Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “WEIGHT FACTOR”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2002

A comparison of quality factors and weighting factors for characterizing astronaut radiation exposures

Radiation exposures are typically characterized by two quantities. The first is the absorbed dose, or the energy deposited per unit mass for specific types of radiation passing through specified materials. The same amount of energy deposited in material by two different types of radiation, however, can result in two different levels of risk. Because of this, for the purpose of radiation protection operations, absorbed dose is modified by a second factor intended to normalize the risk associated with a given exposure. We present here an inter-comparison of methods for this modification. First is the radiation quality factor (Q), as defined by ICRP publication 60. This quantity is related functionally to the unrestricted linear energy transfer (LET) of a given radiation, and is multiplied by the absorbed dose to derive the dose equivalent (H). The second method for modifying absorbed dose is the radiation weighting factor, also given in ICRP-60, or as modified in NCRP report 115. To implement the weighting factor, the absorbed dose resulting from incidence of a particular radiation is multiplied by a factor assigned to that type of radiation, giving the equivalent dose. We compare calculations done based on identical fields of radiation representative of that encountered by the MIR space station, applying each of these two methods. c2002 COSPAR. Published by Elsevier Science Ltd. All rights reserved.

NASA Center JSC↗
DOE OSTI2020

Default Radioactive and Hazardous Waste Management (RHWM) Dose Conversion Factors (DCFs) and Weighting Factors and plutonium-239 equivalent Curie (PE-Ci) methodology for acceptance into the Waste Storage Facilities

DOE-STD-5506-2007 (Ref. 1) is the standard that provides the methodology for preparing hazard analysis and accident analysis for transuranic (TRU) waste facilities. The Waste Storage Facilities hazard and accident analysis for the DSA is developed in accordance with DOE-STD- 5506-2007. Two related issues need to be addressed when implementing DOE-STD-5506-2007 regarding the calculation of consequences from TRU waste releases in accident analysis: Consequences determined in accident analysis must be modeled using inhalation Dose Conversion Factors (DCFs) that are consistent with those from the International Commission on Radiological Protection Publication 72 (ICRP-72, Ref. 2).; The use of a statistical Material at Risk (MAR) representing the distribution of radiological loading of TRU waste containers based on the use of a plutonium-239 equivalent Curie (PE-Ci) methodology. The PE-Ci methodology simplifies accident analysis by allowing one to model releases based on the Curie value of one standard nuclide (e.g., Pu-239) instead of needing to model releases for every potential nuclide of interest. This is accomplished by normalizing the Curie value of all nuclides to a single Curie value of a standard nuclide by using a Weighting Factor that is a ratio of the DCFs associated with the nuclides and that of the standard nuclide. By using the ICRP-72 DCFs to calculate PE-Ci values used in the statistical MAR, the accident analysis that uses that statistical MAR will be consistent with the consequence methodology identified in DOE-STD- 5506-2007.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Development of National New Construction Weighting Factors for the Commercial Building Prototype Analyses (2008-2022)

The U.S. Department of Energy (DOE) tasked Pacific Northwest National Laboratory (PNNL) with updating commercial building construction weights for the purpose of estimating national and state-by-state energy savings impacts of changes made to various commercial energy codes and standards. A similar activity was last completed by PNNL in 2020 using disaggregate construction volume data acquired from the Dodge Data & Analytics database (formerly McGraw Hill) for the years 2003-2018 (Lei et al, 2020). As time passes, changes in economic and social demand reshape construction volume trends. For the current update, PNNL reviewed the same data source with the latest construction data for the years 2008-2022. For commercial building analyses, PNNL typically uses a suite of 16 prototype buildings simulated in the 19 ASHRAE climate zones with 16 of them present in the United States. The 2008-2022 commercial building weighting factors were derived using the same approach employed to develop the 2003-2018 set (Lei et al, 2020). Applying the construction volume data from the database to the prototypes and climate zones resulted in the following new construction area-based weighting factors. Table ES.1 shows the weighting factors including all building categories found in the database, and Table ES.2 shows the weighting factors normalized to include only buildings represented by the 16 prototypes. Section 3.0 also includes national- and state-level weighting factors by area and building count.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS2004

Multi sensor transducer and weight factor

A multi-sensor transducer and processing method allow insitu monitoring of the senor accuracy and transducer `health`. In one embodiment, the transducer has multiple sensors to provide corresponding output signals in response to a stimulus, such as pressure. A processor applies individual weight factors to reach of the output signals and provide a single transducer output that reduces the contribution from inaccurate sensors. The weight factors can be updated and stored. The processor can use the weight factors to provide a `health` of the transducer based upon the number of accurate versus in-accurate sensors in the transducer.

Immer, Christopher D.↗
DOE OSTI2020

Development of National New Construction Weighting Factors for the Commercial Building Prototype Analyses (2003-2018)

The U.S. Department of Energy (DOE), Office of Building Technologies tasked Pacific Northwest National Laboratory to develop construction weights for various commercial building categories for the purpose of estimating weighted national energy savings from the development of ANSI/ASHRAE/IESNA Standard 90.1-2019 compared to ANSI/ASHRAE/IESNA Standard 90.1-2016. Disaggregate construction volume data was acquired from the McGraw Hill Construction Database for the years 2003-2018 and analyzed to develop detailed construction weights by climate zones, subzones and by states. These weights are provided in this report and will be subsequently used in developing a weighted national energy savings estimate for the impact of the 2019 standard. For the current update, PNNL reviewed the same data source with the latest construction data for the years 2003-2018.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1976

Method of discrete modeling and its application to estimation of TF30 engine variables

A method of discrete modeling is presented that effectively isolates steady state model accuracy from dynamic model accuracy. The steady state model may be generated from the engine design equations with any desired degree of accuracy. The dynamic model is generated by applying a step disturbance of a manipulated variable to an open loop engine simulation. The sampled response of the variable is combined with the steady state model's response to form a set of weighting factors. These weighting factors are then used to weight past values of the manipulated variable, thus forming the dynamic model. The method is used to estimate various TF30-P-3 engine variables. A dynamic trim function is developed to compensate for the dynamic nonlinearities of the variables as well as for inaccuracies in dynamic definition. The trim function is shown to be realted to the square root of the sum of the squares of the weighting factors obtained at various engine operating conditions. Finally, the estimation of variables without dynamic modeling is discussed.

Arpasi, D. J.↗
NASA NTRS2010

A Rat Body Phantom for Radiation Analysis

To reduce the uncertainties associated with estimating the biological effects of ionizing radiation in tissue, researchers rely on laboratory experiments in which mono-energetic, single specie beams are applied to cell cultures, insects, and small animals. To estimate the radiation effects on astronauts in deep space or low Earth orbit, who are exposed to mixed field broad spectrum radiation, these experimental results are extrapolated and combined with other data to produce radiation quality factors, radiation weighting factors, and other risk related quantities for humans. One way to reduce the uncertainty associated with such extrapolations is to utilize analysis tools that are applicable to both laboratory and space environments. The use of physical and computational body phantoms to predict radiation exposure and its effects is well established and a wide range of human and non-human phantoms are in use today. In this paper, a computational rat phantom is presented, as well as a description of the process through which that phantom has been coupled to existing radiation analysis tools. Sample results are presented for two space radiation environments.

Qualls, Garry D.↗
NASA NTRS2017

Wind Tunnel Strain-Gage Balance Calibration Data Analysis Using a Weighted Least Squares Approach

A new approach is presented that uses a weighted least squares fit to analyze wind tunnel strain-gage balance calibration data. The weighted least squares fit is specifically designed to increase the influence of single-component loadings during the regression analysis. The weighted least squares fit also reduces the impact of calibration load schedule asymmetries on the predicted primary sensitivities of the balance gages. A weighting factor between zero and one is assigned to each calibration data point that depends on a simple count of its intentionally loaded load components or gages. The greater the number of a data point's intentionally loaded load components or gages is, the smaller its weighting factor becomes. The proposed approach is applicable to both the Iterative and Non-Iterative Methods that are used for the analysis of strain-gage balance calibration data in the aerospace testing community. The Iterative Method uses a reasonable estimate of the tare corrected load set as input for the determination of the weighting factors. The Non-Iterative Method, on the other hand, uses gage output differences relative to the natural zeros as input for the determination of the weighting factors. Machine calibration data of a six-component force balance is used to illustrate benefits of the proposed weighted least squares fit. In addition, a detailed derivation of the PRESS residuals associated with a weighted least squares fit is given in the appendices of the paper as this information could not be found in the literature. These PRESS residuals may be needed to evaluate the predictive capabilities of the final regression models that result from a weighted least squares fit of the balance calibration data.

calibration analysis↗
NASA NTRS2005

Template for Systems Engineering Tools Trade Study

A discussion of Systems Engineering tools brings out numerous preferences and reactions regarding tools of choice as well as the functions those tools are to perform. A recent study of Systems Engineering Tools for a new Program illustrated the need for a generic template for use by new Programs or Projects to determine the toolset appropriate for their use. This paper will provide the guidelines new initiatives can follow and tailor to their specific needs, to enable them to make their choice of tools in an efficient and informed manner. Clearly, those who perform purely technical functions will need different tools than those who perform purely systems engineering functions. And, everyone has tools they are comfortable with. That degree of comfort is frequently the deciding factor in tools choice rather than an objective study of all criteria and weighting factors. This paper strives to produce a comprehensive list of criteria for selection with suggestions for weighting factors based on a number of assumptions regarding the given Program or Project. In addition, any given Program will begin with assumptions for its toolset based on Program size, tool cost, user base and technical needs. In providing a template for tool selection, this paper will guide the reader through assumptions based on Program need; decision criteria; potential weighting factors; the need for a compilation of available tools; the importance of tool demonstrations; and finally a down selection of tools. While specific vendors cannot be mentioned in this work, it is expected that this template could serve other Programs in the formulation phase by alleviating the trade study process of some of its subjectivity.

Michelle D Bailey↗
NASA NTRS1997

Parallel interference cancellation for CDMA applications

The present invention provides a method of decoding a spread spectrum composite signal, the composite signal comprising plural user signals that have been spread with plural respective codes, wherein each coded signal is despread, averaged to produce a signal value, analyzed to produce a tentative decision, respread, summed with other respread signals to produce combined interference signals, the method comprising scaling the combined interference signals with a weighting factor to produce a scaled combined interference signal, scaling the composite signal with the weighting factor to produce a scaled composite signal, scaling the signal value by the complement of the weighting factor to produce a leakage signal, combining the scaled composite signal, the scaled combined interference signal and the leakage signal to produce an estimate of a respective user signal.

Divsalar, Dariush↗
DOE OSTI2021

Uniformly Ordered Binary Decision Algorithm for Benchmark Experiment Correlations in Whisper Validation

When performing a validation exercise for determining the upper subcritical limit of a nuclear criticality safety application, an analyst should select and perform a statistical analysis on a population of benchmark experiments that are neutronically similar to the application. The size of this population should be sufficiently large such that the statistical analysis has a high degree of confidence that the bias plus bias uncertainty (calculational margin) has been accurately quantified. A complication arises because many benchmark experiments share common components, leading to correlations in their measured effective multiplication factors. Correlations between benchmark experiments within the population reduces its predictive power. This motivates the need for methods that consider benchmark experiment correlations and ensure adequate statistical significance of results. The Whisper code is a statistical analysis pack- age that incorporates nuclear data sensitivity coefficients from MCNP to assess benchmark experiment similarity and then performs an extreme-value analysis to estimate the bias plus bias uncertainty. The original methodology in Whisper does not consider the effect of benchmark experiment correlations when making this estimation, and this summary proposes the uniformly ordered binary decision algorithm to address this shortcoming. The original methodology in Whisper computes similarity coefficients ck for an application compared to all benchmark experiments in its library and develops weighting factors for a selected population proportional to the ck values. The methodology can be interpreted as statistically emulating a validation exercise for a particular application where the weighting factors may be viewed as the likelihood that an analyst would include a particular benchmark experiment within the population. The effective sample size of the population is the expected or mean number of benchmark experiments in the population. The uniformly ordered binary decision algorithm identifies clusters of correlated benchmark experiments within the population and then computes adjusted weighting factors based on the magnitude of the correlation coefficients within the cluster to compute a reduced effective sample size accounting for the lower information content because of correlations. Benchmark experiments within the cluster are ordered randomly with equal probability and probabilistic decisions are made as to whether a benchmark. experiment within the cluster should treated as redundant with a previous one; if two redundant benchmark experiments are included, then the conservative worst case bias plus bias uncertainty is used and the pair is counted as a single benchmark experiment in the population. Results are provided for HEU solutions in a research version of the Whisper software using benchmark experiment correlations provided by DICE, the Database for the International Criticality Safety Benchmark Evaluation Project (ICSBEP). These show that there can be a significant increase in the bias plus bias uncertainty because the effective sample size is reduced, and therefore the algorithm, needing to meet sample size requirements, expands the benchmark experiment population by accepting less similar benchmark experiments that would have otherwise not been included.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1993

Vibrational nonequilibrium effects on diatomic dissociation rates

The collision-induced dissociation rate of diatomic molecules from a ladder of rotational and anharmonic vibrational states is developed, and the correction for vibrational nonequilibrium is considered. The result is similar to an analytic correction derived by Hammerling et al. (1959) for harmonic oscillators. An empirical correction algorithm suggested by Park (1987, 1990) gives similar results when vibrational temperature is comparable to kinetic temperature but underestimates the dissociation rate when vibrational temperature is small compared with the kinetic temperature. This algorithm uses an effective temperature in the experimentally determined Arrhenius expression for the rate coefficient, which is a weighted average of the vibrational and kinetic temperature, whereas theory indicates that kinetic temperature should appear only in the exponential term of the Arrhenius expression. Nevertheless, an effective temperature can always be found that will numerically duplicate the proper rate coefficient at any given condition, but a constant weighting factor cannot be expected to provide this. However, the algorithm can he adjusted to give reasonable results over a range of conditions if the geometric weighting factor is taken to be a simple linear function of the ratio of vibrational to kinetic temperature in the gas.

Hansen, C. F.↗
NASA NTRS1993

An adaptive grid/Navier-Stokes methodology for the calculation of nozzle afterbody base flows with a supersonic freestream

This paper describes an adaptive grid method for base flows in a supersonic freestream. The method is based on the direct finite-difference statement of the equidistribution principle. The weighting factor is a combination of the Mach number, density, and velocity first-derivative gradients in the radial direction. Two key ideas of the method are to smooth the weighting factor by using a type of implicit smoothing and to allow boundary points to move in the grid adaptation process. An AGARD nozzle afterbody base flow configuration is used to demonstrate the performance of the adaptive grid methodology. Computed base pressures are compared to experimental data. The adapted grid solutions offer a dramatic improvement in base pressure prediction compared to solutions computed on a nonadapted grid. A total-variation-diminishing (TVD) Navier-Stokes scheme is used to solve the governing flow equations.

Williams, Morgan↗
DOE OSTI2019

FGR 13 Dose Conversion Factor Files

The purpose of this document is to discuss the construction of two MACCS dose conversion factor (DCF) files in some detail, an older file created in 2007 named FGR13DCF.inp and a newer file created in 2018 called FGR13GyEquiv_RevA.inp. Very briefly, the difference between the two files is that the older file follows the standard conventions of assigning a radiation weighting factor of 20 for alpha radiation for all tissues and organs; whereas, the newer file complies with the FGR 13 health effects modeling and uses modified radiation weighting factors (referred to as relative biological effectiveness (RBE) factors) for alpha radiation of 10 for breast and of 1 for red bone marrow. During an intermediate period the creation of these two DCF files, a file called FGR13GyEquiv was created and used for the SOARCA calculations. This file was not released to the MACCS user community, but it is also discussed briefly in this document. DCF files are used by MACCS to convert air and ground radionuclide concentrations to doses to an organ or to the whole body. The MACCS calculation considers duration and shielding factor for each exposure pathway including cloudshine, groundshine, inhalation, and ingestion. Dose coefficients for cloudshine and groundshine are expressed as dose rates; dose coefficients for inhalation and ingestion are expressed as committed doses. In this document, dose coefficients (newer ICRP terminology) is used to describe the values contained in dose conversion factor (older ICRP terminology) files.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
DOE OSTI2019

FGR 13 Dose Conversion Factor Files

The purpose of this document is to discuss the construction of two MELCOR Accident Consequence Code System (MACCS) dose conversion factor (DCF) files in some detail, an older file created in 2007 named FGR13DCF.inp and a newer file created in 2018 called FGR13GyEquiv_RevAinp. Very briefly, the difference between the two files is that the older file follows the standard conventions of assigning a radiation weighting factor of 20 for alpha radiation for all tissues and organs; whereas, the newer file complies with the Federal Guidance Report (FGR) 13 health effects modeling and uses modified radiation weighting factors (referred to as relative biological effectiveness (RBE) factors) for alpha radiation of 10 for breast and of 1 for red bone marrow. During an intermediate period, a file called FGR13GyEquiv.inp was created and used for the State-of-the-Art Reactor Consequence Analysis (SOARCA) calculations. This file was not released to the MACCS user community, but it is also discussed briefly in this document.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
NASA NTRS1972

Optimal inputs for system identification

Identification criteria are presented for linear dynamic systems with and without process noise. With process noise, the state equations are replaced by the Kalman filter equations. If the identification performance index is expanded in a Taylor's series with respect to the parameters to be identified, then maximizing the weighting factor of the quadratic term with respect to the inputs will insure that an identification algorithm will converge more rapidly and to a more accurate result than with nonoptimal inputs. The expectation of this weighting factor is the Fisher information matrix, and its inverse is a lower bound for the covariance of the parameters. Direct and indirect methods of calculating the information matrix are presented for systems with and without process noise.

Reid, D. B.↗