SEARCH · Search NASA
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
An application test of the crop calendar portion of a corn (maize) stress indicator model developed by the early warning, crop condition assessment component of AgRISTARS was performed over the corn for grain producing regions of the U.S.S.R. during the 1980 crop year using real data. Performance of the crop calendar submodel was favorable; efficiency gains in meteorological data analysis time were on a magnitude of 85 to 90 percent.
The NEAMS Multiphysics Applications team aims at providing assessment of code useability and functionality for microreactor design and analyses, together with demonstration of their capabilities to properly capture the steady-state and time-dependent behavior of different microreactor concepts. In FY-24, significant progress was achieved in improving multi-physics models of several microreactors systems: HP-MR, GC-MR and KRUSTY. These efforts focused on solving more complex multiphysics problems enabled by enhanced tools capability, verifying and validating results obtained, providing feedback to developers for suggested improvements, and sharing these models to facilitate user training. A series of new multiphysics transients were completed on the HP-MR (using Griffin/BISON/Sockeye) with core startup transient, control drum inadvertent rotation accident, and hydrogen leakage from hydride moderator (also including SWIFT). On the GC-MR, a new full-core model was developed and analyzed through a series of new multiphysics (Griffin/BISON/SAM) transients to simulate moderator leakage (also including SWIFT), flow blockage and coolant depressurization. Additional and updated TRISO failure analyses were completed on the HP-MR unit-cell and GC-MR assembly models leveraging improved TRISO modeling capabilities. The amount of SiC failure following accidental transients at end-of-life was null. However, GC-MR assembly TRISO analysis highlighted Pd penetration rate can be problematic and may require design changes on the studied microreactor concept. The neutronics discrepancies observed on the KRUSTY model in previous years were resolved using hybrid set of Monte Carlo/Deterministic cross-sections. The multiphysics (Griffin neutronics / BISON thermal-mechanics) 15₵ insertion transient simulation displayed good agreement when comparing with experimental data. Initial modeling of the 30 ₵ reactivity insertion also displays promising results. Such close agreement provides important validation data that can be leveraged by the NEAMS program and by microreactor vendors to support licensing of their technology. Finally, important experience was gathered with the NEAMS tools leading to several user feedback shared with tools developers, especially with regards to MOOSE mesh generator and Griffin. This project led to many publications demonstrating modeling capabilities, and to three models shared on the Virtual Test Bed.
Abstract In porous media theory, upscaling techniques are fundamental to deriving rigorous Darcy‐scale models for flow and reactive transport in subsurface systems. Due to limitations in classical techniques, a number of ad hoc approaches have been proposed to address physical regimes in which reactive time scales are similar to, or faster than, diffusive time scales. In Part 1 of this two part series, we present a strategy for expanding the applicability of classical homogenization theory by generalizing the assumed closure form. We detail the implementation of this strategy on two reactive mass transport problems with moderately reactive physics. The strategy produces nontrivial homogenized models with emergent terms and effective parameters that couple reactive, diffusive, and advective transport. The differences in equation forms between the macroscopic and pore‐scale descriptions advise caution to further studies where the forms of macroscopic equations are assumed, as opposed to rigorously derived. Numerical validation is provided for each problem to show that the error estimates of homogenization theory are satisfied, and to justify the implemented strategy. In Part 2, the presented strategy is automated using symbolic computing to expedite its implementation.
Absorption of infrared radiation by various line and band models are briefly reviewed. Narrow band model relations for absorptance are used to develop 'exact' formulations for total absorption by four wide band models. Application of a wide band model to a particular gas largely depends upon the spectroscopic characteristic of the absorbing-emitting molecule. Seven continuous correlations for the absorption of a wide band model are presented and each one of these is compared with the exact (numerical) solutions of the wide band models. Comparison of these results indicate the validity of a correlation for a particular radiative transfer application. In radiative transfer analyses, use of continuous correlations for total band absorptance provides flexibilities in various mathematical operations.
Integrated modeling of spacecraft systems is a rapidly evolving area in which multidisciplinary models are developed to design and analyze spacecraft configurations. These models are especially important in the early design stages where rapid trades between subsystems can substantially impact design decisions. Integrated modeling is one of the cornerstones of two of NASA's planned missions in the Origins Program -- the Next Generation Space Telescope (NGST) and the Space Interferometry Mission (SIM). Common modeling tools for control design and opto-mechanical analysis have recently emerged and are becoming increasingly widely used. A discipline that has been somewhat less integrated, but is nevertheless of critical concern for high precision optical instruments, is thermal analysis and design. A major factor contributing to this mild estrangement is that the modeling philosophies and objectives for structural and thermal systems typically do not coincide. Consequently the tools that are used in these discplines suffer a degree of incompatibility, each having developed along their own evolutionary path. Although standard thermal tools have worked relatively well in the past. integration with other disciplines requires revisiting modeling assumptions and solution methods. Over the past several years we have been developing a MATLAB based integrated modeling tool called IMOS (Integrated Modeling of Optical Systems) which integrates many aspects of structural, optical, control and dynamical analysis disciplines. Recent efforts have included developing a thermal modeling and analysis capability, which is the subject of this article. Currently, the IMOS thermal suite contains steady state and transient heat equation solvers, and the ability to set up the linear conduction network from an IMOS finite element model. The IMOS code generates linear conduction elements associated with plates and beams/rods of the thermal network directly from the finite element structural model. Conductances for temperature varying materials are accommodated. This capability both streamlines the process of developing the thermal model from the finite element model, and also makes the structural and thermal models compatible in the sense that each structural node is associated with a thermal node. This is particularly useful when the purpose of the analysis is to predict structural deformations due to thermal loads. The steady state solver uses a restricted step size Newton method, and the transient solver is an adaptive step size implicit method applicable to general differential algebraic systems. Temperature dependent conductances and capacitances are accommodated by the solvers. In addition to discussing the modeling and solution methods. applications where the thermal modeling is "in the loop" with sensitivity analysis, optimization and optical performance drawn from our experiences with the Space Interferometry Mission (SIM), and the Next Generation Space Telescope (NGST) are presented.
This paper documents the blind and post-blind analysis predictions for the 2023 Sandia Mechanics Challenge (SMC), which involved predicting the behavior of a threaded fastener joint structure subjected to shock loading. Utilizing repeat sets of fastener calibration data from various experimental configurations including tension, double shear, and joint tension, we developed a library of calibrated models which were propagated through the application model using the Discrete-Direct (DD) uncertainty quantification (UQ) approach. Although the initial blind predictions did not incorporate spare-sample processing to quantify fastener failure probabilities, the analyses yielded reasonable conclusions aligned with experimental results. In the post-blind analysis phase, we focused on enhancing the fidelity of the aluminum constitutive model and innovating the DD approach to obtain probabilistic predictions for fastener failure, particularly when quantities of interest (QoIs) approach their bounds. The improved aluminum model captures the behavior of the cantilever under shock loading more accurately, predicting both partial and complete cracks, although it tends to underpredict failure propagation. The enhanced DD approach facilitates probabilistic predictions that reflect the interdependent failure mechanisms of the fasteners and the cantilever, revealing that while certain fasteners are more likely to fail, the failure does not necessarily follow a progressive pattern. Overall, the post-blind analyses significantly improved the predictive capabilities of the model, providing valuable insights into the SMC application and establishing a robust foundation for informed engineering decisions. The methodology demonstrates a cost-effective and extensible approach suitable for a wide range of applications, highlighting the importance of uncertainty quantification to provide context for engineering decision making.
Inland waters receive large quantities of dissolved organic carbon (DOC) from soils and act as conduits for the lateral transport of this terrestrially derived carbon, ultimately storing, mineralizing, or delivering it to oceans. The lateral DOC flux plays a crucial role in the global carbon cycle, and numerous models have been developed to estimate the DOC export from different landscapes. We reviewed 34 published models and compared their characteristics to identify challenges in model applications and opportunities for future model development. We classified these models into three types: indicator-driven, hydrology-forced, and process-based DOC export simulation models. They differ mainly in their environmental inputs, simulation approaches for soil DOC production, leaching from soils to inland waters, and transit through inland waters. It is essential to consider landscape characteristics, climate conditions, available data, and research questions when selecting the most appropriate model. Given the substantial assumptions associated with these models, sufficient measurements are required to benchmark estimates. Accurate accounting of terrestrially derived DOC export to oceans requires incorporating the DOC produced in aquatic ecosystems and deposited with rainwater; otherwise, global export estimates may be overestimated by 40.7%. Additionally, improving the representation of mineralization and burial processes in inland waters allows for more accurate accounting of carbon sequestration through land ecosystems. When all the inland water processes are ignored or assuming DOC leaching is equivalent to DOC export, the loss of soil carbon through this lateral flux could be underestimated by 43.9%.
The geostationary Operational Environmental Satellite (GOES) 1/M series of spacecraft are geostationary weather satellites that use the latest in weather imaging technology. The inertial reference unit package onboard consists of three gyroscopes measuring angular velocity along each of the spacecraft's body axes. This digital integrating rate assembly (DIRA) is calibrated and used to maintain spacecraft attitude during orbital delta-V maneuvers. During the early orbit support of GOES-8 (April 1994), the gyro drift rate biases exhibited a large dependency on gyro temperature. This complicated the calibration and introduced errors into the attitude during delta-V maneuvers. Following GOES-8, a model of the DIRA temperature and drift rate bias variation was developed for GOES-9 (May 1995). This model was used to project a value of the DIRA bias to use during the orbital delta-V maneuvers based on the bias change observed as the DIRA warmed up during the calibration. The model also optimizes the yaw reorientation necessary to achieve the correct delta-V pointing attitude. As a result, a higher accuracy was achieved on GOES-9 leading to more efficient delta-V maneuvers and a propellant savings. This paper summarizes the: Data observed on GOES-8 and the complications it caused in calibration; DIRA temperature/drift rate model; Application and results of the model on GOES-9 support.
Unsteady aerodynamic models based on windtunnel forced oscillation test data and analyzed with a fuzzy logic algorithm arc incorporated into an F-16XL flight simulation code. The reduced frequency needed in the unsteady models is numerically calculated by using a limited prior time history of state variables in a least-square sense. Numerical examples arc presented to show the accuracy of the calculated reduced frequency. Oscillatory control inputs are employed to demonstrate the differences in the flight characteristics based on unsteady and quasi-steady aerodynamic models. Application of the unsteady aerodynamic models is also presented and the results are compared with one set of F16XIL longitudinal maneuver flight data. It is shown that the main differences in dynamic response are in the lateral-directional characteristics, with the quasi-steady model being more stable than the flight vehicle, while the unsteady model being more unstable. Similar conclusions can also be made in a simulated rapid sideslipping roll. To improve unsteady aerodynamic modeling, it is recommended to acquire test data with coupled motions in pitch, roll and yaw.
The C-130 aircraft observations were successfully collected during May and July 1998. The aircraft data has been processed and is already available to the community. Integrated data sets for modelling applications have been prepared and modelling studies have been completed. Included is a list of papers that have been submitted since the start of the project.
Thermal infrared-based remote sensing of surface energy fluxes has traditionally relied on high spatial resolution satellite data with revisit frequencies on the order of weeks. In this study, we evaluate a biophysics-based analytical surface energy balance model for predicting latent energy (LE) and sensible heat (H) fluxes using proximal sensing observations. The Surface Temperature Initiated Closure (STIC1.2) model has been extensively validated across a wide range of spatial and temporal scales using various satellite-derived thermal infrared data sets. Here we extend this validation by applying STIC at sub-hourly temporal resolution over multiple growing seasons for four distinct agricultural systems. We further develop and evaluate novel STIC variants that incorporate machine learning (ML) techniques to eliminate the need for surface energy balance observations, specifically net radiation and soil heat flux, thereby enhancing model applicability in data-sparse settings. The integration of a ML component to estimate surface available energy is shown to have strong predictive performance for both LE (R2 = 0.81–0.94) and H (R2 = 0.46–0.72) across all agricultural systems examined here, demonstrating the potential of hybrid biophysical-machine learning approaches for surface energy balance modeling with minimal data requirements. This study concludes with a novel application of explainable machine learning (exML) to diagnose sources of model error. This exML framework attributes residual prediction errors to both model input variables and environmental drivers not explicitly included in the simulation experiments. This approach provides a new pathway for improving model design and integrating previously overlooked yet influential variables into future model iterations.
Digital engineering strategies typically assume that digital engineering models interoperate seamlessly across the multiple different engineering modeling software applications involved, such as model- based systems engineering (MBSE), mechanical computer-aided design (MCAD), electrical computer-aided design (ECAD), and other engineering modeling applications. The presumption is that the data schema in these modeling software applications are structured in the familiar flat- tabular schema like any other software application. Engineering domain-specific applications (e.g., systems, mechanical, electrical, simulation) are typically designed to solve domain-specific problems, necessarily excluding explicit representations of non-domain information to help the engineer focus on the domain problems (system definition, design, simulation). Such exclusions become problematic in inter-domain information exchange. The obvious assumptions of one domain might not be so obvious to experts in another domain. Ambiguity in domain-specific language can erode the ability to enable different domain modeling applications to interoperate, unless the underlying language is understood and used as the basis for translation from one application to another. The engineering modeling software application industry has struggled for decades to enable these applications to interoperate. Industry standards have been developed, but they have not unified the industry. Why is this? The authors assert that the industry has relied on traditional database integration methods. The basic issue prohibiting successful application integration then is that traditional database-driven integration does not consider the distinct languages of each domain. An engineering models meaning is expressed through the underlying language of that engineering domain. In essence, traditional integration methods do not retain the semantic context (meaning) of the model. The basis of this research stems from the widely held assumption that systems engineering models are (or can be) structured according to the underlying semantic ontology of the model. This assumption can be imagined from two thoughts. 1) Digital systems engineering models are often represented using graph theory (the graph of a complex systems model can contain millions of nodes and edges). When examining the nodes one at a time and following the outbound edges of each node one by one, one can end up with rudimentary statements about the model (i.e., node A relates to node B), as in a semantic graph. 2) Likewise, from the study of natural languages, a sentence can be structured into unambiguous triples of subject-predicate-object within formal and highly expressive semantic ontologies. The rudimentary statements about a systems model discerned with graph theory closely mimic the triples used in the ontologies that try to structure natural languages. In other words, a systems models semantic graph can be (or is) structured into an ontology. Additionally, it is well established in industry that through natural language processing (NLP), which provides the means to create language structures, that computers can interpret ontological graphs. Therefore, the authors hypothesized that if the integrity of the underlying semantic structure of a systems model is retained, the contextual meaning of the model is retained. By structuring system models into the triples of the underlying ontology during the transformation from one MBSE application to another, the authors have provided a proof of the concept that the meaning of a system model can be retained during transformation. The authors assert that this is the missing ingredient in effective systems model-to-model interoperability. ACKNOWLEDGEMENTS The authors would like to thank the FY19 Model Interoperability team members who provided a solid foundation for the FY20 team to leverage: John McCloud, for the work he did to guide us toward the right use of technology that will appropriately discover and manipulate ontologies. Carlos Tafoya, for the work he did to develop an application programming interface (API)/Adapter that would export ontology-based data from GENESYS. Peter Chandler, for the work he did to architect our overall integration solution, with an eye toward the future that would influence a large-scale federated production-level systems engineering digital model ecosystem.
With the expected convergence between HPC, BigData and AI, new applications with different profiles are coming to HPC infrastructures. Here, we aim at better understanding the features and needs of these applications in order to be able to run them efficiently on HPC platforms. The approach followed is bottom-up: we study thoroughly an emerging application from the neuroscience community (SLANT) to understand its behavior. Based on these observations, we derive a generic, yet simple, application model (namely, a linear sequence of stochastic jobs). We expect this model to be representative for a large set of upcoming applications that require the computational power of HPC clusters without fitting the typical behavior of large-scale traditional applications. In a second step, we show how one can manipulate this generic model in a scheduling framework. Specifically we consider the problem of making reservations (both time and memory) for an execution on an HPC platform. We derive solutions using the model of the first step of this work. We experimentally show the robustness of the model, even with very few data or with another application, to generate the model, and provide performance gains with regards to standard and more recent approaches used in the neuroscience community.
Numerous components in reusable space propulsion systems such as the SSME are exposed to high pressure gaseous hydrogen environments. Flow areas and passages in the fuel turbopump, fuel and oxidizer preburners, main combustion chamber, and injector assembly contain high pressure hydrogen either high in purity or as hydrogen rich steam. Accurate constitutive and damage material models applicable to high pressure hydrogen environments are therefore needed for engine design and analysis. Existing constitutive and cyclic crack initiation models were evaluated only for conditions of oxidizing environments. The main objective is to evaluate these models for applicability to high pressure hydrogen environments.
Recent models for accretion of terrestrial bodies involve metal-silicate equilibrium as the metallic core formed during growth. Most elements considered are either refractory or well studied elements for which effects of pressure, temperature, oxygen fugacity, and metallic liquid composition are well known. There are a large number of elements that are both siderophile and volatile, whose fate in such models is unknown, largely due to a lack of data at comparable conditions and com-positions (FeNi core with light elements such as S, C, Si, and O). We have focused on Ge, In, As, Sb and determined the effect of Si and C on metal-silicate partitioning, and developed a thermo-dynamic model that allows application of these new data to a wide range of planetary bodies. New experiments: We have previously carried out experiments with FeSi metallic liquid at C-saturated conditions at 1600 and 1800 C [4]. In a new series of experiments we investigate the effect of Si in carbon-free systems at 1600 C for comparison. Experiments were carried out at 1 GPa in MgO capsules using the same basaltic starting composition as in previous studies. The MgO capsule reacts with the silicate melt to form more MgO-rich liquids that have 22-26 wt% MgO. Experimental met-als and silicates were analyzed using a combination of electron microprobe analysis and laser ablation ICP-MS. Results: The new results can be interpreted by considering Ge as an example, in the simple exchange equilibrium Fe + GeO = FeO + Ge, where the equilibrium constant Kd can be examined as a function of Si content of the metal. The slope of lnKd vs. (1-XSi) for this new series allows derivation of the epsilon interaction parameter for each of these four elements and Si (both C-saturated and C-free).All four elements have positive epsilon values, indicating that Si causes a decrease in the partition coefficients; values are 6.6, 6.5, 27.8 and 25.2 for In, Ge, As, and Sb, respectively, at 1 GPa and 1600 C. As an example of how large the effect of Si can be, these epsilon values correspond to activity coefficients (gamma) for As of 0.01 when XSi = 0, and up to gamma = 23 when XSi = 0.2. Combining these new results with previous determinations [5,6] of epsilon parameters for S and C for these elements allows us calculate activity of Ge, In, As, and Sb in Fe-Ni-Si-S-C-O metallic liquids. We apply this new model to sever-al terrestrial bodies such as Earth (Si-rich core), Mars (S-rich core), Moon (S-, C-, and Si-poor core), and Vesta, and examine the resulting core and mantle concentrations of these elements. Mantle concentrations of these four elements are well explained for Earth and Mars in models that call for mid-mantle equilibration between Si-bearing and S-bearing FeNi cores, respectively. Modeling results for the Moon and Vesta will also be presented.
Abstract. For the underground disposal of high-level nuclear waste in rock salt formations, the safety concept includes the backfilling of open cavities with crushed salt. For the prognosis of the sealing function of the backfill for the safe containment of the radioactive waste, it is crucial to have a comprehensive process understanding of the crushed-salt compaction behavior. The crushed-salt compaction process is influenced by internal properties (e.g., grain size, mineralogy, and moisture content) and boundary conditions (e.g., temperature, stress state, and compaction rate) and, therefore, involves several coupled thermal–hydro–mechanical (THM) processes (Hansen et al., 2014; Kröhn et al., 2017). With the paradigm shift from the limited release of radionuclides to safe containment due to the German Repository Site Selection Act passed in 2017, the importance of crushed salt as geotechnical barrier has increased, with a focus on the evolution of its hydraulic properties. Based on the knowledge gaps in the current process understanding, the “Compaction of crushed salt for safe containment” (KOMPASS) projects were initiated to improve the scientific basis behind using crushed salt for the long-term isolation of high-level nuclear waste within rock salt repositories. The efforts to improve the prediction of crushed-salt compaction begun during the first phase of the KOMPASS projects (Czaikowski et al., 2020) and were followed up in a second phase ending in June 2023. The primary achievements of the projects are as follows (Czaikowski et al., 2020; Friedenberg et al., 2022): specification of the KOMPASS reference material, an easily available and reproducible synthetic crushed-salt material, for generic investigations; development of pre-compaction methods and successful production of samples in the short term and under in situ loading conditions; formulation of an extended laboratory program addressing the isolated investigation of known relevant factors influencing the compaction behavior of crushed salt (Düsterloh et al., 2022); execution of long-term compaction tests addressing isotropic and deviatoric load changes, temperature, and compaction state; construction of a backfill body using the KOMPASS reference material in the Sondershausen mine through collaboration with the SAVER (Entwicklung eines salzgrusbasierten Versatzkonzepts unter der Option Rückholbarkeit) project (Schaarschmidt and Friedenberg, 2022); advancement of the tools for microstructure investigation methods (Svensson and Laurich, 2022); generation (first stages) of a microphysical process list combining literature research with our own findings; benchmarking of long-term compaction test for model development and optimization of various existing models as well as the development of new models; application of a virtual demonstrator (2D model representing a backfilled drift in rock salt) for the visualization of developments and the quantification of the models (Rabbel, 2022). In summary, the KOMPASS projects contributed to the reduction of uncertainties and the strengthening of the safety case for using crushed salt within rock salt repositories.
The main subject of the discussed investigation is the infrared brightness variation of the A, B, and C rings, as a function of solar elevation. Existing models for the B ring are not entirely satisfactory. A description is presented of a model applicable to all three rings. This model and other existing models are compared with the available data. Particular attention is given to the 20-micrometer observations of Saturn's rings. It is found that the brightness variation of the A and B rings with solar elevation angle can be well modeled by an optically thick monolayer of particles, or equivalently, a flat sheet, emitting on one side only. This points to a temperature contrast between the two sides of the ring plane. The infrared brightness of the C ring increases as the solar elevation angle with respect to the ring plane decreases.
CARES calculates fast-fracture reliability or failure probability of macroscopically isotropic ceramic components. Program uses results from commercial structural-analysis program (MSC/NASTRAN or ANSYS) to evaluate reliability of component in presence of inherent surface- and/or volume-type flaws. Computes measure of reliability by use of finite-element mathematical model applicable to multiple materials in sense model made function of statistical characterizations of many ceramic materials. Reliability analysis uses element stress, temperature, area, and volume outputs, obtained from two-dimensional shell and three-dimensional solid isoparametric or axisymmetric finite elements. Written in FORTRAN 77.