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At least 271 records · Page 15

Fast Algorithm for Evaluating Critical Current of High-Temperature Superconducting Pancake Coil

Second-generation (2G) high-temperature superconducting (HTS) tapes are now capable of carrying very high transport current and promising for a wide range of applications. The critical current of HTS coils is important for applications, such as superconducting electric machines, superconducting magnetic energy storage, and superconducting magnets. Therefore, precisely and quickly calculating critical current of HTS coils is very important for designing HTS devices. This paper provides a fast algorithm for evaluating critical current of HTS pancake coil. The fast algorithm is realized through a stationary model, which is based on finite element method (FEM) software. The stationary model means that the model is solved by stationary study instead of time-dependent study. To validate this method, a pancake HTS coil was wound and its critical current was measured. Meanwhile, an axial symmetric stationary model was built according to the geometry of the measured HTS coil. By comparing measured and calculated results, the effectiveness of the stationary model was demonstrated. Moreover, the stationary model is compared with H formulation model. The calculated results by the two models are nearly the same. However, by using stationary calculation, the stationary model can remarkably speed up the computational process. Due to the advantage of calculating speed, the stationary model can be used to characterize and design large-scale HTS applications.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Assessing time-of-flight signal-to-noise ratio gains within the myocardium and subsequent reductions in administered activity in cardiac PET studies

Background: Time-of-flight (TOF) is known to increase signal-to-noise ratio (SNR) and facilitate reductions in administered activity. Established measures of SNR gain are derived from areas of uniform uptake, which is not applicable to the heterogeneous uptake in cardiac PET images using fluoro-deoxyglucose (FDG). This study aimed to develop a technique to quantify SNR gains within the myocardium due to TOF. Methods: Reference TOF SNR gains were measured in 88 FDG oncology patients. Phantom data were used to translate reference SNR gains and validate a method of quantifying SNR gains within the myocardium from parametric images produced from multiple replicate images. This technique was applied to 13 FDG cardiac viability patients. Results: Reference TOF SNR gains of +23% ± 8.5% were measured in oncology patients. Measurements of SNR gain from the phantom data were in agreement and showed the parametric image technique to be sufficiently robust. SNR gains within the myocardium in the viability patients were +21% ± 2.8%. Conclusion: A method to quantify SNR gains from TOF within the myocardium has been developed and evaluated. SNR gains within the myocardium are comparable to those observed by established methods. This allows guidance for protocol optimization for TOF systems in cardiac PET.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Three-dimensional traction microscopy accounting for cell-induced matrix degradation

Tractions exerted by cells on the extracellular matrix (ECM) are critical in many important physiological and pathological processes such as embryonic morphogenesis, wound healing, and cancer metastasis. Three-dimensional Traction Microscopy (3DTM) is a tool to quantify cellular tractions by first measuring the displacement field in the ECM in response to these tractions, and then using this measurement to infer tractions. Most applications of 3DTM have assumed that the ECM has spatially-uniform mechanical properties, but cells secrete enzymes that can locally degrade the ECM. In this work, a novel computational method is developed to quantify both cellular tractions and ECM degradation. In particular, the ECM is modeled as a hyperelastic, Neo-Hookean solid, whose material parameters are corrupted by a single degradation parameter. The feasibility of determining both the traction and the degradation parameter is first demonstrated by showing the existence and uniqueness of the solution. An inverse problem is then formulated to determine the nodal values of the traction vector and the degradation parameter, with the objective of minimizing the difference between a predicted and measured displacement field, under the constraint that the predicted displacement field satisfies the equation of equilibrium. The inverse problem is solved by means of a gradient-based optimization approach, and the gradient is computed efficiently using appropriately derived adjoint fields. The computational method is validated in-silico using a geometrically realistic neuronal cell model and synthetic traction and degradation fields. It is found that the method accurately recovers both the traction and degradation fields. Moreover, it is found that neglecting ECM degradation can yield significant errors in traction measurements. Finally, our method can extend the range of context where tractions can be appropriately measured.

42 ENGINEERING↗

Arctic Vegetation Mapping Using Unsupervised Training Datasets and Convolutional Neural Networks

Land cover datasets are essential for modeling and analysis of Arctic ecosystem structure and function and for understanding land–atmosphere interactions at high spatial resolutions. However, most Arctic land cover products are generated at a coarse resolution, often limited due to cloud cover, polar darkness, and poor availability of high-resolution imagery. A multi-sensor remote sensing-based deep learning approach was developed for generating high-resolution (5 m) vegetation maps for the western Alaskan Arctic on the Seward Peninsula, Alaska. The fusion of hyperspectral, multispectral, and terrain datasets was performed using unsupervised and supervised classification techniques over a ~343 km 2 area, and a high-resolution (5 m) vegetation classification map was generated. An unsupervised technique was developed to classify high-dimensional remote sensing datasets into cohesive clusters. We employed a quantitative method to add supervision to the unlabeled clusters, producing a fully labeled vegetation map. We then developed convolutional neural networks (CNNs) using the multi-sensor fusion datasets to map vegetation distributions using the original classes and the classes produced by the unsupervised classification method. To validate the resulting CNN maps, vegetation observations were collected at 30 field plots during the summer of 2016, and the resulting vegetation products developed were evaluated against them for accuracy. Our analysis indicates the CNN models based on the labels produced by the unsupervised classification method provided the most accurate mapping of vegetation types, increasing the validation score (i.e., precision) from 0.53 to 0.83 when evaluated against field vegetation observations.

54 ENVIRONMENTAL SCIENCES↗

Revised single-spacecraft method for determining wave vector k and resolving space-time ambiguity

A practical method is proposed for determining the wave vector of waves from single-spacecraft measurements. This wave vector knowledge can then be used to remove the space-time ambiguity produced by frequency Doppler shift associated with spacecraft motion. The method involves applying the Wiener-Khinchin theorem to cross correlations of the current and magnetic field oscillations and to autocorrelations of the magnetic field oscillations. Lastly, the method requires that each wave frequency component map to a unique wave vector, a condition presumed true in many spacecraft measurement situations. Examples validating the method are presented.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Accurate and Sensitive Analytical Strategy for the Determination of Antimony: Hydrogen Assisted T-Shaped Slotted Quartz Tube-Atom Trap-Flame Atomic Absorption Spectrometry

Antimony is known to have some adverse health effects on human health. Flame atomic absorption spectrometry (FAAS) is a widely used instrumental for the determination of antimony and other metals. However, it lacks the sensitivity to determine these metals at trace levels. This study was aimed at overcoming this setback by using hydrogen assisted T-shaped slotted quartz tube technique to preconcentrate and determine antimony by FAAS. All the system parameters were optimized to enhance the detection power of the system. Under the optimum experimental conditions, the limits of detection and quantification were found to be 0.75 and 2.49 µg L{sup −1}, respectively with R{sup 2} value of 0.9999. Accuracy of the developed method was validated by experimental results agreeing to the certified value of a standard reference material. Recovery studies were also carried out to determine the method’s applicability to tap and mineral water samples, and the results obtained were appreciable.

54 ENVIRONMENTAL SCIENCES↗

Extended real-time voltage instability identification method based on synchronized phasor measurements

This paper presents an extended adaptive approach designed to accurately estimate the Thévenin equivalent parameters using phasor measurements at a given bus for measurements lying in any of four quadrants of the PQ-plane. The improvement is achieved by using a new condition to properly update the estimated parameters after an initial guess. Based on an adaptive philosophy, the proposed approach can correctly account for the intrinsic nonlinearities of a power system, can provide a real-time estimation of Thévenin parameters, and does not require network topology knowledge. The method is validated using the Kundur 2-area system, showing estimation improvements compared to the current adaptive approach and the classical recursive least-squares method. The proposed approach is able to estimate both sides of the system with respect to the measurement bus. In addition, a data-driven voltage stability index is developed. To illustrate the performance of the proposed approach in a larger power system, a voltage stability assessment is carried out on the IEEE 39-bus system, considering the action of overexcitation limiters of generators and nonlinear loads. The proposed approach is suitable for applications that require an accurate Thévenin equivalent estimation in real-time, such as for voltage stability assessment. The new approach provides a reliable tool for the system operators to make proper and timely decisions.

42 ENGINEERING↗

Nonadiabatic transition path sampling

Fewest-switches surface hopping (FSSH) is combined with transition path sampling (TPS) to produce a new method called nonadiabatic path sampling (NAPS). The NAPS method is validated on a model electron transfer system coupled to a Langevin bath. Numerically exact rate constants are computed using the reactive flux (RF) method over a broad range of solvent frictions that span from the energy diffusion (low friction) regime to the spatial diffusion (high friction) regime. The NAPS method is shown to quantitatively reproduce the RF benchmark rate constants over the full range of solvent friction. Integrating FSSH within the TPS framework expands the applicability of both approaches and creates a new method that will be helpful in determining detailed mechanisms for nonadiabatic reactions in the condensed-phase.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A geometric framework for momentum-based optimizers for low-rank training

Low-rank pre-training and fine-tuning have recently emerged as promising techniques for reducing the computational and storage costs of large neural networks. Training low-rank parameterizations typically relies on conventional optimizers such as heavy ball momentum methods or Adam. In this work, we identify and analyze potential difficulties that these training methods encounter when used to train low-rank parameterizations of weights. In particular, we show that classical momentum methods can struggle to converge to a local optimum due to the geometry of the underlying optimization landscape. To address this, we introduce novel training strategies derived from dynamical low-rank approximation, which explicitly account for the underlying geometric structure. Our approach leverages and combines tools from dynamical low-rank approximation and momentum-based optimization to design optimizers that respect the intrinsic geometry of the parameter space. We validate our methods through numerical experiments, demonstrating faster convergence, and stronger validation metrics at given parameter budgets.

Schotthoefer, Steffen [ORNL] (ORCID:00000002156965↗

Applying a Compact Porous Media Model to Numerically Derive Resistance Coefficients for Lattice Structures

Additive Manufacturing allows for exploring various geometries to achieve specific engineering criteria. Lattices are one geometry with unique properties, including being periodically repeating structures which allow flow through them to be represented as a porous media according to Darcy-Forchheimer equations. These equation’s coefficients are generally experimentally derived, but this work demonstrates the ability to numerically derive them with CFD. Simulations were performed using three-dimensional stead state Reynolds-averaged Navier-Stokes with a k-ω Shear Stress Transport turbulence model using Ansys Fluent. Three lattice geometries were investigated and drag coefficients were derived. The method was validated against externally published data for similar geometries demonstrating strong agreement, and grid convergence for all simulations was calculated with a Grid Convergence Index method. Wall roughness is demonstrated to have a non-negligible impact on results and roughness values are considered for the primary focus Octahedral geometry where both smooth wall and rough wall coefficients were derived. The porosity coefficients for the Octahedral geometry at 1.0 [m/s] were found to be 2.89×10 6 and 2.90×10 6 [1/(Pa*m*s)] for the permeability coefficients, 6.37×10 1 and 5.44×10 1 [m 2 /kg] for the inertial resistance coefficients, and with a max pressure drop of 5116.7 [Pa] and 4429.5 [Pa] for the smooth walls and rough walls, respectively. The derived numerical method enables rapid exploration and optimization of new lattice designs for diverse engineering applications.

42 ENGINEERING↗

Multi-Factor-Coupled, Ahead-of-Time Aggregation of Power Flexibility Under Forecast Uncertainty

The increasing penetration of distributed energy resources (DERs) is significantly reshaping the role of distribution systems under active energy management. To aggregate the active-reactive power flexibility of DERs dispersed at the feeder and provide capacity support to the transmission system, it is essential to efficiently identify feasible substation power injection trajectories. This paper introduces a novel ahead-of-time flexibility characterization method to address it. First, a polyhedral non-feeder-level power flexibility region (PFR) is constructed, accounting for various time-dependent, power-coupled, and forecast error uncertainties. Then, a polyhedral feeder-level PFR is analytically derived through a coordinate transformation, which can reveal the uncertainty propagation path, i.e., how uncertainty applies to the feeder-level PFR. To facilitate the high-level application, a tractable chance-constrained Chebyshev centering optimization model is further developed to find a ball-shaped inner approximation of the feeder-level PFR. Finally, the proposed method is validated on a modified IEEE 123-bus test system. Here, both theoretical and experimental results show that, with appropriate robustness parameter settings, the proposed method can make the approximated PFR less conservative with abundant robustness against forecast error uncertainty.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Data association algorithm for large-scale multi-object tracking with complex interactions

We present an online multi-object tracking algorithm to track multiple objects across a large number of image frames. Our work is motivated by the need to study evolution of nanoscale objects by transmission electron microscopy. The proposed approach is based on the existing multi-way data association tracking algorithm that is capable of tracking interacting objects with complex behaviors (i.e., merge, split, overlap, and appearance or disappearance). The multi-way data association is an offline algorithm to associate objects across all image frames at one step with a global optimization, which does not scale very well for large number of image frames. The proposed online tracking algorithm processes image frames as they arrive by detecting all objects in the newly arrived image frame and making the associations of the objects to those detected from the previous frame by the multi-way data association. This frameby-frame association scheme can cause fragmented traces of the objects that are occasionally misdetected for some image frames. We overcome this issue by allowing previously unassociated objects to be associated when the objects reappear within a fixed number of future image frames, namely the frame-delayed association. We combine the multi-way data association with the frame-delayed association to be able to track interacting objects with accurate handling of object disappearance events. The proposed method is validated through applications to simulated multi-object tracking problem and a real multi-object tracking problem. Here, the outcome of the proposed method is compared with four state-of-the-art algorithms.

36 MATERIALS SCIENCE↗

Seventy-Five Years of Nuclear Criticality Safety Documents - A Bibliography

A collection of nuclear criticality documents was begun in the 1970s at the University of California’s Lawrence Livermore Laboratory (now Lawrence Livermore National Laboratory). Documents in this bibliography are dated as early as 1940. The early documents described experimental work that was of vital importance to the safe use of fissile materials at nuclear reactors, the facilities for preparing or transporting nuclear fuel, or its eventual storage. The experiments were of direct value to support safe operations with fissile material, but they were also needed for validating early physics data and calculational methods and then for validating computational methods used in criticality safety evaluations. Bibliographic information from the past seventy-five years have been entered into a computerized bibliographic database. The database continues to expand. Publications were issued several decades ago based on the information collected at that time. Our new publication is based on a current “snapshot” of the present status of the database. Contributions of information or corrections to this bibliography will be appreciated.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Validation of Nuclear Data Sensitivity Calculations by the MCNP PERT Card [Poster]

This work validates a method of estimating sensitivities that utilized the MCNP PERT card and tallies. The agreement of the PERT card and Brute Force results proves the validity of calculating nuclear data sensitivities by use of the MCNP PERT card, especially at higher energies. The overall agreement will be easier to understand once an uncertainty analysis is completed.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Seventy-Five Years of Nuclear Criticality Safety Documents--A Bibliography

A collection of nuclear criticality documents was begun in the 1970s at the University of California’s Lawrence Livermore Laboratory (now Lawrence Livermore National Laboratory). Documents in this bibliography are dated as early as 1940. The early documents described experimental work that was of vital importance to the safe use of fissile materials at nuclear reactors, the facilities for preparing or transporting nuclear fuel, or its eventual storage. The experiments were of direct value to support safe operations with fissile materials, but they were also needed for validating early physics data and calculational methods and then for validating computational methods used in criticality safety evaluations. These documents provided information for our computerized bibliographic database. The bibliography was originally intended for use by Livermore staff members but criticality safety "pioneers” encouraged us to make the database available to the broader nuclear safety community and even shared copies of their bibliographies and reports. A publication of the bibliography is being prepared and a searchable database is available on the U.S. Department of Energy’s Nuclear Criticality Safety Program’s NCSP website. The NCSP website also includes links from the bibliography to many full-text documents. The database continues to expand--the information in this paper is based on a “snapshot” of its present status. The “vintage” hardcopy document collection is preserved and is being scanned into digital format.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Seventy-five years of nuclear criticality safety documents - a bibliography

A collection of nuclear criticality documents was begun in the 1970's at the University of California's Lawrence Livermore Laboratory (now Lawrence Livermore National Laboratory). Documents in this bibliography are dated as early as 1940. The early documents described experimental work that was of vital importance to the safe use of fissile materials at nuclear reactors, the facilities for preparing or transporting nuclear fuel, or its eventual storage. The experiments were of direct value to support safe operations with fissile materials but they were also needed for validating early physics data and calculational methods and then for validating computational methods used in criticality safety evaluations. These documents provided information for our computerized bibliographic database. The bibliography was originally intended for use by Livermore staff members but criticality safety 'pioneers' encouraged us to make the database available to the broader nuclear safety community and even shared copies of their bibliographies and reports. A publication of the bibliography is being prepared and a searchable database is available on the U.S. Department of Energy's Nuclear Criticality Safety Program's NCSP web site. The NCSP web site also includes links from the bibliography to many full-text documents. The database continues to expand--the information in this paper is based on a 'snapshot' of its present status. The 'vintage' hardcopy document collection is preserved and is being scanned into digital format. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Seventy-five years of nuclear criticality safety documents - A bibliography, part II - Links to full-text documents

A collection of nuclear criticality documents was begun in the 1970's at the University of California's Lawrence Livermore Laboratory (now Lawrence Livermore National Laboratory). Documents in this bibliography are dated as early as 1940. The early documents described experimental work that was of vital importance to the safe use of fissile materials at nuclear reactors, the facilities for preparing or transporting nuclear fuel, or its eventual storage. The experiments were of direct value to support safe operations with fissile materials but they were also needed for validating early physics data and calculational methods and then for validating computational methods used in criticality safety evaluations. These documents provided information for our computerized bibliographic database which was originally published in hard-copy format. Our original 'vintage' hardcopy document collection is preserved and is being scanned into digital format. The bibliography is available online as 'LLNL Database' within the U.S. Department of Energy's Nuclear Criticality Safety Program's NCSP web site. Bibliographic information and full-text documents continue to be downloaded from online databases. The online bibliography now contains close to 23,000 records. Links are available to over 3600 full-text documents within NCSP. This capability will be demonstrated at this conference. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Validation of the stochastic inversion algorithm for acoustic travel-time tomography: a large eddy simulation study

Acoustic tomography (AT) is explored as a remote sensing technique to obtain instantaneous snapshots of temperature and velocity fluctuations for wind energy applications. This study integrates Large Eddy Simulation (LES) with the Stochastic Inversion (SI) method to validate the algorithm’s capacity for accurate reconstruction of atmospheric fluctuations. The initial findings demonstrate the efficacy of the method in accurately capturing the predominant flow structures. Normalized L2 error evaluations further inform the algorithm’s precision, with errors accentuated in less sampled peripheral regions. The results underscore the method’s promise as a non-intrusive observational tool, with ongoing development poised to improve its precision and reliability.

17 WIND ENERGY↗