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At least 1,261 records · Page 70

Mathematical Modeling on the Influence of Casting Parameters on Initial Solidification at the Meniscus of Slab Continuous Casting

In the current study, the two-dimensional mold model was applied to investigate the influence of different casting parameters on the initial solidification at the meniscus of the continuous casting mold. The profile of the meniscus and the slag rim, and the heat flux on the hot face of the copper plate, were compared with different locations of the mold and different casting parameters. The depth of the oscillation marks and solidified meniscus through simulation was measured with different casting parameters. With the mold oscillating downward from the peak to the valley, the maximum heat flux on the hot face of the copper plate near the meniscus increased from 4.3 to 5.5 MW/m{sup 2}, the thickness of the slag rim decreased from 4.7 to 4.2 mm, and the height of the curved meniscus also decreased. With the increase of casting speed from 1.2 to 1.45 m/min, the maximum speed of the upper backflow increased from 0.6 to 0.8 m/s, and the lowest location of the meniscus at approximately 310 mm from the copper plate decreased from 22 to 12 mm below the meniscus near the nozzle, where the slag entrapment easily occurred. With the increase of the casting speed, casting superheat, and oscillation frequency, and the decrease of the water flow rate in the mold and oscillation amplitude, the thickness of the slag rim decreased. With the increase of casting speed and superheat, and the decrease of the water flow rate in the mold, oscillation frequency, and oscillation amplitude, the depth of the solidified meniscus decreased. The regression equation was fitted to estimate the depth of hooks at the subsurface of slabs.

36 MATERIALS SCIENCE↗

Life cycle cost modeling of conceptual space vehicles

This paper documents progress to date by the University of Dayton on the development of a life cycle cost model for use during the conceptual design of new launch vehicles and spacecraft. This research is being conducted under NASA Research Grant NAG-1-1327. This research effort changes the focus from that of the first two years in which a reliability and maintainability model was developed to the initial development of a life cycle cost model. Cost categories are initially patterned after NASA's three axis work breakdown structure consisting of a configuration axis (vehicle), a function axis, and a cost axis. The focus will be on operations and maintenance costs and other recurring costs. Secondary tasks performed concurrent with the development of the life cycle costing model include continual support and upgrade of the R&M model. The primary result of the completed research will be a methodology and a computer implementation of the methodology to provide for timely cost analysis in support of the conceptual design activities. The major objectives of this research are: to obtain and to develop improved methods for estimating manpower, spares, software and hardware costs, facilities costs, and other cost categories as identified by NASA personnel; to construct a life cycle cost model of a space transportation system for budget exercises and performance-cost trade-off analysis during the conceptual and development stages; to continue to support modifications and enhancements to the R&M model; and to continue to assist in the development of a simulation model to provide an integrated view of the operations and support of the proposed system.

Ebeling, Charles↗

Alternative translation initiation from two in-frame start codons in DHX33 gene

Highlights: • DHX33 can be translated via leaky scanning. • The isoforms of DHX33 via leaky scanning have similar localization and functions. • Leaky scanning of DHX33 is conserved in human and in mouse. DHX33 has been shown to play key roles in promoting cell proliferation. We have previously found that DHX33 protein is a doublet. In this report, we discovered that DHX33 doublet is due to alternative translation initiation by two in-frame initiation codons. This is supported by studies from both cell lines and mouse models. DHX33 translation initiation from either AUG codon happens at equal efficiency. Short DHX33 protein has similar cellular location and functions with full-length DHX33. Our results suggest that leaky scanning normally occur in DHX33 mRNA translation, which may serve as a safeguard mechanism to ensure optimal DHX33 translation efficiency. This is the first report of DEAD/DEAH box proteins that can be regulated by alternative translation initiation.

60 APPLIED LIFE SCIENCES↗

A coupled rate theory-Monte Carlo model of helium bubble evolution in plasma-facing micro-engineered tungsten

A multiscale model of helium bubble evolution in plasma-facing materials is developed. The model links different stages of helium bubble evolution: deposition, nucleation, growth, motion, and coalescence. Helium deposition is simulated with the SRIM Monte Carlo program to give spatial information on helium and displacement damage distributions near the surface. This deposition profile is then introduced into a space-dependent rate theory of bubble nucleation and growth to describe the early stages of the distribution and size of helium bubbles. The coarsening stage of bubble evolution as a result of whole bubble motion, interaction, and coalescence is modeled by a new Object Kinetic Monte Carlo (OKMC) model, for which initial conditions are taken from the mean-field rate theory calculations. The model is compared to experimental data on low-energy helium plasma interaction with micro-engineered tungsten (W), and on high-energy helium ion deposition in flat W samples. Novel features of the multiscale model include: (1) space-dependent rate theory; (2) OKMC model of bubble motion in stress and temperature fields; and (3) application of the model to micro-engineered materials, and comparison with experiments on the same time-scale. At low helium ion energy, it is found that the mechanism of trap mutation is essential in achieving good agreement with experimental measurements. On the other hand, good agreement with experiments at high incident ion energy and temperature showed the importance of bubble coalescence and coarsening as main mechanisms. The results of the model are compared with experiments on flat W surfaces irradiated at high ion energy (30 keV), and with micro-engineered W, where the surface is coated with high-density micro-pillars at low ion energy (around 100 eV). The predicted average bubble radius and density are in qualitative agreement with experimental results.

36 MATERIALS SCIENCE↗

The 25 kW power module evolution study. Part 3: Conceptual designs for power module evolutions. Volume 3: Cost estimates

Cost data generated for the evolutionary power module concepts selected are reported. The initial acquisition costs (design, development, and protoflight unit test costs) were defined and modeled for the baseline 25 kW power module configurations. By building a parametric model of this initial building block, the cost of the 50 kW and the 100 kW power modules were derived by defining only their configuration and programmatic differences from the 25 kW baseline module. Variations in cost for the quantities needed to fulfill the mission scenarios were derived by applying appropriate learning curves.

Source record↗

Mesoscale modeling of the severe thunderstorm environment

The abilities of limited-area mesoscale models to provide accurate predictions of the environment of midlatitude severe thunderstorms and the possible feedback effects of the storms upon their environment are reviewed. Mesoaplha-scale models, mesobeta models, and terrain-induced mesoscale systems are discussed. The importance of the initial state and model numerics and physics is examined. It is found that mesoscale models must be run locally if they are to be used for short-range forecasting.

Koch, Steven E.↗

Suborbital Research and Development Opportunities

This slide presentation reviews the new strategies for problem solving in the life sciences in the suborbital realm. Topics covered are: an overview of the space life sciences, the strategic initiatives that the Space Life Sciences organization engaged in, and the new business model that these initiatives were developed. Several opportunities for research are also reviewed.

Davis, Jeffrey R.↗

ORION Environmental Control and Life Support Systems Suit Loop and Pressure Control Analysis

Under NASA's ORION Multi-Purpose Crew Vehicle (MPCV) Environmental Control and Life Support System (ECLSS) Project at Johnson Space Center's (JSC), the Crew and Thermal Systems Division has developed performance models of the air system using Thermal Desktop/FloCAD. The Thermal Desktop model includes an Air Revitalization System (ARS Loop), a Suit Loop, a Cabin Loop, and Pressure Control System (PCS) for supplying make-up gas (N2 and O2) to the Cabin and Suit Loop. The ARS and PCS are designed to maintain air quality at acceptable O2, CO2 and humidity levels as well as internal pressures in the vehicle Cabin and during suited operations. This effort required development of a suite of Thermal Desktop Orion ECLSS models to address the need for various simulation capabilities regarding ECLSS performance. An initial highly detailed model of the ARS Loop was developed in order to simulate rapid pressure transients (water hammer effects) within the ARS Loop caused by events such as cycling of the Pressurized Swing Adsorption (PSA) Beds and required high temporal resolution (small time steps) in the model during simulation. A second ECLSS model was developed to simulate events which occur over longer periods of time (over 30 minutes) where O2, CO2 and humidity levels, as well as internal pressures needed to be monitored in the cabin and for suited operations. Stand-alone models of the PCS and the Negative Pressure relief Valve (NPRV) were developed to study thermal effects within the PCS during emergency scenarios (Cabin Leak) and cabin pressurization during vehicle re-entry into Earth's atmosphere. Results from the Orion ECLSS models were used during Orion Delta-PDR (July, 2014) to address Key Design Requirements (KDR's) for Suit Loop operations for multiple mission scenarios.

Eckhardt, Brad↗

Quantitative Prediction of Perovskite Stability Using Accelerated Testing and Machine Learning

PV technologies based on hybrid perovskites offer the potential for reducing solar cell costs, but they are particularly vulnerable to degradation by environmental factors such as moisture, oxygen, and illumination. Commercialization will require not only stable materials and device architectures but also accelerated testing protocols and models that can predict degradation from the accelerated testing data. Here, we report results from in situ photoluminescence (PL) and photoconductivity (PC) measurements during perovskite degradation with simultaneous optical transmittance (Tr) measurements or reflected dark field (DF) imaging. From PL, PC, Tr, and DF, we determine (respectively) the steady-state quasi-Fermi level splitting, the mean effective carrier diffusion length, the extent of conversion of perovskite to higher bandgap degradation products, and the extent of scattering from domains with different orientation or composition, all as a function of time during degradation. Simultaneous measurement of PL-PC-Tr or PL-PC-DF on perovskite absorbers in an environmental chamber over a wide range of humidity, oxygen, temperature, and illumination levels yields a rich data set. We use machine learning to develop a model that accurately predicts (within 10%) the time for the diffusion length to decrease to 85% of its initial value. The model takes the environmental conditions and the first few measurements from the PL-PC-Tr or PL-PC-DF experiment as input. Thus, the model provides a framework to interpret the results of accelerated testing of absorber materials. One of the dominant features in the model of degradation for CH 3 NH 3 PbI 3 is the initial rate at which transmittance increase. For devices with opaque contacts, the pixel-averaged rate of change of the intensity in dark-field images can be used in place of transmittance. Results are also presented on full PV devices with in-situ current-voltage (JV) measurements. Here, the data from simultaneous PL-DF-JV under environmental stresses reveal intimate connection between degradation and shunts and provide a framework to extend accelerated testing to devices. Further, the presentation reveals underlying universal behavior in degradation pathways over a broad range of environmental stresses and perovskite compositions.

14 SOLAR ENERGY↗

Hybrid model with dynamical sources for heavy-ion collisions at BES energies

We develop a (3+1)-dimensional hybrid evolution model for heavy-ion collisions with dynamical sources for the energy-momentum tensor and baryon current. During an initial pre-equilibrium stage based on UrQMD, the four-momenta and baryon numbers carried by secondary particles created within UrQMD are fed continuously, after a short thermalization time, into a (3+1)-dimensional viscous hydrodynamic evolution module including baryon transport. The sensitivity of the initial conditions to model parameters and the effect of baryon diffusion on the hydrodynamic evolution are studied.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

COMPUTATIONAL MODELING OF IGNITION AND PREMIXED FLAME PROPAGATION INITIATED BY A PRE-CHAMBER TURBULENT JET

Addressing the pressing need for reduced carbon emissions, Turbulent Jet Ignition (TJI) emerges as a promising technology for ultra-lean combustion, offering enhanced thermal efficiencies and minimized cyclic variability in spark-ignited engines. To facilitate rapid testing and integration of this technology, a robust computational modeling framework is crucial. This study delves into the predictive capabilities of computational models for main-chamber ignition and premixed flame propagation using a single-cycle TJI rig measured by Biswas et al. (Applied Thermal Engineering, vol 106, 2016). Employing an open-source compressible flow simulation solver with Large Eddy Simulation (LES) for turbulence modeling, the investigation integrates the conventional Laminar Finite Rate Chemistry (LFRC) model alongside the transported Probability Density Method (PDF) for turbulence-chemistry interaction. A fully-consistent Eulerian Monte-Carlo Fields (EMCF) method is utilized to approximate the transported PDF, while Interaction by Exchange with Mean is employed to close micro-mixing terms in stochastic differential equations. A reduced chemical reaction mechanism with 21 species and 84 reactions (DRM-19) is used for solving chemical kinetics, and a double Gaussian energy deposition model is used to approximate the spark ignition in the pre-chamber. An unstructured O-grid mesh with 0.3 million cells in the prechamber and 1 million cells in the main chamber is employed. Results are divided into two phases: pre-chamber initialization and full TJI simulations. Validation of the predicted pre-chamber flame propagation and the lean ignition in the main-chamber is carried out by using available experimental data. Under quiescent conditions, both the LFRC and transported PDF methods largely underestimate the flame speed and subsequent pressure growth in the pre-chamber. A linear momentum forcing technique is applied to investigate the impact of initial turbulence in the pre-chamber, demonstrating a notable influence on flame propagation. Fine-tuning of the forcing coefficient reproduces the sudden pressure growth observed in the experiment. The experimentally validated pre-chamber simulation serves as the initial condition for the full TJI simulations. It is found that the LFRC model fails to predict lean-ignition in the main-chamber, resulting in a misfiring event. Incorporation of turbulence-chemistry interaction using the transported PDF method substantially improves the prediction of the ignition event in the main-chamber, achieving fair qualitative agreement and quantitative validation of combustion parameters within ±10% of the reported experimental data. The rich simulation results consisting of a full set of statistical description of the thermo-chemical states enable us to gain deep insights into the ignition mechanisms in the main chamber, which is limited when done experimentally. A novel dual ignition phenomenon is revealed in the TJI rig for the first time. Initially, a primary ignition kernel is formed at a downstream location which eventually detaches from the main jet. As the jet momentum decreases, a secondary ignition event follows, this time at a more upstream location which eventually combines with the primary ignition kernel to form a single connected flame front. Investigation of these ignition sequences in chemical composition space reveal distinct differences between the two. The primary ignition event in the main-chamber is followed by a large concentration of active radicals from the pre-chamber jet, accelerating the chain-branching steps, characterizing what has been referred to as flame ignition. In contrast, the secondary ignition occurs in the absence of active radicals in the pre-chamber jet, hence characterized as jet ignition. Further analysis of the effect of pre-chamber jet characteristics on lean ignition in the main-chamber is conducted by setting up cases with different initial pressure ratios (por) between the two chambers, a non-dimensional parameter, ranging from 1.2 to 3.2. As the initial pressure ratio increases, jet momentum increases, with dual ignition observed in cases above por= 2.2. Case with por= 3.2 lead to misfiring. The effect of ignition sequence on global combustion characteristics of TJI is analyzed. Dual ignition events lead to non-monotonicity in combustion characteristics such as global reaction progress variable, flame penetration, and global heat release rate. In dual ignition events, although the rate of fuel consumption and global heat release rate is initially lower, the secondary ignition leads to a sudden increase in flame surface area, resulting in a sudden jump and promoting the overall performance of the TJI system.

42 ENGINEERING↗

Collapses of stellar protogalaxies from aspheric initial conditions

Numerical experimens are presented which were intended to verify the independence of bar formation in rotating galaxy models from special initial conditions. Three-dimensional n-body programs were run starting from aspherical initial conditions characterized by particle rotational and peculiar velocities and offsets from sphericity for a set of 100,000 particles. All the initial configurations examined are observed to collapse to a thin form, overshoot, collapse again and again overshoot, with diameters and central densities similar to those observed under spheric initial conditions. Every aspheric collapse is also found to result in bar formation within two rotation periods, which is even sooner than in initially spherical conditions. In the intermediate stages of collapse, transient sheet patterns are found to be destroyed at asymmetries of 2-3%, while transient rings survived asymmetries of 6-7% but not 15-18%. It is noted that the results may be applicable to galaxy formation in the early universe, and possible mechanisms for the arresting of protogalactic collapse are indicated.

Miller, R. H.↗

Numerical simulations of the Los Alamos gapstick experiment

The gapstick is a high explosive (HE) sensitivity test recently developed at Los Alamos. The experiment design was motivated by the traditional gap test and consists of a series of HE and inert pellets in a rate stick configuration. The inert pellets are made increasingly longer so that eventually the attenuated shock is unable to initiate the next HE pellet. While the gapstick is a mechanically simple experiment it poses several challenges for numerical simulation. In particular, accurately modeling the HE initiation and detonation phenomena requires a reactive burn model with sufficient mesh resolution to capture the reaction scales. In this work, the Scaled Uniform Reactive Front (SURF) and Arrhenius Wescott-Stewart-Davis (AWSD) burn models are used for simulations of a PBX 9501 (95 wt% HMX, 5% binder) gapstick. Furthermore, the material model for the inert pellet material, Polyvinylidene Fluoride (PVDF), has a direct influence on the shock propagation and a new equation of state (EOS) calibration for PVDF is developed using available Hugoniot data. Despite some challenges, the simulations are able to reasonably predict shock transit velocities and detonation failure in the gapstick.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Skewness in large-scale structure and non-Gaussian initial conditions

We compute the skewness of the galaxy distribution arising from the nonlinear evolution of arbitrary non-Gaussian intial conditions to second order in perturbation theory including the effects of nonlinear biasing. The result contains a term identical to that for a Gaussian initial distribution plus terms which depend on the skewness and kurtosis of the initial conditions. The results are model dependent; we present calculations for several toy models. At late times, the leading contribution from the initial skewness decays away relative to the other terms and becomes increasingly unimportant, but the contribution from initial kurtosis, previously overlooked, has the same time dependence as the Gaussian terms. Observations of a linear dependence of the normalized skewness on the rms density fluctuation therefore do not necessarily rule out initially non-Gaussian models. We also show that with non-Gaussian initial conditions the first correction to linear theory for the mean square density fluctuation is larger than for Gaussian models.

Fry, J. N.↗

Technical Report on Waveform Fit Metrics for Global Models

The new WAVEFORMS Initiative in the Ground-based Nuclear Detonation Detection (GNDD) program includes an increased emphasis on the development of Earth models and methods to predict entire seismic and acoustic waveforms more accurately. In general, this increased emphasis is predicated on the need to better characterize seismic events and provide improved model-based discrimination between event types including earthquakes and explosions. More specifically, while current moment tensor inversion methods tend to work well for larger events (M>~4) using tuned 1-D Earth models, the development of state-of-the-art 3-D models and methods is required for the prediction of shorter period waves over large areas for discrimination of smaller events. There is no standard metric for model-based waveform prediction accuracy used in the waveform modeling/inversion community. However, there are several popular waveform misfit definitions; and minimizing the corresponding objective functions is the goal of waveform inversion. Some example misfit definitions employed for adjoint waveform tomography include measures of simple travel time differences (e.g. Tape et al., 2010), cross-correlation travel time differences (e.g. Luo and Schuster, 1991), multi-taper frequency dependent methods (e.g. Lei et al., 2020), time-frequency phase misfit functions (e.g. Fichtner 2010; Rodgers et al., 2022), normalized cross-correlation methods (e.g. Tao et al., 2018), and others. In some cases, these misfit definitions also involve complicated weighting schemes and summations over multiple frequency bands making it difficult to duplicate the misfit measurement with alternative models and datasets. Although each of the misfit definitions mentioned above are useful for developing waveform models, the actual misfit values are not usually meaningful outside of a given project, model, and/or dataset. Therefore, it is difficult to understand and communicate model performance for predicting waveforms and comparing to other models and/or new model iterations with a different dataset. Therefore, there is a need for a generalized method for evaluating overall model performance that is independent from the specific misfit chosen to develop the waveform models that is also intuitive and meaningful. In this report, we describe a new metric we refer to as ‘Percent of Correlated Signal’. The following sections describe and demonstrate the metric with a case study event and a more rigorous test using a random selection of globally distributed events. While the focus here is on global tomography models, the metric is meant to applicable to regional ‘wiggle-for-wiggle’ waveform models/studies as well.

58 GEOSCIENCES↗

Data from: "Towards CONUS-Wide ML-Augmented Conceptually-Interpretable Modeling of Catchment-Scale Precipitation-Storage-Runoff Dynamics"

This data package was generated to support the manuscript “Towards CONUS-Wide Machine Learning-Augmented Conceptually Interpretable Modeling of Catchment-Scale Precipitation-Storage-Runoff Dynamics.” It provides input files, model outputs, plotting data, scripts, notebooks, and documentation used to develop, evaluate, and reproduce Mass-Conserving Perceptron (MCP)-based hydrologic modeling experiments across 513 selected Catchment Attributes and Meteorology for Large-sample Studies in the United States (CAMELS-US) basins. The files are organized by modeling component and analysis purpose, including rainfall–runoff experiments, snow module experiments, coupled hydrologic-snow experiments, Long Short-Term Memory (LSTM) benchmark results, model skill metrics, initialization and epoch records, cell-state normalization files, Akaike Information Criterion (AIC)-based model comparison files, and data used to generate manuscript figures. Tabular files can be opened using standard spreadsheet software or Python/R data-analysis tools. Python scripts, Jupyter notebooks, and selected MATLAB scripts are included for model execution, postprocessing, plotting, and statistical analysis. Quality assurance and quality control were conducted through the source-data selection and modeling workflow. Meteorological forcing, streamflow, and static catchment attributes were derived from the CAMELS-US dataset, and snow water equivalent data were derived from the University of Arizona (UA) Snow Water Equivalent dataset. Selected basins and time periods were screened during the associated research workflow to avoid missing observations or poor-quality cases. Static geospatial features were processed primarily using Quantum Geographic Information System (QGIS) and Geospatial Data Abstraction Library (GDAL) workflows. Additional details are provided in the associated manuscript and documentation.

ESS-DIVE CSV File Formatting Guidelines Reporting ↗

gcamfaostat: An R package to prepare, process, and synthesize FAOSTAT data for global agroeconomic and multisector dynamic modeling

The gcamfaostat R package is designed for the preparation, processing, and synthesis of the Food and Agriculture Organization (FAO) Statistics (FAOSTAT) agroeconomic data. The primary purpose is to facilitate FAOSTAT data use in global economic and multisector dynamic models while ensuring transparency, traceability, and reproducibility. Here, we provide an overview of the development of gcamfaostat (v1.0) and demonstrate its capabilities in generating and maintaining agroeconomic data required for the Global Change Analysis Model (GCAM). Our initiative seeks to enhance the quality and accessibility of data for the global agroeconomic modeling community, with the aim of fostering more robust and harmonized outcomes in a collaborative, efficient, and open-source framework. One of the important features of the package is the possibility to construct the FAO Food Balance Sheets at the disaggregated commodity level (with over 500 commodities), which provides a comprehensive and detailed data input for a variety of analytical and modeling applications. The processed data and visualizations offered by gcamfaostat can also be valuable to a broader audience interested in gaining insights into the intricacies of global agriculture.

97 MATHEMATICS AND COMPUTING↗

Protein folding, protein structure and the origin of life: Theoretical methods and solutions of dynamical problems

Theoretical methods and solutions of the dynamics of protein folding, protein aggregation, protein structure, and the origin of life are discussed. The elements of a dynamic model representing the initial stages of protein folding are presented. The calculation and experimental determination of the model parameters are discussed. The use of computer simulation for modeling protein folding is considered.

Weaver, D. L.↗