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At least 55 records · Page 3

Verilog-A Device Models for Cryogenic Temperature Operation of Bulk Silicon CMOS Devices

Verilog-A based cryogenic bulk CMOS (complementary metal oxide semiconductor) compact models are built for state-of-the-art silicon CMOS processes. These models accurately predict device operation at cryogenic temperatures down to 4 K. The models are compatible with commercial circuit simulators. The models extend the standard BSIM4 [Berkeley Short-channel IGFET (insulated-gate field-effect transistor ) Model] type compact models by re-parameterizing existing equations, as well as adding new equations that capture the physics of device operation at cryogenic temperatures. These models will allow circuit designers to create optimized, reliable, and robust circuits operating at cryogenic temperatures.

Akturk, Akin↗

Structural Analysis of the Right Rear Lug of American Airlines Flight 587

A detailed finite element analysis of the right rear lug of the American Airlines Flight 587 - Airbus A300-600R was performed as part of the National Transportation Safety Board s failure investigation of the accident that occurred on November 12, 2001. The loads experienced by the right rear lug are evaluated using global models of the vertical tail, local models near the right rear lug, and a global-local analysis procedure. The right rear lug was analyzed using two modeling approaches. In the first approach, solid-shell type modeling is used, and in the second approach, layered-shell type modeling is used. The solid-shell and the layered-shell modeling approaches were used in progressive failure analyses (PFA) to determine the load, mode, and location of failure in the right rear lug under loading representative of an Airbus certification test conducted in 1985 (the 1985-certification test). Both analyses were in excellent agreement with each other on the predicted failure loads, failure mode, and location of failure. The solid-shell type modeling was then used to analyze both a subcomponent test conducted by Airbus in 2003 (the 2003-subcomponent test) and the accident condition. Excellent agreement was observed between the analyses and the observed failures in both cases. The moment, Mx (moment about the fuselage longitudinal axis), has significant effect on the failure load of the lugs. Higher absolute values of Mx give lower failure loads. The predicted load, mode, and location of the failure of the 1985- certification test, 2003-subcomponent test, and the accident condition are in very good agreement. This agreement suggests that the 1985-certification and 2003-subcomponent tests represent the accident condition accurately. The failure mode of the right rear lug for the 1985-certification test, 2003-subcomponent test, and the accident load case is identified as a cleavage-type failure. For the accident case, the predicted failure load for the right rear lug from the PFA is greater than 1.98 times the limit load of the lugs.

Raju, Ivatury S.↗

NASA Structural Analysis Report on the American Airlines Flight 587 Accident - Local Analysis of the Right Rear Lug

A detailed finite element analysis of the right rear lug of the American Airlines Flight 587 - Airbus A300-600R was performed as part of the National Transportation Safety Board s failure investigation of the accident that occurred on November 12, 2001. The loads experienced by the right rear lug are evaluated using global models of the vertical tail, local models near the right rear lug, and a global-local analysis procedure. The right rear lug was analyzed using two modeling approaches. In the first approach, solid-shell type modeling is used, and in the second approach, layered-shell type modeling is used. The solid-shell and the layered-shell modeling approaches were used in progressive failure analyses (PFA) to determine the load, mode, and location of failure in the right rear lug under loading representative of an Airbus certification test conducted in 1985 (the 1985-certification test). Both analyses were in excellent agreement with each other on the predicted failure loads, failure mode, and location of failure. The solid-shell type modeling was then used to analyze both a subcomponent test conducted by Airbus in 2003 (the 2003-subcomponent test) and the accident condition. Excellent agreement was observed between the analyses and the observed failures in both cases. From the analyses conducted and presented in this paper, the following conclusions were drawn. The moment, Mx (moment about the fuselage longitudinal axis), has significant effect on the failure load of the lugs. Higher absolute values of Mx give lower failure loads. The predicted load, mode, and location of the failure of the 1985-certification test, 2003-subcomponent test, and the accident condition are in very good agreement. This agreement suggests that the 1985-certification and 2003- subcomponent tests represent the accident condition accurately. The failure mode of the right rear lug for the 1985-certification test, 2003-subcomponent test, and the accident load case is identified as a cleavage-type failure. For the accident case, the predicted failure load for the right rear lug from the PFA is greater than 1.98 times the limit load of the lugs. I.

Raju, Ivatury S↗

Comparison of linear regression, k-nearest neighbour and random forest methods in airborne laser-scanning-based prediction of growing stock

Abstract In this study, for five sites around the world, we look at the effects of different model types and variable selection approaches on forest yield modelling performances in an area-based approach (ABA). We compared ordinary least squares regression (OLS), k-nearest neighbours (kNN) and random forest (RF). Our objective was to test if there are systematic differences in accuracy between OLS, kNN and RF in ABA predictions of growing stock volume. The analyses are based on a 5-fold cross-validation at five study sites: an eucalyptus plantation, a temperate forest and three different boreal forests. Two completely independent validation datasets were also available for two of the boreal sites. For the kNN, we evaluated multiple measures of distance including Euclidean, Mahalanobis, most similar neighbour (MSN) and an RF-based distance metric. The variable selection approaches we examined included a heuristic approach (for OLS, kNN and RF), exhaustive search among all combinations (OLS only) and all variables together (RF only). Performances varied by model type and variable selection approaches among sites. OLS and RF had similar accuracies and were more efficient than any of the kNN variants. Variable selection did not affect RF performance. Heuristic and exhaustive variable selection performed similarly for OLS. kNN fared the poorest amongst model types, and kNN with RF distance was prone to overfitting when compared with a validation dataset. Additional caution is therefore required when building kNN models for volume prediction though ABA, being preferable instead to opt for models based on OLS with some variable selection, or RF with all variables together.

Cosenza, Diogo N.↗

Phenomenology and cosmology of no-scale attractor models of inflation

We have recently proposed attractor models for modulus fixing, inflation, supersymmetry breaking and dark energy based on no-scale supergravity. In this paper we develop phenomenological and cosmological aspects of these no-scale attractor models that underpin their physical applications. We consider models in which inflation is driven by a modulus field (T-type) with supersymmetry broken by a Polonyi field, or a matter field (φ-type) with supersymmetry broken by the modulus field. We derive the possible patterns of soft supersymmetry-breaking terms, which depend in T-type models whether the Polonyi and/or matter fields are twisted or not, and in φ-type models on whether the inflaton and/or other matter fields are twisted or not. In φ-type models, we are able to directly relate the scale of supersymmetry breaking to the inflaton mass. We also discuss cosmological constraints from entropy considerations and the density of dark matter on the mechanism for stabilizing the modulus field via higher-order terms in the no-scale K¨ahler potential.

79 ASTRONOMY AND ASTROPHYSICS↗

Safety Analysis Report for Packagings – Model 9979 Type AF Shipping Package

This Safety Analysis Report for Packaging (SARP) documents the performance of the Department of Energy (DOE) Model USA/9979/AF-96 shipping package and compliance with the regulatory safety requirements of Title 10 and Title 49 of the Code of Federal Regulations. The SARP is prepared in accordance with U.S. Department of Energy (DOE) Order 460.1D. The Model 9979 Type A Fissile shipping package replaces the Department of Transportation (DOT) UN1A2 Specification Packaging. Formerly, the UN1A2 was authorized under Title 49 of the Code of Federal Regulations, Section 173.417 (2004) for transport of Type A quantities of fissile material over public highways. In accordance with the Federal Register, final rule making issued on January 26, 2004, the Nuclear Regulatory Commission, in a joint effort with the Department of Transportation, initiated a planned phase out of multiple Specification Packagings from 49 CFR 173, the UN1A2 being one. The rulemaking mandated, by law, removal of these specification packagings from service no later than September 30, 2008. The 9979 is a Performance Packaging and replaces the UN1A2 Specification Packaging. The Packaging Technology and Transportation Engineering (PT&TE) organization of the Savannah River National Laboratory (SRNL) is the Design Authority and Design Agency for the 9979.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

A 1D–0D–3D coupled model for simulating blood flow and transport processes in breast tissue

In this work, we present mixed dimensional models for simulating blood flow and transport processes in breast tissue and the vascular tree supplying it. These processes are considered, to start from the aortic inlet to the capillaries and tissue of the breast. Large variations in biophysical properties and flow conditions exist in this system necessitating the use of different flow models for different geometries and flow regimes. In total, we consider four different model types. First, a system of 1D nonlinear hyperbolic partial differential equations (PDEs) is considered to simulate blood flow in larger arteries with highly elastic vessel walls. Second, we assign 1D linearized hyperbolic PDEs to model the smaller arteries with stiffer vessel walls. The third model type consists of ODE systems (0D models). It is used to model the arterioles and peripheral circulation. Finally, homogenized 3D porous media models are considered to simulate flow and transport in capillaries and tissue within the breast volume. Sink terms are used to account for the influence of the venous and lymphatic systems. Combining the four model types, we obtain two different 1D–0D–3D coupled models for simulating blood flow and transport processes: The first model results in a fully coupled 1D–0D–3D model covering the complete path from the aorta to the breast combining a generic arterial network with a patient specific breast network and geometry. The second model is a reduced one based on the separation of the generic and patient specific parts. The information from a calibrated fully coupled model is used as inflow condition for the patient specific sub-model allowing a significant computational cost reduction. Several numerical experiments are conducted to calibrate the generic model parameters and to demonstrate realistic flow simulations compared to existing data on blood flow in the human breast and vascular system. Moreover, we use two different breast vasculature and tissue data sets to illustrate the robustness of our reduced sub-model approach.

multiscale blood flow models↗

Accreting white dwarf models for type 1 supernovae. 1: Presupernova evolution and triggering mechanisms

As a plausible explosion model for a Type I supernova, the evolution of carbon-oxygen white dwarfs accreting helium in binary systems was investigated from the onset of accretion up to the point at which a thermonuclear explosion occurs. The relationship between the conditions in the binary system and the triggering mechanism for the supernova explosion is discussed, especially for the cases with relatively slow accretion rate. It is found that the growth of a helium zone on the carbon-oxygen core leads to a supernova explosion which is triggered either by the off-center helium detonation for slow and intermediate accretion rates or by the carbon deflagration for slow and rapid accretion rates. Both helium detonation and carbon deflagration are possible for the case of slow accretion, since in this case the initial mass of the white dwarf is an important parameter for determining the mode of ignition. Finally, various modes of building up the helium zone on the white dwarf, namely, direct transfer of helium from the companion star and the various types and strength of the hydrogen shell flashes are discussed in some detail.

Nomoto, K.↗

Comparison of the CEAS and Williams-type barley yield models for North Dakota and Minnesota

The CEAS and Williams type models were compared based on specified selection criteria which includes a ten year bootstrap test (1970-1979). Based on this, the models were quite comparable; however, the CEAS model was slightly better overall. The Williams type model seemed better for the 1974 estimates. Because that year spring wheat yield was particularly low, the Williams type model should not be excluded from further consideration.

Leduc, S.↗

Legacy Survey of Space and Time Data Preview 2: object_scarlet_models dataset type

We present Rubin Data Preview 2 (DP2), the second data preview from the NDF-DOE Vera C. Rubin Observatory. Data Preview 2 (DP2) comprises coadds, detection catalogs, and ancillary data products; and when fully released will also include single-epoch images and difference images. DP2 is derived from observations acquired by the LSST Science Camera (LSSTCam) on the Simonyi Survey Telescope at the Summit Facility on Cerro Pachón, Chile, primarily during the on-sky commissioning campaign between 2025-04-16 and 2025-09-21, supplemented by observations taken between 2025-10-25 and 2026-01-06 that overlap the commissioning footprint. The DP2 footprint comprises the Science Validation wide-area survey, five Deep Drilling Fields, and a number of targeted small-field regions, including Trifid and Lagoon, Prawn, M49, and New Horizons, all observed as part of the Rubin First Look campaign. Each field was imaged in up to six broad photometric bands, ugrizy, and coadded to produce deep imaging covering an estimated 3,000 deg2. The addition of single-visit-only areas expands the total DP2 footprint to an estimated 15,000 deg2, with coverage in at least one filter. The median per-visit PSF FWHM across the wide-area survey ranges from 1.17 arcsec in the z band to 1.26 arcsec in g and r bands. The deepest field, reaches estimated coadded 5σ depths of u=26 mag, g=26.8 mag, r=26.3 mag, i=26.1 mag, z=25.3 mag, y=23.9 mag. Based on a roughly five-month primary observing baseline and covering only part of the eventual LSST footprint, DP2's area, depth, and multiband coverage nonetheless support a broad range of early science investigations ahead of LSST Data Release This dataset is a subset of the full data release consisting of the object_scarlet_models dataset type. These are scarlet deblender models for detected sources in the deep coadds. This release contains 195,366 datasets of this type.

79 ASTRONOMY AND ASTROPHYSICS↗

Regional and Model-Specific Response Types in A Global Gridded Crop Model Ensemble

Crop models are often employed to project crop yields under changing conditions such as global warming and associated management change for adaptation. Multi-model ensembles are promoted to enhance the robustness of projections, but questions remain on what causes often large differences between projections of individual models. Global Gridded Crop Models (GGCMs) are especially exposed to this question when applied for assessing climate change impacts, adaptation, environmental impacts of agricultural production, because their results are used in downstream analyses, such as in integrated assessment or economic modeling for projecting future land-use change. Even though global gridded crop models are often based on detailed field-scale models or have implemented similar modeling principles in other ecosystem models, global-scale models are subject to substantial uncertainties from both model structure and parametrization as well as from calibration and input data quality. AgMIP’s Global Gridded Crop Model Intercomparison (GGCMI) has thus set out to intercompare GGCMs in order to evaluate model performance, describe model uncertainties, identify inconsistencies within the ensemble and underlying reasons, and to ultimately improve models and modeling capacities. In phase 2 of the GGCMI activities, 12 modeling groups followed a modeling protocol that asked for up to 1404 31-year global simulations at 0.5 arc-degree spatial resolution to assess models’ sensitivities to changes in carbon dioxide (C; 4 different levels) temperature (T; 7 different offset levels), water supply (W; 9 levels), and nitrogen (N; 3 levels), the so-called CTWN experiment (Franke et al. 2020; http://dx.doi.org/10.5194/gmd-13-2315-2020). We here present analyses of model response types using impact response surfaces along the C, T, W, and N dimensions, respectively and collectively. Doing so, we can understand differences in simulated responses per driver rather than aggregated changes in yields. We find that models’ sensitivities to the individual driver dimensions are substantially different and often more different across models than across regions. A cluster analysis finds regional and model-specific patterns. There is some agreement across models with respect to the spatial patterns of response types but strong differences in the distribution of response type clusters across models suggests that models need to undergo further scrutiny. We suggest establishing standards in model process evaluation not only against historical dynamics but also against dedicated experiments across the CTWN dimensions.

crop models↗

Workforce planning: a review of methodologies

Workforce planning deals with determining the number of employees and associated skills necessary to meet the future operational needs of an organization. A workforce system consists of six elements: recruitment, attrition, promotion, training, retention, and scheduling. Historically, several workforce modeling and analysis methodologies have been developed to capture these elements. This paper reviews the results of workforce and manpower models published within peer-reviewed literature between 1959 and 2021 to provide an in-depth analysis of current models. The focus of this review is on analytical, simulation, and empirical models found in literature that were collected based on a citation requirement and keyword search criteria. Results demonstrate the trends in workforce modeling research and discuss the common uses of each model type and the advantages/disadvantages related to each model. Based on the common attributes of workforce systems, the discussion focuses on the most frequently used model type for each element and the best use for each model. Lastly, recommendations are made for the development of workforce models that allow the most comprehensive view of the workforce systems of the future.

42 ENGINEERING↗

Models for Type I supernovae

Two somewhat disjoint scenarios for Type I supernovae are presented. One scenario is based on mass accretion by a white dwarf in a binary system, while the other involves a star of 8 to 10 solar masses which may or may not be a solitary star. In spite of the apparent dissimilarities of the two models, it may be that each occurs to some extent in nature, for they both share the possibility of producing substantial quantities of Ni-56 and explosions in stars devoid of hydrogen envelopes. It is concluded that these are two properties that must be shared by any viable Type I model.

Woosley, S. E.↗

Late-time spectra and type Ia supernova models: New clues from the Hubble Space Telescope

Calculated late-time spectra of two classical hydrodynamical models for Type Ia supernovae (deflagration model W7 of Nomoto, Thielemann, & Yokoi, and delayed detonation model DD4 of Woosley & Weaver) are compared with observations of SN 1992A and other spectroscopically normal SNe Ia. An important new piece of information is provided by observations done with the Hubble Space Telescope (HST) which cover the ultraviolet range at the nebular phase of a SN Ia: SN 1992A in NGC 1380. For the first time a picture of SN Ia emission from the ultraviolet through the optical is obtained at these phases. Predictions of the classical model (W7 and DD4) are compared with the observed spectrum of SN 1992A and with the optical spectra of SN 1989M in NGC 4579 and SN 1990N in NGC 4639 at similar epochs. The absolute B and V magnitudes of the models are also estimated at these late phases. Taken at face value the nebular spectra of these 'classical' models are more consistent with the long extragalactic distance scale, pointing to distances to NGC 4579 around 21 +/- 3 Mpc and a slightly larger distance, 22 +/- 3 Mpc, to NGC 4639, on the back side of the Virgo Cluster. However, the calculated Fe(+3) luminosity as predicted from the models exceeds the observed limit from the HST data of SN 1992A. Other differences in the ratios of the line intensities between calculated and observed spectra, show some disagreement with the observed spectra at the nebular phases. They may not be the best choice for spectroscopically normal SNe Ia, and their use as an independent calibration of the extragalactic distance scale should be viewed with caution.

Ruiz-Lapuente, P.↗

Detection of Diversion in a Realistic Heat Pipe Microreactor Using Supervised Machine Learning

Microreactors (MRs) pose new challenges for international safeguards. Here, their small size and mass reproducibility make them ideal for deployment in greater numbers and in remote locations, making the job of safeguards inspectors more challenging. Machine learning (ML) is currently being applied to many fields to augment human performance and increase automation; in particular, ML could be used to provide insight for international inspectors to help detect the diversion of nuclear fuel from MR cores. Four ML model types (k-nearest neighbors, decision tree, random forest, and histogram-based gradient boosted ensemble) were trained on integrated flux and critical control drum angle data generated with Serpent 2 for a realistic heat pipe MR design, achieving nearly 100% binary classification accuracy of nominal and diversion core configurations by the end of 1 full power year for three of the four model types. Regression model variants were also trained, using the same input data, for predicting the number of fuel pins diverted. Root-mean-square errors below 5% of the total number of fuel pins were achieved by the 1 full power year mark for all models.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗