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Software reliability through fault-avoidance and fault-tolerance

Strategies and tools for the testing, risk assessment and risk control of dependable software-based systems were developed. Part of this project consists of studies to enable the transfer of technology to industry, for example the risk management techniques for safety-concious systems. Theoretical investigations of Boolean and Relational Operator (BRO) testing strategy were conducted for condition-based testing. The Basic Graph Generation and Analysis tool (BGG) was extended to fully incorporate several variants of the BRO metric. Single- and multi-phase risk, coverage and time-based models are being developed to provide additional theoretical and empirical basis for estimation of the reliability and availability of large, highly dependable software. A model for software process and risk management was developed. The use of cause-effect graphing for software specification and validation was investigated. Lastly, advanced software fault-tolerance models were studied to provide alternatives and improvements in situations where simple software fault-tolerance strategies break down.

Vouk, Mladen A.↗

Design of a Formation of Earth-Orbiting Satellites: The Auroral Lites Mission

The National Aeronautics and Space Administration (NASA) Goddard Space Flight Center (GSFC) has proposed a set of spacecraft flying in close formation around the Earth in order to measure the behavior of the auroras. The mission, named Auroral Lites, consists of four spacecraft configured to start at the vertices of a tetrahedron, flying over three mission phases. During the first phase, the distance between any two spacecraft in the formation is targeted at 10 kilometers (km). The second mission phase is much tighter, requiring satellite interrange spacing targeted at 500 meters. During the final phase of the mission, the formation opens to a nominal 100-km interrange spacing. In this paper, we present the strategy employed to initialize and model such a close formation during each of these phases. The analysis performed to date provides the design and characteristics of the reference orbit, the evolution of the formation during Phases I and II, and an estimate of the total mission delta-V budget. AI Solutions' mission design tool, FreeFlyer, was used to generate each of these analysis elements. The tool contains full force models, including both impulsive and finite duration maneuvers. Orbital maintenance can be fully modeled in the system using a flexible, natural scripting language built into the system. In addition, AI Solutions is in the process of adding formation extensions to the system facilitating mission analysis for formations like Auroral Lites. We will discuss how FreeFlyer is used for these analyses.

Hametz, Mark E.↗

Design of a Formation of Earth Orbiting Satellites: The Auroral Lites Mission

The National Aeronautics and Space Administration (NASA) Goddard Space Flight Center (GSFC) has proposed a set of spacecraft flying in close formation around the Earth in order to measure the behavior of the auroras. The mission, named Auroral Lites, consists of four spacecraft configured to start at the vertices of a tetrahedron, flying over three mission phases. During the first phase, the distance between any two spacecraft in the formation is targeted at 10 kilometers (km). The second mission phase is much tighter, requiring satellite interrange spacing targeted at 500 meters. During the final phase of the mission, the formation opens to a nominal 100-km interrange spacing. In this paper, we present the strategy employed to initialize and model such a close formation during each of these phases. The analysis performed to date provides the design and characteristics of the reference orbit, the evolution of the formation during Phases I and II, and an estimate of the total mission delta-V budget. AI Solutions' mission design tool, FreeFlyer(R), was used to generate each of these analysis elements. The tool contains full force models, including both impulsive and finite duration maneuvers. Orbital maintenance can be fully modeled in the system using a flexible, natural scripting language built into the system. In addition, AI Solutions is in the process of adding formation extensions to the system facilitating mission analysis for formations like Auroral Lites. We will discuss how FreeFlyer(R) is used for these analyses.

Hametz, Mark E.↗

A Geosynchronous Lidar System for Atmospheric Winds, Temperature, and Moisture Measurements

A geosynchronous Lidar would enable synoptic measurement of atmospheric winds; temperature; and moisture, which are key first-order variables of the Earth's weather equation. Simultaneous measurement of these parameters at fast revisit rates promises large advancements in our weather predictive skills. Such capabilities would: a) yield greatly improved initial conditions for models, b) make obsolete existing (discrete) measurement approaches which are both costly and cumbersome, and c) obviate the use of numerical techniques needed to correct data obtained using present methods. Additionally, simultaneous synoptic Lidar observations would lead to improvements in model parameters, and in our knowledge of small-scale weather processes. A Dial Lidar system could simultaneously measure winds, temperatures, and humidity through a combination of Doppler and Differential Absorption techniques. Also, such a system would provide basic aerosol (dry dust) measurement capabilities that could have an impact on Earth radiation budget measurements. On the technical side, a geosynchronous Lidar DAR system would require transmit optics of a few meters in diameter, a hundred meter diameter receive telescope, fineness of both optical systems scaled to the wavelength, and scanning for the transmit system. Potential technology issues include optical quality of large transmit and receive telescope optics, the large detector area needed, the transmit scanning system, signal detection (S/N ratio of detector system) for the extremely weak return signal at GEO, and power demands in the KW range.

Emmitt, Dave↗

Modeling and Analysis of Global and Regional Climate Change in Relation to Atmospheric Hydrologic Processes

This research was directed to the development and application of global isentropic modeling and analysis capabilities to describe hydrologic processes and energy exchange in the climate system, and discern regional climate change. An additional objective was to investigate the accuracy and theoretical limits of global climate predictability which are imposed by the inherent limitations of simulating trace constituent transport and the hydrologic processes of condensation, precipitation and cloud life cycles.

Johnson, Donald R.↗

Phase Transition in Dusty Plasmas: A Microphysical Description

Dust grains immersed in plasma discharges acquire a large negative charge and settle into a dust cloud at the edge of the sheath. In this region, the plasma ions stream toward the electrode at a velocity u approx. cs=(T(sub e)/m(sub i))(exp 1/2). Experimentally at sufficiently high gas pressure P, the random kinetic energy of the grains is damped by gas friction, and the grains are strongly coupled and self-organize into a crystalline configuration. For lower pressures despite the dissipation of grain kinetic energy to gas friction, the dust grains reach a steady-state kinetic temperature T(sub d) which is much larger than the temperature of any other component in the plasma. T(sub d) is so large that the dust acts like a fluid. We have used the dynamically shielded dust (DSD) model to simulate these physical processes. We find that the known experimental features are nicely reproduced in the simulations, and that additional features are revealed. In the figure we plot the variation of T(sub d) as P is continuously varied in a DSD code run. A marked difference is evident between the critical pressure P(sub m) for the melting transition as P is decreased, and the critical pressure P(sub c) for the condensation transition as P is increased. For P(sub m) is less than P is less than P(sub c), mixed phase states are seen. This hysteresis occurs because the instability which triggers melting is different from the instability that heats the dust in the fluid phase and inhibits freezing. At low pressure, the dust is subject to a two-stream instability with the ions. This instability is responsible for the high temperature of the dust at low pressure. The basic physics underlying the melting transition has been elucidated in a series of papers. We are developing a first-principles analytic approach to the melting transition, which embodies the same physics that is present in the DSD code.

Joyce, Glenn↗

Flight Trajectory Prediction Based on Hybrid-Recurrent Networks

The development of future technologies for the National Airspace System (NAS) will be reliant on a new communications infrastructure capable of managing the limited available spectrum for communications among aircraft and ground systems. Emerging approaches to autonomous allocation of aviation spectrum mostlyrely on machine learning techniques, where 4D (longitude, latitude, altitude, time) trajectory prediction is an important data input to enable real-time resource allocation. This study explores and evaluates effective data sources and deep recurrent neural network techniques when determining flight trajectories. Specifically, data are collected and evaluated in a 100-day and 14-day period. Sources of data include NASA Sherlock Data Warehouse, MIT Lincoln Labs Corridor Integrated Weather Service (CIWS), and assorted NOAA weather datasets. Deep learning models for 4D predictions all utilize a hybrid-recurrent technique. A baseline model is considered via the convolutional-LSTM design from the existing literature. The modified design considers Gated Recurrent Units (GRU), Independently Recurrent Neural Networks (IndRNN), and stand-alone self-attention layers. Results indicatethe effectiveness of LSTM and GRUcells for state-of-the-art data processing (interpolation). Additionally, GRUs may be quickly trained with limited data, allowing for exacting improvements with optimizer selection. Attention mechanisms provide notable performance improvements to convolutional layers and may extend dimensional capabilities of a learning model. Finally, NOAA measurements provide only a supplemental value, requiring support from tailored measurements for Air Traffic Management.

Nathan Schimpf↗

Establishing and Maintaining the Digital Thread of Additively Manufactured Materials and Applications

Additive Manufacturing (AM) and Integrated Computational Materials Engineering (ICME) are complementary enabling technologies for design and manufacturing of “fit-for-purpose” materials. Both technologies will impact rapid material design, reduction in cost- and time-to-market for new applications, and discovery and implementation of new materials. An ICME approach to design, however, requires experimentally validated material models at multiple length and time scales, an integrated framework that can connect analysis tools with one another to ensure the digital thread of an application is maintained, and the manufacturing (e.g., AM) capability to leverage processing-structure-property-performance (PSPP) relationships to achieve spatially varying material properties where desired. AM enables the implementation of the design of an optimized, spatially varying microstructure through careful selection of the processing parameters used during an additively manufactured build. In order to establish these PSPP relations, a large amount of data is necessary, and that data must be properly captured, analyzed and maintained in an information management system that can establish the required traceability between various aspects of the design process to ensure an application’s digital thread is maintained (from design to end of life). Such an information management system must be able to capture feedstock material pedigree, resulting microstructure from various build parameters, subsequent mechanical properties derived from testing, developed material models, and enable spatial variations in material assignment in an engineering application. Furthermore, the information management system should be easily integrated with traditionally engineered materials in a single, centralized platform to enable an ICME optimization tool to explore both types of manufacturing processes. At NASA GRC, a robust, 21st century materials information management system has been previously developed with a focus towards enabling ICME. In this work, GRC’s ICME schema is extended to accommodate additively manufactured materials, enabling storage of both traditionally and additively manufactured materials in the same construct. The methodology for properly capturing additively manufactured materials across the entire material lifecycle is presented, following the previously established database best practices, as a potential framework for establishing PSPP relationships for additively manufactured materials and applying them to engineering applications.

Data management↗

Enabling the Broader Use of MOOSE for Nuclear Energy and Other Simulation

This Final Scientific and Technical Report summarizes work performed under the Phase IIA SBIR project “Enabling the Broader Use of MOOSE for Nuclear Energy and Other Simulation” (DE-SC0020906) from August 2023 through August 2025. The objective of the Phase IIA effort was to mature and harden capabilities developed during Phase II, with the goal of enabling practical interoperability between Coreform’s isogeometric analysis (IGA) technologies and the Multiphysics Object-Oriented Simulation Environment (MOOSE), while improving robustness, performance, and scalability for complex, nuclear-relevant geometries. Over the course of Phase IIA, the project established and validated an extraction-based interoperability pathway between Coreform tools and MOOSE. A combined mesh and matrix format was defined collaboratively with MOOSE developers and integrated into the solver, enabling standard MOOSE workflows to operate on data exported from Coreform’s IGA and Flex Representation Method (FRM) pipelines. Early demonstrations validated architectural compatibility using linear solid mechanics problems, while later efforts focused on benchmark testing and external use. By the end of the project period, engineers at BWXT were able to independently set up and execute a simulation using the Coreform–MOOSE workflow and provide direct feedback that informed further refinement. In parallel, substantial effort was devoted to improving the robustness of trimmed U-spline construction for complex CAD geometries. A growing test suite of nuclear-relevant models was compiled through collaboration with multiple stakeholders and used to drive extensive bug fixing and reliability improvements. These efforts resulted in improved robustness and performance, including the addition of fallback capabilities that enhance reliability when the underlying commercial CAD kernel fails. Performance-oriented work progressed later in the project, with the development and demonstration of methods to decompose complex geometries into structured subregions and updated data representations to support more efficient solver processing. Additionally, extensive enhancements to threadsafe parallel data structures and trimming operations established a foundation for scalable processing of large assemblies. Collaboration with Sandia National Laboratories on the SGM geometric modeling kernel advanced to a functioning interface test case, positioning the workflow for future kernel integration. Overall, the Phase IIA effort successfully transitioned the project from architectural proof-of-concept to externally exercised, solver-integrated capability, while clarifying remaining technical challenges related to standardization, performance optimization, and kernel integration.

42 ENGINEERING↗

Technical Note: AQMEII4 Activity 1: Evaluation of Wet and Dry Deposition Schemes as an Integral Part of Regional-scale Air Quality Models

We present in this technical note the research protocol for phase 4 of the Air Quality Model Evaluation International Initiative (AQMEII4). This research initiative is divided into two activities, collectively having three goals: (i) to define the current state of the science with respect to representations of wet and especially dry deposition in regional models, (ii) to quantify the extent to which different dry deposition parameterizations influence retrospective air pollutant concentration and flux predictions, and (iii) to identify, through the use of a common set of detailed diagnostics, sensitivity simulations, model evaluation, and reduction of input uncertainty, the specific causes for the current range of these predictions. Activity 1 is dedicated to the diagnostic evaluation of wet and dry deposition processes in regional air quality models (described in this paper), and Activity 2 to the evaluation of dry deposition point models against ozone flux measurements at multiple towers with multiyear observations (to be described in future submissions as part of the special issue on AQMEII4). The scope of this paper is to present the scientific protocols for Activity 1, as well as to summarize the technical information associated with the different dry deposition approaches used by the participating research groups of AQMEII4. In addition to describing all common aspects and data used for this multi-model evaluation activity, most importantly, we present the strategy devised to allow a common process-level comparison of dry deposition obtained from models using sometimes very different dry deposition schemes. The strategy is based on adding detailed diagnostics to the algorithms used in the dry deposition modules of existing regional air quality models, in particular archiving diagnostics specific to land use–land cover (LULC) and creating standardized LULC categories to facilitate cross-comparison of LULC-specific dry deposition parameters and processes, as well as archiving effective conductance and effective flux as means for comparing the relative influence of different pathways towards the net or total dry deposition. This new approach, along with an analysis of precipitation and wet deposition fields, will provide an unprecedented process-oriented comparison of deposition in regional air quality models. Examples of how specific dry deposition schemes used in participating models have been reduced to the common set of comparable diagnostics defined for AQMEII4 are also presented.

Air Quality Model Evaluation International Initiat↗

The Global Ocean Observing System

A Global Ocean Observing System (GOOS) should be established now with international coordination (1) to address issues of global change, (2) to implement operational ENSO forecasts, (3) to provide the data required to apply global ocean circulation models, and (4) to extract the greatest value from the one billion dollar investment over the next ten years in ocean remote sensing by the world's space agencies. The objectives of GOOS will focus on climatic and oceanic predictions, on assessing coastal pollution, and in determining the sustainability of living marine resources and ecosystems. GOOS will be a complete system including satellite observations, in situ observations, numerical modeling of ocean processes, and data exchange and management. A series of practical and economic benefits will be derived from the information generated by GOOS. In addition to the marine science community, these benefits will be realized by the energy industries of the world, and by the world's fisheries. The basic oceanic variables that are required to meet the oceanic and predictability objectives of GOOS include wind velocity over the ocean, sea surface temperature and salinity, oceanic profiles of temperature and salinity, surface current, sea level, the extent and thickness of sea ice, the partial pressure of CO2 in surface waters, and the chlorophyll concentration of surface waters. Ocean circulation models and coupled ocean-atmosphere models can be used to evaluate observing system design, to assimilate diverse data sets from in situ and remotely sensed observations, and ultimately to predict future states of the system. The volume of ocean data will increase enormously over the next decade as new satellite systems are launched and as complementary in situ measuring systems are deployed. These data must be transmitted, quality controlled, exchanged, analyzed, and archived with the best state-of-the-art computational methods.

Kester, Dana↗

Conformal Ablative Thermal Protection System for Planetary and Human Exploration Missions: An Update of the Technology Maturation Effort

This presentation will update the community on the development of conformal ablative TPS. As described at IPPW-10, in FY12, the CA-TPS element focused on establishing materials requirements based on MSL-type and COTS Low Earth orbit (LEO) conditions (q 250 Wcm2) to develop and deliver a conformal ablative TPS. This involved downselecting, manufacturing and testing two of the best candidate materials, demonstrating uniform infiltration of resins into baseline 2-cm thick carbon felt, selecting a primary conformal material formulation based on novel arc jet and basic material properties testing, developing and demonstrating instrumentation for felt-based materials and, based on the data, developing a low fidelity material response model so that the conformal ablator TPS thickness for missions could be established. In addition, the project began to develop Industry Partnerships. Since the nominal thickness of baseline carbon felts was only 2-cm, a partnership with a rayon felt developer was made in order to upgrade equipment, establish the processes required and attempt to manufacture 10-cm thick white goods. A partnership with a processing house was made to develop the methodology to carbonize large pieces of the white goods into 7.5-cm thick carbon felt.In FY13, more advanced testing and modeling of the downselected conformal material was performed. Material thermal properties tests and structural properties tests were performed. The first 3 and 4-point bend tests were performed on the conformal ablator as well as PICA for comparison and the conformal ablator had outstanding behavior compared to PICA. Arc jet testing was performed with instrumented samples of both the conformal ablator and standard PICA at heating rates ranging from 40 to 400 Wcm2 and shear as high as 600 Pa. The results from these tests showed a remarkable improvement in the thermal penetration through the conformal ablator when compared to PICAs response. The data from these tests were used to develop a mid-fidelity thermal response model. Additional arc jet testing in the same conditions on various seam designs were very successful in showing that the material could be joined with a minimum of adhesive and required no complicated gap and gap filler design for installation. In addition, the partnership with industry to manufacture thicker rayon felt was very successful. The vendor made a 2-m wide by 30-m long sample of 10-cm thick rayon felt. When carbonized, the resulting thickness was over 7.5-cm thick, nearly 4 times the thickest off-the-shelf carbon felt. In FY14, the project has initiated a partnership with another vendor to begin the scale-up manufacturing effort. This year, the vendor will duplicate the process and manufacture at the current scale for comparison with NASA-processed materials. Properties testing and arc jet testing will be performed on the vendor-processed materials. Planning for manufacturing large, 1-m x 1-m, panels will begin as well. In FY15, the vendor will then manufacture large panels and the project will build a 2-m x 2-m Manufacturing Demonstration Unit (MDU).

thermal protection systems↗

Symbolic Processing Combined with Model-Based Reasoning

A computer program for the detection of present and prediction of future discrete states of a complex, real-time engineering system utilizes a combination of symbolic processing and numerical model-based reasoning. One of the biggest weaknesses of a purely symbolic approach is that it enables prediction of only future discrete states while missing all unmodeled states or leading to incorrect identification of an unmodeled state as a modeled one. A purely numerical approach is based on a combination of statistical methods and mathematical models of the applicable physics and necessitates development of a complete model to the level of fidelity required for prediction. In addition, a purely numerical approach does not afford the ability to qualify its results without some form of symbolic processing. The present software implements numerical algorithms to detect unmodeled events and symbolic algorithms to predict expected behavior, correlate the expected behavior with the unmodeled events, and interpret the results in order to predict future discrete states. The approach embodied in this software differs from that of the BEAM methodology (aspects of which have been discussed in several prior NASA Tech Briefs articles), which provides for prediction of future measurements in the continuous-data domain.

James, Mark↗

Experimental and Theoretical Thermokinetic Analysis of the Na 3 VO 4 –CO 2 Reaction System under Different Physicochemical Conditions

Sodium vanadate (Na 3 VO 4 ) was synthesized, structural and microstructurally characterized as well as tested as possible carbon dioxide (CO 2 ) captor through thermodynamic calculations in addition to thermogravimetric dynamic and isothermal analyses. Ceramic structural characterization evidenced the formation of the Na 3 VO 4 crystal phase, while microstructural features evidenced dense agglomerates with a poor specific surface area, although synthesis temperature (600 °C) was not as high as that for other sodium ceramics. Na 3 VO 4 was investigated for the CO 2 capture process through dynamic and isothermal experiments, in the presence or absence of oxygen. All these experiments showed that Na 3 VO 4 possesses interesting CO 2 capture properties in a specific temperature range (520 and 600 °C). Isothermal products characterization allowed to elucidate the reaction pathway, implying the Na 4 V 2 O 7 formation, as possible reactive intermediate. In fact, reaction path evolution was supported with theoretical thermodynamic data. Moreover, the kinetic analysis, performed using the Avrami-Erofeev mathematical model and subsequent thermodynamic data obtention, probed the positive influence of the temperature, in both CO 2 superficial and bulk chemical sorption processes, while oxygen addition did not enhance the superficial process. Additionally, as it would be expected, kinetics were enhanced as a function of the CO 2 concentration.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

An Update to a Conformal Ablative Thermal Protection System for Planetary and Human Exploration Missions

As described at IPPW-10, in FY12, the CA-TPS element focused on establishing materials requirements based on MSL-type and COTS Low Earth orbit (LEO) conditions (q 250 Wcm2) to develop and deliver a conformal ablative TPS. This involved down selecting, manufacturing and testing two of the best candidate materials, demonstrating uniform infiltration of resins into baseline 2-cm thick carbon felt, selecting a primary conformal material formulation based on novel arc jet and basic material properties testing, developing and demonstrating instrumentation for felt-based materials and, based on the data, developing a low fidelity material response model so that the conformal ablator TPS thickness for missions could be established. In addition, the project began to develop Industry Partnerships. Since the nominal thickness of baseline carbon felts was only 2-cm, a partnership with a rayon felt developer was made in order to upgrade equipment, establish the processes required and attempt to manufacture 10-cm thick white goods. A partnership with a processing house was made to develop the methodology to carbonize large pieces of the white goods into 7.5-cm thick carbon felt. In FY13, more advanced testing and modeling of the down selected conformal material was performed. Material thermal properties tests and structural properties tests were performed. The first 3 and 4-point bend tests were performed on the conformal ablator as well as PICA for comparison and the conformal ablator had outstanding behavior compared to PICA. Arc jet testing was performed with instrumented samples of both the conformal ablator and standard PICA at heating rates ranging from 40 to 400 Wcm2 and shear as high as 600 Pa. The results from these tests showed a remarkable improvement in the thermal penetration through the conformal ablator when compared to PICAs response. The data from these tests were used to develop a mid-fidelity thermal response model. Additional arc jet testing in the same conditions on various seam designs were very successful in showing that the material could be joined with a minimum of adhesive and required no complicated gap and gap filler design for installation. In addition, the partnership with industry to manufacture thicker rayon felt was very successful. The vendor made a 2-m wide by 30-m long sample of 10-cm thick rayon felt. When carbonized, the resulting thickness was over 7.5-cm thick, nearly 4 times the thickest off-the-shelf carbon felt. In FY14, the project has initiated a partnership with another vendor to begin the scale-up manufacturing effort. This year, the vendor will duplicate the process and manufacture at the current scale for comparison with NASA-processed materials. Properties testing and arc jet testing will be performed on the vendor-processed materials. Planning for manufacturing large, 1-m x 1-m, panels will begin as well. In FY15, the vendor will then manufacture large panels and the project will build a 2-m x 2-m Manufacturing Demonstration Unit (MDU).

Ablative materials↗

Leveraging machine learning to enhance aerosol classification using Single-Particle Mass Spectrometry

Advancing automated classification of atmospheric aerosols from Single-Particle Mass Spectrometry (SPMS) data remains challenging due to overlapping ion signatures, compositional diversity, and limited labeled data. This study evaluates supervised and semi-supervised learning frameworks to enhance aerosol identification by jointly leveraging labeled and unlabeled spectra. Four models were compared: a supervised Support Vector Machine (SVM), a self-training SVM, a stacked autoencoder classifier, and a stacked autoencoder trained using a temporal-ensembling Mean Teacher approach. All models achieved high and stable accuracies (90.0 %–91.1 %), surpassing previous results on the same dataset (87 %) and matching the performance of state-of-the-art deep learning methods. Despite small global metric differences (≤ 1 %), semi-supervised variants yielded up to 5 %–10 % improvements for compositionally rare particle types – such as soot (0.77 % of spectra, F1-score: 0.93–0.97) and hazelnut pollen (0.98 % of spectra, F1-score: 0.97–1.00) – equating to roughly ∼ 187 additional correctly classified spectra. These gains are scientifically significant, as such rare particles exert disproportionate influence on radiative absorption and ice nucleation processes; their improved detection reduces modeled uncertainties in aerosol absorption optical depth and mixed-phase cloud ice nucleation rates. The models' residual misclassifications (≈ 9 %) largely arise from true spectral overlap among chemically adjacent species (e.g., Na- vs. K-feldspar, coated vs. uncoated feldspars), reflecting physical compositional continuity rather than algorithmic error. Collectively, these findings demonstrate that leveraging unlabeled data to learn robust spectral representations and refine classification enhances both fidelity and interpretability, bridging data-driven analysis with aerosol–climate process understanding.

54 ENVIRONMENTAL SCIENCES↗

Advances in automatic extraction of earth resources information from multispectral scanner data

The basis of spectral discrimination was briefly examined indicating sources of variability which tend to obscure the spectral attributes of the classes of interest. Spatial and temporal discrimination bases are also discussed. Automatic processing functions, techniques and methods, and equipment are discussed with emphasis on techniques and equipment required for operational large area surveys with satellite data. Techniques for carrying out major functions of preprocessing for signature extension, feature extraction, discrimination, display, and applications modeling were examined. A multiplicative and additive signature correction technique and a proportion estimation technique are discussed. The development of the multivariate interactive digital analysis system multispectral processor system which represents a breakthrough in cost effective high throughput processing for large area surveys from satellites and aircraft is reviewed. Applications and results are discussed briefly for agricultural crop inventories, environmental monitoring, and resources surveys from ERIM LANDSAT and EREP investigations to indicate the substantial progress achieved to date.

Erickson, J. D.↗

Numerical simulations of liquid jetting with solid inclusions

The dynamics of finite-sized particles in fluids, and their influence on the overall flow, are of great interest across several industrial, environmental, and medical fields. In the context of inkjet printing, the presence of solid inclusions can be either intentional, as in additive manufacturing, or unintentional, as in standard printing processes. These inclusions can strongly impact the jetting process, causing effects such as jet asymmetry, bubble entrapment, and the formation of satellite droplets. Understanding and controlling particle behavior is therefore essential, particularly to predict how and when particles are ejected over multiple jetting cycles. It is therefore critical to develop reliable models that allow for a deeper understanding of the complex interplay between particle and fluid during the whole printing process. To address this, we present a tailored implementation of the Color-Gradient multicomponent Lattice Boltzmann Method for fully resolved three-dimensional (3D) simulations of multicycle liquid jetting with particles. Our method supports realistic parameter settings aligned with industrial inkjet systems, and we provide both qualitative and quantitative validation against experimental data. Additionally, we introduce a simplified model based on the Stokes drag law, in which solid particles are represented as point particles and do not influence the fluid flow. Despite this limitation, the model offers a computationally efficient means to explore the vast parameter space typically encountered in industrial applications, allowing, e.g., identifying critical ejection regions and estimating the number of cycles required for particle release. These qualitative insights are valuable for guiding and complement fully two-way coupled simulations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗