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At least 613 records · Page 34

Validating Drag and Heating Coefficients for Hollow Reentry Objects in Continuum Flow Using a Mach 7 Ludwieg Tube

Drag and heating coefficient databases and models are crucial to destructive reentry simulation. The NASA Orbital Debris Program Office (ODPO) develops, maintains, and performs analysis with the Object Reentry Survival Analysis Tool (ORSAT), which comprises drag and heating models for free molecular, transitional, and continuum flow regimes. These models have, in the past, only included solid, convex, blunt shapes (such as boxes, spheres, and cylinders). Previous work led by ODPO includes the extension of these models to hollow cylinders and square boxes in free molecular and transitional flow using the Direct Simulation Monte Carlo (DSMC) method. Since 2019, the ODPO has continued its program of DSMC simulations and extended the project to include analyses with the NASA Data Parallel Line Relaxation (DPLR) program on hollow cylinders and boxes (with varying wall thickness-diameter ratio). In fall 2022, the ODPO began a collaboration with the University of Texas San Antonio (UTSA) to use the Mach 7 Ludwieg Tube facility to validate the model built using numerical simulations. This facility can replicate (at a scale of approximately 100:1) the conditions seen by reentering objects near typical demise altitudes. We present here the drag and heating coefficients derived from the continued DSMC simulations, the new DPLR simulations, and the 26-test series at UTSA.

Chris Ostrom↗

Validating Drag and Heating Coefficients for Hollow Reentry Objects in Continuum Flow Using a Mach 7 Ludwieg Tube

Drag and heating coefficient databases and models are crucial to destructive reentry simulation. The NASA Orbital Debris Program Office (ODPO) develops, maintains, and performs analysis with the Object Reentry Survival Analysis Tool (ORSAT), which comprises drag and heating models for free molecular, transitional, and continuum flow regimes. These models have, in the past, only included solid, convex, blunt shapes (such as boxes, spheres, and cylinders). Previous work led by ODPO includes the extension of these models to hollow cylinders and square boxes in free molecular and transitional flow using the Direct Simulation Monte Carlo (DSMC) method. Since 2019, the ODPO has continued its program of DSMC simulations and extended the project to include analyses with the NASA Data Parallel Line Relaxation (DPLR) program on hollow cylinders and boxes (with varying wall thickness-diameter ratio). In fall 2022, the ODPO began a collaboration with the University of Texas San Antonio (UTSA) to use the Mach 7 Ludwieg Tube facility to validate the model built using numerical simulations. This facility can replicate (at a scale of approximately 100:1) the conditions seen by reentering objects near typical demise altitudes. We present here the drag and heating coefficients derived from the continued DSMC simulations, the new DPLR simulations, and the 26-test series at UTSA.

Chris Ostrom↗

Validation of Design and Analysis Techniques of Tailored Composite Structures

Aeroelasticity is the relationship between the elasticity of an aircraft structure and its aerodynamics. This relationship can cause instabilities such as flutter in a wing. Engineers have long studied aeroelasticity to ensure such instabilities do not become a problem within normal operating conditions. In recent decades structural tailoring has been used to take advantage of aeroelasticity. It is possible to tailor an aircraft structure to respond favorably to multiple different flight regimes such as takeoff, landing, cruise, 2-g pull up, etc. Structures can be designed so that these responses provide an aerodynamic advantage. This research investigates the ability to design and analyze tailored structures made from filamentary composites. Specifically the accuracy of tailored composite analysis must be verified if this design technique is to become feasible. To pursue this idea, a validation experiment has been performed on a small-scale filamentary composite wing box. The box is tailored such that its cover panels induce a global bend-twist coupling under an applied load. Two types of analysis were chosen for the experiment. The first is a closed form analysis based on a theoretical model of a single cell tailored box beam and the second is a finite element analysis. The predicted results are compared with the measured data to validate the analyses. The comparison of results show that the finite element analysis is capable of predicting displacements and strains to within 10% on the small-scale structure. The closed form code is consistently able to predict the wing box bending to 25% of the measured value. This error is expected due to simplifying assumptions in the closed form analysis. Differences between the closed form code representation and the wing box specimen caused large errors in the twist prediction. The closed form analysis prediction of twist has not been validated from this test.

Jegley, Dawn C.↗

Assessing the Impact of Variable Air Volume Box Damper Stuck Faults Using a Building Automation System and Building Energy Simulation Model

The study examines the impact of variable air volume (VAV) damper stuck faults on the system operation, building indoor conditions, and reheating energy consumption. This study includes both experimental and simulation studies for five test scenarios, including a fault-free scenario. We implemented VAV damper stuck fault through the building automation system (BAS). Results show that a damper stuck in a high opening position (60% damper opening) results in supplying an excessive amount of cold air from the rooftop unit (RTU) to the conditioned zone, increasing reheating energy consumption. The results of this research can serve as a foundational resource for developing fault detection algorithms.

Jung, Sungkyun↗

An adaptive granular representative volume element model with an evolutionary periodic boundary for hierarchical multiscale analysis

The hierarchical multiscale analysis normally utilizes a microscopic representative volume element (RVE) model to capture path/history-dependent macroscopic responses instead of using phenomenological constitutive models. However, for problems involving large deformation, the current RVE model used in geomechanics may lose representative properties due to the progressive distortion of the RVE box, unless a proper reinitialization is applied. This work develops an adaptive RVE model in conjunction with an evolutionary periodic boundary (EPB) algorithm for hierarchical multiscale analysis of granular materials undergoing large deformation based on a recent RVE model proposed for coupling molecular dynamics and the material point method. The proposed adaptive RVE model avoids the reinitialization of the RVE box that even undergoes extremely large shear deformation; meanwhile, it accounts for the deformation history of the RVE model and treats the interaction between boundary particles and other image particles in a more efficient way. Numerical examples with extremely large deformation are used to illustrate the adaptive granular RVE model enhanced by the proposed EPB algorithm. Furthermore, some key features of this new methodology are further discussed for clarification.

42 ENGINEERING↗

The interpretation of remotely sensed cloud properties from a model paramterization perspective

A study has been made of the relationship between mean cloud radiative properties and cloud fraction in stratocumulus cloud systems. The analysis is of several Land Resources Satellite System (LANDSAT) images and three hourly International Satellite Cloud Climatology Project (ISCCP) C-1 data during daylight hours for two grid boxes covering an area typical of a general circulation model (GCM) grid increment. Cloud properties were inferred from the LANDSAT images using two thresholds and several pixel resolutions ranging from roughly 0.0625 km to 8 km. At the finest resolution, the analysis shows that mean cloud optical depth (or liquid water path) increases somewhat with increasing cloud fraction up to 20% cloud coverage. More striking, however, is the lack of correlation between the two quantities for cloud fractions between roughly 0.2 and 0.8. When the scene is essentially overcast, the mean cloud optical tends to be higher. Coarse resolution LANDSAT analysis and the ISCCP 8-km data show lack of correlation between mean cloud optical depth and cloud fraction for coverage less than about 90%. This study shows that there is perhaps a local mean liquid water path (LWP) associated with partly cloudy areas of stratocumulus clouds. A method has been suggested to use this property to construct the cloud fraction paramterization in a GCM when the model computes a grid-box-mean LWP.

HARSHVARDHAN↗

Explaining machine-learning models for gamma-ray detection and identification

As more complex predictive models are used for gamma-ray spectral analysis, methods are needed to probe and understand their predictions and behavior. Recent work has begun to bring the latest techniques from the field of Explainable Artificial Intelligence (XAI) into the applications of gamma-ray spectroscopy, including the introduction of gradient-based methods like saliency mapping and Gradient-weighted Class Activation Mapping (Grad-CAM), and black box methods like Local Interpretable Model-agnostic Explanations (LIME) and SHapley Additive exPlanations (SHAP). In addition, new sources of synthetic radiological data are becoming available, and these new data sets present opportunities to train models using more data than ever before. In this work, we use a neural network model trained on synthetic NaI(Tl) urban search data to compare some of these explanation methods and identify modifications that need to be applied to adapt the methods to gamma-ray spectral data. We find that the black box methods LIME and SHAP are especially accurate in their results, and recommend SHAP since it requires little hyperparameter tuning. We also propose and demonstrate a technique for generating counterfactual explanations using orthogonal projections of LIME and SHAP explanations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Deducing Electronic Unit Internal Response During a Vibration Test Using a Lumped Parameter Modeling Approach

During random vibration testing of electronic boxes there is often a desire to know the dynamic response of certain internal printed wiring boards (PWBs) for the purpose of monitoring the response of sensitive hardware or for post-test forensic analysis in support of anomaly investigation. Due to restrictions on internally mounted accelerometers for most flight hardware there is usually no means to empirically observe the internal dynamics of the unit, so one must resort to crude and highly uncertain approximations. One common practice is to apply Miles Equation, which does not account for the coupled response of the board in the chassis, resulting in significant over- or under-prediction. This paper explores the application of simple multiple-degree-of-freedom lumped parameter modeling to predict the coupled random vibration response of the PWBs in their fundamental modes of vibration. A simple tool using this approach could be used during or following a random vibration test to interpret vibration test data from a single external chassis measurement to deduce internal board dynamics by means of a rapid correlation analysis. Such a tool might also be useful in early design stages as a supplemental analysis to a more detailed finite element analysis to quickly prototype and analyze the dynamics of various design iterations. After developing the theoretical basis, a lumped parameter modeling approach is applied to an electronic unit for which both external and internal test vibration response measurements are available for direct comparison. Reasonable correlation of the results demonstrates the potential viability of such an approach. Further development of the preliminary approach presented in this paper will involve correlation with detailed finite element models and additional relevant test data.

random vibration response↗

Structural Analysis of Composite Test panels

An analytical study was conducted for a 1/4 scale model skin-stringer compression panel using STructural Analysis of General Shells (STAGS) code for finite element analysis. This was a study to investigate scaling methods for composite structures using reduced ply thicknesses for 1/2 and 1/4 scale models. A computer model for a curved panel in a pressure-box was also constructed in order to simulate test conditions in the pressure box test machine. The pressure box is a test facility at NASA Langley Research Center used to simulate flight conditions in fuselage panels. This model will be used to investigate modifications to the pressure-box for curved panels with different radii.

Berhan, Sean↗

Traceable Black-Box Watermarks For Federated Learning

Due to the distributed nature of Federated Learning (FL) systems, each local client has access to the global model, which poses a critical risk of model leakage. Existing works have explored injecting watermarks into local models to enable intellectual property protection. However, these methods either focus on non-traceable watermarks or traceable but white-box watermarks. We identify a gap in the literature regarding the formal definition of traceable black-box watermarking and the formulation of the problem of injecting such watermarks into FL systems. In this work, we first formalize the problem of injecting traceable black-box watermarks into FL. Based on the problem, we propose a novel server-side watermarking method, TraMark, which creates a traceable watermarked model for each client, enabling verification of model leakage in black-box settings. To achieve this, TraMark partitions the model parameter space into two distinct regions: the main task region and the watermarking region. Subsequently, a personalized global model is constructed for each client by aggregating only the main task region while preserving the watermarking region. Each model then learns a unique watermark exclusively within the watermarking region using a distinct watermark dataset before being sent back to the local client. Extensive results across various FL systems demonstrate that TraMark ensures the traceability of all watermarked models while preserving their main task performance.

Xu, Jiahao [University of Nevada, Reno]↗

Development of CFD Flow Analysis for Nuclear Facility Ventilation Systems

Understanding and modeling of particulate transport has importance related to safety in ventilated environments that contain hot cells, gloveboxes, and fume hoods. In particular, good modeling of the airflow in these spaces is required to understand areas of stagnation where particles drop out of the free stream and accumulate. This accumulation of particulate can cause either contamination and/or higher than acceptable local dose levels. It is known that multiple sites across the DOE complex take credit for hot cells, gloveboxes, and/or hoods in their safety basis for providing a defense-in-depth benefit for both onsite and offsite releases. By providing confinement of radioactive materials, such features serve to reduce direct doses to facility workers and mitigate the consequences to the environment due to an uncontrolled release. Each of these features has access points that interface with the personnel space. Understanding how air flow behaves at these access points is of great interest to those performing hazard analysis. Computational Fluid Dynamics (CFD) can be used to analyze and model the flows in hot cells and glove boxes as a way to confirm operation. While CFD capability continues to advance, there are still important modeling assumptions that are left to the analyst's discretion. These are most notably the choice of the turbulence models, mesh structure, and wall boundary condition assumptions used in the model. In this work, we apply CFD in modeling airflow through an occupiable work area of the Alpha Gamma Hot Cell Facility (AGHCF) at Argonne National Laboratory (ANL). This modeling is then compared to field test data to both inform and verify the modeling assumptions. Based on the results of field tests, modeling assumptions and boundary conditions are refined and the process is repeated until the results are found to be reliable with a high level of confidence.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Limitations to the ‘basic’ HOD model and beyond

ABSTRACT We use the IllustrisTNG cosmological, hydrodynamical simulations to test fundamental assumptions of the mass-based halo occupation distribution (HOD) approach to modelling the galaxy–halo connection. By comparing the clustering of galaxies measured in the 300 Mpc TNG box (TNG300) with that predicted by the standard (basic) HOD model, we find that, on average, the ‘basic’ HOD model underpredicts the real-space correlation function in the TNG300 box by ∼15 per cent on scales of $1 \,\,\lt\,\, r \,\,\lt\,\, 20 \ {\rm Mpc}\, h^{-1}$, which is well beyond the target precision demanded of next-generation galaxy redshift surveys. We perform several tests to establish the robustness of our findings to systematic effects, including the effect of finite box size and the choice of halo finder. In our exploration of ‘secondary’ parameters with which to augment the ‘basic’ HOD, we find that the local environment of the halo, the velocity dispersion anisotropy, β, and the product of the half-mass radius and the velocity dispersion, σ2Rhalfmass, are the three most effective measures of assembly bias that help reconcile the ‘basic’ HOD-predicted clustering with that in TNG300. In addition, we test other halo properties such as halo spin, formation epoch, and halo concentration. We also find that at fixed halo mass, galaxies in one type of environment cluster differently from galaxies in another. We demonstrate that a more complete model of the galaxy–halo connection can be constructed if we combine both mass and local environment information about the halo.

42 ENGINEERING↗

A Velocity Distribution Model for Steady State Heat Transfer

Consider a box that is filled with an ideal gas and that is aligned along Cartesian coordinates (x, y, z) having until length in the 'y' direction and unspecified length in the 'x' and 'z' directions. Heat is applied uniformly over the 'hot' end of the box (y = 1) and is removed uniformly over the 'cold' end (y = O) at a constant rate such that the ends of the box are maintained at temperatures T(sub 0) at y = O and T(sub 1) at y = 1. Let U, V, and W denote the respective velocity components of a molecule inside the box selected at some random time and at some location (x, y, z). If T(sub 0) = T(sub 1), then U, Y, and W are mutually independent and Gaussian, each with mean zero and variance RT(sub 0), where R is the gas constant. When T(sub 0) does not equal T(sub 1) the velocity components are not independent and are not Gaussian. Our objective is to characterize the joint distribution of the velocity components U, Y, and W as a function of y, and, in particular, to characterize the distribution of V given y. It is hoped that this research will lead to an increased physical understanding of the nature of turbulence.

Hall, Eric B.↗

An Optimization Platform Based on Coupled Indoor Environment and HVAC Simulation and its Application in Optimal Thermostat Placement

Model-based optimization can help improve the indoor thermal comfort and energy efficiency of Heating, Ventilation and Air Conditioning (HVAC) systems. The models used in previous optimization studies either omit the dynamic interaction between indoor airflow and HVAC or are too slow for model-based optimization. To address this limitation, we propose an optimization methodology using coupled simulation of the airflow and HVAC that captures the dynamics of both systems. We implement an optimization platform using the coupled models of a coarse grid Fast Fluid Dynamics model for indoor airflow and Modelica models for HVAC which is linked to the GenOpt optimization engine. Then, we demonstrate the new optimization platform by studying the optimal thermostat placement in a typical office room with a VAV terminal box in the design phase. After validating the model, we perform an optimization study, in which the VAV terminal box is dynamically controlled, and find that our optimization platform can determine the optimal location of thermostat to achieve either best thermal comfort or least energy consumption, or the combined. Finally, the time cost for performing such optimization study is about 6.2 h, which is acceptable in the design phase.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Metabolic Cages for a Space Flight Model in the Rat

A variety of space flight models are available to mimic the physiologic changes seen in the rat during weightlessness. The model reported by Wronski and Morey-Holton has been widely used by many investigators, in musculoskeletal physiologic studies especially, resulting in accumulation of an extensive database that enables scientists to mimic space flight effects in the 1-g environment of Earth. However, information on nutrition or gastrointestinal and renal function in this space flight model is limited by the difficulty in acquiring uncontaminated metabolic specimens for analysis. In the Holton system, a traction tape harness is applied to the tail, and the rat's hindquarters are elevated by attaching the harness to a pulley system. Weight-bearing hind limbs are unloaded, and there is a headward fluid shift. The tail-suspended rats are able to move freely about their cages on their forelimbs and tolerate this procedure with minimal signs of stress. The cage used in Holton's model is basically a clear acrylic box set on a plastic grid floor with the pulley and tail harness system attached to the open top of the cage. Food is available from a square food cup recessed into a corner of the floor. In this system, urine, feces, and spilled food fall through the grid floor onto absorbent paper beneath the cage and cannot be separated and recovered quantitatively for analysis in metabolic balance studies. Commercially available metabolic cages are generally cylindrical and have been used with a centrally located suspension apparatus in other space flight models. The large living area, three times as large as most metabolic cages, and the free range of motion unique to Holton's model, essential for musculoskeletal investigations, were sacrificed. Holton's cages can accommodate animals ranging in weight from 70 to 600 g. Although an alternative construction of Holton's cage has been reported, it does not permit collection of separate urine and fecal samples. We describe the modifications to Holton's food delivery system, cage base, and the addition of a separator system for the collection of urine and fecal samples for metabolic and nutrition studies in the tail suspension model.

Harper, Jennifer S.↗

Active Learning Meets Foundation Models: Fast Remote Sensing Data Annotation for Object Detection

Object detection in remote sensing demands extensive, high-quality annotations—a process that is both labor-intensive and time-consuming. In this work, we introduce a real-time active learning and semi-automated labeling framework that leverages foundation models to streamline dataset annotation for object detection in remote sensing imagery. For example, by integrating a Segment Anything Model (SAM), our approach generates mask-based bounding boxes that serve as the basis for dual sampling: (a) uncertainty estimation to pinpoint challenging samples, and (b) diversity assessment to ensure broad data coverage. Furthermore, our Dynamic Box Switching Module (DBS) addresses the well-known cold start problem for object detection models by replacing its suboptimal initial predictions with SAM-derived masks, thereby enhancing early-stage localization accuracy. Extensive evaluations on multiple remote sensing datasets plus a real-world user study, demonstrate that our framework not only reduces annotation effort, but also significantly boosts detection performance compared to traditional active learning sampling methods. The code for training and the user interface will be made available.

Burges, Marvin [ORNL] (ORCID:0000000312690769)↗

Nucleation in Synoptically Forced Cirrostratus

Formation and evolution of cirrostratus in response to weak, uniform and constant synoptic forcing is simulated using a one-dimensional numerical model with explicit microphysics, in which the particle size distribution in each grid box is fully resolved. A series of tests of the model response to nucleation modes (homogeneous-freezing-only/heterogeneous nucleation) and heterogeneous nucleation parameters are performed. In the case studied here, nucleation is first activated in the prescribed moist layer. A continuous cloud-top nucleation zone with a depth depending on the vertical humidity gradient and one of the nucleation parameters is developed afterward. For the heterogeneous nucleation cases, intermittent nucleation zones in the mid-upper portion of the cloud form where the relative humidity is on the rise, because existent ice crystals do not uptake excess water vapor efficiently, and ice nuclei (IN) are available. Vertical resolution as fine as 1 m is required for realistic simulation of the homogeneous-freezing-only scenario, while the model resolution requirement is more relaxed in the cases where heterogeneous nucleation dominates. Bulk microphysical and optical properties are evaluated and compared. Ice particle number flux divergence, which is due to the vertical gradient of the gravity-induced particle sedimentation, is constantly and rapidly changing the local ice number concentration, even in the nucleation zone. When the depth of the nucleation zone is shallow, particle number concentration decreases rapidly as ice particles grow and sediment away from the nucleation zone. When the depth of the nucleation zone is large, a region of high ice number concentration can be sustained. The depth of nucleation zone is an important parameter to be considered in parametric treatments of ice cloud generation.

Lin, R.-F.↗

A scale-invariant cellular-automata model for distributed seismicity

In the standard cellular-automata model for a fault an element of stress is randomly added to a grid of boxes until a box has four elements, these are then redistributed to the adjacent boxes on the grid. The redistribution can result in one or more of these boxes having four or more elements in which case further redistributions are required. On the average added elements are lost from the edges of the grid. The model is modified so that the boxes have a scale-invariant distribution of sizes. The objective is to model a scale-invariant distribution of fault sizes. When a redistribution from a box occurs it is equivalent to a characteristic earthquake on the fault. A redistribution from a small box (a foreshock) can trigger an instability in a large box (the main shock). A redistribution from a large box always triggers many instabilities in the smaller boxes (aftershocks). The frequency-size statistics for both main shocks and aftershocks satisfy the Gutenberg-Richter relation with b = 0.835 for main shocks and b = 0.635 for aftershocks. Model foreshocks occur 28 percent of the time.

Barriere, Benoit↗