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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 1,729 records · Page 96
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Controls on methane expulsion during melting of natural gas hydrate systems. Topic area 2

1.1. Project Goal The project goal is to predict, given characteristic climate-induced temperature change scenarios, the conditions under which gas will be expelled from existing accumulations of gas hydrate into the shallow ocean or directly to the atmosphere. When those conditions are met, the fraction of the gas accumulation that escapes and the rate of escape shall be quantified. The predictions shall be applicable in Arctic regions and in gas hydrate systems at the up dip limit of the stability zone on continental margins. The behavior shall be explored in response to two warming scenarios: longer term change due to sea level rise (e.g. 20 thousand years) and shorter term due to atmospheric warming by anthropogenic forcing (decadal time scale). 1.2. Project Objectives During the first budget period, the objectives are to review and categorize the stability state of existing well-studied hydrate reservoirs, develop conceptual and numerical models of the melting process, and to design and conduct laboratory experiments that dissociate methane hydrate in a model sediment column by systematically controlling the temperature profile along the column. The final objective of the first budget period shall be to validate the models against the experiments. In the second budget period, the objectives are to develop a model of gas flow into sediment in which hydrate is thermodynamically stable, and conduct laboratory experiments of this process to validate the model. The developed models shall be used to quantify the rate and volume of gas that escapes from dissociating hydrate accumulations. In addition, specific scaled simulations characteristic of Arctic regions and regions near the stability limit at continental margins shall be performed. 1.3. Project Background and Rationale The central hypothesis proposed is that hydrate melting (dissociation) due to climate change generates free gas that can, under certain conditions, propagate through the gas hydrate stability zone and vent at the seafloor. Gas venting through the regional hydrate stability zone is accomplished by alteration of the regional equilibrium conditions (creation of three phase conditions) by increased salinity and heat due to hydrate formation, due to gas fracturing, or a combination of both. This research will explore the controls on whether methane reaches the seafloor (or atmosphere) as the original hydrate deposit dissociates and what the magnitude of these fluxes are. This hypothesis has significant implications for the forcings and feedbacks associated with climate change. It is described below the observations and models that have led to formulating this hypothesis.

03 NATURAL GAS↗
DOE OSTI2024

PV Performance Modeling and Stakeholder Engagement (Final Technical Report)

This core capability project’s objective is to increase the value of photovoltaic (PV) performance models by improving their functionality, demonstrating, and quantifying their validity, and offering a wide range of stakeholder engagement opportunities. In FY22-24, we developed new and improved modeling algorithms and functions to represent PV performance more accurately in a variety of environments and conditions. The “Model parameter toolkit” was developed and includes functions to translate between different module temperature models, incidence angle modifier models, and single-diode models. A new modeling capability named “PV Atlas” was also developed leveraging Sandia’s High Performance Computing resources. This capability allows us to investigate several questions and provide climate-specific best practices and geographic data files; all these are hosted on an interactive website on Sandia’s GitHub and can be used for training, system optimization, or to provide best practices for uncertainty reduction. For model validation, we published high-quality PV performance, and weather data; these data are well documented, filtered, and processed for quality and include examples on how to run PV simulations. We also developed well documented, standardized methods for validating PV models and ran independent model validation and 2 blind modeling intercomparisons engaging with 49 organizations from 17 countries. We co-led and contributed to a growing, well documented and maintained suite of open-source functions for PV modeling (i.e., the pvlib-python) and we outreached to the PV modeling stakeholders via the PVPMC workshops and web resources. In addition, this project supported US representation and leadership for the International Energy Agency (IEA) PVPS Task 13; specifically, members of our team led and supported 3 subtasks on: 1) Best practices for the optimization of bifacial photovoltaic tracking, 2) Extreme weather events and their multiple impact on PV power plants: Risks, failure mechanisms and mitigation strategies, and 3) Best practice guidelines for the use of economic and technical Key Performance Indicators (KPIs). This project resulted in the publications of 14 peer reviewed journal papers, 37 conference presentations, 6 SAND reports, 5 public datasets and 6 new webpages on the PVPMC website. It supported the release of 13 pvlib-python versions where 28 enhancements were from this PV Performance Modeling project. We co-organized 5 PVPMC workshops in FY22-24 with the participation of 214 unique institutions and around 700 participants. The PVPMC website was redesigned, and its reliability was improved; it receives over 50,000 visitors/year from 202 unique countries.

14 SOLAR ENERGY↗
DOE OSTI2019

An integrated two-dimensional modeling method for predicting ductility of thin-walled die cast magnesium

In this paper, a two-dimensional (2D) microstructure-based modeling method is developed in order to predict the ductility of a thin-walled high pressure die cast magnesium (Mg) by considering the three-dimensional (3D) thru-thickness pore distributions. For this purpose, a series of 3D synthetic microstructure-based finite element models and the corresponding 2D models are first generated with various pore volume fractions, pore size distributions and pore shapes. The input material properties for the 2D models are determined based on the 3D cubic model with a spherical pore and the generalized Neuber’s rule. Based on the resulting ductility of the 3D and 2D models, a 3D/2D ductility correlation curve is developed as a function of the characteristics/shape of the input fracture strain curve used in the 3D model. The validity of the ductility correlation curve is examined with casting samples with actual microstructures. Here, the results show that the suggested 2D modeling methodology can be used together with the ductility correlation curve in predicting the ductility of thin-walled Mg castings.

36 MATERIALS SCIENCE↗
DOE OSTI2013

C6 plate puncture testing report.

There are numerous scenarios where critical systems could be subject to penetration by projectiles or fixed objects (e.g., collision, natural disaster, act of terrorism, etc.). It is desired to use computational models to examine these scenarios and make risk-informed decisions; however, modeling of material failure is an active area of research, and new models must be validated with experimental data. The purpose of this report is to document the experimental work performed from FY07 through FY08 on the Campaign Six Plate Puncture project. The goal of this project was to acquire experimental data on the puncture and penetration of metal plates for use in model validation. Of particular interest is the PLH failure model also known as the multilinear line segment model. A significant amount of data that will be useful for the verification and validation of computational models of ductile failure were collected during this project were collected and documented herein; however, much more work remains to be performed, collecting additional experimental data that will further the task of model verification.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2015

Predicting Overall Survival After Stereotactic Ablative Radiation Therapy in Early-Stage Lung Cancer: Development and External Validation of the Amsterdam Prognostic Model

Purpose: A prognostic model for 5-year overall survival (OS), consisting of recursive partitioning analysis (RPA) and a nomogram, was developed for patients with early-stage non-small cell lung cancer (ES-NSCLC) treated with stereotactic ablative radiation therapy (SABR). Methods and Materials: A primary dataset of 703 ES-NSCLC SABR patients was randomly divided into a training (67%) and an internal validation (33%) dataset. In the former group, 21 unique parameters consisting of patient, treatment, and tumor factors were entered into an RPA model to predict OS. Univariate and multivariate models were constructed for RPA-selected factors to evaluate their relationship with OS. A nomogram for OS was constructed based on factors significant in multivariate modeling and validated with calibration plots. Both the RPA and the nomogram were externally validated in independent surgical (n=193) and SABR (n=543) datasets. Results: RPA identified 2 distinct risk classes based on tumor diameter, age, World Health Organization performance status (PS) and Charlson comorbidity index. This RPA had moderate discrimination in SABR datasets (c-index range: 0.52-0.60) but was of limited value in the surgical validation cohort. The nomogram predicting OS included smoking history in addition to RPA-identified factors. In contrast to RPA, validation of the nomogram performed well in internal validation (r{sup 2}=0.97) and external SABR (r{sup 2}=0.79) and surgical cohorts (r{sup 2}=0.91). Conclusions: The Amsterdam prognostic model is the first externally validated prognostication tool for OS in ES-NSCLC treated with SABR available to individualize patient decision making. The nomogram retained strong performance across surgical and SABR external validation datasets. RPA performance was poor in surgical patients, suggesting that 2 different distinct patient populations are being treated with these 2 effective modalities.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2024

Computationally evaluating high-yield metabolites for sustainable aviation fuel (SAF) using machine learning

The computational tool described in this report helps identify promising biological pathways that produce SAF platform molecules (either a drop-in SAF, or a precursor that can be easily converted to a drop-in SAF). The workflow the computational tool follows first identifies possible biological pathways from a user-defined metabolite. These pathways may, or may not lead to a SAF platform molecule, thus the second step involves insilico testing of the end product of each pathway to assess whether it is, or is not, a SAF platform molecule. The identification of biological pathways performed in the first step is facilitated by linking the metabolite to a biological reaction database. Pathways are found by identifying pathways in the reaction database that include the metabolite. The computational tool includes an alternative way to find pathways. The alternative way develops a Flux Balanced Analysis (FBA), and modifying the FBA to include reactions that transform the metabolite. These modifications serve as a basis for understanding, in a semi-quantitative way, if there is an increase in the flux to desirable products. The second step, in silico testing of the end-products, is accomplished by estimating key physical properties relevant to SAF. When good models are available, we have integrated those models into the computational tool. In a few instances, we have developed our own models. In all instances, we have validated the models against available measured data. Finally, we have evaluated the effectiveness of our computational tool by genetically engineering Rhodosporidium toruloides. Validation occurred without the use of a FBA, and further validation is required.

09 BIOMASS FUELS↗
DOE OSTI2015

SU-E-J-244: Development and Validation of a Knowledge Based Planning Model for External Beam Radiation Therapy of Locally Advanced Non-Small Cell Lung Cancer

Purpose: The study aims to develop and validate a knowledge based planning (KBP) model for external beam radiation therapy of locally advanced non-small cell lung cancer (LA-NSCLC). Methods: RapidPlan™ technology was used to develop a lung KBP model. Plans from 65 patients with LA-NSCLC were used to train the model. 25 patients were treated with VMAT, and the other patients were treated with IMRT. Organs-at-risk (OARs) included right lung, left lung, heart, esophagus, and spinal cord. DVH and geometric distribution DVH were extracted from the treated plans. The model was trained using principal component analysis and step-wise multiple regression. Box plot and regression plot tools were used to identify geometric outliers and dosimetry outliers and help fine-tune the model. The validation was performed by (a) comparing predicted DVH boundaries to actual DVHs of 63 patients and (b) using an independent set of treatment planning data. Results: 63 out of 65 plans were included in the final KBP model with PTV volume ranging from 102.5cc to 1450.2cc. Total treatment dose prescription varied from 50Gy to 70Gy based on institutional guidelines. One patient was excluded due to geometric outlier where 2.18cc of spinal cord was included in PTV. The other patient was excluded due to dosimetric outlier where the dose sparing to spinal cord was heavily enforced in the clinical plan. Target volume, OAR volume, OAR overlap volume percentage to target, and OAR out-of-field volume were included in the trained model. Lungs and heart had two principal component scores of GEDVH, whereas spinal cord and esophagus had three in the final model. Predicted DVH band (mean ±1 standard deviation) represented 66.2±3.6% of all DVHs. Conclusion: A KBP model was developed and validated for radiotherapy of LA-NSCLC in a commercial treatment planning system. The clinical implementation may improve the consistency of IMRT/VMAT planning.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Computational Modeling of Micrometastatic Breast Cancer Radiation Dose Response

Purpose: Prophylactic cranial irradiation (PCI) involves giving radiation to the entire brain with the goals of reducing the incidence of brain metastasis and improving overall survival. Experimentally, we have demonstrated that PCI prevents brain metastases in a breast cancer mouse model. We developed a computational model to expand on and aid in the interpretation of our experimental results. Methods and Materials: MATLAB was used to develop a computational model of brain metastasis and PCI in mice. Model input parameters were optimized such that the model output would match the experimental number of metastases per mouse from the unirradiated group. An independent in vivo–limiting dilution experiment was performed to validate the model. The effect of whole brain irradiation at different measurement points after tumor cells were injected was evaluated in terms of the incidence, number of metastases, and tumor burden and was then compared with the corresponding experimental data. Results: In the optimized model, the correlation between the number of metastases per mouse and the experimental fits was >95. Our attempt to validate the model with a limiting dilution assay produced 99.9% correlation with respect to the incidence of metastases. The model accurately predicted the effect of whole-brain irradiation given 3 weeks after cell injection but substantially underestimated its effect when delivered 5 days after cell injection. The model further demonstrated that delaying whole-brain irradiation until the development of gross disease introduces a dose threshold that must be reached before a reduction in incidence can be realized. Conclusions: Our computational model of mouse brain metastasis and PCI correlated strongly with our experiments with unirradiated mice. The results further suggest that early treatment of subclinical disease is more effective than irradiating established disease.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2015

Predicting chemically-induced skin reactions. Part I: QSAR models of skin sensitization and their application to identify potentially hazardous compounds

Repetitive exposure to a chemical agent can induce an immune reaction in inherently susceptible individuals that leads to skin sensitization. Although many chemicals have been reported as skin sensitizers, there have been very few rigorously validated QSAR models with defined applicability domains (AD) that were developed using a large group of chemically diverse compounds. In this study, we have aimed to compile, curate, and integrate the largest publicly available dataset related to chemically-induced skin sensitization, use this data to generate rigorously validated and QSAR models for skin sensitization, and employ these models as a virtual screening tool for identifying putative sensitizers among environmental chemicals. We followed best practices for model building and validation implemented with our predictive QSAR workflow using Random Forest modeling technique in combination with SiRMS and Dragon descriptors. The Correct Classification Rate (CCR) for QSAR models discriminating sensitizers from non-sensitizers was 71–88% when evaluated on several external validation sets, within a broad AD, with positive (for sensitizers) and negative (for non-sensitizers) predicted rates of 85% and 79% respectively. When compared to the skin sensitization module included in the OECD QSAR Toolbox as well as to the skin sensitization model in publicly available VEGA software, our models showed a significantly higher prediction accuracy for the same sets of external compounds as evaluated by Positive Predicted Rate, Negative Predicted Rate, and CCR. These models were applied to identify putative chemical hazards in the Scorecard database of possible skin or sense organ toxicants as primary candidates for experimental validation. - Highlights: • It was compiled the largest publicly-available skin sensitization dataset. • Predictive QSAR models were developed for skin sensitization. • Developed models have higher prediction accuracy than OECD QSAR Toolbox. • Putative chemical hazards in the Scorecard database were found using our models.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

A two-set order parameters phase-field modeling of crack deflection/penetration in a heterogeneous microstructure

Modeling of crack deflection/penetration or manifested as intergranular/transgranular fracture in polycrystals has long been a challenge in both fracture mechanics and materials science. A phase-field model formulated with two-set order parameters describing the crack field and the microstructure field respectively, is herein established to investigate the competition between crack penetration and deflection at an interface. The advantages of the proposed model are three-fold: (1) the fracture toughness of grain boundaries and/or interfaces, besides single crystal properties (e.g., Young’s modulus, Poisson ratio, and fracture toughness), can be automatically incorporated, (2) cohesive interfaces are treated in one phase-field framework in comparison with the integrated phase-field and cohesive zone model in which cohesive elements have to be manually placed at the interface, and (3) two-set order parameters enable to describe the concurrent crack propagation and microstructure evolution. The proposed model is validated by comparing the simulated critical deflection angles with the results from theoretical analysis of the linear elastic fracture mechanics and the experiments. The model is then applied to a heterogeneous Silicon Nitride polycrystal to determine the effect of interface fracture toughness on the intergranular/transgranular fracture transition and the effective toughness of the materials.

Chen, Hu↗
DOE OSTI2013

Validation of a Hot Water Distribution Model Using Laboratory and Field Data

Characterizing the performance of hot water distribution systems is a critical step in developing best practice guidelines for the design and installation of high performance hot water systems. Developing and validating simulation models is critical to this effort, as well as collecting accurate input data to drive the models. In this project, the ARBI team validated the newly developed TRNSYS Type 604 pipe model against both detailed laboratory and field distribution system performance data. Validation efforts indicate that the model performs very well in handling different pipe materials, insulation cases, and varying hot water load conditions. Limitations of the model include the complexity of setting up the input file and long simulation run times. In addition to completing validation activities, this project looked at recent field hot water studies to better understand use patterns and potential behavioral changes as homeowners convert from conventional storage water heaters to gas tankless units. Based on these datasets, we conclude that the current Energy Factor test procedure overestimates typical use and underestimates the number of hot water draws. This has implications for both equipment and distribution system performance. Gas tankless water heaters were found to impact how people use hot water, but the data does not necessarily suggest an increase in usage. Further study in hot water usage and patterns is needed to better define these characteristics in different climates and home vintages.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Advances in prediction of tokamak experiments with theory-based models

The successful validation of theory-based models of transport, MHD stability, heating and current drive, with tokamak measurements over the last 20 years, has laid the foundation for a new era where these models can be routinely used in a "predict first" approach to design and predict the outcomes of experiments on tokamaks today. The capability to predict the plasma confinement and core profiles with a quantified uncertainty, based on a multi-machine, international, database of experience, will provide confidence that a proposed discharge will remain within the operational limits of the tokamak. Developing this predictive capability for the first generation of burning plasma devices, beginning with ITER, and progressing to tokamak demonstration reactors, is a critical mission of fusion energy research. Major advances have been made implementing this predict first methodology on today's tokamaks. In this work, an overview of several of these recent advances will be presented, providing the integrated modeling foundations of the experimental successes. The first steps to include boundary plasmas, and tokamak control systems, have been made. A commitment to predicting experiments as part of the planning process is needed in order to collect predictive accuracy data and evolve the models and software into a robust whole discharge pulse design simulator.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Heat pump water heater enhanced with phase change materials thermal energy storage: Modeling study

A promising solution to improve the first hour rating (FHR) of a heat pump water heater (HPWH) involves employing a secondary tank which contains phase change material (PCM) capsules. To better understand the influence of PCM thermal storage on the HPWH operational performance, a dynamic model was developed to simulate and analyze the behavior of a newly developed HPWH technology that incorporates PCM storage into a standard HPWH to optimize key parameters such as the uniform energy factor and FHR. Mathematical models of several key components of the proposed HPWH-PCM integrated thermal energy storage (TES) system, e.g., water heater tank, PCM TES tank, evaporator, compressor, and expansion valve, have been elaborated. Also, a model-based control co-simulation platform was developed to integrate a embed PCM storage HPWH dynamic model with a control model for better supporting control design, analysis, verification, and validation. The model accuracy has been validated through comparing simulation results with lab test results, with a mean average percentage error of <5.5% for most of the selected performance variables. In addition, using the developed co-simulation platform, the demand response control strategy was studied to evaluate the load flexibility of the combined HPWH-PCM storage system by shifting system power usage to outside of the 3.5 h peak load period.

25 ENERGY STORAGE↗
DOE OSTI2013

A stochastic perturbation theory for non-autonomous systems

We develop a perturbation theory for a class of first order nonlinear non-autonomous stochastic ordinary differential equations that arise in climate physics. The perturbative procedure produces moments in terms of integral delay equations, whose order by order decay is characterized in a Floquet-like sense. Both additive and multiplicative sources of noise are discussed and the question of how the nature of the noise influences the results is addressed theoretically and numerically. By invoking the Martingale property, we rationalize the transformation of the underlying Stratonovich form of the model to an Ito form, independent of whether the noise is additive or multiplicative. The generality of the analysis is demonstrated by developing it both for a Brownian particle moving in a periodically forced quartic potential, which acts as a simple model of stochastic resonance, as well as for our more complex climate physics model. The validity of the approach is shown by comparison with numerical solutions. The particular climate dynamics problem upon which we focus involves a low-order model for the evolution of Arctic sea ice under the influence of increasing greenhouse gas forcing ΔF{sub 0}. The deterministic model, developed by Eisenman and Wettlaufer [“Nonlinear threshold behavior during the loss of Arctic sea ice,” Proc. Natl. Acad. Sci. U.S.A. 106(1), 28–32 (2009)] exhibits several transitions as ΔF{sub 0} increases and the stochastic analysis is used to understand the manner in which noise influences these transitions and the stability of the system.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2013

Validation of a Hot Water Distribution Model Using Laboratory and Field Data

Characterizing the performance of hot water distribution systems is a critical step in developing best practice guidelines for the design and installation of high performance hot water systems. Developing and validating simulation models is critical to this effort, as well as collecting accurate input data to drive the models. In this project, the Building America research team ARBI validated the newly developed TRNSYS Type 604 pipe model against both detailed laboratory and field distribution system performance data. Validation efforts indicate that the model performs very well in handling different pipe materials, insulation cases, and varying hot water load conditions. Limitations of the model include the complexity of setting up the input file and long simulation run times. This project also looked at recent field hot water studies to better understand use patterns and potential behavioral changes as homeowners convert from conventional storage water heaters to gas tankless units. The team concluded that the current Energy Factor test procedure overestimates typical use and underestimates the number of hot water draws, which has implications for both equipment and distribution system performance. Gas tankless water heaters were found to impact how people use hot water, but the data does not necessarily suggest an increase in usage. Further study in hot water usage and patterns is needed to better define these characteristics in different climates and home vintages.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2019

Validation of Wichner Predictive Model for Chronic Oxidation by Moisture of Nuclear Graphite

This document reports the results of multi-year extensive research on chronic oxidation of nuclear graphite by traces of moisture that might be present in the helium coolant of high-temperature gas-cooled reactors (HTGRs). The research focuses on four grades of nuclear graphite that are considered potential candidates for component fabrication in advanced nuclear reactors. The four grades are (1) PCEA (medium-fine grain, extruded, manufactured by GrafTech Inc., USA); (2) NBG-17 (medium-fine grain, vibrationally molded, manufactured by SGL Carbon, Germany/France); (3) IG-110 (microfine grain, isostatically molded, manufactured by Toyo Tanso, Japan); and (4) 2114 (microfine grain, isostatically pressed, manufactured by Mersen, USA). The experimental part of this research comprised three objectives that were consistently pursued for each graphite material: (1) accelerated oxidation tests in well-controlled conditions (temperature, gas composition) and analysis of chemical kinetic models and of their parameters for each graphite grade; (2) measurements of water vapor transport rates from H 2 O/He mixtures through thin graphite slabs for estimation of the water effective diffusivity specific to each material; (3) controlled oxidation of graphite specimens in H 2 O/He mixtures and characterization of the effects of oxidation temperatures on the density profiles of oxidized layers. These three groups of experimental results were interpreted using the model developed by Wichner et al. for predicting the penetration depth of oxidants (moisture or oxygen) as a function of oxidation conditions. Basically, starting from the kinetic and transport properties of each graphite grade, the ultimate goal was predicting the stable density profile in the oxidized layer and its dependence on the oxidation temperature. The profiles obtained this way were then compared against direct observations of oxidized layers in specimens obtained in well-controlled oxidation conditions. The general agreement between predictions and observations validated the general applicability of the Wichner model. The results obtained in this project were presented at annual Department of Energy–Advanced Reactor Technologies program reviews and at specialist meetings and conferences and were published in Oak Ridge National Laboratory (ORNL) reports and in professional journals. The results published in 2018 had an immediate impact in 2019, when a group from three US universities used ORNL kinetic data as input information in a complex simulation of chronic oxidation by moisture using the same graphite grades during long-time operation in a modular high-temperature gas-cooled reactor. Their conclusion, in line with the conclusions obtained at the end of this project, was that chronic graphite oxidation by moisture during normal operation conditions of an HTGR will be limited to a thin surface layer of graphite blocks at the reactor bottom, where the highest temperatures are. That will not affect the integrity of graphite components and reactor safety, provided the impurity concentration in the helium coolant is rigorously controlled and maintained at the design specifications.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2016

Characterizing the Thermal Column Beam in the University of Massachusetts Lowell Research Reactor

The University of Massachusetts Lowell operates a 1 MW, light water cooled and moderated Research Reactor (UMLRR) fueled by low-enriched uranium to generate neutron flux that is used at a variety of in-core and beam port facilities within the reactor to perform irradiation experiments for academic and industrial research. One of the irradiation sites is a graphite-moderated thermal column designed to deliver a collimated beam of thermal neutrons to a neutron radiography imaging system. A detailed characterization of the neutron beam is essential for the design and interpretation of experiments at the facility and for radiation safety. This work aimed to characterize the neutron flux and energy spectrum in the UMLRR thermal column beam by employing experimental and computational methods known as the foil activation and spectrum unfolding technique. A previously existing Monte Carlo N-Particle transport (MCNP) model of the UMLRR reactor core has been extended to the thermal column where the neutron flux and energy spectrum have been computed and experimentally validated. This work employed the foil activation and spectrum unfolding technique along with neutron transport computation to extend the knowledge of the neutron fluence and energy spectrum from the UMLRR core to the adjacent thermal column beam. Radiography systems are used for materials characterization, studying dynamic behavior of engineering systems, and for nuclear forensics applications. Foil activation is an experimental method where thin foils of highly pure materials are placed in the beam where interactions between the neutrons and the foil material activate radioisotopes in the foils whose activities can be measured after the irradiation. Downstream computation with MCNP and the spectrum unfolding code SAND can deconvolute the neutron fluence and energy spectrum that must have been necessary to induce the production rates of radioisotopes that were obtained through foil activation. The necessary ingredients for successful spectrum unfolding are the experimentally measured production rates and some a priori (initial guess) knowledge of the flux spectrum. The thermal column is equipped with a neutron radiography imaging system, so any experimenters who desire to use neutron radiography at UMass Lowell will benefit significantly from knowing the characteristics of the neutron beam. Comprehensive knowledge of these characteristics of the beam is essential to compare and benchmark results obtained for similar experiments at other facilities. The Integrated Nuclear Security and Safeguards Laboratory (INSSL) is pursuing the investigation of the performance of self-healing materials under stress-strain environments and the characterization of radiation detectors and special containers for storing and transporting nuclear material. This work contributes to the improvement of the current radiography system, expands the utility of the system for nuclear safeguards and security application and provides information that will enhance the general safety of the UMLRR experimental facilities. The main objective of this work has been achieved; an appropriate neutron flux spectrum for the UMLRR thermal column beam has been determined using the foil activation method followed by spectrum unfolding. There now exists an experimentally validated computational model of the neutron flux spectrum and the thermal column's neutron environment is characterized. We can conclude that the thermal column is well characterized; an appropriate neutron flux spectrum has been determined through an experimentally validated computational model. Future experimenters interested in the thermal column may now expand on the computational model or use the spectral information for their own purposes. The knowledge gained herein will be helpful for the INSSL's future work using neutron radiography to analyze the effectiveness of self-healing materials and special containers. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2012

Determining Wind Turbine Gearbox Model Complexity Using Measurement Validation and Cost Comparison: Preprint

The Gearbox Reliability Collaborative (GRC) has conducted extensive field and dynamometer test campaigns on two heavily instrumented wind turbine gearboxes. In this paper, data from the planetary stage is used to evaluate the accuracy and computation time of numerical models of the gearbox. First, planet-bearing load and motion data is analyzed to characterize planetary stage behavior indifferent environments and to derive requirements for gearbox models and life calculations. Second, a set of models are constructed that represent different levels of fidelity. Simulations of the test conditions are compared to the test data and the computational cost of the models are compared. The test data suggests that the planet-bearing life calculations should be made separately for eachbearing on a row due to unequal load distribution. It also shows that tilting of the gear axes is related to planet load share. The modeling study concluded that fully flexible models were needed to predict planet-bearing loading in some cases, although less complex models were able to achieve good correlation in the field-loading case. Significant differences in planet load share were found insimulation and were dependent on the scope of the model and the bearing stiffness model used.

17 WIND ENERGY↗