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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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At least 361 records · Page 20

Barotropic Tidal Predictions and Validation in a Relocatable Modeling Environment

Under funding from the Office of Naval Research (ONR), the Mississippi State University Center for Air Sea Technology (CAST) has been working on developing a Relocatable Modeling Environment (RME) to provide a uniform and unbiased infrastructure for efficiently configuring numerical models in any geographic or oceanic region. Under Naval Oceanographic Office (NAVOCEANO) funding, the model was implemented and tested for NAVOCEANO use. With our current emphasis on ocean tidal modeling, CAST has adopted the Colorado University's numerical ocean model, known as CURReNTSS (Colorado University Rapidly Relocatable Nestable Storm Surge) Model, as the model of choice. During the RME development process, CURReNTSS has been relocated to several coastal oceanic regions, providing excellent results that demonstrate its veracity. This report documents the model validation results and provides a brief description of the Graphic user Interface.

Mehra, Avichal↗

Validation of GNSS Multipath Model for Space Proximity Operations Using the Hubble Servicing Mission 4 Experiment

In the rendezvous and docking of spacecraft, GNSS signals can reflect off the target vehicle and cause large errors in the chaser vehicle receiver at ranges below a few hundred meters. It has been proposed that the additional ray paths, or multipath, be used as a source of information about the state of the target relative to the receiver. With Hubble Servicing Mission 4 as a case study, electromagnetic ray tracing has been used to construct a model of reflected signals from known geometry. Oscillations in the prompt correlator power due to multipath, known as multipath fading, are studied as a means of model validation. Agreement between the measured and simulated multipath fading serves to confirm the presence of signals reflected off the target spacecraft that might be used for relative navigation.

targets↗

Validation of GNSS Multipath Model for Space Proximity Operations Using the Hubble Servicing Mission 4 Experiment

In the rendezvous and docking of spacecraft, GNSS signals can reflect off the target vehicle and cause prohibitively large errors in the chaser vehicle receiver at ranges below 200 meters. It has been proposed that the additional ray paths, or multipath, be used as a source of information about the state of the target relative to the receiver. With Hubble Servicing Mission 4 as a case study, electromagnetic ray tracing has been used to construct a model of reflected signals from known geometry. Oscillations in the prompt correlator power due to multipath, known as multipath fading, are studied as a means of model validation. Agreement between the measured and simulated multipath fading serves to confirm the presence of signals reflected off the target spacecraft that might be used for relative navigation.

Ashman, Ben↗

Wave Energy Converter Power Take-Off Modeling and Validation From Experimental Bench Tests

This article describes the implementation of a new numerical model of the power take-off system installed in the Monterey Bay Aquarium Research Institute wave energy converter, a device developed to provide power to various oceanic research missions. The simultaneous presence of hydraulic, pneumatic, and electrical subsystems in the power take-off system represents a significant challenge in forging an accurate model able to replicate the main dynamic characteristics of the system. The validation of the new numerical model is addressed by comparing simulations with the measurements obtained during a series of bench tests. Data from the bench tests show good agreement with the numerical model. The validated model provides deeper insights into the complex nonlinear dynamics of the power take-off system and will support further performance improvements in the future.

16 TIDAL AND WAVE POWER↗

Experimental validation of multiphysics model simulations of the thermal response of a cement clinker rotary kiln at laboratory scale

Abstract An increasing demand for buildings, transportation systems and civil infrastructure development has driven expansion of cement consumption world‐wide, producing a significant increase in related global energy demand. With approximately 7% of the world‐wide industrial energy consumption (10.7 exajoules [EJ]), the cement industry is the third most energy intensive industrial processes and a key component for concrete, the most consumed composite material in the global construction industry. In cement manufacturing, the cement kiln accounts for most of the energy consumption in the production process. As the heart of a cement plant, the cement kiln is where the kiln feed primarily containing calcium oxide (CaO), silica (SiO 2 ), alumina (Al 2 O 3 ), and iron (Fe 2 O 3 ) are thermally and chemically transformed into clinker minerals. The presented work developed a multiphysics model, designed and built a laboratory‐scale rotary cement clinker kiln, and produced cement clinker at laboratory‐scale. The model was developed to study the interaction between the various thermal, fluid dynamic and chemical interactions involved in the sintering process used to form Portland cement clinker in an effort to reduce energy use. The analytical model was validated through experimental testing using a unique laboratory‐scale rotary cement kiln developed during the investigation. Also demonstrated was the feasibility of producing clinker at laboratory scale. This modeling and lab scale tests were designed to better understand the clinker sintering process so that operational and quality decisions can be made to optimize energy consumption without compromising cement clinker quality. The computational fluid dynamics modeling was developed in COMSOL Multiphysics 6.0. The characteristics of the combustion fluid flow, concentration of species, temperature and heat transfer were studied for a turbulent flow of methane (CH 4 ) gas and oxygen (O 2 ). Theory suggests that heat transfer impacts the cement production process but the multiphysics model more accurately describes the convection, conduction, and radiant heat transfer in the kilning process and thus allows for a better understanding of the energy exchange driving the chemical reactions that produce Portland cement. Clinker minerals were formed because of appropriate burning conditions implemented during experimental model validation.

Tabares, Juan David↗

Calibration verification for stochastic agent-based disease spread models

Accurate disease spread modeling is crucial for identifying the severity of outbreaks and planning effective mitigation efforts. To be reliable when applied to new outbreaks, model calibration techniques must be robust. However, current methods frequently forgo calibration verification (a stand-alone process evaluating the calibration procedure) and instead use overall model validation (a process comparing calibrated model results to data) to check calibration processes, which may conceal errors in calibration. In this work, we develop a stochastic agent-based disease spread model to act as a testing environment as we test two calibration methods using simulation-based calibration, which is a synthetic data calibration verification method. The first calibration method is a Bayesian inference approach using an empirically-constructed likelihood and Markov chain Monte Carlo (MCMC) sampling, while the second method is a likelihood-free approach using approximate Bayesian computation (ABC). Simulation-based calibration suggests that there are challenges with the empirical likelihood calculation used in the first calibration method in this context. These issues are alleviated in the ABC approach. Despite these challenges, we note that the first calibration method performs well in a synthetic data model validation test similar to those common in disease spread modeling literature. We conclude that stand-alone calibration verification using synthetic data may benefit epidemiological researchers in identifying model calibration challenges that may be difficult to identify with other commonly used model validation techniques.

60 APPLIED LIFE SCIENCES↗

Test Cases for Modeling and Validation of Structures with Piezoelectric Actuators

A set of benchmark test articles were developed to validate techniques for modeling structures containing piezoelectric actuators using commercially available finite element analysis packages. The paper presents the development, modeling, and testing of two structures: an aluminum plate with surface mounted patch actuators and a composite box beam with surface mounted actuators. Three approaches for modeling structures containing piezoelectric actuators using the commercially available packages: MSC/NASTRAN and ANSYS are presented. The approaches, applications, and limitations are discussed. Data for both test articles are compared in terms of frequency response functions from deflection and strain data to input voltage to the actuator. Frequency response function results using the three different analysis approaches provided comparable test/analysis results. It is shown that global versus local behavior of the analytical model and test article must be considered when comparing different approaches. Also, improper bonding of actuators greatly reduces the electrical to mechanical effectiveness of the actuators producing anti-resonance errors.

Reaves, Mercedes C.↗

Integrated Modeling Methodology Validation Using the Micro-Precision Interferometer Testbed

This paper validates the integrated modeling methodology used for design and performance evaluation of complex opto-mechanical systems, particularly spaceborne interferometers. The methodology integrates structural modeling, optical modeling, and control system design into a common environment, the Integrated Modeling of Optical Systems (IMOS) software package.

opto-mechanical↗

Collisional-Radiative Models of Neutral and Singly-Ionized Xenon in Hall Thrusters: Experimental Validation and Model Investigations

The recently developed collisional radiative (CR) models for neutral xenon (Xe I) and singly charged xenon ion (Xe II) described by Chaplin et al. in the paper "Insights from Collisional-Radiative Models of Neutral and Singly-Ionized Xenon in Hall Thrusters" also submitted to the 2021 AIAA Propulsion and Energy Forum are more thoroughly investigated. Comparisons between the existing and recently developed JPL Xe I CR models are done and reasons for discrepancies between the two models are explored. An experiment to validate the Xe II CR model is carried out in the anode region of the UCLA Plasma interactions facility. The Xe II CR model is applied to measured xenon ion emission line intensities to determine electron temperature and density. Spatial resolution of these optical measurements is obtained through an Abel inversion for direct comparison to Langmuir probe results. Although the measured electron densities were on the order of $10^{17}$ m$^{-3}$ and the Xe II CR model is most suitable for use with densities above $10^{18}$ m$^{-3}$ due to the strong dependence of the line ratios on electron temperature in that regime, initial results from the validation experiment show reasonable agreements between the optical and Langmuir probe results. The 441 nm to 605 nm line ratio appears to have the most promise for non-intrusive electron temperature measurements with the Xe II CR model. Shortcomings of the Xe II CR model revealed in the validation experiment are to be explored further.

Lobbia, Robert B.↗

Thermal modeling of three lakes within the continuous permafrost zone in Alaska using the LAKE 2.0 model

Abstract. Lakes in the Arctic are important reservoirs of heat with much lower albedo in summer and greater absorption of solar radiation than surrounding tundra vegetation. In the winter, lakes that do not freeze to their bed have a mean annual bed temperature >0 ∘C in an otherwise frozen landscape. Under climate warming scenarios, we expect Arctic lakes to accelerate thawing of underlying permafrost due to warming water temperatures in the summer and winter. Previous studies of Arctic lakes have focused on ice cover and thickness, the ice decay process, catchment hydrology, lake water balance, and eddy covariance measurements, but little work has been done in the Arctic to model lake heat balance. We applied the LAKE 2.0 model to simulate water temperatures in three Arctic lakes in northern Alaska over several years and tested the sensitivity of the model to several perturbations of input meteorological variables (precipitation, shortwave radiation, and air temperature) and several model parameters (water vertical resolution, sediment vertical resolution, depth of soil column, and temporal resolution). The LAKE 2.0 model is a one-dimensional model that explicitly solves vertical profiles of water state variables on a grid. We used a combination of meteorological data from local and remote weather stations, as well as data derived from remote sensing, to drive the model. We validated modeled water temperatures with data of observed lake water temperatures at several depths over several years for each lake. Our validation of the LAKE 2.0 model is a necessary step toward modeling changes in Arctic lake ice regimes, lake heat balance, and thermal interactions with permafrost. The sensitivity analysis shows us that lake water temperature is not highly sensitive to small changes in air temperature or precipitation, while changes in shortwave radiation and large changes in precipitation produced larger effects. Snow depth and lake ice strongly affect water temperatures during the frozen season, which dominates the annual thermal regime of Arctic lakes. These findings suggest that reductions in lake ice thickness and duration could lead to more heat storage by lakes and enhanced permafrost degradation.

Clark, Jason A. (ORCID:0000000248105261)↗

An experimentally validated mesoscale model for the effective thermal conductivity of U-Zr fuels

An experimentally validated mesoscale model was developed to simulate the effective thermal conductivity (ETC) of metallic U and U–Zr nuclear fuels. The effects of microstructure, temperature, composition, and interfacial thermal resistance (ITR) were investigated. Companion experiments were conducted to validate the model. The numerical simulations clearly demonstrate that accounting for the interface (Kapitza) thermal resistance and Zr precipitation is necessary to improve the model predictions. The dependence of the effective Kapitza resistance of depleted-U and U-10Zr on temperature was determined. Finally, for both materials, the largest difference between the model calculations and the experimental data was about 4.5%, which is within the precision of the experimental measurements.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Validation of Exploding Wire Tests Using Alegra-NG

Exploding wire tests are used to characterize materials undergoing high voltage loading and to validate computational models in a simple configuration. In this report, the materials emphasized are gold, aluminum, copper and nickel wires. Model validation is presented using the nominal model (no uncertainty) in the form of heat maps (per material) that show model bias across scalar quantities and initial voltage. Mesh convergence and uncertainty quantification is also presented.

36 MATERIALS SCIENCE↗

Uncertainty quantification of fireball features extracted from nuclear test films using computer vision

Films from the US’s historic nuclear testing era comprise the only extensive collection of imagery depicting high-yield detonations. These films offer unique insights into the characteristics of flows occurring on scales that are difficult to replicate experimentally, and they are a valuable source of data for the validation of models used to describe nuclear detonations. In recent work, we implemented modern computer vision and machine learning techniques to extract features of the fireball following nuclear detonation. With a training dataset of fireball films, we fine-tuned a You Only Look Once 11 (YOLO11) model to detect and track the fireball. Applied to a video, the outer bounding box produced in each frame by YOLO11 is used as an input prompt to Meta’s Segment Anything Model 2 (SAM2), which is shown to accurately predict the boundary of the fireball over time with high resolution. These state-of-the-art computer vision foundation models exhibit impressive visual accuracy in their results but lack an output of values that robustly quantify uncertainty in scientific applications. In this paper, we develop procedures for uncertainty quantification of extracted fireball features. We outline the application of a parallel attention mechanism to calculate uncertainty ranges that complement and better pose model validation data. This higher quality fireball validation data may serve to improve prognostic models describing nuclear detonations in support of nuclear forensic and emergency response activities.

Khristy, Joel [ORNL] (ORCID:0000000209963060)↗

Verification, Validation, and Solution Quality in Computational Physics: CFD Methods Applied to Ice Sheet Physics

Procedures and methods for veri.cation of coding algebra and for validations of models and calculations used in the aerospace computational fluid dynamics (CFD) community would be ef.cacious if used by the glacier dynamics modeling community. This paper presents some of those methods, and how they might be applied to uncertainty management supporting code veri.cation and model validation for glacier dynamics. The similarities and differences between their use in CFD analysis and the proposed application of these methods to glacier modeling are discussed. After establishing sources of uncertainty and methods for code veri.cation, the paper looks at a representative sampling of veri.cation and validation efforts that are underway in the glacier modeling community, and establishes a context for these within an overall solution quality assessment. Finally, a vision of a new information architecture and interactive scienti.c interface is introduced and advocated.

Thompson, David E.↗

Plasma Reactor Modeling and Validation Experiments

Plasma processing is a key processing stop in integrated circuit manufacturing. Low pressure, high density plum reactors are widely used for etching and deposition. Inductively coupled plasma (ICP) source has become popular recently in many processing applications. In order to accelerate equipment and process design, an understanding of the physics and chemistry, particularly, plasma power coupling, plasma and processing uniformity and mechanism is important. This understanding is facilitated by comprehensive modeling and simulation as well as plasma diagnostics to provide the necessary data for model validation which are addressed in this presentation. We have developed a complete code for simulating an ICP reactor and the model consists of transport of electrons, ions, and neutrals, Poisson's equation, and Maxwell's equation along with gas flow and energy equations. Results will be presented for chlorine and fluorocarbon plasmas and compared with data from Langmuir probe, mass spectrometry and FTIR.

Meyyappan, M.↗

Predicting Pilot Error in Nextgen: Pilot Performance Modeling and Validation Efforts

We review 25 articles presenting 5 general classes of computational models to predict pilot error. This more targeted review is placed within the context of the broader review of computational models of pilot cognition and performance, including such aspects as models of situation awareness or pilot-automation interaction. Particular emphasis is placed on the degree of validation of such models against empirical pilot data, and the relevance of the modeling and validation efforts to Next Gen technology and procedures.

pilot error↗