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At least 217 records · Page 12

System data communication structures for active-control transport aircraft, volume 1

Candidate data communication techniques are identified, including dedicated links, local buses, broadcast buses, multiplex buses, and mesh networks. The design methodology for mesh networks is then discussed, including network topology and node architecture. Several concepts of power distribution are reviewed, including current limiting and mesh networks for power. The technology issues of packaging, transmission media, and lightning are addressed, and, finally, the analysis tools developed to aid in the communication design process are described. There are special tools to analyze the reliability and connectivity of networks and more general reliability analysis tools for all types of systems.

Hopkins, A. L.↗

CAPRI: Using a Geometric Foundation for Computational Analysis and Design

CAPRI (Computational Analysis Programming Interface) is a software development tool intended to make computerized design, simulation and analysis faster and more efficient. The computational steps traditionally taken for most engineering analysis (Computational Fluid Dynamics (CFD), structural analysis, etc.) are: Surface Generation, usually by employing a Computer Aided Design (CAD) system; Grid Generation, preparing the volume for the simulation; Flow Solver, producing the results at the specified operational point; Post-processing Visualization, interactively attempting to understand the results. It should be noted that the structures problem is more tractable than CFD; there are fewer mesh topologies used and the grids are not as fine (this problem space does not have the length scaling issues of fluids). For CFD, these steps have worked well in the past for simple steady-state simulations at the expense of much user interaction. The data was transmitted between phases via files. In most cases, the output from a CAD system could go IGES files. The output from Grid Generators and Solvers do not really have standards though there are a couple of file formats that can be used for a subset of the gridding (i.e. PLOT3D) data formats and the upcoming CGNS). The user would have to patch up the data or translate from one format to another to move to the next step. Sometimes this could take days. Instead of the serial approach to analysis, CAPRI takes a geometry centric approach. CAPRI is a software building tool-kit that refers to two ideas: (1) A simplified, object-oriented, hierarchical view of a solid part integrating both geometry and topology definitions, and (2) programming access to this part or assembly and any attached data. The connection to the geometry is made through an Application Programming Interface (API) and not a file system.

Haimes, Robert↗

Material coherence from trajectories via Burau eigenanalysis of braids

In this paper, we provide a numerical tool to study a material’s coherence from a set of 2D Lagrangian trajectories sampling a dynamical system, i.e., from the motion of passive tracers. We show that eigenvectors of the Burau representation of a topological braid derived from the trajectories have levelsets corresponding to components of the Nielsen–Thurston decomposition of the dynamical system. One can thus detect and identify clusters of space–time trajectories corresponding to coherent regions of the dynamical system by solving an eigenvalue problem. Unlike previous methods, the scalable computational complexity of our braid-based approach allows the analysis of large amounts of trajectories.

36 MATERIALS SCIENCE↗

Thermal scanning probe and laser lithography for patterning nanowire based quantum devices

Semiconductor nanowire (NW) quantum devices offer a promising path for the pursuit and investigation of topologically-protected quantum states, and superconducting and spin-based qubits that can be controlled using electric fields. Theoretical investigations into the impact of disorder on the attainment of dependable topological states in semiconducting nanowires with large spin–orbit coupling and g-factor highlight the critical need for improvements in both growth processes and nanofabrication techniques. In this work, we used a hybrid lithography tool for both the high-resolution thermal scanning probe lithography and high-throughput direct laser writing of quantum devices based on thin InSb nanowires with contact spacing of 200 nm. Electrical characterization demonstrates quasi-ballistic transport. The methodology outlined in this study has the potential to reduce the impact of disorder caused by fabrication processes in quantum devices based on 1D semiconductors.

36 MATERIALS SCIENCE↗

Geomorphic analyses from space imagery

One of the most obvious applications of space imagery to geomorphological analyses is in the study of drainage patterns and channel networks. LANDSAT, high altitude photography and other types of remote sensing imagery are excellent for depicting stream networks on a regional scale because of their broad coverage in a single image. They offer a valuable tool for comparing and analyzing drainage patterns and channel networks all over the world. Three aspects considered in this geomorphological study are: (1) the origin, evolution and rates of development of drainage systems; (2) the topological studies of network and channel arrangements; and (3) the adjustment of streams to tectonic events and geologic structure (i.e., the mode and rate of adjustment).

Morisawa, M.↗

Integrated Simulation Design Challenges to Support TPS Repair Operations

During the Orbiter Repair Maneuver (ORM) operations planned for Return to Flight (RTF), the Shuttle Remote Manipulator System (SRMS) must grapple the International Space Station (ISS), undock the Orbiter, maneuver it through a long duration trajectory, and orient it to an EVA crewman poised at the end of the Space Station Remote Manipulator System (SSRMS) to facilitate the repair of the Thermal Protection System (TPS). Once repair has been completed and confirmed, then the SRMS proceeds back through the trajectory to dock the Orbiter to the Orbiter Docking System. In order to support analysis of the complex dynamic interactions of the integrated system formed by the Orbiter, ISS, SRMS, and SSMS during the ORM, simulation tools used for previous ‘nominal’ mission support required substantial enhancements. These upgrades were necessary to provide analysts with the capabilities needed to study integrated system performance. Prevalent throughout this ORM operation is a dynamically varying topology. In other words, the ORM starts with the SRMS grappled to the mated Shuttle/ISS stack (closed loop topology), moves to an open loop chain topology consisting of the Shuttle, SRMS, and ISS, and then, at the repair configuration, extends the chain topology to one consisting of the Shuttle, SMS, ISS, and SSRMS/EVA crewman. The resulting long dynamic chain of vehicles and manipulators may exhibit significant motion between the Shuttle worksite and the EVA crewman due to the system flexibility throughout the topology (particularly within the SRMS/SSRMS joints and links). Since the attachment points of both manipulators span the flexible structure of the ISS, simulation analysis may also need to take that into consideration. Moreover, due to the lengthy time duration associated with the maneuver and repair, orbital effects become a factor and require the ISS vehicle control system to maintain active attitude control. Several facets of the ORM operation make the associated analytical efforts different from previous mission support, including: (1) the magnitude of the SRMS handled payload (Le., Orbiter class), (2) the orbital effects induced on the integrated system consisting of the large Shuttle and ISS masses connected by a light flexible SRMS, (3) long duration environmental consequences due to the lengthy operational times associated with the maneuver and repair of the TPS, (4) active attitude control (as opposed to free drift) interacting with the SRMS and SSRMS manipulators (also due to the length of the maneuver and repair), (5) relative dynamics between the EVA crewman and thc worksite influenced by the extended flexible topology. In order to meet these analysis challenges, an ORM simulation architecture was developed leveraging upon numerous pre-existing simulation elements to analyze the various subsystems individually. For example, core manipulator subsystem simulations for both the SRMS and SSRMS were originally combined to provide the dual-arm dynamics topology simulation (in the absence of orbital dynamics and vehicle control). This capability was later merged with the simulation used to analyze SRMS loading with a heavy payload in the orbital environment with an active payload control system (in this case, the ISS Attitude Control System (ACS)), configured for the ORM. The resulting worksite dynamics simulation, based off of the modified ORM simulation, provided the extended topological chain of vehicles and manipulators, while taking into account the orbital effects of both the Shuttle and ISS (as well as its ACS). Verification and validation (V&V) of these integrated simulations became a challenge in itself. A systematic approach needed to be developed such that integration simulation results could be tested against previous constituent simulations upon which these simulations were built. General V&V categories included: (1) core orbital state propagation, (2), stand-alone SRMS, (3) stand-alone SSRMS, (4) stand-alone ISS ACS, (5) integrated Shuttle, SRMS, ISS (with active ACS) in the orbital environment, and (5) dual-arm SRMS/SSRMS dynamics topology. Integrated simulation V&V run suites were created and correlated to verification runs from subsystem simulations, in order to establish the validity of the results. This paper discusses the simulation design challenges encountered while developing simulation capabilities to mirror the ORM operations. The paper also describes the incremental build approach that was utilized, starting with the subsystem simulation elements and integration into increasing more complex simulations until the resulting ORM worksite dynamics simulation had been assembled. Furthermore, the paper presents an overall integrated simulation V&V methodology based upon a subsystem level testing, integrated comparisons, and phased checkout.

Thermal Protection System↗

A Guide to Conquer the Biological Network Era Using Graph Theory

Networks are one of the most common ways to represent biological systems as complex sets of binary interactions or relations between different bioentities. In this article, we discuss the basic graph theory concepts and the various graph types, as well as the available data structures for storing and reading graphs. In addition, we describe several network properties and we highlight some of the widely used network topological features. We briefly mention the network patterns, motifs and models, and we further comment on the types of biological and biomedical networks along with their corresponding computer- and human-readable file formats. Finally, we discuss a variety of algorithms and metrics for network analyses regarding graph drawing, clustering, visualization, link prediction, perturbation, and network alignment as well as the current state-of-the-art tools. We expect this review to reach a very broad spectrum of readers varying from experts to beginners while encouraging them to enhance the field further.

59 BASIC BIOLOGICAL SCIENCES↗

Modelling Development in Radical (Co)Polymerization of Multivinyl Monomers

Radical polymerization (RP) of multivinyl monomers (MVMs) provides a facile solution for manipulating polymer topology and has received increasing attention due to their industrial and academic significance. Continuous efforts have been made to understand their mechanism, which is the key to regulating materials structure. Modelling techniques have become a powerful tool that can provide detailed information on polymerization kinetics which is inaccessible by experiments. Many publications have reported the combination of experiments and modelling for free radical polymerization (FRP) and reversible-deactivation radical polymerizations (RDRP) of MVMs. Herein, a minireview is presented for the most important modelling techniques and their applications in FRP/RDRP of MVMs. This review hopes to illustrate that the combination of modelling and wet experiments can be a great asset to polymer researchers and inspire new thinking for the future MVMs experiment optimization and product design.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Wigner meets ’t Hooft near the black hole horizon

Recent work on Euclidean quantum gravity, black hole thermodynamics, and the holographic principle has seen the return of random matrix models as a powerful tool. It is explained how they allow for the study of the physics well beyond the perturbative expansion. In fact, a fully nonperturbative treatment naturally unites the familiar approach of summing over smooth geometries of all topologies with the statistical approach to characterize the typical properties of a Hamiltonian. Remarkably, this leads to an explicit excavation of the underlying microstates of quantum gravity that has applications to the low-temperature dynamics of a large class of black holes.

Astronomy & Astrophysics↗

Knowledge-guided graph machine learning for spatially distributed prediction of daily discharge and nitrogen export dynamics

Spatially distributed prediction of streamflow and nitrogen export dynamics is essential for precision management of agricultural watersheds. While temporal deep learning models such as Long Short-Term Memory (LSTM) have shown strong performance at basin scales, their ability to generalize spatially is limited by insufficient representation of spatial dependencies and flow paths, particularly under data-scarce conditions. To address this gap, we propose HydroGraphNet, a knowledge-guided graph machine learning framework that integrates process-based knowledge and explicit spatial learning into temporal modeling. This framework incorporates directed graph topology to encode watershed connectivity and upstream inflows, with mass balance constraints to improve physical consistency. To enhance generalization in sparsely monitored regions, HydroGraphNet is pretrained on synthetic data generated by the SWAT+ (Soil and Water Assessment Tool Plus) model. We evaluated HydroGraphNet in the Upper Sangamon River Basin (44 HUC-12 subwatersheds, 2001–2020) against two LSTM baselines: a lumped basin-level model and a distributed variant. When benchmarked on SWAT+ simulations in pretraining, HydroGraphNet improved test NSEs by 8.9% (discharge) and 13.7% (NO₃–N load) in temporal extrapolation, and by 27.1% and 34.7% in spatial extrapolation, relative to the Lumped LSTM baseline. After fine-tuning with USGS monitoring data, the model achieved mean test NSE (KGE) scores of 0.768 (0.861) for discharge and 0.626 (0.664) for NO₃–N load, substantially outperforming baselines. Attribution analysis further highlighted the importance of upstream inflow representation and graph-based spatial learning in capturing cross-subwatershed dependencies. The model also reproduced seasonal hydrological and biogeochemical patterns consistent with known processes, demonstrating its robustness and process fidelity for spatially distributed prediction. Altogether, HydroGraphNet advances the integration of physical knowledge and spatially explicit learning in hydrological modeling, offering a generalizable framework for distributed modeling to support spatially targeted water quality management in data-scarce watersheds.

54 ENVIRONMENTAL SCIENCES↗

CFM-ID 4.0: More Accurate ESI MS/MS Spectral Prediction and Compound Identification

In the field of metabolomics, mass spectrometry (MS) is the method most commonly used for identifying and annotating metabolites. As this typically involves matching a given MS spectrum against an experimentally acquired reference spectral library, this approach is limited by the coverage and size of such libraries (which typically number in the thousands). These experimental libraries can be greatly extended by predicting the MS spectra of known chemical structures (which number in the millions) to create computational reference spectral libraries. To facilitate the generation of predicted spectral reference libraries we developed CFM-ID, a computer program that can accurately predict ESI-MS/MS spectrum for a given compound structure. CFM-ID is one of the best-performing methods for compound-to-mass-spectrum prediction, and also one of the top tools for in silico mass-spectrum-to-compound identification. This work improves CFM-ID’s ability to predict ESI-MS/MS spectra from compounds by: (1) learning parameters from features based on the molecular topology, (2) adding a new approach to ring cleavage that models such cleavage as a sequence of simple chemical bond dissociations and (3) expanding its hand-written rule-based predictor to cover more chemical classes, including acylcarnitines, acylcholines, flavonols, flavones, flavanones, and flavonoid glycosides. We demonstrate that this new version of CFM-ID (version 4.0) is significantly more accurate than previous CFM-ID versions, in terms of both EI-MS/MS spectral prediction and compound identification. CFM-ID 4.0 is available at http://cfmid4.wishartlab.com/ as a webservice and docker images can be downloaded at https://hub.docker.com/r/wishartlab/cfmid

Wang, Fei↗

XFEM Development for Modeling Crack Growth in Prototypical Welded Components

Nuclear power plant components are subjected to harsh operating environments that can lead to multiple degradation mechanisms in which fracture can play a prominent role. Predicting crack growth is important for assessing the integrity of welded components. The extended finite element method (XFEM) is an important tool for modeling such crack growth, and XFEM capabilities have been developed within the MOOSE framework. This report documents work in the MOOSE XFEM module to model fractures in three-dimensional representations of components using a topologically two-dimensional mesh to define cutting planes. Crack growth algorithms have been implemented to evolve the cutting mesh based on equations for stress corrosion cracking. Additionally, several usability and robustness improvements have been developed to enable three-dimensional fracture simulations. The cutting algorithms were demonstrated on a three-dimensional model of a prototypical reactor component undergoing stress corrosion cracking driven by idealized weld residual stresses. This is an incremental step toward using this capability to model more complex components with residual stresses computed through welding process simulations.

42 - ENGINEERING↗

Topological Characterization and Uncertainty Visualization of Atmospheric Rivers

Atmospheric rivers (ARs) are long, narrow regions of water vapor in the Earth's atmosphere that transport heat and moisture from the tropics to the mid-latitudes. ARs are often associated with extreme weather events in North America and contribute significantly to water supply and flood risk. However, characterizing ARs has been a major challenge due to the lack of a universal definition and their structural variations. Existing AR detection tools (ARDTs) produce distinct AR boundaries for the same event, making the risk assessment of ARs a difficult task. Understanding these uncertainties is crucial to improving the predictability of AR impacts, including their landfall areas and associated precipitation, which could cause catastrophic flooding and landslides over the coastal regions. In this work, we develop an uncertainty visualization framework that captures boundary and interior uncertainties, i.e., structural variations, of an ensemble of ARs that arise from a set of ARDTs. We first provide a statistical overview of the AR boundaries using the contour boxplots of Whitaker et al. that highlight the structural variations of AR boundaries based on their nesting relationships. We then introduce the topological skeletons of ARs based on Morse complexes that characterize the interior variation of an ensemble of ARs. We propose an uncertainty visualization of these topological skeletons, inspired by MetroSets of Jacobson et al. that emphasizes the agreements and disagreements across the ensemble members. Through case studies and expert feedback, we demonstrate that the two approaches complement each other, and together they could facilitate an effective comparative analysis process and provide a more confident outlook on an AR's shape, area, and onshore impact.

54 ENVIRONMENTAL SCIENCES↗

Optimal Communication Topology Determination and Sensor Selection for Independent Airspace Surveillance

The paper presents an approach to sensors selection and network topology determination for independent airspace surveillance with maximum outcome and minimum cost using ground based distributed sensing, computing and communication network infrastructure. The selection criteria includes minimum estimation error, maximum airspace coverage, minimum communication time and power consumption while guaranteeing the system observability and providing in-time quality information to a monitoring observer. The developed algorithm uses multi-objective optimization strategy taking into account trade-offs between conflicting objectives and relaxations for in time implementation. It is implemented utilizing graph theoretic tools. The approach is validated in a desktop simulation environment using synthetic sensors data generated for a simulated multi-vehicle flight scenario in the selected regional airspace.

Distributed sensing↗

De Novo Design of High‐Affinity Miniprotein Binders Targeting Francisella Tularensis Virulence Factor

Abstract Francisella tularensis poses considerable public health risk due to its high infectivity and potential for bioterrorism. Francisella‐like lipoprotein (Flpp3), a key virulence factor unique to Francisella, plays critical roles in infection and immune evasion, making it a promising target for therapeutic development. However, the lack of well‐defined binding pockets and structural information on native interactions has hindered structure‐guided ligand discovery against Flpp3. Here, we used a combination of physics‐based and deep‐learning methods to design high‐affinity miniprotein binders targeting two distinct sites on Flpp3. We identified four binders for site I with binding affinities ranging between 24–110 nM. For the second site, an initial binder showed a dissociation constant ( K D ) of 81 nM, and subsequent site saturation mutagenesis yielded variants with sub‐nanomolar affinities. Circular dichroism confirmed the topology of designed miniproteins. The X‐ray crystal structure of Flpp3 in complex with a site I binder is nearly identical to the design model (Cα root‐mean‐square deviation (RMSD): 0.9 Å). These designed miniproteins provide research tools to explore the roles of Flpp3 in tularemia and should enable the development of new therapeutic candidates.

Gokce‐Alpkilic, Gizem [Molecular Engineering and S↗

Thermodynamic modeling of the Nb-Ni system with uncertainty quantification using PyCalphad and ESPEI

Here, the Nb–Ni system is remodeled with uncertainty quantification (UQ) using software tools of PyCalphad and ESPEI (the Extensible, Self-optimizing Phase Equilibria Infrastructure) with the presently implemented capability of modeling site fraction based on Wyckoff positions. The five- and three-sublattice models are used to model the topologically close pack (TCP) μ-Nb 7 Ni 6 and δ-NbNi 3 phases according to their Wyckoff positions. The inputs for CALPHAD-based thermodynamic modeling include the thermochemical data as a function of temperature predicted by first-principles and phonon calculations based on density functional theory (DFT), ab initio molecular dynamics (AIMD) simulations, together with phase equilibrium and site fraction data in the literature. In addition to phase diagram and thermodynamic properties, the CALPHAD-based predictions of site fractions of Nb in μ-Nb 7 Ni 6 agree well with experimental data. Furthermore, the UQ estimation using the Markov Chain Monte Carlo (MCMC) method as implemented in ESPEI is applied to study the uncertainty of site fraction in μ-Nb 7 Ni 6 and enthalpy of mixing (ΔH mix ) in liquid.

36 MATERIALS SCIENCE↗

Detection of chiral spin fluctuations driven by frustration in Mott insulators

Topologically ordered states, such as chiral spin liquids, have been proposed as candidates that host fraction alized excitations. However, detecting chiral character or proximity to these nontrivial states remains a challenge. Resonant Raman scattering can be a powerful tool for detecting chiral fluctuations, as the 𝐴 2⁢𝑔 channel probes excitations with broken time-reversal symmetry and local chiral order. Here, we use exact diagonalization to characterize the resonant 𝐴 2⁢𝑔 channel, alongside two-magnon scattering in 𝐵 1⁢𝑔 and 𝐸 𝑔 channels, for the Hubbard model on lattices with increasing levels of geometric spin frustration, where tuning the incident energy near the Mott gap reveals strong chiral spin excitation intensity. In conclusion, increased spin frustration in the Mott insulator results in an overall softening of the Raman 𝐴 2⁢𝑔 response, indicating a tendency toward low energy chiral-chiral fluctuations in Mott insulators with magnetic frustration and proximity to chiral spin liquid states that can potentially be tuned by external perturbations.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Engineering a pure Dirac regime in ZrTe$_5$

Real-world topological semimetals typically exhibit Dirac and Weyl nodes that coexist with trivial Fermi pockets. This tends to mask the physics of the relativistic quasiparticles. Using the example of ZrTe _5 5 , we show that strain provides a powerful tool for in-situ tuning of the band structure such that all trivial pockets are pushed far away from the Fermi energy, but only for a certain range of Van der Waals gaps. Our results naturally reconcile contradicting reports on the presence or absence of additional pockets in ZrTe _5 5 , and provide a clear map of where to find a pure three-dimensional Dirac semimetallic phase in the structural parameter space of the material.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗