated spaceflight hardware and ground processing software. As more sensors push to observe at larger bandwidths in unprotected or shared spectrum, RFI detection continues to be essential. This article presents a deep learning approach to RFI detection using SMAP spectrogram data as input images. The study utilizes the benefits of transfer learning to evaluate the viability of this method for RFI detection in microwave radiometers. The well-known pretrained convolutional neural networks, AlexNet, GoogleNet, and ResNet-101 were investigated. ResNet-101 provided the highest accuracy with respect to validation data (99%), while AlexNet exhibited the highest agreement with SMAP detection (92%).

Microwave radiometry↗

Findings from the Supersonic Qualification Program of the Mars Science Laboratory Parachute System

In 2012, the Mars Science Laboratory Mission (MSL) will deploy NASA's largest extra-terrestrial parachute, a technology integral to the safe landing of its advanced robotic explorer on the surface. The supersonic parachute system is a mortar deployed 21.5 m disk-gap-band (DGB) parachute, identical in geometric scaling to the Viking era DGB parachutes of the 1970's. The MSL parachute deployment conditions are Mach 2.3 at a dynamic pressure of 750 Pa. The Viking Balloon Launched Decelerator Test (BLDT) successfully demonstrated a maximum of 700 Pa at Mach 2.2 for a 16.1 m DGB parachute in its AV4 flight. All previous Mars deployments have derived their supersonic qualification from the Viking BLDT test series, preventing the need for full scale high altitude supersonic testing. The qualification programs for Mars Pathfinder, Mars Exploration Rover, and Phoenix Scout Missions were all limited to subsonic structural qualification, with supersonic performance and survivability bounded by the BLDT qualification. The MSL parachute, at the edge of the supersonic heritage deployment space and 33% larger than the Viking parachute, accepts a certain degree of risk without addressing the supersonic environment in which it will deploy. In addition, MSL will spend up to 10 seconds above Mach 1.5, an aerodynamic regime that is associated with a known parachute instability characterized by significant canopy projected area fluctuation and dynamic drag variation. This aerodynamic instability, referred to as "area oscillations" by the parachute community has drag performance, inflation stability, and structural implications, introducing risk to mission success if not quantified for the MSL parachute system. To minimize this risk and as an alternative to a prohibitively expensive high altitude test program, a multi-phase qualification program using computation simulation validated by subscale test was developed and implemented for MSL. The first phase consisted of 2% of fullscale supersonic wind tunnel testing of a rigid DGB parachute with entry-vehicle to validate two high fidelity computational fluid dynamics (CFD) tools. The computer codes utilized Large Eddy Simulation and Detached Eddy Simulation numerical approaches to accurately capture the turbulent wake of the entry vehicle and its coupling to the parachute bow-shock. The second phase was the development of fluid structure interaction (FSI) computational tools to predict parachute response to the supersonic flow field. The FSI development included the integration of the CFD from the first phase with a finite element structural model of the parachute membrane and cable elements. In this phase, a 4% of full-scale supersonic flexible parachute test program was conducted to provide validation data to the FSI code and an empirical dataset of the MSL parachute in a flight-like environment. The final phase is FSI simulations of the full-scale MSL parachute in a Mars type deployment. Findings from this program will be presented in terms of code development and validation, empirical findings from the supersonic testing, and drag performance during supersonic operation.

EDL↗

Correlation Calculations for the Russian Pu Metal Fast Experiments

Nuclear criticality experiments are often conducted in campaigns with multiple variations. These experiments reuse the same basic components, like the fuel, moderator, or positioning machines. The components have uncertainties in their geometry and composition that propagate to models of the experiments. Shared components create shared uncertainty between the $k_{eff}$ of benchmarks. The shared uncertainty is commonly quantified with a covariance, or correlation coefficient. These covariances can impact criticality safety and nuclear data validation applications. While benchmark evaluations tabulate an experiment’s uncertainty, they often lack a detailed calculation of correlations between experiments. Even some very commonly used benchmarks, like the Russian Pu Metal Fast (PMF) experiments, have missing correlations. This paper presents our approach to calculate the correlations for five of the Russian PMF experiments. The experiments share hemispherical Pu shells that induce a correlation between modeled $k_{eff}$ values. We estimated the correlations with simplified and detailed models of the experiments through linear-perturbation theory. The correlations between the experiments vary significantly between the detailed vs. simplified models. We also investigate how the correlations affect validation metrics of the experiments.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Second International Airborne Remote Sensing Conference and Exhibition

The conference provided four days of displays and scientific presentations on applications, technology, a science of sub-orbital data gathering and analysis. The twelve displayed aircraft equipped with sophisticated instrumentation represented a wide range of environmental and reconnaissance missions,including marine pollution control, fire detection, Open Skies Treaty verification, thermal mapping, hydrographical measurements, military research, ecological and agricultural observations, geophysical research, atmospheric and meterological observations, and aerial photography. The U.S. Air Force and the On-Site Inspection Agency displayed the new Open Skies Treaty verification Boeing OC 135B that promotes international monitoring of military forces and activities. SRl's Jetstream uses foliage and ground penetrating SAR for forest inventories, toxic waste delineation, and concealed target and buried unexploded ordnance detection. Earth Search Sciences's Gulfstream 1 with prototype miniaturized airborne hyperspectral imaging equipment specializes in accurate mineral differentiation, low-cost hydrocarbon exploration, and nonproliferation applications. John E. Chance and the U.S. Army Corps of Engineers displayed the Bell 2 helicopter with SHOALS that performs hydrographic surveying of navigation projects, coastal environment assessment, and nautical charting surveys. Bechtel Nevada and U.S. DOE displayed both the Beech King AIR B-200 platform equipped to provide first response to nuclear accidents and routine environmental surveillance, and the MBB BO-105 helicopter used in spectral analysis for environmental assessment and military appraisal. NASA Ames Research Center's high-altitude Lockheed ER-2 assists in earth resources monitoring research in atmospheric chemistry, oceanography, and electronic sensors; ozone and greenhouse studies and satellite calibration and data validation. Ames also showcased the Learjet 24 Airborne Observatory that completed missions in Venus cloud cover analysis, Quadantid meteor shower studies, extra-solar far infrared ionic structure lines measurement, Cape Kennedy launch support, and studies in air pollution, The Products and Services Exhibit showcased new sensor and image processing technologies, aircraft data collection services, unmanned vehicle technology, platform equipment, turn-key services, software a workstations, GPS services, publications, and processing and integration systems by 58 exhibitors. The participation of aircraft users and crews provided unique dialogue between those who plan data collection a operate the remote sensing technology, and those who supply the data processing and integration equipment. Research results using hyperspectral imagery, radar and optical sensors, lidar, digital aerial photography, a integrated systems were presented. Major research and development programs and campaigns we reviewed, including CNR's LARA Project and European Space Agency's 1991-1995 Airborne Campaign. The pre-conference short courses addressed airborne video, photogrammetry, hyperspectral data analysis, digital orthophotography, imagery and GIS integration, IFSAR, GPS, and spectrometer calibration.

Source record↗

Personalized, disease-stage specific, rapid identification of immunosuppression in sepsis

Introduction Data overlapping of different biological conditions prevents personalized medical decision-making. For example, when the neutrophil percentages of surviving septic patients overlap with those of non-survivors, no individualized assessment is possible. To ameliorate this problem, an immunological method was explored in the context of sepsis. Methods Blood leukocyte counts and relative percentages as well as the serum concentration of several proteins were investigated with 4072 longitudinal samples collected from 331 hospitalized patients classified as septic (n=286), non-septic (n=43), or not assigned (n=2). Two methodological approaches were evaluated: (i) a reductionist alternative, which analyzed variables in isolation; and (ii) a non-reductionist version, which examined interactions among six (leukocyte-, bacterial-, temporal-, personalized-, population-, and outcome-related) dimensions. Results The reductionist approach did not distinguish outcomes: the leukocyte and serum protein data of survivors and non-survivors overlapped. In contrast, the non-reductionist alternative differentiated several data groups, of which at least one was only composed of survivors (a finding observable since hospitalization day 1). Hence, the non-reductionist approach promoted personalized medical practices: every patient classified within a subset associated with 100% survival subset was likely to survive. The non-reductionist method also revealed five inflammatory or disease-related stages (provisionally named ‘early inflammation, early immunocompetence, intermediary immuno-suppression, late immuno-suppression, or other’). Mortality data validated these labels: both ‘suppression’ subsets revealed 100% mortality, the ‘immunocompetence’ group exhibited 100% survival, while the remaining sets reported two-digit mortality percentages. While the ‘intermediary’ suppression expressed an impaired monocyte-related function, the ‘late’ suppression displayed renal-related dysfunctions, as indicated by high concentrations of urea and creatinine. Discussion The data-driven differentiation of five data groups may foster early and non-overlapping biomedical decision-making, both upon admission and throughout their hospitalization. This approach could evaluate therapies, at personalized level, earlier. To ascertain repeatability and investigate the dynamics of the ‘other’ group, additional studies are recommended.

Immunology↗

The Spectroscopic Data Processing Pipeline for the Dark Energy Spectroscopic Instrument

Abstract We describe the spectroscopic data processing pipeline of the Dark Energy Spectroscopic Instrument (DESI), which is conducting a redshift survey of about 40 million galaxies and quasars using a purpose-built instrument on the 4 m Mayall Telescope at Kitt Peak National Observatory. The main goal of DESI is to measure with unprecedented precision the expansion history of the universe with the baryon acoustic oscillation technique and the growth rate of structure with redshift space distortions. Ten spectrographs with three cameras each disperse the light from 5000 fibers onto 30 CCDs, covering the near-UV to near-infrared (3600–9800 Å) with a spectral resolution ranging from 2000 to 5000. The DESI data pipeline generates wavelength- and flux-calibrated spectra of all the targets, along with spectroscopic classifications and redshift measurements. Fully processed data from each night are typically available to the DESI collaboration the following morning. We give details about the pipeline’s algorithms, and provide performance results on the stability of the optics, the quality of the sky background subtraction, and the precision and accuracy of the instrumental calibration. This pipeline has been used to process the DESI Survey Validation data set, and has exceeded the project’s requirements for redshift performance, with high efficiency and a purity greater than 99% for all target classes.

79 ASTRONOMY AND ASTROPHYSICS↗

Features of Afterbody Radiative Heating for Earth Entry

Radiative heating is identified as a major contributor to afterbody heating for Earth entry capsules at velocities above 10 km/s. Because of rate-limited electron-ion recombination processes, a large fraction of the electronically-excited N and O atoms produced in the high temperature/pressure forebody remain as they expand into the afterbody region, which results in significant afterbody radiation. Large radiative heating sensitivities to electron-impact ionization rates and escape factors are identified. Ablation products from a forebody ablator are shown to increase the afterbody radiation by as much as 40%. The tangent-slab radiation transport approach is shown to over-predict the radiative flux by as much as 40% in the afterbody, therefore making the more computationally expensive ray-tracing approach necessary for accurate radiative flux predictions. For the Stardust entry, the afterbody radiation is predicted to be nearly twice as large as the convective heating during the peak heating phase of the trajectory. Comparisons between simulations and the Stardust Echelle observation measurements, which are shown to be dominated by afterbody emission, indicate agreement within 20% for various N and O lines. Similarly, calorimeter measurements from the Fire II experiment are identified as a source of validation data for afterbody radiation. For the afterbody calorimeter measurement closest to the forebody, which experiences the largest afterbody radiative heating component, the convective heating alone is shown to under-predict the measurement, even for the fullycatalytic assumption. Agreement with the measurements is improved with the addition of afterbody radiation. These comparisons with Stardust and Fire II measurements provide validation that the significant afterbody radiation values proposed in this work are legitimate.

Johnston, Christopher O.↗

Improved Prediction of Losses with Large Eddy Simulation in a Low-Pressure Turbine

There is a need to improve predictions of losses resulting from large eddy simulations (LES) of low-pressure turbines (LPT) in gas turbines. This may be done by assessing the accuracy of predictions against validation data and understanding the source of any inaccuracies. LES is a promising approach for capturing the laminar/turbulent transition process in a LPT. In previous studies, the authors utilized LES to model the flow field over a Variable Speed Power Turbine (VSPT) blade and successfully captured characteristic features of separation/reattachment and transition on the suction side at both the cruise (positive incidence) and take-off conditions (negative incidence) and as well, simulated the effect of freestream turbulence (FST) on those phenomena. The predicted pressure loading profiles agreed well with the experimental data for both a high and a low FST case at a Reynolds number of Reex=220,000. In this paper, we present wake profiles resulting from computations for a range of FST values. Although the predicted wake profiles for the lowest FST case (Tu=0.5%) matched the experimental data, at higher FST (Tu=10-15%,) the wake was wider than the experimentally measured wake and for both cases were displaced laterally when compared to the experimental measurements. In our investigation of the causes of the said discrepancies we have identified important effects which could strongly influence the predicted wake profile. Predicted losses were improved by assuring the validity of the flow solution. This was done by utilizing spectral analysis to scrutinize the dynamic behavior of the wake and determine solution accuracy resulting from low mesh density and low accuracy of convective modeling.

CFD↗

Improved Prediction of Losses with Large Eddy Simulation in a Low-Pressure Turbine

There is a need to improve predictions of losses resulting from large eddy simulations (LES) of low-pressure turbines (LPT) in gas turbines. This may be done by assessing the accuracy of predictions against validation data and understanding the source of any inaccuracies. LES is a promising approach for capturing the laminar/turbulent transition process in a LPT. In previous studies, the authors utilized LES to model the flow field over a Variable Speed Power Turbine (VSPT) blade and successfully captured characteristic features of separation/reattachment and transition on the suction side at both the cruise (positive incidence) and take-off conditions (negative incidence) and as well, simulated the effect of free-stream turbulence (FST) on those phenomena. The predicted pressure loading profiles agreed well with the experimental data for both a high and a low FST case at a Reynolds number of Re(ex)=220,000. In this paper, we present wake profiles resulting from computations for a range of FST values. Although the predicted wake profiles for the lowest FST case (Tu=0.5%) matched the experimental data, at higher FST (Tu=10-15%,) the wake was wider than the experimentally measured wake and for both cases were displaced laterally when compared to the experimental measurements. In our investigation of the causes of the said discrepancies we have identified important effects which could strongly influence the predicted wake profile. Predicted losses were improved by assuring the validity of the flow solution. This was done by utilizing spectral analysis to scrutinize the dynamic behavior of the wake and determine solution accuracy resulting from low mesh density and low accuracy of convective modeling.

LES-LDKM↗

Reactivity Coefficient Measurements and Sensitivity Studies [Abstract]

Nuclear data validation is often performed today using criticality measurements. The gold standard for criticality measurements is the International Criticality Safety Benchmark Experiment Project (ICSBEP). The validation specifically focuses on the effective multiplication factor (k eff ). K eff is a relatively easy parameter to infer and has reduced uncertainty due to being at or above critical. However, while k eff is a well-documented parameter with detailed sensitivity and uncertainty analysis, it cannot be used as a standalone metric to determine inaccuracies in nuclear data (e.g., cross section data, PFNS, nu), which is based on theory, physics, and differential measurements. The Experiments Underpinned by Computational Learning for Improvements in nuclear Data (EUCLID) project aims to identify compensating errors in specific nuclear data by optimally designing experiments that are sensitive to a suite of measurement parameters beyond k eff . By identifying how each parameter's nuclear data sensitivity differs from others, experiments can be designed to constrain questionable nuclear data. One sensitivity that is of particular interest to this project includes reactivity coefficient sensitivities.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗