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137 records · Page 8

7. Space-Filling Toolpath Generation

Space-filling toolpaths are used to fill whatever space remains on a layer after closed-loop contours have been planned. They provide structure to the object, both supporting the geometry and creating solid surfaces. As such, there are two main types of space-filling toolpaths: infill and skin. Infill paths are sparse and meant to cover a large area quickly. Infill is typically not visible once a print is complete, because infill is covered by skins. Skins are the solid space-filling toolpaths meant to solidify the top and bottom of the object, which, unlike the sides of the object, are not completely covered by layering contours. Space-filling paths are typically planned by projecting a pattern over the layer, clipping the pattern at the boundary of the object, and then linking the remaining portions of the pattern. A subcategory of skin paths, called gradual infill, can be employed to densify the infill when approaching a top skin layer so that the print path of the top skin is sufficiently supported. Space-filling paths come in a variety of patterns to optimize how the space is filled. This chapter will discuss space-filling path categories, how to find the space for each path type, and how to apply the path type to generate toolpaths.

Roschli, Alex↗

Recent and Planned Improvements to the System Advisor Model (SAM)

This talk will focus on recent and planned modeling improvements to the NREL System Advisor ModelTM (SAM), with recently released features including PV hourly clipping correction, expanded geographic scope of SAM's NSRDB interface to Europe and Africa, and additional options for hybrids. Upcoming improvements include a case comparison feature, improved visualizations, and extensions of PVWatts for battery modeling and utility rate calculations.

batteries↗

Mu2e Tracker Electronics - Construction of a Straw Tracker

The Mu2e experiment, currently under construction at the Fermi National Accelerator Laboratory (FNAL) in Batavia, Illinois, is a particle physics experiment designed to detect Charged Lepton Flavor Violation (CLFV) via muon-to-electron conversion, a process beyond the Standard Model (BSM). One of the primary Mu2e detectors is the Straw Tracker, whose purpose is to measure the momentum of the electron, identify the signal, and reject background. The straw tubes are being read out by a total of 20,736 preamplifiers (preamps) within 36 planes that make up the Tracker. In this presentation, the installation of electronics into the Tracker, the implementation of anti-oscillation copper clips, and the process of installing fully constructed planes into the frame will be discussed in depth.

Lynch, Alec [UC, Berkeley]↗

House Advantage or House of Cards? Stacking the Deck for Data Videos Leads to Null Results: Preprint

Videos are becoming a ubiquitous means of sharing information on social media platforms. In response, data videos - short clips combining visualization with dynamic storytelling, audio descriptions, and spatial referencing - have gained popularity for communicating data. These affordances suggest that data videos might communicate data patterns, trends, and concepts more effectively than static visualizations, enhancing comprehension. However, existing research has not systematically tested this claim. To address this gap, we conducted three controlled studies to measure comprehension differences between data videos and static visualizations. Despite leveraging visual cues and audio explanations, no data video led to significantly better comprehension than an analogous static visualization. Our results suggest data videos are not categorically better and that future research should examine the tradeoffs between their engagement benefits and costs.

97 MATHEMATICS AND COMPUTING↗

Searches for New Physics With Muon Conversion at Fermilab and Triboson Production at the LHC

We report on several efforts to search for physics beyond the standard model of particle physics at broad energy scales. The Mu2e experiment at Fermilab will search for charged lepton flavor violation via the muon to electron conversion process, which is suppressed in the Standard Model. Mu2e will be operated at a low energy, yet can probe New Physics at very high mass scales (O(1e3 - 1e4 ) TeV). At high energies, the CMS experiment at the CERN LHC continues to deliver an impressive suite of Standard Model measurements and limits on a variety of New Physics signatures. Mu2e is under construction and slated to collect its first physics data in the coming years. This thesis describes work done during the construction phase of Mu2e and focuses on two critical areas: magnetic field modeling and statistical analysis. We describe a novel method for field modeling which we validate using a simulated dataset representing the expected magnetic field in the Detector Solenoid. This method blends a standard least-squares fitting technique that utilizes physically motivated analytical model functions with a novel physics informed network that is constructed to obey Maxwell’s equations. We show the technique can model the field with an accuracy of 10−7 despite the presence of injected noise in the pseudo-measurements at the 10−5 level. We then present preliminary results of the calibration of 3D Hall probes at the sub-10−4 level. These probes will be used to directly measure the Mu2e Detector Solenoid magnetic field on a sparse grid; these measurements serve as the input to the field model fitting. Finally, we describe the first implementation of both an unbinned shape analysis and a Bayesian interpretation applied to Mu2e pseudo-data. Up to 20% tighter limits can be set by the shape analysis compared to a standard cut & count analysis. The AlCap experiment collected data at PSI in 2015 to measure several important quantities related to nuclear muon capture on an aluminum target, which is a significant background process for Mu2e. The neutron emission from muon capture can introduce background hits in the Mu2e detectors and can increase radiation damage in various elements of the apparatus. We present measurements of the neutron group fluence and mean neutron multiplicity for muon capture on aluminum nuclei. Finally, we discuss an analysis of triboson production at CMS using an Effective Field Theory framework. Standard Model triboson production, which was first observed at CMS in 2020, has a relatively small cross section and provides direct access to both anomalous triple gauge couplings and quartic gauge couplings. These couplings, interpreted in the Standard Model Effective Field Theory, are studied in the present work. We target the boosted regime where the background rate is low and yields are enhanced when dimension-6 and dimension-8 Wilson coefficients are non-zero. We do not observe an excess in the data and therefore set bounds on the Wilson coefficients. For dimension-6 coefficients the tightest observed (expected) bounds are set on cW /Λ2 where Λ is the mass scale of new physics; the bounds are [−0.13, 0.12] TeV−2 ([−0.12, 0.12] TeV−2 ) at 95% CL. The tightest bounds in dimension-8 are set on fT,0 / Λ4 ; the observed (expected) bounds at 95% CL are [−0.63, 0.69] TeV−4 ([−0.54, 0.62] TeV−4 ). Additional results are presented which include scenarios where multiple Wilson coefficients are non-zero, the application of signal model clipping to address unitarity violation in Effective Field Theories, and a novel template fit developed for easier reinterpretation of our results.

Kampa, Cole Erik [Northwestern U. (main)] (ORCID:0↗

Mu2e Tracker Electronics - Construction of a Straw Tracker

The Mu2e experiment, located at the Fermi National Accelerator Laboratory (FNAL), also known as Fermilab, in Batavia, Illinois, is an in-progress particle physics experiment aiming to detect Charged Lepton Flavor Violation (CLFV) via the $\mu^-Al\rightarrow e^-Al$ interaction, a Beyond the Standard Model (BSM) process. One of the sections of the Mu2e experiment is the Tracker, which aims to identify the signal and reject the background while the experiment is running. A total of 20,736 Calibration (CAL) and High-Voltage (HV) preamplifiers (preamps) are being installed within 36 planes that make up the Tracker. During this process, MHz oscillations were discovered on the CAL preamps, obscuring desired signal detection in the \~kHz range. To solve this issue, copper clips are installed onto the CALs to remove the MHz oscillations. The installation of electronics into the Tracker will be discussed in depth.

Lynch, Alec Michael [UC, Berkeley; Fermilab]↗

MoRE-Brain: Routed Mixture of Experts for Interpretable and Generalizable Cross-Subject fMRI Visual Decoding

Decoding visual experiences from fMRI offers a powerful avenue to understand human perception and develop advanced brain-computer interfaces. However, current progress often prioritizes maximizing reconstruction fidelity while overlooking interpretability, an essential aspect for deriving neuroscientific insight. To address this gap, we propose MoRE-Brain, a neuro-inspired framework designed for high-fidelity, adaptable, and interpretable visual reconstruction. MoRE-Brain uniquely employs a hierarchical Mixture-of-Experts architecture where distinct experts process fMRI signals from functionally related voxel groups, mimicking specialized brain networks. The experts are first trained to encode fMRI into the frozen CLIP space. A finetuned diffusion model then synthesizes images, guided by expert outputs through a novel dual-stage routing mechanism that dynamically weighs expert contributions across the diffusion process. MoRE-Brain offers three main advancements: First, it introduces a novel Mixture-of-Experts architecture grounded in brain network principles for neuro-decoding. Second, it achieves efficient cross-subject generalization by sharing core expert networks while adapting only subject-specific routers. Third, it provides enhanced mechanistic insight, as the explicit routing reveals precisely how different modeled brain regions shape the semantic and spatial attributes of the reconstructed image. Extensive experiments validate MoRE-Brain’s high reconstruction fidelity, with bottleneck analyses further demonstrating its effective utilization of fMRI signals, distinguishing genuine neural decoding from over-reliance on generative priors. Consequently, MoRE-Brain marks a substantial advance towards more generalizable and interpretable fMRI-based visual decoding.

Wei, Yuxiang [Georgia Institute of Technology]↗

The Automatic Reactor Control System (ARCS) Upgrade, version 2.0 for TREAT

The Transient REActor Test Facility (TREAT) recently underwent an upgraded to the Automatic Reactor Control System (ARCS). The purpose of the upgrade was to institute a new software architecture that is better suited for the programming environment, patched software bugs and applied two new segments for reactor control. This paper will focus on the new segments for reactor control. The two new control segments added to ARCS are called Generic Power and Generic Rods. The original version of ARCS provided only two power related functions, namely periods and ramps, that had to be spliced together to generate any power shape. The Generic Power segment allows the user to input data points to define the function and then the algorithm does its best to create the desired shape. The original ARCS program utilized two direct rod commands (i.e. open loop control), these were a rod stop and clip. A Generic Rod segment extends the ability of the computer to directly command any rod position. The functionality of these new segments was proven during the TREAT outage in 2024.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗

High-throughput identification of novel heat tolerance genes via genome-wide pooled mutant screens in the model green alga Chlamydomonas reinhardtii

Different high temperatures adversely affect crop and algal yields with various responses in photosynthetic cells. The list of genes required for thermotolerance remains elusive. Additionally, it is unclear how carbon source availability affects heat responses in plants and algae. Here, we utilized the insertional, indexed, genome-saturating mutant library of the unicellular, eukaryotic green alga Chlamydomonas reinhardtii to perform genome-wide, quantitative, pooled screens under moderate (35°C) or acute (40°C) high temperatures with or without organic carbon sources. We identified heat-sensitive mutants based on quantitative growth rates and identified putative heat tolerance genes (HTGs). By triangulating HTGs with heat-induced transcripts or proteins in wildtype cultures and MapMan functional annotations, we presented a high/medium-confidence list of 933 Chlamydomonas genes with putative roles in heat tolerance. Triangulated HTGs include those with known thermotolerance roles and novel genes with little or no functional annotation. About 50% of these high-confidence HTGs in Chlamydomonas have orthologs in green lineage organisms, including crop species. Arabidopsis thaliana mutants deficient in the ortholog of a high-confidence Chlamydomonas HTG were also heat sensitive. This work expands our knowledge of heat responses in photosynthetic cells and provides engineering targets to improve thermotolerance in algae and crops.

59 BASIC BIOLOGICAL SCIENCES↗

PV Storm Hardening Costs

While solar arrays often survive severe weather events, systems are occasionally compromised and left unable to provide power. For PV systems to act as resilient power providers, they must remain operational. Building a system that is more likely to survive a storm comes at a cost, though. Previous efforts have identified various system measures and practices that can increase the likelihood of a PV system surviving a severe weather event. But what is the cost premium for a storm hardened PV system? This report provides initial estimates for the up-front cost premiums for various methods of storm hardening PV systems.

14 SOLAR ENERGY↗