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NASA NTRS2016

Estimating Snow Water Storage in North America Using CLM4, DART, and Snow Radiance Data Assimilation

This paper addresses continental-scale snow estimates in North America using a recently developed snow radiance assimilation (RA) system. A series of RA experiments with the ensemble adjustment Kalman filter are conducted by assimilating the Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) brightness temperature T(sub B) at 18.7- and 36.5-GHz vertical polarization channels. The overall RA performance in estimating snow depth for North America is improved by simultaneously updating the Community Land Model, version 4 (CLM4), snow/soil states and radiative transfer model (RTM) parameters involved in predicting T(sub B) based on their correlations with the prior T(sub B) (i.e., rule-based RA), although degradations are also observed. The RA system exhibits a more mixed performance for snow cover fraction estimates. Compared to the open-loop run (0.171m RMSE), the overall snow depth estimates are improved by 1.6% (0.168m RMSE) in the rule-based RA whereas the default RA (without a rule) results in a degradation of 3.6% (0.177mRMSE). Significant improvement of the snow depth estimates in the rule-based RA as observed for tundra snow class (11.5%, p < 0.05) and bare soil land-cover type (13.5%, p < 0.05). However, the overall improvement is not significant (p = 0.135) because snow estimates are degraded or marginally improved for other snow classes and land covers, especially the taiga snow class and forest land cover (7.1% and 7.3% degradations, respectively). The current RA system needs to be further refined to enhance snow estimates for various snow types and forested regions.

snow depth↗

DOE OSTI2021

Assessing the predictive impact of factor fixing with an adaptive uncertainty-based approach .

Despite widespread use of factor fixing in environmental modeling, its effect on model predictions has received little attention and is instead commonly presumed to be negligible. We propose a proof-of-concept adaptive method for systematically investigating the impact of factor fixing. The method uses Global Sensitivity Analysis methods to identify groups of sensitive parameters, then quantifies which groups can be safely fixed at nominal values without exceeding a maximum acceptable error, demonstrated using the 21-dimensional Sobol’ G-function. Furthermore, three error measures are considered for quantities of interest, namely Relative Mean Absolute Error, Pearson Product-Moment Correlation and Relative Variance. Results demonstrate that factor fixing may cause large errors in the model results unexpectedly, when preliminary analysis suggests otherwise, and that the default value selected affects the number of factors to fix. To improve the applicability and methodological development of factor fixing, a new research agenda encompassing five opportunities is discussed for further attention.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2011

Identification of $\tau$ leptons and Higgs boson search in the $\mu+\tau$ final state at the D0 experiment at the Tevatron

The gauge symmetry is the heart of our understanding of the electroweak interaction and describes all the current experimental results. However, the intrinsic incompatibility between the gauge invariance and the mass of particles leads to the introduction of a new particle, the Higgs boson, for which we have no experimental evidence as of today. This thesis describes the Higgs boson search in the μ + τ final state in 7.3 fb -1 of pp collisions at √s = 1.96 TeV collected by the DØ detector at the Tevatron. This analysis completes the golden channels (dimuons, electron-muon, dielectrons) exploiting the decay chain H → WW → ℓvℓv , which is the main Higgs boson decay mode in the mass window accessible to the Tevatron. Since the final state includes a lepton, work was done to improve their identification among jets. An increase of 15% was achieved thanks to the the following : changing tuning parameters for the identification neural network, use of the kinematical dependence of the algorithm performances, incorporation of the τ lepton life time information and full study of the additionnal information coming from the central preshower measurements. Then, since the dominant background of the μ + τ Higgs boson search is W+jets (where one jet fakes a τ ), a method was developed to obtain good modeling of this background, not provided by the default simulation. This method is based, among other things, on the charge correlation between the muon and the τ candidate which allows for calibration of this background in the data excluding the signal region. Finally, all the kinematic and/or topological differences between the signal and the background were exploited to optimize this search, reaching an (observed) expected sensitivity of 7.8 (6.6) times the Standard Model for m H = 165 GeV=c 2 . In addition, this result was also interpreted in a fourth fermion generation scenario. For the first time, this analysis is included in the D and Tevatron combinations, both presented at Moriond EW and EPS 2011.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2014

Analysis of DOE's Roof Savings Calculator with Comparison to other Simulation Engines

A web-based Roof Savings Calculator (RSC) has been deployed for the Department of Energy as an industry-consensus tool to help building owners, manufacturers, distributors, contractors and researchers easily run complex roof and attic simulations. This tool employs the latest web technologies and usability design to provide an easy input interface to an annual simulation of hour-by-hour, whole-building performance using the world-class simulation tools DOE-2.1E and AtticSim. Building defaults were assigned based on national averages and can provide estimated annual energy and cost savings after the user selects nothing more than building location. In addition to cool reflective roofs, the RSC tool can simulate multiple roof and attic configurations including different roof slopes, above sheathing ventilation, radiant barriers, low-emittance surfaces, HVAC duct location, duct leakage rates, multiple layers of building materials, ceiling and deck insulation levels, and other parameters. A base case and energy-efficient alternative can be compared side-by-side to generate an energy/cost savings estimate between two buildings. The RSC tool was benchmarked against field data for demonstration homes in Ft. Irwin, CA. However, RSC gives different energy savings estimates than previous cool roof simulation tools so more thorough software and empirical validation proved necessary. This report consolidates much of the preliminary analysis for comparison of RSC s projected energy savings to that from other simulation engines.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2016

MO-DE-BRA-04: Hands-On Fluoroscopy Safety Training with Real-Time Patient and Staff Dosimetry

Purpose: Fluoroscopically guided interventions (FGI) are routinely performed across many different hospital departments. However, many involved staff members have minimal training regarding safe and optimal use of fluoroscopy systems. We developed and taught a hands-on fluoroscopy safety class incorporating real-time patient and staff dosimetry in order to promote safer and more optimal use of fluoroscopy during FGI. Methods: The hands-on fluoroscopy safety class is taught in an FGI suite, unique to each department. A patient equivalent phantom is set on the patient table with an ion chamber positioned at the x-ray beam entrance to the phantom. This provides a surrogate measure of patient entrance dose. Multiple solid state dosimeters (RaySafe i2 dosimetry systemTM) are deployed at different distances from the phantom (0.1, 1, 3 meters), which provide surrogate measures of staff dose. Instructors direct participating clinical staff to operate the fluoroscopy system as they view live fluoroscopic images, patient entrance dose, and staff doses in real-time. During class, instructors work with clinical staff to investigate how patient entrance dose, staff doses, and image quality are affected by different parameters, including pulse rate, magnification, collimation, beam angulation, imaging mode, system geometry, distance, and shielding. Results: Real-time dose visualization enables clinical staff to directly see and learn how to optimize their use of their own fluoroscopy system to minimize patient and staff dose, yet maintain sufficient image quality for FGI. As a direct result of the class, multiple hospital departments have implemented changes to their imaging protocols, including reduction of the default fluoroscopy pulse rate and increased use of collimation and lower dose fluoroscopy modes. Conclusion: Hands-on fluoroscopy safety training substantially benefits from real-time patient and staff dosimetry incorporated into the class. Real-time dose display helps clinical staff visualize, internalize, and ultimately utilize the safety techniques learned during the training. RaySafe/Unfors/Fluke lent us a portable version of their RaySafe i2 Dosimetry System for 6 months.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2024

Antiproton bounds on dark matter annihilation from a combined analysis using the DRAGON2 code

Abstract Early studies of the AMS-02 antiproton ratio identified a possible excess over the expected astrophysical background that could be fit by the annihilation of a weakly interacting massive particle (WIMP). However, recent efforts have shown that uncertainties in cosmic-ray propagation, the antiproton production cross-section, and correlated systematic uncertainties in the AMS-02 data, may combine to decrease or eliminate the significance of this feature. We produce an advanced analysis using the DRAGON2 code which, for the first time, simultaneously fits the antiproton ratio along with multiple secondary cosmic-ray flux measurements to constrain astrophysical and nuclear uncertainties. Compared to previous work, our analysis benefits from a combination of: (1) recently released AMS-02 antiproton data, (2) updated nuclear fragmentation cross-section fits, (3) a rigorous Bayesian parameter space scan that constrains cosmic-ray propagation parameters.We find no statistically significant preference for a dark matter signal and set strong constraints on WIMP annihilation tobb̅, ruling out annihilation at the thermal cross-section for dark matter masses below ∼ 200 GeV. We do find a positive residual that is consistent with previous work, and can be explained by a ∼ 70 GeV WIMP annihilating below the thermal cross-section. However, our default analysis finds this excess to have a local significance of only 2.8σ, which is decreased to 1.8σwhen the look-elsewhere effect is taken into account.

Astronomy & Astrophysics↗

DOE OSTI2025

Representing Soil Microbial Dynamics and Organo‐Mineral Interactions in the E3SM Land Model (ELM‐ReSOM)

Explicit representation of soil microbial processes and interactions with biotic and abiotic processes in Earth System Models (ESMs) remains limited, despite their importance in biogeochemical cycles. To address this gap, which hinders prediction of global biogeochemial cycling and responses to atmospheric conditions, we integrated a microbe- and mineral-surface-explicit model, the Reaction-network-based model of soil organic matter and Microbes (ReSOM), into the Energy Exascale ESM (E3SM) land model (ELM). Here, we describe ELM-ReSOM and show a case study at a conifer forest in California. ELM-ReSOM accurately simulated surface CO 2 fluxes and SOM stocks, demonstrating improved representations of microbial and mineral interactions compared to the default ELM. We examined ELM-ReSOM sensitivity to microbial traits, enzyme properties, and organo-mineral interactions. Microbial traits such as the maximum mortality rate, transporter-density scaling factor, and maximum monomer assimilation rate were strong controllers of heterotrophic respiration, while these microbial traits and enzyme-related properties collectively influenced SOM stocks. Mineral surfaces primarily affected SOM stocks by adsorbing enzymes, thereby limiting depolymerization. Synergies among processes led to stronger impacts of parameters when evaluated together versus separately (i.e., most parameters had greater indirect than direct effects). For example, due to interactions of microbial necromass with mineral surface adsorption, the indirect effect of the maximum microbial mortality rate was 33% larger than its direct effect on SOM stock. Thus, microbial and enzyme dynamics and their interactions with mineral surfaces play critical roles in SOM cycling. Tackling the challenges of microbe-explicit models will advance understanding and modeling of SOM dynamics.

Tao, Jing [Lawrence Berkeley National Laboratory (↗

DOE OSTI2023

Predicting displacement damage for ion irradiation: Origin of the overestimation of vacancy production in SRIM full-cascade calculations

Ion irradiation and implantation have wide applications that demand accurate determination of displacement damage profile and distribution of implanted ion concentration. The prediction of vacancies is especially important to determine displacements per atom (dpa), the standard parameter of primary radiation damage in materials. However, significant discrepancies exist in estimations of vacancies between full-cascade (F-C) and quick calculation (Q-C) options in the popular computer code SRIM. This study inspected the SRIM code and a relatively new code called Iradina, which uses a similar methodology, to develop an understanding of the origin of vacancy overestimation in the F-C options for SRIM and Iradina. Here, we found that the default values of thresholds (namely final energy in SRIM and replacement energy in Iradina) in displacement production calculations results in excessively large number of calculated vacancies and very few replacements. After conducting multiple calculations using SRIM, Iradina, and MARLOWE (all based on the binary collision approximation), a comparison of the results indicates that there is a shortcoming in the SRIM and Iradina F-C methodology for treating near-threshold collisions. This issue is responsible for the deficiency of replacements and excess of calculated vacancies in the SRIM and Iradina F-C results. Drawing on the principles of collision physics, we propose recommendations for modifying the source codes to address these issues.

36 MATERIALS SCIENCE↗

NASA NTRS2022

Use of Machine Learning to Reduce Uncertainties in Particle Number Concentration and Aerosol Indirect Radiative Forcing Predicted by Climate Models

The radiative forcing of anthropogenic aerosols associated with aerosol–cloud interactions (RF(sub aci)) remains the largest source of uncertainty in climate prediction. The calculation of particle number concentration (PNC), one of the critical parameters affecting RF(sub aci), is generally simplified in climate models. Here we employ outputs from long-term (30-years) simulations of a global size-resolved (sectional) aerosol microphysics model and a machine-learning tool to develop a Random Forest Regression Model (RFRM) for PNC. We have implemented the PNC RFRM in GISS-ModelE2.1 with a mass-based One-Moment Aerosol module, which is one of CMIP6 models. Compared to the default setting, the GISS-ModelE2.1 simulation based on RFRM reduces the changes of cloud droplet number concentration associated with anthropogenic emissions, and decreases the RF(sub aci) from −1.46 W⋅m(exp −2) to −1.11 W⋅m(exp −2). This work highlights a promising approach based on machine learning to reduce uncertainties of climate models in predicting PNC and RF(sub aci) without compromising their computing efficiency.

Radiative forcing↗

DOE OSTI2013

New constraints on the cooling of the central compact object in CAS A

To examine the previously claimed fast cooling of the Central Compact Object (CCO) in the Cas A supernova remnant (SNR), we analyzed two Chandra observations of this CCO, taken in a setup minimizing instrumental spectral distortions. We fit the two CCO X-ray spectra from 2006 and 2012 with hydrogen and carbon neutron star atmosphere models. The temperature and flux changes in the 5.5 yr between the two epochs depend on the adopted constraints on the fitting parameters and the uncertainties of the effective area calibrations. If we allow a change of the equivalent emitting region size, R {sub Em}, the effective temperature remains essentially the same. If R {sub Em} is held constant, the best-fit temperature change is negative, but its statistical significance ranges from 0.8σ to 2.5σ, depending on the model. If we assume that the optical depth of the ACIS filter contaminant in 2012 was ±10% different from its default calibration value, the significance of the temperature drop becomes 0.8σ-3.1σ, for the carbon atmospheres with constant R {sub Em}. Thus, we do not see a statistically significant temperature drop in our data, but the involved uncertainties are too large to firmly exclude the previously reported fast cooling. Our analysis indicate a decrease of 4%-6% (1.9σ-2.9σ significance) for the absorbed flux in the energy range 0.6-6 keV between 2006 and 2012, most prominent in the ≈1.4-1.8 keV energy range. It could be caused by unaccounted changes of the detector response or contributions from unresolved SNR material along the line of sight to the CCO.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2011

Development of a Roof Savings Calculator

A web-based Roof Savings Calculator (RSC) has been deployed for the Department of Energy as an industry-consensus tool to help building owners, manufacturers, distributors, contractors and researchers easily run complex roof and attic simulations. This tool employs the latest web technologies and usability design to provide an easy input interface to an annual simulation of hour-by-hour, whole-building performance using the world-class simulation tools DOE-2.1E and AtticSim. Building defaults were assigned and can provide annual energy and cost savings after the user selects nothing more than building location. In addition to cool reflective roofs, the RSC tool can simulate multiple roof types at arbitrary inclinations. There are options for above sheathing ventilation, radiant barriers and low-emittance surfaces. The tool also accommodates HVAC ducts either in the conditioned space or in the attic with custom air leakage rates. Multiple layers of thermal mass, ceiling insulation and other parameters can be compared side-by-side to generate energy/cost savings between two buildings. The RSC tool was benchmarked against field data for demonstration homes in Ft Irwin, CA.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2019

Real-Time Selective Sequencing with RUBRIC: Read Until with Basecall and Reference-Informed Criteria

Abstract The Oxford MinION, the first commercial nanopore sequencer, is also the first to implement molecule-by-molecule real-time selective sequencing or “Read Until”. As DNA transits a MinION nanopore, real-time pore current data can be accessed and analyzed to provide active feedback to that pore. Fragments of interest are sequenced by default, while DNA deemed non-informative is rejected by reversing the pore bias to eject the strand, providing a novel means of background depletion and/or target enrichment. In contrast to the previously published pattern-matching Read Until approach, our RUBRIC method is the first example of real-time selective sequencing where on-line basecalling enables alignment against conventional nucleic acid references to provide the basis for sequence/reject decisions. We evaluate RUBRIC performance across a range of optimizable parameters, apply it to mixed human/bacteria and CRISPR/Cas9-cut samples, and present a generalized model for estimating real-time selection performance as a function of sample composition and computing configuration.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Power Converter Circuit Design Automation using Parallel Monte Carlo Tree Search

The tidal waves of modern electronic/electrical devices have led to increasing demands for ubiquitous application-specific power converters. A conventional manual design procedure of such power converters is computation- and labor-intensive, which involves selecting and connecting component devices, tuning component-wise parameters and control schemes, and iteratively evaluating and optimizing the design. To automate and speed up this design process, we propose an automatic framework that designs custom power converters from design specifications using Monte Carlo Tree Search. Specifically, the framework embraces the upper-confidence-bound-tree (UCT), a variant of Monte Carlo Tree Search, to automate topology space exploration with circuit design specification-encoded reward signals. Moreover, our UCT-based approach can exploit small offline data via the specially designed default policy and can run in parallel to accelerate topology space exploration. Further, it utilizes a hybrid circuit evaluation strategy to substantially reduce design evaluation costs. Empirically, we demonstrated that our framework could generate energy-efficient circuit topologies for various target voltage conversion ratios. Compared to existing automatic topology optimization strategies, the proposed method is much more computationally efficient --- the sequential version can generate topologies with the same quality while being up to 67% faster. Here, the parallelization schemes can further achieve high speedups compared to the sequential version.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2011

Development of a Roof Savings Calculator

A web-based Roof Savings Calculator (RSC) has been deployed for the Department of Energy as an industry-consensus tool to help building owners, manufacturers, distributors, contractors and researchers easily run complex roof and attic simulations. This tool employs the latest web technologies and usability design to provide an easy input interface to an annual simulation of hour-by-hour, whole-building performance using the world-class simulation tools DOE-2.1E and AtticSim. Building defaults were assigned and can provide estimated annual energy and cost savings after the user selects nothing more than building location. In addition to cool reflective roofs, the RSC tool can simulate multiple roof types at arbitrary inclinations. There are options for above sheathing ventilation, radiant barriers, and low-emittance surfaces. The tool also accommodates HVAC ducts either in the conditioned space or in the attic with custom air leakage rates. Multiple layers of building materials, ceiling and deck insulation, and other parameters can be compared side-by-side to generate an energy/cost savings estimate between two buildings. The RSC tool was benchmarked against field data for demonstration homes in Ft. Irwin, CA.

DOE cool roof calculator↗

DOE OSTI2019

SubKit

Generating a CTF (thermal-hydraulics subchannel code) model can be time consuming and error prone because of the rigid formatting of the input file and the amount of input requirements. Because of the structured input format, making small changes to a model can require large scale changes to the input file. Furthermore, a user typically has to perform calculations to develop CTF input parameters from actual model geometry. Changing model geometry requires re-calculating input parameters and copying them from wherever the calculation was performed, be it a script, spreadsheet, or piece of paper. This process complicates the quality assurance process for that model and makes changing the model more difficult. CtfDeckBuilder is an object-oriented Python interface to CTF that allows the user to build a CTF model in Python. The user no longer needs to interface with the CTF input file when using the CtfDeckBuilder. The interface reduces the information required of the user by offering defaults for most modeling options provided by CTF. The user can perform calculations directly in Python when building the model so that calculations stay with the model itself.

Salko, Jr., RobertK↗

DOE OSTI2020

An ERCOT test system for market design studies

An open source test system is developed that permits the dynamic modeling of centrally-managed wholesale power markets operating over highvoltage transmission grids. In default mode, the test system models basic operations in the Electric Reliability Council of Texas (ERCOT): namely, centrally-managed day-ahead and real-time markets operating over successive days, with congestion handled by locational marginal pricing. These basic operational features characterize all seven U.S. energy regions organized as centrally-managed wholesale power markets. Modeled participants include dispatchable generators, load-serving entities, and non-dispatchable generation such as unrmed wind and solar power. Users can congure a broad variety of parameters to study basic market and grid features under alternative system conditions. Users can also easily extend the test system's Java/Python software classes to study modied or newly envisioned market and grid features. Finally, the test system is integrated with a high-level simulation framework that permits it to function as a software component within larger systems, such as multi-country systems or integrated transmission and distribution systems. Finally, detailed test cases with 8-bus and 200-bus transmission grids are reported to illustrate these test system capabilities.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2015

Comparison of MODTRAN5 atmospheric extinction predictions with narrowband astronomical flux observations

Improving the precision of ground-based astronomical observations is an objective of both current (e.g. PanSTARRS1) and future (e.g. Dark Energy Survey and the Large Synoptic Survey Telescope) sky surveys. An important element of this effort is to determine the optical attenuation imposed by the atmosphere. We have obtained atmospheric extinction observations from narrowband photometry (typically 10 nm bandwidth) at central wavelengths of 380 nm, 488 nm, 500 nm, 585 nm, 656 nm, 675 nm and 840 nm. The passbands were selected to measure the continuum component (predominantly from Rayleigh and aerosol scattering) of atmospheric attenuation, and to avoid molecular absorption features in the atmosphere. We compare these atmospheric extinction observations with predictions from MODTRAN5, a commonly used computer model of atmospheric optical transmission. Here, the MODTRAN5 calculations were informed by a satellite-based determination of atmospheric ozone on the night of observations. We also adjusted the MODTRAN5 predictions of Rayleigh scattering to account for the difference between the default pressure and that measured at the observatory on the night of observations. We find excellent agreement across all passbands between the pressureadjusted MODTRAN5 extinction model and the observations, within our typical extinction uncertainty of 0.013 mag/airmass, but only if we exclude any aerosol scattering component in the MODTRAN5 model. Even though this is a very limited test, with observations of a single star for a single night, the fact that we obtain excellent agreement between extinction measurements and the MODTRAN5 model, with no adjustable fit parameters, bodes well for exploiting MODTRAN5 to increase the precision of ground-based flux measurements.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2012

Parameterized Micro-benchmarking: An Auto-tuning Approach for Complex Applications

Auto-tuning has emerged as an important practical method for creating highly optimized implementations of key computational kernels and applications. However, the growing complexity of architectures and applications is creating new challenges for auto-tuning. Complex applications can involve a prohibitively large search space that precludes empirical auto-tuning. Similarly, architectures are becoming increasingly complicated, making it hard to model performance. In this paper, we focus on the challenge to auto-tuning presented by applications with a large number of kernels and kernel instantiations. While these kernels may share a somewhat similar pattern, they differ considerably in problem sizes and the exact computation performed. We propose and evaluate a new approach to auto-tuning which we refer to as parameterized micro-benchmarking. It is an alternative to the two existing classes of approaches to auto-tuning: analytical model-based and empirical search-based. Particularly, we argue that the former may not be able to capture all the architectural features that impact performance, whereas the latter might be too expensive for an application that has several different kernels. In our approach, different expressions in the application, different possible implementations of each expression, and the key architectural features, are used to derive a simple micro-benchmark and a small parameter space. This allows us to learn the most significant features of the architecture that can impact the choice of implementation for each kernel. We have evaluated our approach in the context of GPU implementations of tensor contraction expressions encountered in excited state calculations in quantum chemistry. We have focused on two aspects of GPUs that affect tensor contraction execution: memory access patterns and kernel consolidation. Using our parameterized micro-benchmarking approach, we obtain a speedup of up to 2 over the version that used default optimizations, but no auto-tuning. We demonstrate that observations made from microbenchmarks match the behavior seen from real expressions. In the process, we make important observations about the memory hierarchy of two of the most recent NVIDIA GPUs, which can be used in other optimization frameworks as well.

auto-tuning↗