As a response to the Geospace Environment modeling (GEM) Global Radiation Belt modeling Challenge, a 3d diffusion model is used to simulate the radiation belt electron dynamics during two intervals of the Combined Rel...
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As a response to the Geospace Environment modeling (GEM) Global Radiation Belt modeling Challenge, a 3d diffusion model is used to simulate the radiation belt electron dynamics during two intervals of the Combined Release and Radiation Effects Satellite (CRRES) mission, 15 August to 15 October 1990 and 1 February to 31 July 1991. The 3d diffusion model, developed as part of the dynamic Radiation Environment Assimilation model (dREAM) project, includes radial, pitch angle, and momentum diffusion and mixed pitch angle-momentum diffusion, which are driven by dynamic wave databases from the statistical CRRES wave data, including plasmaspheric hiss, lower-band, and upper-band chorus. By comparing the dREAM3dmodel outputs to the CRRES electron phase space density (PSd) data, we find that, with a data-driven boundary condition at L-max=5.5, the electron enhancements can generally be explained by radial diffusion, though additional local heating from chorus waves is required. Because the PSd reductions are included in the boundary condition at L-max=5.5, our model captures the fast electron dropouts over a large L range, producing better model performance compared to previous published results. Plasmaspheric hiss produces electron losses inside the plasmasphere, but the model still sometimes overestimates the PSd there. Test simulations using reduced radial diffusion coefficients or increased pitch angle diffusion coefficients inside the plasmasphere suggest that better wave models and more realistic radial diffusion coefficients, both inside and outside the plasmasphere, are needed to improve the model performance. Statistically, the results show that, with the data-driven outer boundary condition, including radial diffusion and plasmaspheric hiss is sufficient to model the electrons during geomagnetically quiet times, but to best capture the radiation belt variations during active times, pitch angle and momentum diffusion from chorus waves are required.
3d Reconstruction Using Images has made strides in small-scale, uncomplicated scenes but struggles with complex, large-scale architectural forms. Targeting early-stage architectural design, we introduce Archidiff, a p...
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3d Reconstruction Using Images has made strides in small-scale, uncomplicated scenes but struggles with complex, large-scale architectural forms. Targeting early-stage architectural design, we introduce Archidiff, a platform for 3d architectural form generation and editing from images to point clouds. First, we curated a dataset specifically tailored for architectural design, ArchiCloudNet. Second, we proposed a 3d generation method using a conditional denoising diffusionmodel, with an arbitrary object segmentation model to enhance recognition capabilities in complex input. Finally, we incorporate an interactive feature enabling instantaneous 2d image editing through simple drag-and-drops with simultaneous updates to 3d forms, giving designers improved control. We evaluated Archidiff's generation accuracy against cutting-edge baselines on ArchiCloudNet and two other datasets, RealCity3d and BuildingNet. We also validated it with real sketches from early-stage architectural design. The experiments indicated that our model could generate accurate architectural point clouds, providing rapid-response modification and effective processing of complex backgrounds. demostration: http://39.101.72 .109:3000/archidiff.
We present PointInfinity, an efficient family of point clouddiffusionmodels. Our core idea is to use a transformer-based architecture with a fixed-size, resolution-invariant latent representation. This enables effic...
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ISBN:
(纸本)9798350353006
We present PointInfinity, an efficient family of point clouddiffusionmodels. Our core idea is to use a transformer-based architecture with a fixed-size, resolution-invariant latent representation. This enables efficient training with low-resolution point clouds, while allowing high-resolution point clouds to be generatedduring inference. More importantly, we show that scaling the test-time resolution beyond the training resolution improves the fidelity of generated point clouds and surfaces. We analyze this phenomenon anddraw a link to classifier-free guidance commonly used in diffusionmodels, demonstrating that both allow trading off fidelity and variability during inference. Experiments on CO3d show that PointInfinity can efficiently generate high-resolution point clouds (up to 131k points, 31 more than Point-E) with state-of-the-art quality.
3d Gaussian Splatting (3dGS) can achieve higher-quality novel view synthesis (NVS) results in a relatively short period of time. Nevertheless, when sampling rates are not aligned with the camera track, unreal artifact...
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ISBN:
(纸本)9798350377859;9798350377842
3d Gaussian Splatting (3dGS) can achieve higher-quality novel view synthesis (NVS) results in a relatively short period of time. Nevertheless, when sampling rates are not aligned with the camera track, unreal artifacts that are not part of the view often emerge, including floaters. This phenomenon has a significant impact on the quality of the reconstruction results. Furthermore, existing regularization methods are ineffective in terms of both inference speed and optimization. Accordingly, this study proposes the elimination of unrealistic artifacts in 3d Gaussian Splatting (3dGS-Hd), a scene optimization method based on the 3d diffusion model. This method optimizes the adaptive density mechanism by deeply understanding the local structural characteristics of the reconstructed objects, removes unrealistic artifacts, and significantly improves the reconstruction quality. Furthermore, it ensures consistency between 2d and3d views. The results of the experiments demonstrate that this method produces notable improvements in optimization, particularly in the context of object-level reconstruction tasks.
Leading resist calibration for sub-0.3 k(1) lithography demands accuracy 0.8) imaging characteristics, customized illuminations (measured vs. modeled pupil profiles), resolution enhancement technology (RET) mask with...
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ISBN:
(纸本)0819458538
Leading resist calibration for sub-0.3 k(1) lithography demands accuracy < 2nm for Cd through pitch. An accurately calibrated resist process is the prerequisite for establishing production-worthy manufacturing under extreme low k(1). From an integrated imaging point of view, the following key components must be simultaneously consideredduring the calibration - high numerical aperture (NA > 0.8) imaging characteristics, customized illuminations (measured vs. modeled pupil profiles), resolution enhancement technology (RET) mask with OPC, reticle metrology, and resist thin film substrate. For imaging at NA approaching unity, polarized illumination can impact significantly the contrast formation in the resist film stack, and therefore it is an important factor to consider in the Cd-based resist calibration. For aggressive dRAM memory core designs at k(1)< 0.3, pattern-specific illumination optimization has proven to be critical for achieving the required imaging performance. Various optimization techniques from source profile optimization with fixed mask design to the combined source and mask optimization have been considered for customer designs and available imaging capabilities. For successful low-k(1) process development, verification of the optimization results can only be made with a sufficiently tunable resist. model that can predicate the wafer printing accurately under various optimized process settings. We have developed, for resist patterning under aggressive low-k(1) conditions, a novel 3d diffusion model equipped with double-Gaussian convolution in each dimension. Resist calibration with the new diffusionmodel has demonstrated a fitness and Cd predication accuracy that rival or outperform the traditional 3d physical resist models. In this work, we describe our empirical approach to achieving the nm-scale precision for advanced lithography process calibrations, using either measured Id Cd through-pitch or 2d memory core patterns. We show that for ArF imagi
Because the CO gas is usually used as the reduction gas in the blast furnace process, a huge CO2 gas has been emittedduring the ironmaking process. Therefore, H-2 reduction gas has been proposed as a potential altern...
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Because the CO gas is usually used as the reduction gas in the blast furnace process, a huge CO2 gas has been emittedduring the ironmaking process. Therefore, H-2 reduction gas has been proposed as a potential alternative to the CO gas for achieving carbon neutrality. However, the diffusion behaviors of CO and H-2 gases inside the iron-oxide particle are markedly different due to the higher gas diffusivity of H-2 gas. The reaction surface is observed in the CO reduction whereas the H-2 reduction has a broadly-reaction area. The conventional reduction analysis models were suitable for use in the CO reduction, as they assumed an exponential gas diffusion behavior through the certain reaction surface inside the particle. However, exponential diffusion is not sufficient to analyze the broaddiffusion aspect of H-2 gas. In this study, the H-2-based reduction reactions is applied to the 3d diffusion model, which can accurately analyze the broad H-2 diffusion behavior. The gas components considered were the CO-CO2-H-2-H2O-N-2, considering the conditions of the blast furnace. The necessity of the 3d diffusion model was analyzed by comparing the H-2 reduction distributions with those obtained using the shrinking core model. The intra-particle distribution for reducing iron oxide particles, which have pellet and sintered ore shapes, were analyzed in CO-H-2 and CO-CO2-H-2-H2O-N-2 gas to clarify the impact of H-2 on reduction behavior. As the results, the presence of H-2 gas affected the effective gas diffusivity of the gas mixture, the reduction rate increased with the H-2 content.
The production of steel, which is achieved by the reduction of iron ores mainly through indirect reduction reactions in a blast furnace, is gradually increasing worldwide. Because the reducing gas diffuses threedimens...
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The production of steel, which is achieved by the reduction of iron ores mainly through indirect reduction reactions in a blast furnace, is gradually increasing worldwide. Because the reducing gas diffuses threedimensionally, irregular particle shapes influence the reduction through differences in the diffusion length. The analysis of actual irregularly shaped iron-ore particles using existing models is difficult because they are primarily effective for 1d systems. Therefore, a novel reduction model based on the 3ddiffusion equation that accommodates irregular particle shapes and3d systems was developed in this study. The establishedmodel was validated by reproducing experimental conditions and comparing the quantified effective diffusivity and chemical reaction rate constant using the shrinking core model. In addition, the model was used to investigate the reducing behavior of an actual sintered-ore particle and the effects of particle sphericity and macro pore content. The sintered-ore particle had a higher reduction rate than that of a spherical equivalent with the same volume because sections of the surface with shorter diffusion lengths facilitated the gas diffusion. Additionally, the particle sphericity was determined to be inversely proportional to the reduction rate because the rate of gas diffusion into the particle
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