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At least 1,243 records · Page 69

The NASA-ER2 meteorological measurement system: Instrumentaion, calibration and intercomparison results

The NASA ER-2 aircraft is used as a platform for high altitude atmospheric missions. The Meteorological Measurement System (MMS) was designed specifically for atmospheric research to provide accurate, fast response, in situ measurements of pressure, temperature, and the three dimensional wind vector. The MMS consists of three subsystems: an air motion sensing system to measure the velocity of the air with respect to the aircraft, a high resolution Inertial Navigation System (INS) to measure the velocity of the aircraft with respect to the Earth, and a Data Acquisition System, to sample, process and record the measured quantities. Details of each of these systems are given. The location of the MMS instrumentation is illustrated. The calibration of the MMS is discussed and results on an intercomparison of MMS measurements, Vaisala radiosonde observation and radar tracking data are given. An illustration of the MMS measurement of vertical wind is given.

Chan, K. Roland↗

Evaluation of the maximum cross-correlation method of estimating sea surface velocities from sequential satellite images

The maximum cross correlation (MCC) method of Leese et al. (1971) for estimating sea surface velocities from sequences of satellite images is evaluated by comparing the MCC fields obtained from sequences of AVHRR and CZCS with in situ data and velocity fields calculated with a high-resolution quasi-geostrophic model. The rms differences and vector correlations between the velocity field produced by the MCC method and the model's field are presented. It is shown that much of the difference between the MCC fields and either the in situ data or the model velocity fields can be accounted for by considering physical and biological processes not included in the MCC method. The conditions under which the method is likely to be most successful are discussed.

Tokmakian, Robin↗

Evaluation and modeling of autonomous attitude thrust control for the Geostation Operational Environmental Satellite (GOES)-8 orbit determination

The Geostationary Operational Environmental Satellite (GOES)-8 experienced a series of orbital perturbations from autonomous attitude control thrusting before perigee raising maneuvers. These perturbations influenced differential correction orbital state solutions determined by the Goddard Space Flight Center (GSFC) Goddard Trajectory Determination System (GTDS). The maneuvers induced significant variations in the converged state vector for solutions using increasingly longer tracking data spans. These solutions were used for planning perigee maneuvers as well as initial estimates for orbit solutions used to evaluate the effectiveness of the perigee raising maneuvers. This paper discusses models for the incorporation of attitude thrust effects into the orbit determination process. Results from definitive attitude solutions are modeled as impulsive thrusts in orbit determination solutions created for GOES-8 mission support. Due to the attitude orientation of GOES-8, analysis results are presented that attempt to absorb the effects of attitude thrusting by including a solution for the coefficient of reflectivity, C(R). Models to represent the attitude maneuvers are tested against orbit determination solutions generated during real-time support of the GOES-8 mission. The modeling techniques discussed in this investigation offer benefits to the remaining missions in the GOES NEXT series. Similar missions with large autonomous attitude control thrusting, such as the Solar and Heliospheric Observatory (SOHO) spacecraft and the INTELSAT series, may also benefit from these results.

Forcey, W.↗

Using WorldView-2 Imagery to Track Flooding in Thailand in a Multi-Asset Sensorweb

For the flooding seasons of 2011-2012 multiple space assets were used in a "sensorweb" to track major flooding in Thailand. Worldview-2 multispectral data was used in this effort and provided extremely high spatial resolution (2m / pixel) multispectral (8 bands at 0.45-1.05 micrometer spectra) data from which mostly automated workflows derived surface water extent and volumetric water information for use by a range of NGO and national authorities. We first describe how Worldview-2 and its data was integrated into the overall flood tracking sensorweb. We next describe the use of Support Vector Machine learning techniques that were used to derive surface water extent classifiers. Then we describe the fusion of surface water extent and digital elevation map (DEM) data to derive volumetric water calculations. Finally we discuss key future work such as speeding up the workflows and automating the data registration process (the only portion of the workflow requiring human input).

surface water extent↗

Geostar – a ‘Shovel Ready’ Geostationary Microwave Sounder

A geostationary microwave sounder, capable of providing temperature, water vapor, clouds, precipitation, and wind in the presence of clouds, convection and precipitation, will add tremendously to our ability to observe dynamic atmospheric phenomena, such as hurricanes and severe storms, monsoonal moisture flow, atmospheric rivers, etc. Such a sensor is now feasible, enabled by technology that has been developed under NASA’s Instrument Incubator Program at the Jet Propulsion Laboratory. The Geostationary Synthetic Thinned Aperture Radiometer (GeoSTAR) is essentially an “AMSU in GEO”, i.e. it has similar capabilities as AMSU would have if it were operating on a geostationary satellite, but with similar spatial resolution. GEO orbits are almost 50 times higher than the LEO orbits that current AMSUs operate from, and the corresponding scaling of aperture size required to maintain spatial resolution has stymied the development of such a sensor for many decades. The aperture synthesis approach implemented with GeoSTAR finally overcomes that obstacle, and the large number of microwave receivers and associated electronics required is made possible with new technology that has now been developed. A low-cost mission operating as a hosted payload on a commercial communications satellite has been designed and is “shovel-ready”. The objectives of such a mission could be to advance our understanding and modeling of storm processes that control rapid or explosive intensification of hurricanes, mesoscale convective systems, and extratropical cyclones, or it could be to support operational weather forecasting and nowcasting. Retrieval of temperature and water vapor profiles is possible even in the presence of moderate precipitation, and with the ability to derive horizontal wind vectors by tracking water vapor features, a rich set of parameters measuring the thermodynamics, dynamics and convection and sampled every 15 minutes, will enable significant progress in storm science and forecasting.

Lambrigtsen, Bjorn H↗

Developing Concepts of Operations Using Multi-Step Tool Techniques With Large Language Models

The National Aeronautics and Space Administration (NASA) Air Mobility Pathfinders (AMP) project is developing and evaluating concepts of operations (ConOps) for safe, secure, and scalable Urban Air Mobility (UAM) operations. The AMP project’s Operational Concepts, Architecture, and Requirements Integration (OCARI) Team is using a Model Based System Engineering (MBSE) approach for integration, interoperability, and traceability of Advanced Air Mobility (AAM) ecosystems centered around urban air taxi services. The team’s goal is to define structures and behaviors needed for system feasibility, readiness, and interoperability, establish a UAM knowledge base, and trace and validate assumptions and requirements relevant to AAM. NASA Langley Research Center (LaRC) is spearheading an innovative digital engineering approach to integrate, communicate, and facilitate the research of multi-modal transportation systems. The Knowledge-based Digital Platform (KbDP) is a concept being developed that ties the workflows of Project Managers (PM), Principal Investigators (PI), and System Engineers together across organizational boundaries. It does so through the management of an information database defined by mathematical, data science, and system engineering principles. Machine Learning (ML) algorithms play a key role in this concept by extracting meaningful knowledge from relational and graph databases, document repositories, and system artifacts, which the human user leverages to greatly improve the efficiency and effectiveness of their research. Recent advancements in the field of Large Language Models (LLMs), specifically models trained for tool use, such as Command-R , now allow for the reliable implementation of single-step and multi-step tool-centric systems. These techniques provide the LLM with a set of tools, in our case Python functions, that can be called on to answer a much wider range of questions compared to LLMs implemented using a traditional single-source or Retrieval Augmented Generation (RAG) approach. Through this method, the LLM can pull information from multiple data sources, such as relational or graph databases, document repositories, application programming interfaces (APIs), and SysML artifacts depending on the user’s question. The LLM can also output the information in a variety of different formats, using output generation tools, such as CSV, UML, or SysML artifacts. Additionally, tools can be assigned roles and can work together to provide answers to queries in an “agent” like approach, similar to that implemented by Microsoft’s AutoGen framework where different agents can converse with each other to accomplish tasks. Previously, our team developed a chatbot system with “agent like” functionality in the form of different “modes” the user could select from a user interface (UI), this architecture can be seen on the left in figure 1. Three different modes were implemented, the first mode allowed the LLM to utilize the structures and algorithms within a graph database to trace UAM requirements. The second mode gave the LLM access to a vector search capable of providing relevant information from thousands of document pages related to UAM ConOps and requirements. The third mode served as a general assistant where users could enter open-ended questions and custom prompts to utilize the LLM for different use-cases. This system improved the process surrounding generating and analyzing information related to UAM requirements, however, the implementation provided a clunky user experience. Users were required to know what mode to select within the UI in advance before entering their question to the selected tool. Moreover, the different tools were isolated from each other, they lacked bidirectional links that would allow for tools to collaborate to generate better responses. Our team is working on a new architecture, seen on the right in the below figure, with the goal to address many of the UX shortcomings of our original system while improving the accuracy and depth of responses from the LLM. This new system will automatically select the appropriate tool to use based off the user’s question. Each tool will be capable of calling on any of the other tools available to the LLM, resulting in a collaborative pipeline where tools can pass data between other tools until enough data is received to generate an answer to the user’s question. Using a locally deployed, open-source, LLM, the NASA OCARI team, in collaboration with Collins Aerospace, will implement a prototype application that will bridge knowledge across multiple sources to assist System Engineers (SEs) with requirements discovery and tracing, research question and use case identification, and assumption validation. Such a system will also allow SEs to more easily, and intuitively, explore the AAM ecosystem, ultimately improving the efficiency and effectiveness of the SE's research and decision-making processes surrounding ConOps development and validation. In this session, our team will provide a video demonstration of our new prototype architecture in action. We will also present an overview of our prototype system architecture and talk about its advantages over traditional LLM deployments along with how those advantages can provide additional value to the field of System Engineering.

systems engineering↗

Interflow Is Not Binary: A Continuous Shallow Perched Layer Does Not Imply Continuous Connectivity

Hillslopes exert critical controls on the quality and quantity of downstream waters. To understand and model dominant headwater catchment processes, we need to estimate the relative importance of different runoff generation processes. In this work we analyze published data from studies of 17 hillslopes from a range of landscapes to better understand the relative role of interflow, that is, shallow lateral subsurface flow moving over a layer impeding percolation, in streamflow generation. For each slope, we calculated downslope interflow travel distances, that is, the potential distance a water parcel travels downslope above an impeding layer until it percolates into the impeding layer. The downslope travel distances for the 17 hillslopes ranged from around 1 m to several hundred meters. The vector analysis of downslope travel distances revealed that all but three hillslopes had slope lengths that were much longer than downslope travel distances. For the remaining 14 cases we could show that most water perched above a shallow impeding layer percolates through the impeding layer before reaching the valley or the stream channel. Thus, interflow usually contributes directly to valley water or streamflow only from the lower portions of the hillslope in most landscapes. A critical finding of our analysis is that a continuously perched saturated zone with downslope flow does not imply continuous connectivity to the stream. Such a continuous connectivity is the exception rather than the rule in most landscapes. Future hillslope and headwater processes and modeling studies will need to account for this.

60 APPLIED LIFE SCIENCES↗

Single-Vector Calibration of Wind-Tunnel Force Balances

An improved method of calibrating a wind-tunnel force balance involves the use of a unique load application system integrated with formal experimental design methodology. The Single-Vector Force Balance Calibration System (SVS) overcomes the productivity and accuracy limitations of prior calibration methods. A force balance is a complex structural spring element instrumented with strain gauges for measuring three orthogonal components of aerodynamic force (normal, axial, and side force) and three orthogonal components of aerodynamic torque (rolling, pitching, and yawing moments). Force balances remain as the state-of-the-art instrument that provide these measurements on a scale model of an aircraft during wind tunnel testing. Ideally, each electrical channel of the balance would respond only to its respective component of load, and it would have no response to other components of load. This is not entirely possible even though balance designs are optimized to minimize these undesirable interaction effects. Ultimately, a calibration experiment is performed to obtain the necessary data to generate a mathematical model and determine the force measurement accuracy. In order to set the independent variables of applied load for the calibration 24 NASA Tech Briefs, October 2003 experiment, a high-precision mechanical system is required. Manual deadweight systems have been in use at Langley Research Center (LaRC) since the 1940s. These simple methodologies produce high confidence results, but the process is mechanically complex and labor-intensive, requiring three to four weeks to complete. Over the past decade, automated balance calibration systems have been developed. In general, these systems were designed to automate the tedious manual calibration process resulting in an even more complex system which deteriorates load application quality. The current calibration approach relies on a one-factor-at-a-time (OFAT) methodology, where each independent variable is incremented individually throughout its full-scale range, while all other variables are held at a constant magnitude. This OFAT approach has been widely accepted because of its inherent simplicity and intuitive appeal to the balance engineer. LaRC has been conducting research in a "modern design of experiments" (MDOE) approach to force balance calibration. Formal experimental design techniques provide an integrated view to the entire calibration process covering all three major aspects of an experiment; the design of the experiment, the execution of the experiment, and the statistical analyses of the data. In order to overcome the weaknesses in the available mechanical systems and to apply formal experimental techniques, a new mechanical system was required. The SVS enables the complete calibration of a six-component force balance with a series of single force vectors.

Parker, P. A.↗

Forbidden scalar dark matter and dark Higgses

As experimental searches for WIMP dark matter continue to yield null results, models beyond the WIMP paradigm have proliferated in order to elude ever improving observational constraints, among them that of sub-GeV dark matter mediated by a massive vector portal (a dark photon) associated with a new dark U(1) gauge symmetry. It has been previously noted that for a significant range of the parameter space of this class of models, the annihilation of dark matter particles into a pair of dark photons can dominate the freeze-out process even when this process is kinematically forbidden for dark matter at rest — this is known as the “forbidden dark matter” (FDM) regime. Prior studies of this regime, however, assume that any “dark Higgs” associated with breaking the dark U(1) and imparting mass to the dark photon is decoupled from the dark matter and as such plays no role in the freeze-out process. In this paper, we explore the effects of a dark Higgs on sub-GeV dark matter phenomenology in this FDM regime by considering the simplest possible construction in which there exist non-trivial dark matter-dark Higgs couplings: a model with a single complex scalar DM candidate coupled directly to the dark Higgs field. We find that for a wide range of parameter space, the dark Higgs can alter the resulting relic abundance by many orders of magnitude, and that this effect can remain significant even for a small dark matter-dark Higgs coupling constant. Considering measurements from direct detection and measurements of the CMB, we further find that points in this model’s parameter space which recreate the appropriate dark matter relic abundance suffer only mild constraints from other sources at present, but may become accessible in near-future direct detection experiments.

79 ASTRONOMY AND ASTROPHYSICS↗

Cloning, Purification, and Characterization of Recombinant Thermostable β-Xylanase Tnap-0700 from Thermotoga naphthophila

The gene of a β-xylanase (Tnap-0700) was cloned from a hyperthermophilic Thermotoga naphthophila strain ATCC BAA-489 and expressed in Escherichia coli BL21 (DE3) via pET-21a (+) as an expression vector. The growth steps were upgraded for highest β-xylanase expression via several factors, for example, IPTG concentration, time of induction, pH, and temperature. The pH and temperature optima for the extreme expression of β-xylanase were 7.0 pH and 37 °C, correspondingly. Recombinant enzyme purified by heat treatment process, then later by immobilized metal ion affinity chromatography. Molecular mass of the purified β-xylanase was 38 kDa observed by sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE). The enzyme was stable at room temperature for 30 days. It exhibited high stability over wide series of temperature 50–90 °C and pH 4.0–9.0 upon the addition of 1 mM Ca{sup +2} and reduced in the existence of Cu{sup +2} and EDTA. The addition of about 10–30% different organic solvents have no considerable effect on enzyme. However, SDSF and urea acting as an inhibitor leads to decrease in the enzyme activity. The β-xylanase enzyme was active to hydrolyze xylan from beechwood forming xylose. Thermostable β-xylanase causes the breakdown of complex carbohydrates into monosaccharide components. This thermostable β-xylanase revealed remarkable properties, which make it an encouraging candidate for various industrial applications especially in the alteration of renewable biomaterials into ethanol production, and biofuels from lignocellulosics has acknowledged much devotion subsequently in the last decade.

60 APPLIED LIFE SCIENCES↗

A data-centric weak supervised learning for highway traffic incident detection

Using the data from loop detector sensors for near-real-time detection of traffic incidents on highways is crucial to averting major traffic congestion. While recent supervised machine learning methods offer solutions to incident detection by leveraging human-labeled incident data, the false alarm rate is often too high to be used in practice. Specifically, the inconsistency in the human labeling of the incidents significantly affects the performance of supervised learning models. To that end, we focus on a data-centric approach to improve the accuracy and reduce the false alarm rate of traffic incident detection on highways. We develop a weak supervised learning workflow to generate high-quality training labels for the incident data without the ground truth labels, and we use those generated labels in the supervised learning setup for final detection. This approach comprises three stages. First, we introduce a data preprocessing and curation pipeline that processes traffic sensor data to generate high-quality training data through leveraging labeling functions, which can be domain knowledge-related or simple heuristic rules. Second, we evaluate the training data generated by weak supervision using three supervised learning models-random forest, k-nearest neighbors, and a support vector machine ensemble-and long short-term memory classifiers. The results show that the accuracy of all of the models improves significantly after using the training data generated by weak supervision. Third, we develop an online real-time incident detection approach that leverages the model ensemble and the uncertainty quantification while detecting incidents. Finally, we show that our proposed weak supervised learning workflow achieves a high incident detection rate (0.90) and low false alarm rate (0.08).

97 MATHEMATICS AND COMPUTING↗

Calcium-mediated nitrogen reduction for electrochemical ammonia synthesis

Ammonia (NH 3 ) is a key commodity chemical for the agricultural, textile and pharmaceutical industries, but its production via the Haber–Bosch process is carbon-intensive and centralized. Alternatively, an electrochemical method could enable decentralized, ambient NH 3 production that can be paired with renewable energy. The first verified electrochemical method for NH 3 synthesis was a process mediated by lithium (Li) in organic electrolytes. So far, however, elements other than Li remain unexplored in this process for potential benefits in efficiency, reaction rates, device design, abundance and stability. In our demonstration of a Li-free system, we found that calcium can mediate the reduction of nitrogen for NH 3 synthesis. Here we verified the calcium-mediated process using a rigorous protocol and achieved an NH 3 Faradaic efficiency of 40 ± 2% using calcium tetrakis(hexafluoroisopropyloxy)borate (Ca[B(hfip) 4 ] 2 ) as the electrolyte. Our results offer the possibility of using abundant materials for the electrochemical production of NH 3 , a critical chemical precursor and promising energy vector

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Revisiting supernova constraints on a light CP-even scalar

A light CP-even Standard Model (SM) gauge-singlet scalar S can be produced abundantly in the supernova core, via the nucleon bremsstrahlung process NN → NNS, due to its mixing with the SM Higgs boson. Including the effective S coupling to both nucleons and the pion mediators, we evaluate the production amplitude for the S particle and point out a key difference with the well-known light CP-odd scalar (axion) and vector boson (dark photon) cases. Taking the subsequent decay and re-absorption of S into account, we present a complete calculation of the energy loss rate for the S particle. We then use the SN1987A luminosity constraints to derive updated supernova limits on the mixing of the scalar S with the SM Higgs boson. We find that the mixing angle sin θ with the SM Higgs is excluded only in the narrow range of 3.9 × 10 -7 to 7.0 × 10 -6 , depending on the scalar mass up to about 147 MeV, beyond which the supernova limit disappears.

79 ASTRONOMY AND ASTROPHYSICS↗

Cumulative Spatial Impact Layers: A Novel Multivariate Spatio-Temporal Analytical Summarization Tool

Scientific inquiry often requires analysis of multiple spatio-temporal datasets, ranging in type and size, using complex multi-step processes demanding an understanding of GIS theory and software. Cumulative Spatial Impact Layers (CSIL) is a GIS-based tool that summarizes spatio-temporal datasets based on overlapping features and attributes. Leveraging a recursive quadtree method, and applying multiple additive frameworks, the CSIL tool allows users to analyze raster and vector datasets by calculating data, record, or attribute density. Providing an efficient and robust method for summarizing disparate, multi-format, multi-source geospatial data, CSIL addresses the need for a new integration approach and resulting geospatial product. The built-in flexibility of the CSIL tool allows users to answer a range of spatially-driven questions. Example applications are provided in this paper to illustrate the versatility and variety of uses for this CSIL tool and method. Use cases include addressing regulatory decision-making needs, economic modeling, and resource management. Performance reviews for each use case are also presented, demonstrating how CSILs provides a more efficient and robust approach to assess a range of multivariate spatial data for a variety of uses.

58 GEOSCIENCES↗

Vector elastic deconvolution migration with dual wavefield decomposition

Here, we report elastic-wave imaging using multicomponent data can provide more useful subsurface information than acoustic-wave imaging, but it is usually algorithmically challenging. We have developed a vector elastic deconvolution migration method for high-resolution imaging of subsurface structures in isotropic and anisotropic elastic media. Our new method uses a vector deconvolution imaging condition based on dual wavefield decomposition, including an explicit directional wavefield separation using the Hilbert transform and a P/S vector wavefield decomposition using the low-rank decomposition method. Using three elastic models, we numerically determine that our new method produces notably higher resolution and more amplitude-balanced elastic images compared with a crosscorrelation-based vector elastic reverse time migration method.

58 GEOSCIENCES↗

Pushing the Limits of Micro battery Capacity and Energy

Micro battery with higher energy density will extend the service life of the miniature sensors so that the scientists and engineers could be able to collect more data along with the time in ecological and environmental vectors, such as animal tracking. Within this project, a completely new cell design (Gen2) for micro batteries to further increase their cell capacity and energy is developed. The new cell design directly packages the active material in a hard aluminum case, decreasing the percentage of non-active components. The manufacturing process to improve wetting ability is studied and the trial run is finally given to evaluate the feasibility of the proposed technology. It’s found that both the capacity and energy with same battery size could be increased by 30% comparing with Gen1 micro battery technology previously developed by PNNL. The yield of Gen2 micro batteries is still lower due to the high degree of manual operation, especially for drilling process where more precise position control is needed. More effort is still required to improve the capability of automatic manufacturing processes. The new battery technology will support the development of smaller and lighter miniature sensors at PNNL and could potentially contribute to the large-scale manufacturing capabilities of micro batteries in US with reliable performances and long-term shelf life.

25 ENERGY STORAGE↗

Bulk viscosity of two-flavor color superconducting quark matter in neutron star mergers

This work investigates the bulk viscosity of warm, dense, neutrino-transparent, color-superconducting quark matter, where damping of density oscillations in the kHz frequency range arises from weak-interaction-driven direct Urca processes involving quarks. We study the two-flavor red-green paired color-superconducting (2SC) phase, while allowing for the presence of unpaired strange quarks and blue color light quarks of all flavors. Our calculations are based on the SU(3) Nambu–Jona–Lasinio model, extended to include both vector interactions and the ‘t Hooft determinant term. The primary focus is on how variations in the NJL Lagrangian parameters—specifically, the diquark and vector coupling strengths—affect both the static properties of quark matter, such as its equation of state and composition, and its dynamical behavior, including bulk viscosity and associated damping timescales. We find that the bulk viscosity and corresponding damping timescale can change by more than an order of magnitude upon varying the vector coupling by a factor of two at high densities and by a lesser degree at lower densities. This sensitivity primarily arises from the susceptibility of 2SC matter, with a smaller contribution from modifications to the weak interaction rates. In comparison, changes in the diquark coupling have a more limited impact. The damping of density oscillations in 2SC matter is similar quantitatively to nucleonic matter and can be a leading mechanism of dissipation in merging hybrid stars containing color superconducting cores.

Gravitational Waves↗

Measurements of rain effects on an 18-GHz dual-polarized propagation link

The paper presents highlights of rain attenuation and depolarization data collected between August 1972 and March 1974 in an experimental setup consisting of a 1.43-km line-of-sight path with 1.22-m diam dual-polarized parabolic reflector antennas at each end. The antennas used question-mark mounted scalar feeds oriented to transmit or receive linearly polarized 17.65-GHz signals having electric field vectors at +45 deg and -45 deg from the vertical. Rain data were collected and analyzed for 24 individual storms in which the rain rate exceeded 10 mm/hr. Received signal levels were sampled once each second and stored by a small digital computer which controlled the experiment and performed preliminary data processing. The results are compared with a theoretical model presented by Wiley et al. (1974). Experimental cross-polarization isolation data are found to agree well with theoretical values, especially at high rain rates where the antenna effects are the least significant.

Bostian, C. W.↗