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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 415 records · Page 23

Characterizing Porous and Nonporous Phenolic Resins from Molecular Dynamics Simulations

Phenolic resins are an important component of many ablative heat shield materials, which protect spacecrafts from the extreme temperatures reached during atmospheric entry. Examples include the high-density Heritage Carbon Phenolic (HCP) used in the Pioneer-Venus and Galileo missions, as well as the low-density Phenolic Impregnated Carbon Ablator (PICA) used in the Mars Science Laboratory and Mars 2020 missions. Additionally, recent developments within NASA have produced the mid-density Heatshield for Extreme Entry Environment Technology (HEEET) and its derivative 3D Woven Mid-Density Carbon Phenolic (3MDCP). Unlike the nonporous phenolic in HCP, PICA and HEEET/3MDCP are fabricated by infusing preforms with diluted phenolic formulations to obtain a lower density porous matrix. Despite the importance of the phenolic phase to the material response during entry, the variation in properties of porous and nonporous phenolic is not well understood. Here, we present an investigation of porous and nonporous phenolic resins using molecular dynamics (MD) simulations. Resin cure is mimicked in the simulations through the inclusion of representative reaction templates to generate accurate models of the complex crosslinked structures. To create porous models, explicit solvent molecules are included during the cure simulations. We observe nanoscale separation of the phenolic and solvent phases, which results in significant differences in the final structures of porous and nonporous models. In addition to a quantitative assessment of the network structure and porosity, we elucidate the effects of the phenolic formulation on the final material properties. These results are compared with experimental data as appropriate.

phenolic↗

The structure and evolution of seasonal wind anomalies over the near-equatorial eastern Indian and western Pacific Oceans

The longitude-height-time structure and evolution of near-equatorial wind variability over the eastern Indian and western Pacific Oceans are studied using data obtained from a network of eight radiosonde stations extending from southern India to the central Pacific Ocean. The seasonal zonal wind anomalies observed at the cross section beween Trivandrum and Majuro stations are analyzed using an empirical orthogonal function. The Walker Circulation fluctuations are described in terms of standing oscillations in the longitude-height plane, and it is determined that Southern Oscillation propagation anomaly best represents the wind fluctuations. A complex empirical orthogonal function (CEOF) analysis and an El Nino compositing methodology are applied to the seasonal zonal wind anomalies. It is determined that the composite El Nino anomalies correspond to the spatial structure and temporal evolution of anomalies implied by the CEOF analysis.

Gutzler, David S.↗

Application of Advanced Earth Observations and Model Simulations to Improve Air Quality Monitoring in the Hindu-Kush-Himalayan Region

Air pollution is a serious environmental health concern in the Hindu Kush Himalayan (HKH) region of south-central Asia, as rapid industrialization and population growth have led to increased anthropogenic emissions from transportation, residential, industrial, energy, and biomass burning sources. Natural emissions from dust and forest fires are additional sources of air pollutants that can exacerbate air quality in the region. The combination of the complex pollutant mixtures and atmospherically stable weather conditions during the winter monsoon can visibility reductions and hazardous air quality from persistent haze episodes. The Kathmandu Valley is especially vulnerable to extreme haze issues due to the surrounding mountains that restrict air movement and retains pollutants in the atmosphere. This study uses state-of-the-art satellite observations and modeling capabilities in conjunction with ground-based networks to provide a comprehensive data toolkit for advancing air quality monitoring and forecasting decisions in the HKH region. The toolkit includes new generation satellite observations from the TROPOspheric Monitoring Instrument (TROPOMI), Geostationary Environment Monitoring Spectrometer (GEMS), and Advanced Meteorological Imager, which provide high spatiotemporal information on NO2, HCHO, SO2, O3, and aerosol optical depth (AOD). Particulate matter with diameters less than 2.5 micrometers (PM2.5) are derived from the satellite-retrieved AOD using ground-based observations and forecast model data. The satellite observations are also used to initialize and constrain forecast model systems designed for the HKH region. This talk will highlight the performance of the air quality toolkit for enhancing decision-making processes during exceptional air quality events in the region. Note: Presentation includes additional attachment of full presentation with sound and animation (best when viewed as slide show) with runtime of 15 min 32 secs

Aaron Naeger↗

A Mars environmental survey (MESUR) - Feasibility of a low cost global approach

In situ measurements of Mars' surface and atmosphere are the objectives of a novel network mission concept called the Mars Environmental SURvey (MESUR). As envisioned, the MESUR mission will emplace a pole-to-pole global distribution of 16 landers on the Martian surface over three launch opportunites using medium-lift (Delta-class) launch vehicles. The basic concept is to deploy small free-flying probes which would directly enter the Martian atmosphere, measure the upper atmospheric structure, image the local terrain before landing, and survive landing to perform meteorology, seismology, surface imaging, and soil chemistry measurements. Data will be returned via dedicated relay orbiter or direct-to-earth transmission. The mission philosophy is to: (1) 'grow' a network over a period of years using a series of launch opportunities; (2) develop a level-of-effort which is flexible and responsive to a broad set of objectives; (3) focus on Mars science while providing a solid basis for future human presence; and (4) minimize overall project cost and complexity wherever possible.

Hubbard, G. S.↗

Comment on 'A dramatic decrease in the growth rate of atmospheric methane in the Northern Hemisphere during 1992' by E. J. Dlugokencky et al.

The carefully measured decrease in the growth rate of atmospheric methane (CH4) in 1992 reported by Dlugokencky et al. (1994) is an impressive accomplishment, and testimony for the importance of maintaining high-quality, long-term monitoring of atmospheric composition. The changing growth rate of atmospheric CH4 has important implications for assessing and understanding the potential magnitude and rates of a future greenhouse gas-induced climate change. Furthermore, the CH4 data from the current Climate Monitoring and Diagnostics Laboratory (CMDL) globally-distributed network of cooperative air sampling sites are clearly the best record of global CH4 trends and distribution currently available. However, we argue briefly here that the speculation by Dlugokencky et al. (1994) on possible mechanisms for the decreased growth rate in 1992 is only one scenario of many that could possibly fit with the constraints imposed by the reported data. Our comments are to (1) illustrate the difficulties of deducing small changes in complex, poorly understood, geographically diverse natural and anthropogenic sources of CH4 from measurements at the remotely-located CMDL sampling sites and (2) emphasize that detailed bottoms-up analyses are necessary to really advance the understanding of changes in source strengths; we are not promoting alternative mechanisms to explain the 1992 decrease in atmospheric CH4.

Hogan, Kathleen B.↗

NASA Tech Briefs, October 2003

Topics covered include: Cryogenic Temperature-Gradient Foam/Substrate Tensile Tester; Flight Test of an Intelligent Flight-Control System; Slat Heater Boxes for Thermal Vacuum Testing; System for Testing Thermal Insulation of Pipes; Electrical-Impedance-Based Ice-Thickness Gauges; Simulation System for Training in Laparoscopic Surgery; Flasher Powered by Photovoltaic Cells and Ultracapacitors; Improved Autoassociative Neural Networks; Toroidal-Core Microinductors Biased by Permanent Magnets; Using Correlated Photons to Suppress Background Noise; Atmospheric-Fade-Tolerant Tracking and Pointing in Wireless Optical Communication; Curved Focal-Plane Arrays Using Back-Illuminated High-Purity Photodetectors; Software for Displaying Data from Planetary Rovers; Software for Refining or Coarsening Computational Grids; Software for Diagnosis of Multiple Coordinated Spacecraft; Software Helps Retrieve Information Relevant to the User; Software for Simulating a Complex Robot; Software for Planning Scientific Activities on Mars; Software for Training in Pre-College Mathematics; Switching and Rectification in Carbon-Nanotube Junctions; Scandia-and-Yttria-Stabilized Zirconia for Thermal Barriers; Environmentally Safer, Less Toxic Fire-Extinguishing Agents; Multiaxial Temperature- and Time-Dependent Failure Model; Cloverleaf Vibratory Microgyroscope with Integrated Post; Single-Vector Calibration of Wind-Tunnel Force Balances; Microgyroscope with Vibrating Post as Rotation Transducer; Continuous Tuning and Calibration of Vibratory Gyroscopes; Compact, Pneumatically Actuated Filter Shuttle; Improved Bearingless Switched-Reluctance Motor; Fluorescent Quantum Dots for Biological Labeling; Growing Three-Dimensional Corneal Tissue in a Bioreactor; Scanning Tunneling Optical Resonance Microscopy; The Micro-Arcsecond Metrology Testbed; Detecting Moving Targets by Use of Soliton Resonances; and Finite-Element Methods for Real-Time Simulation of Surgery.

Source record↗

Large-Scale Simulation of a Distributed Sensing Network Supporting Regional Urban Air Mobility Operations

Urban Air Mobility (UAM) is set to transform transportation in densely populated regions like the San Francisco Bay Area. This paper introduces an innovative simulation approach to explore large-scale UAM scenarios, emphasizing the use of distributed sensing to enhance operational efficiency and safety. The Revolutionary Vertical Lift Technology (RVLT) model is employed as the framework for simulating complex interactions among multiple vehicles within urban landscapes. Strategically deployed ground sensor nodes enable distributed sensing, enhancing situational awareness and operational effectiveness. By integrating empirical data and geographical realism, the simulations provide a systematic analysis of the feasibility, efficiency, and safety considerations associated with UAM deployment in urban environments. Factors such as air traffic density and infrastructural requirements are thoroughly examined, offering actionable insights for policymakers and industry stakeholders. This paper aims to refine the structure and scenarios for large-scale simulations based on distributed sensing, thereby contributing to the advancement of UAM operations.

UAM↗

Large-Scale Simulation of a Distributed Sensing Network Supporting Regional Urban Air Mobility Operations

Urban Air Mobility (UAM) is set to transform transportation in densely populated regions like the San Francisco Bay Area. This paper introduces an innovative simulation approach to explore large-scale UAM scenarios, emphasizing the use of distributed sensing to enhance operational efficiency and safety. The Revolutionary Vertical Lift Technology (RVLT) model is employed as the framework for simulating complex interactions among multiple vehicles within urban landscapes. Strategically deployed ground sensor nodes enable distributed sensing, enhancing situational awareness and operational effectiveness. By integrating empirical data and geographical realism, the simulations provide a systematic analysis of the feasibility, efficiency, and safety considerations associated with UAM deployment in urban environments. Factors such as air traffic density and infrastructural requirements are thoroughly examined, offering actionable insights for policymakers and industry stakeholders. This paper aims to refine the structure and scenarios for large-scale simulations based on distributed sensing, thereby contributing to the advancement of UAM operations.

Aircraft Mobility↗

Using Machine Learning to Estimate Surface-Level SO2 Concentrations from Satellite-Based Measurements

Sulfur dioxide (SO2) is a criteria air pollutant due to its contributions to aerosol formation, rainfall acidification, and harm to human health. The placement of air quality monitoring sites is typically biased towards urban areas, leaving large areas with very limited monitoring data. The Ozone Monitoring Instrument (OMI) has been used to provide estimates of SO2 vertical column densities (VCDs) globally at spatial resolution of 10s of kms once per day. OMI SO2 VCDs have been previously used to estimate surface SO2 concentrations using chemical transport model (CTM) simulations. The CTMs use estimated emissions and assimilated meteorological data, and simulate the chemical and physical processes that determine the vertical profile of SO2, which can be used to derive a ratio between the surface concentrations and VCDs. These models are complex, computationally expensive, and have large uncertainties in the simulated surface-to-VCD ratio due to biases in emissions and relatively coarse resolution. Machine learning techniques are comparatively easier to use, much less computationally expensive to use after training, and can produce more accurate estimations of surface concentrations than the CTM-based method. The interpretation of machine learning models often poses challenges, and in some cases, non-physical variables unrelated to SO2 are used as predictors. In this work, we create an artificial neural network (ANN) to relate OMI retrievals and archived GEOS-FP boundary layer heights to surface SO2 concentrations from the ChinaHighAirPollutants ChinaHighSO2 dataset (CHAP; Wei et al., 2023) on a seasonal average timescale from 2013-2018. Our model only utilizes five variables that are directly relevant to the satellite retrieval, lifetime, and spatial distribution of SO2. The model was trained on 16 seasons (four of each) with independent validation (one of each season) and testing datasets (one of each season) to avoid overfitting. Our ANN generates surface SO2 concentrations that are sensitive (slope = 0.51) and consistent (r = 0.74) with the CHAP data, but are underpredicted by an average of 1.2 ppbv with a mean absolute error of 2.2 ppbv. These results are better than recent studies utilizing the CTM method. To our knowledge, this is the best performing machine learning model that only uses physical variables to predict surface SO2. Our work demonstrates that a carefully constructed, simple ML model can accurately estimate surface-based SO2 concentrations from satellite VCD measurements, and this technique has future promise to expend to newer, higher resolution satellites and other air pollutants.

SO2, air quality, OMI, machine learning↗

Maintenance of time and frequency in the Jet Propulsion Laboratory's Deep Space Network using the Global Positioning System

The Deep Space Network (DSN), managed by the Jet Propulsion Laboratory for NASA, must maintain time and frequency within specified limits in order to accurately track the spacecraft engaged in deep space exploration. Various methods are used to coordinate the clocks among the three tracking complexes. These methods include Loran-C, TV Line 10, Very Long Baseline Interferometry (VLBI), and the Global Positioning System (GPS). Calculations are made to obtain frequency offsets and Allan variances. These data are analyzed and used to monitor the performance of the hydrogen masers that provide the reference frequencies for the DSN Frequency and Timing System (DFT). Areas of discussion are: (1) a brief history of the GPS timing receivers in the DSN, (2) a description of the data and information flow, (3) data on the performance of the DSN master clocks and GPS measurement system, and (4) a description of hydrogen maser frequency steering using these data.

Clements, P. A.↗

Identification of the connections in biologically inspired neural networks

We developed an identification method to find the strength of the connections between neurons from their behavior in small biologically-inspired artificial neural networks. That is, given the network external inputs and the temporal firing pattern of the neurons, we can calculate a solution for the strengths of the connections between neurons and the initial neuron activations if a solution exists. The method determines directly if there is a solution to a particular neural network problem. No training of the network is required. It should be noted that this is a first pass at the solution of a difficult problem. The neuron and network models chosen are related to biology but do not contain all of its complexities, some of which we hope to add to the model in future work. A variety of new results have been obtained. First, the method has been tailored to produce connection weight matrix solutions for networks with important features of biological neural (bioneural) networks. Second, a computationally efficient method of finding a robust central solution has been developed. This later method also enables us to find the most consistent solution in the presence of noisy data. Prospects of applying our method to identify bioneural network connections are exciting because such connections are almost impossible to measure in the laboratory. Knowledge of such connections would facilitate an understanding of bioneural networks and would allow the construction of the electronic counterparts of bioneural networks on very large scale integrated (VLSI) circuits.

Demuth, H.↗

Assessing the Evolving Fragility of the Global Food System

The world food crisis in 2008 highlighted the susceptibility of the global food system to price shocks. Here we use annual staple food production and trade data from 1992-2009 to analyse the changing properties of the global food system. Over the 18-year study period, we show that the global food system is relatively homogeneous (85 of countries have low or marginal food self-sufficiency) and increases in complexity, with the number of global wheat and rice trade connections doubling and trade flows increasing by 42 and 90, respectively. The increased connectivity and flows within these global trade networks suggest that the global food system is vulnerable to systemic disruptions, especially considering the tendency for exporting countries to switch to non-exporting states during times of food scarcity in the global markets. To test this hypothesis, we superimpose continental-scale disruptions on the wheat and rice trade networks. We find greater absolute reductions in global wheat and rice exports along with larger losses in network connectivity as the networks evolve due to disruptions in European wheat and Asian rice production. Importantly, our findings indicate that least developed countries suffer greater import losses in more connected networks through their increased dependence on imports for staple foods (due to these large-scale disturbances): mean (median) wheat losses as percentages of staple food supply are 8.9 (3.8) for 1992-1996, increasing to 11 (5.7) for 20052009. Over the same intervals, rice losses increase from 8.2 (2.2) to 14 (5.2). Our work indicates that policy efforts should focus on balancing the efficiency of international trade (and its associated specialization) with increased resilience of domestic production and global demand diversity.

complex networks↗

Emulated Spacecraft Communication Testbed for Evaluating Cognitive Networking Technology

The ability to emulate the full space protocol stack is an essential aspect required to evaluate and mature cognitive communication capabilities. The interaction between the physical layer and network layers is key to developing network optimizations for a dynamic and complex environment. We present a laboratory testbed for the evaluation of cognitive radio and networking techniques applied to space communications. The testbed is a high fidelity, flight-like hardware testbed consisting of software-defined radios, channel emulators, modems, and orbital analysis and scheduling software. The testbed uses RF links with signal quality, propagation delay, and Doppler effects driven by orbital mechanics simulations of emulated spacecraft. Our framework enables control of link bidirectionality, data rates, and interference sources. In addition to hardware radio nodes, the testbed can incorporate virtualized emulated nodes for larger and more challenging network scenarios. Our approach to a cognitive communication system uses delay tolerant networking (DTN) to mitigate the challenges of the space environment. While many DTN networks use only preplanned schedules, our system uses User-Initiated Service (UIS) to dynamically schedule service providers. Software-defined radio allows the system to adapt to a variety of service providers. Integration of DTN, UIS, and software-defined radio technologies provides a framework for the implementation of a cognitive communication system. This paper describes the testbed capabilities, network emulation approach, component integration, and initial end-to-end testing results.

cognitive radio↗

Commissioning of NASA's 3rd Generation Tracking and Data Relay Satellites (TDRS KLM)

In the summer of 2017, the third and final spacecraft of the 3rd generation of the Tracking and Data Relay Satellites (TDRS) launched aboard an Atlas V rocket from Complex 41 on the Eastern Test Range. Finishing final testing and integration in the first quarter of 2018, the TDRS-M communication and navigation satellite completes a constellation that began service in the early 1980s. The 3rd generation of spacecraft, TDRS-K, L, and M, not only provided beneficial systems engineering lessons in handling anomalous Radio Frequency and Doppler interference as well as integrating new spacecraft into an aging ground support infrastructure, but also supplies NASA with a valuable test bed for new operational concepts and technologies useful in defining the future architecture of the NASA Space Network. This paper presents an overview of the TDRS-K, L, and M missions, including transfer orbit, Level 5 bus and payload testing, and finally NASA-led Level 6 testing, which includes active TDRS System (TDRSS) users. Highlights include relevant testing results, commissioning challenges, and lessons learned. The final discussion includes a brief overview of future NASA communication and navigation technologies and network architectures.

Data Relay↗

A twenty-first century perspective

The status of the NASA assets which are operated by the Office of Space Operations is briefly reviewed. These assets include the ground network, the space network, and communications and data handling facilities. The current plans for each element are examined, and a projection of each is made to meet the user needs in the 21st century. The following factors are noted: increasingly responsive support will be required by the users; operational support concepts must be cost-effective to serve future missions; and a high degree of system reliability and availability will be required to support manned exploration and increasingly complex missions.

Aller, Robert O.↗

A feasibility study for long-path multiple detection using a neural network

Least-squares inverse filters have found widespread use in the deconvolution of seismograms and the removal of multiples. The use of least-squares prediction filters with prediction distances greater than unity leads to the method of predictive deconvolution which can be used for the removal of long path multiples. The predictive technique allows one to control the length of the desired output wavelet by control of the predictive distance, and hence to specify the desired degree of resolution. Events which are periodic within given repetition ranges can be attenuated selectively. The method is thus effective in the suppression of rather complex reverberation patterns. A back propagation(BP) neural network is constructed to perform the detection of first arrivals of the multiples and therefore aid in the more accurate determination of the predictive distance of the multiples. The neural detector is applied to synthetic reflection coefficients and synthetic seismic traces. The processing results show that the neural detector is accurate and should lead to an automated fast method for determining predictive distances across vast amounts of data such as seismic field records. The neural network system used in this study was the NASA Software Technology Branch's NETS system.

Feuerbacher, G. A.↗

Architectural Methodology Report

The establishment of conventions between two communicating entities in the end systems is essential for communications. Examples of the kind of decisions that need to be made in establishing a protocol convention include the nature of the data representation, the for-mat and the speed of the date representation over the communications path, and the sequence of control messages (if any) which are sent. One of the main functions of a protocol is to establish a standard path between the communicating entities. This is necessary to create a virtual communications medium with certain desirable characteristics. In essence, it is the function of the protocol to transform the characteristics of the physical communications environment into a more useful virtual communications model. The final function of a protocol is to establish standard data elements for communications over the path; that is, the protocol serves to create a virtual data element for exchange. Other systems may be constructed in which the transferred element is a program or a job. Finally, there are special purpose applications in which the element to be transferred may be a complex structure such as all or part of a graphic display. NASA's Glenn Research Center (GRC) defines and develops advanced technology for high priority national needs in communications technologies for application to aeronautics and space. GRC tasked Computer Networks and Software Inc. (CNS) to describe the methodologies used in developing a protocol architecture for an in-space Internet node. The node would support NASA:s four mission areas: Earth Science; Space Science; Human Exploration and Development of Space (HEDS); Aerospace Technology. This report presents the methodology for developing the protocol architecture. The methodology addresses the architecture for a computer communications environment. It does not address an analog voice architecture.

Dhas, Chris↗

Software Configurable Multichannel Transceiver

Emerging test instrumentation and test scenarios increasingly require network communication to manage complexity. Adapting wireless communication infrastructure to accommodate challenging testing needs can benefit from reconfigurable radio technology. A fundamental requirement for a software-definable radio system is independence from carrier frequencies, one of the radio components that to date has seen only limited progress toward programmability. This paper overviews an ongoing project to validate the viability of a promising chipset that performs conversion of radio frequency (RF) signals directly into digital data for the wireless receiver and, for the transmitter, converts digital data into RF signals. The Software Configurable Multichannel Transceiver (SCMT) enables four transmitters and four receivers in a single unit the size of a commodity disk drive, programmable for any frequency band between 1 MHz and 6 GHz.

Freudinger, Lawrence C.↗