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At least 541 records · Page 30

Characterizing diurnal and seasonal cycles in monsoon systems from TRMM and CEOP observations

The CEOP Inter-Monsoon Study (CIMS) is one of the two main science drivers of CEOP that aims to (a) provide better understanding of fundamental physical processes in monsoon regions around the world, and (b) demonstrate the synergy and utility of CEOP data in providing a pathway for model physics evaluation and improvement. As the data collection phase for EOP-3 and EOP-4 is being completed, two full annual cycles (2003-2004) of research-quality data sets from satellites, reference sites, and model output location time series (MOLTS) have been processed and made available for data analyses and model validation studies. This article presents preliminary results of a CIMS study aimed at the characterization and intercomparison of all major monsoon systems. The CEOP reference site data proved its value in such exercises by being a powerful tool to cross-validate the TRMM data, and to intercompare with multi-model results in ongoing work. We use 6 years (1998-2003) of pentad CEOP/TRMM data with 2deg x 2.5deg latitude-longitude grid, over the domain of interests to define the monsoon climatological diurnal and annual cycles for the East Asian Monsoon (EAM), the South Asian Monsoon (SAM), the West Africa Monsoon (WAM), the North America/Mexican Monsoon (NAM), the South American Summer Monsoon (SASM) and the Australian Monsoon (AUM). As noted, the TRMM data used in the study were cross-validated using CEOP reference site data, where applicable. Results show that the observed diurnal cycle of rain peaked around late afternoon over monsoon land, and early morning over the oceans. The diurnal cycles in models tend to peak 2-3 hours earlier than observed. The seasonal cycles of the EAM and SAM show the strongest continentality, i.e, strong control by continental processes away from the ITCZ. The WAM, and the AUM shows the less continentality, i.e, strong control by the oceanic ITCZ.

Lau, William K. M.↗

Characterizing Diurnal and Seasonal Cycles in Monsoon Systems from TRMM and CEOP Observations

The CEOP Inter-Monsoon Study (CIMS) is one of the two main science drivers of CEOP that aims to (a) provide better understanding of fundamental physical processes in monsoon regions around the world, and (b) demonstrate the synergy and utility of CEOP data in providing a pathway for model physics evaluation and improvement. As the data collection phase for EOP-3 and EOP-4 is being completed, two full annual cycles (2003-2004) of research-quality data sets from satellites, reference sites, and model output location time series (MOLTS) have been processed and made available for data analyses and model validation studies. This article presents preliminary results of a CIMS study aimed at the characterization and intercomparison of all major monsoon systems. The CEOP reference site data proved its value in such exercises by being a powerful tool to cross-validate the TRMM data, and to intercompare with multi-model results in ongoing work. We use 6 years (1998-2003) of pentad CEOP/TRMM data with 2 deg x 2.5 deg. latitude-longitude grid, over the domain of interests to define the monsoon climatological diurnal and annual cycles for the East Asian Monsoon (EAM), the South Asian Monsoon (SAM), the West Africa Monsoon (WAM), the North America/Mexican Monsoon (NAM), the South American Summer Monsoon (SASM) and the Australian Monsoon (AUM). As noted, the TRMM data used in the study were cross-validated using CEOP reference site data, where applicable. Results show that the observed diurnal cycle of rain peaked around late afternoon over monsoon land, and early morning over the oceans. The diurnal cycles in models tend to peak 2-3 hours earlier than observed. The seasonal cycles of the EAM and SAM show the strongest continentality, i.e, strong control by continental processes away from the ITCZ. The WAM, and the AUM shows the less continentality, i.e, strong control by the oceanic ITCZ.

Lau, William K. M.↗

On the Reprocessing and Reanalysis of Observations for Climate

The long observational record is critical to our understanding of the Earths climate, but most observing systems were not developed with a climate objective in mind. As a result, tremendous efforts have gone into assessing and reprocessing the data records to improve their usefulness in climate studies. The purpose of this paper is to both review recent progress in reprocessing and reanalyzing observations, and to summarize the challenges that must be overcome in order to improve our understanding of climate and variability. Reprocessing improves data quality through more scrutiny and improved retrieval techniques for individual observing systems, while reanalysis merges many disparate observations with models through data assimilation, yet both aim to provide an climatology of Earth processes. Many challenges remain, such as tracking the improvement of processing algorithms and limited spatial coverage. Reanalyses have fostered significant research, yet reliable global trends in many physical fields are not yet attainable, despite significant advances in data assimilation and numerical modeling. Oceanic reanalyses have made significant advances in recent years, but will only be discussed here in terms of progress toward integrated Earth system analyses. Climate data sets are generally adequate for process studies and large-scale climate variability. Communication of the strengths, limitations and uncertainties of reprocessed observations and reanalysis data, not only among the community of developers, but also with the extended research community, including the new generations of researchers and the decision makers is crucial for further advancement of the observational data records. It must be emphasized that careful investigation of the data and processing methods are required to use the observations appropriately.

Uncertainty↗

Simulations of the NASA Langley 14- by 22-Foot Subsonic Tunnel for the Juncture Flow Experiment

NASA’s Transformational Tools and Technologies Program’s Juncture Flow experiment aims to provide data to improve Computational Fluid Dynamics (CFD) modeling in the juncture flow region. The experiment is planned to provide validation-quality data for CFD that focuses on the separation bubble near the wing-body juncture trailing edge region. Because wind tunnel tests associated with the Juncture Flow project have been designed for the purpose of CFD validation, considerable effort is going into modeling and simulating the wind tunnel. This is not only important because wind tunnel wall effects can play a role in integrated testing uncertainties, but also because the better the boundary conditions are known, the better CFD can accurately represent the experiment. This paper builds on the recent CFD efforts to model the NASA Langley 14- by 22-Foot Subsonic Tunnel. Current best practices in simulating wind tunnels are evaluated. The features of each method, as well as some of their pros and cons, are highlighted. Boundary conditions and modeling techniques currently used by CFD for empty-tunnel simulations are also described. Preliminary CFD studies associated with modeling the Juncture Flow model are summarized, with the intention to determine sensitivities of the flow near the wing-body juncture region of the model to a variety of modeling decisions.

Subsonic↗

Foundation AI Models for Science

Foundation Models (FM) are AI models that are designed to replace a task or an application specific model. These FM can be applied to many different downstream applications. These FM are trained using self supervised techniques and can be built on any type of sequence data. The use of self supervised learning removes the hurdle for developing a large labeled dataset for training. Most FM use transformer architecture utilizes the notion of self attention which allows the network to model the influence of distant data points to each other both in space and time. The FM models exhibit emergent properties that are induced from the data. FM can be an important tool for science. The scale of these models results in better performance for different downstream applications and these applications show better accuracy over models built from scratch. FM drastically reduces the cost of entry to build different downstream applications both in time and effort. FM for selected science datasets such as optical satellite data, can accelerate applications ranging from data quality monitoring, feature detection and prediction. FM can make it easier to infuse AI into scientific research by removing the training data bottleneck and increasing the use of science data.

Manil Maskey↗

A Markov chain Monte Carlo (MCMC) Bayesian inference approach to analyze apparent activation barriers and reaction orders from microreactor data

Statistical analysis of steady-state catalytic kinetic data is often limited by data sparsity due to the slow pace at which the data is collected. Data sparsity and limitations in statistical analysis make it difficult to differentiate between mechanistic models and catalytic sites. A Bayesian inference tool is reported for catalysis researchers to estimate error in the determination of reaction orders from steady state microreactor data. The benefits of a Bayesian inference approach are discussed, as an alternative to the more common frequentist approach. The approach incorporates prior knowledge of the system and the data collected to form an error estimate on reaction orders. We investigated the effects of three distinct data treatments—individual fitting of trials, pooled analysis, and constrained regression methods—on the precision and uncertainty of reaction order determinations. To assess the robustness of our findings, we conducted sensitivity analyses to evaluate the influence of Bayesian parameters on uncertainty estimation. Additionally, we utilized synthetic data to illustrate how data quality impacts the precision of uncertainty assessments. We show Bayesian analysis can obtain a more precise estimation of error with a sparse data set than a frequentist analysis. Finally, this work provides strong evidence that the adoption of Bayesian analysis of kinetic data may help researchers make more precise arguments as to the strength of their evidence for a particular mechanistic hypothesis, or in comparing across different catalysts.

42 ENGINEERING↗

TDRSS tracking data and orbit determination evaluation

TDRS-1 was launched on April 4, 1983. This paper presents preliminary results of TDRSS tracking data evaluation through September 1983. TDRSS tracking data evaluation is a summary of valid tracking data that characterizes data quality. TDRS-1 orbit accuracy is evaluated by using orbit consistency measured by comparing overlaps of TDRS-1 ephemerides produced from consecutive data arcs. TDRS-1 and user orbit accuracies and consistencies are also estimated. Orbit accuracy is estimated by comparing user orbits based on tracking data obtained both through the TDRSS and from ground-based tracking.

Campion, R. E.↗

Smart Sensors' Role in Integrated System Health Management

During the last decade, there has been a major effort in the aerospace industry to reduce the cost per pond of payload and become competitive in the international market. Competition from Europe, Japan, and China has reduced this cost to almost a third from 1990 to 2000. This cost has leveled in recent years to an average price of around $12,000/pound of payload. One of NASA's goals is to promote the development of technologies to reduce this cost by a factor of 10 or more Exploration of space, specially manned exploration missions, involves very complex launch and flight vehicles, associated ground support systems, and extensive human support during all phases of the mission. When considering the Space Shuttle Program, we can see that vehicle and ground support systems' processing, operation, and maintenance represent a large percentage of the program cost and time. Reducing operating, processing and maintenance costs will greatly reduce the cost of Exploration programs. The Integrated System Health Management (ISHM) concept is one of the technologies that will help reduce these operating, processing and maintenance costs. ISHM is an integrated health monitoring system applicable to both flight and ground systems. It automatically and autonomously acquires information from sensors and actuators and processes that information using the ISHM-embedded knowledge. As a result, it establishes the health of the system based on the acquired information and its prior knowledge. When this concept is fully implemented, ISHM systems shall be able to perform failure prediction and remediation before actual hard failures occurs, preventing its costly consequences. Data sources, sensors, and their associated data acquisition systems, constitute the foundation of the system. A smart sensing architecture is required to support the acquisition of reliable, high quality data, required by the ISHM. A thorough definition of the smart sensor architectures, their embedded diagnostic agents, and communication protocols need to be established and standardized to allow the embedding and exchange of health information among sensors and ISHM. This workshop is aimed to foster the exchange of ideas and lessons learned between government, industry and academia to aid in the establishment of ISHM (and smart sensors) standards and guidelines as well as to identify present technology gaps that will have to be overcome to successfully achieve this goal.

Perotti, Jose M.↗

Recent Efforts to Improve the Near Real Time Forest Disturbance Monitoring Capabilities of the ForWarn System

This presentation discusses the development of anew method for computing NDVI temporal composites from near real time eMODIS data This research is being conducted to improve forest change products used in the ForWarn system for monitoring regional forest disturbances in the United States. ForWarn provides nation-wide NDVI-based forest disturbance detection products that are refreshed every 8 days. Current eMODIS and historical MOD13 24 day NDVI data are used to compute the disturbance detection products. The eMODIS 24 day NDVI data re-aggregated from 7 day NDVI products. The 24 day eMODIS NDVIs are generally cloud free, but do not necessarily use the freshest quality data. To shorten the disturbance detection time, a method has been developed that performs adaptive length/maximum value compositing of eMODIS NDVI, along with cloud and shadow "noise" mitigation. Tests indicate that this method can reduce detection rates by 8-16 days for known recent disturbance events, depending on the cloud frequencies and disturbance type. The noise mitigation in these tests, though imperfect, helped to improve quality of the resulting NDVI and forest change products.

Spruce, Joseph↗

Searches for CE ν NS and physics beyond the standard model using Skipper-CCDs at CONNIE

The Coherent Neutrino-Nucleus Interaction Experiment (CONNIE) aims to detect the coherent scattering ( CE ν NS ) of reactor antineutrinos off silicon nuclei using thick fully depleted high-resistivity silicon CCDs. Two Skipper-CCD sensors with subelectron readout noise capability were installed at the experiment next to the Angra-2 reactor in 2021, making CONNIE the first experiment to employ Skipper-CCDs for reactor neutrino detection. We report on the performance of the Skipper-CCDs, the new data processing, data quality, and event selection for CE ν NS interactions, which enable CONNIE to reach a record low detection threshold of 15 eV. The data were collected over 300 days in 2021–2022 and correspond to exposures of 14.9 g-days with the reactor-on and 3.5 g-days with the reactor-off. The difference between the reactor-on and off event rates shows no excess and yields upper limits for the neutrino interaction rates, comparable with previous CONNIE limits from standard CCDs and higher exposures. Searches for new neutrino interactions beyond the Standard Model improve the previous CONNIE limit on a simplified model with light vector mediators. A first dark matter (DM) search by diurnal modulation by CONNIE obtains the best limits on the DM-electron scattering cross section by a surface-level experiment. These promising results, obtained using a very small-mass sensor, illustrate the potential of Skipper-CCDs to probe rare neutrino interactions and motivate the plans to increase the detector mass in the near future.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Lunar surface chemistry - A new imaging technique

Detailed chemical maps of the lunar surface have been constructed by applying a new weighted-filter imaging technique to Apollo 15 and Apollo 16 X-ray fluorescence data. The data quality improvement is amply demonstrated by (1) modes in the frequency distribution, representing highland and mare soil suites, which are not evident before data filtering, and (2) numerous examples of chemical variations which are correlated with small-scale (about 15 kilometer) lunar topographic features.

Andre, C. G.↗

Preliminary Results of the 1.5% TCA (Modular) Controls Model in the NASA Langley UPWT

To summarize the significant highlights in this report: (1) Data quality, determined by multiple repeat runs performed on the TCA baseline configuration, and long-term repeatability, determined by comparing baseline Reference H data from this test to a previous test, have been shown to be good. (2) The longitudinal stability of the TCA is more non-linear than for the Reference H, and while it is similar at normal lift values, the TCA has considerably more pitch-up at higher lift. (3) Longitudinal control effectiveness of the TCA is similar to the Reference H and the ratio of elevator effectiveness to horizontal tail effectiveness is approximately 0.3. 4) The directional stability of the TCA is improved relative to Reference H at higher angles-of attack. The chine is effective for improving directional stability. (5) The directional control effectiveness 'of the TCA rudder is the same as that of the Reference H rudder at low angles-of-attack, after taking factors, such as number of rudder panels deflected and vertical tail volume into account. However, rudder effectiveness was shown to be reduced at higher angles-of-attack. (6) The lateral stability was shown to be reduced relative to the Reference H, which may be beneficial at low speeds for alleviating lateral control saturation. (7) Lateral control effectiveness for the TCA was shown to be similar to the Reference H for negative trailing-edge flap deflections and was reduced by approximately 25% for positive trailing-edge flap deflections.

Kubiatko, Paul↗

Preliminary Results of the 1.5% TCA (Modular) Controls Model in the NASA Langley UPWT

To summarize the significant highlights in this report: (1) Data quality, determined by multiple repeat runs performed on the TCA baseline configuration, and long-term repeatability, determined by comparing baseline Reference H data from this test to a previous test, have been shown to be good. (2) The longitudinal stability of the TCA is more non-linear than for the Reference H, and while it is similar at normal lift values, the TCA has considerably more pitch-up at higher lift. (3) Longitudinal control effectiveness of the TCA is similar to the Reference H and the ratio of elevator effectiveness to horizontal tail effectiveness is approximately 0.3. (4) The directional stability of the TCA is improved relative to Reference H at higher angles-of attack. The chine is effective for improving directional stability.

Kubiatko, Paul↗

Verifying Data Integrity of Electronically Scanned Pressure Systems at the NASA Glenn Research Center

The proper operation of the Electronically Scanned Pressure (ESP) System critical to accomplish the following goals: acquisition of highly accurate pressure data for the development of aerospace and commercial aviation systems and continuous confirmation of data quality to avoid costly, unplanned, repeat wind tunnel or turbine testing. Standard automated setup and checkout routines are necessary to accomplish these goals. Data verification and integrity checks occur at three distinct stages, pretest pressure tubing and system checkouts, daily system validation and in-test confirmation of critical system parameters. This paper will give an overview of the existing hardware, software and methods used to validate data integrity.

Panek, Joseph W.↗

In-Flight System Identification

A method is proposed and studied whereby the system identification cycle consisting of experiment design and data analysis can be repeatedly implemented aboard a test aircraft in real time. This adaptive in-flight system identification scheme has many advantages, including increased flight test efficiency, adaptability to dynamic characteristics that are imperfectly known a priori, in-flight improvement of data quality through iterative input design, and immediate feedback of the quality of flight test results. The technique uses equation error in the frequency domain with a recursive Fourier transform for the real time data analysis, and simple design methods employing square wave input forms to design the test inputs in flight. Simulation examples are used to demonstrate that the technique produces increasingly accurate model parameter estimates resulting from sequentially designed and implemented flight test maneuvers. The method has reasonable computational requirements, and could be implemented aboard an aircraft in real time.

Morelli, Eugene A.↗

Human Factors and Behavioral Performance Exploration Measures Harmonized Across HERA, NEK, and ISS: Teams Risk

BACKGROUNDThe Human Factors and Behavioral Performance Exploration Measures (HFBP-EM) suite is a set of standardized measures to assess behavioral health and performance risk related to future exploration class missions, and to support reduction of the Human Research Program’s (HRP) Behavioral Medicine (BMed), Team, Sleep, and Human Systems Integration Architecture risks. HFBP-EM were collected during Human Exploration Research Analogs (HERA) campaigns 4 (C4) and 5 (C5), and during SIRIUS 17 and 19 missions in the Russian Ground Based Experiment Complex, NEK, to document the feasibility, flexibility, and acceptability of these measures in analogsof the spaceflight environment. A subset of the HFBP-EM suite was collected during spaceflight as part HRP’s Standard Measures in Spaceflight Project. Whenever possible, the HFBP-EM protocol and measures are kept the same across studies, however, differences across research settings (e.g., experimental manipulations, mission scenarios, mission length) and implementation of the measures require the data are harmonized to ensure comparable views across missions. The purpose of our project is to develop a harmonized database of HFBP-EM data from different settings, and to summarize the trajectory of behavioral health and performance within and between research settings. In this presentation, we will summarize the harmonized dataset and the trajectory of measures related to the Team Risk, including team performance, team cohesion, team processes, and psychological safety, over time and between and within settings.METHODSWe followed best practices for data harmonization. Characteristics of each research setting were assessed for harmonization potential, and we deemed NEK-SIRIUS 17 as inappropriate due to study aims, length, and data quality. Common variables of interest were identified. Study characteristics and key variables with which datafiles could be merged were defined as “meta-data.” HFBP-EM data from all settings were processed under a common format. We then created a harmonized team-level database designed to facilitate analyses that address HRP research gaps related to HRP’s Team risk. In this database, team cohesion, processes, performance, psychological safety, and group living were operationalized as the team mean of the crew responses for each data collection (e.g., on mission day 7). Data collected on the International Space Station (ISS) included a subset of scale items administered to participants. Data collected from ISS team members within +/- 7 days of the first data collection and every following 30 +/-4 days were aggregated to the team level. We generated figures that display the mean and variability of team constructs across research settings. We also generated plots of changes in team constructs with mission day and with percentage of the mission completed. Where possible, we compared data from spaceflight analogs with data from astronauts aboard the ISS. RESULTS AND DISCUSSIONThe team-level harmonized database was structured such that each row represents data for a team on a specific mission day. Team constructs (e.g., team cohesion) were included as columns (i.e., wide format) with repeated measures across mission days given in rows (i.e., long format). The database included data from 18 crews: five, 4-person American crews in HERA C4, four 4-person American crews in HERA C5, one 6-person multinational crew in NEK-SIRIUS 19, and eight, 2–11-person multinational crews aboard the ISS. Results provide insights into mission and campaign differences in team functioning and performance. For example, between campaign differences were observed for team processes—the interdependent team actions that orchestrate taskwork in pursuit of the team’s goals [1]. Greater between-team variability on team processes was detected during HERA C4 than during C5, and a downward trend was observed over the duration of C4, but not C5 or SIRIUS 19. This may be due to the campaign-level differences such as the sleep deprivation implemented during C4. Responses on the subset of team process items administered on the ISS indicate between-crew variability more like those observed in C4 than C5 and NEK, with some, but not all ISS crews demonstrating a downward trend over time. Additional findings will be presented. REFERENCESMarks, M. A., et al (2001) Academy of Management Review, 26(3), 356-376.

S T Bell↗

Landsat 9 Mission Update and Status

Landsat 9 is currently undergoing testing at the integrated observatory level in preparation for launch from Vandenberg Air Force Base in 2021. Landsat 9 will replace Landsat 7 in orbit, 8 days out of phase with Landsat 8. Landsat 9 is largely a copy of Landsat 8 in terms of instrumentation, with an Operational Land Imager (OLI), model #2 and a Thermal Infrared Sensor (TIRS), model #2. The TIRS-2 is more significantly changed from TIRS with increased redundancy, as well as changes to the telescope baffling to improve stray light control and a revised scene select mirror encoder mechanism. Data quality of the Landsat 9 instruments is comparable to, or better than the Landsat 8 ones, with an increase to 14 bits of data transmitted and more detailed pre-launch characterization for OLI-2, and with more detailed characterization of the TIRS-2 pre-launch, in addition to the improved stray light control. The performance of the two instruments is summarized and compared to that of the Landsat 8 instruments.

Brian Markham↗

Integration of CFD and Wind-Tunnel Testing at NASA

The debate over when wind-tunnel testing will be replaced by Computational Fluid Dynamics (CFD) comes and goes. More recently, however, the debate has subsided with a more collaborative spirit between practitioners of these two disciplines. Combining these complementary disciplines has led to significant improvements in both as well as better understanding of aero- and fluid dynamics. Also, as CFD codes become more accurate, the need for comparisons with experimental data has increased. New measurement techniques, pressure-sensitive paint and off-body velocity measurements for example, have provided detailed, high-quality data for the comparisons. In-tunnel CFD simulations are also providing more direct comparisons between predicted and measured flows. Given this newenvironment, a concerted effort is now underway to facilitate in-tunnel CFD for the 12 major wind tunnels operated by NASA.The Aerosciences Evaluation and Test Capabilities Portfolio (AETC) manages the major aerodynamic ground-testing facilities within NASA. This group is responsible for the operation, maintenance, and improvement of the wind-tunnel facilities and their capabilities. AETC has recently added a project to integrate CFD and wind-tunnel testing to better support customers of the NASA wind tunnels and to better understand the flow in the wind tunnels themselves. Being able to perform CFD simulations of wind-tunnel models in the wind tunnel environment providesthe cleanest way to assess the accuracy of the simulations relative to test data. AETC plans to provide accurate geometry and guidance to wind-tunnel customers who request it, to facilitate in-tunnel simulations. How this effort got started will be presented along with the status and plans for the project.

CFD↗