GEOS-MLT: A High-Altitude Atmospheric Model to Bridge Earth System Modeling and Heliophysics Data
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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Photovoltaic system model calibration using monitored system data.
Abstract not provided.
Hansen, Clifford W.↗
A Multiplex Complex Systems Model for Engineering Security Systems.
Abstract not provided.
Williams, Adam David↗
NASA Lewis Wind Tunnel Model Systems Criteria
This report describes criteria for the design, analysis, quality assurance, and documentation of models or test articles that are to be tested in the aeropropulsion facilities at the NASA Lewis Research Center. The report presents three methods for computing model allowable stresses on the basis of the yield stress or ultimate stress, and it gives quality assurance criteria for models tested in Lewis' aeropropulsion facilities. Both customer-furnished model systems and in-house model systems are discussed. The functions of the facility manager, project engineer, operations engineer, research engineer, and facility electrical engineer are defined. The format for pretest meetings, prerun safety meetings, and the model criteria review are outlined Then, the format for the model systems report (a requirement for each model that is to be tested at NASA Lewis) is described, the engineers that are responsible for developing the model systems report are listed, and the time table for its delivery to the facility manager is given.
Soeder, Ronald H.↗
Hydrogen Storage System Modeling: Public Access, Maintenance, and Enhancements
The hydrogen storage system modeling project aims to develop new and enhance existing material-based hydrogen storage system models and make them accessible to the research community through a public web page. Updating existing storage systems models supports material developers in evaluating the performance of their new materials in mobile and stationary applications relative to the available DOE Technical Targets. Developing new tools helps researchers evaluate the performance of hydrogen storage materials developed under HyMARC activities or other fundamental hydrogen storage materials discovery research. New models will also work for validating alternatives to material-based systems (liquefied & gaseous hydrogen), comparing various mobile and stationary use cases, and expand to include medium-, heavy-duty, and mining vehicles and stationary application(s).
AMR↗
A Fortran-Python Interface for Integrating Machine Learning Parameterization into Earth System Models
Parameterizations in Earth System Models (ESMs) are subject to biases and uncertainties arising from subjective empirical assumptions and incomplete understanding of the underlying physical processes. Recently, the growing representational capability of machine learning (ML) in solving complex problems has spawned immense interests in climate science applications. Specifically, ML-based parameterizations have been developed to represent convection, radiation and microphysics processes in ESMs by learning from observations or high-resolution simulations, which have the potential to improve the accuracies and alleviate the uncertainties. Previous works have developed some surrogate models for these processes using ML. These surrogate models need to be coupled with the dynamical core of ESMs to investigate the effectiveness and their performance in a coupled system. In this study, we present a novel Fortran-Python interface designed to seamlessly integrate ML parameterizations into ESMs. This interface showcases high versatility by supporting popular ML frameworks like PyTorch, TensorFlow, and Scikit-learn. We demonstrate the interface's modularity and reusability through two cases: a ML trigger function for convection parameterization and a ML wildfire model. We conduct a comprehensive evaluation of memory usage and computational overhead resulting from the integration of Python codes into the Fortran ESMs. By leveraging this flexible interface, ML parameterizations can be effectively developed, tested, and integrated into ESMs.
54 ENVIRONMENTAL SCIENCES↗
Technology Investments in the NASA Entry Systems Modeling Project
The Entry Systems Modeling (ESM) technology development project, initiated in 2012 under NASAs Game Changing Development (GCD) Program, is engaged in maturation of fundamental research developing aerosciences, materials, and integrated systems products for entry, descent, and landing(EDL)technologies [1]. To date, the ESM project has published over 200 papers in these areas, comprising the bulk of NASAs research program for EDL modeling. This presentation will provide an overview of the projects successes and challenges, and an assessment of future investments in EDL modeling and simulation relevant to NASAs mission
Barnhardt, Michael↗
SP-100 control system modeling
SP-100 Control Systems modeling was done using a thermal hydraulic transient analysis model called ARIES-S. The ARIES-S Computer Simulation provides a basis for design, integration and analysis of the reactor including the control and protection systems. It is a modular digital computer simulation written in FORTRAN that operates interactively in real time on a VAX minicomputer.
Meyer, R. A.↗
Knowledge Graph for End-to-End Traceability of an Integrated Human-Earth System Model
Integrated human-Earth system models inform energy-water-land system dynamics and policies, yet their results are difficult to trace through input-data, model structure, scenario configurations, and solved outputs. Because this information is siloed across disconnected artifacts, process-based IAMs have historically lacked a unified, queryable representation. Such lack of traceability prevents researchers from systematically isolating the multi-sector drivers of complex outcomes (such as tracing water-scarcity results back to distant energy-system dynamics) or conducting holistic uncertainty attribution across hundreds of interacting parameters. To address this concern, our work documents the software engineering process of a knowledge graph that unifies these four layers for the Global Change Analysis Model (GCAM-USA_Reference scenario, GCAM v9.1). The graph was built as a relational property graph in DuckDB from the run’s own artifacts: the input-preparation dependency map (gcamdata chunk map), the model’s XML input files, the run configuration, and the results database (BaseX), successfully mapping the model’s declared structure. The resulting graph comprises 204,321 nodes and 1,687,814 edges across 16 node types and 15 edge types, with approximately 16.3 million time-series values stored separately to maintain structural efficiency. To ensure representation fidelity, every edge carries an epistemic-status annotation recording the warrant for the relationship (structural, provenance, dependency, or model-derived), and a machine-readable provenance ledger classifying the origin of every schema element. Evaluation against a fixed five-benchmark suite with locked baselines reports zero structural orphans, zero dangling edge endpoints, and 100% of output-producing technologies traceable to raw input files. Two interactive interfaces present the graph, including a serverless browser application built on DuckDB-Wasm. By establishing the first end-to-end provenance framework for an IAM, this work enables researchers and scientists to systematically audit complex policy scenarios, debug model structures, and trace policy-relevant outputs to their data origins in real time.
Artifical Intelligence↗
Toward a subhourly net zero energy district design through integrated building and distribution system modeling
A modeling framework integrating both building energy modeling and power system modeling is introduced for the design of net zero energy (NZE) districts for the simultaneous selection of both demand-side efficiency measures and supply-side generation technologies. A novel district control scheme is proposed for pursuing NZE on a subhourly basis while mitigating potential grid impacts such as power backfeeding and voltage violations. As a case study, Pena Station NEXT, a new 100-building, mixed-use district on a 1200-node distribution feeder in Denver, Colorado, is modeled in the integrated framework. An exhaustive scenario analysis is conducted for sizing the district's distributed energy resources, considering multiple objectives such as capital cost, net energy import, and equipment violations. Here, when trying to achieve annual NZE, the district incurs frequent operating violations, and achieving NZE on a 15-min basis is also limited by seasonal fluctuations in photovoltaic output, illustrating the need for diverse generation or seasonal storage. As a practical compromise, both annual and 15-min district import can be reduced by ~78% without significant violations.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
Improved Representations of Longwave Surface Emissivity to Reduce Surface and Atmospheric Heating Biases in Earth System Models
Abstract Many Earth system models (ESMs) approximate surface emissivity as a broadband constant. This approximation reduces the computational burden, yet omits the spectral structure of emissivity and atmospheric absorption. Neglecting spectral variation in surface emission introduces biases in longwave (LW) atmospheric fluxes and heating. Biases are strongest over surfaces with strongly varying emissivity and minimal atmospheric opacity. We examine these biases over water, ice, and snow surfaces. We partition spectral emissivity into the 16 spectral bands utilized by a single‐column atmospheric radiative transfer model (RRTMG_LW) commonly used in ESMs. We quantify flux and heating biases introduced by broadband assumptions relative to the spectrally resolved case for standard atmospheric profiles over each surface type. Current assumptions tend to overestimate upwelling surface fluxes; for example, the greybody assumption overestimates flux by 1.6 W/m 2 (0.52%) at the bottom of a mid‐latitude winter atmosphere over ice, and by 2.33 (1.0%) at the top of atmosphere. The blackbody assumption tends to artificially cool Earth's surface, stabilizing the lower troposphere. Interestingly, the optimal broadband emissivity can deviate from the Planck‐weighted mean by up to 3% depending on surface type and atmospheric profile. We investigate bias sensitivity to surface temperature, cloud water path, and atmospheric water vapor. Bias is most sensitive to water vapor content, and least sensitive to cloud water path. Lastly, we show that a modified greybody method with updated broadband values can reduce total surface flux bias up to 1.69 , comparable to a five‐band approach and at a fraction of the computational cost.
Manzo, L. [Department of Earth System Science Univ↗
Microphysics in Goddard Multi-Scale Modeling Systems
Advances in computing power allow atmospheric prediction and general circulation models to be run at progressively finer scales of resolution, using increasingly more sophisticated physical parameterizations. The representation of cloud microphysical processes is one of key components of these models. In addition, over the past decade both research and operational numerical weather prediction models have started using more complex microphysical schemes that were originally developed for high-resolution cloud-resolving models (CRMs). In the paper, we described different microphysics schemes that are used in Goddard Multi-scale Modeling System. There are three major models, Goddard Cumulus Ensemble (GCE), NASA Unified Weather Research Forecast (NU-WRF) and Multi-scale Modeling Framework (MMF) model, in this modeling system. The microphysics schemes are Goddard three class ice (3ICE) and four class (4ICE) scheme, Morrison two moments (2M) 3ICE, Colorado State University Regional Atmospheric Modeling System (RAMS) 2M five class ice (5ICE) and spectral bin microphysics schemes. The performance of these schemes are examined and compared with radar and satellite observation. In addition, the inter-comparison with different microphysics schemes are conducted. Current and future observations needed for microphysics schemes evaluation as well as major characteristics of current microphysics are discussed.
Tao, W.-K.↗
Smart Data Mapping for Connecting Power System Model and Geospatial Data
Knowing the geospatial locations of power system model elements is the foundation for analyzing system vulnerability to natural hazards and connecting loads with end users and their communities. However, power system models and geospatial data for power grid assets may have been developed asynchronously without close coordination. Creating a direct mapping between the two may be a challenging task, considering heterogeneous data structures, target uses, historical legacies, and human errors. This work aims to build an automatic data mapping workflow to connect power system model elements and geospatial data for transmission network, and to support energy grid resilience studies for Puerto Rico. The primary steps in this workflow include constructing graphs using geospatial data, and aligning them to the transmission networks defined in the power system data. The results have been evaluated against existing manual mapping practices for part of the Puerto Rico Power Grid model to illustrate the performance of such auto-mapping solutions.
Resilience, geospatial data, grid transmission net↗
A study of the development of a basic plane- tary transportation systems model
Basic planetary transportation system model
TRANSPORTATION↗
Entry Systems Modeling Project
ESM (Entry Systems Modeling Project) is the only dedicated research effort for EDL (Entry, Descent and Landing) modeling at NASA. ESM provides consistent support for experts to develop high-priority model improvements and validation testing, driven by mission needs, that can be delivered in 3-5 years to reduce mission risk and improve performance. Focused research in four elements: Predictive Materials Modeling; Guidance, Navigation and Control; Computational and Experimental Aerosciences; Shock Layer Kinetics and Radiation.
CFD↗
An Overview of Experiments in The Entry Systems Modeling Project
The Entry Systems Modeling (ESM) project has invested in experiments designed to enhance understanding of salient interactions between thermal protection materials (TPS) and mission-relevant planetary entry environments. An arc-jet campaign has been carried out at the Aerodynamic Heating Facility (AHF) to investigate the spallation of fiber particles as a function of gas composition and to measure the effect of pyrolysis gas flow on the in-depth temperature response of phenolic impregnated carbon ablator (PICA). Moreover, fundamental insights into the pyrolysis and oxidation mechanisms of the phenolic binding agent of FiberForm will be discussed. Finally, two new apparatus developed at NASA will be presented that were designed to interrogate phenomena associated with the production of gases and particles generated under simulated flight conditions.
Material Response↗
An Overview of Experiments in The Entry Systems Modeling Project
The Entry Systems Modeling (ESM) project has invested in experiments designed to enhance understanding of salient interactions between thermal protection materials (TPS) and mission-relevant planetary entry environments. An arc-jet campaign has been carried out at the Aerodynamic Heating Facility (AHF) to investigate the spallation of fiber particles as a function of gas composition and to measure the effect of pyrolysis gas flow on the in-depth temperature response of phenolic impregnated carbon ablator (PICA). Moreover, fundamental insights into the pyrolysis and oxidation mechanisms of the phenolic binding agent of FiberForm will be discussed. Finally, two new apparatus developed at NASA will be presented that were designed to interrogate phenomena associated with the production of gases and particles generated under simulated flight conditions.
Varcum↗
Formulation and solution approach for calibrating activity-based travel demand model-system via microsimulation
This study addresses the problem of calibrating utility-maximizing nested logit activity-based travel demand model-systems. After estimation, it is common practice to use aggregate measurements to calibrate the estimated model-system’s parameters prior to their application in transportation planning, policy making, and operations. However, calibration of activity-based model-systems has received much less attention. Existing calibration approaches are myopic heuristics in the sense that they do not consider the fundamental inter-dependencies among choice-models and do not have a systematic way to adjust model parameters. Also, other purely simulation-based approaches do not perform well in large-scale applications. In this study, we focus on utility-maximizing nested logit activity-based model-systems and calibrating aggregate statistics such as activity shares, mode shares, time-dependent & mode-specific OD flows, and time-dependent & mode-specific sensor counts. We formulate the calibration problem as a simulation-based optimization problem and propose a stochastic gradient-based solution procedure to solve it. The solution procedure relies on microsimulation to calculate expectations of the aggregate statistics of interest to the calibration problem. Additionally, we derive approximate analytical expressions for the gradient of the objective function —that are evaluated through microsimulation on mini-batches of the population. The proposed solution procedure is sensitive to the fundamental structure of the activity-based model-system and is non-myopic in considering the dependencies across its model components. The formulated optimization problem is non-convex, highly nonlinear, and potentially has multiple-minima. Lastly, we show —through a real-world application— that the proposed solution procedure outperforms other state-of-the-art purely simulation-based optimization approaches in terms of computational efficiency, stability, and convergence. We also compare various gradient-based solution algorithms to determine the best algorithm to update the parameters. This work has the potential to facilitate wider and easier application of activity-based model-systems.
97 MATHEMATICS AND COMPUTING↗