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DOE OSTI2019

Understanding End‐of‐Century Snowpack Changes Over California's Sierra Nevada

Abstract This study uses dynamical and statistical methods to understand end‐of‐century mean changes to Sierra Nevada snowpack. Dynamical results reveal that middle‐elevation watersheds experience considerably more rain than snow during winter, leading to substantial snowpack declines by spring. Despite some high‐elevation watersheds receiving slightly more snow in January and February, the warming signal still dominates across the wet season and leads to notable declines by springtime. A statistical model is created to mimic dynamical results for 1 April snowpack, allowing for an efficient downscaling of all available general circulation models from the Coupled Model Intercomparison Project phase 5. For all general circulation models and emission scenarios, dramatic 1 April snowpack loss occurs at elevations below 2,500 m, despite increased precipitation in many general circulation models. Only 36% (±12%) of historical 1 April total snow water equivalent volume remains at the century's end under a “business‐as‐usual” emission scenario, with 70% (±12%) remaining under a realistic “mitigation” scenario.

Sun, Fengpeng↗

NASA NTRS2016

Real-Time Early Warning Techniques

Contemporary approaches to aerospace vehicle system monitoring rely heavily on thresholds that represent a compromise between providing warning early enough to avert a mishap while simultaneously minimizing false alarms. While this reliance on thresholds has been in place for decades and has permeated both cockpits and control rooms, we often find it insufficient when retrospectively analyzing data from an accident. To modernize and enhance flight test safety, we introduce new methods of monitoring for anomalous patterns of interaction rather than for thresholds exceedance. For systems with a well characterized baseline we show how the Inductive Monitoring System (IMS), utilized by NASA in the aftermath of the Columbia accident, might be implemented in real-time to provide earlier warning than currently employed techniques. For systems without such a baseline, we introduce new developments in statistical methods relating to critical slowing down, first applied in medicine and physics, which show promise for adaptation to flight test. Finally, the familiar resource constrained environment leads to a reliance on increased instrumentation that is challenging the limits of the current one-sensor, one-indicator threshold paradigm. Existing methods thus fail to accurately reflect the true complexity of a vehicle rich with interdependent interacting systems. We highlight these concepts in a brief summary of the 2001 Air Transat Flight 236 deadstick landing in the Azores. We then suggest control room and cockpit modifications to better display the information gleaned using these novel monitoring methods.

Javorsek, Dan↗

NASA NTRS2016

Enhancing Flight Test Safety with Real-Time Early Warning Techniques

Contemporary approaches to aerospace vehicle system monitoring rely heavily on thresholds that represent a compromise between providing warning early enough to avert a mishap while simultaneously minimizing false alarms. While this reliance on thresholds has been in place for decades and has permeated both cockpits and control rooms, we often find it insufficient when retrospectively analyzing data from an accident. To modernize and enhance flight test safety, we introduce new methods of monitoring for anomalous patterns of interaction rather than for thresholds exceedance. For systems with a well characterized baseline we show how the Inductive Monitoring System (IMS), utilized by NASA in the aftermath of the Columbia accident, might be implemented in real-time to provide earlier warning than currently employed techniques. For systems without such a baseline, we introduce new developments in statistical methods relating to critical slowing down, first applied in medicine and physics, which show promise for adaptation to flight test. Finally, the familiar resource constrained environment leads to a reliance on increased instrumentation that is challenging the limits of the current "one-sensor, one-indicator" threshold paradigm. Existing methods thus fail to accurately reflect the true complexity of a vehicle rich with interdependent interacting systems. We highlight these concepts in a brief summary of the 2001 Air Transat Flight 236 deadstick landing in the Azores. We then suggest control room and cockpit modifications to better display the information gleaned using these novel monitoring methods.

Javorsek, Daniel, II↗

DOE OSTI2017

Modeling Soot Oxidation and Gasification with Bayesian Statistics

This paper presents a statistical method for model calibration using data collected from literature. The method is used to calibrate parameters for global models of soot consumption in combustion systems. This consumption is broken into two different submodels: first for oxidation where soot particles are attacked by certain oxidizing agents; second for gasification where soot particles are attacked by H 2 O or CO 2 molecules. Rate data were collected from 19 studies in the literature and evaluated using Bayesian statistics to calibrate the model parameters. Bayesian statistics are valued in their ability to quantify uncertainty in modeling. The calibrated consumption model with quantified uncertainty is presented here along with a discussion of associated implications. The oxidation results are found to be consistent with previous studies. Significant variation is found in the CO 2 gasification rates.

01 COAL, LIGNITE, AND PEAT↗

NASA NTRS1995

Rainfall estimation from ESMIR-5 measurements and application to El Nino

An algorithm to estimate monthly 5 deg x 5 deg area-averaged rain rate over the oceans from January 1973 to December 1976 using single-channel microwave data from the Nimbus-5 satellite has been developed. This study extends the work of Shin et al. by including the full width of scan angles (from -50 deg to 50 deg) in order to reduce sampling error. The scan-angle dependence of the estimated rain rate due to variable antenna sidelobe effects, surface emissivity, and propagation pathlength is eliminated using a statistical method. A globally uniform beam-filling correction factor of 2.2 is applied in this study. Comparison with island station rainfall measurements over the Pacific shows a remarkably high correlation between two data in the equatorial dry zone and South Pacific convergence zone (SPCZ) but a low correlation in the extratropics and equatorial western Pacific. It is also proved that the retrieved rain rates are statistically significant. The rainfall deviations from non-El Nino years April 1973 to December 1975 reveal the temporal and spatial variations produced by the 1972-73 and 1976-77 El Nino episodes. We observe an increase of rainfall over the eastern and central equatorial Pacific Ocean and a decrease over the equatorial western Pacific Ocean and eastern Australia during these events. Consistent with previous work, the rainfall anomaly of the 1972-73 El Nino was much stronger than that of the 1976-77 El Nino.

Lim, Hyo-Suk↗

DOE OSTI2015

Uncertainty quantification in application of the enrichment meter principle for nondestructive assay of special nuclear material

The various methods of nondestructive assay (NDA) of special nuclear material (SNM) have applications in nuclear nonproliferation, including detection and identification of illicit SNM at border crossings, and quantifying SNM at nuclear facilities for safeguards. No assay method is complete without “error bars,” which provide one way of expressing confidence in the assay result. Consequently, NDA specialists typically quantify total uncertainty in terms of “random” and “systematic” components, and then specify error bars for the total mass estimate in multiple items. Uncertainty quantification (UQ) for NDA has always been important, but it is recognized that greater rigor is needed and achievable using modern statistical methods. To this end, we describe the extent to which the guideline for expressing uncertainty in measurements (GUM) can be used for NDA. Also, we propose improvements over GUM for NDA by illustrating UQ challenges that it does not address, including calibration with errors in predictors, model error, and item-specific biases. A case study is presented using low-resolution NaI spectra and applying the enrichment meter principle to estimate the U-235 mass in an item. The case study illustrates how to update the current American Society for Testing and Materials guide for application of the enrichment meter principle using gamma spectra from a NaI detector.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2016

Parameterizing the Variability and Uncertainty of Wind and Solar in CEMs

We present current and improved methods for estimating the capacity value and curtailment impacts from variable generation (VG) in capacity expansion models (CEMs). The ideal calculation of these variability metrics is through an explicit co-optimized investment-dispatch model using multiple years of VG and load data. Because of data and computational limitations, existing CEMs typically approximate these metrics using a subset of all hours from a single year and/or using statistical methods, which often do not capture the tail-event impacts or the broader set of interactions between VG, storage, and conventional generators. In our proposed new methods, we use hourly generation and load values across all hours of the year to characterize the (1) contribution of VG to system capacity during high load hours, (2) the curtailment level of VG, and (3) the reduction in VG curtailment due to storage and shutdown of select thermal generators. Using CEM model outputs from a preceding model solve period, we apply these methods to exogenously calculate capacity value and curtailment metrics for the subsequent model solve period. Preliminary results suggest that these hourly methods offer improved capacity value and curtailment representations of VG in the CEM from existing approximation methods without additional computational burdens.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2017

Evaluation of NMME temperature and precipitation bias and forecast skill for South Asia

Systematic error and forecast skill for temperature and precipitation in two regions of Southern Asia are investigated using hindcasts initialized May 1 from the North American Multi-Model Ensemble. We focus on two contiguous but geographically and dynamically diverse regions: the Extended Indian Monsoon Rainfall (70–100E, 10–30 N) and the nearby mountainous area of Pakistan and Afghanistan (60–75E, 23–39 N). Forecast skill is assessed using the Sign test framework, a rigorous statistical method that can be applied to non-Gaussian variables such as precipitation and to different ensemble sizes without introducing bias. We find that models show significant systematic error in both precipitation and temperature for both regions. The multi-model ensemble mean (MMEM) consistently yields the lowest systematic error and the highest forecast skill for both regions and variables. However, we also find that the MMEM consistently provides a statistically significant increase in skill over climatology only in the first month of the forecast. While the MMEM tends to provide higher overall skill than climatology later in the forecast, the differences are not significant at the 95% level. We also find that MMEMs constructed with a relatively small number of ensemble members per model can equal or outperform MMEMs constructed with more members in skill. This suggests some ensemble members either provide no contribution to overall skill or even detract from it.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

How Can Probabilistic Solar Power Forecasts Be Used to Lower Costs and Improve Reliability in Power Spot Markets? A Review and Application to Flexiramp Requirements

Net load uncertainty in electricity spot markets is rapidly growing. There are five general approaches by which system operators and market participants can use probabilistic forecasts of wind, solar, and load to help manage this uncertainty. These include operator situation awareness, resource risk hedging, reserves procurement, definition of contingencies, and explicit stochastic optimization. We review these approaches, and then provide a case study in which a method for using probabilistic solar forecasts to define needs for reserves is developed and evaluated. The case study has three parts. First, we describe building blocks for enhancing the Watt-Sun solar forecasting system to produce probabilistic irradiance and power forecasts. Second, relationships between Watt-Sun forecasts for multiple sites in California and the system's need for flexible ramp capability (flexiramp) are defined by machine learning and statistical methods. Third, the performance of present methods to defining flexiramp requirements, which are not conditioned on weather and renewables forecasts, is compared with that of probabilistic solar forecast-based requirements, using a multi-timescale production costing model with an 1820-bus representation of the WECC power system. Significant potential savings in fuel and flexiramp procurement costs from using solar-informed reserve requirements are found.

14 SOLAR ENERGY↗

NASA NTRS1992

Data exploration systems for databases

Data exploration systems apply machine learning techniques, multivariate statistical methods, information theory, and database theory to databases to identify significant relationships among the data and summarize information. The result of applying data exploration systems should be a better understanding of the structure of the data and a perspective of the data enabling an analyst to form hypotheses for interpreting the data. This paper argues that data exploration systems need a minimum amount of domain knowledge to guide both the statistical strategy and the interpretation of the resulting patterns discovered by these systems.

Greene, Richard J.↗

DOE OSTI2017

Employing Whisper in selecting benchmarks for traditional validation methods

The Nuclear Criticality Safety Program at Sandia National Laboratories (SNL) uses a collection of benchmarks developed from the International Handbook of Evaluated Criticality Safety Benchmark Experiments for validation of MCNP. In early 2016, an effort began to expand the benchmark collection to cover a broader range of materials and neutron spectra. The program undertook the task of updating current benchmarks to reflect best practices from Los Alamos National Laboratory (LANL) for MCNP calculations. Spring of 2016, LANL shared the Whisper code with SNL in a collaborated effort to investigate application of the code to activities at SNL. Whisper is a statistical package developed to support nuclear criticality safety validation efforts. It measures how well benchmarks correlate to a system or process and calculates a USL. Whisper has begun to develop into an asset for the SNL Nuclear Criticality Safety team to determine and reassure benchmarks selected for validation truly correlate process parameters (i.e., fall within an acceptable Area of Applicability). SNL's use of traditional statistical methods, with the abilities of Whisper to identify correlating benchmarks, has facilitated in ensuring confidence in validation and USL determination. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2016

Microscopic molecular dynamics characterization of the second-order non-Navier-Fourier constitutive laws in the Poiseuille gas flow

The second-order non-Navier-Fourier constitutive laws, expressed in a compact algebraic mathematical form, were validated for the force-driven Poiseuille gas flow by the deterministic atomic-level microscopic molecular dynamics (MD). Emphasis is placed on how completely different methods (a second-order continuum macroscopic theory based on the kinetic Boltzmann equation, the probabilistic mesoscopic direct simulation Monte Carlo, and, in particular, the deterministic microscopic MD) describe the non-classical physics, and whether the second-order non-Navier-Fourier constitutive laws derived from the continuum theory can be validated using MD solutions for the viscous stress and heat flux calculated directly from the molecular data using the statistical method. Peculiar behaviors (non-uniform tangent pressure profile and exotic instantaneous heat conduction from cold to hot [R. S. Myong, “A full analytical solution for the force-driven compressible Poiseuille gas flow based on a nonlinear coupled constitutive relation,” Phys. Fluids 23(1), 012002 (2011)]) were re-examined using atomic-level MD results. It was shown that all three results were in strong qualitative agreement with each other, implying that the second-order non-Navier-Fourier laws are indeed physically legitimate in the transition regime. Furthermore, it was shown that the non-Navier-Fourier constitutive laws are essential for describing non-zero normal stress and tangential heat flux, while the classical and non-classical laws remain similar for shear stress and normal heat flux.

42 ENGINEERING↗

DOE OSTI2017

OR14-V-Uncertainty-PD2La Uncertainty Quantification for Nuclear Safeguards and Nondestructive Assay Final Report

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2020

Herding Cats: Firm Non-Compliance in China’s Industrial Energy Efficiency Program

Here we study firm responses to a large-scale energy efficiency program in China, focusing on the quality of reporting and compliance outcomes. Using statistical methods to detect data manipulation in compliance reports, we find evidence that firms deliberately exaggerated performance during the first phase of the program (2006-2010), suggesting the high compliance rate was overstated. In its second phase (2011-2015), the number of firms in the program expanded by an order of magnitude, and the compliance rate decreased. We develop a simple model to show how the observed increase in non-compliance is consistent with reduced misreporting. Statistical tests find no evidence of manipulation in the second phase. Larger firms, especially those not controlled by the state, and firms in cities with relatively low growth were more likely to report non-compliance, which suggests a role for state control and local protectionism in shaping compliance decisions. Based on our findings, we offer several lessons for future program design.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2017

Are clear boundaries a prerequisite for well‐functioning collaboration in home health care? A mixed methods study

Aim The aim of this study was to examine whether professional collaboration in home health care is associated with clear boundaries between principals′ areas of responsibility and the professions areas of responsibility, respectively. Methods Data were derived from a web‐based survey that was carried out in one county in the middle of Sweden during spring 2013. Participants were health professionals and managers from the county council and from all the municipalities in the county. Both structured and open‐ended questions were utilised. A total of 421 individuals (90% women) answered the structured questions, and 91 individuals (22% of the 421) answered the open‐ended questions. Quantitative data were analysed with descriptive statistics methods, tests of independence and of correlation strength. Qualitative data were analysed with content analysis. Results The results from the structured questions showed that well‐functioning collaboration was associated with clear boundaries between principals in the county overall, and for respondents in two of three parts of the county. Association between clear boundaries between professions and well‐functioning collaboration was found in the county overall among the municipality population. However, in one part of the county, we did not find any correlations between well‐functioning collaboration and clear boundaries between professions or principals, with the exception of home help services. The analysis of the open questions gave similar results as the quantitative analysis, illustrated within three themes: The significance of concepts, trust and interdependence, and collaboration as a means for well‐being. Conclusion The results indicate that, recently after an organisational change, clear boundaries between the principals′ areas of responsibility and professions' area of responsibility respectively are necessary for effective cooperation between professionals. If the organisation and professionals have previous positive experience of colocated activities, clear boundaries do not share the same importance.

Beijer, Ulla↗

DOE OSTI2022

Estimation of process steady state with autoregressive models and Bayesian inference

To improve efficiency, separations engineers will typically design process circuits containing recirculating streams, which mix one or more of the process outputs with the feed material. Doing so can improve efficiency, but will cause a delay in the system reaching steady state conditions until the recirculating load mass flows stabilize. In testing separation circuits, engineers will often test a variety of factors and complete an analysis from sample results. Knowledge of if a process is at steady state, as well as the steady state conditions of a process, is essential for a valid techno-economic analysis. However, the definition of process steady state is often poorly defined, or does not include uncertainty quantification. If the performance of a process operating under two different sets of conditions are compared, an engineer who does not test for steady state or quantify steady state conditions risks producing a faulty analysis. In this work, a Bayesian statistical method for testing if all streams are at steady state is further motivated and then derived. Then after testing for steady state, the same model is used with a prior distribution that enforces a steady state assumption to estimate steady state conditions. Further, these methods were validated in a solvent extraction pilot plant where steady state conditions for all outflows were inferred with uncertainty quantification. Analysis is completed with functions available to the reader as part of the BayesMassBal (V 1.1.0) software package written in R.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2017

Statistical dielectronic recombination rates for multielectron ions in plasma

We describe the general analytic derivation of the dielectronic recombination (DR) rate coefficient for multielectron ions in a plasma based on the statistical theory of an atom in terms of the spatial distribution of the atomic electron density. The dielectronic recombination rates for complex multielectron tungsten ions are calculated numerically in a wide range of variation of the plasma temperature, which is important for modern nuclear fusion studies. The results of statistical theory are compared with the data obtained using level-by-level codes ADPAK, FAC, HULLAC, and experimental results. We consider different statistical DR models based on the Thomas–Fermi distribution, viz., integral and differential with respect to the orbital angular momenta of the ion core and the trapped electron, as well as the Rost model, which is an analog of the Frank–Condon model as applied to atomic structures. In view of its universality and relative simplicity, the statistical approach can be used for obtaining express estimates of the dielectronic recombination rate coefficients in complex calculations of the parameters of the thermonuclear plasmas. The application of statistical methods also provides information for the dielectronic recombination rates with much smaller computer time expenditures as compared to available level-by-level codes.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2017

Uncertainty quantification for optical model parameters

Although uncertainty quantification has been making its way into nuclear theory, these methods have yet to be explored in the context of reaction theory. For example, it is well known that different parameterizations of the optical potential can result in different cross sections, but these differences have not been systematically studied and quantified. The purpose of our work is to investigate the uncertainties in nuclear reactions that result from fitting a given model to elastic-scattering data, as well as to study how these uncertainties propagate to the inelastic and transfer channels. We use statistical methods to determine a best fit and create corresponding 95% confidence bands. A simple model of the process is fit to elastic-scattering data and used to predict either inelastic or transfer cross sections. In this initial work, we assume that our model is correct, and the only uncertainties come from the variation of the fit parameters. Here, we study a number of reactions involving neutron and deuteron projectiles with energies in the range of 5–25 MeV/u, on targets with mass A=12–208. We investigate the correlations between the parameters in the fit. The case of deuterons on 12 C is discussed in detail: the elastic-scattering fit and the prediction of 12 C(d,p) 13 C transfer angular distributions, using both uncorrelated and correlated χ 2 minimization functions. The general features for all cases are compiled in a systematic manner to identify trends. This work shows that, in many cases, the correlated χ 2 functions (in comparison to the uncorrelated χ 2 functions) provide a more natural parameterization of the process. These correlated functions do, however, produce broader confidence bands. Further optimization may require improvement in the models themselves and/or more information included in the fit.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗