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At least 1,585 records · Page 88

The sol–gel autocombustion as a route towards highly CO 2 -selective, active and long-term stable Cu/ZrO 2 methanol steam reforming catalysts

The adaption of the sol-gel autocombustion method to the Cu/ZrO 2 system opens new pathways for the specific optimisation of the activity, long-term stability and CO 2 selectivity of methanol steam reforming (MSR) catalysts. Calcination of the same post-combustion precursor at 400 °C, 600 °C or 800 °C allows accessing Cu/ZrO 2 interfaces of metallic Cu with either amorphous, tetragonal or monoclinic ZrO 2 , influencing the CO 2 selectivity and the MSR activity distinctly different. While the CO 2 selectivity is less affected, the impact of the post-combustion calcination temperature on the Cu and ZrO 2 catalyst morphology is more pronounced. A porous and largely amorphous ZrO 2 structure in the sample, characteristic for sol-gel autocombustion processes, is obtained at 400 °C. This directly translates into superior activity and long-term stability in MSR compared to Cu/tetragonal ZrO 2 and Cu/monoclinic ZrO 2 obtained by calcination at 600 °C and 800 °C. The morphology of the latter Cu/ZrO 2 catalysts consists of much larger, agglomerated and non-porous crystalline particles. Based on aberration-corrected electron microscopy, we attribute the beneficial catalytic properties of the Cu/amorphous ZrO 2 material partially to the enhanced sintering resistance of copper particles provided by the porous support morphology.

36 MATERIALS SCIENCE↗

Automatic Traffic Queue-End Identification using Location-Based Waze User Reports

Traffic queues, especially queues caused by non-recurrent events such as incidents, are unexpected to high-speed drivers approaching the end of queue (EOQ) and become safety concerns. Though the topic has been extensively studied, the identification of EOQ has been limited by the spatial-temporal resolution of traditional data sources. This study explores the potential of location-based crowdsourced data, specifically Waze user reports. It presents a dynamic clustering algorithm that can group the location-based reports in real time and identify the spatial-temporal extent of congestion as well as the EOQ. The algorithm is a spatial-temporal extension of the density-based spatial clustering of applications with noise (DBSCAN) algorithm for real-time streaming data with an adaptive threshold selection procedure. Here, the proposed method was tested with 34 traffic congestion cases in the Knoxville, Tennessee area of the United States. It is demonstrated that the algorithm can effectively detect spatial-temporal extent of congestion based on Waze report clusters and identify EOQ in real-time. The Waze report-based detection are compared to the detection based on roadside sensor data. The results are promising: The EOQ identification time of Waze is similar to the EOQ detection time of traffic sensor data, with only 1.1 min difference on average. In addition, Waze generates 1.9 EOQ detection points every mile, compared to 1.8 detection points generated by traffic sensor data, suggesting the two data sources are comparable in respect of reporting frequency. The results indicate that Waze is a valuable complementary source for EOQ detection where no traffic sensors are installed.

99 GENERAL AND MISCELLANEOUS↗

Development of 225Ac-doped biocompatible nanoparticles for targeted alpha therapy

Abstract Targeted alpha therapy (TAT) relies on chemical affinity or active targeting using radioimmunoconjugates as strategies to deliver α-emitting radionuclides to cancerous tissue. These strategies can be affected by transmetalation of the parent radionuclide by competing ions in vivo and the bond-breaking recoil energy of decay daughters. The retention of α-emitting radionuclides and the dose delivered to cancer cells are influenced by these processes. Encapsulating α-emitting radionuclides within nanoparticles can help overcome many of these challenges. Poly(lactic- co -glycolic acid) (PLGA) nanoparticles are a biodegradable and biocompatible delivery platform that has been used for drug delivery. In this study, PLGA nanoparticles are utilized for encapsulation and retention of actinium-225 ([ 225 Ac]Ac 3+ ). Encapsulation of [ 225 Ac]Ac 3+ within PLGA nanoparticles (Z ave = 155.3 nm) was achieved by adapting a double-emulsion solvent evaporation method. The encapsulation efficiency was affected by both the solvent conditions and the chelation of [ 225 Ac]Ac 3+ . Chelation of [ 225 Ac]Ac 3+ to a lipophilic 2,9-bis-lactam-1,10-phenanthroline ligand ([ 225 Ac]AcBLPhen) significantly decreased its release (< 2%) and that of its decay daughters (< 50%) from PLGA nanoparticles. PLGA nanoparticles encapsulating [ 225 Ac]AcBLPhen significantly increased the delivery of [ 225 Ac]Ac 3+ to murine (E0771) and human (MCF-7 and MDA-MB-231) breast cancer cells with a concomitant increase in cell death over free [ 225 Ac]Ac 3+ in solution. These results demonstrate that PLGA nanoparticles have potential as radionuclide delivery platforms for TAT to advance precision radiotherapy for cancer. In addition, this technology offers an alternative use for ligands with poor aqueous solubility, low stability, or low affinity, allowing them to be repurposed for TAT by encapsulation within PLGA nanoparticles. Graphical Abstract

60 APPLIED LIFE SCIENCES↗

OperonSEQer: A set of machine-learning algorithms with threshold voting for detection of operon pairs using short-read RNA-sequencing data

Operon prediction in prokaryotes is critical not only for understanding the regulation of endogenous gene expression, but also for exogenous targeting of genes using newly developed tools such as CRISPR-based gene modulation. A number of methods have used transcriptomics data to predict operons, based on the premise that contiguous genes in an operon will be expressed at similar levels. While promising results have been observed using these methods, most of them do not address uncertainty caused by technical variability between experiments, which is especially relevant when the amount of data available is small. In addition, many existing methods do not provide the flexibility to determine the stringency with which genes should be evaluated for being in an operon pair. We present OperonSEQer, a set of machine learning algorithms that uses the statistic and p-value from a non-parametric analysis of variance test (Kruskal-Wallis) to determine the likelihood that two adjacent genes are expressed from the same RNA molecule. We implement a voting system to allow users to choose the stringency of operon calls depending on whether your priority is high recall or high specificity. In addition, we provide the code so that users can retrain the algorithm and re-establish hyperparameters based on any data they choose, allowing for this method to be expanded as additional data is generated. We show that our approach detects operon pairs that are missed by current methods by comparing our predictions to publicly available long-read sequencing data. OperonSEQer therefore improves on existing methods in terms of accuracy, flexibility, and adaptability.

59 BASIC BIOLOGICAL SCIENCES↗

SIERRA Multimechanics Module: Aria Thermal Theory Manual - Version 4.58

Aria is a Galerkin finite element based program for solving coupled-physics problems described by systems of PDEs and is capable of solving nonlinear, implicit, transient and direct-to-steady state problems in two and three dimensions on parallel architectures. The suite of physics currently supported by Aria includes thermal energy transport, species transport, and electrostatics as well as generalized scalar, vector and tensor transport equations. Additionally, Aria includes support for manufacturing process flows via the incompressible Navier-Stokes equations specialized to a low Reynolds number (R e < 1) regime. Enhanced modeling support of manufacturing processing is made possible through use of either arbitrary Lagrangian-Eulerian (ALE) and level set based free and moving boundary tracking in conjunction with quasi-static nonlinear elastic solid mechanics for mesh control. Coupled physics problems are solved in several ways including fully-coupled Newtons method with analytic or numerical sensitivities, fully-coupled Newton-Krylov methods and a loosely-coupled nonlinear iteration about subsets of the system that are solved using combinations of the aforementioned methods. Error estimation, uniform and dynamic-adaptivity and dynamic load balancing are some of Arias more advanced capabilities.

42 ENGINEERING↗

SIERRA Multimechanics Module: Aria User Manual (V.5.6)

Aria is a Galerkin finite element based program for solving coupled-physics problems described by systems of PDEs and is capable of solving nonlinear, implicit, transient and direct-to-steady state problems in two and three dimensions on parallel architectures. The suite of physics currently supported by Aria includes thermal energy transport, species transport, and electrostatics as well as generalized scalar, vector and tensor transport equations. Additionally, Aria includes support for manufacturing process flows via the incompressible Navier-Stokes equations specialized to a low Reynolds number ( $Re$ < 1 ) regime. Enhanced modeling support of manufacturing processing is made possible through use of either arbitrary Lagrangian-Eulerian (ALE) and level set based free and moving boundary tracking in conjunction with quasi-static nonlinear elastic solid mechanics for mesh control. Coupled physics problems are solved in several ways including fully-coupled Newton's method with analytic or numerical sensitivities, fully-coupled Newton-Krylov methods and a loosely-coupled nonlinear iteration about subsets of the system that are solved using combinations of the aforementioned methods. Error estimation, uniform and dynamic $h$-adaptivity and dynamic load balancing are some of Aria's more advanced capabilities.

97 MATHEMATICS AND COMPUTING↗

SIERRA Multimechanics Module: Aria User Manual (V.5.10)

Aria is a Galerkin finite element based program for solving coupled-physics problems described by systems of PDEs and is capable of solving nonlinear, implicit, transient and direct-to-steady state problems in two and three dimensions on parallel architectures. The suite of physics currently supported by Aria includes thermal energy transport, species transport, and electrostatics as well as generalized scalar, vector and tensor transport equations. Additionally, Aria includes support for manufacturing process flows via the incompressible Navier-Stokes equations specialized to a low Reynolds number ($Re$ < 1) regime. Enhanced modeling support of manufacturing processing is made possible through use of either arbitrary Lagrangian-Eulerian (ALE) and level set based free and moving boundary tracking in conjunction with quasi-static nonlinear elastic solid mechanics for mesh control. Coupled physics problems are solved in several ways including fully-coupled Newton’s method with analytic or numerical sensitivities, fully-coupled Newton-Krylov methods and a loosely-coupled nonlinear iteration about subsets of the system that are solved using combinations of the aforementioned methods. Error estimation, uniform and dynamic $h$-adaptivity and dynamic load balancing are some of Aria’s more advanced capabilities.

97 MATHEMATICS AND COMPUTING↗

SIERRA Multimechanics Module: Aria Thermal Theory Manual (V.5.10)

Aria is a Galerkin finite element based program for solving coupled-physics problems described by systems of PDEs and is capable of solving nonlinear, implicit, transient and direct-to-steady state problems in two and three dimensions on parallel architectures. The suite of physics currently supported by Aria includes thermal energy transport, species transport, and electrostatics as well as generalized scalar, vector and tensor transport equations. Additionally, Aria includes support for manufacturing process flows via the incompressible Navier-Stokes equations specialized to a low Reynolds number ($Re$ < 1) regime. Enhanced modeling support of manufacturing processing is made possible through use of either arbitrary Lagrangian-Eulerian (ALE) and level set based free and moving boundary tracking in conjunction with quasi-static nonlinear elastic solid mechanics for mesh control. Coupled physics problems are solved in several ways including fully-coupled Newton’s method with analytic or numerical sensitivities, fully-coupled Newton-Krylov methods and a loosely-coupled nonlinear iteration about subsets of the system that are solved using combinations of the aforementioned methods. Error estimation, uniform and dynamic $h$-adaptivity and dynamic load balancing are some of Aria’s more advanced capabilities.

42 ENGINEERING↗

SIERRA Multimechanics Module: Aria Thermal Theory Manual (V.4.56)

Aria is a Galerkin finite element based program for solving coupled-physics problems described by systems of PDEs and is capable of solving nonlinear, implicit, transient and direct-to-steady state problems in two and three dimensions on parallel architectures. The suite of physics currently supported by Aria includes thermal energy transport, species transport, and electrostatics as well as generalized scalar, vector and tensor transport equations. Additionally, Aria includes support for manufacturing process flows via the incompressible Navier-Stokes equations specialized to a low Reynolds number ( Re < 1) regime. Enhanced modeling support of manufacturing processing is made possible through use of either arbitrary Lagrangian-Eulerian (ALE) and level set based free and moving boundary tracking in conjunction with quasi-static nonlinear elastic solid mechanics for mesh control. Coupled physics problems are solved in several ways including fully-coupled Newton’s method with analytic or numerical sensitivities, fully-coupled Newton-Krylov methods and a loosely-coupled nonlinear iteration about subsets of the system that are solved using combinations of the aforementioned methods. Error estimation, uniform and dynamic h -adaptivity and dynamic load balancing are some of Aria’s more advanced capabilities.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Virtual to Physical: Reinforcement Learning to Optimize SNS Particle Accelerator Controls

Complex accelerators must have control systems that can handle dynamic nonlinear environments. This makes traditional control methods unsuitable as they can struggle to adapt to these uncertainties. This provides an ideal environment for reinforcement learning algorithms as they are adaptable and generalizable. We present a reinforcement learning pipeline that can effectively handle the dynamics of a complex accelerator. We test and prove our pipelines capabilities on multiple environments including the Spallation Neutron Source (SNS) and the Beam Test Facility (BTF) at Oakridge National Lab (ORNL). Due to the limited time available to train an online algorithm like reinforcement learning on a real accelerator, we utilize a virtual twin accelerator (VIRAC) developed by ORNL to pretrain the policy and show its ability to converge in the virtual environment. We then test the adaptability of the pretrained RL model by applying it on the real accelerator and comparing the results. Utilizing our Scientific Optimization and Controls Toolkit (SOCT) and open-source standards such as Gymnasium we create and solve for a MEBT orbit correction problem in the SNS and an emittance maximization problem in the BTF. We show how Twin Delayed Deep Deterministic Policy Gradient (TD3) can solve this optimization environment in the virtual accelerator and transfer this policy onto the real accelerator for inference and model retraining. We show how reinforcement learning can be utilized as a control system for complex accelerators and provide a model pipeline for how an implementation performs and can be adapted to new accelerator control problems.

Kasparian, Armen [Thomas Jefferson National Accele↗

Aerodynamic influence coefficient method using singularity splines.

A new numerical formulation with computed results, is presented. This formulation combines the adaptability to complex shapes offered by paneling schemes with the smoothness and accuracy of the loading function methods. The formulation employs a continuous distribution of singularity strength over a set of panels on a paneled wing. The basic distributions are independent, and each satisfies all of the continuity conditions required of the final solution. These distributions are overlapped both spanwise and chordwise (termed 'spline'). Boundary conditions are satisfied in a least square error sense over the surface using a finite summing technique to approximate the integral.

Mercer, J. E.↗

Water resources planning for rivers draining into Mobile Bay

The application of remote sensing, automatic data processing, modeling and other aerospace related technologies to hydrological engineering and water resource management are discussed for the entire river drainage system which feeds the Mobile Bay estuary. The adaptation and implementation of existing mathematical modeling methods are investigated for the purpose of describing the behavior of Mobile Bay. Of particular importance are the interactions that system variables such as river flow rate, wind direction and speed, and tidal state have on the water movement and quality within the bay system.

April, G. C.↗

Discrete model reference adaptive systems with measurement noise

A digital computer simulation study is presented for a class of discrete model reference adaptive systems designed using Liapunov's direct method. Plant output measurements are assumed to contain uniformly distributed additive noise. It is shown that the design works well even when such noise is relatively extreme. A new result is presented pertaining to improving the convergence properties of these systems. This result is obtained by modifying the dynamic characteristics of the augmented error equation.

Monopoli, R. V.↗

A numerical simulation of two-dimensional inlet flow fields

Inlet flow fields for airbreathing missiles are calculated by the adaptation of a two-dimensional computational method developed for the flow around airfoils. A supersonic free stream is assumed to allow the forebody calculation to be uncoupled from the inlet calculation. The inlet calculation employs an implicit, time-marching finite-difference procedure to solve the thin-layer Navier-Stokes equations formulated in body-fitted coordinates. Because the method can be used for a flow field with both subsonic and supersonic regions, it is applicable to subcritical as well as supercritical inlet operation.

Biringen, S.↗

The effects of weld-repair and hot isostatic pressing on the fracture properties of Ti-5Al-2.5Sn ELI castings

The Ti-5Al-2.5Sn extremely low interstitial alloy employed in the large castings which form the critical attachment fittings of the Space Shuttle External Tank was selected because of its high fracture resistance at cryogenic temperatures. Casting was selected over alternative fabrication methods because of its lower cost and adaptability to design changes, although it was found necessary to weld-repair surface and subsurface casting defects in order to reduce the scrap rate and maintain the inherent cost advantage of the castings. Hot Isostatic Pressing was experimentally found to heal the surface and internal defects of the castings, but did not improve tensile or fracture properties and was therefore rejected as a production technique. Production castings are instead weld-repaired, without any mechanical property degradation.

Misra, M. S.↗

Geometric accuracy assessment of Landsat-4 Thematic Mapper p-tapes

An analysis was performed on the P-format computer compatible tapes for the Landsat-4 Thematic Mapper (TM) scene 40109-15140 acquired November 2, 1982 over Washington, D.C. and environs. Three tests of sensor geometry were undertaken: (1) band-to-band registration, (2) line-to-line registration between swaths, and (3) geometric correction of sensor and spacecraft/ephemeris characteristics. The band-to-band and line-to-line registration was measured at one hundred pixel spacings along a line using the phase correlation image alignment method developed by Kuglin and Hines and adapted to a one-dimensional FFT correlation technique. The sensor and spacecraft geometric calibration analysis was checked by identifying 75 ground control points in the TM scene and on 1:24,000 topographic maps. A least squares fit of the gaps was computed and the vector offsets of the residuals was tabulated and plotted.

Bryant, N. A.↗