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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 127 records · Page 7

Recommendations to Improve the Nuclear Regulatory Commission Reactor Licensing and Approval Process

Due to the urgency around climate change and associated goals for clean energy transition, and Battelle Energy Alliance's (BEA) and Idaho National Laboratory's (INL) role as the nation's nuclear energy laboratory, numerous stakeholders have asked for BEA’s thoughts and recommendations to reduce the time and costs associated with licensing new reactors at the U.S. Nuclear Regulatory Commission (NRC). As an M&O contractor for an FFRDC, BEA is a long-term partner with the Government in seeking to achieve clean energy goals, yet has a level of independence needed to appropriately evaluate this topic. The views herein are informed by extensive BEA experience supporting nuclear energy endeavors including ongoing discussions with current and former regulators, applicants, and licensees. With this background in mind, the United States benefits from having an agency such as the NRC, which is viewed internationally as the leader in nuclear safety licensing and regulation. Nonetheless, while acknowledging the important nuclear safety role satisfied by the NRC, it is apparent that one of the most significant time and resource intensive activities for new reactor developers is the NRC licensing process. The time and cost to obtain NRC licenses add significant financial stress for new reactor projects and may result in abandonment of projects or failure to even begin new projects. The challenge is particularly acute for advanced reactors which may raise unique or new regulatory questions and may be smaller in size, resulting in a much higher proportional impact from regulatory and cost challenges. This situation presents a particularly troublesome risk for the nation given the urgency in which utilities are working to transition to clean, non-carbon-emitting energy sources like nuclear energy. Reforms to the NRC licensing process have the potential to greatly increase certainty and support the successful progress of new reactors. The NRC can retain its world-class nuclear safety reputation while becoming a world leader for regulatory efficiency and a critical enabler to the clean energy transition. This report describes potential NRC reforms, focusing on those with a statutory connection. Recognizing the potential tradeoffs with any proposed changes, the report attempts to highlight those considerations in the analysis of the reforms. The recommendations are presented as a set of options for consideration. Unless noted, they are independent options, offering stakeholders the option to select a subset for further consideration. Although difficult to calculate precise time improvements for some of the changes, the reforms have the potential for substantial improvements, perhaps even by a factor of two.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Optimizing resource allocation in Miscanthus breeding via sparse testing designs for genomic prediction

Phenotyping high-biomass perennial crops is laborious and the rate of genetic gain in conventional perennial crop breeding programs is typically low. So, it is especially important to identify methods that produce efficiency gains in the breeding process. Miscanthus is a C4 perennial grass with favorable characteristics for producing biomass as a feedstock for biofuels and diverse bio-based products. Increasing biomass yield will increase profitability and environmental benefits, so it is a key target for Miscanthus breeding. In addition, the identification of well-adapted genotypes across a wide range of environmental conditions requires the establishment of multi-environment trials (METs). Sparse testing is a genomic prediction-based strategy that reduces the phenotyping costs in METs by selecting a subset of genotypes to evaluate in a subset of environments and then predicts the performance of the unobserved genotype-environment combinations. A Miscanthus sacchariflorus (MSA) population comprising 336 genotypes observed across three environments was analyzed implementing sparse testing designs. Three prediction models considering main effects (environments, genotypes, genomic) and interaction effects (genotype-by-environment; G×E interaction) were implemented for forecasting dry biomass yield (YDY), total culm (TCM), average internode length (AIL), and culm node number (CNN). Multiple calibration sets based on different compositions and sizes were considered to evaluate performance in terms of the predictive ability (PA) and the mean square error (MSE) for a fixed testing set size. The training set size ranged from 52 to 112 to predict a fixed set of 224 unobserved genotypes across all three environments. The results showed that the model accounting for G×E interaction consistently presented the highest PA and the lowest MSE: for CNN (PA: ~0.77, MSE: ~0.5) and YDY (PA: ~0.70, MSE: ~1.3) while for TCM and AIL these ranged from ~0.28 to 0.41 and ~1.3 to 4.3, respectively. Overall, varying training sets and allocation strategies did not affect PA and MSE, with 52 non-overlapping and 0 overlapping genotypes per environment as the optimal cost-effective allocation framework. This suggests that implementing sparse testing designs could significantly reduce phenotyping costs by fivefold, without compromising PA in breeding programs for perennial crops such as Miscanthus.

Miscanthus sacchariflorus (MSA)↗

Scheduling Algorithm for Mission Planning and Logistics Evaluation (SAMPLE). Volume 3: The GREEDY algorithm

The functional specifications, functional design and flow, and the program logic of the GREEDY computer program are described. The GREEDY program is a submodule of the Scheduling Algorithm for Mission Planning and Logistics Evaluation (SAMPLE) program and has been designed as a continuation of the shuttle Mission Payloads (MPLS) program. The MPLS uses input payload data to form a set of feasible payload combinations; from these, GREEDY selects a subset of combinations (a traffic model) so all payloads can be included without redundancy. The program also provides the user a tutorial option so that he can choose an alternate traffic model in case a particular traffic model is unacceptable.

Dupnick, E.↗

Maclisp extensions

A common subset of selected facilities available in Maclisp and its derivatives (PDP-10 and Multics Maclisp, Lisp Machine Lisp (Zetalisp), and NIL) is decribed. The object is to add in writing code which can run compatibly in more than one of these environments.

Bawden, A.↗

Low-cost digital image processing at the University of Oklahoma

Computer assisted instruction in remote sensing at the University of Oklahoma involves two separate approaches and is dependent upon initial preprocessing of a LANDSAT computer compatible tape using software developed for an IBM 370/158 computer. In-house generated preprocessing algorithms permits students or researchers to select a subset of a LANDSAT scene for subsequent analysis using either general purpose statistical packages or color graphic image processing software developed for Apple II microcomputers. Procedures for preprocessing the data and image analysis using either of the two approaches for low-cost LANDSAT data processing are described.

Harrington, J. A., Jr.↗

Sulfur trioxide in the lower atmosphere of Venus

Inconsistencies and ambiguities are noted by the present consideration of Pioneer Venus and Venera atmospheric composition measurement of Venus in the context of lower atmosphere thermodynamic equilibrium. Among the scenarios projected on the basis of assumed correctness for selected data subsets, the O2 and SO2 concentrations reported by the Pioneer Venus chromatograph and the H2O concentrations reported by Venera 11 suggest that large concentrations of SO3 are present in the lower atmosphere of Venus. Such SO3 concentrations lead, however, to difficulties in explaining the atmosphere at and above the cloud tops, and in addition require specific assumptions concerning chemical reaction rates at and near the surface.

Craig, R. A.↗

Some methods of estimating a coverage parameter

To demonstrate the high reliability of fault-tolerant computing systems, experimental testing can be performed by injecting faults into their hardware and observing the times needed to detect and isolate failed components and reconfigure the good components. Coverage, a parameter measuring continued system success, is the probability that recovery occurs before other, perhaps catastrophic, component failures occur. Methods of estimating coverage are given for the case of randomly selecting a subset of the pins or chips for testing. Pin-level samples of times to recovery are treated by the Type I censoring model often used in life testing.

Lee, L. D.↗

An imaging spectrometer experiment for the Shuttle

An imaging spectrometer experiment concept for earth remote sensing, developed as part of NASA's Multispectral Linear Array program, will map a series of test sites at high spatial and spectral resolution from the vantage point of the Shuttle payload bay. The instrument covers the spectral range from 0.4 to 2.5 micrometers with a sampling interval of 10 nanometers in the visible and near infrared (to 1.0 micrometer) and 20 nanometers in the short wavelength infrared (1.0 to 2.5 micrometers). Resolution corresponding to a ground instantaneous field of view (pixel size) of 30 meters is provided over a swath width of 12 kilometers. On-board data editing is utilized to select a subset of the data stream for transmission to the ground. The instrument utilizes silicon and mercury cadmium telluride area array detectors. Pointing mirrors are included to permit specific test sites to be imaged from the Shuttle orbit.

Wellman, J. B.↗

Orbiter Flying Qualities (OFQ) Workstation user's guide

This project was devoted to the development of a software package, called the Orbiter Flying Qualities (OFQ) Workstation, for working with the OFQ Archives which are specially selected sets of space shuttle entry flight data relevant to flight control and flying qualities. The basic approach to creation of the workstation software was to federate and extend commercial software products to create a low cost package that operates on personal computers. Provision was made to link the workstation to large computers, but the OFQ Archive files were also converted to personal computer diskettes and can be stored on workstation hard disk drives. The primary element of the workstation developed in the project is the Interactive Data Handler (IDH) which allows the user to select data subsets from the archives and pass them to specialized analysis programs. The IDH was developed as an application in a relational database management system product. The specialized analysis programs linked to the workstation include a spreadsheet program, FREDA for spectral analysis, MFP for frequency domain system identification, and NIPIP for pilot-vehicle system parameter identification. The workstation also includes capability for ensemble analysis over groups of missions.

Myers, Thomas T.↗

Interchangeable end effector tools utilized on the protoflight manipulator arm

A subset of teleoperator and effector tools was designed, fabricated, delivered and successfully demonstrated on the Marshall Space Flight Center (MSFC) protoflight manipulator arm (PFMA). The tools delivered included a rotary power tool with interchangeable collets and two fluid coupling mate/demate tools; one for a Fairchild coupling and the other for a Purolator coupling. An electrical interface connector was also provided for the rotary power tool. A tool set, from which the subset was selected, for performing on-orbit satellite maintenance was identified and conceptionally designed. Maintenance requirements were synthesized, evaluated and prioritized to develop design requirements for a set of end effector tools representative of those needed to provide on-orbit maintenance of satellites to be flown in the 1986 to 2000 timeframe.

Source record↗

The composite classification problem in optical information processing

Optical pattern recognition allows objects to be recognized from their images and permits their positional parameters to be estimated accurately in real time. The guiding principle behind optical pattern recognition is that a lens focusing a beam of coherent light modulated with an image produces the two-dimensinal Fourier transform of that image. When the resulting output is further transformed by the matched filter corresponding to the original image, one obtains the autocorrelation function of the original image, which has a peak at the origin. Such a device is called an optical correlator and may be used to recognize the locate the image for which it is designed. (From a practical perspective, an approximation to the matched filter must be used since the spatial light modulator (SLM) on which the filter is implemented usually does not allow one to independently control both the magnitude and phase of the filter.) Generally, one is not just concerned with recognizing a single image but is interested in recognizing a variety of rotated and scaled views of a particular image. In order to recognize these different views using an optical correlator, one may select a subset of these views (whose elements are called training images) and then use a composite filter that is designed to produce a correlation peak for each training image. Presumably, these peaks should be sharp and easily distinguishable from the surrounding correlation plane values. In this report we consider two areas of research regarding composite optical correlators. First, we consider the question of how best to choose the training images that are used to design the composite filter. With regard to quantity, the number of training images should be large enough to adequately represent all possible views of the targeted object yet small enough to ensure that the resolution of the filter is not exhausted. As for the images themselves, they should be distinct enough to avoid numerical difficulties yet similar enough to avoid gaps in which certain views of the target will be unrecognized. One method that we introduce to study this problem is called probing and involves the creation of the artificial imagery. The second problem we consider involves the clasification of the composite filter's correlation plane data. In particular, we would like to determine not only whether or not we are viewing a training image, but, in the former case, we would like to determine which training image is being viewed. This second problem is investigated using traditional M-ary hypothesis testing techniques.

Hall, Eric B.↗

Feature Detection in Linked Derived Spaces

This paper describes by example a strategy for plotting and interacting with data in multiple metric spaces. The example system was designed for use with time-varying computational fluid dynamics (CFD) datasets, but the methodology is directly applicable to other types of field data. The central objects embodied by the tool are {\em portraits}, which show the data in various coordinate systems, while preserving their spatial connectivity and temporal variability. The coordinates are derived in various ways from the field data, and an important feature is that new and derived portraits can be created interactively. The primary operations supported by the tool are brushing and linking: the user can select a subset of a given portrait, and this subset is highlighted in all portraits. The user can combine highlighted subsets from an arbitrary number of portraits with the usual logical operators, thereby indicating where an arbitrarily complex set of conditions holds. The system is useful for exploratory visualization and feature detection in multivariate data.

Henze, Chris↗

Automated Attitude Sensor Calibration: Progress and Plans

This paper describes ongoing work a NASA/Goddard Space Flight Center to improve the quality of spacecraft attitude sensor calibration and reduce costs by automating parts of the calibration process. The new calibration software can autonomously preview data quality over a given time span, select a subset of the data for processing, perform the requested calibration, and output a report. This level of automation is currently being implemented for two specific applications: inertial reference unit (IRU) calibration and sensor alignment calibration. The IRU calibration utility makes use of a sequential version of the Davenport algorithm. This utility has been successfully tested with simulated and actual flight data. The alignment calibration is still in the early testing stage. Both utilities will be incorporated into the institutional attitude ground support system.

Sedlak, Joseph↗

Using a Web Browser for Environmental and Climate Change Studies

A new web browser for viewing and manipulating meteorological data sets is located on a web server at NASA, Langley Research Center. The browser uses a live access server (LAS) developed by the Thermal Modeling and Analysis Project at NOAA's Pacific Marine Environmental Laboratory. LAS allows researchers to interact directly with the data to view, select, and subset the data in terms of location (latitude, longitude) and time such as day, month, or year. In addition, LAS can compare two data sets and can perform averages and variances, LAS is used here to show how it functions as an internet/web browser for use by the scientific and educational community. In particular its versatility in displaying and manipulating data sets of atmospheric measurements in the earth's radiation budget (ERB) or energy balance, which includes measurements of absorbed solar radiation, reflected shortwave radiation (RSW), thermal outgoing longwave radiation (OLR), and net radiation is demonstrated. These measurements are from the Clouds and the Earth's Radiant Energy System (CERES) experiment and the surface radiation budget (SRB) experiment.

Bess, T. Dale↗

Using a Web Browser for Environmental and Climate Change Studies

A new web browser for viewing and manipulating meteorological data sets is located on a web server at NASA, Langley Research Center. The browser uses a live access server (LAS) developed by the Thermal Modeling and Analysis Project at NOAA's Pacific Marine Environmental Laboratory. LAS allows researchers to interact directly with the data to view, select, and subset the data in terms of location (latitude, longitude) and time such as day, month, or year. In addition, LAS can compare two data sets and can perform averages and variances, LAS is used here to show how it functions as an internet/web browser for use by the scientific and educational community. In particular its versatility in displaying and manipulating data sets of atmospheric measurements in the earth s radiation budget (ERB) or energy balance, which includes measurements of absorbed solar radiation, reflected shortwave radiation (RSW), thermal outgoing longwave radiation (OLR), and net radiation is demonstrated. These measurements are from the Clouds and the Earth s Radiant Energy System (CERES) experiment and the surface radiation budget (SRB) experiment.

Bess, T. Dale↗

How simple is software defect detection?

This study benchmarks several FSS techniques and reports several studies where a large set metrics were reduced to a handful with little loss of detection accuracy. This result raises the possibility that software defect detection may be much simpler than previously believed.

feature subset selection software fault model soft↗

Learning User Preferences for Sets of Objects

Most work on preference learning has focused on pairwise preferences or rankings over individual items. In this paper, we present a method for learning preferences over sets of items. Our learning method takes as input a collection of positive examples--that is, one or more sets that have been identified by a user as desirable. Kernel density estimation is used to estimate the value function for individual items, and the desired set diversity is estimated from the average set diversity observed in the collection. Since this is a new learning problem, we introduce a new evaluation methodology and evaluate the learning method on two data collections: synthetic blocks-world data and a new real-world music data collection that we have gathered.

preferences↗

A Systematic Approach for Model-Based Aircraft Engine Performance Estimation

A requirement for effective aircraft engine performance estimation is the ability to account for engine degradation, generally described in terms of unmeasurable health parameters such as efficiencies and flow capacities related to each major engine module. This paper presents a linear point design methodology for minimizing the degradation-induced error in model-based aircraft engine performance estimation applications. The technique specifically focuses on the underdetermined estimation problem, where there are more unknown health parameters than available sensor measurements. A condition for Kalman filter-based estimation is that the number of health parameters estimated cannot exceed the number of sensed measurements. In this paper, the estimated health parameter vector will be replaced by a reduced order tuner vector whose dimension is equivalent to the sensed measurement vector. The reduced order tuner vector is systematically selected to minimize the theoretical mean squared estimation error of a maximum a posteriori estimator formulation. This paper derives theoretical estimation errors at steady-state operating conditions, and presents the tuner selection routine applied to minimize these values. Results from the application of the technique to an aircraft engine simulation are presented and compared to the estimation accuracy achieved through conventional maximum a posteriori and Kalman filter estimation approaches. Maximum a posteriori estimation results demonstrate that reduced order tuning parameter vectors can be found that approximate the accuracy of estimating all health parameters directly. Kalman filter estimation results based on the same reduced order tuning parameter vectors demonstrate that significantly improved estimation accuracy can be achieved over the conventional approach of selecting a subset of health parameters to serve as the tuner vector. However, additional development is necessary to fully extend the methodology to Kalman filter-based estimation applications.

Simon, Donald L.↗