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At least 973 records · Page 54

Additive Manufacturing of Controlled Porous Elastomeric Nanocomposites for Enhanced Sensing Function

Sensors manufactured using piezoresistive elastomeric nanocomposites have a wide range of applications in many fields such as structural health monitoring, robotics, and biomedical industries. Additive manufacturing of these sensors, achieved using Direct Ink Writing (DIW), has provided numerous advantages including increased sensitivity and the fabrication of complex geometry. However, solid sensors manufactured either additively or using conventional methods, display a greater level of hysteresis, especially at strains higher than 10%, which limits their sensitivity. The solid sensors also display a greater level of piezoresistive relaxation where the resistance change with time either in a static or dynamic loading environment. Porosity can be introduced in the form of varying infill patterns and densities to reduce bulk material effects. In this paper, a lattice structure with four infill densities are investigated, and the samples are printed using a grid infill pattern. The fabricated samples are characterized using a scanning electron microscope (SEM) to validate the microstructural features and layer bonding. The pressure-sensing capability of each sensor is investigated using cyclic compression loading at various strain levels. Sensing results show that an increase in sensitivity, as well as a decrease in hysteresis with an increase in porosity, compared to solid samples (100% in-fill). The highest porosity was measured to be 62.3% with a corresponding 112% increase in the gauge factor compared to the solid bulk. These results indicate that introducing porosity using DIW is a sensible strategy to improve the piezoresistive performance of nanocomposites and to allow for the tunability of sensing capacity in pressure sensors

Sukati, Musa↗

Updating PV and Battery Bill Savings Calculations for Net Billing: New Best Practices for Input Data and Uncertainty

Jurisdictions are increasingly adopting compensation structures for distributed PV and PV-battery systems that price exported energy lower than energy consumed onsite (net billing rates). Standard methods for calculating the bill savings from PV and PV-battery systems were developed for net metering structures, and applying these same methods to net billing structures (such as using Typical Meteorological Year weather with actual year load) introduces bias errors that underestimate PV-battery system bill savings by between 1.5\% and 9\%, depending on the utility rate. We assess the magnitude of these errors and compare them to other sources of uncertainty when estimating the bill savings from PV and PV-battery systems under more complex utility rates.

14 SOLAR ENERGY↗

Mechanical Roles of Polysaccharide Assembly and Interactions in Plant Cell Walls

Plants synthesize polysaccharide-based primary cell walls that possess unique microstructures and mechanical properties to accommodate plant growth and provide protection. Here, it remains challenging to assess the role of polysaccharide organization and interactions in the mechanical behavior of primary cell walls owing to their complex microstructure and highly nonlinear mechanical responses. Employing a coarse-grained molecular dynamics model developed for onion epidermal walls, this work explores the conditions under which polysaccharide assembly and interactions might play a significant role in primary cell wall mechanics. Cellulose–cellulose adhesion plays a dominant role in the wall load-bearing capacity, but when cellulose–cellulose adhesion was disrupted computationally, cellulose–xyloglucan adhesion could influence the wall load-bearing capacity. Contrary to the common concept that xyloglucans mechanically tether well-separated cellulose microfibrils, xyloglucans functioned in this case as interfibrillar adhesives capable of transmitting tensile forces between cellulose microfibrils. Our findings may inform design criteria of new materials inspired by plant cell walls.

59 BASIC BIOLOGICAL SCIENCES↗

Perovskite-Derived Cs 2 SnCl 6 –Silica Composites as Advanced Waste Forms for Chloride Salt Wastes

Advanced materials and processes are required to separate halides and fission products from complex salt waste streams associated with the chemical reprocessing of used nuclear fuels and molten salt reactor technologies for immobilization into chemically durable waste forms. Here, in this work, we explore an innovative concept using metal-halide perovskites as advanced host phases to incorporate Cs and Cl with very high waste loadings. Wet chemistry-synthesized Cs 2 SnCl 6 powders from CsCl salt solutions are successfully encapsulated into a silica matrix to form a composite using low-temperature spark plasma sintering with tunable Cs and Cl loadings up to 31 wt.% and 26 wt.%, respectively. Chemical durability testing of the composite waste forms by semi-dynamic leaching experiments demonstrates that incongruent leaching mechanism dominated. The metal-halide perovskite-silica composite waste forms display exceptional chemical durability with the long-term release rates of Cs and Cl comparable to or outperforming the state-of-the-art waste form materials but with significantly higher waste loadings. The scalable synthesis of the metal-halide perovskite from wet-chemistry processes opens up new opportunities in designing perovskite-glass composite waste forms for salt wastes with very high waste loadings and exceptional chemical durability for the sustainable development of advanced fuel cycles and next-generation reactor technologies.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Hooks versus Pedicle Screws at the Upper Instrumented Level: An In Vitro Biomechanical Comparison

Study Design. Controlled laboratory study Objective. To compare motions at the upper instrumented vertebra (UIV) and supra-adjacent level (UIV+1) between two fixation techniques in thoracic posterior spinal fusion (PSF) constructs. We hypothesized there would be greater motion at UIV+1 after cyclic loading across all constructs and bilateral pedicle screws (BPS) with posterior ligamentous compromise would demonstrate the greatest UIV+1 range of motion (ROM). Summary of Background Data. Proximal junctional kyphosis (PJK) is a well-recognized complication following long thoraco-lumbar PSF, however its mechanism is poorly understood. Methods. Twenty-seven thoracic functional spine units (FSU) were randomly divided into three UIV fixation groups (n=9): (1) BPS, (2) bilateral transverse process hooks (TPH), and (3) BPS with compromise of the posterior elements between UIV and UIV+1 (BPS-C). Specimens were tested on a servohydraulic materials testing system in native state, following instrumentation, and after cyclic loading. FSUs were loaded in flexion-extension (FE), lateral bending (LB), and axial rotation (AR). Results. After cyclic testing, the TPH group had a mean 29.4% increase in FE ROM at UIV+1 versus 76.6% in the BPS group ( P <0.05). The BPS-C group showed an increased FE of 49.9% and 62.19% with sectioning of the facet joints and interspinous ligament respectively prior to cyclic testing. Conclusion. Bilateral pedicle screws at the UIV led to greater motion at UIV+1 compared to bilateral TPH after cyclic loading. This is likely due to the increased rigidity of BPS compared to TPH leading to a “softer” transition between the TPH construct and native anatomy at the supra-adjacent level. Facet capsule compromise led to a 49.9% increase in UIV+1 motion, underscoring the importance of preserving the posterior ligamentous complex. Clinical studies that account for fusion rates are warranted to determine if constructs with a “soft transition” result in less PJK in vivo.

Neurosciences & Neurology↗

Adaptive Power System Emergency Control using Deep Reinforcement Learning

Power system emergency control is generally regarded as the final safety net for grid security and resiliency. Existing emergency control schemes are usually designed off-line based on either the conceived “worst” case scenarios or a few typical operation scenarios. These schemes are facing significant adaptiveness and robustness issues as increasing uncertainties and variations occur in modern electrical grids. To address these challenges, for the first time, this paper proposes a novel adaptive emergency control scheme using deep reinforcement learning (DRL), by leveraging the high-dimensional feature extraction and non-linear generalization capabilities DRL has for complex systems with high-dimensional variations. Furthermore, an open-source platform named DeepGrid has been designed for the first time to assist the DRL development and benchmarking processes in power system emergency control. Details of the platform, DRL, and emergency control schemes that use dynamic braking or under-voltage load shedding are presented. Extensive case studies performed in both two-area four-machine system and IEEE 39-Bus system have demonstrated the excellent performance and robustness of the proposed schemes.

Deep reinforcement learning, emergency control, lo↗

Distribution Substation Planning Toolkit (dsp-toolkit) v1.0

The Distribution Substation Planning Toolkit (DSP Toolkit) is a software suite designed to streamline the planning and optimization of distribution substations. This toolkit offers a comprehensive set of tools and APIs for data curation, short-term electric load forecasting, and weather-sensitive load adjustment, making it an essential resource for utility companies, engineers, and researchers. Features • Data Preprocessing and Curation: Efficiently manage and preprocess large datasets to ensure high-quality input for analysis. • Short-Term Load Forecasting: Utilize data-driven models to predict short-term electric loads accurately. • Weather-Sensitive Modeling: Automatically adjust load forecasts based on weather data to predict future peak demands more precisely. Uses The DSP Toolkit is ideal for planning and optimizing distribution substations, providing a user-friendly interface and comprehensive documentation. It is suitable for both novice and experienced users, facilitating efficient and accurate planning processes. Advantages • Efficiency: Automates complex planning tasks, reducing manual effort and minimizing errors. • Scalability: Handles large datasets and complex models, making it suitable for large-scale projects. • Community and Support: Open-source with active community contributions, ensuring continuous improvement and support. • Extensibility: Easily extendable with custom modules and plugins, allowing users to tailor the toolkit to their specific needs. The DSP Toolkit stands out by offering a robust, flexible, and user-friendly solution for distribution substation planning. Public Abstract

Li, Han [Lawrence Berkeley National Laboratory (LB↗

Experimental Study of the Fundamental Properties of Warm Dense Mixtures

The aim of the proposed research was to provide a multi-scale study of the properties of warm dense hydrocarbons, by studying the thermodynamic properties through the equation of state and the microscopic properties by x-ray scattering. Understanding the fundamental properties of warm dense mixtures is an intellectual challenge due to the complexity of the system. Unlike liquids or gases, where constituent particle interactions occur through collisions or bonding between valence electrons, in these strongly coupled systems the atoms will be partially ionized and compressed so tightly together that interactions between the inner core electrons can play a role in the systems chemistry. Advances in computational capabilities and development of new theoretical models have been used to predict the properties of mixtures but there is currently no experimental data of the fundamental interaction between the particles in mixtures to test these predictions against. The proposed research was to experimentally investigate the interaction of the different species in hydrocarbons by measuring the compressibility of substances with different carbon and hydrogen ratios and the complexity of the microscopic interactions through elastic and inelastic x-ray scattering. To study the bulk properties of warm dense hydrocarbons we established the Warm Dense Matter Research Laboratory (WDMRL) in the Institute for Shock Physics at Washington State University. The goal was for experiments in the WDMRL to determine shock loading conditions of interest in the hydrocarbon mixtures. We planned on using Hugoniot EOS measurements and a range of carbon and hydrogen concentrations to determine conditions when the EOS of the mixture varied significantly from that of the classical mixing model. Even though shock transit measurements through aluminum foils suggested pressures upto 400GPa, the experiments in the WDMRL were unsuccessful in getting usable shockwave compression data above 100GPa in polystyrene which was below the pressure of interest for hydrocarbon mixtures (>200GPa). To complete the project, we tested a technique using x-ray phase contrast imaging to map the location of tracer layers in a test sample of polycarbonate to record the material motion in dynamically compressed samples. A technique that will be useful for future warm dense matter experiments. These experiments used <200nm gold layers in polycarbonate samples to measure the material velocity and shock speed using x-ray phase contrast imaging. These results were compared to continuum surface measurements performed at ISP and show that the tracer layer technique can measure hydrodynamic properties accurately in dynamically compressed materials.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

CACTI ARM Aerial Facility Measurements of Ice Nucleating Particles

The dataset comprises measures, using Colorado State University's Ice Spectrometer (IS, an immersion freezing device with a range from 0&deg;C down to -26 to -29&deg;C) of atmospheric ice nucleating particle (INP) concentrations taken on the Atmospheric Radiation Measurement (ARM) program Aerial Facilty (AAF) G-1 aircraft. INP measurements on the G-1 were collected from varied altitudes on different flights over the region of the Sierras de C&oacute;rdoba mountain range of north-central Argentina, centred over ARM's Mobile Facility (AMF-1) near Villa Yacanto, where ground-based INP measures were being taken concurrently. Both studies took place as part of the Cloud, Aerosol, and Complex Terrain Interactions (CACTI) Experiment. A filter sampling system was deployed on the G-1 to collect aerosol particles for post-processing of INPs collected on filters (measuring their immersion freezing ability) once returned to Colorado State University (CSU). Filter holders used were pre-cleaned aluminum in-line units loaded with pre-cleaned and pre-sterilized 47 mm dia. Nuclepore polycarbonate filters (0.2 mm pore size). Filters were drawn for varied times, resulting in varied volumes collected (51 to 1667 SL). Mass flow rate was recorded in real-time so that total sampled volume (at standard temperature and pressure) could be determined. A total of 34 sample filters were collected over the IOP, including 5 blanks. Filters were stored at -20&deg;C freezer prior to frozen return to Colorado State University (CSU). . Processing to obtain spectra of INP number concentration active via the immersion freezing mechanism versus temperature was conducted using CSU's IS instrument (McCluskey et al., 2018). For measurment of INPs, collected aerosol particles were re-suspended in 7 mL of 0.02 &micro;m-filtered deionized water. Aliquots of each suspension, and serial dilutions, were dispensed into trays which were fit into aluminum blocks in the IS. Samples are cooled at 0.33&deg;C min-1 and the freezing temperatures of wells recorded automatically. Cumulative INP concentrations were determined by first calculating the INPs per mL of suspension based on Vali (1971) and then converting to concentration per standard liter of air using the proportion of the total liquid sample dispensed and the air sample volumes. Aliquots of suspensions from selected samples were also heat treated (95&deg;C for 20 min) to denature and deactivate biological INPs, and digested in 10% H2O2 at 95&deg;C under UV-B to remove all organic carbon INPs. McCluskey, C. S., J. Ovadnevaite, M. Rinaldi, J. Atkinson, F. Belosi, D. Ceburnis, S. Marullo, T. C. J. Hill, U. Lohmann, Z. A. Kanji, C. O&rsquo;Dowd, S. M. Kreidenweis, P. J. DeMott, 2018: Marine and Terrestrial Organic Ice Nucleating Particles in Pristine Marine to Continentally-Influenced Northeast Atlantic Air Masses, Journal of Geophysical Research: Atmospheres, 123, 6196&ndash;6212, https://doi.org/10.1029/2017JD028033. Vali, G., 1971: Quantitative evaluation of experimental results on the heterogeneous freezing nucleation of supercooled liquids. J. Atmos. Sci., 28, 402&ndash;409.

54 ENVIRONMENTAL SCIENCES↗

Load Flexibility Analysis of Residential HVAC and Water Heating and Commercial Refrigeration

The emergence of connected devices and the Internet of Things has opened the door to the concept of widespread use of building equipment for load-side flexibility. This stems from the increased use of distributed and clean energy resources for electric generation and the growing demand for a more resilient and reliable grid. A significant challenge associated with the use of building equipment as a distributed energy resource is quantifying the magnitude of power or energy flexibility. Unlike batteries that have well-defined and relatively constant capacity and maximum charge/discharge rates, building equipment often has characteristics that vary based on external factors (e.g., weather or occupant behavior). This makes quantifying the availability and flexibility of these resources difficult. Controlling a fleet of equipment while minimizing any adverse impacts to the occupants (e.g., discomfort or food spoilage) is a nontrivial matter. Although there are many different control methodologies available, this study focuses on two: priority-based control (PBC) and model-predictive control (MPC). These were selected because they represent two ends of the control spectrum. PBC is a relatively simple control strategy that requires only the current state of the devices to be controlled and an estimate of how much power each device consumes when turned on. MPC is much more complex and requires a model of the system and forecasts of any disturbances that influence the system. Because MPC has a predictive element, it can prepare for a desired response before the event and therefore is expected to provide a more optimal control relative to PBC. Both MPC and PBC are compared with a baseline simulation that uses feedback control typical of the thermostatically controlled devices being evaluated. This report investigates the load flexibility of three building systems: residential air conditioners, residential water heaters, and commercial refrigeration. Air heating and cooling and water heating account for 45% of residential electricity use, making them good candidates for providing load flexibility. Refrigeration in commercial buildings accounts for 16% of commercial building electricity use, making it another good candidate. Simplified models of each system were generated and validated based on measured data from actual equipment. These models were used to simulate the thermal and power response of the systems using PBC and MPC for a fleet of devices trying to achieve a variety of different responses, including hourly load shed, hourly load up, and daily peak demand reduction. Significant findings from each piece of equipment follow.

42 ENGINEERING↗

Design Studies for the Optimization of 238 Pu Production in NpO 2 Targets Irradiated at the High Flux Isotope Reactor

Efforts to reestablish a domestic 238 Pu production capability in support of National Aeronautics and Space Administration mission objectives are ongoing throughout the U.S. Department of Energy complex. The Plutonium-238 Supply Project (PSP) was initiated in response to a report published by the National Research Council in 2011 stating that “without a restart of 238 Pu production, it will be impossible for the United States, or any other country, to conduct certain important types of planetary missions after this decade.” The PSP is targeting a sustained, constant production rate of 1.5 kg/year of heat source PuO 2 for several years. Design and optimization studies of 237 Np-bearing targets are underway at Oak Ridge National Laboratory (ORNL). It is anticipated that targets will be irradiated in ORNL’s High Flux Isotope Reactor (HFIR) and in the Advanced Test Reactor (ATR) at Idaho National Laboratory. A variety of target materials, containments, arrangements, and irradiation histories have been analyzed, and the results indicate that a sufficient quantity of 238 Pu can be produced in HFIR and ATR to fulfill the PSP’s constant production rate target. This paper focuses on the design and optimization of new target configurations containing pellets that are (1) ~93% of the theoretical density of NpO 2 , (2) loaded into pins of cladding materials that can be handled as solid waste following postirradiation 238 Pu recovery operations, (3) irradiated in various vertical experiment facility (VXF) locations in the HFIR permanent beryllium reflector, and (4) rotated within and/or moved to another VXF location following each HFIR operational cycle to maximize 238Pu production and minimize peak heat generation rates.

07 ISOTOPE AND RADIATION SOURCES↗

Collaborating CPU and GPU for large-scale high-order CFD simulations with complex grids on the TianHe-1A supercomputer

Programming and optimizing complex, real-world CFD codes on current many-core accelerated HPC systems is very challenging, especially when collaborating CPUs and accelerators to fully tap the potential of heterogeneous systems. In this paper, with a tri-level hybrid and heterogeneous programming model using MPI + OpenMP + CUDA, we port and optimize our high-order multi-block structured CFD software HOSTA on the GPU-accelerated TianHe-1A supercomputer. HOSTA adopts two self-developed high-order compact definite difference schemes WCNS and HDCS that can simulate flows with complex geometries. We present a dual-level parallelization scheme for efficient multi-block computation on GPUs and perform particular kernel optimizations for high-order CFD schemes. The GPU-only approach achieves a speedup of about 1.3 when comparing one Tesla M2050 GPU with two Xeon X5670 CPUs. To achieve a greater speedup, we collaborate CPU and GPU for HOSTA instead of using a naive GPU-only approach. We present a novel scheme to balance the loads between the store-poor GPU and the store-rich CPU. Taking CPU and GPU load balance into account, we improve the maximum simulation problem size per TianHe-1A node for HOSTA by 2.3×, meanwhile the collaborative approach can improve the performance by around 45% compared to the GPU-only approach. Further, to scale HOSTA on TianHe-1A, we propose a gather/scatter optimization to minimize PCI-e data transfer times for ghost and singularity data of 3D grid blocks, and overlap the collaborative computation and communication as far as possible using some advanced CUDA and MPI features. Scalability tests show that HOSTA can achieve a parallel efficiency of above 60% on 1024 TianHe-1A nodes. With our method, we have successfully simulated an EET high-lift airfoil configuration containing 800M cells and China's large civil airplane configuration containing 150M cells. To our best knowledge, those are the largest-scale CPU–GPU collaborative simulations that solve realistic CFD problems with both complex configurations and high-order schemes.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

A numerical approach for simulating fluid structure interaction of flexible thin shells undergoing arbitrarily large deformations in complex domains

We present a new numerical methodology for simulating fluid–structure interaction (FSI) problems involving thin flexible bodies in an incompressible fluid. The FSI algorithm uses the Dirichlet–Neumann partitioning technique. The curvilinear immersed boundary method (CURVIB) is coupled with a rotation-free finite element (FE) model for thin shells enabling the efficient simulation of FSI problems with arbitrarily large deformation. Turbulent flow problems are handled using large-eddy simulation with the dynamic Smagorinsky model in conjunction with a wall model to reconstruct boundary conditions near immersed boundaries. The CURVIB and FE solvers are coupled together on the flexible solid–fluid interfaces where the structural nodal positions, displacements, velocities and loads are calculated and exchanged between the two solvers. Loose and strong coupling FSI schemes are employed enhanced by the Aitken acceleration technique to ensure robust coupling and fast convergence especially for low mass ratio problems. The coupled CURVIB-FE-FSI method is validated by applying it to simulate two FSI problems involving thin flexible structures: 1) vortex-induced vibrations of a cantilever mounted in the wake of a square cylinder at different mass ratios and at low Reynolds number; and 2) the more challenging high Reynolds number problem involving the oscillation of an inverted elastic flag. For both cases the computed results are in excellent agreement with previous numerical simulations and/or experiential measurements. Grid convergence tests/studies are carried out for both the cantilever and inverted flag problems, which show that the CURVIB-FE-FSI method provides their convergence. Finally, the capability of the new methodology in simulations of complex cardiovascular flows is demonstrated by applying it to simulate the FSI of a tri-leaflet, prosthetic heart valve in an anatomic aorta and under physiologic pulsatile conditions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Acute Stroke and Obstruction of the Extracranial Carotid Artery Combined with Intracranial Tandem Occlusion: Results of Interventional Revascularization

PurposeDue to high thrombus load, acute stroke patients with tandem obstructions of the extra- and intracranial carotid arteries or the middle cerebral artery show a very limited response to systemic thrombolysis. Interventional treatment with mechanical thrombectomy—often in combination with acute stenting of underlying atherosclerotic stenosis or dissection—is increasingly used. It has been shown that such complex interventions are technically feasible. The lack of optimal management strategies and clinical data encouraged us to review our acute stroke interventions in patient with anterior circulation tandem lesions to determine lesion patterns, interventional approaches, and angiographic or clinical outcomes.Patients and MethodsWe retrospectively analyzed a series of 39 consecutive patients with intracranial vessel occlusion of the anterior circulation simultaneously presenting with high-grade cervical internal carotid artery (ICA) stenosis or occlusion.ResultsEmergency ICA stent implantation was technically feasible in all patients, and intracranial recanalization with TICI ≥ 2b was reached in a large number of patients (64 %). Good clinical outcomes (mRS ≤ 2 at 3 months) were achieved in one third of the patients (36 %). Symptomatic hemorrhages occurred in four patients (10 %). Mortality was 10 %.ConclusionEndovascular recanalization of acute cervical carotid artery occlusion was technically feasible in all patients, and resulted in high extra- and intracranial revascularization rates. A trend for favorable clinical outcome was seen in a higher TICI score, younger age, good collateral status, and combined IV rTPA and endovascular therapy.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

A cut-cell finite volume – finite element coupling approach for fluid–structure interaction in compressible flow

We present a loosely coupled approach for the solution of fluid–structure interaction problems between a compressible flow and a deformable structure. The method is based on staggered Dirichlet–Neumann partitioning. The interface motion in the Eulerian frame is accounted for by a conservative cut-cell Immersed Boundary method. The present approach enables sub-cell resolution by considering individual cut-elements within a single fluid cell, which guarantees an accurate representation of the time-varying solid interface. The cut-cell procedure inevitably leads to non-matching interfaces, demanding for a special treatment. A Mortar method is chosen in order to obtain a conservative and consistent load transfer. We validate our method by investigating two-dimensional test cases comprising a shock-loaded rigid cylinder and a deformable panel. Moreover, the aeroelastic instability of a thin plate structure is studied with a focus on the prediction of flutter onset. Finally, we propose a three-dimensional fluid–structure interaction test case of a flexible inflated thin shell interacting with a shock wave involving large and complex structural deformations.

42 ENGINEERING↗

Sample glue layer investigation and mitigation for laser induced prompt impulse experiments

Understanding longer timescale material reactions under dynamic stress loading is critical for applications in materials engineering, shock physics, and planetary science. Prompt impulse experiments generate lower pressures since the ablator—the material first removed by the laser—is thicker and farther from the diagnostic plane, capturing aggregate material responses from the initial shock wave, rarefaction waves, and later time effects. This complexity demands thorough material characterization and simulation support. Since traditional sample construction is specific to supported shock experiments, designing prompt impulse experiments requires reconsideration around target design and sample engineering. Here, we present sample preparation techniques, experimental investigations, and theoretical simulations to investigate glue layer impacts, aiming to standardize samples for consistent data at lower laser fluences. We find that glue layers <30 μm have a minimal impact on peak velocity and pulse shape. The peak velocity scales linearly with glue layer thickness until a glue layer of 75 μm. For glue layers >75 μm, the peak velocity no longer scales with thickness; however, the pulse shape continues to degrade as described by simulations.

Lasers↗

Leveraging In-Network Computing and Programmable Switches for Streaming Analysis of Scientific Data

With the emergence of programmable network devices that match the performance of fixed function devices, several recent projects have explored in-network computing, where the processing that is traditionally done outside the network is offloaded to the network devices. In-network computing has typically been applied to network functions (e.g., load balancing, NAT, and DNS), caching, data reduction/aggregation, and coordination/consensus functions. In some cases it has been used to accelerate stream-processing tasks that involve small payloads and simple operations. In this work we focus on leveraging in-network computing for stream processing of scientific datasets with large payloads that require complex operations such as floating-point computations and logarithmic functions. We demonstrate in-network computing for a real-world scientific application performing streaming normalization of a 2-D image from a light source experiment. We discuss the challenges we encountered and potential approaches to address them.

Sankaran, Ganesh↗