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At least 1,729 records · Page 96

Upset Simulation and Training Initiatives for U.S. Navy Commercial Derived Aircraft

Militarized versions of commercial platforms are growing in popularity due to many logistical benefits in the form of commercial off-the-shelf (COTS) parts, established production methods, and commonality for different certifications. Commercial data and best practices are often leveraged to reduce procurement and engineering development costs. While the developmental and cost reduction benefits are clear, these militarized aircraft are routinely operated in flight at significantly different conditions and in significantly different manners than for routine commercial flight. Therefore they are at a higher risk of flight envelope exceedance. This risk may lead to departure from controlled flight and/or aircraft loss1. Historically, the risk of departure from controlled flight for military aircraft has been mitigated by piloted simulation training and engineering analysis of typical aircraft response. High-agility military aircraft simulation databases are typically developed to include high angles of attack (AoA) and sideslip due to the dynamic nature of their missions and have been developed for many tactical configurations over the previous decades. These aircraft simulations allow for a more thorough understanding of the vehicle flight dynamics characteristics at high AoA and sideslip. In recent years, government sponsored research on transport airplane aerodynamic characteristics at high angles of attack has produced a growing understanding of stall/post-stall behavior. This research along with recent commercial airline training initiatives has resulted in improved understanding of simulator-based training requirements and simulator model fidelity.2-5 In addition, inflight training research over the past decade has produced a database of pilot performance and recurrency metrics6. Innovative solutions to aerodynamically model large commercial aircraft for upset conditions such as high AoA, high sideslip, and ballistic damage, as well as capability to accurately account for scaling factors, is necessary to develop realistic engineering and training simulations. Such simulations should significantly reduce the risk of departure from controlled flight, loss of aircraft, and ease the airworthiness certification process. The characteristics of commercial derivative aircraft are exemplified by the P-8A Multi-mission Maritime Aircraft (MMA) aircraft, and the largest benefits of initial investigation are likely to be yielded from this platform. The database produced would also be utilized by flight dynamics engineers as a means to further develop and investigate vehicle flight characteristics as mission tactics evolve through the years ahead. This paper will describe ongoing efforts by the U.S. Navy to develop a methodology for simulation and training for large commercial-derived transport aircraft at unusual attitudes, typically experienced during an aircraft upset. This methodology will be applied to a representative Navy aircraft (P-8A) and utilized to develop a robust simulation that should accurately represent aircraft response in these extremes. Simulation capabilities would then extend to flight dynamics analysis and simulation, as well as potential training applications. Recent evaluations of integrated academic, ground-based simulation, and in-flight upset training will be described along with important lessons learned, specific to military requirements.

Donaldson, Steven↗

Sampling Technique for Robust Odorant Detection Based on MIT RealNose Data

This technique enhances the detection capability of the autonomous Real-Nose system from MIT to detect odorants and their concentrations in noisy and transient environments. The lowcost, portable system with low power consumption will operate at high speed and is suited for unmanned and remotely operated long-life applications. A deterministic mathematical model was developed to detect odorants and calculate their concentration in noisy environments. Real data from MIT's NanoNose was examined, from which a signal conditioning technique was proposed to enable robust odorant detection for the RealNose system. Its sensitivity can reach to sub-part-per-billion (sub-ppb). A Space Invariant Independent Component Analysis (SPICA) algorithm was developed to deal with non-linear mixing that is an over-complete case, and it is used as a preprocessing step to recover the original odorant sources for detection. This approach, combined with the Cascade Error Projection (CEP) Neural Network algorithm, was used to perform odorant identification. Signal conditioning is used to identify potential processing windows to enable robust detection for autonomous systems. So far, the software has been developed and evaluated with current data sets provided by the MIT team. However, continuous data streams are made available where even the occurrence of a new odorant is unannounced and needs to be noticed by the system autonomously before its unambiguous detection. The challenge for the software is to be able to separate the potential valid signal from the odorant and from the noisy transition region when the odorant is just introduced.

Duong, Tuan A.↗

Description of Alicyclobacillus montanus sp. nov., a mixotrophic bacterium isolated from acidic hot springs

Three morphologically similar thermo-acidophilic strains, USBA-GBX-501, USBA-GBX-502 and USBA-GBX-503T, were isolated from acidic thermal springs at the National Natural Park Los Nevados (Colombia). All isolates were spore-forming, Gram-stain-positive and motile, growing aerobically at 25–55°C (optimum ~45°C) and at pH 1.5–4.5 (optimum pH ~3.0). Phylogenetic analysis of the 16S rRNA gene sequences of these isolates showed an almost identical sequence (99.0% similarity) and they formed a robust cluster with the closest relative Alicyclobacillus tolerans DSM 16297 T with a sequence similarity of 99.0%. Average similarity to other species of the genus Alicyclobacillus was 93.0% and average similarity to species of the genus Effusibacillus was 90%. In addition, the level of DNA–DNA hybridization between strain USBA-GBX-503 T and Alicyclobacillus tolerans DSM 16297 T was 31.7 %. The genomic DNA G+C content of strain USBA-GBX-503 T was 44.6 mol%. The only menaquinone was MK-7 (100.0%). No ω-alicyclic fatty acids were detected in strain USBA-GBX-503 T , and the major cellular fatty acids were C18:1ω7c, anteiso-C17:0 and iso-C17:0. Based on phenotypic and chemotaxonomic characteristics, phylogenetic analysis and DNA–DNA relatedness values, along with low levels of identity at the whole genome level (ANIb and ANIm values of <67.0 and <91.0%, respectively), it can be concluded that strain USBA-GBX-503 T represents a novel species of the genus Alicyclobacillus , for which the name Alicyclobacillus montanus sp. nov. is proposed. The type strain is USBA-GBX-503 T (=CMPUJ UGB U503 T =CBMAI1927 T ).

López, G.↗

Developing Asparagaceae1726: An Asparagaceae‐specific probe set targeting 1726 loci for Hyb‐Seq and phylogenomics in the family

Abstract Premise Target sequence capture (Hyb‐Seq) is a cost‐effective sequencing strategy that employs RNA probes to enrich for specific genomic sequences. By targeting conserved low‐copy orthologs, Hyb‐Seq enables efficient phylogenomic investigations. Here, we present Asparagaceae1726—a Hyb‐Seq probe set targeting 1726 low‐copy nuclear genes for phylogenomics in the angiosperm family Asparagaceae—which will aid the often‐challenging delineation and resolution of evolutionary relationships within Asparagaceae. Methods Here we describe and validate the Asparagaceae1726 probe set (https://github.com/bentzpc/Asparagaceae1726) in six of the seven subfamilies of Asparagaceae. We perform phylogenomic analyses with these 1726 loci and evaluate how inclusion of paralogs and bycatch plastome sequences can enhance phylogenomic inference with target‐enriched data sets. Results We recovered at least 82% of target orthologs from all sampled taxa, and phylogenomic analyses resulted in strong support for all subfamilial relationships. Additionally, topology and branch support were congruent between analyses with and without inclusion of target paralogs, suggesting that paralogs had limited effect on phylogenomic inference. Discussion Asparagaceae1726 is effective across the family and enables the generation of robust data sets for phylogenomics of any Asparagaceae taxon. Asparagaceae1726 establishes a standardized set of loci for phylogenomic analysis in Asparagaceae, which we hope will be widely used for extensible and reproducible investigations of diversification in the family.

Plant Sciences↗

Chemo-mechanical-microstructural coupling in the tarsus exoskeleton of the scorpion Scorpio palmatus

The multiscale structure of biomaterials enables their exceptional mechanical robustness, yet the impact of each constituent at their relevant length scale remains elusive. Here, we used SAXD analysis to expose the intact chitin-fiber architecture within the exoskeleton on a scorpion's claw, revealing varying orientations, including Bouligand and unidirectional regions different from other arthropod species. We uncovered the contribution of individual components’ constituent behavior to its mechanical properties from the micro- to the nanoscale. At the microscale, in-situ micromechanical experiments were used to determine site-specific stiffness, strength, and failure of the biocomposite due to fiber orientation, while metal-crosslinking of proteins is characterized via fluorescence maps. At the constituent level, combined with FEA simulations, we uncovered the behavior of fiber-matrix deformation with fiber diameter <53.7 nm and protein modulus in the range 1.4–11 MPa. The unveiled microstructure-mechanics relationship sheds light on the evolved structural functionalities and constituents' interactions within the scorpion cuticle.

59 BASIC BIOLOGICAL SCIENCES↗

Market-driven automotive industry compliance with fuel economy and greenhouse gas standards: Analysis based on consumer choice

This paper explored factors that affect market-driven compliance with both Corporate Average Fuel Economy (CAFE) and greenhouse gas (GHG) standards (together called the National Program) in the United States for phase I 2012–2016 and phase II 2017–2025. We considered a consumer-choice-based simulation approach, using the MA3T model, to estimate the market acceptance of fuel efficiency (FE) technologies and alternative fuel technologies as reflected by new sales of light-duty vehicle (LDV). Because both full and extremely low FE valuations are common in the literature, we use a moderate assumption of a 10-year perceived vehicle lifetime at a 7% annual discount rate in the baseline and include both extreme views (5 years and 15 years) in the sensitivity analysis. The study focuses on market-driven compliance and therefore excludes manufacturers’ cross-subsidization. The model results suggest that the LDV industry is able to comply with both standards even without cross-subsidization and with projected high technology cost, mainly thanks to the multiple credit programs and technology advancements. The compliance robustness, while encouraging, however is based on moderate market assumptions, such as Annual Energy Outlook 2016 Reference oil price projection and moderate FE consumer valuation. Finally, sensitivity analysis results reveal two significant risk factors for compliance: low oil prices and consumers’ FE undervaluation.

54 ENVIRONMENTAL SCIENCES↗

A new polymer nanocomposite repair material for restoring wellbore seal integrity

Seal integrity of functional oil wells and abandoned wellbores used for CO 2 subsequent storage has become of significant interest with the oil and gas leaks worldwide. This is attributed to the fact that wellbores intersecting geographical formations contain potential leakage pathways. One of the critical leakage pathways is the cement-shale interface. In this study, we examine the efficiency of a new polymer nanocomposite repair material that can be injected for sealing micro annulus in wellbores. The bond strength and microstructure of the interface of Type G oil well cement (reference), microfine cement, Novolac epoxy incorporating Neat, 0.25%, 0.5%, and 1.0% Aluminum Nanoparticles (ANPs) with shale is investigated. Interfacial bond strength testing shows that injected microfine cement repair has considerably low bond strength, while ANPs-epoxy nanocomposites have a bond strength that is an order of magnitude higher than cement. Microscopic investigations of the interface show that micro annulus interfacial cracks with widths up to 40 μm were observed at the cement-shale interface while these cracks were absent at the cement-epoxy-shale interface. Finally, Fourier Transform Infrared and Dynamic mechanical analysis measurements showed that ANPs improve interfacial bond by limiting epoxy crosslinking, and therefore allowing epoxy to form robust bonds with cement and shale.

36 MATERIALS SCIENCE↗

Importance of limiting hohlraum leaks at cryogenic temperatures on NIF targets

Inertial confinement fusion targets are complex systems designed to allow fine control of temperature and pressure for making precise spherical ice layers of hydrogen isotopes at cryogenic temperatures. We discuss the various technical considerations for a maximum leak rate based on heat load considerations. This maximum flow rate turns out to be $5\times 10^{-6}$ standard cc per second, which can be caused by an orifice less than half a micron in diameter. This makes the identification of the location and resolution of the leak a significant challenge. To illustrate this, we showcase one example of a peculiar failure mode that appeared suddenly but persisted whereby target production yield was severely lowered. Identification of the leak source and the root cause requires very careful analysis of multiple thermomechanical aspects to ensure that the end solution is indeed the right remedy and is robust.

36 MATERIALS SCIENCE↗

Automated “Cells-To-Peptides” Sample Preparation Workflow for High-Throughput, Quantitative Proteomic Assays of Microbes

Mass spectrometry-based quantitative proteomic analysis has proven valuable for clinical and biotechnology-related research and development. Improvements in sensitivity, resolution, and robustness of mass analyzers have also added value. However, manual sample preparation protocols are often a bottleneck for sample throughput and can lead to poor reproducibility, especially for applications where thousands of samples per month must be analyzed. To alleviate these issues, we developed a “cells-to-peptides” automated workflow for Gram-negative bacteria and fungi that includes cell lysis, protein precipitation, resuspension, quantification, normalization, and tryptic digestion. The workflow takes 2 h to process 96 samples from cell pellets to the initiation of the tryptic digestion step and can process 384 samples in parallel. We measured the efficiency of protein extraction from various amounts of cell biomass and optimized the process for standard liquid chromatography–mass spectrometry systems. The automated workflow was tested by preparing 96 Escherichia coli samples and quantifying over 600 peptides that resulted in a median coefficient of variation of 15.8%. Similar technical variance was observed for three other organisms as measured by highly multiplexed LC-MRM–MS acquisition methods. These results show that this automated sample preparation workflow provides robust, reproducible proteomic samples for high-throughput applications.

59 BASIC BIOLOGICAL SCIENCES↗

Intermediate States Enable Keratin-like α-To-β Transformations in Strain-Responsive Synthetic Polypeptides

Nature’s fibrous proteins, such as α-keratin, achieve remarkable mechanical properties by undergoing strain-induced α-to-β conformational transitions. Inspired by these materials, we report a strategy for designing synthetic polypeptides that undergo similar transformations at elevated temperatures far exceeding keratin’s operational range. By employing helix-confined ring-opening polymerization (ROP) of N -carboxyanhydrides (NCAs) initiated by a short poly(γ-benzyl- L -glutamate) (PBLG) precursor, we synthesized poly( O -benzyl- L -serine) (PBLS) chains that adopt an α-helical structure yet transition into β-sheets upon heating. Compression molding at carefully chosen temperatures drives PBLS segments into an α-β intermediate state, characterized by relaxed intrachain hydrogen bonds and a hexagonal packing arrangement. Under mechanical strain, these intermediate states convert in situ into β-sheets, producing significant strain-hardening well below the spontaneous α-to-β temperature threshold. Further, this approach extends to polypeptides bearing different side chains, such as poly(S-benzyl- L -cysteine), demonstrating robust mechanical reinforcement across a wide temperature window up to ∼ 200 °C. In situ synchrotron X-ray analysis confirms that chain alignment, β-sheet formation, and domain growth occur stepwise during deformation. By harnessing the intermediate states and the supramolecular cooperativity conferred by compression-molded films, our method provides a versatile platform for developing next-generation polypeptide materials with tunable mechanical resilience and responsiveness─surpassing the temperature limitations of natural fibrous proteins and enabling potential applications demanding broad-temperature mechanical adaptability.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Chapter 7: Systems Engineering and Optimization of Wind Turbines and Power Plants

In this chapter, wind turbine optimization has been demonstrated as an effective approach to exploring complex design decisions. However, it is not a push-button solution and effective use requires a multidisciplinary design team and expertise in optimization algorithms. Common techniques include using reduced-order models for computationally intensive portions of the analysis, taking advantage of gradients to solve large problems, and more recently to include UQ to allow for robust design decisions. Current efforts continue to push for increased model fidelity, more comprehensive disciplinary coverage, and incorporation of uncertainty.

17 WIND ENERGY↗

A deep learning enabler for nonintrusive reduced order modeling of fluid flows

Here in this paper, we introduce a modular deep neural network (DNN) framework for data-driven reduced order modeling of dynamical systems relevant to fluid flows. We propose various DNN architectures which numerically predict evolution of dynamical systems by learning from either using discrete state or slope information of the system. Our approach has been demonstrated using both residual formula and backward difference scheme formulas. However, it can be easily generalized into many different numerical schemes as well. We give a demonstration of our framework for three examples: (i) Kraichnan-Orszag system, an illustrative coupled nonlinear ordinary differential equation, (ii) Lorenz system exhibiting chaotic behavior, and (iii) a nonintrusive model order reduction framework for the two-dimensional Boussinesq equations with a differentially heated cavity flow setup at various Rayleigh numbers. Using only snapshots of state variables at discrete time instances, our data-driven approach can be considered truly nonintrusive since any prior information about the underlying governing equations is not required for generating the reduced order model. Our a posteriori analysis shows that the proposed data-driven approach is remarkably accurate and can be used as a robust predictive tool for nonintrusive model order reduction of complex fluid flows.

42 ENGINEERING↗

Thermal degradation of the solvent employed in the next-generation caustic-side solvent extraction process and its effect on the extraction, scrubbing, and stripping of cesium

As part of the ongoing development of the Next-Generation Caustic-Side Solvent Extraction (NGS) process, the thermal stability of the process solvent was investigated and shown to be adequate for industrial application. The solvent was thermally treated at 35 C over a period of 13 months whilst in dynamic contact with each of the aqueous phases of the current NGS process, namely SRS 15 (a highly caustic waste simulant), sodium hydroxide scrub solution (0.025 M), and boric acid strip solution (0.01 M). The effect of thermal treatment was evaluated by assessing batch extract/scrub/strip performance as a function of time, by monitoring the sodium extraction capacity of the solvent, and by analysis of the solvent using electrospray mass spectrometry. Current studies indicate that the NGS solvent should be thermally robust for a period of XXX months at the Modular Caustic-Side Solvent Extraction Unit (MCU) pilot plant located at Savannah River Site. Furthermore, the guanidine suppressor appears to be the solvent component most significantly impacted by thermal treatment of the solvent, showing significant degradation over time.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Optical follow-up of gravitational wave triggers with DECam

Gravitational wave (GW) events have several possible progenitors, including black hole mergers, cosmic string cusps, supernovae, neutron star mergers, and black hole{neutron star mergers. A subset of GW events are expected to produce electromagnetic (EM) emission that, once detected, will provide complementary information about their astrophysical context. To that end, the LIGO-Virgo Collaboration has partnered with other teams to send GW candidate alerts so that searches for their EM counterparts can be pursued. One such partner is the Dark Energy Survey (DES) and Dark Energy Camera (DECam) Gravitational Waves Program (DES- GW). Situated on the 4m Blanco Telescope at the Cerro Tololo Inter-American Observatory in Chile, DECam is an ideal instrument for optical followup observations of GW triggers in the southern sky. The DES-GW program performs subtraction of new search images with respect to preexisting overlapping images to select candidate sources. Due to the short decay timescale of the expected EM counterparts and the need to quickly eliminate survey areas with no counterpart candidates, it is critical to complete the initial analysis of each night's images within 24 hours. The computational challenges in achieving this goal include maintaining robust I/O pipelines during the processing, being able to quickly acquire template images of new sky regions outside of the typical DES observing regions, and being able to rapidly provision additional batch computing resources with little advance notice. We will discuss the search area determination, imaging pipeline, general data transfer strategy, and methods to quickly increase the available amount of batch computing. We will present results from the rst season of observations from September 2015 to January 2016 and conclude by presenting improvements planned for the second observing season.

79 ASTRONOMY AND ASTROPHYSICS↗

Coefficient-to-Basis Network: a fine-tunable operator learning framework for inverse problems with adaptive discretizations and theoretical guarantees

We propose a Coefficient-to-Basis Network (C2BNet), a novel framework for solving inverse problems within the operator learning paradigm. C2BNet efficiently adapts to different discretizations through fine-tuning, using a pre-trained model to significantly reduce computational cost while maintaining high accuracy. Unlike traditional approaches that require retraining from scratch for new discretizations, our method enables seamless adaptation without sacrificing predictive performance. Furthermore, we establish theoretical approximation and generalization error bounds for C2BNet by exploiting low-dimensional structures in the underlying datasets. Our analysis demonstrates that C2BNet adapts to low-dimensional structures without relying on explicit encoding mechanisms, highlighting its robustness and efficiency. To validate our theoretical findings, we conducted extensive numerical experiments that showcase the superior performance of C2BNet on several inverse problems. The results confirm that C2BNet effectively balances computational efficiency and accuracy, making it a promising tool to solve inverse problems in scientific computing and engineering applications.

97 MATHEMATICS AND COMPUTING↗

Unique Gap Structure and Symmetry of the Charge Density Wave in Single-Layer VSe 2

Single layers of transition metal dichalcogenides (TMDCs) are great candidates for electronic applications beyond the graphene platform; many of them exhibit novel properties including charge density waves (CDWs) and magnetic ordering. CDWs in these single layers are typically a planar projection of the corresponding bulk CDWs because of the quasi-two-dimensional nature of TMDCs; a different CDW symmetry is unexpected. We report herein the successful creation of pristine single-layer VSe 2 , which shows a ($\sqrt{7}×\sqrt{3}$) CDW in contrast to the (4×4) CDW for the layers in bulk VSe 2 . Angle-resolved photoemission spectroscopy from the single layer shows a sizable ($\sqrt{7}×\sqrt{3}$) CDW gap of ~100 meV at the zone boundary, a 220 K CDW transition temperature twice the bulk value, and no ferromagnetic exchange splitting as predicted by theory. This robust CDW with an exotic broken symmetry as the ground state is explained via a first-principles analysis. The findings illustrate a unique CDW phenomenon in the two-dimensional limit.

36 MATERIALS SCIENCE↗

Experimental determination of precision, resolution, accuracy and trueness of time-of-flight neutron diffraction strain measurements

We discuss a simple statistical analysis which yields the precision, resolution, accuracy and trueness of diffraction-based lattice strain measurements. The procedure consists of measuring the thermal expansion induced in each component of an ideal, non-reacting, two-component, crystalline powder sample in situ. One component, with a high coefficient of thermal expansion (CTE), serves as an internal thermometer. The quantities of interest are obtained by determining the smallest, statistically significant, thermal lattice strain which can be detected through diffraction analysis in the second, low CTE, component in response to controlled temperature changes. This procedure also provides a robust check of the alignment of the diffraction system and is able to reveal the presence of systematic errors. The application of this technique to a time-of-flight engineering diffractometer/strain scanner is presented.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗