A molecularly defined duplication set for the X chromosome of Drosophila melanogaster
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60 APPLIED LIFE SCIENCES↗
SEARCH · Engineering Papers
Results for “FUNCTIONAL MODELS”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Source spectra of the first four Source Physics Experiments (SPE) explosions from the frequency-domain moment-tensor inversion
In this study, I used seismic waveforms recorded within 2 km from the epicenter of the first four Source Physics Experiments (SPE) explosions to invert for the moment-tensor spectra of these explosions. I employed a one-dimensional (1D) Earth model for Green's function calculations. The model was developed from P- and R g -wave travel times and amplitudes. I selected data for the inversion based on the criterion that they had consistent travel times and amplitude behavior as those predicted by the 1D model. Due to limited azimuthal coverage of the sources and the mostly vertical-component-only nature of the dataset, only long-period, volumetric components of the moment-tensor spectra were well constrained.
58 GEOSCIENCES↗
Point spread function estimation using radially symmetric prior modeling and enhanced Gibbs sampling
Presentation describes research to extract quantitative information about an imaging system from calibration imagery using radiographic data from the Cygnus Dual Beam Radiography Facility at the Nevada National Security Site.
97 MATHEMATICS AND COMPUTING↗
Updates to Nek5000: RANS wall functions, NRC support, and documentation
As a key part of the U.S. Department of Energy’s Nuclear Energy Advanced Modeling and Simulation program (NEAMS), the next generation of tools for nuclear reactor design are being developed. A primary metric for success of this program is the adoption of those tools by industry stakeholders. To help meet this metric for Nek5000, development efforts this year have focused on the expansion of the available Reynolds-averaged Navier-Stokes (RANS) turbulence models to include wall function models, continued support of the U.S. Nuclear Regulatory Commission in simulating a hydrogen mitigation benchmark experiment, and expansion of the Nek5000 documentation to enhance the code’s usability. The implementation of wall functions is intended to significantly decrease time to-solution for a wide range of problems and it has been identified as an important feature by stakeholders across the nuclear community. The initial implementation of standard and pressure corrected wall functions has been tested in Nek5000 on the classical problems of channel flow and a backward facing step. It has also been tested on a 2D molten salt fast reactor core and a T-junction. The recommended formulation of choosing y + = 30 as a boundary value combined with a Neumann-Neumann formulation of the boundary condition for k and τ produces the most consistent results compared to a wall resolved approach. The collaboration with the NRC is a continuing exercise that has been ongoing for multiple years. This year we have concluded investigations into appropriate inlet conditions, showing that fully developed turbulent conditions are adequate for the full PANDA domain. We have also concluded simulations for an unobstructed jet and are now refocusing to the original obstructed jet case. The expansion of the code documentation has also been an ongoing effort over the past few years to address feedback from the various stakeholders. The documentation now more fully covers many of the available features and closes identified SQA gaps. Finally we report on three training sessions that were offered over the past year in an effort to expand the Nek5000 user base.
22 GENERAL STUDIES OF NUCLEAR REACTORS↗
Modeling the Joint Effects of Vegetation Characteristics and Soil Properties on Ecosystem Dynamics in a Panama Tropical Forest
Abstract In tropical forests, both vegetation characteristics and soil properties are important not only for controlling energy, water, and gas exchanges directly but also determining the competition among species, successional dynamics, forest structure and composition. However, the joint effects of the two factors have received limited attention in Earth system model development. Here we use a vegetation demographic model, the Functionally Assembled Terrestrial Ecosystem Simulator (FATES) implemented in the Energy Exascale Earth System Model (E3SM) Land Model (ELM), ELM‐FATES, to explore how plant traits and soil properties affect tropical forest growth and composition concurrently. A large ensemble of simulations with perturbed vegetation and soil hydrological parameters is conducted at the Barro Colorado Island, Panama. The simulations are compared against observed carbon, energy, and water fluxes. We find that soil hydrological parameters, particularly the scaling exponent of the soil retention curve ( B sw ), play crucial roles in controlling forest diversity, with higher B sw values (>7) favoring late successional species in competition, and lower B sw values (1 ∼ 7) promoting the coexistence of early and late successional plants. Considering the additional impact of soil properties resolves a systematic bias of FATES in simulating sensible/latent heat partitioning with repercussion on water budget and plant coexistence. A greater fraction of deeper tree roots can help maintain the dry‐season soil moisture and plant gas exchange. As soil properties are as important as vegetation parameters in predicting tropical forest dynamics, more efforts are needed to improve parameterizations of soil functions and belowground processes and their interactions with aboveground vegetation dynamics.
54 ENVIRONMENTAL SCIENCES↗
Adsorption of simple square-well fluids in slit nanopores: Modeling based on Generalized van der Waals partition function and Monte Carlo simulation
A model based on the Generalized van der Waals partition function is derived to predict the adsorption of square-well fluid in slit pores of any size, the walls of which also have square-well potential. The space inside the pore is divided into several regions based on the extent of the attractive regions generated by the walls. Closed-form expressions of the chemical potentials of the confined fluid in different regions in the pore are obtained. The densities of fluid in different regions are calculated by equalizing the chemical potentials of fluid in those regions to that of the bulk phase. To examine the accuracy of the model, the Grand Canonical Monte Carlo (GCMC) simulation is also conducted. Here we find that the model well captures the effects of the bulk conditions and the properties of adsorbate and pore on the density of adsorbate in the pore. The model is also shown to be able to predict the adsorption of real gases in various activated carbons.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Application of Density Functional Theory To Study the Double Layer of an Electrolyte with an Explicit Dimer Model for the Solvent
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catalysis (heterogeneous)↗
Deep Inelastic Electron Scattering Off the Helium and Tritium Mirror Nuclei
We discuss a possible measurement of the ratio of nucleon structure functions, F{sub 2}{sup n}/F{sub 2}{sup p}, and the ratio of up to down quark distributions, u/d, at large Bjorken x, by performing deep inelastic electron scattering from the {sup 3}H and {sup 3}He mirror nuclei with the 11 GeV upgraded beam of Jefferson Lab. The measurement is expected to be almost free of nuclear effects, which introduce a significant uncertainty in the extraction of these two ratios from deep inelastic scattering off the proton and deuteron. The results are expected to test perturbative and non-perturbative mechanisms of spin-flavor symmetry breaking in the nucleon, and constrain the structure function parametrizations needed for the interpretation of high energy collider and neutrino oscillations data. The precision of the expected data can also test models of the nuclear EMC effect and provide valuable input for its full explanation.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
A Framework for Inverse Prediction Using Functional Response Data
Inverse prediction models have commonly been developed to handle scalar data from physical experiments. However, it is not uncommon for data to be collected in functional form. When data are collected in functional form, it must be aggregated to fit the form of traditional methods, which often results in a loss of information. For expensive experiments, this loss of information can be costly. In this study, we introduce the functional inverse prediction (FIP) framework, a general approach which uses the full information in functional response data to provide inverse predictions with probabilistic prediction uncertainties obtained with the bootstrap. The FIP framework is a general methodology that can be modified by practitioners to accommodate many different applications and types of data. We demonstrate the framework, highlighting points of flexibility, with a simulation example and applications to weather data and to nuclear forensics. Results show how functional models can improve the accuracy and precision of predictions.
42 ENGINEERING↗
Potential reductions in fine particulate matter and premature mortality following implementation of air pollution controls on coal-fired power plants in India
Coal-fired power plants (CFPPs) account for > 70% of electricity generation in India, but < 5% of facilities have installed technologies for sulfur dioxide (SO 2 ) and nitrogen oxide (NO X ) removal. Emissions of these pollutants lead to the formation of fine particulate matter (PM 2.5 ) and an increased risk of premature mortality for exposed populations. Here, we use a nested version of the GEOS-Chem global chemical transport model (0.5° × 0.625° resolution) for India to estimate reductions in PM 2.5 concentrations that could have been achieved by implementing existing emission control technologies like flue-gas desulfurization (FGD) and/or selective catalytic reduction (SCR). We quantify the associated burden of disease using the integrated exposure response (IER) and global exposure mortality model (GEMM) functions and compare the costs of premature mortality to those for FGD installation. Model simulations for 2010 suggest installation of FGD would have reduced mean annual PM 2.5 concentrations across India by 8%, compared to 3% with SCR installation, and 11% with both FGD and SCR. A 7–28% reduction in PM 2.5 was simulated for local communities closest to CFPPs (same model grid cell), leading to up to 17% reduction in annual premature mortality. Overall, more than 0.21–0.48 million premature deaths would have been avoided over a 10-year period if FGD had been implemented on all CFPPs, compared to 0.09–0.21 million with SCR and 0.22–0.72 million with both FGD and SCR. Benefits associated with such actions are approximately $\$18.1$–$\$604$ billion USD per year, which is equivalent to ~ 0.44 to 10% of India’s GDP. These results suggest that monetary benefits from avoided premature mortality far outweigh the capital and operational costs of FGD and/or SCR installation of $\$19.5$ billion and/or $\$32.8$ billion per year, respectively. This information is essential because the high costs of installation and operation are often given as reasons for delaying installation and commissioning. Finally, we conclude that policy actions to control air pollution from CFPPs are economically justifiable.
63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
Technical Note: On the analytical proton dose evaluation in compounds and mixtures
Purpose: By combining the physical processes occurring due to the interaction of protons with matter, analytical theories published so far have provided acceptable models for calculating depth-dose distributions in homogeneous media. As a well-defined and comprehensive theory, the formula derived by Bortfeld models the dose transferred to the target in terms of the parabolic cylinder function. The model also includes three parameters with values specified for an initial proton energy and for the target material. These parameters are obtainable through the data gathered in nuclear data tables. The analytical studies using this interesting model are therefore restricted to those materials for which the data have been provided in these tables. This study aims to find general solutions for calculation of these parameters for a compound or mixture composed of an arbitrary choice of constituent elements. Methods: Inspired by formulas dedicated for calculating the range and the probability of undergoing nonelastic nuclear interactions for protons in desired compounds, the analytical methods for finding the three mentioned parameters are investigated. The accuracy of the methods suggested is examined through comparison of the results with those which are calculated using the data taken from nuclear data tables. By employing the calculated parameters using the derived formulas in the Bortfeld model, the dose distribution at depth in a chosen target is calculated. Results: For an arbitrary selection of compounds, the predictions of the analytical depth-dose model using these parameters have been found to closely match the results employing the parameters calculated using the data reported in nuclear data tables. Conclusions: The formulas presented are general, mathematically easy to handle, and valid for almost every compound or mixture including materials of interest for proton radiotherapy purposes, making the Bortfeld model more practical and advantageous.
61 RADIATION PROTECTION AND DOSIMETRY↗
Leveraging Artificial Intelligence to Predict Novel Eutectic Alloys
The goal of this project was to train an artificial neural network (ANN) to predict the fractional composition and melting point of eutectic alloys using fundamental atomic properties as inputs. The fundamental properties considered include atomic number, atomic weight, atomic radius, valence electron concentration, electronegativity, and electron affinity. The project involved several phases, starting with data preparation, where phase diagram data was harvested from the ASM International database. Approximately 1300 binary eutectics were collected and cleaned to ensure relevance and accuracy. A regression model was selected for training, utilizing a rectified linear unit as the activation function. Various model configurations were evaluated for predictive accuracy, with validation techniques employed to ensure robustness. The model demonstrated predictive capabilities above random guessing and was able to achieve up to 11% accuracy under certain conditions. An ablative test identified atomic radius and valence electron concentration as critical inputs for model performance. Incorporating the melting point of atomic constituents improved accuracy significantly, although ultimately the model’s predictive capability still fell short of the 80% target. This report details the methodology, results, and implications of the research, contributing to the understanding of employing artificial intelligence to predict the phase transition behavior of eutectic alloys.
36 MATERIALS SCIENCE↗
Interference effects in proton scattering on {sup 15}N nuclei at intermediate energies
The differential cross section for proton scattering on {sup 15}N nuclei is calculated within Glauber diffraction theory at energies of 0.2, 0.6, and 1.0 GeV. Use is made of the shell-model wave function for the {sup 15}N nucleus. The contribution of single and double collisions to the Glauber operator {Omega} is taken into account. The sensitivity of the differential cross sections to the contributions of scattering on nucleons from different shells, to the parameters of the elementary pN amplitude, and to the energy of projectile protons is investigated. It is shown that the interference between amplitudes corresponding to different collision multiplicities, as well as between the amplitudes for scattering on nucleons from different shells, determines special features of the cross section.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
String in Horava-Lifshitz gravity
We generalize recent analysis of the dynamics of point particle in Horava-Lifshitz background to the case of string probe when we replace the Hamiltonian constraint of the Polyakov string with the constraint that breaks Lorentz invariance of target space-time. Then, we find corresponding Lagrangian and argue that the world sheet theory is invariant under foliation-preserving diffeomorphism. Finally, we discuss the Hamiltonian dynamics and show that this is well defined on condition that the world sheet lapse function obeys the projectability condition.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Decomposition by ectomycorrhizal fungi alters soil carbon storage in a simulation model
Carbon cycle models often lack explicit belowground organism activity, yet belowground organisms regulate carbon storage and release in soil. Ectomycorrhizal fungi are important players in the carbon cycle because they are a conduit into soil for carbon assimilated by the plant. It is hypothesized that ectomycorrhizal fungi can also be active decomposers when plant carbon allocation to fungi is low. Here, we reviewed the literature on ectomycorrhizal decomposition and we developed a simulation model of the plant-mycorrhizae interaction where a reduction in plant productivity stimulates ectomycorrhizal fungi to decompose soil organic matter. Our review highlights evidence demonstrating the potential for ectomycorrhizal fungi to decompose soil organic matter. Our model output suggests that ectomycorrhizal activity accounts for a portion of carbon decomposed in soil, but this portion varied with plant productivity and the mycorrhizal carbon uptake strategy simulated. Lower organic matter inputs to soil were largely responsible for reduced soil carbon storage. Using mathematical theory, we demonstrated that biotic interactions affect predictions of ecosystem functions. Specifically, we developed a simple function to model the mycorrhizal switch in function from plant symbiont to decomposer. In conclusion, we show that including mycorrhizal fungi with the flexibility of mutualistic and saprotrophic lifestyles alters predictions of ecosystem function.
59 BASIC BIOLOGICAL SCIENCES↗
Perspective: Size selected clusters for catalysis and electrochemistry
We report that size-selected clusters containing a handful of atoms may possess noble catalytic properties different from nano-sized or bulk catalysts. Size- and composition-selected clusters can also serve as models of the catalytic active site, where an addition or removal of a single atom can have a dramatic effect on their activity and selectivity. In this Perspective, we provide an overview of studies performed under both ultra-high vacuum and realistic reaction conditions aimed at the interrogation, characterization and understanding of the performance of supported size-selected clusters in heterogeneous and electrochemical reactions, which address the effects of cluster size, cluster composition, cluster-support interactions and reaction conditions, the key parameters for the understanding and control of catalyst functionality. Computational modelling based on density functional theory sampling of local minima and energy barriers or ab initio Molecular Dynamics simulations is an integral part of this research by providing fundamental understanding of the catalytic processes at the atomic level, as well as by predicting new materials compositions which can be validated in experiments. Lastly, we discuss approaches which aim at the scale up of the production of well-defined clusters for use in real world applications.
36 MATERIALS SCIENCE↗
In vivo mapping of mutagenesis sensitivity of human enhancers
Distant-acting enhancers are central to human development1. However, our limited understanding of their functional sequence features prevents the interpretation of enhancer mutations in disease2. Here we determined the functional sensitivity to mutagenesis of human developmental enhancers in vivo. Focusing on seven enhancers that are active in the developing brain, heart, limb and face, we created over 1,700 transgenic mice for over 260 mutagenized enhancer alleles. Systematic mutation of 12-base-pair blocks collectively altered each sequence feature in each enhancer at least once. We show that 69% of all blocks are required for normal in vivo activity, with mutations more commonly resulting in loss (60%) than in gain (9%) of function. Using predictive modelling, we annotated critical nucleotides at the base-pair resolution. The vast majority of motifs predicted by these machine learning models (88%) coincided with changes in in vivo function, and the models showed considerable sensitivity, identifying 59% of all functional blocks. Taken together, our results reveal that human enhancers contain a high density of sequence features that are required for their normal in vivo function and provide a rich resource for further exploration of human enhancer logic.
Kosicki, Michael↗
Functionally Assembled Terrestrial Ecosystem Simulator (FATES) for Hurricane Disturbance and Recovery
Tropical cyclones are an important cause of forest disturbance, and major storms caused severe structural damage and elevated tree mortality in coastal tropical forests. Model capabilities that can be used to understand post-hurricane forest recovery are still limited. We use a vegetation demography model, the Functionally Assembled Terrestrial Ecosystem Simulator, coupled with the Energy Exascale Earth System Model Land Model (ELM-FATES) to study the processes and the key factors regulating post-hurricane forest recovery. We implemented hurricane-induced forest damage, including defoliation, structural biomass reduction, and tree mortality, performed ensemble model simulations, and used random forest feature importance. For the simulation in the Luquillo Experimental Forest, Puerto Rico, we identified factors controlling the post-hurricane forest recovery, and quantified the sensitivity of key model parameters to the post-hurricane forest recovery. The results indicate a tendency for the Bisley forests to shift toward the light demanding plant functional type (PFT) when the pre-hurricane biomass between the light demanding and shade tolerant PFTs is nearly equal and forests experience hurricane disturbance with mortality >60% for both the two PFTs. Under more realistic conditions where the shade tolerant PFT is initially dominant, mortality >80% is required for a shift toward dominance of the light demanding PFT at Bisley. Hurricane mortality and background mortality are the two major factors regulating post-hurricane forest recovery in simulations. This research improves understanding of the ELM-FATES model behavior associated with hurricane disturbance and provides guidance for dynamic vegetation model development in representing hurricane induced forest damage with varied intensities.
54 ENVIRONMENTAL SCIENCES↗