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At least 1,531 records · Page 85

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DOE OSTI2016

New type of hill-top inflation

We suggest a new type of hill-top inflation originating from the initial conditions in the form of the microcanonical density matrix for the cosmological model with a large number of quantum fields conformally coupled to gravity. Initial conditions for inflation are set up by cosmological instantons describing underbarrier oscillations in the vicinity of the inflaton potential maximum. These periodic oscillations of the inflaton field and cosmological scale factor are obtained within the approximation of two coupled oscillators subject to the slow roll regime in the Euclidean time. This regime is characterized by rapid oscillations of the scale factor on the background of a slowly varying inflaton, which guarantees smallness of slow roll parameters ϵ and η of the following inflation stage. A hill-like shape of the inflaton potential is shown to be generated by logarithmic loop corrections to the tree-level asymptotically shift-invariant potential in the non-minimal Higgs inflation model and R{sup 2}-gravity. The solution to the problem of hierarchy between the Planckian scale and the inflation scale is discussed within the concept of conformal higher spin fields, which also suggests the mechanism bringing the model below the gravitational cutoff and, thus, protecting it from large graviton loop corrections.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2021

SWAT model application for evaluating agricultural conservation practice effectiveness in reducing phosphorous loss from the Western Lake Erie Basin

Lake Erie is threatened by eutrophication and harmful algal blooms due to excess nutrient loading from agricultural sources. Agricultural conservation practices (ACPs) have been developed and implemented to reduce nutrient losses but estimating ACP effectiveness is challenging. The Soil and Water Assessment Tool (SWAT) has been used to investigate ACP effectiveness for water quality improvement. Many SWAT applications have been developed by different investigators to evaluate ACP effectiveness for reducing nutrient, particularly phosphorus (P), loading in the agriculturally-dominated Western Lake Erie Basin (WLEB). Our objective is to establish what has been achieved by past modeling research and make suggestions for future applications and improvements. We synthesized the findings of 28 SWAT modeling studies within the WLEB. Models generally performed satisfactorily against accepted criteria for streamflow and sediment, but performance for P loads, like soluble reactive P, was mostly “unsatisfactory”. The “unsatisfactory” performance maybe due to imperfections and idealizations in model formulations and/or parameterization. Thus, simulations of P transport and transformation processes need improvement. In addition, model parameter selection is the key part of model set-up. Most SWAT modeling studies used default values during initial set-up, then performed calibration and validation. It was found that the calibrated P related parameter values varied widely across different studies, even within the same watershed with some values unrealistic for the study areas. The phenomena of different combinations of model parameters producing similar outputs indicates equifinality. Equifinality in the baseline model may impact results when ACPs are incorporated. Furthermore, the unrealistic values used in ACP assessment undermine the credibility of ACP effectiveness. Future model applications should try to re-examine the calibrated P parameters and make sure they are realistic for the study area as well as reduce equifinality by constraining the model with characterization of watershed conditions, better understanding of hydrologic processes, and parameter values based on real-world observations. As a result, future model applications should focus on improving P transport and transformation processes, using measured watershed characteristics for parameterization, and improving reflections of climate change, which could result in more accurate assessments of ACP effectiveness to meet targeted goals.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Nuclear Energy Cost Estimates for Net Zero World Initiative

This report provides recommended parameters for incorporating nuclear energy systems into decarbonization modeling scenarios. The values are primarily intended for the Net Zero World (NZW) Initiative but are expected to prove useful to other related efforts. Both costs and operational metrics are provided in the study. Several cost factors, namely overnight capital costs (OCC) and operational costs are taken to be country specific. OCC is defined as the value of building the reactor in one night considering all costs prior to the start of operations including fuel for the initial core load. The value assumes the build is neither a first nor a ‘Nth’ of a kind, but somewhere in between. All costs are escalated to 2022 USD values.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2024

Enhancing Photosynthesis Simulation Performance in ESMs with Machine Learning-Assisted Solvers

When simulating vegetation dynamics, photosynthesis accounts for a large fraction of the computational cost in most Earth System Models (ESMs). This is largely since photosynthesis is represented as a system of nonlinear equations, and the solution requires the use of an initial guess followed by many iterations of the numerical solver to obtain a solution. We use machine learning (ML) to replicate the response surface of the model’s numerical solver to improve the choice of initial guess, therefore requiring fewer iterations to obtain a final solution. We implemented this test on the leaf-level calculations as well as at the canopy scale, and for both we observed fewer iterations of the photosynthesis solver when a ML-based initial guess was implemented. The model tested here is the Energy Exascale Earth System Model - Land Model (ELM). The ML-based algorithms used here are trained on simulations from the model itself and used only to improve the initial guess for the solver; therefore, the model maintains its own set of physics to obtain the final solution. This work shows novel ways to utilize ML-based methods to improve the performance of numerical solvers in ESMs.

Massoud, Elias [ORNL] (ORCID:0000000217725361)↗

DOE OSTI2024

H2@Scale CRADA: CA Research Consort. (Ref. Station, Fueling Perf. Test Device, Station Cap Model)

In support of DOE's H2@Scale initiative, this project leverages with national lab capabilities at SNL, NREL, and ANL with collaboration and funding cost share from California agencies (CEC, South Coast AQMD, and GO-Biz) to enable the build-out of heavy-duty (HD) hydrogen fueling stations with large dispensing capacity and high flow rates by providing tools and information that lead to more efficient design, acceptance, and commissioning. In this presentation, we describe the progress as related to the subtasks of: HD Reference Station Design, HD Station Test Device Design, and the Station Capacity Model.

AMR↗

DOE OSTI2025

Radiative, Hydrologic, and Circulation Responses to Warming in Cess‐Potter Simulations Using the Global 3.25‐km SCREAM

Using the global 3.25-km Simple Cloud Resolving E3SM Atmosphere Model (SCREAM 3 km), a pair of 13-month Cess-Potter simulations are performed to quantify the radiative feedbacks and the hydrologic and circulation responses to warming. Large-scale aspects of SCREAM 3 km's top-of-atmosphere radiative fluxes, precipitation rates, and circulations are in good agreement with observations and reanalysis, with notable differences, including a drier lower free-troposphere in the Tropics, reduced precipitation and humidity over the Tropical West Pacific, and poleward shifted Southern Hemisphere midlatitude jet. In response to warming, SCREAM 3 km predicts a total radiative feedback within the top 15% of the CMIP5 and CMIP6 models, which puts it substantially higher than the feedback reported by other kilometer-scale models. SCREAM 3 km's high radiative feedback stems from a strongly positive shortwave cloud feedback, most prominent over the mid- and high-latitudes. SCREAM 3 km's high precipitation response also puts it among the highest of CMIP models, whereas its circulation response is within the spread of CMIP models. An ensemble of five perturbed initial condition Cess-Potter simulations with a 12 km version of SCREAM (SCREAM 12 km) is performed to characterize uncertainty and resolution sensitivity. It suggests that the uncertainty from analyzing a pair of 1-year simulations is small compared to the inter-model spread in feedbacks and precipitation response. SCREAM 12 km also produces a strong precipitation response to warming but a much lower cloud feedback and total radiative feedback. The results from these experiments suggest that the spread in climate feedbacks will likely persist in the next generation of kilometer-scale models.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

SRF Cavity Instability Detection with Machine Learning at CEBAF

During the operation of CEBAF, one or more unstable superconducting radio-frequency (SRF) cavities often cause beam loss trips while the unstable cavities themselves do not necessarily trip off. Identifying an unstable cavity out of the hundreds of cavities installed at CEBAF is difficult and time-consuming. The present RF controls for the legacy cavities report at only 1 Hz, which is too slow to detect fast transient instabilities. A fast data acquisition system for the legacy SRF cavities is being developed which samples and reports at 5 kHz to allow for detection of transients. A prototype chassis has been installed and tested in CEBAF. An autoencoder based machine learning model is being developed to identify anomalous SRF cavity behavior. The model is presently being trained on the slow (1 Hz) data that is currently available, and a separate model will be developed and trained using the fast (5 kHz) DAQ data once it becomes available. This paper will discuss the present status of the new fast data acquisition system and results of testing the prototype chassis. This paper will also detail the initial performance metrics of the autoencoder model.

Carpenter, A.↗

DOE OSTI2022

SRF Cavity Instability Detection with Machine Learning at CEBAF

Carpenter, A.↗

DOE OSTI2024

Integrating chromosome conformation and DNA repair in a computational framework to assess cell radiosensitivity

Objective. The arrangement of chromosomes in the cell nucleus has implications for cell radiosensitivity. The development of new tools to utilize Hi-C chromosome conformation data in nanoscale radiation track structure simulations allows for in silico investigation of this phenomenon. We have developed a framework employing Hi-C-based cell nucleus models in Monte Carlo radiation simulations, in conjunction with mechanistic models of DNA repair, to predict not only the initial radiation-induced DNA damage, but also the repair outcomes resulting from this damage, allowing us to investigate the role chromosome conformation plays in the biological outcome of radiation exposure. Approach. In this study, we used this framework to generate cell nucleus models based on Hi-C data from fibroblast and lymphoblastoid cells and explore the effects of cell type-specific chromosome structure on radiation response. The models were used to simulate external beam irradiation including DNA damage and subsequent DNA repair. The kinetics of the simulated DNA repair were compared with previous results. Main results. We found that the fibroblast models resulted in a higher rate of inter-chromosome misrepair than the lymphoblastoid model, despite having similar amounts of initial DNA damage and total misrepairs for each irradiation scenario. Significance. This framework represents a step forward in radiobiological modeling and simulation allowing for more realistic investigation of radiosensitivity in different types of cells.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2018

A numerical study of bubble and spike velocities in shock-driven liquid metals

In this study, we use detailed continuum hydrodynamics and molecular dynamics simulations to investigate the dynamics of ejecta that are initialized with large amplitude perturbations and non-sinusoidal shapes. Insights from the simulations are used to suggest a modified expression for the velocity associated with ejected spike structures, whereas a recently suggested model explains the observed bubble velocities. Specifically, we find the asymptotic bubble velocity prediction given by Mikaelian is in excellent agreement with the simulations, when a nonlinear correction for finite amplitudes is used in that model. In contrast, existing models can overpredict observed spike velocities if they do not include the modification of the initial spike growth rates due to nonlinearities. Instead, we find that when potential flow models are corrected with a suitable nonlinear prefactor, this leads to predictions in close agreement with our simulation data. We also propose a simple empirical expression for the nonlinear correction for spike velocities which is able to reproduce results from our simulations and published experimental and simulation data over a wide range of initial conditions and Mach numbers. We discuss extensions of these models to initial interfaces with arbitrary shapes. In particular, for non-sinusoidal shapes, the bubble and spike velocities are still predicted by these models provided we use an effective wavelength λ eff which is the wavelength of an equivalent sinusoid that has the same missing area. Lastly, the issues of nonlinearity, non-standard shapes and shock Mach number addressed in this work are relevant to recent experimental campaigns involving twice-shocked targets.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2024

Impacts of aluminum-cerium alloy deployment on different cerium commodities

An imbalance problem exists in the rare earth element (REE) market with cerium and lanthanum being more abundant and less valuable than REEs used in permanent magnets such as neodymium, praseodymium, and dysprosium. Research has been conducted on new applications for abundant REEs to improve mining economics. However, potential market impacts of these applications on individual REE commodities are unknown. A system dynamics model was built to investigate the impacts of a new aluminum-cerium (Al-Ce) alloy that can theoretically utilize three separate cerium forms: cerium carbonate, cerium oxide, or cerium metal. Cerium carbonate currently possesses the lowest price of the three available forms making it initially the most favorable choice. However, model results showed that cerium oxide could provide the best economics for future Al-Ce alloy deployment because its larger market size buffers major shocks to price.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2021

Adoption of delivery services in light of the COVID pandemic: Who and how long?

A significant growth in demand for online shopping in light of the Coronavirus Disease (COVID) crisis has received attention from transportation practitioners, policy-makers, and researchers. However, an important question arises in this increase in online shopping and resulting deliveries: How long will this last? Very little is known whether this popularity would last a long time. Here, to address this question, the authors conducted a survey of 915 individuals residing in the U.S. and classified them into the four distinctive consumer types (i.e., the prior adopter, temporary adopter and permanent new adopter, and non-adopter) depending on their usage of delivery services before, during, and after (expected) the COVID crisis. This research aims to gain behavioral insight by exploring the differences between the four consumer types and investigating factors affecting the initial adoption and continuance intention of using delivery services. The descriptive analysis revealed that there are clear differences not only between the four types of consumers but also between the four product types (i.e., grocery, food, home goods, and other packages) considered in the survey. The models found that factors affecting the initial adoption and continuance intention are different from the previous studies conducted before the COVID pandemic. Implications for planning and policymaking are also discussed.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2025

Interplays In The Rare Earth Element Value Chain

Severson, Michael [Idaho National Laboratory (INL)↗

DOE OSTI2020

Combined Environments: Driving multiple loads on Z

Pulsed power drivers such as the Z generator of Sandia National Laboratories typically deliver high current (>20MA) to single experiments. This project is intended to develop and assess ways to simultaneously drive multiple targets on a single pulsed power driver (specifically a neutron and an x-ray producing target driven in a single experiment). The combined x-ray/neutron environment produced will then be used to investigate potential synergistic effects in integrated circuits. A pre-requisite for being able to design and study multiple targets on Z is first adapting simulation tools to be able to model them effectively. This will enable us to assess the tradeoffs between the different ways multiple targets can be combined, and to better understand how existing and future pulsed power machines can be used to generate combined testing environments. This report is limited to documenting the initial development of a parallel load modeling capability that is presently being applied to design experiments to produce combined neutron/x-ray environments on Z.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2015

Evaluation of cloud-resolving model simulations of midlatitude cirrus with ARM and A-train observations

Cirrus clouds are ubiquitous in the upper troposphere and still constitute one of the largest uncertainties in climate predictions. Our paper evaluates cloud-resolving model (CRM) and cloud system-resolving model (CSRM) simulations of a midlatitude cirrus case with comprehensive observations collected under the auspices of the Atmospheric Radiation Measurements (ARM) program and with spaceborne observations from the National Aeronautics and Space Administration A-train satellites. The CRM simulations are driven with periodic boundary conditions and ARM forcing data, whereas the CSRM simulations are driven by the ERA-Interim product. Vertical profiles of temperature, relative humidity, and wind speeds are reasonably well simulated by the CSRM and CRM, but there are remaining biases in the temperature, wind speeds, and relative humidity, which can be mitigated through nudging the model simulations toward the observed radiosonde profiles. Simulated vertical velocities are underestimated in all simulations except in the CRM simulations with grid spacings of 500 m or finer, which suggests that turbulent vertical air motions in cirrus clouds need to be parameterized in general circulation models and in CSRM simulations with horizontal grid spacings on the order of 1 km. The simulated ice water content and ice number concentrations agree with the observations in the CSRM but are underestimated in the CRM simulations. The underestimation of ice number concentrations is consistent with the overestimation of radar reflectivity in the CRM simulations and suggests that the model produces too many large ice particles especially toward the cloud base. Simulated cloud profiles are rather insensitive to perturbations in the initial conditions or the dimensionality of the model domain, but the treatment of the forcing data has a considerable effect on the outcome of the model simulations. Despite considerable progress in observations and microphysical parameterizations, simulating the microphysical, macrophysical, and radiative properties of cirrus remains challenging. Comparing model simulations with observations from multiple instruments and observational platforms is important for revealing model deficiencies and for providing rigorous benchmarks. But, there still is considerable need for reducing observational uncertainties and providing better observations especially for relative humidity and for the size distribution and chemical composition of aerosols in the upper troposphere.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2016

Experimental comparison of residual stresses for a thermomechanical model for the simulation of selective laser melting

Selective laser melting (SLM) is an additive manufacturing process in which multiple, successive layers of metal powders are heated via laser in order to build a part. Modeling of SLM requires consideration of the complex interaction between heat transfer and solid mechanics. Here, the present work describes the authors initial efforts to validate their first generation model. In particular, the comparison of model-generated solid mechanics results, including both deformation and stresses, is presented. Additionally, results of various perturbations of the process parameters and modeling strategies are discussed.

42 ENGINEERING↗

DOE OSTI2017

Particle tracing modeling of ion fluxes at geosynchronous orbit

The initial results of a coupled MHD/particle tracing method to evaluate particle fluxes in the inner magnetosphere are presented. This setup is capable of capturing the earthward particle acceleration process resulting from dipolarization events in the tail region of the magnetosphere. On the period of study, the MHD code was able to capture a dipolarization event and the particle tracing algorithm was able to capture our results of these disturbances and calculate proton fluxes in the night side geosynchronous orbit region. The simulation captured dispersionless injections as well as the energy dispersion signatures that are frequently observed by satellites at geosynchronous orbit. Currently, ring current models rely on Maxwellian-type distributions based on either empirical flux values or sparse satellite data for their boundary conditions close to geosynchronous orbit. In spite of some differences in intensity and timing, the setup presented here is able to capture substorm injections, which represents an improvement regarding a reverse way of coupling these ring current models with MHD codes through the use of boundary conditions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2020

Reconciling Contrasting Relationships Between Relative Dispersion and Volume-Mean Radius of Cloud Droplet Size Distributions

Cloud droplet spectral relative dispersion is critical to parameterizations of cloud radiative properties, warm-rain initiation, and aerosol-cloud interactions in models; however, there is no consistent relationship between relative dispersion and volume-mean radius in literature, which hinders improving relative dispersion parameterization and calls for physical explanation. Here we show, by analyzing aircraft observations of cumulus clouds during Routine AAF [Atmospheric Radiation Measurement (ARM) Aerial Facility] Clouds with Low Optical Water Depths (CLOWD) Optical Radiative Observations, that the correlation between relative dispersion and volume-mean radius changes from positive to negative as volume-mean radius increases. With the new observation, we postulate that the sign of the correlation is determined by whether or not condensation (evaporation) occurs simultaneously with significant new activation (deactivation). The hypothesis is validated by simulations of both an adiabatic cloud parcel model and a parcel model accounting for entrainment-mixing. A new quantity, first bin strength, is introduced to quantify this new observation. Theoretical analysis of truncated gamma and modified gamma size distributions further supports the hypothesis and reconciles the contrasting relationships between relative dispersion and volume-mean radius, including the results in polluted fog observations. The results could shed new light on the so-called “twilight zone” between cloudy and cloud-free air, which in turn affects evaluation of aerosol-cloud interactions and retrieval of aerosol optical depth.

Lu, Chunsong↗