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All sources NASA NTRS DOE OSTI

DOE OSTI2016

Search for massive WH resonances decaying into the $\ell \nu \mathrm{b} \overline{\mathrm{b}} $ final state at $\sqrt{s}=8$ $~\text {TeV}$

A search for a massive resonance ${\mathrm{W}^{\prime }}$ decaying into a W and a Higgs boson in the $\ell \nu \mathrm{b} \overline{\mathrm{b}} $ ( $\ell = \mathrm {e}$ , $\mu $ ) final state is presented. Results are based on data corresponding to an integrated luminosity of 19.7 $\,\text {fb}^{{-1}}$ of proton–proton collisions at $\sqrt{s}=8$ $~\text {TeV}$ , collected using the CMS detector at the LHC. For a high-mass ( $\gtrsim $ 1 $~\text {TeV}$ ) resonance, the two bottom quarks coming from the Higgs boson decay are reconstructed as a single jet, which can be tagged by placing requirements on its substructure and flavour. Exclusion limits at 95 % confidence level are set on the production cross section of a narrow resonance decaying into WH, as a function of its mass. In the context of a little Higgs model, a lower limit on the ${\mathrm{W}^{\prime }}$ mass of 1.4 $~\text {TeV}$ is set. In a heavy vector triplet model that mimics the properties of composite Higgs models, a lower limit on the ${\mathrm{W}^{\prime }}$ mass of 1.5 $~\text {TeV}$ is set. In the context of this model, the results are combined with related searches to obtain a lower limit on the ${\mathrm{W}^{\prime }}$ mass of 1.8 $~\text {TeV}$ , the most restrictive to date for decays to a pair of standard model bosons.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2022

Adaptive Urban Traffic Signal Control for Multiple Intersections: An LQR Approach

Traffic congestion leads to severe problems especially in urban traffic networks. It increases the chance of accidents, energy waste, and social costs. In order to address these problems, an adaptive linear quadratic regulator (LQR) approach is developed for traffic signal control at multiple intersections in an urban area. The proposed method controls the green time of the traffic signals to reduce traffic congestion and smooth traffic flow. Real-world data from vision-based traffic sensors are used to build the traffic network model, which mimics the real-world traffic behavior. In addition, the proposed control utilizes recursive least square parameter estimation, which is capable of tracking dynamic changes in traffic conditions. Simulation of Urban MObility (SUMO) is used to analyze the efficacy of the proposed method. Results of the simulation show that the proposed method outperforms pretimed control in various aspects.

adaptive LQR control↗

DOE OSTI2016

Enzymatic degradation of in vitro Staphylococcus aureus biofilms supplemented with human plasma

Enzymatic debridement is a therapeutic strategy used clinically to remove necrotic tissue from wounds. Some of the enzymes utilized for debridement have been tested against bacterial pathogens, but the effectiveness of these agents in dispersing clinically relevant biofilms has not been fully characterized. Here, we developed an in vitro Staphylococcus aureus biofilm model that mimics wound-like conditions and employed this model to investigate the antibiofilm activity of four enzymatic compounds. Human plasma at concentrations of 0%–50% was supplemented into growth media and used to evaluate biofilm biomass accumulation over 24 hours and 48 hours in one methicillin-sensitive and five methicillin-resistant strains of S. aureus. Supplementation of media with 10% human plasma resulted in the most robust biofilms in all six strains. The enzymes α-amylase, bromelain, lysostaphin, and papain were then tested against S. aureus biofilms cultured in 10% human plasma. Quantification of biofilms after 2 hours and 24 hours of treatment using the crystal violet assay revealed that lysostaphin decreased biomass by up to 76%, whereas α-amylase, bromelain, and papain reduced biomass by up to 97%, 98%, and 98%, respectively. Scanning electron microscopy confirmed that the dispersal agents detached the biofilm exopolysaccharide matrix and bacteria from the growth surface. Lysostaphin caused less visible dispersal of the biofilms, but unlike the other enzymes, induced morphological changes indicative of bacterial cell damage. Overall, our results indicate that use of enzymes may be an effective means of eradicating biofilms and a promising strategy to improve treatment of multidrug-resistant bacterial infections.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2024

Assessing equation of state-independent relations for neutron stars with nonparametric models

Relations between neutron star properties that do not depend on the nuclear equation of state offer insights on neutron star physics and have practical applications in data analysis. Such relations are obtained by fitting to a range of phenomenological or nuclear physics equation of state models, each of which may have varying degrees of accuracy. In this study we revisit commonly used relations and reassess them with a very flexible set of phenomenological nonparametric equation of state models that are based on Gaussian processes. Our models correspond to two sets: equations of state which mimic hadronic models, and equations of state with rapidly changing behavior that resemble phase transitions. Here we quantify the accuracy of relations under both sets and discuss their applicability with respect to expected upcoming statistical uncertainties of astrophysical observations. We further propose a goodness-of-fit metric which provides an estimate for the systematic error introduced by using the relation to model a certain equation-of-state set. Overall, the nonparametric distribution is more poorly fit with existing relations, with the I–Love–Q relations retaining the highest degree of universality. Fits degrade for relations involving the tidal deformability, such as the binary-Love and compactness-Love relations, and when introducing phase transition phenomenology. For most relations, systematic errors are comparable to current statistical uncertainties under the nonparametric equation of state distributions.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS2019

A Fast Vector Radiative Transfer Model for the Atmosphere-Ocean Coupled System

To infer atmospheric and oceanic constituent properties from polarimetric observations, an efficient and accurate retrieval algorithm is desirable. In-line radiative transfer calculations are indispensable if a large state vector, including both atmospheric profiles and surface properties, is used to improve retrieval accuracy. However, in-line radiative transfer calculations are usually not computationally efficient for remote sensing applications. Therefore, there is a pressing need to develop an accurate and fast vector radiative transfer model (RTM) to fully utilize satellite polarimetric observations. This paper reports on a fast vector RTM, referred to as TAMU-VRTM, in support of polarimetric remote sensing, which is capable of simulating the Stokes vector values observed at the top of the atmosphere and at the surface by fully considering absorption, scattering, and emission in the atmosphere and ocean. Gaseous absorption is parameterized with respect to gas concentration, temperature, and pressure, by using a regression method applicable to an inhomogeneous atmospheric path. An efficient two-component approach combining the small angle approximation and the adding-doubling method is utilized to solve the vector radiative transfer equation (RTE). The thermal emission component of the RTE solution is obtained by an efficient doubling process. The air-sea interface is treated as a wind-ruffled rough surface in the model to mimic a realistic ocean surface. Several oceanic optical property models are introduced to model ocean inherent optical properties. To demonstrate the applicability of the TAMUVRTM, simulations are compared with satellite observations, and results from other vector radiative transfer methods including benchmarks.

radiative transfer in coupled atmosphere-ocean sys↗

DOE OSTI2015

Toward a new parameterization of hydraulic conductivity in climate models: Simulation of rapid groundwater fluctuations in N orthern C alifornia

Abstract Preferential flow through weathered bedrock leads to rapid rise of the water table after the first rainstorms and significant water storage (also known as “rock moisture”) in the fractures. We present a new parameterization of hydraulic conductivity that captures the preferential flow and is easy to implement in global climate models. To mimic the naturally varying heterogeneity with depth in the subsurface, the model represents the hydraulic conductivity as a product of the effective saturation and a background hydraulic conductivity K bkg , drawn from a lognormal distribution. The mean of the background K bkg decreases monotonically with depth, while its variance reduces with the effective saturation. Model parameters are derived by assimilating into Richards’ equation 6 years of 30 min observations of precipitation (mm) and water table depths (m), from seven wells along a steep hillslope in the Eel River watershed in Northern California. The results show that the observed rapid penetration of precipitation and the fast rise of the water table from the well locations, after the first winter rains, are well captured with the new stochastic approach in contrast to the standard van Genuchten model of hydraulic conductivity, which requires significantly higher levels of saturated soils to produce the same results. “Rock moisture,” the moisture between the soil mantle and the water table, comprises 30% of the moisture because of the great depth of the weathered bedrock layer and could be a potential source of moisture to sustain trees through extended dry periods. Furthermore, storage of moisture in the soil mantle is smaller, implying less surface runoff and less evaporation, with the proposed new model.

58 GEOSCIENCES↗

NASA NTRS1999

Multistage Turbomachinery Flows Simulated Numerically

At the NASA Lewis Research Center, a comprehensive assessment was made of the predictive capability of the average passage flow model as applied to multistage axial-flow compressors. This model, which describes the time-averaged flow field within a typical passage of a blade row embedded in a multistage configuration, is being widely used throughout U.S. aircraft industry as an integral part of their design systems. Rotor flow-angle deviation. In this work, detailed data taken within a four and one-half stage large low-speed compressor were used to assess the weaknesses and strengths of the predictive capabilities of the average passage flow model. The low-speed compressor blading is of modern design and employs stator end-bends. Measurements were made with slow- and high response instrumentation. The high-response measurements revealed the velocity components of both the rotor and stator wakes. From the measured wake profiles, we found that the flow exiting the rotors deviated from the rotor exit metal angle to a lesser degree than was predicted by the average passage flow model. This was found to be due to blade boundary layer transition, which recently has been shown to exist on multistage axial compressor rotor and stator blades, but was not accounted for in the average passage model. Consequently, a model that mimics the effects of blade boundary layer transition, Shih k-epsilon model, was incorporated into the average passage model. Simulations that incorporated this transition model showed a dramatic improvement in agreement with data. The altered model thus improved predictive capability for multistage axial-flow compressors, and this was verified by detailed experimental measurement.

Hathaway, Michael D.↗

NASA NTRS2017

Multi-Layer RF Tissue Phantoms for Mimicking a Human Core

This work presents the design recipe, fabrication process and characterization of tissue-simulating materials, configured as a physical model to mimic the electrical and some physical properties of an abdominal cavity. The complete three layer design is called the human core model (HCM). To our knowledge, presented is the first hybrid skin-muscle phantom developed to mimic the electrical properties of the intervening tissue layers of an abdominal cavity within the frequency band of 1 GHz 2 GHz, a band of interest for human body sensing due to its deep detection depth. To complete the model, a liquid blood phantom was also developed and characterized in this frequency band. The phantoms were characterized with respect to complex dielectric constant using the Agilent 85070E dielectric probe kit, and the results compared to the Gabriel model, which is used as the standard for human tissue characterization. Since the tissue impedance is an important parameter for characterizing on-body sensors and near field antenna performance, the impedance of the phantoms were also calculated and presented in the analysis.

Bonds, Quenton↗

DOE OSTI2020

Multi-Scale Simulation of Wind Farm Performance during a Frontal Passage

Predicting the response of wind farms to changing flow conditions is necessary for optimal design and operation. Here in this work, simulation and analysis of a frontal passage through a utility scale wind farm is achieved for the first time using a seamless multi-scale modeling approach. A generalized actuator disk (GAD) wind turbine model is used to represent turbine–flow interaction, and results are compared to novel radar observations during the frontal passage. The Weather Research and Forecasting (WRF) model is employed with a nested grid setup that allows for coupling between multi-scale atmospheric conditions and turbine response. Starting with mesoscale forcing, the atmosphere is dynamically downscaled to the region of interest, where the interaction between turbulent flows and individual wind turbines is simulated with 10 m grid spacing. Several improvements are made to the GAD model to mimic realistic turbine operation, including a yawing capability and a power output calculation. Ultimately, the model is able to capture both the dynamics of the frontal passage and the turbine response; predictions show good agreement with observed background velocity, turbine wake structure, and power output after accounting for a phase shift in the mesoscale forcing. This study demonstrates the utility of the WRF-GAD model framework for simulating wind farm performance under complex atmospheric conditions.

17 WIND ENERGY↗

DOE OSTI2019

Multi-scale simulations of wind farm performance with complex terrain and weather events

Predicting the response of wind farms to local weather is necessary for optimal design and operation. In this work, simulation and analysis of a frontal passage through a utility scale wind farm is achieved for the first time using a seamless multi-scale modeling approach. A generalized actuator disk (GAD) wind turbine model is used to represent turbine wakes, and results are compared to novel radar observations during the frontal passage. The Weather Research and Forecasting (WRF) model is employed with a nested grid setup that allows for coupling between multi-scale atmospheric conditions and turbine response. Starting with mesoscale forcing, the atmosphere is dynamically downscaled to the region of interest, where the interaction between turbulent flows and individual wind turbines is simulated with the GAD at10 m resolution. Several improvements are made to the GAD model to mimic realistic turbine operation, including a yawing capability and a power output calculation. Ultimately, the model is able to capture both the dynamics of the frontal passage and the turbine response; predictions show good agreement with observed turbine wake structure, velocity deficit, and power output after accounting for a phase shift in the mesoscale forcing. This study demonstrates the utility of the WRF-GAD framework for simulating wind farm performance under complex atmospheric conditions.

17 WIND ENERGY↗

NASA NTRS2017

Multi-Layer RF Tissue Phantoms for Mimicking a Human Core

Biomedical Microwave Sensing↗

DOE OSTI2021

Leveraging observed soil heterotrophic respiration fluxes as a novel constraint on global-scale models

Microbially-explicit models may improve understanding and projections of carbon dynamics in response to future climate change, but their fidelity in simulating global-scale soil heterotrophic respiration (RH), a stringent test for soil biogeochemical models, has never been evaluated. We used statistical global RH products, as well as 7,821 daily site-scale RH measurements, to evaluate the spatio-temporal performance of one first-order decay model (CASA-CNP) and two microbially-explicit biogeochemical models (CORPSE and MIMICS) that were forced by two different climate datasets. CORPSE and MIMICS did not provide any measurable performance improvement; instead, the models were highly sensitive to the meteorological input data used to drive them. Spatial RH variability was generally well simulated except in the northern middle latitudes (~50°N) and arid regions; models captured the seasonal variability of RH well, but showed more divergence in tropic and arctic regions. Our results demonstrate that the next generation of biogeochemical models shows promise, but also needs to be improved for realistic spatio-temporal variability of RH. Finally, we emphasize the importance of net primary production, soil moisture, and soil temperature inputs, and that jointly evaluating soil models for their spatial (global scale) and temporal (site scale) performance provides crucial benchmarks for improving biogeochemical models.

Jian, Jinshi↗

DOE OSTI2019

Geomechanical modeling of distributed fiber-optic sensor measurements

Fiber-optic-based distributed acoustic sensors (DAS) are a new technology that can be deployed in a well and are continuously interrogated during operations. These sensors calculate the strain (or strain rate) at all points along the fiber and have been used extensively to monitor hydraulic stimulations. The data from these sensors indicate that they are sensitive to high-frequency signals associated with microseismicity and low-frequency signals associated with fracture growth. We have developed a set of idealized models to simulate these signals and to identify interpretation methods that may be used to estimate fracture location, geometry, and extent. We use a multiphysics code that includes rock physics, fluid flow, and elastic-wave propagation to generate synthetic DAS measurements from a set of simple models that mimic hydraulic fracturing. We then relate the signals observed in the synthetic DAS to specific features in the model such as fracture height, width, and aperture. Our results demonstrate that the synthetic DAS measurements may be used to determine field DAS measurements and to optimize the design of future sensor deployments for sensitivity to fracture attributes.

03 NATURAL GAS↗

DOE OSTI2026

Structure–Property Relationships of Recycled Lithium-Ion Battery Cathodes: Microstructure Optimization Using Virtual Materials Testing

The increasing demand for sustainable battery technologies requires effective recycling strategies for end-of-life lithium-ion battery cathodes. In this study, virtual materials testing, a well-established framework for modeling conventionally manufactured NMC-based cathodes, is applied to partially recycled cathodes. To this end, virtual cathodes consisting of mixtures of pristine and recycled NMC particles are utilized to systematically analyze structure–property relationships depending on mixing ratios and different spatial arrangement strategies. For this purpose, a stochastic 3D model is developed that is capable of generating virtual cathodes with arbitrary volume fractions of active materials and mixing ratios of pristine and recycled NMC particles. Particularly, the stochastic 3D model can mimic the different size distributions of pristine and recycled particles that are observed in image data. Additionally, the model allows the structuring of pristine and recycled NMC either uniformly mixed or layer-wise arranged, mimicking single- and dual-layer cathodes. Subsequently, a systematic computational analysis is conducted to assess the influence of increasing active material ratios of recycled particles, ranging from 0 % to 100 %, while maintaining a constant overall active material volume fraction. The impact of particle mixing on cathode performance is evaluated by examining transport-relevant geometrical descriptors and effective properties, such as geodesic tortuosity, specific surface area, and tortuosity factor.

25 ENERGY STORAGE↗

DOE OSTI2024

PHASM: A Toolkit for Creating AI Surrogate Models within Legacy Codebases

PHASM (“Parallel Hardware viA Surrogate Models”) is a software toolkit for creating AI-based surrogate models of scientific code. AI-based surrogate models are widely used for creating fast and inverse simulations. PHASM anticipates an additional future use case: adapting legacy code to modern hardware. While data centers are investing in heterogeneous hardware such as GPUs and FPGAs, many established scientific codebases remain unable to take advantage of the hardware’s higher parallelism without undergoing a costly rewrite. An alternative is to train a AI-based surrogate model to mimic computationally intensive functions in the code, and run the surrogate instead. PHASM formalizes a development lifecycle for such surrogate models, including discovering functions amenable to replacement with a surrogate model, predicting the resulting performance, identifying the function’s space of inputs and outputs, binding the model to the code, and managing model versions. A suite of software tools for facilitating these steps was written and validated against a set of model problems.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

A reduced-order model of concentration polarization in reverse osmosis systems with feed spacers

Feed spacers in reverse osmosis systems generate complex fluid flows that limit computational fluid dynamics (CFD) simulations to small length and time scales. That limits our ability to simulate mineral scaling and other membrane fouling phenomena, which occur over longer length and time scales. Thus motivated, we develop a reduced model that replaces the CFD simulation of the velocity field with an analytical model that mimics spacers. This focuses the remaining numerical effort on simulating the advection–diffusion equation governing solute transport. We motivate and validate the model with CFD simulations and bench-scale experiments of spacer filaments in three different arrangements, including cases of unsteady vortex shedding. We show that the model produces a roughly 10,000-fold speedup compared to CFD, and accurately reproduces CFD predictions of not only the average and maximum concentrations, but also the local concentration distribution along the membrane. Here, we also demonstrate the model for simulating a feed channel with a length-to-height ratio of 200. The model provides a simple testbed for exploratory studies of multispecies transport, precipitation, and membrane fouling phenomena for which simulating spacers is often prohibitive.

Computational fluid dynamics↗

DOE OSTI2020

Benchmarking and Improving Microbial-explicit Soil Biogeochemistry Models

Soils represent the largest terrestrial carbon pool on Earth. Yet emerging theories regarding stabilization of soil organic matter remain poorly represented in global-scale models; thus, underestimating the true uncertainty associated with potential terrestrial carbon cycle – climate feedbacks. With this project we created a testbed to compare and evaluate soil biogeochemical models (W. Wieder at the Univ. of CO, Boulder), data synthesis (R. Phillips, Indiana Univ.) and parameter estimation (S Allison, Univ. CA Irvine) to quantify uncertainty associated with potential soil C changes. This project resulted in 14 Presentations, 14 Publications and helped support the training of three graduate students. A significant accomplishment with this work was the creation of a soil biogeochemical testbed, which forces three soil carbon models (CASA, MIMICS, and CORPSE) with common environmental drivers.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Transition Core Modeling for Extended Enrichment & Accident-Tolerant Fuels Using Polaris/PARCS

Commercial light water reactor (LWR) operators and fuel vendors are currently interested in increasing the low-enriched uranium (LEU) fuel enrichments from the current limit of 5.0 $^w/_o$ $^{235}U$ up to 10 $^ w/_o$ $^{235}U$ (referred to as "LEU+") in their current fleets; they are also interested in using accident-tolerant fuel (ATF) with both LEU and LEU+ fuel. This report aims to identify modeling challenges and accuracy concerns in transition core analysis using the SCALE Polaris lattice physics code and U.S. Nuclear Regulatory Commission core simulator PARCS. At the time this study was started, no publicly available LEU+ core designs existed for boiling water reactor (BWR) or pressurized water reactor (PWR) systems. Therefore, fuel lattices were shuffled within a multi-assembly model to mimic neutronically challenging lattice combinations seen in transition cores, such as a fresh LEU+ lattice next to depleted LEU lattices. In addition to multi-assembly models, whole-core BWR transition core calculations were performed for ATF and LEU+ fuel using an existing Hatch-1 Cycle 3 core model. A whole-core BWR model was chosen due to the more heterogeneous core designs compared to those for a PWR core. Since the original core is an old checkerboard core design and no core or fuel design optimization was performed for the modeled fuel types, these core calculations were intended only to provide: (1) Comparisons of core characteristics of interest, such as the pin power distributions and peaking factors, Doppler temperature coefficients (DTCs), and control blade worths (CBWs) under challenging core designs, (2) Identification of reactor physics challenges in modeling LEU+ and ATF cores, and (3) A stress test for the Polaris/PARCS two-step modeling approach, including characterization of the relative accuracy for predicting characteristics of interest such as pin power distributions.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗