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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Full-scale 3-D finite element modeling of a two-loop pressurized water reactor for heat transfer, thermal–mechanical cyclic stress analysis, and environmental fatigue life estimation

This paper discusses a system-level finite element model of a two-loop pressurized water reactor (PWR). Based on this model, system-level heat transfer analysis and subsequent sequentially coupled thermal-mechanical stress analysis were performed for typical thermal-mechanical fatigue cycles. The in-air fatigue lives of example components, such as the hot and cold legs, were estimated on the basis of stress analysis results, ASME in-air fatigue life estimation criteria, and fatigue design curves. Furthermore, environmental correction factors and associated PWR environment fatigue lives for the hot and cold legs were estimated by using estimated stress and strain histories and the approach described in US-NRC report: NUREG-6909.

Full-scale 3-D finite element model, Pressurized w↗
DOE OSTI2015

Direct assignment of molecular vibrations via normal mode analysis of the neutron dynamic pair distribution function technique

For over a century, vibrational spectroscopy has enhanced the study of materials. Yet, assignment of particular molecular motions to vibrational excitations has relied on indirect methods. Here, we demonstrate that applying group theoretical methods to the dynamic pair distribution function analysis of neutron scattering data provides direct access to the individual atomic displacements responsible for these excitations. Applied to the molecule-based frustrated magnet with a potential magnetic valence-bond state, LiZn{sub 2}Mo{sub 3}O{sub 8}, this approach allows direct assignment of the constrained rotational mode of Mo{sub 3}O{sub 13} clusters and internal modes of MoO{sub 6} polyhedra. We anticipate that coupling this well known data analysis technique with dynamic pair distribution function analysis will have broad application in connecting structural dynamics to physical properties in a wide range of molecular and solid state systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Appalachian Basin Play Fairway Analysis: Revised 2016 Combined Risk Factor Analysis

This submission contains information used to compute the combined risk factors for deep geothermal energy opportunities in the Appalachian Basin, in the context of a the Play Fairway Analysis project. The risk factors are sedimentary rock reservoir quality, thermal resource quality, potential for induced seismicity, and utilization for direct-use heating of neighborhoods. The methods used to combine the risk factors included taking the average, the geometric mean, and the minimum of the four risk factors. Combined risk maps are provided for three different sedimentary rock reservoir metrics. Combined risk maps are also provided for the three geologic risk factors alone (thermal, reservoir, and seismic), and for the three risk factors that exclude reservoir quality (utilization, seismicity, and thermal qualities). The 2015 data submission should be visited to obtain associated shapefiles, which include: 1) definition of the High and Medium priority play fairways (Inner_Fairway, and Outer_Fairway), 2) definition of the US Census Places (usCensusPlaces), 3) places (cities) of interest in the region (Places_of_Interest) identified as geothermal play fairways, 4) the point centers of the raster cells (Raster_Center_Locations), and 5) locations of industries and special-use communities (e.g., colleges and military bases) identified as low temperature heat users (Industries). The 2015 submission also includes: 1) a methodology memo that explains how the risk factors were combined (GPFA-AB_combining_risk_factors.pdf), 2) the earthquake-based seismic risk map, and 3) supporting information with details of the calculations or processing used in generating these data files. More details on each file are given in the spreadsheet "list_of_contents.xlsx" in the folder "Supporting_Information". Code used to calculate values is available at https://github.com/calvinwhealton/geothermal_pfa under the folder "combining_metrics". Note that the 2016 code is currently under the branch named "combining_metrics_2016" in the folder called "combining_metrics". This branch may be merged with the master branch in the future. Many files contained within this submission update and replace the indicated files contained in: Cornell University. (2015). Risk Factor Analysis in Low-Temperature Geothermal Play Fairway Analysis for the Appalachian Basin (GPFA-AB) [data set]. Retrieved from https://gdr.openei.org/submissions/622. doi:10.15121/1261942

15 GEOTHERMAL ENERGY↗
DOE OSTI2015

System-Level Heat Transfer Analysis, Thermal- Mechanical Cyclic Stress Analysis, and Environmental Fatigue Modeling of a Two-Loop Pressurized Water Reactor. A Preliminary Study

This report provides an update on an assessment of environmentally assisted fatigue for light water reactor components under extended service conditions. This report is a deliverable in April 2015 under the work package for environmentally assisted fatigue under DOE's Light Water Reactor Sustainability program. In this report, updates are discussed related to a system level preliminary finite element model of a two-loop pressurized water reactor (PWR). Based on this model, system-level heat transfer analysis and subsequent thermal-mechanical stress analysis were performed for typical design-basis thermal-mechanical fatigue cycles. The in-air fatigue lives of components, such as the hot and cold legs, were estimated on the basis of stress analysis results, ASME in-air fatigue life estimation criteria, and fatigue design curves. Furthermore, environmental correction factors and associated PWR environment fatigue lives for the hot and cold legs were estimated by using estimated stress and strain histories and the approach described in NUREG-6909. The discussed models and results are very preliminary. Further advancement of the discussed model is required for more accurate life prediction of reactor components. This report only presents the work related to finite element modelling activities. However, in between multiple tensile and fatigue tests were conducted. The related experimental results will be presented in the year-end report.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2015

In-situ Condition Monitoring of Components in Small Modular Reactors Using Process and Electrical Signature Analysis. Final report, volume 1. Development of experimental flow control loop, data analysis and plant monitoring

The research and development under this project was focused on the following three major objectives: Objective 1: Identification of critical in-vessel SMR components for remote monitoring and development of their low-order dynamic models, along with a simulation model of an integral pressurized water reactor (iPWR). Objective 2: Development of an experimental flow control loop with motor-driven valves and pumps, incorporating data acquisition and on-line monitoring interface. Objective 3: Development of stationary and transient signal processing methods for electrical signatures, machinery vibration, and for characterizing process variables for equipment monitoring. This objective includes the development of a data analysis toolbox. The following is a summary of the technical accomplishments under this project: - A detailed literature review of various SMR types and electrical signature analysis of motor-driven systems was completed. A bibliography of literature is provided at the end of this report. Assistance was provided by ORNL in identifying some key references. - A review of literature on pump-motor modeling and digital signal processing methods was performed. - An existing flow control loop was upgraded with new instrumentation, data acquisition hardware and software. The upgrading of the experimental loop included the installation of a new submersible pump driven by a three-phase induction motor. All the sensors were calibrated before full-scale experimental runs were performed. - MATLAB-Simulink model of a three-phase induction motor and pump system was completed. The model was used to simulate normal operation and fault conditions in the motor-pump system, and to identify changes in the electrical signatures. - A simulation model of an integral PWR (iPWR) was updated and the MATLAB-Simulink model was validated for known transients. The pump-motor model was interfaced with the iPWR model for testing the impact of primary flow perturbations (upsets) on plant parameters and the pump electrical signatures. Additionally, the reactor simulation is being used to generate normal operation data and data with instrumentation faults and process anomalies. A frequency controller was interfaced with the motor power supply in order to vary the electrical supply frequency. The experimental flow control loop was used to generate operational data under varying motor performance characteristics. Coolant leakage events were simulated by varying the bypass loop flow rate. The accuracy of motor power calculation was improved by incorporating the power factor, computed from motor current and voltage in each phase of the induction motor.- A variety of experimental runs were made for steady-state and transient pump operating conditions. Process, vibration, and electrical signatures were measured using a submersible pump with variable supply frequency. High correlation was seen between motor current and pump discharge pressure signal; similar high correlation was exhibited between pump motor power and flow rate. Wide-band analysis indicated high coherence (in the frequency domain) between motor current and vibration signals. - Wide-band operational data from a PWR were acquired from AMS Corporation and used to develop time-series models, and to estimate signal spectrum and sensor time constant. All the data were from different pressure transmitters in the system, including primary and secondary loops. These signals were pre-processed using the wavelet transform for filtering both low-frequency and high-frequency bands. This technique of signal pre-processing provides minimum distortion of the data, and results in a more optimal estimation of time constants of plant sensors using time-series modeling techniques.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

Failure analysis of a cooling pump using modal and vibration analysis

Four pumps redundantly supply cooling water to a system. All four pumps underwent maintenance during a recently scheduled downtime. During preliminary evaluation following maintenance, one pump, the subject of this document, exhibited higher vibration levels compared to the other three pumps. The pump underwent further performance testing to rule out potential damage resulting from the higher vibration. Vibration analysis and modal analysis including steady state spectrum, operational deflection shape, run up transients, and modal impact have been utilized to identify dynamic characteristics that could contribute to the increased vibration levels. This article will cover the testing setup, methodology, analysis results, and recommendations.

42 ENGINEERING↗
DOE OSTI2016

Field-to-Fuel Performance Testing of Lignocellulosic Feedstocks for Fast Pyrolysis and Upgrading: Techno-economic Analysis and Greenhouse Gas Life Cycle Analysis

This work shows preliminary results from techno-economic analysis and life cycle greenhouse gas analysis of the conversion of seven (7) biomass feedstocks to produce liquid transportation fuels via fast pyrolysis and upgrading via hydrodeoxygenation. The biomass consists of five (5) pure feeds (pine, tulip poplar, hybrid poplar, switchgrass, corn stover) and two blends. Blend 1 consists of equal weights of pine, tulip poplar and switchgrass, and blend 2 is 67% pine and 33% hybrid poplar. Upgraded oil product yield is one of the most significant parameters affecting the process economics, and is a function of both fast pyrolysis oil yield and hydrotreating oil yield. Pure pine produced the highest overall yield, while switchgrass produced the lowest. Interestingly, herbaceous materials blended with woody biomass performed nearly as well as pure woody feedstock, suggesting a non-trivial relationship between feedstock attributes and production yield. Production costs are also highly dependent upon hydrotreating catalyst-related costs. The catalysts contribute an average of ~15% to the total fuel cost, which can be reduced through research and development focused on achieving performance at increased space velocity (e.g., reduced catalyst loading) and prolonging catalyst lifetime. Green-house-gas reduction does not necessarily align with favorable economics. From the greenhouse gas analysis, processing tulip poplar achieves the largest GHG emission reduction relative to petroleum (~70%) because of its lower hydrogen consumption in the upgrading stage that results in a lower natural gas requirement for hydrogen production. Conversely, processing blend 1 results in the smallest GHG emission reduction from petroleum (~58%) because of high natural gas demand for hydrogen production.

Analysis↗
DOE OSTI2015

GLOBAL ANALYSIS OF KOI-977: SPECTROSCOPY, ASTEROSEISMOLOGY, AND PHASE-CURVE ANALYSIS

We present a global analysis of KOI-977, one of the planet host candidates detected by Kepler. The Kepler Input Catalog (KIC) reports that KOI-977 is a red giant, for which few close-in planets have been discovered. Our global analysis involves spectroscopic and asteroseismic determinations of stellar parameters (e.g., mass and radius) and radial velocity (RV) measurements. Our analyses reveal that KOI-977 is indeed a red giant, possibly in the red clump, but its estimated radius (≳ 20 R {sub ☉} = 0.093 AU) is much larger than KOI-977.01's orbital distance (∼0.027 AU) estimated from its period (P {sub orb} ∼ 1.35 days) and host star's mass. RV measurements show a small variation, which also contradicts the amplitude of ellipsoidal variations seen in the light curve folded with KOI-977.01's period. Therefore, we conclude that KOI-977.01 is a false positive, meaning that the red giant, for which we measured the radius and RVs, is different from the object that produces the transit-like signal (i.e., an eclipsing binary). On the basis of this assumption, we also perform a light curve analysis including the modeling of transits/eclipses and phase-curve variations, adopting various values for the dilution factor D, which is defined as the flux ratio between the red giant and eclipsing binary. Fitting the whole folded light curve as well as individual transits in the short cadence data simultaneously, we find that the estimated mass and radius ratios of the eclipsing binary are consistent with those of a solar-type star and a late-type star (e.g., an M dwarf) for D ≳ 20.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Discrete Adjoint Sensitivity Analysis of Hybrid Dynamical Systems With Switching [Discrete Adjoint Sensitivity Analysis of Hybrid Dynamical Systems]

Sensitivity analysis is an important tool for describing power system dynamic behavior in response to parameter variations. It is a central component in preventive and corrective control applications. The existing approaches for sensitivity calculations, namely, finite-difference and forward sensitivity analysis, require a computational effort that increases linearly with the number of sensitivity parameters. In this paper, we investigate, implement, and test a discrete adjoint sensitivity approach whose computational effort is effectively independent of the number of sensitivity parameters. The proposed approach is highly efficient for calculating sensitivities of larger systems and is consistent, within machine precision, with the function whose sensitivity we are seeking. This is an essential feature for use in optimization applications. Moreover, our approach includes a consistent treatment of systems with switching, such as dc exciters, by deriving and implementing the adjoint jump conditions that arise from state-dependent and time-dependent switchings. The accuracy and the computational efficiency of the proposed approach are demonstrated in comparison with the forward sensitivity analysis approach. In conclusion, this paper focuses primarily on the power system dynamics, but the approach is general and can be applied to hybrid dynamical systems in a broader range of fields.

42 ENGINEERING↗
DOE OSTI2016

Advancing Risk Analysis for Nanoscale Materials: Report from an International Workshop on the Role of Alternative Testing Strategies for Advancement: Advancing Risk Analysis for Nanoscale Materials

The Society for Risk Analysis (SRA) has a history of bringing thought leadership to topics of emerging risk. In September 2014, the SRA Emerging Nanoscale Materials Specialty Group convened an international workshop to examine the use of alternative testing strategies (ATS) for manufactured nanomaterials (NM) from a risk analysis perspective. Experts in NM environmental health and safety, human health, ecotoxicology, regulatory compliance, risk analysis, and ATS evaluated and discussed the state of the science for in vitro and other alternatives to traditional toxicology testing for NM. Based on this review, experts recommended immediate and near-term actions that would advance ATS use in NM risk assessment. Three focal areas-human health, ecological health, and exposure considerations-shaped deliberations about information needs, priorities, and the next steps required to increase confidence in and use of ATS in NM risk assessment. The deliberations revealed that ATS are now being used for screening, and that, in the near term, ATS could be developed for use in read-across or categorization decision making within certain regulatory frameworks. Participants recognized that leadership is required from within the scientific community to address basic challenges, including standardizing materials, protocols, techniques and reporting, and designing experiments relevant to real-world conditions, as well as coordination and sharing of large-scale collaborations and data. Experts agreed that it will be critical to include experimental parameters that can support the development of adverse outcome pathways. Numerous other insightful ideas for investment in ATS emerged throughout the discussions and are further highlighted in this article.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Analysis of Gaps in Techno-Economic Analysis to Advance Heliostat Technologies for Concentrating Solar-Thermal Power

The Heliostat Consortium (HelioCon) was launched in 2021 to advance heliostat technology. One of its first efforts was to do a detailed analysis of gaps in technology and capabilities in the heliostat industry and complete a roadmap study describing high-priority gaps. HelioCon gathered gaps through a series of outreach activities with representatives and experts from industries and research institutes. Here, this paper discusses the gap analysis for the techno-economic analysis (TEA) topic. One of the main objectives of the TEA topic is to relate the cost and performance of heliostats and heliostat components to the overall system performance. In this study, we limit the scope of this topic to the heliostat field, tower, and receiver and do not consider downstream applications or uses of thermal energy. We conducted a thorough review of existing models and compiled a list of the state of the art in open-source tools currently available to researchers. We collected an initial list of gaps for the TEA of heliostats from industry developers and experts. Each gap is briefly described, and the heliostat development cycle stages that the gap impacts are indicated. We ranked the initial list of TEA gaps into tiers depending on their potential impact. For TEA, most of the gaps identified are related to developing models or data. Strictly speaking, none of these gaps are essential for heliostat development, but all would aid in the heliostat development process.

14 SOLAR ENERGY↗
DOE OSTI2015

SU-E-T-679: Retrospective Analysis of the Sensitivity of Planar Dose Measurements To Gamma Analysis Criteria

Purpose: IMRT QA using planar dose measurements is still a widely used method for checking the accuracy of treatment plans. A pass/fail judgment is made using gamma analysis based on a single endpoint. Using more stringent criteria is a way to increase the sensitivity to planning and delivery errors. Before such implementation, it is necessary to understand how the sensitivity to different gamma criteria settings affects gamma passing rates (GPR). Methods: 752 IMRT QA measurements were re-analyzed with varying distance to agreement (DTA) and dose difference (DD) percentages using a Matlab program. Other quantifying information such as the mean dose difference in the treatment target (defined as points that are greater than 80% of maximal dose) were stored in a relational database for retrospective analysis. Results: The average and standard deviation of GPR (%) fell from 99.84 ± (0.43) to 89.61 ± (6.08) when restricting DD from 5 − 1% respectively, as compared to a drop from 99.15 ± (1.19) to 95.00 ± (4.43), when restricting the DTA from 5 − 1 mm respectively. The mean dose difference (%) in the treatment target between measured and calculated dose was −1.96 ± (0. 83), −0.09 ± (0.98), and 1.44 ± (0. 86) for each of our institution’s three matched linear accelerators (LINAC 1, 2, and 3 respectively). For plans that are approximately 2.7 sigma below the mean GPR, an average of 78.4% of those plans were measured on LINAC 1 or 3, while only 48% of the total plans were run on those machines. Conclusion: The data demonstrates that when restricting gamma criterion, such as the DD, the greatest indicator of reduced GPR in our institution is which matched LINAC the plan was measured on. While small, these differences manifest themselves to levels comparable to other treatment related differences and possibly confound the gamma analysis.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2020

Kepler Data Analysis: Non-Gaussian Noise and Fourier Gaussian Process Analysis of Stellar Variability

We develop a statistical analysis model of Kepler stellar flux data in the presence of planet transits, non-Gaussian noise, and stellar variability. We first develop a model for the Kepler noise probability distribution in the presence of outliers, which make the noise probability distribution non-Gaussian. We develop a signal likelihood analysis based on this probability distribution, in which we model the signal as a sum of the star variability and planetary transits. We argue that these components need to be modeled together if optimal signal is to be extracted from the data. For the stellar variability model we develop an optimal Gaussian process analysis using a Fourier-based Wiener filter approach, where the power spectrum is non-parametric and learned from the data. We develop high dimensional optimization of the objective function, where we jointly optimize all the model parameters, including thousands of star variability modes, and planet transit parameters. We apply the method to Kepler-90 data and show that it gives a better match to the stellar variability than the existing methods, and robustly handles noise outliers. As a consequence, the planet radii have a higher value than what the existing methods give, including splines and celerite.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Economic and Environmental Analysis to Evaluate the Potential Value of Co-Optima Diesel Bioblendstocks to Petroleum Refiners

The U.S. petroleum refining sector is undergoing a period of historic transformation, catalyzed by the decarbonization of the U.S. economy. Diesel-boiling-range bioblendstocks have gained traction, owing to their superior fuel properties and environmental performance as compared to traditional petroleum fuels. This work couples refinery linear programming models with life cycle assessment to quantify the potential economic and environmental benefits, and trade-offs, of blending diesel-boiling-range bioblendstocks at petroleum refineries. Linear programming models were developed in Aspen Process Industry Modeling Systems (PIMS) for three representative petroleum refinery configurations of differing complexity. Seven diesel-boiling-range bioblendstocks: 4-butoxyheptane, 5-ethyl-4-propylnonane, soy biodiesel, sludge hydrothermal liquefaction diesel, polyoxymethylene ethers, renewable diesel, and hexyl hexanoate, were investigated to identify key fuel properties that influence refineries' economics and to track the effect of adding bioblendstocks on refinery-wide cradle-to-gate greenhouse gases (GHG) emissions. These analyses considered blending levels from 10 to 30 vol% and fuel demand projections over the period 2040 to 2050. This analysis determines that bioblendstock sulfur content and cetane number are the primary fuel attributes with the potential to provide value to refiners. Life cycle assessment results indicate that the use of diesel-boiling-range bioblendstocks can reduce cradle-to-gate refinery GHG emissions by up to ~ 40 % relative to conventional refinery operations when considering carbon uptake in the supply chain of the bioblendstock. Refinery-wide marginal GHG abatement costs range from 120 to 3,600 USD2016/metric tons carbon dioxide equivalent avoided across the scenarios evaluated. Reducing the price of bioblendstocks is identified as a key to their adoption.

ADVANCED PROPULSION SYSTEMS,BIOMASS FUELS,ENERGY P↗
DOE OSTI2015

Aerosol transport and wet scavenging in deep convective clouds: a case study and model evaluation using a multiple passive tracer analysis approach

The effect of wet scavenging on ambient aerosols in deep, continental convective clouds in the mid-latitudes is studied for a severe storm case in Oklahoma during the Deep Convective Clouds and Chemistry (DC3) field campaign. A new passive-tracer based transport analysis framework is developed to characterize the convective transport based on the vertical distribution of several slowly reacting and nearly insoluble trace gases. The passive gas concentration in the upper troposphere convective outflow results from a mixture of 47% from the lower level (0-3 km), 21% entrained from the upper troposphere, and 32% from mid-atmosphere based on observations. The transport analysis framework is applied to aerosols to estimate aerosol transport and wet-scavenging efficiency. Observations yield high overall scavenging efficiencies of 81% and 68% for aerosol mass (Dp < 1μm) and aerosol number (0.03< Dp < 2.5μm), respectively. Little chemical selectivity to wet scavenging is seen among observed submicron sulfate (84%), organic (82%), and ammonium (80%) aerosols, while nitrate has a much lower scavenging efficiency of 57% likely due to the uptake of nitric acid. Observed larger size particles (0.15 - 2.5μm) are scavenged more efficiently (84%) than smaller particles (64%; 0.03 - 0.15μm). The storm is simulated using the chemistry version of the WRF model. Compared to the observation based analysis, the standard model underestimates the wet scavenging efficiency for both mass and number concentrations with low biases of 31% and 40%, respectively. Adding a new treatment of secondary activation significantly improves simulation results, so that the bias in scavenging efficiency in mass and number concentrations is reduced to <10%. This supports the hypothesis that secondary activation is an important process for wet removal of aerosols in deep convective storms.

Yang, Qing↗