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At least 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

GT2024-139262: Development of a Computational Fluid Dynamics Model for a High-Speed Centrifugal Compressor

Computational fluid dynamics (CFD) has become widely used in the design and analysis of turbomachinery components such as centrifugal compressors. However, CFD is only a limited representation of experimental cases and struggles to model complex flows or lack model details to increase computation speed. The High Efficiency Centrifugal Compressor (HECC) was designed by United Technologies Research Center for NASA to investigate the difficulties behind improving centrifugal compressor technology and to provide an open case to the turbomachinery research community. The CFD technology seen in previous numerical models of the compressor have improved since then. In this study, a high-fidelity computational model for the vaneless configuration of HECC operating at its design point was developed and compared to an equivalent experimental case. This model incorporated GPU versions of mesh generation code WAND and solver code LEO from AeroDynamic Solutions, Inc. Blade sections extracted from the solid model formed the basis of the impeller mesh, while the remainder of the stage was modeled as ducts. Standard day aerodynamic conditions, design rotational speed, design mass flow rate, and inlet flow angles served as additional inputs. A mesh sensitivity study was performed prior to using the model for analysis. The accuracy of the model’s predictions of impeller and stage performance were assessed by comparing the total pressure ratio, total temperature rise ratio, and adiabatic efficiency to the corresponding parameters observed in the experimental case. Results showed a general overprediction of compressor performance by the model. Predictions were more accurate for the impeller performance compared to those for the full compressor stage. Spanwise analyses showed that the model tended to follow flow behavior patterns exhibited in the experiment. Beyond this study, this model was used to examine HECC aerodynamics and performance in research following thereafter.

centrifugal compressor↗
DOE OSTI2023

Evaluation of Irradiation Creep Effects in HT9 Cladding for FAST Experiments

The push for advanced reactor fuels for improved reactor safety and efficiency had led to a renewed interest in metallic fuel for nuclear reactor applications. Experimental investigation is necessary to ensure a robust understanding of the thermomechanical properties of new metallic fuel designs. Unfortunately, with the current experimental facilities, thoroughly investigating the responses of metallic fuel burnup would take a prohibitively long time. To alleviate this, the Fission Accelerated Steady State Test (FAST) was developed to accelerate the irradiation testing while simultaneously decreasing the sensitivity to fabrication tolerances by reducing the fuel diameter and scaling the experiment. This method successfully scales the radiation effects on the fuel, but the HT9 cladding is not exposed to prototypic radiation conditions. This raises questions on whether the FAST experiment results are truly indicative of the HT9 cladding performance due to radiation induced creep effects not being appropriately accounted for. Using BISON fuel performance code, the simulated FAST cladding strain is compared to simulated EBR-II cladding strain. This is done through a sensitivity study of input parameters and scaling of neutron fluence on the cladding. This allows a parametric comparison of physical phenomena on the effective difference between cladding strains between FAST and equivalent burnup EBR-II fuel pins. The results show that the irradiation induced deformation (creep or swelling) is insignificant compared to the thermal-mechanical deformation. Therefore, the difference between the FAST experiment cladding and the EBR-II experiment cladding is negligible and comparison of fuel system performance between the two experiments is appropriate.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2015

Calculating uncertainty on K-effective with MONK10 - 14583

Criticality safety assessments require a demonstration that a particular configuration of fissile material has an adequate sub-critical margin (k-effective sufficiently below unity) to ensure that the risk of criticality under normal operation and accident conditions is acceptable. The required sub-critical margin depends upon the uncertainty in the estimated value of k-effective. The uncertainty in the calculated value of k-effective arises from a number of sources, including: manufacturing tolerances on input data to the code (affecting geometry, compositions and densities), uncertainty in the nuclear data used by the code, stochastic uncertainty resulting from Monte Carlo simulation and modelling approximations/errors, including the inevitable bugs in the software. The ANSWERS Software Service, in collaboration with industrial partners, is developing a number of techniques to better understand and quantify uncertainty on predicted values of k-effective, using MONK. The SPRUCE utility code has been developed to allow uncertainty to be estimated using sampling methods. This can include the sampling of input parameters (including dimensions, compositions and densities) from statistical distributions. It can also include sampling different nuclear data libraries. A set of nuclear data libraries has been generated for this purpose by sampling from statistical distributions that represent the uncertainties in the published nuclear data evaluated files; a set of libraries has been produced for Latin Hypercube Sampling. By varying the input data and nuclear data, separate and combined uncertainties due to manufacturing tolerances and nuclear data can be derived. By performing least squares fitting on the results it is also possible to estimate the contribution of each of the uncertain inputs and a sensitivity method in MONK can break down the nuclear data uncertainty. (authors)

42 ENGINEERING↗
NASA NTRS1974

A unified approach to aircraft parameter identification

The most accurate identification results are obtained when all three elements of the identification process - the identification algorithm, the control input, and the instrumentation system - are considered in a unified approach. This type of approach for the design of optimal control inputs and for determining the effect of the instrumentation system, in each case with respect to the identification process is discussed. Design of control inputs which optimize the sensitivity of the system output to the unknown parameters is given. Results using these inputs in an extensive simulation of the identification process indicate they perform measurably better than doublet type inputs. A technique is then presented for specifying an optimal instrumentation system or for determining the effect, the instrumentation system has on the accuracy of the parameter estimates.

Stepner, D. E.↗
DOE OSTI2024

Component innovations for lower cost mechanical vapor compression

Despite significant capital and operating costs, mechanical vapor compression (MVC) remains the preferred technology for challenging brine concentration applications. Here, this work seeks to assess the dependence of MVC costs on feedwater salinity and desired water recovery and to quantify the value of improved component performance or reduced component costs for reducing the levelized cost of water (LCOW) of MVC. We built a cost optimization model coupling thermophysical, heat and mass transfer, and technoeconomic models to optimize and identify low cost MVC system designs as a function of feedwater salinity and water recovery. The LCOW ranges over 3.6 to 6.1 $\$$/m 3 for seawater feed salinities of 25–150 g/kg and water recoveries of 40–80 %. We then perform sensitivity analysis on parameter inputs to isolate irreducible costs and determine high value component innovation targets. The LCOW was most sensitive to evaporator material costs and performance, including the overall heat transfer coefficient in the evaporator. Process and material innovations such as polymer-composite evaporator tubes that reduce evaporator costs by 25 % without reducing heat transfer performance by more than 10 % would result in MVC cost reductions of 8 %.

42 ENGINEERING↗
DOE OSTI2024

Sensitivity of mesoscale modeling to urban morphological feature inputs and implications for characterizing urban sustainability

We examine the differences in meteorological output from the Weather Research and Forecasting (WRF) model run at 270 m horizontal resolution using 10 m, 100 m and 1 km resolution 3D neighborhood morphological inputs and with no morphological inputs. We find that the spatial variability in temperature, humidity, and other meteorological variables across the city can vary with the resolution and the coverage of the 3D urban morphological input, and that larger differences occur between simulations run without 3D morphological input and those run with some type of 3D morphology. We also find that the inclusion of input-building-defined roughness length calculations would improve simulation results further. We show that these inputs produce different patterns of heat wave spatial heterogeneity across the city of Washington, DC. These findings suggest that understanding neighborhood level urban sustainability under extreme heat waves, especially for vulnerable neighborhoods, requires attention to the representation of surface terrain in numerical weather models.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2002

Otolith-Canal Convergence In Vestibular Nuclei Neurons

The current final report covers the period from June 1, 1999 to May 31, 2002. The primary objective of the investigation was to determine how information regarding head movements and head position relative to gravity is received and processed by central vestibular nuclei neurons in the brainstem. Specialized receptors in the vestibular labyrinths of the inner ear function to detect angular and linear accelerations of the head, with receptors located in the semicircular canals transducing rotational head movements and receptors located in the otolith organs transducing changes in head position relative to gravity or linear accelerations of the head. The information from these different receptors is then transmitted to central vestibular nuclei neurons which process the input signals, then project the appropriate output information to the eye, head, and body musculature motor neurons to control compensatory reflexes. Although a number of studies have reported on the responsiveness of vestibular nuclei neurons, it has not yet been possible to determine precisely how these cells combine the information from the different angular and linear acceleration receptors into a correct neural output signal. In the present project, rotational and linear motion stimuli were separately delivered while recording responses from vestibular nuclei neurons that were characterized according to direct input from the labyrinth and eye movement sensitivity. Responses from neurons receiving convergent input from the semicircular canals and otolith organs were quantified and compared to non-convergent neurons.

Dickman, J. David↗
NASA NTRS2016

Sensitivity Analysis of the Integrated Medical Model for ISS Programs

Sensitivity analysis estimates the relative contribution of the uncertainty in input values to the uncertainty of model outputs. Partial Rank Correlation Coefficient (PRCC) and Standardized Rank Regression Coefficient (SRRC) are methods of conducting sensitivity analysis on nonlinear simulation models like the Integrated Medical Model (IMM). The PRCC method estimates the sensitivity using partial correlation of the ranks of the generated input values to each generated output value. The partial part is so named because adjustments are made for the linear effects of all the other input values in the calculation of correlation between a particular input and each output. In SRRC, standardized regression-based coefficients measure the sensitivity of each input, adjusted for all the other inputs, on each output. Because the relative ranking of each of the inputs and outputs is used, as opposed to the values themselves, both methods accommodate the nonlinear relationship of the underlying model. As part of the IMM v4.0 validation study, simulations are available that predict 33 person-missions on ISS and 111 person-missions on STS. These simulated data predictions feed the sensitivity analysis procedures. The inputs to the sensitivity procedures include the number occurrences of each of the one hundred IMM medical conditions generated over the simulations and the associated IMM outputs: total quality time lost (QTL), number of evacuations (EVAC), and number of loss of crew lives (LOCL). The IMM team will report the results of using PRCC and SRRC on IMM v4.0 predictions of the ISS and STS missions created as part of the external validation study. Tornado plots will assist in the visualization of the condition-related input sensitivities to each of the main outcomes. The outcomes of this sensitivity analysis will drive review focus by identifying conditions where changes in uncertainty could drive changes in overall model output uncertainty. These efforts are an integral part of the overall verification, validation, and credibility review of IMM v4.0.

medical equipment↗
DOE OSTI2023

Sensor Anomaly Detection for Nuclear Reactor Systems Utilizing Linear Regression and K-Means Unsupervised Machine Learning

Nuclear reactors and related systems are becoming increasingly complex due to advancing technologies in next-generation power reactors. This increased complexity necessitates enhanced automation and data management capabilities. To successfully realize autonomous systems, methods must be developed to handle vast volumes of data and effectively distinguish anomalous data from noise and expected data. While impressive models utilizing digital twins and similar approaches are under development, here we propose a simplified model for analyzing fundamental methods and techniques. Initially, we created a general dataset by using initial data from PCTRAN in order to represent ideal steady-state conditions. We then inserted anomalies based on prevalent sensor anomaly types (e.g., point anomalies, linear drift, and downward deviations), along with unusual anomalies such as exponential drift and upward deviations. To detect anomalies, we developed a program that employs data partitioning and linear regression to preprocess and filter the anomalous data. A K-Means machine learning (ML) method was then applied to separate and count the data within the anomalous partition. The results from all datasets—apart from exponential growth—demonstrated positive outcomes, with each returning multiple instances of greaterthan-95% accuracy. We conducted further investigations using Idaho National Laboratory’s RAVEN software to perform a sensitivity analysis on the input variables (R 2 Tolerance, Slope Tolerance, and Window Size) and found that the output variables (Accuracy and Time) were most sensitive to the Window Size. Despite the promising results published, further development is required to effectively apply these methods to nuclear systems. Nevertheless, the strengths of this approach are evident and hold promise for future applications in the field.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS1994

Arctic ocean radiative fluxes and cloud forcing estimated from the ISCCP C2 cloud dataset, 1983-1990

Radiative fluxes and cloud forcings for the ocean areas of the Arctic are computed from the monthly cloud product of the International Satellite Cloud Climatology Project (ISCCP) for 1983-90. Spatially averaged short-wave fluxes are compared well with climatological values, while downwelling longwave fluxes are significantly lower. This is probably due to the fact that the ISCCP cloud amounts are underestimates. Top-of-the-atmosphere radiative fluxes are in excellent agreement with measurements from the Earth Radiation Budget Experiment (ERBE). Computed cloud forcings indicate that clouds have a warming effect at the surface and at the top of the atmosphere during winter and a cooling effect during summer. The net radiative effect of clouds is larger at the surface during winter but greater at the top of the atmosphere during summer. Overall the net radiative effect of clouds at the top of the atmosphere is one of cooling. This is in contrast to a previous result from ERBE data showing arctic cloud forcings have a net warming effect. Sensitivities to errors in input parameters are generally greater during winter with cloud amount being the most important paarameter. During summer the surface radiation balance is most sensitive to errors in the measurements of surface reflectance. The results are encouraging, but the estimated error of 20 W/sq m in surface net radiative fluxes is too large, given that estimates of the net radiative warming effect due to a doubling of CO2 are on the order of 4 W/sq m. Because it is difficult to determine the accuracy of results with existing in situ observations, it is recommended that the development of improved algorithms for the retrieval of surface radiative properties be accompanied by the simultaneous assembly of validation datasets.

Schweiger, Axel J.↗
DOE OSTI2019

Adjoint Sensitivity of FARMS to the Forecasting Variables of WRF-Solar: Preprint

This study presents the development and application of an adjoint model for investigating the sensitivity of solar radiation to forecasted variables from WRF-Solar. The first part of this study focuses on developing an adjoint model for the Fast All-sky Model for Solar Applications (FARMS) to investigate the input variables having the highest sensitivity to global horizontal irradiance (GHI), direct normal irradiance (DNI), and diffuse horizontal irradiance (DHI), which are the output variables. The applicability and usefulness of the adjoint sensitivity approach are demonstrated by conducting a sensitivity analysis under various scenarios defined by low, medium, and high values for the input variables. This preliminary study uses elasticity values to understand the sensitivity of solar radiation to the input variables (e.g. solar zenith angle, Angstrom turbidity coefficient, and cloud optical depth) of FARMS. This presentation will illustrate the implemented methodology and the obtained sensitivity results for FARMS, as well as future research steps that will lead to the development of high-quality probabilistic solar forecasts.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

The sensitivity of the forest carbon budget shifts across processes along with stand development and climate change

Abstract The future trajectory of atmospheric CO 2 concentration depends on the development of the terrestrial carbon sink, which in turn is influenced by forest dynamics under changing environmental conditions. An in‐depth understanding of model sensitivities and uncertainties in non‐steady‐state conditions is necessary for reliable and robust projections of forest development and under scenarios of global warming and CO 2 enrichment. Here, we systematically assessed if a biogeochemical process‐based model (3D‐CMCC‐CNR), which embeds similarities with many other vegetation models, applied in simulating net primary productivity (NPP) and standing woody biomass (SWB), maintained a consistent sensitivity to its 55 input parameters through time, during forest ageing and structuring as well as under climate change scenarios. Overall, the model applied at three contrasting European forests showed low sensitivity to the majority of its parameters. Interestingly, model sensitivity to parameters varied through the course of >100 yr of simulations. In particular, the model showed a large responsiveness to the allometric parameters used for initialize forest carbon and nitrogen pools early in forest simulation (i.e., for NPP up to ~37%, 256 g C·m −2 ·yr −1 and for SWB up to ~90%, 65 Mg C/ha, when compared to standard simulation), with this sensitivity decreasing sharply during forest development. At medium to longer time scales, and under climate change scenarios, the model became increasingly more sensitive to additional and/or different parameters controlling biomass accumulation and autotrophic respiration (i.e., for NPP up to ~30%, 167 g C·m −2 ·yr −1 and for SWB up to ~24%, 64 Mg C/ha, when compared to standard simulation). Interestingly, model outputs were shown to be more sensitive to parameters and processes controlling stand development rather than to climate change (i.e., warming and changes in atmospheric CO 2 concentration) itself although model sensitivities were generally higher under climate change scenarios. Our results suggest the need for sensitivity and uncertainty analyses that cover multiple temporal scales along forest developmental stages to better assess the potential of future forests to act as a global terrestrial carbon sink.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1999

Utilization of Satellite Data in Land Surface Hydrology: Sensitivity and Assimilation

This paper investigates the sensitivity of potential evapotranspiration to input meteorological variables, viz- surface air temperature and surface vapor pressure. The sensitivity studies have been carried out for a wide range of land surface variables such as wind speed, leaf area index and surface temperatures. Errors in the surface air temperature and surface vapor pressure result in errors of different signs in the computed potential evapotranspiration. This result has implications for use of estimated values from satellite data or analysis of surface air temperature and surface vapor pressure in large scale hydrological modeling. The comparison of cumulative potential evapotranspiration estimates using ground observations and satellite observations over Manhattan, Kansas for a period of several months shows very little difference between the two. The cumulative differences between the ground based and satellite based estimates of potential evapotranspiration amounted to less that 20mm over a 18 month period and a percentage difference of 15%. The use of satellite estimates of surface skin temperature in hydrological modeling to update the soil moisture using a physical adjustment concept is studied in detail including the extent of changes in soil moisture resulting from the assimilation of surface skin temperature. The soil moisture of the surface layer is adjusted by 0.9mm over a 10 day period as a result of a 3K difference between the predicted and the observed surface temperature. This is a considerable amount given the fact that the top layer can hold only 5mm of water.

Lakshmi, Venkataraman↗
NASA NTRS2007

Toward Scientific Numerical Modeling

Ultimately, scientific numerical models need quantified output uncertainties so that modeling can evolve to better match reality. Documenting model input uncertainties and verifying that numerical models are translated into code correctly, however, are necessary first steps toward that goal. Without known input parameter uncertainties, model sensitivities are all one can determine, and without code verification, output uncertainties are simply not reliable. To address these two shortcomings, two proposals are offered: (1) an unobtrusive mechanism to document input parameter uncertainties in situ and (2) an adaptation of the Scientific Method to numerical model development and deployment. Because these two steps require changes in the computational simulation community to bear fruit, they are presented in terms of the Beckhard-Harris-Gleicher change model.

Kleb, Bil↗
DOE OSTI2024

Sensitivity Analysis for the Component Design App: Analysis of Success Assured Data

A new tool has been developed to perform variance-based global sensitivity analysis (VBGSA) on data from a set-based concurrent engineering software called Success Assured (SA). The tool is part of a digital component design app, which is currently in production as an Accelerated Digital Engineering Pathfinder at Sandia National Laboratories. When working with complex digital models, it is important to understand relationships between inputs and outputs, i.e., how “sensitive” model outputs are to changes in model inputs. After extensive research and trials of various sensitivity analysis methods, it was determined that estimation of Sobol’ indices for VBGSA with Monte Carlo simulation, paired with simple surrogate models, produces the best results for SA data. This tool increases understanding of SA models and streamlines the creation of SA datasets. This report details the methodology and implementation of this sensitivity analysis tool so others can understand it and implement it.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1979

Monolithic InSb imaging arrays with charge-coupled device /CCD/ readout

The paper demonstrates the detection of infrared radiation and signal readout on a monolithic InSb charge coupled infrared imaging device. The device is a 20-element linear imager with MOS detectors coupled to a four-phase, surface-channel, charge transfer structure. The charge transfer device is p-channel and has planar ion implanted diode structures for zero input and charge readout. Sensitivity measurements on the MOS infrared detectors were determined for the 20-element array. Data are presented on the operational characteristics of the 20-element linear imager under various conditions of electrical and optical inputs in both multiplexed and a time delay and integration (TDI) mode. Plans are discussed for a monolithic InSb 100-element linear imager and a 20 x 16 TDI linear imager.

Miller, W. E.↗
NASA NTRS1985

Lowering Ammeter Input Impedance

Feedback circuit operates in conjunction with sensitive microammeter or other current-measuring instrument to reduce input impedance of composite circuit. In contrast with older current-amplifier circuits, current much less subject to drift and noise, calibration not necessary, and values of components not critical.

Siegel, C. M.↗