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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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The design and performance of a modestly sized utility-connected power conditioning system and its supporting photovoltaic collector are described and estimated. Utility preparations and guidelines to conform with the output of a small generating station with that of a large power network are examined.
The dynamic environment must be known to evaluate high pressure oxidizer turbopump inducer fatigue life. This report sets the dynamic design loads for the alternate turbopump inducer as determined by water-flow rig testing. Also, guidelines are given for estimating the dynamic environment for other inducer and impeller applications.
The estimated plant capital cost for a coal fired 200 MWE electric generating plant with open cycle magnetohydrodynamics is divided into principal accounts based on Federal Energy Regulatory Commision account structure. Each principal account is defined and its estimated cost subdivided into identifiable and major equipment systems. The cost data sources for compiling the estimates, cost parameters, allotments, assumptions, and contingencies, are discussed. Uncertainties associated with developing the costs are quantified to show the confidence level acquired. Guidelines established in preparing the estimated costs are included. Based on an overall milestone schedule related to conventional power plant scheduling experience and starting procurement of MHD components during the preliminary design phase there is a 6 1/2-year construction period. The duration of the project from start to commercial operation is 79 months. The engineering phase of the project is 4 1/2 years; the construction duration following the start of the man power block is 37 months.
Accurate quantification of photovoltaic (PV) system degradation rate (R D ) is essential for lifetime yield predictions. Although R D is a critical parameter, its estimation lacks a standardized methodology that can be applied on outdoor field data. The purpose of this paper is to investigate the impact of time period duration and missing data on R D by analyzing the performance of different techniques applied to synthetic PV system data at different linear R D patterns and known noise conditions. The analysis includes the application of different techniques to a 10-year synthetic dataset of a crystalline Silicon PV system, with emulated degradation levels and imputed missing data. Here, the analysis demonstrated that the accuracy of ordinary least squares (OLS), year-on-year (YOY), autoregressive integrated moving average (ARIMA) and robust principal component analysis (RPCA) techniques is affected by the evaluation duration with all techniques converging to lower R D deviations over the 10-year evaluation, apart from RPCA at high degradation levels. Moreover, the estimated R D is strongly affected by the amount of missing data. Filtering out the corrupted data yielded more accurate R D results for all techniques. It is proven that the application of a change-point detection stage is necessary and guidelines for accurate R D estimation are provided.
The design of breeding blankets represents the major challenge for fusion reactor engineering because of performance requirements and severe operating conditions in terms of heat load and neutron flux. Liquid metal alloys such as lead-lithium, due to their lithium content, can be used to breed tritium, one of the plasma fuel components, and owing to their high thermal conductivity, they may serve as coolants. On the other hand, there are technical issues related to the fact that the liquid metals are electrically conducting and interact with the plasma-confining magnetic field. Induced electric currents and generated electromagnetic forces affect velocity and pressure distribution in the blankets. Magnetohydrodynamic (MHD) flows for fusion applications have been often investigated in simplified geometries, such as pipes, ducts, bends, with focus on their fundamental features. These analyses are essential, since results remain valid as background for the development of blanket designs, even when a concept is dismissed. However, the conceptual study of fusion blankets requires to take into account the global multiple effects, that arise when the full system is considered. Progress made in fusion-related MHD research results from combined numerical and experimental activities. In this paper we review and summarize features of 2D and 3D MHD flows that are typical in liquid metal blankets, together with available correlations for MHD pressure losses. This knowledge can provide simple design MHD guidelines that support a preliminary estimate of MHD effects in a blanket concept, in terms of pressure drop and flow distribution.
The purpose of this paper is to provide the experimental and theoretical background necessary to extend guidelines to ceiling heights between 9 m and 18 m. Based on the results of experiments conducted in 15 m and 22 m high hangars, detector activation thresholds and detector spacing are analyzed for both smoke and heat detectors. Only ceiling mounted detection devices are analyzed in this paper. In addition to the detector threshold study, the predictive capabilities of computer fire model simulations were compared with experimental results. This comparison, which is based on 12 fire tests, resulted in the development of a new ceiling jet algorithm to model phenomena which had not been included in previous algorithms. The improved algorithm provides a better representation of the development of the ceiling jet temperature to a growing hot layer and a better estimation of plume centerline temperature. Guidelines are examined, based on the experimental results, for fire detector spacing, placement, and sensitivity. Recommendations concerning the use of computer fire models at these heights are made as a function of fire size and hot layer development. The role of draft curtains is discussed and their impact on detector activation is demonstrated.
Detailed mean velocity and disturbance amplitude measurements were conducted in a Blasius boundary-layer flow with wall suction applied at three downstream locations. The main emphasis was a direct comparison of the growth rate of the instability wave with discrete spanwise slots versus wide porous strips. The results demonstrate that the local effects of suction through slots or very narrow porous strips have a greater beneficial effect on the stability of the boundary-layer flow relative to the suction influence of a wide porous strip. Codes which use continuous suction for the growth rates of the instability waves to determine the suction quantities for a multiple series of slots will be quite conservative in the estimation of the suction quantity. Guidelines were provided for suction-chamber design and flow rates to minimize internal oscillations which propagate into the boundary-layer flow.
Quantitative guidelines are proposed for Electrostatic Discharge (ESD) pulse shape on charged spacecraft. The guidelines are based on existing ground test data, and on a physical description of the pulsed discharge process. The guidelines are designed to predict pulse shape for surface charging and internal charging on a wide variety of spacecraft structures. The pulses depend on the area of the sample, its capacitance to ground, and the strength of the electric field in the vacuum adjacent to the charged surface. By knowing the pulse shape, current vs. time, one can determine if nearby circuits are threatened by the pulse. The quantitative guidelines might be used to estimate the level of threat to an existing spacecraft, or to redesign a spacecraft to reduce its pulses to a known safe level. The experiments which provide the data and the physics that allow one to interpret the data will be discussed, culminating in examples of how to predict pulse shape/size. This method has been used, but not confirmed, on several spacecraft.
If the current estimate of proposed large constellations is realized, the near-Earth space environment will see more than 50,000 new satellites added to the catalog of resident space objects (RSOs) in the coming decade. This is an order of magnitude increase from the current population and poses new policy challenges as global operators seek to leverage the benefits these new satellite systems provide while also ensuring a sustainable approach to collision avoidance. Various guidelines have been proposed to date to support this effort, including the development of right of way rules to guide how a collision avoidance maneuver should be performed, and how the maneuver burden should be shared between the two satellites involved. However, it is very difficult to evaluate and compare proposed guidelines due to the complex nature of space traffic and the rapidly changing space environment. This study seeks to address this issue by utilizing the Virtual Environment for Space Traffic Analysis (VESTA), a high-fidelity simulation tool that has been developed at Georgia Tech over the past few years with the explicit purpose of evaluating the future of space traffic environment. Using this tool, a sensitivity study is performed that incorporates a likely set of future large constellations and provides metrics on the impact that a select set of proposed maneuvering guidelines would have on operators given realistic variations in spacecraft capabilities (e.g. maneuverability and propulsion capabilities), and other factors (owner-country, public vs. private, etc.). Specifically, this study compares three potential right of way rules: 1) a rule based on maneuverability proposed by the Space Safety Coalition, 2) a rule based on the geometry of the spacecraft rendezvous, and 3) a rule that equally distributes the maneuver burden between two operators, The results highlight general observations on the effectiveness and limitations of each of the proposed maneuvering guidelines. In addition to the choice of right of way rule, success of space traffic management will be significantly impacted by compliance – which operators, or how many operators, comply with the space traffic rules. The findings of this analysis have important implications for future methods that could be pursued to put in place right of way rules. For example, non-binding right of way rules may have variable levels of compliance that differ across actors. The impact of compliance by just one nation, or non-compliance by just one nation, help to demonstrate the impact of ensuring all major space actors coordinate on this effort. Overall, this analysis provides insight into the relative gains in safety (decrease in collision risk) that would likely result from more politically intense efforts to increase the number of countries implementing space traffic management rules.
Quantitative results for aerospace engineering problems are influenced by many sources of uncertainty. Uncertainty analysis aims to make a technical contribution to decision-making through the quantification of uncertainties in the relevant variables as well as through the propagation of these uncertainties up to the result. Uncertainty can be thought of as a measure of the 'goodness' of a result and is typically represented as statistical dispersion. This paper will explain common measures of centrality and dispersion; and-with examples-will provide guidelines for how they may be estimated to ensure effective technical contributions to decision-making.
"Uncertainty analysis itself is uncertain, therefore, you cannot evaluate it exactly," Source Uncertain. Quantitative results for aerospace engineering problems are influenced by many sources of uncertainty. Uncertainty analysis aims to make a technical contribution to decision-making through the quantification of uncertainties in the relevant variables as well as through the propagation of these uncertainties up to the result. Uncertainty can be thought of as a measure of the 'goodness' of a result and is typically represented as statistical dispersion. This presentation will explain common measures of centrality and dispersion; and-with examples-will provide guidelines for how they may be estimated to ensure effective technical contributions to decision-making.
"Uncertainty analysis itself is uncertain, therefore, you cannot evaluate it exactly," Source Uncertain Quantitative results for aerospace engineering problems are influenced by many sources of uncertainty. Uncertainty analysis aims to make a technical contribution to decision-making through the quantification of uncertainties in the relevant variables as well as through the propagation of these uncertainties up to the result. Uncertainty can be thought of as a measure of the 'goodness' of a result and is typically represented as statistical dispersion. This paper will explain common measures of centrality and dispersion; and-with examples-will provide guidelines for how they may be estimated to ensure effective technical contributions to decision-making.
This software package contains a simple calculator that can be used to estimate savings from implementing a retrofit of HVAC controls to ASHRAE Guideline 36 in a multi-zone office building. Implemented in Excel, the calculator has a user-interface front-end to configure parameters of the case study, such as location, building size, and existing control strategies, and a back-end containing results from a large number of pre-run annual energy simulations. The software package also contains the simulation models and associated pre- and post-processing scripts to generate these results.
Remote sensing, or Earth Observation (EO), is increasingly used to understand Earth system dynamics and create continuous and categorical maps of biophysical properties and land cover, especially based on recent advances in machine learning (ML). ML models typically require large, spatially explicit training datasets to make accurate predictions. Training data (TD) are typically generated by digitizing polygons on high spatial-resolution imagery, by collecting in situ data, or by using pre-existing datasets. TD are often assumed to accurately represent the truth, but in practice almost always have error, stemming from (1) sample design, and (2) sample collection errors. The latter is particularly relevant for image-interpreted TD, an increasingly commonly used method due to its practicality and the increasing training sample size requirements of modern ML algorithms. TD errors can cause substantial errors in the maps created using ML algorithms, which may impact map use and interpretation. Despite these potential errors and their real-world consequences for map-based decisions, TD error is often not accounted for or reported in EO research. Here we review the current practices for collecting and handling TD. We identify the sources of TD error, and illustrate their impacts using several case studies representing different EO applications (infrastructure mapping, global surface flux estimates, and agricultural monitoring), and provide guidelines for minimizing and accounting for TD errors. To harmonize terminology, we distinguish TD from three other classes of data that should be used to create and assess ML models: training reference data, used to assess the quality of TD during data generation; validation data, used to iteratively improve models; and map reference data, used only for final accuracy assessment. We focus primarily on TD, but our advice is generally applicable to all four classes, and we ground our review in established best practices for map accuracy assessment literature. EO researchers should start by determining the tolerable levels of map error and appropriate error metrics. Next, TD error should be minimized during sample design by choosing a representative spatio-temporal collection strategy, by using spatially and temporally relevant imagery and ancillary data sources during TD creation, and by selecting a set of legend definitions supported by the data. Furthermore, TD error can be minimized during the collection of individual samples by using consensus-based collection strategies, by directly comparing interpreted training observations against expert-generated training reference data to derive TD error metrics, and by providing image interpreters with thorough application-specific training. We strongly advise that TD error is incorporated in model outputs, either directly in bias and variance estimates or, at a minimum, by documenting the sources and implications of error. TD should be fully documented and made available via an open TD repository, allowing others to replicate and assess its use. To guide researchers in this process, we propose three tiers of TD error accounting standards. Finally, we advise researchers to clearly communicate the magnitude and impacts of TD error on map outputs, with specific consideration given to the likely map audience.
Emission Inventory (EI) is a fundamental tool to monitor global compliance of greenhouse gases (GHGs) emissions reduction actions. Inventory guidelines provide a best practice to help EI compilers to make comparable national emission estimates, in spite of the differences in data availability across countries and regions. There are a variety of sources of errors and uncertainties, however, that originate beyond what the inventory guidelines define. For example, spatially-explicit EIs, which are a key product for atmospheric modeling applications, are often developed for research purposes, and there are no specific guidelines to disaggregate emission estimates from country scale. On top of that, EIs are fundamentally prone to systematic biases due to the simple calculation methodology and thus an objective evaluation (e.g. atmospheric top-down estimates) is needed to assure the accuracy of the estimates. ODIAC is a global high-resolution (1x1 km) fossil fuel carbon dioxide (CO2) gridded EI that is now often used in atmospheric CO2 modeling. ODIAC is based on disaggregation of national emission estimates made by CDIAC, which is the well accepted standard in the community. The ODIAC emission data product is updated on an annual basis using best available statistical data. Subnational spatial emission patterns are estimated using power plant profiles and satellite-observations of nighttime lights. In addition to the conventional CDIAC gridded data product, ODIAC carries international bunker emissions (shipping and aviation), which allows flux inversion modelers to accurately impose the global total fossil fuel emissions and their horizontal and vertical distribution. We have extensively evaluated ODIAC emissions using fine-grained EIs as well as a high-resolution atmospheric model simulation across different scales (national, subnational/regional, and urban policy relevant) with a focus on the uncertainties associated with the emission disaggregation. We have examined the use of NASA's Black Marble Suomi-NPP/VIIRS nightlight data.
Under a sampling program operated in conformity with EPA guidelines, calculational procedures are described for estimating the corresponding ambient pollution level. The statistical independence of the data, the commutativity of expectation and exponential operations, and the statistical variability of the calculated results are quantitatively evaluated. It is shown that the recommended sampling frequencies of every third to every sixth day are inadequate in determining conformity when the standards are expressed as levels not to be exceeded more than once a year.
We develop guidelines for a priori assessment of risk due to potentially SEL susceptible parts by exploratory analysis of large datasets of SEL test data for unhardened CMOS parts.
The coal combusted at coal-fired power plants (CFPPs) contains several trace elements that impact human heath if released to the environment. Effective combinations of air pollution control devices (APCDs) and water pollution control devices (WPCDs) are critical to reducing these impacts. This work sampled pulverized CFPPs owned and operated by Louisville Gas & Electricity – Kentucky Utilities (LGE-KU) during baseload and cycling conditions. Next, an open-source and easy-to-implement trace element partitioning model was developed using publicly available datasets, literature studies of trace element partitioning, and sampling data to estimate trace element partitioning in APCDs to the gas, liquid, and solid phases exiting CFPPs. These estimates of the liquid phase trace element concentration in FGD wastewater were then used to estimate trace element behavior in WPCDs and evaluate treated wastewater effluent concentrations for compliance with the Effluent Limitation Guidelines (ELG) for the Steam Electric Generating Sector. Finally, cost estimates were developed for established and emerging wastewater treatment trains to identify the most cost-effective approaches for ELG compliance.