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At least 145 records · Page 8

Thermomechanical Modeling and Analysis of a High-Temperature Light Trapping Planar Cavity Receiver

Solar energy harnessed through concentrating solar power (CSP) systems offers a promising path to sustainable energy production, with the efficiency and longevity of these systems relying on key components like solar receivers. This study analyzes the thermomechanical behavior of an innovative enclosed light-trapping solar receiver optimized for particle heating applications. The receiver utilizes sheet metal alloys to form enclosed cavities that reflect and trap incoming solar flux, as well as enclosed channels that contain fluidized particle beds absorbing solar heat. Finite element analysis (FEA) is applied to predict the receiver's thermomechanical performance under extreme solar flux conditions. Temperature distributions from a thermal model simulating a multi-panel assembly at steady state are input into the FEA thermomechanical model for stress analysis. A key aspect of the analysis focuses on evaluating creep-fatigue damage, with a design target of achieving a 30- year service life. Various stress relief techniques are also proposed to extend the receiver's service life. The results highlight the significant impact of the particle-to-wall heat transfer coefficients (HTCs), ranging from 800 W/m2*K to 1400 W/m2*K. The 800 W/m2*K case shows a maximum von Mises stress of 164 MPa, while the 1400 W/m2*K case reduces it to 150 MPa. The creep life increases from 4,000 hrs in the 800 W/m2*K case to over 100,000 hrs in the 1400 W/m2*K case with Inconel 740H used, indicating that higher HTCs reduce stress and extend lifespan. This research advances the design of high-efficiency, low-stress solar receivers for particle-based thermal energy storage in CSP and industrial heating applications.

concentrating solar power↗

Particle tracing in the magnetosphere - New algorithms and results

A fast and efficient method is employed to trace charged particles through realistic magnetospheric electric and magnetic fields, greatly reducing computer simulation times. The method is applicable for particles having arbitrary charge, energy, or pitch angle but which conserve the first two adiabatic invariants. An efficient method is used to classify drift orbits, which greatly facilitates identification of the last closed drift path or other drift boundaries. The time-independent evolution of the bounce-averaged phase space density along convective drift orbits is calculated. These three tools can be used to quantitatively describe convective evolution of the particle distribution from the tail, an essential step in understanding the production of unstable distributions in the magnetosphere.

Sheldon, R. B.↗

Evaluation of two-particle properties within finite-temperature self-consistent one-particle Green’s function methods: Theory and application to GW and GF2

One-particle Green’s function methods can model molecular and solid spectra at zero or non-zero temperatures. One-particle Green’s functions directly provide electronic energies and one-particle properties, such as dipole moment. However, the evaluation of two-particle properties, such as $\langle$S 2 $\rangle$ and $\langle$N 2 $\rangle$, can be challenging because they require a solution of the computationally expensive Bethe–Salpeter equation to find two-particle Green’s functions. We demonstrate that the solution of the Bethe–Salpeter equation can be completely avoided. Applying the thermodynamic Hellmann–Feynman theorem to self-consistent one-particle Green’s function methods, we derive expressions for two-particle density matrices in a general case and provide explicit expressions for GF2 and GW methods. Such density matrices can be decomposed into an antisymmetrized product of correlated one-electron density matrices and the two-particle electronic cumulant of the density matrix. Cumulant expressions reveal a deviation from ensemble representability for GW, explaining its known deficiencies. We analyze the temperature dependence of $\langle$S 2 $\rangle$ and $\langle$N 2 $\rangle$ for a set of small closed-shell systems. Interestingly, both GF2 and GW show a non-zero spin contamination and a non-zero fluctuation of the number of particles for closed-shell systems at the zero-temperature limit.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Coherent optical instrumentation for measurements of particle parameters

The application of cross-beam Laser Doppler Velocimeter (LDV) for sizing small particles was investigated from September 1973 to August 1974. Theoretical results were obtained by analyzing the scattering characteristics of small particles in a cross-beam LDV system. Theoretical calculations based on scalar diffraction theory and Mie scattering theory were performed. Experimental results were also obtained to compare with theoretical predictions. It is concluded that the forward scattering characteristics of small particles in a cross-beam LDV system can be used for particle sizing.

Chu, W. P.↗

Recoil imaging for dark matter, neutrinos, and physics beyond the Standard Model

Recoil imaging entails the detection of spatially resolved ionization tracks generated by particle interactions. This is a highly sought-after capability in many classes of detector, with broad applications across particle and astroparticle physics. However, at low energies, where ionization signatures are small in size, recoil imaging only seems to be a practical goal for micro-pattern gas detectors. This white paper outlines the physics case for recoil imaging, and puts forward a decadal plan to advance towards the directional detection of low-energy recoils with sensitivity and resolution close to fundamental performance limits. The science case covered includes: the discovery of dark matter into the neutrino fog, directional detection of sub-MeV solar neutrinos, the precision study of coherent-elastic neutrino-nucleus scattering, the detection of solar axions, the measurement of the Migdal effect, X-ray polarimetry, and several other applied physics goals. We also outline the R&D programs necessary to test concepts that are crucial to advance detector performance towards their fundamental limit: single primary electron sensitivity with full 3D spatial resolution at the $\sim$100 micron-scale. These advancements include: the use of negative ion drift, electron counting with high-definition electronic readout, time projection chambers with optical readout, and the possibility for nuclear recoil tracking in high-density gases such as argon. We also discuss the readout and electronics systems needed to scale-up such detectors to the ton-scale and beyond.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Lensless Particle Image Velocimetry

The application of lensless imaging to particle image velocimetry (PIV) is demonstrated. Lensless PIV eliminates the need for imaging lenses to measure flow fields near a surface. Only the camera sensor, a thin mask, and computations are required to image particles in a flow field and to compute the velocity field. The small form factor could enable embedded sensors for near-wall measurements. Flow field measurements are obtained simultaneously for a lensless system and lens-based 2D PIV system, and several different reconstruction techniques are demonstrated. The reconstructed particle images and computed velocity fields compare well for both a uniform and shear flow. The potential for stereo and 3D volumetric PIV with a single camera sensor is demonstrated through different image reconstruction approaches.

Lensless imaging↗

Decay of long-lived particles in the early universe

It is pointed out that radiative decay of massive fermions can distort the cosmic background radiation. The present investigation is concerned with a study of decay lifetimes in the range from 10 to 100,000 years. Attention is given to the physics involved in determining the effect of radiative decay of massive fermions on observed photon backgrounds. The case of particles which decoupled when the effective number of species in equilibrium was in the range from 50 to 100 is considered, and constraints on particle masses and lifetimes are placed on the basis of observed photon fluxes. This approach provides results with special applications to particles predicted by supersymmetry theories and to right-handed neutrinos. Implications for galaxy formation are also discussed.

Silk, J.↗

GASP cloud- and particle-encounter statistics and their application to LFC aircraft studies. Volume 2: Appendixes

Summary studies are presented for the entire cloud observation archive from the NASA Global Atmospheric Sampling Program (GASP). Studies are also presented for GASP particle-concentration data gathered concurrently with the cloud observations. Cloud encounters are shown on about 15 percent of the data samples overall, but the probability of cloud encounter is shown to vary significantly with altitude, latitude, and distance from the tropopause. Several meteorological circulation features are apparent in the latitudinal distribution of cloud cover, and the cloud-encounter statistics are shown to be consistent with the classical mid-latitude cyclone model. Observations of clouds spaced more closely than 90 minutes are shown to be statistically dependent. The statistics for cloud and particle encounter are utilized to estimate the frequency of cloud encounter on long-range airline routes, and to assess the probability and extent of laminaar flow loss due to cloud or particle encounter by aircraft utilizing laminar flow control (LFC). It is shown that the probability of extended cloud encounter is too low, of itself, to make LFC impractical. This report is presented in two volumes. Volume I contains the narrative, analysis, and conclusions. Volume II contains five supporting appendixes.

Jasperson, W. H.↗

GASP cloud- and particle-encounter statistics and their application to LPC aircraft studies. Volume 1: Analysis and conclusions

Summary studies are presented for the entire cloud observation archieve from the NASA Global Atmospheric Sampling Program (GASP). Studies are also presented for GASP particle concentration data gathered concurrently with the cloud observations. Cloud encounters are shown on about 15 percent of the data samples overall, but the probability of cloud encounter is shown to vary significantly with altitude, latitude, and distance from the tropopause. Several meteorological circulation features are apparent in the latitudinal distribution of cloud cover, and the cloud encounter statistics are shown to be consistent with the classical mid-latitude cyclone model. Observations of clouds spaced more closely than 90 minutes are shown to be statistically dependent. The statistics for cloud and particle encounter are utilized to estimate the frequency of cloud encounter on long range airline routes, and to assess the probability and extent of laminar flow loss due to cloud or particle encounter by aircraft utilizing laminar flow control (LFC). It is shown that the probability of extended cloud encounter is too low, of itself, to make LFC impractical.

Jasperson, W. H.↗

Analysis of Particle Image Velocimetry (PIV) Data for Application to Subsonic Jet Noise Studies

Global velocimetry measurements were taken using Particle Image Velocimetry (PIV) in the subsonic flow exiting a 1 inch circular nozzle in an attempt to better understand the turbulence characteristics of its shear layer region. This report presents the results of the PIV analysis and data reduction portions of the test and details the processing that was done. Custom data analysis and data validation algorithms were developed and applied to a data ensemble consisting of over 750 PIV 70 mm photographs taken in the 0.85 mach flow facility. Results are presented detailing spatial characteristics of the flow including ensemble mean and standard deviation, turbulence intensities and Reynold's stress levels, and 2-point spatial correlations.

Blackshire, James L.↗

Development and Understanding of Nb 3 Sn films for radiofrequency applications through a sample-host 9-cell cavity

Nb 3 Sn is a promising advanced material under development for superconducting radiofrequency cavities. Past efforts have been focused primarily on small development-scale cavities, but large, often multi-celled cavities, are needed for particle accelerator applications. In this work, we report on successful Nb 3 Sn coatings on Nb in a 1 m-long 9-cell Nb sample-host cavity at Fermilab. The geometry of the first coating with only one Sn source made it possible to study the influence of Sn flux on the microstructure. Based on these results, we postulate a connection between recently observed anomalously large thin grains and uncovered niobium spots observed in the past by other authors (Trenikhina et al 2018 Supercond. Sci. Technol. 32 015004). A phenomenological model to explain how these anomalously large grains could form is proposed. Overall, this model is invoked to provide possible explanations for literature results from several groups and to guide key process parameters to achieve uniform vapor-diffusion coatings, when applied to complex structures as the multi-cell cavity under study.

43 PARTICLE ACCELERATORS↗

A Theory of Immersion Freezing

Immersion freezing is likely involved in the initiation of precipitation and determines to large extent the phase partitioning in convective clouds. Theoretical models commonly used to describe immersion freezing in atmospheric models are based on the classical nucleation theory which however neglects important interactions near the immersed particle that may affect nucleation rates. This work introduces a new theory of immersion freezing based on two premises. First, immersion ice nucleation is mediated by the modification of the properties of water near the particle-liquid interface, rather than by the geometry of the ice germ. Second, the same mechanism that leads to the decrease in the work of germ formation also decreases the mobility of water molecules near the immersed particle. These two premises allow establishing general thermodynamic constraints to the ice nucleation rate. Analysis of the new theory shows that active sites likely trigger ice nucleation, but they do not control the overall nucleation rate nor the probability of freezing. It also suggests that materials with different ice nucleation efficiency may exhibit similar freezing temperatures under similar conditions but differ in their sensitivity to particle surface area and cooling rate. Predicted nucleation rates show good agreement with observations for a diverse set of materials including dust, black carbon and bacterial ice nucleating particles. The application of the new theory within the NASA Global Earth System Model (GEOS-5) is also discussed.

Ice Nucleating particle↗

Microgravity Superagglomerates Produced By Silane And Acetylene

The size of the agglomerates produced in the upper portion of a flame is important for a variety of applications. Soot particle size and density effect the amount of radiative heat transfer from a fire to its surroundings. Particle size determines the lifetime of smoke in a building or in the atmosphere, and exposure hazard for smoke inhaled and deposited in the lungs. The visibility through a smoke layer and dectectability of the smoke are also greatly affected by agglomerate size. Currently there is limited understanding of soot growth with an overall dimension of 10 m and larger. In the case of polystyrene, smoke agglomerates in excess of 1 mm have been observed raining out from large fires. Unlike hydrocarbon fuels, silane has the advantage that silica particles are the major combustion product resulting in a particle volume fraction a factor of ten greater than that for a carbonaceous smoke. There are two very desirable properties of silica aero-gels that are important for both space and earth based applications. The first important property is its inertness to most oxidizing and reducing atmospheres. Therefore, silica aero-gels make excellent fire ablatives and can be used in very demanding applications. The second important property is that silica aero-gels are expected to have very high porosity (greater than 0.999), making them lightweight and ideal for aerospace applications. The added benefit of the high porosity is that they can be used as extremely efficient filters for many earth based applications as well. Evidence of the formation of superagglomerates in a laminar acetylene/air diffusion flame was found by Sorensen et al. [1]. An interconnecting web of super-agglomerates was observed to span the width of the soot plume in the region just above the flame tip and described as a gel state. It was observed that this gel state immediately breaks up into agglomerates as larges as 100 m due to buoyancy induced turbulence. Large soot agglomerates were observed in microgravity butane jet diffusion flames by Ito et al.[2]. Several other works to date have studied the effect of flame structure on soot volume fraction and agglomeration size in a microgravity environment.[3-4]. In microgravity the absence of buoyant convective flows increases the residence time in the flame and causes a broadening of the high temperature region in the flame. Both of these factors play a significant role in gas phase radiation and soot formation

Gokoglu, Suleyman↗

Model-Based Fatigue Prognosis of Fiber-Reinforced Laminates Exhibiting Concurrent Damage Mechanisms

Prognostics of large composite structures is a topic of increasing interest in the field of structural health monitoring for aerospace, civil, and mechanical systems. Along with recent advancements in real-time structural health data acquisition and processing for damage detection and characterization, model-based stochastic methods for life prediction are showing promising results in the literature. Among various model-based approaches, particle-filtering algorithms are particularly capable in coping with uncertainties associated with the process. These include uncertainties about information on the damage extent and the inherent uncertainties of the damage propagation process. Some efforts have shown successful applications of particle filtering-based frameworks for predicting the matrix crack evolution and structural stiffness degradation caused by repetitive fatigue loads. Effects of other damage modes such as delamination, however, are not incorporated in these works. It is well established that delamination and matrix cracks not only co-exist in most laminate structures during the fatigue degradation process but also affect each other's progression. Furthermore, delamination significantly alters the stress-state in the laminates and accelerates the material degradation leading to catastrophic failure. Therefore, the work presented herein proposes a particle filtering-based framework for predicting a structure's remaining useful life with consideration of multiple co-existing damage-mechanisms. The framework uses an energy-based model from the composite modeling literature. The multiple damage-mode model has been shown to suitably estimate the energy release rate of cross-ply laminates as affected by matrix cracks and delamination modes. The model is also able to estimate the reduction in stiffness of the damaged laminate. This information is then used in the algorithms for life prediction capabilities. First, a brief summary of the energy-based damage model is provided. Then, the paper describes how the model is embedded within the prognostic framework and how the prognostics performance is assessed using observations from run-to-failure experiments

Prognostics↗

Facilitating Machine Learning Collaborations Between Labs, Universities, And Industry

It is clear from numerous recent community reports, papers, and proposals that machine learning is of tremendous interest for particle accelerator applications. The quickly evolving landscape continues to grow in both the breadth and depth of applications including physics modeling, anomaly detection, controls, diagnostics, and analysis. Consequently, laboratories, universities, and companies across the globe have established dedicated machine learning (ML) and data science efforts aiming to make use of these new state-of-the-art tools. The current funding environment in the U.S. is structured in a way that supports specific application spaces rather than larger collaboration on community software. Here, we discuss the existing collaboration bottlenecks and how a shift in the funding environment, and how we develop collaborative tools, can help fuel the next wave of ML advancements for particle accelerators.

Edelen, J.P.↗

A Reconfigurable Neural Network ASIC for Detector Front-End Data Compression at the HL-LHC

Despite advances in the programmable logic capabilities of modern trigger systems, a significant bottleneck remains in the amount of data to be transported from the detector to off-detector logic where trigger decisions are made. We demonstrate that a neural network (NN) autoencoder model can be implemented in a radiation-tolerant application-specific integrated circuit (ASIC) to perform lossy data compression alleviating the data transmission problem while preserving critical information of the detector energy profile. For our application, we consider the high-granularity calorimeter from the Compact Muon Solenoid (CMS) experiment at the CERN Large Hadron Collider. The advantage of the machine learning approach is in the flexibility and configurability of the algorithm. By changing the NN weights, a unique data compression algorithm can be deployed for each sensor in different detector regions and changing detector or collider conditions. To meet area, performance, and power constraints, we perform quantization-aware training to create an optimized NN hardware implementation. The design is achieved through the use of high-level synthesis tools and the hls4ml framework and was processed through synthesis and physical layout flows based on a low-power (LP)-CMOS 65-nm technology node. The flow anticipates 200 Mrad of ionizing radiation to select gates and reports a total area of 3.6 mm 2 and consumes 95 mW of power. The simulated energy consumption per inference is 2.4 nJ. Furthermore, this is the first radiation-tolerant on-detector ASIC implementation of an NN that has been designed for particle physics applications.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Particle-in-cell simulation of laser wakefield accelerators with oblique lasers in quasicylindrical geometry

In the studies of optical injections in laser or beam-driven wakefield accelerators, there is a frequent demand for using obliquely propagating assistant lasers in particle-in-cell simulations. In conventional methods, this is only possible in either two- or three-dimensional Cartesian geometries, which have the drawbacks of either lack of fidelity for the actual situation or requiring a huge amount of computational resources. In this work, we develop a new method that uses an expression-defined oblique laser field to simulate such situations in quasicylindrical geometry particle-in-cell simulations, having the advantages of both maintaining good fidelity and saving computational resources. As an example, we use this method in the scissor-cross ionization injection scheme for the optimization of the injected beam quality. This method is widely applicable to particle injections with assistant lasers in wakefield accelerators, as long as the assistant lasers only influence the injected particles during the injection process. Published by the American Physical Society 2025

Ma, Minghao (ORCID:0009000602317775)↗

Spatiotemporal Structure in Intense THz Pulsed Beams

Optically generated terahertz radiation, with gigavolt per meter (GV/m) electric fields accessible in tabletop experiments, provides a promising source of accelerating gradients for future particle accelerator applications. Manipulation and characterization of radiation is essential for efficiently producing high fields and effectively delivering them to an accelerating structure or interaction region. The talk will cover a method of generating and characterizing high quality and structured terahertz pulsed laser beams for compact particle acceleration.

Hine, George↗