Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Model selection”

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.

At least 235 records · Page 13

Community Coordinated Modeling Center: Addressing Needs of Operational Space Weather Forecasting

Models are key elements of space weather forecasting. The Community Coordinated Modeling Center (CCMC, http://ccmc.gsfc.nasa.gov) hosts a broad range of state-of-the-art space weather models and enables access to complex models through an unmatched automated web-based runs-on-request system. Model output comparisons with observational data carried out by a large number of CCMC users open an unprecedented mechanism for extensive model testing and broad community feedback on model performance. The CCMC also evaluates model's prediction ability as an unbiased broker and supports operational model selections. The CCMC is organizing and leading a series of community-wide projects aiming to evaluate the current state of space weather modeling, to address challenges of model-data comparisons, and to define metrics for various user s needs and requirements. Many of CCMC models are continuously running in real-time. Over the years the CCMC acquired the unique experience in developing and maintaining real-time systems. CCMC staff expertise and trusted relations with model owners enable to keep up to date with rapid advances in model development. The information gleaned from the real-time calculations is tailored to specific mission needs. Model forecasts combined with data streams from NASA and other missions are integrated into an innovative configurable data analysis and dissemination system (http://iswa.gsfc.nasa.gov) that is accessible world-wide. The talk will review the latest progress and discuss opportunities for addressing operational space weather needs in innovative and collaborative ways.

Kuznetsova, M.↗

A model for plant lighting system selection

A decision model is presented that compares lighting systems for a plant growth scenario and chooses the most appropriate system from a given set of possible choices. The model utilizes a Multiple Attribute Utility Theory approach, and incorporates expert input and performance simulations to calculate a utility value for each lighting system being considered. The system with the highest utility is deemed the most appropriate system. The model was applied to a greenhouse scenario, and analyses were conducted to test the model's output for validity. Parameter variation indicates that the model performed as expected. Analysis of model output indicates that differences in utility among the candidate lighting systems were sufficiently large to give confidence that the model's order of selection was valid.

NASA Center KSC↗

Self-consistent equilibrium and transport simulations for NSTX-U plasmas enhanced via machine learning surrogate models

The Control-Oriented Transport SIMulator (COTSIM) is an advanced equilibrium and transport code designed for simulating tokamak discharges at computational speeds suitable for control applications. COTSIM’s modular framework enables users to select models that balance accuracy with speed according to specific needs, allowing the code to operate from fast to faster-than-real-time performance levels. This work presents recent enhancements to COTSIM’s predictive accuracy for NSTX-U scenarios, achieved by integrating neural-network-based surrogate models and self-consistent equilibrium calculations. To improve source deposition predictions, a surrogate model for NUBEAM has been incorporated. Additionally, a surrogate model for the Multi-Mode Module (MMM) now supports predictions of anomalous thermal, momentum, and particle diffusivities—key factors for modeling the evolution of temperature and rotation. Each surrogate model was specifically trained for the NSTX-U operational regime to enhance COTSIM’s accuracy while maintaining computational efficiency. Moreover, COTSIM now couples fixed-boundary equilibrium solvers with its transport solvers, enabling self-consistent predictions of plasma profiles and equilibrium evolution over the discharge. Simulation results demonstrate strong agreement between COTSIM and TRANSP predictions for NSTX-U discharges. These substantial advancements expand COTSIM’s utility in model-based control applications for NSTX-U. Potential applications include simultaneous optimization of equilibrium and transport scenarios, integration into digital twins, real-time profile estimation (e.g., temperature and rotation) from limited or noisy measurements, and advanced feedback-based scenario control.

Equilibrium and transport modeling↗

Understanding the trade-offs of national municipal solid waste estimation methods for circular economy policy

Policies embracing circular economy concepts have taken hold in national legislation around the world. As the number of governments and organizations adopting circular economy policies increases, so does the need for accurate and timely measurement of material resource flows. Since many countries do not have access to centrally reported municipal solid waste (MSW) data, estimation and modeling are critical in evaluating circular economy policy effectiveness. The purpose of this paper is to examine three modeling approaches estimating national MSW data in the United States, including industry-based material flow analysis, waste-extended input-output modeling, and aggregated regional waste reporting. We establish five criteria to guide the analysis through the context of policy monitoring (data quality, flow totality, update frequency, sensitivity to disruption, and product granularity) and use these criteria to analyze and score each model. We then use a literature search to identify five, internationally-implemented options for circular economy policy and determine the data and modeling components that are most helpful in evaluating policy effectiveness. Finally, we provide a crosswalk of the model scores and policy needs to inform the suitability of model selection by policy type. We found that data quality and update frequency are identified as critical components for evaluating circular economy policies within the models evaluated, and can both be fulfilled by aggregated regional waste reporting. Flow totality, sensitivity to disruption, and product granularity requirements vary by both model and policy types. While none of the evaluated models satisfy the combination of requirements for any of the five policies, industry-based material flow analysis offers flow totality for extended producer responsibility, landfill bans, and recycling rate target policies that typically require it. Here, the waste-extended input-output model can provide disruption sensitivity and product granularity as needed for policies like minimum recycled content and market restrictions. Policy developers in areas where strong centralized data collection is not an option should design policy action(s) with modeling tradeoffs in mind, including the potential hybridization of modeling approaches that may provide the most accurate national MSW estimates.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

MILK : a Python scripting interface to MAUD for automation of Rietveld analysis

Modern diffraction experiments ( e.g. in situ parametric studies) present scientists with many diffraction patterns to analyze. Interactive analyses via graphical user interfaces tend to slow down obtaining quantitative results such as lattice parameters and phase fractions. Furthermore, Rietveld refinement strategies ( i.e. the parameter turn-on-off sequences) tend to be instrument specific or even specific to a given dataset, such that selection of strategies can become a bottleneck for efficient data analysis. Managing multi-histogram datasets such as from multi-bank neutron diffractometers or caked 2D synchrotron data presents additional challenges due to the large number of histogram-specific parameters. To overcome these challenges in the Rietveld software Material Analysis Using Diffraction ( MAUD ), the MAUD Interface Language Kit ( MILK ) is developed along with an updated text batch interface for MAUD . The open-source software MILK is computer-platform independent and is packaged as a Python library that interfaces with MAUD . Using MILK , model selection ( e.g. various texture or peak-broadening models), Rietveld parameter manipulation and distributed parallel batch computing can be performed through a high-level Python interface. A high-level interface enables analysis workflows to be easily programmed, shared and applied to large datasets, and external tools to be integrated with MAUD . Through modification to the MAUD batch interface, plot and data exports have been improved. The resulting hierarchical folders from Rietveld refinements with MILK are compatible with Cinema: Debye–Scherrer , a tool for visualizing and inspecting the results of multi-parameter analyses of large quantities of diffraction data. In this manuscript, the combined Python scripting and visualization capability of MILK is demonstrated with a quantitative texture and phase analysis of data collected at the HIPPO neutron diffractometer.

97 MATHEMATICS AND COMPUTING↗

Modeling the U.S. Western Electric Interconnection to Understand the Consequences of Hydrometeorological Extremes and Options for Risk Mitigation

Electricity grid operators around the world face a dual challenge; withstanding increasingly severe weather and the longer term impacts of climate change, while simultaneously decarbonizing. Extreme weather events such as heat waves and droughts are rising in both severity and frequency, which is threatening the reliability of electricity grids through increased demand, generation capacity losses, and equipment failures. Consequently, incorporating hydrometeorological stressors into computational power systems analysis is becoming an even more critical tool in long term planning and short term operations. However, there is a general lack of open-source customizable grid simulation software capable of exhaustively stress testing the grid under hydrometeorological uncertainty, and/or examining potential risk mitigation pathways. A related, persistent challenge for power system modelers is striking an appropriate balance between model fidelity (e.g. spatial scale and time resolution) and computational tractability (wall clock run-time). In this study, we are proposing a solution to this problem with open-source software that allows users to seamlessly customize the scale and track the accuracy of grid operations models. Our approach allows users to search over numerous model parameters (network topology, mathematical formulation, economic hurdle rates, and transmission line scaling) to identify model instantiations that accommodate experimental design. Further, we use this approach to demonstrate the importance of including extreme weather events in model validation and model selection. Focusing on the occurrence of heatwaves and droughts in the U.S. Western Interconnection, we examine role of extreme events in balancing tradeoffs between model fidelity and run-time at the model design stage.

Economics↗

Gas physics environment of high altitude Jovian entry.

A description of the gas physics environment associated with high-altitude Jupiter entry is reported. Two aspects of environmental analysis are treated. First, limited discussion is devoted to prediction of the heating environment of the probe aeroshell. Prime emphasis is given to the second aspect of the analysis, a description of the gas particle probe interaction phenomena in the rarefied flow regime. Several molecular reemission models have been devised and exercised. Model selection was based upon the desire to bracket the expected reemission characteristics. Consideration was given to examining diffuse reflection as exemplified by the Maxwellian model and lobular, specular reflection as characterized by the Nocilla model. Variation of fundamental input parameters was investigated to determine particle-probe interaction sensitivity. Regardless of neutral species type, results show that the attenuation of the incoming flux of that species by reflected particles is approximately 15 per cent in the stagnation region at 200 km above the cloud tops.

Lefferdo, J. M.↗

Parameter estimation and error analysis in environmental modeling and computation

A method for the estimation of parameters and error analysis in the development of nonlinear modeling for environmental impact assessment studies is presented. The modular computer program can interactively fit different nonlinear models to the same set of data, dynamically changing the error structure associated with observed values. Parameter estimation techniques and sequential estimation algorithms employed in parameter identification and model selection are first discussed. Then, least-square parameter estimation procedures are formulated, utilizing differential or integrated equations, and are used to define a model for association of error with experimentally observed data.

Kalmaz, E. E.↗

eDNAjoint: An R package for interpreting paired or semi‐paired environmental DNA and traditional survey data in a Bayesian framework

Abstract Environmental DNA (eDNA) sampling is increasingly used in surveys of species distribution as a potentially sensitive and efficient monitoring method. Yet access to modelling tools designed specifically for interpreting this new data type lags behind its ubiquity. While occupancy modelling software has dominated the analytical landscape for eDNA data analysis of single species, this type of model may not always be the most appropriate. The rate of eDNA detection often corresponds to species density, rather than just occupancy, and researchers often have access to observations from non‐genetic sampling methods at the same sites. To provide users access to a modelling framework designed to maximize the use of all available data, we developed an R package, eDNAjoint . The package provides an easy‐to‐use interface for fitting a ‘joint’ model that integrates data from paired or semi‐paired eDNA and traditional surveys in a Bayesian framework. The model can be used to estimate parameters like the probability of a false positive eDNA detection and mean catch rate at a site, and the package allows access to multiple model variations and Bayesian prior customization. Additional functionality can be used for model selection, summarising posteriors and comparing the relative sensitivities of the two survey methods. We demonstrate the use of eDNAjoint by fitting a variation of the model with site‐level covariates that scale the sensitivity of eDNA sampling relative to traditional sampling. The example workflow uses binary eDNA and seine count data for the endangered tidewater goby ( Eucyclogobius newberryi ) from a study by Schmelzle and Kinziger (2016). This use case includes a prior sensitivity analysis and an evaluation of the relationship between detection rates and environmental variables. eDNAjoint has the potential to greatly increase the range of users who will be able to rigorously analyse eDNA and traditional survey data in a Bayesian framework, understand if and how eDNA can improve monitoring practices, and gain confidence in the interpretability of eDNA data.

Keller, Abigail G. [Department of Environment Scie↗

A methodology for the assessment of manned flight simulator fidelity

A relatively simple analytical methodology for assessing the fidelity of manned flight simulators for specific vehicles and tasks is offered. The methodology is based upon an application of a structural model of the human pilot, including motion cue effects. In particular, predicted pilot/vehicle dynamic characteristics are obtained with and without simulator limitations. A procedure for selecting model parameters can be implemented, given a probable pilot control strategy. In analyzing a pair of piloting tasks for which flight and simulation data are available, the methodology correctly predicted the existence of simulator fidelity problems. The methodology permitted the analytical evaluation of a change in simulator characteristics and indicated that a major source of the fidelity problems was a visual time delay in the simulation.

Hess, Ronald A.↗

Studies of the influence of heat pipe model and coupling strategy in heat pipe microreactor simulations using Sockeye

This work demonstrates various modeling approaches for thermally coupling heat pipes to a graphite monolithic block in a microreactor context, accounting for the presence of a gap. We show that heat pipe model selection has a significant impact on the transient behavior of a three-dimensional coupled microreactor assembly problem by comparing results obtained using different heat pipe models from the heat pipe code Sockeye. Additionally, we show that the choice of coupling strategy has significant consequences for both accuracy and performance. Furthermore, we found that our heat flux transfer strategy exhibited greater accuracy than our temperature transfer strategy, even when comparing a loose coupling of the heat flux transfer strategy to a tight coupling of the temperature transfer strategy. Although this research uses only theoretical test problems, it provides important insights in modeling thermal fluids phenomena in heat pipe microreactors.

Direwolf↗

Design Methods and Practices for Fault Prevention and Management in Spacecraft

Integrated Systems Health Management (ISHM) is intended to become a critical capability for all space, lunar and planetary exploration vehicles and systems at NASA. Monitoring and managing the health state of diverse components, subsystems, and systems is a difficult task that will become more challenging when implemented for long-term, evolving deployments. A key technical challenge will be to ensure that the ISHM technologies are reliable, effective, and low cost, resulting in turn in safe, reliable, and affordable missions. To ensure safety and reliability, ISHM functionality, decisions and knowledge have to be incorporated into the product lifecycle as early as possible, and ISHM must be considered as an essential element of models developed and used in various stages during system design. During early stage design, many decisions and tasks are still open, including sensor and measurement point selection, modeling and model-checking, diagnosis, signature and data fusion schemes, presenting the best opportunity to catch and prevent potential failures and anomalies in a cost-effective way. Using appropriate formal methods during early design, the design teams can systematically explore risks without committing to design decisions too early. However, the nature of ISHM knowledge and data is detailed, relying on high-fidelity, detailed models, whereas the earlier stages of the product lifecycle utilize low-fidelity, high-level models of systems and their functionality. We currently lack the tools and processes necessary for integrating ISHM into the vehicle system/subsystem design. As a result, most existing ISHM-like technologies are retrofits that were done after the system design was completed. It is very expensive, and sometimes futile, to retrofit a system health management capability into existing systems. Last-minute retrofits result in unreliable systems, ineffective solutions, and excessive costs (e.g., Space Shuttle TPS monitoring which was considered only after 110 flights and the Columbia disaster). High false alarm or false negative rates due to substandard implementations hurt the credibility of the ISHM discipline. This paper presents an overview of the current state of ISHM design,and a review of formal design methods to make recommendations about possible approaches to enable the ISHM capabilities to be designed-in at the system-level, from the very beginning of the vehicle design process.

Tumer, Irem Y.↗

A Population Pharmacokinetic Model for Disposition in Plasma, Saliva and Urine of Scopolamine after Intranasal Administration to Healthy Human Subjects

An intranasal gel formulation of scopolamine (INSCOP) was developed for the treatment of Space Motion Sickness. The bioavailability and pharmacokinetics (PK) were evaluated under the Food and Drug Administration guidelines for clinical trials with an Investigative New Drug (IND) protocol. The aim of this project was to develop a PK model that can predict the relationship between plasma, saliva and urinary scopolamine concentrations using data collected from the IND clinical trials with INSCOP. Methods: Twelve healthy human subjects were administered three dose levels (0.1, 0.2 and 0.4 mg) of INSCOP. Serial blood, saliva and urine samples were collected between 5 min and 24 h after dosing and scopolamine concentrations were measured by using a validated LC‐MS‐MS assay. Pharmacokinetic Compartmental models, using actual dosing and sampling times, were built using Phoenix (version 1.2). Model selection was based on the likelihood ratio test on the difference of criteria (‐2LL) and comparison of the quality of fit plots. Results: The best structural model for INSCOP (minimal ‐2LL= 502.8) was established. It consisted of one compartment each for plasma, saliva and urine, respectively, which were connected with linear transport processes except the nonlinear PK process from plasma to saliva compartment. The best‐fit estimates of PK parameters from individual PK compartmental analysis and Population PK model analysis were shown in Tables 1 and 2, respectively. Conclusion: A population PK model that could predict population and individual PK of scopolamine in plasma, saliva and urine after dosing was developed and validated. Incorporating a non‐linear transfer from plasma to saliva compartments resulted in a significantly improved model fitting. The model could be used to predict scopolamine plasma concentrations from salivary and urinary drug levels, allowing non‐invasive therapeutic monitoring of scopolamine in space and other remote environments.

Wu, L.↗

Review of multi-fidelity models

Multi-fidelity models provide a framework for integrating computational models of varying complexity, allowing for accurate predictions while optimizing computational resources. These models are especially beneficial when acquiring high-accuracy data is costly or computationally intensive. This review offers a comprehensive analysis of multi-fidelity models, focusing on their applications in scientific and engineering fields, particularly in optimization and uncertainty quantification. It classifies publications on multi-fidelity modeling according to several criteria, including application area, surrogate model selection, types of fidelity, combination methods and year of publication. The study investigates techniques for combining different fidelity levels, with an emphasis on multi-fidelity surrogate models. Here this work discusses reproducibility, open-sourcing methodologies and benchmarking procedures to promote transparency. The manuscript also includes educational toy problems to enhance understanding. Additionally, this paper outlines best practices for presenting multi-fidelity-related savings in a standardized, succinct and yet thorough manner. The review concludes by examining current trends in multi-fidelity modeling, including emerging techniques, recent advancements, and promising research directions.

42 ENGINEERING↗

Measuring earth orientation with the Global Positioning System

A globally distributed network of high-precision receivers which obtain data from the full Global Positioning System (GPS) configuration of 18 or more satellites may soon become an efficient and economical method for the rapid determination of short-term variations in earth orientation. A covariance analysis has been performed to evaluate the errors associated with GPS monitoring of earth orientation. Earth orientation parameters were modeled either as constants over observing windows of various lengths, or as stochastic process-noise variables. The sensitivity of earth orientation estimates to systematic errors in selected model parameters was also examined. GPS measurements appear to be highly competitive with those from other techniques, and have the potential to generate nearly continuous centimeter-level earth orientation information to aid both spacecraft navigation and the study of high-frequency earth orientation-related processes.

Freedman, Adam P.↗

Lifetimes of lunar satellite orbits

The Space Exploration Initiative has generated a renewed interest in lunar mission planning. The lunar missions currently under study, unlike the Apollo missions, involve long stay times. Several lunar gravity models have been formulated, but mission planners do not have enough confidence in the proposed models to conduct detailed studies of missions with long stay times. In this report, a particular lunar gravitational model, the Ferrari 5 x 5 model, was chosen to determine the lifetimes for 100-km and 300-km perilune altitude, near-circular parking orbits. The need to analyze orbital lifetimes for a large number of initial orbital parameters was the motivation for the formulation of a simplified gravitational model from the original model. Using this model, orbital lifetimes were found to be heavily dependent on the initial conditions of the nearly circular orbits, particularly the initial inclination and argument of perilune. This selected model yielded lifetime predictions of less than 40 days for some orbits, and other orbits had lifetimes exceeding a year. Although inconsistencies and limitations are inherent in all existing lunar gravity models, primarily because of a lack of information about the far side of the moon, the methods presented in this analysis are suitable for incorporating the moon's nonspherical gravitational effects on the preliminary design level for future lunar mission planning.

Meyer, Kurt W.↗

Micromechanical models for textile composites

Numerical and analytical micromechanical models are presented to predict the thermoelastic behavior of a textile composite. In the numerical model, the unit-cell is discretized with finite elements, and periodic boundary conditions are imposed between opposite faces of the unit-cell. For a thin textile composite, stress gradients effects through the thickness are demonstrated. The consequent difference in the stiffness and strength behavior of thick and thin composites are discussed. The numerical model is implemented to predict 3-D thermo-elastic constants for a thick textile composite, and the plate thermo-mechanical properties for a thin textile composite. The numerical model is extended to compute the thermal residual microstresses due to processing to predict the composite failure envelopes. An analytical model - Selective Averaging Method (SAM) - is proposed, which is based on a judicious combination of stiffness and compliance averaging to estimate the 3-D elastic constants. Both the models are tested and verified for several examples by comparing the stiffness properties with elasticity solutions and available results.

Sankar, Bhavani V.↗

IM3 SELECT Urbanization Data

IM3 SELECT Urbanization Data Urban fraction is provided in TIF files projected on the WGS84 datum at coarse (1/8 degree) and downscaled (1km) resolutions across the globe for each of three Shared Socioeconomic Pathway (SSP) scenarios corresponding to SSP2, SSP3, and SSP5; and each of two population scenarios corresponding to the default population scenario and an updated population scenario with more detailed projections for the United States. The population projections are provided as CSV files. Folder structure: default_population population urban_fraction coarse SSP2 SSP3 SSP5 downscaled SSP2 SSP3 SSP5united_states_updated_population population urban_fraction coarse SSP2 SSP3 SSP5 downscaled SSP2 SSP3 SSP5 Urban fraction data was produced using the SELECT model v1.0.0 (Gao, J. & O'Neill, B.C. 2019). Default population data derived from Gao, J. & O'Neill, B.C. 2020. Original model outputs produced using the default population data are available from Gao, J. 2020. Updated United States population data derived from Zoraghein, H. & O'Neill, B.C. 2020. Other SELECT input files available at Gao, J. & O'Neill, B.C. 2022.

McManamay, Ryan↗