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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Data and scripts associated with “Sequential Precipitation Input Tagging (SPIT) to Estimate Water Transit Times and Hydrologic Tracer Dynamics within Water-Tagging Enabled Hydrologic Models” (v3)

This data package is associated with the publication “Sequential Precipitation Input Tagging (SPIT) to Estimate Water Transit Times and Hydrologic Tracer Dynamics within Water-Tagging Enabled Hydrologic Models” submitted to Journal of Advances in Modeling Earth Systems (Butler et al. 2025). This study developed the Sequential Precipitation Input Tagging (SPIT) framework to tag input precipitation and estimate water transit times and hydrologic tracers. SPIT tags all precipitation events at regular intervals over an extended period (monthly tags over seven years) in a hydrologic model from 2016-2022. SPIT is applied at six National Ecological Observatory Network (NEON) sites across the continental United States to calculate transit time distributions (TTD) and derive from these mean transit times (MTT), fractions of young water (Fyw), and hydrologic tracer concentrations in stream water (δ18O) within a water-tagging enabled version of the Weather Research and Forecast (WT-WRF-Hydro) model with national water model (NWM) configurations. We go on to validate WT-WRF-Hydro estimates against Butler et al. (2023), who analyzed the same NEON sites using stable water isotope data to estimate water transit times. This new tracking method provides a detailed picture of water movement and helps improve predictions about water availability in the future. This data package was originally published in January 2025. It was updated May 2025 (v2; new and modified files) and October 2025 (v3; new and modified files). File and folder names were not revised to indicate changes. See the change history section in the readme for more details. This data package contains the data and scripts used to develop the SPIT framework WT-WRF-Hydro (Water Tagging Weather Research and Forecasting Hydrologic) model and is associated with the following GitHub repository: https://github.com/zbutler33/SPIT-Framework. This data package contains five parent folders: (1) “Manipulated_outputs”, (2) “Metadata”, (3) “Observed”, (4) “Outputs”, and (5) “Scripts”. Each of these parent folders contains additional subfolders and files. Please see the FLMD (“v*_Butler_2024_WT_WRF_Hydro_flmd.csv”) for a list of all the files contained in this data package and descriptions for each. See the data dictionary (“v*_Butler_2024_WT_WRF_Hydro_dd.csv”) for definitions and units of all of the tabular (files ending in “.csv” and ".tsv") column headers.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

The Effects of Atmospheric Models on the Estimation of Infrasonic Source Functions at the Source Physics Experiment

We invert infrasound signals for an equivalent seismoacoustic source function using different atmospheric models to produce the necessary Green’s functions. The infrasound signals were produced by a series of underground chemical explosions as part of the Source Physics Experiment (SPE). In a previous study, we inverted the infrasound data using so-called predictive atmospheric models, which were based on historic, regional-scaled, publicly available weather observations interpolated onto a 3D grid. For the work presented here, we invert the same infrasound data, but using atmospheric models based on weather data collected in a time window that includes the approximate time of the explosion experiments, which we term postdictive models. We build two versions of the postdictive models for each SPE event: one that is based solely on the regional scaled observations, and one that is based on both regional scaled observations combined with on-site observations obtained by a weather sonde released at the time of the SPE. We then invert the observed data set three times, once for each atmospheric model type. We find that the estimated seismoacoustic source functions are relatively similar in waveform shape regardless of which atmospheric model that we used to construct the Green’s functions. However, we find that the amplitude of the estimated source functions is systematically dependent on the atmospheric model type: using the predictive atmospheric models to invert the data generally yields estimated source functions that are larger in amplitude than those estimated using the postdictive models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Using a 1D Radially Symmetric Coda Envelope Model for Robust Moment Magnitude ( M w ) Estimation in Iraq’s Tectonically Diverse Zones

Robust estimation of moment magnitude (M w ) can be challenging for Iraq due to the strong lateral heterogeneity across diverse tectonic zones. We aim to improve moment magnitude estimation by investigating the reliability of using a 1D coda envelope model in diverse tectonic zones of different lateral effects and offer a way forward for reliable estimates of M w for small events that are difficult to waveform model. Iraq comprises two main tectonic zones: (1) the Outer platform, consisting of the northwestern Zagros fold-thrust belt and the Mesopotamian foredeep, and (2) the Inner Arabian platform which is overlain by the Iraqi desert. A simple 1D coda envelope model was used because coda waves have a low sensitivity to the source and path heterogeneity. Three separate coda calibrations were conducted to investigate the robustness of a single 1D calibration to fit the country: Whole-region calibration, Zagros calibration, and Mesopotamia calibration. In the whole-region calibration, we used stations from both the Zagros and Mesopotamia zones. In the two other calibration models, we used only stations that were in those particular zones. Ground-truth reference spectra derived from the coda spectral ratio method were used to constrain high-frequency site terms. There was no drastic difference when comparing the moment magnitudes calculated from the waveform modeling and the three calibration models. The results show that the 1D coda envelope model is a reliable method even for a region with diverse tectonic zones. Therefore, we recommend using the whole-region calibration model for moment magnitude estimation that provides more complete path coverage and avoids biases introduced by path correction failures. The proposed calibration is a fundamental step in updating the comprehensive earthquake catalog and probabilistic seismic hazard assessments for Iraq.

58 GEOSCIENCES↗
DOE OSTI2022

Estimating Explosion Yields Using Moment Tensor Solutions and Seismic Moment

We report seismic moment, a measurable and well-understood quantity of seismic sources, is used to estimate the yield of explosions. Application of such a method in the past, as in the manner of m b -derived yields, has been complicated by the effect of variations in the explosion working point, depth, and secondary source effects (such as spalling and tectonic release) on the observed moment. We start using the full (six-element) moment tensor solution, which can capture the relevant source physics and, at least in theory, better isolate the primary explosion source. The moment-to-yield ratio is then estimated using an explosion source model which, provided with emplacement conditions, can relate the two parameters. We discuss the major sources of uncertainty associated with the method, and calibrate it with chemical and nuclear explosions at the Nevada National Security Site. We then apply the method to published moment tensor solutions for the six declared North Korean nuclear explosions that occurred between 2006 and 2017. The results are mostly consistent with other yield estimates made using a variety of high-frequency methods. This technique is a new approach to estimating explosive yield and simple to implement, as much of the complexity is captured by the source models.

58 GEOSCIENCES↗
DOE OSTI2012

Using Utility Load Data to Estimate Demand for Space Cooling and Potential for Shiftable Loads

This paper describes a simple method to estimate hourly cooling demand from historical utility load data. It compares total hourly demand to demand on cool days and compares these estimates of total cooling demand to previous regional and national estimates. Load profiles generated from this method may be used to estimate the potential for aggregated demand response or load shifting via coldstorage.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2013

Photogrammetry and Laser Imagery Tests for Tank Waste Volume Estimates: Summary Report

Feasibility tests were conducted using photogrammetry and laser technologies to estimate the volume of waste in a tank. These technologies were compared with video Camera/CAD Modeling System (CCMS) estimates; the current method used for post-retrieval waste volume estimates. This report summarizes test results and presents recommendations for further development and deployment of technologies to provide more accurate and faster waste volume estimates in support of tank retrieval and closure.

Photogrammetry↗
DOE OSTI2014

Enabling Predictive Simulation and UQ of Complex Multiphysics PDE Systems by the Development of Goal-Oriented Variational Sensitivity Analysis and A Posteriori Error Estimation Methods

It was demonstrated that a posteriori analyses in general and in particular one that uses adjoint methods can accurately and efficiently compute numerical error estimates and sensitivity for critical Quantities of Interest (QoIs) that depend on a large number of parameters. Activities include: analysis and implementation of several time integration techniques for solving system of ODEs as typically obtained from spatial discretization of PDE systems; multirate integration methods for ordinary differential equations; formulation and analysis of an iterative multi-discretization Galerkin finite element method for multi-scale reaction-diffusion equations; investigation of an inexpensive postprocessing technique to estimate the error of finite element solution of the second-order quasi-linear elliptic problems measured in some global metrics; investigation of an application of the residual-based a posteriori error estimates to symmetric interior penalty discontinuous Galerkin method for solving a class of second order quasi-linear elliptic problems; a posteriori analysis of explicit time integrations for system of linear ordinary differential equations; derivation of accurate a posteriori goal oriented error estimates for a user-defined quantity of interest for two classes of first and second order IMEX schemes for advection-diffusion-reaction problems; Postprocessing finite element solution; and A Bayesian Framework for Uncertain Quantification of Porous Media Flows.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Estimating customer electricity savings from projects installed by the U.S. ESCO industry

The U.S. energy service company (ESCO) industry has a well-established track record of delivering substantial energy and dollar savings in the public and institutional facilities sector, typically through the use of energy savings performance contracts (ESPC) (Larsen et al. 2012; Goldman et al. 2005; Hopper et al. 2005, Stuart et al. 2013). This ~$6.4 billion industry, which is expected to grow significantly over the next five years, may play an important role in achieving demand-side energy efficiency under local/state/federal environmental policy goals. To date, there has been little or no research in the public domain to estimate electricity savings for the entire U.S. ESCO industry. Estimating these savings levels is a foundational step in order to determine total avoided greenhouse gas (GHG) emissions from demand-side energy efficiency measures installed by U.S. ESCOs. We introduce a method to estimate the total amount of electricity saved by projects implemented by the U.S. ESCO industry using the Lawrence Berkeley National Laboratory (LBNL) /National Association of Energy Service Companies (NAESCO) database of projects and LBNL’s biennial industry survey. We report two metrics: incremental electricity savings and savings from ESCO projects that are active in a given year (e.g., 2012). Overall, we estimate that in 2012 active U.S. ESCO industry projects generated about 34 TWh of electricity savings—15 TWh of these electricity savings were for MUSH market customers who did not rely on utility customer-funded energy efficiency programs (see Figure 1). This analysis shows that almost two-thirds of 2012 electricity savings in municipal, local and state government facilities, universities/colleges, K-12 schools, and healthcare facilities (i.e., the so-called “MUSH” market) were not supported by a utility customer-funded energy efficiency program.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2014

Estimation of k-ε parameters using surrogate models and jet-in-crossflow data

We demonstrate a Bayesian method that can be used to calibrate computationally expensive 3D RANS (Reynolds Av- eraged Navier Stokes) models with complex response surfaces. Such calibrations, conditioned on experimental data, can yield turbulence model parameters as probability density functions (PDF), concisely capturing the uncertainty in the parameter estimates. Methods such as Markov chain Monte Carlo (MCMC) estimate the PDF by sampling, with each sample requiring a run of the RANS model. Consequently a quick-running surrogate is used instead to the RANS simulator. The surrogate can be very difficult to design if the model's response i.e., the dependence of the calibration variable (the observable) on the parameter being estimated is complex. We show how the training data used to construct the surrogate can be employed to isolate a promising and physically realistic part of the parameter space, within which the response is well-behaved and easily modeled. We design a classifier, based on treed linear models, to model the "well-behaved region". This classifier serves as a prior in a Bayesian calibration study aimed at estimating 3 k - ε parameters ( C μ , C ε2 , C ε1 ) from experimental data of a transonic jet-in-crossflow interaction. The robustness of the calibration is investigated by checking its predictions of variables not included in the cal- ibration data. We also check the limit of applicability of the calibration by testing at off-calibration flow regimes. We find that calibration yield turbulence model parameters which predict the flowfield far better than when the nomi- nal values of the parameters are used. Substantial improvements are still obtained when we use the calibrated RANS model to predict jet-in-crossflow at Mach numbers and jet strengths quite different from those used to generate the ex- perimental (calibration) data. Thus the primary reason for poor predictive skill of RANS, when using nominal values of the turbulence model parameters, was parametric uncertainty, which was rectified by calibration. Post-calibration, the dominant contribution to model inaccuraries are due to the structural errors in RANS.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2012

Evaluation of an Incremental Ventilation Energy Model for Estimating Impacts of Air Sealing and Mechanical Ventilation

Changing the rate of airflow through a home affects the annual thermal conditioning energy. Large-scale changes to airflow rates of the housing stock can significantly alter the energy consumption of the residential energy sector. However, the complexity of existing residential energy models hampers the ability to estimate the impact of policy changes on a state or nationwide level. The Incremental Ventilation Energy (IVE) model developed in this study was designed to combine the output of simple airflow models and a limited set of home characteristics to estimate the associated change in energy demand of homes. The IVE model was designed specifically to enable modelers to use existing databases of home characteristics to determine the impact of policy on ventilation at a population scale. In this report, we describe the IVE model and demonstrate that its estimates of energy change are comparable to the estimates of a wellvalidated, complex residential energy model when applied to homes with limited parameterization. Homes with extensive parameterization would be more accurately characterized by complex residential energy models. The demonstration included a range of home types, climates, and ventilation systems that cover a large fraction of the residential housing sector.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2015

Parameter Estimation for Single Diode Models of Photovoltaic Modules

Many popular models for photovoltaic system performance employ a single diode model to compute the I - V curve for a module or string of modules at given irradiance and temperature conditions. A single diode model requires a number of parameters to be estimated from measured I - V curves. Many available parameter estimation methods use only short circuit, o pen circuit and maximum power points for a single I - V curve at standard test conditions together with temperature coefficients determined separately for individual cells. In contrast, module testing frequently records I - V curves over a wide range of irradi ance and temperature conditions which, when available , should also be used to parameterize the performance model. We present a parameter estimation method that makes use of a fu ll range of available I - V curves. We verify the accuracy of the method by recov ering known parameter values from simulated I - V curves . We validate the method by estimating model parameters for a module using outdoor test data and predicting the outdoor performance of the module.

14 SOLAR ENERGY↗
DOE OSTI2014

Band Limited Correlation Estimates for A(ξω/U) and B(ηω/U) Using Beresh et. al. 2013 Data Sets

Here we discuss an improved Corcos (Corcos (1963), (1963)) style cross spectral density utilizing zero pressure gradient, supersonic (Beresh et. al. (2013)) data sets. Using the connection between narrow band measurements with broadband cross-spectral density, i.e. Γ(ξ ,η ,ω )= Φ (ω) A(ωη/U )exp (-i ωξ/U) we focus on estimating coherence expressions of the form: A (ξω nb /U) and B (ηω nb / U) where ω nb denotes the narrow band frequency, i.e. the band center frequency value and ξ and η are sensors spacing in streamwise/longitudinal and cross-stream/lateral directions, respectively. A methodology to estimate the parameters which retains the Corcos exponential functional form, A(ξω/U)=exp(-k lat ηω/U) but identifies new parameters (constants) consistent with the Beresh et. al. data sets is discussed. The Corcos result requires that the data be properly explained by self-similar variable: ξω/U and ηω/U. The longitudinal (streamwise) variable ξω/U tends to provide a better data collapse, while, consistent with the literature the lateral ηω/U is only successful for higher band center frequencies. Assuming the similarity variables provide a useful description of the data, the longitudinal coherence decay constant result using the Beresh et. al. data sets yields a value for the longitudinal constant k long ≈0.36-0.28 that is approximately 3x larger than the “traditional” (low speed, large Reynolds number and zero pressure gradient) of k long ≈0.11. We suggest that the most likely reason that the Beresh et. al. data sets incur increased longitudinal decay which results in reduced coherence lengths is due to wall shear induced compression causing an adverse pressure gradient. Focusing on the higher band center frequency measurements where the frequency dependent similarity variables are applicable, the lateral or transverse coherence decay constant k lat ≈0.7 is consistent with the “traditional” (low speed, large Reynolds number and zero pressure gradient). It should be noted, that the longitudinal/streamwise coherence decay deviates from the value observed by other researchers while the lateral/ cross-stream value is consistent has been observed by other researchers. We believe that while the measurements used to obtain new decay constant estimates are from internal wind tunnel tests, they likely provide a useful estimate expected reentry flow behavior and are therefore recommended for use. These data could also be useful in determining the uncertainty of correlation length for a uncertainty quantification (UQ) analysis.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Input-Output Model for MACCS Nuclear Accident Imp Acts Estimation

Since the original economic model for MACCS was developed, better quality economic data (as well as the tools to gather and process it) and better computational capabilities have become available. The update of the economic impacts component of the MACCS legacy model will provide improved estimates of business disruptions through the use of Input-Output based economic impact estimation. This paper presents an updated MACCS model, bases on Input-Output methodology, in which economic impacts are calculated using the Regional Economic Accounting analysis tool (REAcct) created at Sandia National Laboratories. This new GDP-based model allows quick and consistent estimation of gross domestic product (GDP) losses due to nuclear power plant accidents. This paper outlines the steps taken to combine the REAcct Input-Output-based model with the MACCS code, describes the GDP loss calculation, and discusses the parameters and modeling assumptions necessary for the estimation of long-term effects of nuclear power plant accidents.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2015

GPU Acceleration of Mean Free Path Based Kernel Density Estimators for Monte Carlo Neutronics Simulations

Kernel Density Estimators (KDEs) are a non-parametric density estimation technique that has recently been applied to Monte Carlo radiation transport simulations. Kernel density estimators are an alternative to histogram tallies for obtaining global solutions in Monte Carlo tallies. With KDEs, a single event, either a collision or particle track, can contribute to the score at multiple tally points with the uncertainty at those points being independent of the desired resolution of the solution. Thus, KDEs show potential for obtaining estimates of a global solution with reduced variance when compared to a histogram. Previously, KDEs have been applied to neutronics for one-group reactor physics problems and fixed source shielding applications. However, little work was done to obtain reaction rates using KDEs. This paper introduces a new form of the MFP KDE that is capable of handling general geometries. Furthermore, extending the MFP KDE to 2-D problems in continuous energy introduces inaccuracies to the solution. An ad-hoc solution to these inaccuracies is introduced that produces errors smaller than 4% at material interfaces.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2016

Numerical Estimation of the Spent Fuel Ratio

Sabotage of spent nuclear fuel casks remains a concern nearly forty years after attacks against shipment casks were first analyzed and has a renewed relevance in the post-9/11 environment. A limited number of full-scale tests and supporting efforts using surrogate materials, typically depleted uranium dioxide (DUO 2 ), have been conducted in the interim to more definitively determine the source term from these postulated events. However, the validity of these large- scale results remain in question due to the lack of a defensible spent fuel ratio (SFR), defined as the amount of respirable aerosol generated by an attack on a mass of spent fuel compared to that of an otherwise identical surrogate. Previous attempts to define the SFR in the 1980's have resulted in estimates ranging from 0.42 to 12 and include suboptimal experimental techniques and data comparisons. Because of the large uncertainty surrounding the SFR, estimates of releases from security-related events may be unnecessarily conservative. Credible arguments exist that the SFR does not exceed a value of unity. A defensible determination of the SFR in this lower range would greatly reduce the calculated risk associated with the transport and storage of spent nuclear fuel in dry cask systems. In the present work, the shock physics codes CTH and ALE3D were used to simulate spent nuclear fuel (SNF) and DUO 2 targets impacted by a high-velocity jet at an ambient temperature condition. These preliminary results are used to illustrate an approach to estimate the respirable release fraction for each type of material and ultimately, an estimate of the SFR. This page intentionally blank

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2017

An Improved Global Wind Resource Estimate for Integrated Assessment Models: Preprint

This paper summarizes initial steps to improving the robustness and accuracy of global renewable resource and techno-economic assessments for use in integrated assessment models. We outline a method to construct country-level wind resource supply curves, delineated by resource quality and other parameters. Using mesoscale reanalysis data, we generate estimates for wind quality, both terrestrial and offshore, across the globe. Because not all land or water area is suitable for development, appropriate database layers provide exclusions to reduce the total resource to its technical potential. We expand upon estimates from related studies by: using a globally consistent data source of uniquely detailed wind speed characterizations; assuming a non-constant coefficient of performance for adjusting power curves for altitude; categorizing the distance from resource sites to the electric power grid; and characterizing offshore exclusions on the basis of sea ice concentrations. The product, then, is technical potential by country, classified by resource quality as determined by net capacity factor. Additional classifications dimensions are available, including distance to transmission networks for terrestrial wind and distance to shore and water depth for offshore. We estimate the total global wind generation potential of 560 PWh for terrestrial wind with 90% of resource classified as low-to-mid quality, and 315 PWh for offshore wind with 67% classified as mid-to-high quality. These estimates are based on 3.5 MW composite wind turbines with 90 m hub heights, 0.95 availability, 90% array efficiency, and 5 MW/km2 deployment density in non-excluded areas. We compare the underlying technical assumption and results with other global assessments.

17 WIND ENERGY↗
DOE OSTI2016

Effect of Using Different Vehicle Weight Groups on the Estimated Relationship Between Mass Reduction and U.S. Societal Fatality Risk per Vehicle Miles of Travel

This report recalculates the estimated relationship between vehicle mass and societal fatality risk, using alternative groupings by vehicle weight, to test whether the trend of decreasing fatality risk from mass reduction as case vehicle mass increases, holds over smaller increments of the range in case vehicle masses. The NHTSA baseline regression model estimates the relationship using for two weight groups for cars and light trucks; we re-estimated the mass reduction coefficients using four, six, and eight bins of vehicle mass. The estimated effect of mass reduction on societal fatality risk was not consistent over the range in vehicle masses in these weight bins. These results suggest that the relationship indicated by the NHTSA baseline model is a result of other, unmeasured attributes of the mix of vehicles in the lighter vs. heavier weight bins, and not necessarily the result of a correlation between mass reduction and societal fatality risk. An analysis of the average vehicle, driver, and crash characteristics across the various weight groupings did not reveal any strong trends that might explain the lack of a consistent trend of decreasing fatality risk from mass reduction in heavier vehicles.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2017

Ladtap XL Version 2017: A Spreadsheet For Estimating Dose Resulting From Aqueous Releases

LADTAP XL© is an EXCEL© spreadsheet used to estimate dose to offsite individuals and populations resulting from routine and accidental releases of radioactive materials to the Savannah River. LADTAP XL© contains two worksheets: LADTAP and IRRIDOSE. The LADTAP worksheet estimates dose for environmental pathways including external exposure resulting from recreational activities on the Savannah River and internal exposure resulting from ingestion of water, fish, and invertebrates originating from the Savannah River. IRRIDOSE estimates offsite dose to individuals and populations from irrigation of foodstuffs with contaminated water from the Savannah River. In 2004, a complete description of the LADTAP XL© code and an associated user’s manual was documented in LADTAP XL©: A Spreadsheet for Estimating Dose Resulting from Aqueous Release (WSRC-TR-2004-00059) and revised input parameters, dose coefficients, and radionuclide decay constants were incorporated into LADTAP XL© Version 2013 (SRNL-STI-2011-00238). LADTAP XL© Version 2017 is a slight modification to Version 2013 with minor changes made for more user-friendly parameter inputs and organization, updates in the time conversion factors used within the dose calculations, and fixed an issue with the expected time build-up parameter referenced within the population shoreline dose calculations. This manual has been produced to update the code description, verification of the models, and provide an updated user’s manual. LADTAP XL© Version 2017 has been verified by Minter (2017) and is ready for use at the Savannah River Site (SRS).

61 RADIATION PROTECTION AND DOSIMETRY↗