Results for “dynamic data collection” — Page 25

NASA NTRS2016

Expected Geochemical and Mineralogical Properties of Meteorites from Mercury: Inferences from Messenger Data

Meteorites from the Moon, Mars, and many types of asteroid bodies have been identified among our global inventory of meteorites, however samples of Mercury and Venus have not been identified. The absence of mercurian and venusian meteorites could be attributed to an inability to recognize them in our collections due to a paucity of geochemical information for Venus and Mercury. In the case of mercurian meteorites, this possibility is further supported by dynamical calculations that suggest mercurian meteorites should be present on Earth at a factor of 2-3 less than meteorites from Mars [1]. In the present study, we focus on the putative mineralogy of mercurian meteorites using data obtained from the MErcury Surface, Space ENvironment, GEochemistry, and Ranging (MESSENGER) spacecraft, which has provided us with our first quantitative constraints on the geochemistry of planet Mercury. We have used the MESSENGER data to compile a list of mineralogical and geochemical characteristics that a meteorite from Mercury is likely to exhibit.

McCubbin, F. M.↗

NASA NTRS2011

Estimation and Modeling of Enceladus Plume Density Using Attitude Control Data Collected by the Cassini Spacecraft During Low-Altitude Enceladus Flybys

The Cassini spacecraft was launched on 15 October 1997. After an interplanetary cruise of almost seven years, it arrived at Saturn on June 30, 2004. Major science objectives of the Cassini mission include investigations of the configuration and dynamics of Saturn's magnetosphere, the structure and composition of the rings, the characterization of several of Saturn's icy satellites, and Titan's atmosphere constituent abundance

Enceladus↗

DOE OSTI2025

PubChemLite Plus Collision Cross Section (CCS) Values for Enhanced Interpretation of Nontarget Environmental Data

Finding relevant chemicals in the vast (known) chemical space is a major challenge for environmental and exposomics studies leveraging nontarget high resolution mass spectrometry (NT-HRMS) methods. Chemical databases now contain hundreds of millions of chemicals, yet many are not relevant. This article details an extensive collaborative, open science effort to provide a dynamic collection of chemicals for environmental, metabolomics, and exposomics research, along with supporting information about their relevance to assist researchers in the interpretation of candidate hits. The PubChemLite for Exposomics collection is compiled from ten annotation categories within PubChem, enhanced with patent, literature and annotation counts, predicted partition coefficient (logP) values, as well as predicted collision cross section (CCS) values using CCSbase. Monthly versions are archived on Zenodo under a CC-BY license, supporting reproducible research, and a new interface has been developed, including historical trends of patent and literature data, for researchers to browse the collection. This article details how PubChemLite can support researchers in environmental and exposomics studies, describes efforts to increase the availability of experimental CCS values, and explores known limitations and potential for future developments. The data and code behind these efforts are openly available.

PubChem↗

DOE OSTI2026

Integrative SP3 Workflow for Multi-PTM Proteomics Profiling (TZ-DP0)

The goal of the experiment was to demonstrate that the optimized multiplexed multi-PTM profiling workflow can comprehensively and quantitatively capture dynamic changes in protein abundance, cysteine oxidation, phosphorylation, and acetylation in cytokine-induced inflammatory stress in mouse pancreatic ß-cells. Global proteomic, redox proteomic, phosphoproteomic, and acetylomic were data collected from mouse Beta-TC-6 pancreatic Beta-cells, untreated (mock) and cytokine-treated Beta-cells at 4, 8, and 24 hours with 4 biological replicates. Samples were digested with trypsin and Lys-C, then analyzed by LC-MS/MS. Data were searched with MS-GF+, MASIC, and MaxQuant using PNNL's DMS processing pipeline.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS1977

Fast arithmetic in MacLISP

MacLISP provides a compiler which produces numerical code competitive in speed with some FORTRAN implementations and yet compatible with the rest of the MacLISP system. All numerical programs can be run under the MacLISP interpreter. Additional declarations to the compiler specify type information which allows the generation of optimized numerical code which generally does not require the garbage collection of temporary numerical results. Array accesses are almost as fast as in FORTRAN, and permit the use of dynamically allocated arrays of varying dimensions. The implementation decisions regarding user interface, data representations, and interfacing conventions are discussed which allow the generation of fast numerical LISP code.

Steele, G. L., Jr.↗

NASA NTRS1979

Pioneer Venus Star Sensor

The design predictions and orbital performance verification of the solid state star scanner used in the Onboard Attitude Control of the Pioneer Venus Orbiter and Multiprobe are presented. The star sensor extended the scanner use to active despin control, and it differs from previous sensors in solid state detection, redundant electronics for reliability, larger field of view, and large dynamic spin range. The star scanner hardware and design performance based on the ability to predict all noise sources, signal magnitudes, and expected detection probability are discussed. In-flight data collected to verify sensor ground calibration are tabulated and plotted in predicted accuracy curves. It is concluded that the Pioneer Venus Star Sensor has demonstrated predictable star calibration in the range of .1 magnitude uncertainties and usable star catalogs of 100 stars with very high probabilities of detection, which were much better than expected and well within the mission requirements.

Gutshall, R. L.↗

NASA NTRS1990

Studies of stratospheric particulates

A sophisticated computer model of polar stratospheric clouds was developed and used to study the properties of ice clouds. The model has recently been extended to investigate nitric acid clouds and ice clouds as well as their interactions with stratospheric gases. The model is now being applied to interpret data collected during recent expeditions to the Antarctic and the Arctic. Some work has also been done to understand the properties of noctilucent clouds and their implications for the chemistry and dynamics of the upper stratosphere.

Toon, Owen B.↗

NASA NTRS1995

Distributed Computerized Catalog System

DarkStar Distributed Catalog System describes arbitrary data objects in unified manner, providing end users with versatile, yet simple search mechanism for locating and identifying objects. Provides built-in generic and dynamic graphical user interfaces. Design of system avoids some of problems of standard DBMS, and system provides more flexibility than do conventional relational data bases, or object-oriented data bases. Data-collection lattice partly hierarchical representation of relationships among collections, subcollections, and data objects.

Borgen, Richard L.↗

NASA NTRS2008

CFD Results for an Axisymmetric Isentropic Relaxed Compression Inlet

The OVERFLOW code was used to calculate the flow field for a family of five relaxed compression inlets, which were part of a screening study to determine a configuration most suited to the application of microscale flow control technology as a replacement for bleed. Comparisons are made to experimental data collected for each of the inlets in the 1- by 1-Foot Supersonic Wind Tunnel at the NASA Glenn Research Center (GRC) to help determine the suitability of computational fluid dynamics (CFD) as a tool for future studies of these inlets with flow control devices. Effects on the wind tunnel results of the struts present in a high subsonic flow region accounted for most of the inconsistency between the results. Based on the level of agreement in the present study, it is expected that CFD can be used as a tool to aid in the design of a study of this class of inlets with flow control.

Hirt, Stefanie M.↗

NASA NTRS2014

Increased Mach Number Capability for the NASA Glenn 10x10 Supersonic Wind Tunnel

Computational simulations and wind tunnel testing were conducted to explore the operation of the Abe Silverstein Supersonic Wind Tunnel at the NASA Glenn Research Center at test section Mach numbers above the current limit of Mach 3.5. An increased Mach number would enhance the capability for testing of supersonic and hypersonic propulsion systems. The focus of the explorations was on understanding the flow within the second throat of the tunnel, which is downstream of the test section and is where the supersonic flow decelerates to subsonic flow. Methods of computational fluid dynamics (CFD) were applied to provide details of the shock boundary layer structure and to estimate losses in total pressure. The CFD simulations indicated that the tunnel could be operated up to Mach 4.0 if the minimum width of the second throat was made smaller than that used for previous operation of the tunnel. Wind tunnel testing was able to confirm such operation of the tunnel at Mach 3.6 and 3.7 before a hydraulic failure caused a stop to the testing. CFD simulations performed after the wind tunnel testing showed good agreement with test data consisting of static pressures along the ceiling of the second throat. The CFD analyses showed increased shockwave boundary layer interactions, which was also observed as increased unsteadiness of dynamic pressures collected in the wind tunnel testing.

Wind tunnel↗

NASA NTRS2015

Increased Mach Number Capability for the NASA Glenn 10x10 Supersonic Wind Tunnel

Computational simulations and wind tunnel testing were conducted to explore the operation of the Abe Silverstein Supersonic Wind Tunnel at the NASA Glenn Research Center at test section Mach numbers above the current limit of Mach 3.5. An increased Mach number would enhance the capability for testing of supersonic and hypersonic propulsion systems. The focus of the explorations was on understanding the flow within the second throat of the tunnel, which is downstream of the test section and is where the supersonic flow decelerates to subsonic flow. Methods of computational fluid dynamics (CFD) were applied to provide details of the shock boundary layer structure and to estimate losses in total pressure. The CFD simulations indicated that the tunnel could be operated up to Mach 4.0 if the minimum width of the second throat was made smaller than that used for previous operation of the tunnel. Wind tunnel testing was able to confirm such operation of the tunnel at Mach 3.6 and 3.7 before a hydraulic failure caused a stop to the testing. CFD simulations performed after the wind tunnel testing showed good agreement with test data consisting of static pressures along the ceiling of the second throat. The CFD analyses showed increased shockwave boundary layer interactions, which was also observed as increased unsteadiness of dynamic pressures collected in the wind tunnel testing.

Diffuser↗

NASA NTRS2018

Overview and Evaluation of a Computational Bone Physiology Modeling Toolchain and Its Application to Testing of Exercise Countermeasures

Prolonged microgravity exposure disrupts natural bone remodeling processes and can lead to a significant loss of bone strength, increasing injury risk during missions and placing astronauts at a greater risk of bone fracture later in life. Resistance-based exercise during missions is used to combat bone loss, but current exercise countermeasures do not completely mitigate the effects of microgravity. To address this concern, we present work to develop a personalizable, site-specific computational modeling toolchain of bone remodeling dynamics to understand and estimate changes in volumetric bone mineral density (BMD) in response to microgravity-induced bone unloading and in-flight exercise. The toolchain is evaluated against data collected from subjects in a 70-day bed rest study and is found to provide insight into the amount of exercise stimulus needed to minimize bone loss, quantitatively predicting post-study volumetric BMD of control subjects who did not perform exercise, and qualitatively predicting the effects of exercise. Results suggest that, with additional data, the toolchain could be improved to aid in developing customized in-flight exercise regimens and predict exercise effectiveness.

Schepelmann, Alexander↗

NASA NTRS2018

The Impacts of Recent Drought on Fire, Forest Loss, and Regional Smoke Emissions in Lowland Bolivia

In the southern Amazon relationships have been established among drought, human activities that cause forest loss, fire, and smoke emissions. We explore the impacts of recent drought on fire, forest loss, and atmospheric visibility in lowland Bolivia. To assess human influence on fire, we consider climate, fire, and vegetation dynamics in an area largely excluded from human activities since 1979, Noel Kempff Mercado National Park (NK) in northeastern Bolivia. We use data from five sources: the Moderate Resolution Imaging Spectroradiometer Collection 6 active fire product (2001-2015) (MODIS C6), Global Fire Weather Database (GFWED) data (1982-2015), MODIS land cover data (2001-2010), MODIS forest loss data (2000-2012), and the regional extinction coefficient for the southwestern Amazon (i.e., B(sub ext)), which is derived from horizontal visibility data from surface stations at the World Meteorological Organization (WMO) level (1973-2015). The B(sub ext) is affected by smoke and acts as a proxy for visibility and regional fire emissions. In lowland Bolivia from 2001 to 2015, interannual Drought Code (DC) variability was linked to fire activity, while from 1982 to 2015, interannual DC variability was linked to B(sub ext). From 2001 to 2015, the B(sub ext) and MODIS C6 active fire data for lowland Bolivia captured fire seasonality, and covaried between low- and high-fire years. Consistent with previous studies, our results suggest B(sub ext)t can be used as a longer-term proxy of regional fire emissions in southwestern Amazonia. Overall, our study found drought conditions were the dominant control on interannual fire variability in lowland Bolivia, and fires within NK were limited to the Cerrado and seasonally inundated wetland biomes. Our results suggest lowland Bolivian tropical forests were susceptible to human activities that may have amplified fire during drought. Human activities and drought need to be considered in future projections of southern Amazonian fire, in regard to carbon emissions and global climate.

Forest Loss↗

NASA NTRS2019

Overview and Evaluation of a Computational Bone Physiology Modeling Toolchain and Its Application to Testing of Exercise Countermeasures

Prolonged microgravity exposure disrupts natural bone remodeling processes and can lead to a significant loss of bone strength, increasing injury risk during missions and placing astronauts at a greater risk of bone fracture later in life. Resistance-based exercise during missions is used to combat bone loss, but current exercise countermeasures do not completely mitigate the effects of microgravity. To address this concern, we present work to develop a personalizable, site-specific computational modeling toolchain of bone remodeling dynamics to understand and estimate changes in volumetric bone mineral density (BMD) in response to microgravity-induced bone unloading and in-flight exercise. The toolchain is evaluated against data collected from subjects in a 70-day bedrest study and is found to provide insight into the amount of exercise stimulus needed to minimize bone loss, quantitatively predicting post-study volumetric BMD of control subjects who did not perform exercise, and qualitatively predicting the effects of exercise. Results suggest that, with additional data, the toolchain could be improved to aid in developing customized in-flight exercise regimens and predict exercise effectiveness.

Schepelmann, Alexander↗

NASA NTRSDate not supplied

A Survey of ISS and Visiting Vehicle Returned Surfaces for Environmental Characterization and Computer Model Development

The Orbital Debris Engineering Model (ORDEM) developed by the NASA Orbital Debris Program Office (ODPO) is a data-driven model — extensive radar, optical, laboratory, and in situ measurement data sets have been used to build the model since its earliest versions. A salient aspect of professional software development is the verification and validation (V&V) process. Verification answers the question “Is the model built correctly?” while validation addresses the question “Did we build the correct model?” Less extensive, reserved, or independent data sets serve the validation requirement. Due to the dynamic nature of the orbital debris environment, it is critical to use contemporaneous data sources that represent the current environment to support ORDEM development and validation. ORDEM has utilized in situ data collected from Space Shuttle and Hubble Space Telescope surface inspections, now over a decade old. This historical dataset is fundamental for providing baseline in situ measurement data for sizes between 10 to 300 microns, but new data sources are being evaluated using returned surfaces from or near the International Space Station (ISS). This paper reviews a general microscopic survey of ISS soft goods, the Pressurized Mating Adapter 2 (PMA-2) blanket, and a limited-scope feasibility study conducted on the Space Exploration Technologies Corporation (SpaceX) Dragon capsule’s Thermal Protection System (TPS) material. The PMA-2 blanket, exposed to the space environment between 09 July 2013 and 25 February 2015, is an approximately 3.7 m2-area blanket composed of a betacloth outer layer and multiple ballistic fabric inner layers. The SpaceX Cargo Dragon capsule regularly visited the ISS from 2012 through 2020 and potentially provides a timely and well-characterized source of data for modeling purposes. The capsule’s lateral surfaces use SpaceX Proprietary Ablative Material (SPAM) TPS material, a syntactic foam, for thermal management during all mission phases. Seven SPAM extracted samples have been analyzed to date. This paper will provide an overview of the characterization completed for impact features by size, depth, impactor diameter, and the impactor residues chemical analyses, allowing a differentiation between micrometeoroids and orbital debris and a categorization by mass density and density class. Impactor diameter is estimated using damage equations generated from ground-based hypervelocity impact testing. The orbital debris impactors are compared to the current ORDEM 3.2 model of the environment at ISS altitudes. We briefly discuss the meteoroid impactors, including constituents and mass densities, in the general context of current models.

Phillip Anz-meador↗

NASA NTRSDate not supplied

A Survey of ISS and Visiting Vehicle Returned Surfaces for Environmental Characterization and Computer Model Development

The Orbital Debris Engineering Model (ORDEM) developed by the NASA Orbital Debris Program Office (ODPO) is a data-driven model — extensive radar, optical, laboratory, and in situ measurement data sets have been used to build the model since its earliest versions. A salient aspect of professional software development is the verification and validation (V&V) process. Verification answers the question “Is the model built correctly?” while validation addresses the question “Did we build the correct model?” Less extensive, reserved, or independent data sets serve the validation requirement. Due to the dynamic nature of the orbital debris environment, it is critical to use contemporaneous data sources that represent the current environment to support ORDEM development and validation. ORDEM has utilized in situ data collected from Space Shuttle and Hubble Space Telescope surface inspections, now over a decade old. This historical dataset is fundamental for providing baseline in situ measurement data for sizes between 10 to 300 microns, but new data sources are being evaluated using returned surfaces from or near the International Space Station (ISS). This paper reviews a general microscopic survey of ISS soft goods, the Pressurized Mating Adapter 2 (PMA-2) blanket, and a limited-scope feasibility study conducted on the Space Exploration Technologies Corporation (SpaceX) Dragon capsule’s Thermal Protection System (TPS) material. The PMA-2 blanket, exposed to the space environment between 09 July 2013 and 25 February 2015, is an approximately 3.7 m2-area blanket composed of a betacloth outer layer and multiple ballistic fabric inner layers. The SpaceX Cargo Dragon capsule regularly visited the ISS from 2012 through 2020 and potentially provides a timely and well-characterized source of data for modeling purposes. The capsule’s lateral surfaces use SpaceX Proprietary Ablative Material (SPAM) TPS material, a syntactic foam, for thermal management during all mission phases. Seven SPAM extracted samples have been analyzed to date. This paper will provide an overview of the characterization completed for impact features by size, depth, impactor diameter, and the impactor residues chemical analyses, allowing a differentiation between micrometeoroids and orbital debris and a categorization by mass density and density class. Impactor diameter is estimated using damage equations generated from ground-based hypervelocity impact testing. The orbital debris impactors are compared to the current ORDEM 3.2 model of the environment at ISS altitudes. We briefly discuss the meteoroid impactors, including constituents and mass densities, in the general context of current models.

Phillip Anz-Meador↗

NASA NTRSDate not supplied

Planning Satellite Swarm Measurements for Climate Models: Comparing Dynamic Constraint Processing and MILP Methods

We present D-SHIELD, a challenging climate science application to plan coordinated measurements (observations) for a constellation of satellites, each containing two different sensors, each with 61 pointing angle options. The L-band and P-band radar sensors collect data fed into a soil moisture model which tracks and predicts soil moisture across 1.67 million Ground Positions (GP). Soil moisture is an important predictor of wildfires, and then a predictor of floods, landslides and debris flow after a fire. Each measurement covers multiple GP due to the sensor footprint. Each GP has a "model error" which represents the uncertainty of the the soil moisture state prediction. Model error changes at different rates for each GP as the time since last observation increases and after significant events like rain. The planner's goal is to select measurements which maximize soil moisture model improvement (reduce model uncertainty). This problem is combinatorically explosive, involving many degrees of freedom for planner choices. Good domain heuristics can find solutions within a reasonable time for our application needs but cannot be proven optimal. In this paper we compare two different planning approaches to this problem: Dynamic Constraint Processing (DCP) and Mixed Integer Linear Programming (MILP). We match inputs and metrics for both DCP and MILP algorithms to enable a direct apples-to-apples comparison. We demonstrate and discuss the trades between DCP flexibility and performance vs. MILP's promise of provable optimality.

Rich Levinson↗

DOE OSTI2025

The Second Skin: A Wearable Sensor Suite that Enables Real-Time Human Biomechanics Tracking Through Deep Learning

Objective: Real-time determination of human kinematics and kinetics could advance biomechanics research and enable valuable applications of biofeedback and generalizable exoskeleton control. Here, this work aims to investigate a taskindependent, user-independent method for obtaining precise realtime joint state estimation across lower-body joints during a wide variety of tasks. Methods: We developed a generalizable sensing approach using a suit comprised of inertial measurement units (IMUs) and pressure insoles. With the suit, we collected a dataset of 33 tasks commonly performed during construction and hazardous waste cleanup (N = 10). We then trained deep learning user-independent, task-agnostic models to estimate joint lowerbody kinematics and dynamics using only worn sensor data. We likewise computed joint kinematics and dynamics analytically from sensor data to serve as a comparison tool for model results. Results: Our models achieved overall angle estimation root-meansquared-errors (RMSE) of 6.56±.92°, 8.60±1.01°, 7.58±.89°, and 6.00±.73° compared to 13.9±.1.3°, 15.31±1.0°, 10.76±.70°, and 7.56±.48° via analytical methods at the lower back, hip, knee, and ankle, respectively. Likewise, our models achieved overall normalized moment estimation RMSEs of .207±.069 Nm/kg, .242±.044 Nm/kg, .202±.038 Nm/kg, and .193±.034 Nm/kg compared to .306±.036 Nm/kg, .407±.021 Nm/kg, 1.18 ±.022 Nm/kg, and 1.73±.071 Nm/kg via analytical methods at the lower back, hip, knee, and ankle, respectively. Conclusion: These results are comparable to other state-of-the-art wearable sensing systems, establishing deep learning as a viable sensing approach that generalizes to new users and tasks. Significance: This work shows promise for enabling accurate real-world biomechanical data collection and enhancement of biofeedback systems and wearable robot control.

Casey, Ryan T. F. [Georgia Institute of Technology↗