SEARCH · Engineering Papers
Results for “Model initialization”
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Application of Townsend avalanche theory to tokamak startup by coaxial helicity injection
Townsend avalanche theory is employed to model and interpret plasma initiation in NSTX by Ohmic heating and coaxial helicity injection (CHI). The model is informed by spatially resolved vacuum calculations of electric field and magnetic field line connection length in the poloidal cross-section. The modelis shown to explain observations of Ohmic startup including the duration andlocation of breakdown. Adapting the model to discharges initiated by CHI offers insight into the causes of upper divertor (absorber) arcs in cases where the discharge fails to initiate in the lower divertor gap. Finally, upper and lower limits are established for vessel gas fill based on requirements for breakdown and radiation. It is predicted that CHI experiments on NSTX-U should beable to use as much as four times the amount of prefill gas employed in CHI experiments in NSTX. This should provide greater flexibility for plasma start-up, as the injector flux is projected to be increased in NSTX-U.
Toward particle accelerator machine state embeddings as a modality for large language models
Understanding and diagnosing the state of a particle accelerator requires navigating high-dimensional control system data, often involving hundreds of interdependent parameters. We propose a novel multimodal embedding framework that jointly learns representations of machine states from both numerical control system readouts and natural language descriptions. This enables the translation of complex machine conditions into human-readable summaries while maintaining fidelity to the underlying physical system. The obtained embeddings are subsequently adapted to an open-weights large language model via cross-attention conditioning. We demonstrate a first implementation trained on European XFEL machine state data. This work covers the embedding model architecture, training methodology, and presents initial examples demonstrating the model's capabilities in action. Due to the general concept of machine state, the model can be easily adapted to other facilities and control system environments.
PMIP: Looking back to its first phase
The Paleoclimate Modelling Intercomparison Project celebrates its 30th anniversary in 2021. The first phase initiated systematic model-model and model-data comparisons for the Last Glacial Maximum and Mid-Holocene. Here, we describe the historical context of PMIP, the experiment design, and the project’s early impacts.
Verification Suite for the Application of the Limiting Surface Density Method to Arrays of 9975 Packages
Criticality Safety Engineering at the Savannah River Site’s K-Area Complex seeks to reduce the computational burden of analysis for the K-Area Complex. By applying an adapted Limiting Surface Density hand calculation method, the need for lengthy detailed Monte Carlo models of the storage arrays may be reduced or eliminated. After promising initial results using models of idealized but heterogeneous packages, application of the method to large arrays of highly heterogeneous 9975 shipping packages is attempted. A SCALE KENO-VI model of the 9975 package, with true dimensions and radial and axial heterogeneity is developed. A suite of array arrangements representing both arrays with equal number of packages per side (package-cubic) and arrays with unequal number of packages per side (non-cubic) are evaluated in SCALE. The cubic arrangements are used to derive the 9975-specific material and geometry constants for the LSD method. These constants are then used to implement the LSD method and compare the LSD- predicted critical mass per package to SCALE-predicted critical mass per package. Sensitivities to certain material and geometric nuances are evaluated for inclusion in the verification suite. Finally, the ability of the method to predict neutron multiplication changes induced by fissile mass changes is examined as a segue for evaluating credible abnormal conditions with the LSD method.
Initial Evaluation of WIPP Crushed Salt Model Applied to the Triaxial Compaction Test TK-031.
Abstract not provided.
Quantifying the impact of the initial guess for projection-based model reduction of steady hypersonic aerodynamics.
Abstract not provided.
Verification suite for the application of the limiting surface density method to arrays of 9975 packages
Criticality Safety Engineering at the Savannah River Site's K-Area Complex seeks to reduce the computational burden of analysis for the K-Area Complex. By applying an adapted Limiting Surface Density hand calculation method, the need for lengthy detailed Monte Carlo models of the storage arrays may be reduced or eliminated. After promising initial results using models of idealized but heterogeneous packages, application of the method to large arrays of highly heterogeneous 9975 shipping packages is attempted. A SCALE KENO-VI model of the 9975 package, with true dimensions and radial and axial heterogeneity is developed. A suite of array arrangements representing both arrays with equal number of packages per side (package-cubic) and arrays with unequal number of packages per side (non-cubic) are evaluated in SCALE. The cubic arrangements are used to derive the 9975-specific material and geometry constants for the LSD method. These constants are then used to implement the LSD method and compare the LSD- predicted critical mass per package to SCALE-predicted critical mass per package. Sensitivities to certain material and geometric nuances are evaluated for inclusion in the verification suite. Finally, the ability of the method to predict neutron multiplication changes induced by fissile mass changes is examined as a segue for evaluating credible abnormal conditions with the LSD method. (authors)
Stellar Neutrino Emission across the Mass–Metallicity Plane
We explore neutrino emission from nonrotating, single-star models across six initial metallicities and 70 initial masses from the zero-age main sequence to the final fate. Overall, across the mass spectrum, we find metal-poor stellar models tend to have denser, hotter, and more massive cores with lower envelope opacities, larger surface luminosities, and larger effective temperatures than their metal-rich counterparts. Across the mass–metallicity plane we identify the sequence (initial CNO → 14 N → 22 Ne → 25 Mg → 26 Al → 26 Mg → 30 P → 30 Si) as making primary contributions to the neutrino luminosity at different phases of evolution. For the low-mass models we find neutrino emission from the nitrogen flash and thermal pulse phases of evolution depend strongly on the initial metallicity. For the high-mass models, neutrino emission at He-core ignition and He-shell burning depends strongly on the initial metallicity. Antineutrino emission during C, Ne, and O burning shows a strong metallicity dependence with 22 Ne(α, n) 25 Mg providing much of the neutron excess available for inverse-β decays. We integrate the stellar tracks over an initial mass function and time to investigate the neutrino emission from a simple stellar population. We find average neutrino emission from simple stellar populations to be 0.5–1.2 MeV electron neutrinos. Lower metallicity stellar populations produce slightly larger neutrino luminosities and average β decay energies. This study can provide targets for neutrino detectors from individual stars and stellar populations. We provide convenient fitting formulae and open access to the photon and neutrino tracks for more sophisticated population synthesis models.
Dislocation Density-Based Model for Flow Behavior of a Near-α Titanium Alloy Considering Effects of Initial Lamellar Thickness
A dislocation density-based constitutive model that considered the effects of initial lamellar thickness was proposed to predict the flow behavior of a near-α high-temperature Ti-5.4Al-3.7Sn-3.3Zr-0.5Mo-0.4Si alloy. The evolution equations of dislocation density were improved by introducing the influence of the dynamic globularization of lamellar microstructure with different initial thicknesses. The evolution equations and Hall-Petch behavior were coupled into the constitutive model, which was composed of athermal and thermal stresses. According to the established constitutive equations, the variation and contributions of corresponding stress components were analyzed. The calculated dislocation densities were compared with the experimental values obtained by electron backscattered diffraction data to verify the model. Moreover, the flow stresses of the studied alloy with different initial lamellar microstructures under various deformation conditions were predicted. Good agreements between the predicted and experimental results were obtained. Additionally, steady-state flow behavior was further analyzed and the relationship between the calculated steady-state flow stress and the equiaxed α-phase size was quantitatively obtained. The results indicated the validity of the proposed constitutive model for predicting the flow behavior of the alloy with different initial lamellar microstructures over a range of deformation temperatures and strain rates.
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.
LOX-related collagen crosslink changes act as an initiator of bone fragility in a ZDF rats model
Highlights: • Bone mechanical loss in type 2 diabetes is mainly restricted to the post-yield behavior. • Loss of insoluble collagen in the matrix phase is the initial cause of bone mechanical loss in type 2 diabetes. • The insoluble collagen amount in bone tissue is the positive regressor of bone post-yield behavior. • The expression of Lox and lox-like family are downregulated in bone tissue in type 2 diabetes. Diabetes mellitus type 2 (DM2) results in bone abnormalities that manifest as increased bone fragility. Bone consists of two phases, the mineral phase and the matrix phase, and disorders in both are seen in DM2. However, the phase in which DM2 mediated bone fragility is initiated is still unknown. In this study, a male Zucker diabetic fatty (fa/fa) (ZDF) rat model was used to investigate the underlying mechanism initiating DM2 mediated bone fragility. The fracture surface morphology, pre- and post-yield bone mechanical behavior, insoluble collagen volume, lysyl oxidase family (LOX) enzyme levels and correlation analysis was performed to determine the relationship between insoluble collagen and post-yield behavior. Four weeks after the induction of diabetes, insoluble collagen was decreased in only the matrix phase in diabetic rats. Consistently, mechanical testing of the bone showed changes only in post-yield behavior. Diabetic rats also had decreased levels of enzymes involved in insoluble collagen formation (LOX and LOXL1 families). Correlation analysis demonstrated that insoluble collagen was a positive regressor of post-yield displacement (R = 0.894, P P < 0.001). Together, these findings suggest that bone fragility in DM2 is initiated in the matrix phase and that the LOX family may play a critical part in the pathogenesis of DM2 mediated bone fragility.
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.
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.
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.
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.
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.