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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 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
NASA NTRS2015

Second-Moment RANS Model Verification and Validation Using the Turbulence Modeling Resource Website (Invited)

The implementation of the SSG/LRR-omega differential Reynolds stress model into the NASA flow solvers CFL3D and FUN3D and the DLR flow solver TAU is verified by studying the grid convergence of the solution of three different test cases from the Turbulence Modeling Resource Website. The model's predictive capabilities are assessed based on four basic and four extended validation cases also provided on this website, involving attached and separated boundary layer flows, effects of streamline curvature and secondary flow. Simulation results are compared against experimental data and predictions by the eddy-viscosity models of Spalart-Allmaras (SA) and Menter's Shear Stress Transport (SST).

Eisfeld, Bernhard↗
NASA NTRS2003

Modeling and Validation of Damped Plexiglas Windows for Noise Control

Windows are a significant path for structure-borne and air-borne noise transmission in general aviation aircraft. In this paper, numerical and experimental results are used to evaluate damped plexiglas windows for the reduction of structure-borne and air-borne noise transmitted into the interior of an aircraft. In contrast to conventional homogeneous windows, the damped plexiglas windows were fabricated using two or three layers of plexiglas with transparent viscoelastic damping material sandwiched between the layers. Transmission loss and radiated sound power measurements were used to compare different layups of the damped plexiglas windows with uniform windows of the same nominal thickness. This vibro-acoustic test data was also used for the verification and validation of finite element and boundary element models of the damped plexiglas windows. Numerical models are presented for the prediction of radiated sound power for a point force excitation and transmission loss for diffuse acoustic excitation. Radiated sound power and transmission loss predictions are in good agreement with experimental data. Once validated, the numerical models were used to perform a parametric study to determine the optimum configuration of the damped plexiglas windows for reducing the radiated sound power for a point force excitation.

Buehrle, Ralph D.↗
DOE OSTI2019

Wind Energy Instrumentation Atlas

The US Department of Energy (DOE) A2e program is focused on developing the next generation of predictive tools to better understand wind plant performance and help industry lower the overall cost of energy. A formal verification and validation process is required to demonstrate improved accuracy of these new models beyond those currently employed. And a critical part of model validation is utilization of a diverse set of accurate observations of atmospheric forcing and wind plant response. A number of existing data sets that will be used for this purpose, as highlighted by Schreck and Maniaci (2017) but A2e researchers also realize that new datasets will be required to meet validation objectives. As such, plans for new experiments based on model validation priorities (NALU validation plan, 2017) are currently being developed. This document is intended to serve as a reference to experimental study planners that describes the capability, accuracy and resolution of existing and developing measurement technologies to observe quantities of interest for wind plant model validation. Such systems can be broken into two major categories: those that measure the flow field and surrounding atmosphere around and within a wind plant and those that measure the turbine response within the wind plant. The A2e validation team will use this catalogue of instrument capability in conjunction with the validation plan, to choose the optimal set of instruments to be deployed, inform instrument placement and operation and estimate the types of validation that may be gathered through new field campaigns. Where existing instrumentation is deficient, the document will also help guide DOE towards potential areas where instrumentation development is required to meet validation objectives and A2e technology development funding may be required. The domain of interest is the wind plant microscale, within and surrounding a single wind plant, typically, tens of kilometers on a side in horizontal directions and to the top of the atmospheric boundary layer (about 1km) in the vertical. Some observations of dominant mesoscale forcing phenomena are required, with the highest resolution measurements occurring in the wind turbine wakes and on the turbines themselves. The simulation tools to be validated are mesoscale driven large-eddy simulations of the atmosphere with full aeroelastic response of individual turbines within the plant. Use cases vary slightly among tool users, but should focus on the primary end customers of the simulations and research insights, which would be turbine manufacturers, wind plant developers and owners. Broadly speaking their interests are maximizing energy output, while maintaining turbine reliability and lifetime.

17 WIND ENERGY↗
NASA NTRS2003

Structured Uncertainty Bound Determination From Data for Control and Performance Validation

This report attempts to document the broad scope of issues that must be satisfactorily resolved before one can expect to methodically obtain, with a reasonable confidence, a near-optimal robust closed loop performance in physical applications. These include elements of signal processing, noise identification, system identification, model validation, and uncertainty modeling. Based on a recently developed methodology involving a parameterization of all model validating uncertainty sets for a given linear fractional transformation (LFT) structure and noise allowance, a new software, Uncertainty Bound Identification (UBID) toolbox, which conveniently executes model validation tests and determine uncertainty bounds from data, has been designed and is currently available. This toolbox also serves to benchmark the current state-of-the-art in uncertainty bound determination and in turn facilitate benchmarking of robust control technology. To help clarify the methodology and use of the new software, two tutorial examples are provided. The first involves the uncertainty characterization of a flexible structure dynamics, and the second example involves a closed loop performance validation of a ducted fan based on an uncertainty bound from data. These examples, along with other simulation and experimental results, also help describe the many factors and assumptions that determine the degree of success in applying robust control theory to practical problems.

Lim, Kyong B.↗
NASA NTRS2004

The Role of Structural Models in the Solar Sail Flight Validation Process

NASA is currently soliciting proposals via the New Millennium Program ST-9 opportunity for a potential Solar Sail Flight Validation (SSFV) experiment to develop and operate in space a deployable solar sail that can be steered and provides measurable acceleration. The approach planned for this experiment is to test and validate models and processes for solar sail design, fabrication, deployment, and flight. These models and processes would then be used to design, fabricate, and operate scaleable solar sails for future space science missions. There are six validation objectives planned for the ST9 SSFV experiment: 1) Validate solar sail design tools and fabrication methods; 2) Validate controlled deployment; 3) Validate in space structural characteristics (focus of poster); 4) Validate solar sail attitude control; 5) Validate solar sail thrust performance; 6) Characterize the sail's electromagnetic interaction with the space environment. This poster presents a top-level assessment of the role of structural models in the validation process for in-space structural characteristics.

Johnston, John D.↗
DOE OSTI2025

Burst pressure models and validations for thick-walled pipelines containing corrosion defects

Corrosion is one major threat to pipeline integrity. Over the past decades, many corrosion models have been developed for determining the remaining strength of corroded pipelines, including ASME B31.G, Modified B31.G, LPC, PCORRC and their modified models. All these corrosion models are applicable only to large diameter, thin-walled pipelines with a diameter to wall thickness ratio D/t ≥ 20. In practice, many pipelines have a small diameter and thick wall with a D/t ratio < 20, and thus an adequate corrosion model is needed for assessing remaining strength for corroded thick-walled pipelines. This paper briefly reviews the theoretical burst pressure models for defect-free thin and thick-walled pipelines and four representative corrosion assessment models for thin-walled corroded pipelines. On this basis, two modified corrosion models are proposed to thick-walled pipelines in terms of the average shear stress yield theory. To verify the proposed corrosion models, comprehensive validations are performed. Numerical validations include the elastic-plastic finite element analysis to determine burst pressure for pipelines without and with corrosion defects and the model evaluation using a large dataset of available FEA results of burst pressure for machined defects. Experimental validations include a set of burst pressure tests for defect-free thick-walled pipes with different thicknesses and the model evaluation using one large burst dataset for machined defects with flat bottoms and another large dataset for real corrosion defects with curved river bottom profiles. Both numerical and experimental validations show that the proposed corrosion models can more accurately predict the remaining strength for corroded thin and thick-walled pipelines.

Pipeline↗
DOE OSTI2017

Recommended Research Directions for Improving the Validation of Complex Systems Models.

Improved validation for models of complex systems has been a primary focus over the past year for the Resilience in Complex Systems Research Challenge. This document describes a set of research directions that are the result of distilling those ideas into three categories of research -- epistemic uncertainty, strong tests, and value of information. The content of this document can be used to transmit valuable information to future research activities, update the Resilience in Complex Systems Research Challenge's roadmap, inform the upcoming FY18 Laboratory Directed Research and Development (LDRD) call and research proposals, and facilitate collaborations between Sandia and external organizations. The recommended research directions can provide topics for collaborative research, development of proposals, workshops, and other opportunities.

99 GENERAL AND MISCELLANEOUS↗
NASA NTRS2008

CFD Modeling of Superheated Fuel Sprays

An understanding of fuel atomization and vaporization behavior at superheat conditions is identified to be a topic of importance in the design of modern supersonic engines. As a part of the NASA aeronautics initiative, we have undertaken an assessment study to establish baseline accuracy of existing CFD models used in the evaluation of a ashing jet. In a first attempt towards attaining this goal, we have incorporated an existing superheat vaporization model into our spray solution procedure but made some improvements to combine the existing models valid at superheated conditions with the models valid at stable (non-superheat) evaporating conditions. Also, the paper reports some validation results based on the experimental data obtained from the literature for a superheated spray generated by the sudden release of pressurized R134A from a cylindrical nozzle. The predicted profiles for both gas and droplet velocities show a reasonable agreement with the measured data and exhibit a self-similar pattern similar to the correlation reported in the literature. Because of the uncertainty involved in the specification of the initial conditions, we have investigated the effect of initial droplet size distribution on the validation results. The predicted results were found to be sensitive to the initial conditions used for the droplet size specification. However, it was shown that decent droplet size comparisons could be achieved with properly selected initial conditions, For the case considered, it is reasonable to assume that the present vaporization models are capable of providing a reasonable qualitative description for the two-phase jet characteristics generated by a ashing jet. However, there remains some uncertainty with regard to the specification of certain initial spray conditions and there is a need for experimental data on separate gas and liquid temperatures in order to validate the vaporization models based on the Adachi correlation for a liquid involving R134A.

Raju, M. S.↗
NASA NTRS2006

Cryogenic Tank Modeling for the Saturn AS-203 Experiment

A computational fluid dynamics (CFD) model is developed for the Saturn S-IVB liquid hydrogen (LH2) tank to simulate the 1966 AS-203 flight experiment. This significant experiment is the only known, adequately-instrumented, low-gravity, cryogenic self pressurization test that is well suited for CFD model validation. A 4000-cell, axisymmetric model predicts motion of the LH2 surface including boil-off and thermal stratification in the liquid and gas phases. The model is based on a modified version of the commercially available FLOW3D software. During the experiment, heat enters the LH2 tank through the tank forward dome, side wall, aft dome, and common bulkhead. In both model and test the liquid and gases thermally stratify in the low-gravity natural convection environment. LH2 boils at the free surface which in turn increases the pressure within the tank during the 5360 second experiment. The Saturn S-IVB tank model is shown to accurately simulate the self pressurization and thermal stratification in the 1966 AS-203 test. The average predicted pressurization rate is within 4% of the pressure rise rate suggested by test data. Ullage temperature results are also in good agreement with the test where the model predicts an ullage temperature rise rate within 6% of the measured data. The model is based on first principles only and includes no adjustments to bring the predictions closer to the test data. Although quantitative model validation is achieved or one specific case, a significant step is taken towards demonstrating general use of CFD for low-gravity cryogenic fluid modeling.

Grayson, Gary D.↗
NASA NTRS2002

Comparing Satellite Rainfall Estimates with Rain-Gauge Data: Optimal Strategies Suggested by a Spectral Model

Validation of satellite remote-sensing methods for estimating rainfall against rain-gauge data is attractive because of the direct nature of the rain-gauge measurements. Comparisons of satellite estimates to rain-gauge data are difficult, however, because of the extreme variability of rain and the fact that satellites view large areas over a short time while rain gauges monitor small areas continuously. In this paper, a statistical model of rainfall variability developed for studies of sampling error in averages of satellite data is used to examine the impact of spatial and temporal averaging of satellite and gauge data on intercomparison results. The model parameters were derived from radar observations of rain, but the model appears to capture many of the characteristics of rain-gauge data as well. The model predicts that many months of data from areas containing a few gauges are required to validate satellite estimates over the areas, and that the areas should be of the order of several hundred km in diameter. Over gauge arrays of sufficiently high density, the optimal areas and averaging times are reduced. The possibility of using time-weighted averages of gauge data is explored.

Bell, Thomas L.↗
DOE OSTI2015

A Validated Prediction Model for Overall Survival From Stage III Non-Small Cell Lung Cancer: Toward Survival Prediction for Individual Patients

Purpose: Although patients with stage III non-small cell lung cancer (NSCLC) are homogeneous according to the TNM staging system, they form a heterogeneous group, which is reflected in the survival outcome. The increasing amount of information for an individual patient and the growing number of treatment options facilitate personalized treatment, but they also complicate treatment decision making. Decision support systems (DSS), which provide individualized prognostic information, can overcome this but are currently lacking. A DSS for stage III NSCLC requires the development and integration of multiple models. The current study takes the first step in this process by developing and validating a model that can provide physicians with a survival probability for an individual NSCLC patient. Methods and Materials: Data from 548 patients with stage III NSCLC were available to enable the development of a prediction model, using stratified Cox regression. Variables were selected by using a bootstrap procedure. Performance of the model was expressed as the c statistic, assessed internally and on 2 external data sets (n=174 and n=130). Results: The final multivariate model, stratified for treatment, consisted of age, gender, World Health Organization performance status, overall treatment time, equivalent radiation dose, number of positive lymph node stations, and gross tumor volume. The bootstrapped c statistic was 0.62. The model could identify risk groups in external data sets. Nomograms were constructed to predict an individual patient's survival probability ( (www.predictcancer.org)). The data set can be downloaded at (https://www.cancerdata.org/10.1016/j.ijrobp.2015.02.048). Conclusions: The prediction model for overall survival of patients with stage III NSCLC highlights the importance of combining patient, clinical, and treatment variables. Nomograms were developed and validated. This tool could be used as a first building block for a decision support system.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2026

Validating Simulated Models of Energy Consumption by a Battery Electric Motorcoach: A real-world deployment in a harsh climate.

Many efforts have been made to simulate energy consumption of battery electric buses (BEBs) to optimize their deployment into existing fleets. The models produced, however, are rarely validated against real-world consumption data, limiting their generalizability and widespread application to fleets around the US. Furthermore, a major concern specific to BEBs is the effects of harsh climates on their performance. We build upon the state-of-the-art energy consumption modeling techniques developed for BEBs and apply them to a unique geographic context and a unique electrified vehicle. This geography, climate, and vehicle further the existing understanding of the factors affecting medium- and heavy-duty electric vehicles (MHDEVs) by allowing for new relationships to be tested and by assessing the generalizability of known relationships to new contexts. We find that temperature is less predictive of energy consumption for the battery electric motorcoach (BEM) in the case study environment than it is for BEBs in other studies. A mitigating factor that we presume to be working on the relationship between temperature and energy consumption is the fact that the BEM route does not stop between origin and destination to exchange passengers, and in turn, conditioned cabin air. Our model also incorporates wind speed and direction relative to travel, which is a novel contribution of our methodology. Results from our study are helpful for transit service planners, fleet operators, and logistics firms for improving their ability to predict performance of potential deployments of MHDEVs into existing operations.

32 - ENERGY CONSERVATION, CONSUMPTION, AND UTILIZA↗
DOE OSTI2020

FAST.Farm Development and Validation of Structural Load Prediction Against Large Eddy Simulations

FAST.Farm is a mid-fidelity engineering tool developed by the National Renewable Energy Laboratory targeted at accurately and efficiently predicting wind turbine power production and structural loading in wind farm settings, including wake interactions between turbines. FAST.Farm is based on several principles of the dynamic wake meandering (DWM) model, but also addresses limitations of previous DWM implementations. Previous FAST.Farm studies have shown the similarities and differences between FAST.Farm and large eddy simulations for rigid turbine cases. The objective of this work is to quantify the ability of FAST.Farm to accurately predict turbine structural response in a small wind farm. This is done by comparing FAST.Farm structural response to SOWFA-OpenFAST results for three laterally-aligned turbines. The purpose of this study is to characterize the similarities and differences between FAST.Farm and a higher fidelity model for predicting turbine structural response in a wind farm for differing atmospheric inflows. Strong statistical agreement was found between FAST.Farm and SOWFA-OpenFAST structural response for the non-waked upstream turbine, and good agreement was found for the downstream turbines for most structural quantities. Higher differences were seen for downstream turbines with low ambient turbulence intensity or yawed turbines, suggesting areas for FAST.Farm wake dynamics modeling improvements. For all cases and turbines, small statistical differences were seen between blade deflections and bending moments, with larger differences for tower-top and tower-base bending moments. Overall, the results establish confidence for applying FAST.Farm to wind farm power and loads analyses and identify areas where further model validations and model improvements should be targeted.

49 EE - Wind and Water Power Program - Wind (EE-4W↗
DOE OSTI2016

Using Measured Plane-of-Array Data Directly in Photovoltaic Modeling: Methodology and Validation

Measured plane-of-array (POA) irradiance may provide a lower-cost alternative to standard irradiance component data for photovoltaic (PV) system performance modeling without loss of accuracy. Previous work has shown that transposition models typically used by PV models to calculate POA irradiance from horizontal data introduce error into the POA irradiance estimates, and that measured POA data can correlate better to measured performance data. However, popular PV modeling tools historically have not directly used input POA data. This paper introduces a new capability in NREL's System Advisor Model (SAM) to directly use POA data in PV modeling, and compares SAM results from both POA irradiance and irradiance components inputs against measured performance data for eight operating PV systems.

14 SOLAR ENERGY↗
DOE OSTI2020

BISON High Burnup Structure Modeling Capabilities Validated with a Selection of the Halden IFA-650 Rods

The U.S. Department of Energy (DOE)’s Nuclear Energy Advanced Modeling and Simulation (NEAMS)program aims to develop predictive capabilities using computational methods for the analysis and design of advanced reactor and fuel cycle systems. This program has been supporting the development of BISON, a high-fidelity and high-resolution fuel performance tool at the engineering scale. This document continues analysis and refinement of capabilities added to BISON early this calendar year in regards to the incorporation of capabilities applicable to extended burnups in response to industry interest. Details are provided on high burnup thermal conductivity models, a refitting of the high-burnup structure (HBS) porosity formation model to include additional data, the coupling of the HBS volume fraction model to thermal conductivity and fine fragmentation models, and validation activities. The IFA-650.4 and IFA-650.9 loss of coolant accident (LOCA) analyses are revisited with the latest developments in this report. A new validation case, IFA-650.14 has also been added to the BISON test suite.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2015

SU-E-T-546: Modeling and Validation of the a New Proton Therapy System Using a Monte-Carlo Environment Optimized for Protons

8 particle histories were run. Results: Range measurements of the Monte-Carlo simulations matched the measured data within 1mm. Distal fall-off of the simulated fields matched within <1mm. Lateral penumbra and field size measurements of the standard-sized square and half-beam blocked fields matched within 1mm at all three planes compared. A small difference was seen in the in-air profiles at doses <0%. The suspected cause of the difference was the aperture shape. The measured data utilized a divergent aperture. The Monte-Carlo calculation used a non-divergent aperture. Conclusion: The validation measurements indicate that we were able to accurately model the MEVION s250 Proton therapy system using Monte-Carlo Calculations. This may reduce the commissioning time for future users. Purpose: Monte-Carlo modeling is an important tool for understanding the behavior of therapeutic proton beams in a heterogeneous media such as the patient. To gain confidence that a Monte-Carlo model is accurate in complex geometries and media, it must first be compared with measurement in simple situations. This study documents the validation of our Monte-Carlo Model. Methods: A model of the MEVION s250 Proton therapy system was created in the TOPAS Monte-Carlo environment using machine geometry and field shaping system information provided by the vendor. For each of 24 options, validation of the TOPAS model was performed by comparing the dose scored by TOPAS to the dose measurements obtained during the commissioning of the treatment planning system. The measurements compared consisted of: pristine peak depth-dose profiles, in-air profiles for a standard-sized square field (20cm×20cm or 10cm×10cm depending on the maximum field size for each option) at isocenter and at 20cm upstream and downstream of isocenter, and in-air profiles with a half-beam blocked aperture at isocenter and at 20cm upstream and downstream of isocenter. For all Monte-Carlo simulations,.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
NASA NTRS2024

Intermountain West Wildland Fires: Mapping Tree Mortality and Burn Patches using NASA Earth Observations to Determine Fire Risk and Inform Fire Management Practices

Within the intermountain west, monitoring fuel loads is a major concern for wildland fire management efforts. To address this concern, we partnered with the U.S. Forest Service to inform the agency which forested areas should be prioritized for prescribed burning and fuel reduction near human communities in the Bridger-Teton National Forest, Wyoming. We created burn maps, fuel load maps, and a tutorial document to identify forest impact trends and provide the partner with the tools to replicate project methods for expansion to other wildfire crisis strategy sites. These end products were made using two NASA Earth observations: Landsat 8 Operational Land Imager and Shuttle Radar Topography Mission. Based on our random forest analysis, our maps identified 998 acres within the Wildland Urban Interface that are predicted to have high fuel loading and high burn severity within the Bridger-Teton National Forest. Forested areas closer to heavily populated areas such as Jackson, Kelly, Moran, New Forks Lake, and Star Valley Ranch should be prioritized for fuel reduction. However, our random forest model analysis was limited to using vegetation and topographical indices with no field data for model validation. Therefore, future studies should use field data for model validation to improve model accuracy and additionally incorporate Global Ecosystem Dynamics Investigation data into models to create better predictions of forested areas with high fuel load and high burn severity.

Remote Sensing↗