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NASA NTRSDate not supplied

Exergy-based Sensitivity Analysis of the Generic Hypersonic Vehicle using FUN3D

In this paper, the implementation of an exergy-based objective function and its adjoint gradient into NASA’s FUN3D solver is discussed and verified. In order to verify that the exergy-based functional is properly implemented, it is used to predict the drag of the Generic Hypersonic Vehicle (GHV), which is then compared to more traditional force-based drag predictions. In addition to the functional implementation, FUN3D’s adjoint capability was extended to obtain sensitivities. Results were verified using FUN3D’s native complex step method for di↵erentiation using a generic wing configuration. The complex and adjoint gradients yielded discrete agreement demonstrating correct implementation and that the functional can be used for gradient-based multidisciplinary analysis and optimization. Next, various trade studies are conducted on the GHV to understand the design space of the vehicle. Finally, an inverse design problem is solved to verify the utilized design optimization framework which is ready to be deployed for exergy-based optimizations in future work.

Neal L. Novotny↗
NASA NTRSDate not supplied

Setting the Bar for the Replacement of the Probability of Collision Metric

To date, satellite conjunction assessment (CA) risk analysis has largely embraced the probability of collision (Pc) as the omnibus metric to evaluate collision likelihood, and its use in such assessments has mostly been straightforward: at the point at which a conjunction mitigation decision is required, the calculated Pc is compared to a threshold; and if the calculated Pc exceeds that threshold, then a mitigation action is warranted. With only minor variation, this approach is employed by major CA risk assessment centers (e.g., NASA, EUSST, CNES, JAXA) and is advanced as the preferred method in the published CA best practices handbooks. Despite this near unanimity of operational practice, there is a major strain of secondary literature critical of the Pc and willing to propose alternatives. Alfano (2005) pointed out the ability of the Pc to underrepresent the risk in certain situations and counselled a maximum Pc construct. Carpenter (2017, 2019) reiterated this criticism and proposed using instead a confidence interval on the miss distance. Balch et al. (2019) identified what they argued was a defect in the entire Bayesian Pc construct and believed that the use of a more conservative methodology based on covariance ellipsoid overlap was necessary. Delande (2022) introduced the framework of collision “plausibility” to the risk assessment process and sketched out how this might be used operationally. Elkantassi (2022) published a full development of the miss distance confidence interval approach and applied it to several worked examples. While these different approaches to collision risk assessment do differ in their details, they all converge on two central points: first, the Pc’s failure to give an adequate expression of the risk in dilution region situations is a fatal flaw; and second, a conjunction should be presumed risky and in need of mitigation until the evidence of the situation can establish otherwise. These criticisms, if correct, would counsel a number of modifications to current CA operational practice; as such, they force a re-examination of fundamental aspects of the CA problem, including the following: 1. Is the CA risk assessment a probability problem, a statistics problem, or something else? 2. If it is a statistics problem, does it lend itself naturally to a hypothesis test construction? 3. If it can be construed as a hypothesis test, what form should the null hypothesis take, to wit: what constraints exist on the choice of the null hypothesis, what selections are in best alignment with all of the attendant parameters of the problem, and what is implied philosophically by different choices? 4. What are the implications of using the different proposed risk assessment parameters for CA? This question should be answered both in determining how frequently the dilution region situation cited by the critics of the Pc actually appears in an operationally significant manner and the missed detection and false alarm rates of all of the proposed risk assessment metrics, compared both to the Pc and to each other. This paper explores and offers preliminary answers to the above questions, presenting a researched treatment of the philosophical nature of the CA problem and the null hypothesis choice that achieves the greatest consistency with all of the different aspects of operational CA conduct. It then profiles all of the different proposed risk assessment metrics enumerated in the earlier paragraph against an extremely large database of conjunction events at both the 550km and 700km altitudes. The combination of the philosophical exploration of the CA problem and the results of the profiling activity articulates what a risk assessment metric will need to demonstrate, in terms of both innate construction and performance, in order to be a true competitor to the Pc.

conjunction assessment↗
NASA NTRS2011

Multi-Decadal Change of Atmospheric Aerosols and their Effect on Surface Radiation

We present an investigation on multi-decadal changes of atmospheric aerosols and their effects on surface radiation using a global chemistry transport model, GOCART, along with the near-term to long-term data records. We focus on a 28-year time period of satellite era from 1980 to 2007 during which a suite of aerosol data from satellite observations, ground-based measurements, and intensive field experiments have become available. Particularly: (1) We compare the model calculated clear sky downward radiation at the surface with surface network data from BSRN and CMA (2) We compare the model and surface data with satellite derived downward radiation products from ISCCP and SRS (3) We analyze the long-term global and regional aerosol trends in major anthropogenic source regions (North America, Europe, Asia) that have been experiencing considerable changes of emissions during the three decades, dust and biomass burning regions that have large interannual variability, downwind regions that are directly affected by the changes in the source area, and remote regions that are considered to representing "background" conditions. The comparisons and methods from this study can be applied to multiple model analysis in the AeroCom framework.

Chin, Mian↗
NASA NTRS1981

Applications systems verification and transfer project. Volume 5: Operational applications of satellite snow-cover observations, northwest United States

The study objective was to develop or modify methods in an operational framework that would allow incorporation of satellite derived snow cover observations for prediction of snowmelt derived runoff. Data were reviewed and verified for five basins in the Pacific Northwest. The data were analyzed for up to a 6-year period ending July 1978, and in all cases cover a low, average, and high snow cover/runoff year. Cloud cover is a major problem in these springtime runoff analyses and have hampered data collection for periods of up to 52 days. Tree cover and terrain are sufficiently dense and rugged to have caused problems. The interpretation of snowlines from satellite data was compared with conventional ground truth data and tested in operational streamflow forecasting models. When the satellite snow-covered area (SCA) data are incorporated in the SSARR (Streamflow Synthesis and Reservoir Regulation) model, there is a definite but minor improvement.

Dillard, J. P.↗
NASA NTRS2021

Faster Exo-Earth Yield for HabEx and LUVOIR via Extreme Precision Radial Velocity Prior Knowledge

The HabEx and LUVOIR mission concepts reported science yields for mission scenarios in which the instruments must search for potentially habitable planets, determine their orbits, and, if worthwhile, invest the integration time for a spectral characterization. We evaluate the impact of prior knowledge of planet existence and orbital parameters on yield for four mission concept architectures: HabEx 4m telescope with hybrid starshade and coronagraph, HabEx4m telescope with starshade only, HabEx 4m telescope with coronagraph only, and LUVOIR B8m telescope with coronagraph only. We use perfect prior knowledge to establish an upperbound on yield and use partial prior knowledge from a potential future extreme precision radial velocity (EPRV) instrument with3cm∕ssensitivity. We detail a modeling framework that per-forms dynamically responsive observation scheduling with realistic mission constraints. We evaluate exo-Earth yields against three metrics of spectral characterization for the four mission architectures and three levels of prior knowledge (none, partial, and perfect). The EPRV pro-vided prior knowledge increases yields by∼30%and accelerates by a factor of 3 to 6 the time to achieve half of the yield of the mission. Prior knowledge makes all the mission architectures more nimble and powerful, and most especially starshade-based architectures. With prior knowledge, a small telescope with a starshade can achieve comparable yield to a larger telescope with a coronagraph.

Rhonda Morgan↗
NASA NTRS2022

Alternative regularizations for Outer-Approximation algorithms for convex MINLP

In this work, we extend the regularization framework from Kronqvist et al. (Math Program 180(1):285–310, 2020) by incorporating several new regularization functions and develop a regularized single-tree search method for solving convex mixed-integer nonlinear programming (MINLP) problems. We propose a set of regularization functions based on distance metrics and Lagrangean approximations, used in the projection problem for finding new integer combinations to be used within the Outer-Approximation (OA) method. The new approach, called Regularized Outer-Approximation (ROA), has been implemented as part of the open-source Mixed-integer nonlinear decomposition toolbox for Pyomo—MindtPy. We compare the OA method with seven regularization function alternatives for ROA. Moreover, we extend the LP/NLP Branch and Bound method proposed by Quesada and Grossmann (Comput Chem Eng 16(10–11):937–947, 1992) to include regularization in an algorithm denoted RLP/NLP. We provide convergence guarantees for both ROA and RLP/NLP. Finally, we perform an extensive computational experiment considering all convex MINLP problems in the benchmark library MINLPLib. The computational results show clear advantages of using regularization combined with the OA method.

Convex Mixed-integer nonlinear programming↗
NASA NTRSDate not supplied

Impact Experiments into Granular Targets Containing Solitary Blocks of Varying Strength and Size

Crater scaling relationships provide a means to correlate dimensions of laboratory-scale impact experiments to naturally formed craters at planetary scales. For relatively larger impact events, where gravity is the dominant arresting force against crater growth, these scaling relations are comparatively simple. For smaller craters, however, the target properties have increasing influence over the cratering process. Further complexities are easily envisaged when considering realistic surfaces that contain small-scale heterogeneities in cohesive strength, density, porosity, friction, as these properties will each have unequal effects on the resultant crater morphometry. Even when produced under controlled laboratory conditions, understanding (and controlling) the entire relevant parameter space is daunting, and deconvolution of the relevant contributors can be complicated even in the best-case scenario. To this end, we have begun an extensive series of impact experiments that will provide a nascent framework that will aid in the interpretation of craters observed on complex natural surfaces throughout the solar system. To start with the simplest configuration, experiments were performed with cylindrical PVC buckets that were filled with quartz sand and contained a single cubic block of synthetic sandstone. The blocks varied in size (14-33 mm) and unconfined compressive strength (0.5-7.4 MPa) and were placed in/on the sand along the trajectory of the incoming impactor and buried to different depths. All experiments were conducted using the vertical gun located in the Experimental Impact Lab at NASA Johnson Space Center with alumina projectiles that were accelerated to ~1.53 km s^-1 under a vacuum of 1 torr. After the impact, target containers were removed from the chamber are morphometric data were extracted by using a Peel 2 3D-scanner in combination with the open-source software, CloudCompare. Initial results show that block strength is a secondary effect on crater diameter and depth, but when at least one edge of the block is exposed and the surface (partial burial) the strength will dictate the number of surviving block fragments around the crater, as well as how much disrupted block material is retained within the crater walls.

Christopher J. Cline II↗
NASA NTRS2009

Hypersonic Navier Stokes Comparisons to Orbiter Flight Data

Hypersonic chemical nonequilibrium simulations of low earth orbit entry flow fields are becoming increasingly commonplace as software and computational capabilities become more capable. However, development of robust and accurate software to model these environments will always encounter a significant barrier in developing a suite of high quality calibration cases. The US3D hypersonic nonequilibrium Navier Stokes analysis capability has been favorably compared to a number of wind tunnel test cases. Extension of the calibration basis for this software to Orbiter flight conditions will provide an incremental increase in confidence. As part of the Orbiter Boundary Layer Transition Flight Experiment and the Hypersonic Thermodynamic Infrared Measurements project, NASA is performing entry flight testing on the Orbiter to provide valuable aerothermodynamic heating data. An increase in interest related to orbiter entry environments is resulting from this activity. With the advent of this new data, comparisons of the US3D software to the new flight testing data is warranted. This paper will provide information regarding the framework of analyses that will be applied with the US3D analysis tool. In addition, comparisons will be made to entry flight testing data provided by the Orbiter BLT Flight Experiment and HYTHIRM projects. If data from digital scans of the Orbiter windward surface become available, simulations will also be performed to characterize the difference in surface heating between the CAD reference OML and the digitized surface provided by the surface scans.

Campbell, Charles H.↗
NASA NTRSDate not supplied

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↗
NASA NTRS2011

Visual Object Recognition and Tracking of Tools

A method has been created to automatically build an algorithm off-line, using computer-aided design (CAD) models, and to apply this at runtime. The object type is discriminated, and the position and orientation are identified. This system can work with a single image and can provide improved performance using multiple images provided from videos. The spatial processing unit uses three stages: (1) segmentation; (2) initial type, pose, and geometry (ITPG) estimation; and (3) refined type, pose, and geometry (RTPG) calculation. The image segmentation module files all the tools in an image and isolates them from the background. For this, the system uses edge-detection and thresholding to find the pixels that are part of a tool. After the pixels are identified, nearby pixels are grouped into blobs. These blobs represent the potential tools in the image and are the product of the segmentation algorithm. The second module uses matched filtering (or template matching). This approach is used for condensing synthetic images using an image subspace that captures key information. Three degrees of orientation, three degrees of position, and any number of degrees of freedom in geometry change are included. To do this, a template-matching framework is applied. This framework uses an off-line system for calculating template images, measurement images, and the measurements of the template images. These results are used online to match segmented tools against the templates. The final module is the RTPG processor. Its role is to find the exact states of the tools given initial conditions provided by the ITPG module. The requirement that the initial conditions exist allows this module to make use of a local search (whereas the ITPG module had global scope). To perform the local search, 3D model matching is used, where a synthetic image of the object is created and compared to the sensed data. The availability of low-cost PC graphics hardware allows rapid creation of synthetic images. In this approach, a function of orientation, distance, and articulation is defined as a metric on the difference between the captured image and a synthetic image with an object in the given orientation, distance, and articulation. The synthetic image is created using a model that is looked up in an object-model database. A composable software architecture is used for implementation. Video is first preprocessed to remove sensor anomalies (like dead pixels), and then is processed sequentially by a prioritized list of tracker-identifiers.

English, James↗
NASA NTRS2019

Spectrally Resolved Synthetic Aperture Imaging Interferometer: Final Report of NASA Innovative Advanced Concepts - Phase 1 Study

The Spectrally Resolved Synthetic-Aperture Imaging Interferometer (SRSAII) is a system proposed to provide high-resolution and high-sensitivity measurements of astronomical objects. SRSAII uses long baseline interferometric methods to achieve the resolution and low-noise, high time-precision detection to achieve the sensitivity. The primary goal of the SRSAII study was to lay out a framework for using new optical physics technologies to directly resolve, both spatially and spectrally, the disk of an exoplanet. In addition to the ambitious goal of directly resolving an exoplanet, the SRSAII team also sought to identify science opportunities achievable with intermediate system configurations which may offer resolution significantly higher than the current state of the art, but insufficient for direct resolution of an exoplanetary disk. An operational SRSAII system can function with essentially arbitrarily large baselines, achieving correspondingly high angular resolution. The primary limitation occurs in the system sensitivity, which became the major technical focus for study. In this report, we compare the predicted performance (sensitivity in SNR (Signal-to-Noise Ratio) along with angular resolution) of three interferometric techniques: direct detection (also known as homodyne interferometry), multi-channel intensity interferometry (using the Hanbury Brown and Twiss effect), and multi-channel heterodyne interferometry (using an optical frequency comb as a local oscillator). Additionally, quantum-assisted interferometry is also explored as a prospective enhancement of established methods. This report presents a survey of the technologies that enable the SRSAII techniques - optical frequency combs, single photon detectors, and photonic integrated circuits. These technologies are the basis of methods critical to SRSAII's success: precision timing, length and frequency metrology, sensitive photodetection, fine-scale wavelength filtering, and dense multi-channel operation. Lastly, we give some notional performance metrics and propose some possible experimental observations.

High Resolultion↗
NASA NTRS2011

Global Assimilation of Multi-Sensor Snow Observations for Improved Characterization of Snow Processes

Snow conditions on the land surface are recognized to be key components of the global hydrological cycle as they play a critical role in the determination of local and regional climate. In many mid-latitude and high-latitude regions, the seasonal water storage and associated spring snowmelt dominate the local hydrology. The contribution to the runoff and moisture conditions from snow is vital in supporting agriculture and in determining water resources management practices. Consequently, accurate characterization of snow properties becomes important for both end-use applications and weather and climate research. Recently a joint effort between the u.S. Air Force and NASA has enabled a blended, multi-sensor snow product known as the AFWA NASA Snow Algorithm (ANSA). This global snow dataset has been generated by utilizing the Earth Observation System (EOS) Moderate Resolution Imaging Spectroradiometer (MODIS) and Advanced Microwave Scanning Radiometer for EOS (AMSR-E) datasets. ANSA product includes estimates of snow cover extent, snow water equivalent (SWE) and SWE-derived snow depth fields. The MODIS-based products enable snow cover mappings under cloud-free conditions whereas the passive microwave data from AMSR-E provides measurements under cloudy conditions. These remotely-sensed snow observations are further augmented with the information from ground-based snow measurements through data fusion techniques. The resulting ANSA products are employed in the NASA Land Information System (LIS) data assimilation framework, which provides a comprehensive environment for integrating community land surface models, ground and satellite-based observations, and ensemble-based data assimilation tools. LIS incorporates the multisensor ANSA snow retrievals with the land surface model estimates to generate spatially and temporally continuous estimates of snow states, through data assimilation. A suite of experiments to assimilate ANSA snow cover, SWE and snow depth estimates with different land surface models in LIS are conducted and the resulting estimates of snow conditions are evaluated against a number of in-situ observational datasets, over several regions of the world. These evaluations are used to compare and contrast the advantages and disadvantages of these multi-sensor snow observations.

Kumar, Sujay↗
NASA NTRS2011

Overview of NASA's Carbon Monitoring System Flux-Pilot Project

NASA's space-based observations of physical, chemical and biological parameters in the Earth System along with state-of-the-art modeling capabilities provide unique capabilities for analyses of the carbon cycle. The Carbon Monitoring System is developing an exploratory framework for detecting carbon in the environment and its changes, with a view towards contributing to national and international monitoring activities. The Flux-Pilot Project aims to provide a unified view of land-atmosphere and ocean-atmosphere carbon exchange, using observation-constrained models. Central to the project is the application of NASA's satellite observations (especially MODIS), the ACOS retrievals of the JAXA-GOSAT observations, and the "MERRA" meteorological reanalysis produced with GEOS-S. With a primary objective of estimating uncertainty in computed fluxes, two land- and two ocean-systems are run for 2009-2010 and compared with existing flux estimates. An transport model is used to evaluate simulated CO2 concentrations with in-situ and space-based observations, in order to assess the realism of the fluxes and how uncertainties in fluxes propagate into atmospheric concentrations that can be more readily evaluated. Finally, the atmospheric partial CO2 columns observed from space are inverted to give new estimates of surface fluxes, which are evaluated using the bottom-up estimates and independent datasets. The focus of this presentation will be on the science goals and current achievements of the pilot project, with emphasis on how policy-relevant questions help focus the scientific direction. Examples include the issue of what spatio-temporal resolution of fluxes can be detected from polar-orbiting satellites and whether it is possible to use space-based observations to separate contributions to atmospheric concentrations of (say) fossil-fuel and biological activity

Pawson, Steven↗
NASA NTRS2013

Mission Data System Java Edition Version 7

The Mission Data System framework defines closed-loop control system abstractions from State Analysis including interfaces for state variables, goals, estimators, and controllers that can be adapted to implement a goal-oriented control system. The framework further provides an execution environment that includes a goal scheduler, execution engine, and fault monitor that support the expression of goal network activity plans. Using these frameworks, adapters can build a goal-oriented control system where activity coordination is verified before execution begins (plan time), and continually during execution. Plan failures including violations of safety constraints expressed in the plan can be handled through automatic re-planning. This version optimizes a number of key interfaces and features to minimize dependencies, performance overhead, and improve reliability. Fault diagnosis and real-time projection capabilities are incorporated. This version enhances earlier versions primarily through optimizations and quality improvements that raise the technology readiness level. Goals explicitly constrain system states over explicit time intervals to eliminate ambiguity about intent, as compared to command-oriented control that only implies persistent intent until another command is sent. A goal network scheduling and verification process ensures that all goals in the plan are achievable before starting execution. Goal failures at runtime can be detected (including predicted failures) and handled by adapted response logic. Responses can include plan repairs (try an alternate tactic to achieve the same goal), goal shedding, ignoring the fault, cancelling the plan, or safing the system.

Reinholtz, William K.↗
NASA NTRS2019

Differences Between OCO‐2 and GOME‐2 SIF Products From a Model‐Data Fusion Perspective

Space-borne retrievals of solar-induced chlorophyll fluorescence (SIF) over land surfaces have recently become a resource for studying and quantifying the broad scale dynamics of gross carbon uptake (gross primary productivity—GPP) across ecosystems. To prepare for the assimilation of SIF data in terrestrial biosphere models, we examine how differences between SIF products (due to differences in acquisition characteristics and processing chain) may affect the optimization of model parameters and the resultant GPP estimate. We compare recent daily mean SIF products (one from the Orbiting Carbon Observatory-2 [OCO-2] and two from the Global Ozone Monitoring Experiment–2 [GOME-2], GlobFluo [GF] and NASA-v28 [N28], missions), averaged at 0.5° × 0.5° spatial resolution and 16-day temporal resolution, at the biome level. Phase differences between these products are relatively small. A first-order correction of the difference in spectral sampling between the two instruments shows that OCO-2 and N28 are consistent in terms of magnitude and amplitude, while GF is twice as large as the others. Using a bias-blind toy data assimilation framework, we analyze how biases between SIF products, and between model and products, can be partially alleviated by optimizing the slope and intercept parameters of a linear GPP-SIF operator. As observation biases can transfer to biases in other optimized process-based parameters and to modeled carbon fluxes— thereby resulting in unidentified inaccurate parameter values—we argue that potential SIF biases should be treated cautiously in real-world experiments in order to achieve realistic and reliable future simulations.

Gross primary production↗
NASA NTRS2020

Towards a Soil Moisture Drought Monitoring System for South Korea

The Korea Land Data Assimilation System (KLDAS) has been established for agricultural drought (i.e. soil moisture deficit) monitoring in South Korea, running the Noah-MP land surface model within the NASA Land Information System (LIS) framework with the added value of local precipitation forcing dataset and soil texture maps. KLDAS soil moisture is benchmarked against three global products: the Global Land Data Assimilation System (GLDAS), the Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System (FLDAS), and the European Space Agency Climate Change Initiative (ESA CCI) satellite product. The evaluation is performed using in situ measurements for 2013–2015 and one month standardized precipitation index (SPI-1) for 1982–2016, focusing on four major river basins in South Korea. The KLDAS outperforms all benchmark products in capturing soil moisture states and variability at a basin scale. Compared to GLDAS and FLDAS products, the EAS CCI product is not feasible for long term agricultural monitoring due to lower data quality for early periods (1979–1991) of soil moisture estimates. KLDAS shows that the most recent 2015 drought event leads to highest drought areas in the Han and Geum River basins in the past 35 years. This work supports KLDAS as an effective agricultural drought monitoring system to provide continuous regional high-resolution soil moisture estimates in South Korea.

Agricultural drought↗
NASA NTRSDate not supplied

Calorimeter Heat Flux Trends in NASA’s Subscale Rotating Detonation Rocket Engine

A calorimeter-style rotating detonation rocket engine (RDRE) outer chamber body was designed, additively manufactured in GRCop-42, and hot-fire tested in test cell 105 at NASA Marshall Space Flight Center (MSFC) in Huntsville, AL in August 2024. Steady-state, spatially resolved heat flux and chamber pressure were measured at 13 and 9 locations from the injector face, respectively, for a variety of test conditions and hardware configurations with gaseous methane and oxygen propellants. The 2-in. diameter highly instrumented design, enabled by metal additive manufacturing (AM), allowed for simultaneous measurement of heat flux and chamber pressure through 44 long duration hot-fire tests without failure. Of the 44 tests, only 3 of the tests featured chamber pressures below 100 psia and are discussed in this work. Heat flux trends for this subscale hardware are explored with respect to local propellant mass flux for several different injectors, chamber lengths, and chamber “subsonic” area ratios (contraction ratios). Results show that for increasing chamber pressure, a reduced amount of energy per kilogram of propellant is transferred to the wall. Switching injectors affects the near-face heat flux and chamber pressure profiles. Chamber length does not noticeably affect the heat flux profile but increases bulk heat load. A subsonic area ratio greater than 1 reduces heat losses to the wall compared to a straight annulus case. Equivalence ratio shift did not significantly affect heat flux. Computational fluid dynamics (CFD) and conjugate heat transfer (CHT) analyses were performed to delineate 3-D heat transfer and coolant mass flow maldistribution effects and create a calorimeter transfer function to transform heat flux data and mitigate the profile distortions. Additional CFD/CHT simulations were performed using experimental data as boundary conditions to assess local nucleate boiling propensity during testing and to assess projected hot wall temperatures for future fatigue assessment. Vapor fractions were observed locally for several cases. It is anticipated that this effort will provide a common framework for coolant system design/analysis in calorimeter systems for rocket-based and air-breathing combustors, ensuring greater repeatability in calorimetry measurements across the research community.

Joseph Hernandez-McCloskey↗
NASA NTRS1999

Bubble Generation in a Flowing Liquid Medium and Resulting Two-Phase Flow in Microgravity

The present investigation reports a study of bubble generation under reduced gravity conditions, using both a co-flow and a cross-flow configuration. This study may be used in the conceptual design of a space-based thermal management system. Ensuing two-phase flow void fraction can be accurately monitored using a single nozzle gas injection system within a continuous liquid flow conduit, as utilized in the present investigation. Accurate monitoring of void fraction leads to precise control of heat and mass transfer coefficients related to a thermal management system; hence providing an efficient and highly effective means of removing heat aboard spacecraft or space stations. Our experiments are performed in parabolic flight aboard the modified DC-9 Reduced Gravity Research Aircraft at NASA Lewis Research Center, using an air-water system. For the purpose of bubble dispersion in a flowing liquid, we use both a co-flow and a cross-flow configuration. In the co-flow geometry, air is introduced through a nozzle in the same direction with the liquid flow. On the other hand, in the cross-flow configuration, air is injected perpendicular to the direction of water flow, via a nozzle protruding inside the two-phase flow conduit. Three different flow conduit (pipe) diameters are used, namely, 1.27 cm, 1.9 cm and 2.54 cm. Two different ratios of nozzle to pipe diameter (D(sub N))sup * are considered, namely (D(sub N))sup * = 0.1 and 0.2, while superficial liquid velocities are varied from 8 to 70 cm/s depending on flow conduit diameter. It is experimentally observed that by holding all other flow conditions and geometry constant, generated bubbles decrease in size with increase in superficial liquid velocity. Detached bubble diameter is shown to increase with air injection nozzle diameter. Likewise, generated bubbles grow in size with increasing pipe diameter. Along the same lines, it is shown that bubble frequency of formation increases and hence the time to detachment of a forming bubble decreases, as the superficial liquid velocity is in-creased. Furthermore, it is shown that the void fraction of the resulting two-phase flow increases with volumetric gas flow rate Q(sub d), pipe diameter and gas injection nozzle diameter, while they decrease with surrounding liquid flow. The important role played by flowing liquid in detaching bubbles in a reduced gravity environment is thus emphasized. We observe that the void fraction can be accurately controlled by using single nozzle gas injection, rather than by employing multiple port injection, since the later system gives rise to unpredictable coalescence of adjacent bubbles. It is of interest to note that empirical bubble size and corresponding void fraction are somewhat smaller for the co-flow geometry than the cross-flow configuration at similar flow conditions with similar pipe and nozzle diameters. In order to supplement the empirical data, a theoretical model is employed to study single bubble generation in the dynamic (Q(sub d) = 1 - 1000 cu cm/s) and bubbly flow regime within the framework of the co-flow configuration. This theoretical model is based on an overall force balance acting on the bubble during the two stages of generation, namely the expansion and the detachment stage. Two sets of forces, one aiding and the other inhibiting bubble detachment are identified. Under conditions of reduced gravity, gas momentum flux enhances, while the surface tension force at the air injection nozzle tip inhibits bubble detachment. In parallel, liquid drag and inertia can act as both attaching and detaching forces, depending on the relative velocity of the bubble with respect to the surrounding liquid. Predictions of the theoretical model compare well with our experimental results. However, at higher superficial liquid velocities, as the bubble loses its spherical form, empirical bubble size no longer matches the theoretical predictions. In summary, we have developed a combined experimental and theoretical work, which describes the complex process of bubble generation and resulting two-phase flow in a microgravity environment. Results of the present study can be used in a wide range of space-based applications, such as thermal energy and power generation, propulsion, cryogenic storage and long duration life support systems, necessary for programs such as NASA's Human Exploration for the Development of Space (HEDS).

Pais, S. C.↗