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At least 1,621 records · Page 90

Aeroservoelasticity

The paper describes recent accomplishments and current research projects along four main thrusts in aeroservoelasticity at NASA Langley. One activity focuses on enhancing the modeling and analysis procedures to accurately predict aeroservoelastic interactions. Improvements to the minimum-state method of approximating unsteady aerodynamics are shown to provide precise low-order models for design and simulation tasks. Recent extensions in aerodynamic correction-factor methodology are also described. With respect to analysis procedures, the paper reviews novel enhancements to matched filter theory and random process theory for predicting the critical gust profile and the associated time-correlated gust loads for structural design considerations. Two research projects leading towards improved design capability are also summarized: (1) an integrated structure/control design capability and (2) procedures for obtaining low-order robust digital control laws for aeroelastic applications.

Noll, Thomas E.↗

HOXC10 promotes gastric cancer cell invasion and migration via regulation of the NF-κB pathway

Homeobox gene C10 (HOXC10), known to regulate cell differentiation and proliferation, is upregulated in gastric cancer (GC). The mechanism underlying HOXC10 involvement in GC metastasis is unclear. Herein, we found that HOXC10 is overexpressed in GC relative to normal controls. In the 73 GC patients tissue microarrays (TMA) tested, HOXC10 expression was closely related with tumor-node-metastasis (TNM) stage, lymph node metastasis, and distant metastasis. HOXC10 overexpression tended to associate with low 5-year cumulative survival. Cox regression analysis identified HOXC10 as an independent prognostic factor for poor patient survival. HOXC10 promoted GC cell invasion and migration, regulated the expression of activated ATM and markers of NF-κB signaling. HOXC10 may promote invasion and migration of GC by regulating ATM/NF-κB signaling pathway. HOXC10 should be explored as a clinical marker of GC prognosis.

60 APPLIED LIFE SCIENCES↗

The NANOGrav nine-year data set: Limits on the isotropic stochastic gravitational wave background

We compute upper limits on the nanohertz-frequency isotropic stochastic gravitational wave background (GWB) using the 9 year data set from the North American Nanohertz Observatory for Gravitational Waves (NANOGrav) collaboration. Well-tested Bayesian techniques are used to set upper limits on the dimensionless strain amplitude (at a frequency of 1 yr{sup −1}) for a GWB from supermassive black hole binaries of A{sub gw}<1.5×10{sup −15}. We also parameterize the GWB spectrum with a broken power-law model by placing priors on the strain amplitude derived from simulations of Sesana and McWilliams et al. Using Bayesian model selection we find that the data favor a broken power law to a pure power law with odds ratios of 2.2 and 22 to one for the Sesana and McWilliams prior models, respectively. Using the broken power-law analysis we construct posterior distributions on environmental factors that drive the binary to the GW-driven regime including the stellar mass density for stellar-scattering, mass accretion rate for circumbinary disk interaction, and orbital eccentricity for eccentric binaries, marking the first time that the shape of the GWB spectrum has been used to make astrophysical inferences. Returning to a power-law model, we place stringent limits on the energy density of relic GWs, Ω{sub gw}(f)h{sup 2}<4.2 × 10{sup −10}. Our limit on the cosmic string GWB, Ω{sub gw}(f)h{sup 2}<2.2 × 10{sup −10}, translates to a conservative limit on the cosmic string tension with Gμ<3.3×10{sup −8}, a factor of four better than the joint Planck and high-l cosmic microwave background data from other experiments.

79 ASTRONOMY AND ASTROPHYSICS↗

Detecting CNO solar neutrinos in next-generation xenon dark matter experiments

We study the prospects for measuring the low-energy components of the solar neutrino flux in future direct dark matter detection experiments. We show that for a depletion of 136 Xe by a factor of 1000 relative to its natural abundance, and an extension to electron recoil energies of ~MeV, future xenon experiments with exposure ~1000 ton-yr can detect the carbon-nitrogen-oxygen (CNO) component of the solar neutrino flux at approximately three-sigma significance. A CNO detection will provide important insight into the metallicity of the solar interior. Precise measurement of low-energy solar neutrinos, including as pp, 7 Be, and pep components, will further improve constraints on the “neutrino luminosity” of the Sun, thereby providing constraints on alternative sources of energy production. Furthermore, we find that a measurement of L ν /L ⊙ of order 1% is possible with the above exposure, improving on current bounds from a global analysis of solar neutrino data by a factor of about 7.

79 ASTRONOMY AND ASTROPHYSICS↗

Economic Analysis in the Pacific Northwest Land Resources Project: Theoretical Considerations and Preliminary Results

The Pacific Northwest Land Resources Inventory Demonstration Project i s an a ttempt to combine a whole spectrum of heterogeneous geographic, institutional and applications elements in a synergistic approach to the evaluation of remote sensing techniques. This diversity is the prime motivating factor behind a theoretical investigation of alternative economic analysis procedures. For a multitude of reasons--simplicity, ease of understanding, financial constraints and credibility, among others--cost-effectiveness emerges as the most practical tool for conducting such evaluation determinatIons in the Pacific Northwest. Preliminary findings in two water resource application areas suggest, in conformity with most published studies, that Lands at-aided data collection methods enjoy substantial cost advantages over alternative techniques. The pntential for sensitivity analysis based on cost/accuracy tradeoffs is considered on a theoretical plane in the absence of current accuracy figures concerning the Landsat-aided approach.

Morse, D. R. A.↗

Hierarchical semi-Markov models with duration-aware dynamics for activity sequences

Residential electricity demand at granular scales is driven by what people do and for how long. Accurately forecasting this demand for applications like microgrid management and demand response therefore requires generative models for activities that can produce realistic daily activity sequences, capturing both the timing and duration of human behavior. This paper develops a generative model of human activity sequences using nationally representative time-use diaries at a 10-min resolution. We use this model to quantify which demographic factors are most critical for improving predictive performance. We propose a hierarchical semi-Markov framework that addresses two key modeling challenges. First, a time-inhomogeneous Markov router learns the patterns of “which activity comes next.” Second, a semi-Markov hazard component explicitly models activity durations, capturing “how long” activities realistically last. To ensure statistical stability when data are sparse, the model pools information across related demographic groups and time blocks. The entire framework is trained and evaluated using survey design weights to ensure our findings are representative of the U.S. population. On a held-out test set, we demonstrate that explicitly modeling durations with the hazard component provides a substantial and statistically significant improvement over purely Markovian models. Furthermore, our analysis reveals a clear hierarchy of demographic factors: Sex, Day-Type, and Household Size provide the largest predictive gains, while Region and Season, though important for energy calculations, contribute little to predicting the activity sequence itself. The result is an interpretable and robust generator of synthetic activity traces, providing a high-fidelity foundation for downstream energy systems modeling.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Overheating Anomalies during Flight Test Due to the Base Bleeding

In this paper we present the results of the analytical and numerical studies of the plume interaction with the base flow in the presence of base out-gassing. The physics-based analysis and CFD modeling of the base heating for single solid rocket motor performed in this research addressed the following questions: what are the key factors making base flow so different from that in the Shuttle [1]; why CFD analysis of this problem reveals small plume recirculation; what major factors influence base temperature; and why overheating was initiated at a given time in the flight. To answer these questions topological analysis of the base flow was performed and Korst theory was used to estimate relative contributions of radiation, plume recirculation, and chemically reactive out-gassing to the base heating. It was shown that base bleeding and small base volume are the key factors contributing to the overheating, while plume recirculation is effectively suppressed by asymmetric configuration of the flow formed earlier in the flight. These findings are further verified using CFD simulations that include multi-species gas environment both in the plume and in the base. Solid particles in the exhaust plume (Al2O3) and char particles in the base bleeding were also included into the simulations and their relative contributions into the base temperature rise were estimated. The results of simulations are in good agreement with the temperature and pressure in the base measured during the test.

base bleeding↗

Stress Analysis of Columns and Beam Columns by the Photoelastic Method

Principles of similarity and other factors in the design of models for photoelastic testing are discussed. Some approximate theoretical equations, useful in the analysis of results obtained from photoelastic tests are derived. Examples of the use of photoelastic techniques and the analysis of results as applied to uniform and tapered beam columns, circular rings, and statically indeterminate frames, are given. It is concluded that this method is an effective tool for the analysis of structures in which column action is present, particularly in tapered beam columns, and in statically indeterminate structures in which the distribution of loads in the structures is influenced by bending moments due to axial loads in one or more members.

BEAM-COLUMNS - STRESSES↗

Transcriptome Profiling of Rust Resistance in Switchgrass Using RNA-Seq Analysis

Switchgrass rust caused by Puccinia emaculata is a major limiting factor for switchgrass (Panicum virgatum L.) production, especially in monoculture. Natural populations of switchgrass displayed diverse reactions to P. emaculata when evaluated in an Ardmore, OK, field. In order to identify the differentially expressed genes during the rust infection process and the mechanisms of switchgrass rust resistance, transcriptome analysis using RNA-Seq was conducted in two pseudo-F 1 parents ('PV281' and 'NFGA472'), and three moderately resistant and three susceptible progenies selected from a three-generation, four-founder switchgrass population (K5 x A4) x (AP13 x VS16). On average, 23.5 million reads per sample (leaf tissue was collected at 0, 24, and 60 h post-inoculation (hpi)) were obtained from paired-end (2 x 100 bp) sequencing on the Illumina HiSeq2000 platform. Furthermore, mapping of the RNA-Seq reads to the switchgrass reference genome (AP13 ver. 1.1 assembly) constructed a total of 84,209 transcripts from 98,007 gene loci among all of the samples. Further analysis revealed that host defense- related genes, including the nucleotide binding site-leucinerich repeat domain containing disease resistance gene analogs, play an important role in resistance to rust infection. Rust-induced gene (RIG) transcripts inherited across generations were identified. The rust-resistant gene transcripts can be a valuable resource for developing molecular markers for rust resistance. Finally we identified the rust-resistant genotypes and gene transcripts which can expedite rust-resistant cultivar development in switchgrass.

59 BASIC BIOLOGICAL SCIENCES↗

Correlated Topics in a Scalable Multidimensional Text Cube: Algorithms and Aviation Safety Case Study

As world-wide air traffic continues to grow even at a modest pace, the overall complexity of the system will increase significantly. This increased complexity can lead to a larger number of fatalities per year even if the extremely low fatality rate that we currently enjoy is maintained. One important source of information about the safety of the aviation system is in Aviation Safety Text Reports which are written by members of the flight crew, air traffic controllers, and other parties involved with the aviation system. These anonymized narrative reports contain fixed-field contextual information about the flight but also contain free-form narratives that describe, in the author s own words, the nature of the safety incident and, in many cases, the contributing factors that led to the safety incident. Several thousand such reports are filed each month, each of which is read and analyzed by highly trained experts. However, it is possible that there are emerging safety issues due to the fact that they may be reported very infrequently and in different contexts with different descriptions. The goal of this research paper is to develop correlated topic models which uncover correlations in the subspaces defined by the intersection of numerous fixed fields and discovered correlated topics. This task requires the discovery of latent topics in the text reports and the creation of a topic cube. Furthermore, because the number of potential cells in the topic cube is very large, we discuss novel methods of pruning the search space in the topic cells, thereby making the analysis feasible. We demonstrate the new algorithms on an analysis of pilot fatigue and its contributing factors, as well as the safety incidents that are correlated with this phenomenon.

Zhao, Bo↗

Noise-Resilient Quantum Machine Learning for Stability Assessment of Power Systems

Transient stability assessment (TSA) is a cornerstone for resilient operations of todays interconnected power grids. This paper is a confluence of quantum computing, data science and machine learning to potentially address the power system TSA issue. Here, we devise a quantum TSA (QTSA) method to enable scalable and efficient data-driven transient stability prediction for bulk power systems, which is the first attempt to tackle the TSA issue with quantum computing. Our contributions are three-fold: 1) A high expressibility, low-depth (HELD) quantum circuit is designed for accurate and noise-resilient TSA; 2) A quantum natural gradient descent algorithm is developed for efficient HELD circuit training; 3) A systematical analysis on QTSAs performance under various quantum factors is per-formed. QTSA underpins a foundation of quantum-enabled and data-driven power grid stability analytics. It renders the intractable TSA straightforward and effortless in the Hilbert space, and therefore provides stability information for power system operations. Extensive experiments on quantum simulators and real quantum computers verify the accuracy, noise-resilience, scalability and universality of QTSA.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Multiscale Reactive Model for 1,3,5-Triamino-2,4,6-trinitrobenzene Inferred by Reactive MD Simulations and Unsupervised Learning

When high-energy-density materials are subjected to thermal or mechanical insults at extreme conditions (shock loading), a coupled response between the thermo-mechanical and chemical behaviors is systematically induced. Herein we develop a reaction model for the fast chemistry of 1,3,5-triamino-2,4,6-trinitrobenzene (TATB) at the mesoscopic scale, where the chemical behavior is determined by underlying microscopic reactive simulations. The slow carbon cluster formation is not discussed in the present work. All-atom reactive molecular dynamics (MD) simulations are performed with the ReaxFF potential, and a reduced-order chemical kinetics model for TATB is fitted to isothermal and adiabatic simulations of single crystal chemical decomposition. Unsupervised machine learning techniques based on non-negative matrix factorization are applied to MD trajectories to model the decomposition kinetics of TATB in terms of a four-component model. The associated heats of reaction are fit to the temperature evolution from adiabatic decomposition trajectories. Using a chemical species analysis, we show that non-negative matrix factorization captures the main chemical decomposition steps of TATB and provides an accurate estimation of their evolution with temperature. The final analytical formulation, coupled to a diffusion term, is incorporated into a continuum formalism, and simulation results are compared one-to-one against MD simulations of 1D reaction propagation along different crystallographic directions and with different initial temperatures. A good agreement is found for both the temporal and spatial evolution of the temperature field.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

View factor computer program (program view) user's manual

The purpose of program VIEW is to compute view factors between specified surfaces and to be compatible with level 15.5 of the NASTRAN structural analysis program. Program VIEW is a modification of a (finite element) view factor computation program called RAVFAC. VIEW is designed to run on an IBM System/360 operating under OS (operating system), with a minimum region size of 110 K bytes. The actual computation of view factors is still performed exactly as it was in the original version of RAVFAC. In developing VIEW, RAVFAC was modified to satisfy the following compatibility requirements: (1) accept finite element input which can also be used as input to NASTRAN, (2) produce output (view factors) in a format which can be used as input to NASTRAN, and (3) follow NASTRAN program design so that in the future VIEW can be incorporated into NASTRAN as a subroutine. The VIEW program permits computation of the view factors between surfaces, taking into account the presence of any intermediate surfaces. VIEW also computes these view factors either by contour integration or by finite difference (double summation) methods.

Puccinelli, E. F.↗

Substructure Versus Property-Level Dispersed Modes Calculation

This paper calculates the effect of perturbed finite element mass and stiffness values on the eigenvectors and eigenvalues of the finite element model. The structure is perturbed in two ways: at the "subelement" level and at the material property level. In the subelement eigenvalue uncertainty analysis the mass and stiffness of each subelement is perturbed by a factor before being assembled into the global matrices. In the property-level eigenvalue uncertainty analysis all material density and stiffness parameters of the structure are perturbed modified prior to the eigenvalue analysis. The eigenvalue and eigenvector dispersions of each analysis (subelement and property-level) are also calculated using an analytical sensitivity approximation. Two structural models are used to compare these methods: a cantilevered beam model, and a model of the Space Launch System. For each structural model it is shown how well the analytical sensitivity modes approximate the exact modes when the uncertainties are applied at the subelement level and at the property level.

Stewart, Eric C.↗

Further analysis of LDEF FRECOPA micrometeroid remnants

Experiments dedicated to the detection of interplanetary dust particles (IDP's) were exposed within the FRECOPA payload, installed on the face of the LDEF directly opposed to the velocity vector (west facing direction, location B3). We were mainly interested in the analysis of hypervelocity impact features of sizes less than or = 10 microns, found in thick Al targets devoted to the research of impact features. In the 15 craters found in the scanned area (approximately 4 sq. cm), the chemical analysis suggests an extraterrestrial origin for the impacting particles. The main elements we identified are usually refered to as chondrite elements: Na, Mg, Si, S, Ca, and Fe are found in various proportions, intrinsic Al being masked by the Al target; we notice a strong depletion in Ni, never observed in our samples. Furthermore, C and O are present in 90 percent of the cases; the C/O peak height ratio varies from 0.1 to 3. Impactor simulations by light gas gun hypervelocity impact experiments have shown that meaningful biogenic element and compound information maybe obtained from IDP residues below impacts of critical velocities, that are less than or = 4 km/sec for particles larger than 100 microns in diameter. Our results obtained for the smaller size fraction IDP's suggest that at such sizes, the critical velocity could be higher by a factor of 2 or 3, as chemical analysis of the remnants were possible in all the identified impact craters, performed on targets possibly hit at velocities greater than or = 7.5 km/s, which is the spacecraft velocity. These samples are now subjected to an imagery and analytical protocol that includes FESEM (field emission scanning electron microscopy) and LIMS (laser ionization mass spectrometry). The LIMS analyses were performed using the LIMA-ZA instrument. Results are presented, clearly indicating that such small events show crater features analogous to what is observed at larger sizes; our first analytical results, obtained for 2 events (P6 and P10) suggest that N is present in the IDP's remnants in which C and O were identified by EDX analysis. In one case (P6), enrichment in K and P is observed. Surface contamination by NaCl is evident on the FRECOPA surfaces.

Borg, J.↗

Spatial Mapping of Pyocyanin in Pseudomonas Aeruginosa Bacterial Communities Using Surface Enhanced Raman Scattering

Surface enhanced Raman spectroscopy (SERS) imaging was used in conjunction with principal component analysis (PCA) for the in situ spatiotemporal mapping of the virulence factor pyocyanin in communities of the pathogenic bacterium Pseudomonas aeruginosa. The combination of SERS imaging and PCA analysis provides a robust method for the characterization of heterogeneous biological systems while circumventing issues associated with interference from sample autofluorescence and low reproducibility of SERS signals. The production of pyocyanin is found to depend both on the growth carbon source and on the specific strain of P. aeruginosa studied. A cystic fibrosis lung isolate strain of P. aeruginosa synthesizes and secretes pyocyanin when grown with glucose and glutamate, while the laboratory strain exhibits detectable production of pyocyanin only when grown with glutamate as the source of carbon. Pyocyanin production in the laboratory strain grown with glucose was below the limit of detection of SERS. In addition, the combination of SERS imaging and PCA can elucidate subtle differences in the molecular composition of biofilms. As a result, PCA loading plots from the clinical isolate exhibit features corresponding to vibrational bands of carbohydrates, which represent the mucoid biofilm matrix specific to that isolate, features that are not seen in the PCA loading plots of the laboratory strain.

59 BASIC BIOLOGICAL SCIENCES↗

Experimental Fuel Consumption Results from a Heterogeneous Four-Truck Platoon

Platooning has the potential to reduce greenhouse gas missions of heavy-duty vehicles. Prior platooning studies have chiefly focused on the fuel economy characteristics and three-truck platoons, and most have investigated aerodynamically homogeneous platoons with trucks of the same trim. For real world application and accurate return on investment for potential adopters, non-uniform platoons and the impacts of grade and disturbances on a platoon’s fuel economy must also be characterized. This study investigates the fuel economy of a heterogeneous four-truck platoon on a closed test track. Tests were run for one hour at a speed of 45 mph. The trucks used for this study are two 2015 Peterbilt 579’s with a Cummins ISX15 and a Paccar MX-13, and two 2009 Freightliner M915A5’s, one armored and the other unarmored. Many analysis methodologies were leveraged to describe and compare the fuel data, including lap-wise and track-segment analysis. The methodology for dividing the data into laps is described in detail. The influence of other factors beyond the aerodynamics of platooning is discussed. CAN fuel rate analysis showed excellent agreement with previous experimental trends for two and three-truck platoons. In general, the indicated fuel economy benefits in this study were 5-11% for following vehicles and 0-4% for the lead vehicle in platoon relative to their baseline fuel consumption. On a cumulative basis, all platoons saved fuel, ranging from 6% to 8% versus the sum of the standalone trucks’ fuel consumption. The practical implications of the fuel economy results are discussed, as well as avenues for future research. Introduction and Motivation platooning is controlled coordination of two or more vehicles in a convoy, sometimes called CACC (Coordinated or Cooperative Adaptive Cruise Control). The distance between vehicles in a platoon can be controlled tightly at no additional fatigue to the driver. Platooning vehicles can also respond quickly to braking events of the leader, much more quickly than the typical human driver’s reaction time of 1-1.5 s. Therefore, vehicles in a platoon can follow each other much more closely than would usually be considered a safe following distance under human operation. It is implied that under very close following conditions, platooning technology must be extremely robust before it is safe for wide-scale implementation. Platooning is under investigation as a fuel-saving technology. Close-following significantly reduces aerodynamic drag for both leading and trailing vehicles. According to the NRC in 2010, aerodynamic drag represents roughly half of a Class-8 truck’s on-highway fuel usage, meaning a 20% reduction in drag roughly equals a 10% reduction in fuel usage, if all other sources of energy loss remain equal (i.e. accessory, rolling resistance, drivetrain, braking). It is by aerodynamics that platooning saves fuel. At risk of oversimplifying the aerodynamics, following (or trailing) vehicles experience reduced wind velocity due to shielding, and the leading vehicles experience an increased aft pressure, especially at distances closer than 75’ (23 m).

greenhouse gas emissions, truck platoon, heavy-dut↗

Joint Factorization of QCD and QED Radiation in Lepton-Hadron Scattering

The factorization theorem plays an important role in the analysis of high energy quantum chromodynamic (QCD) processes, separating the nonperturbative hadronic interaction into the universal parton distribution functions (PDFs) and fragmentation functions (FFs) and the process-dependent interactions into short distance perturbative calculations, with any interference power suppressed. With a virtual photon exchange, lepton-hadron deep inelastic scattering (DIS) provides an electromagnetic hard probe for the partonic structure of colliding hadrons and has played an important role in the development of QCD factorization. However, the collision induced QED radiation can change the momentum of the exchanged but unobserved virtual photon, making the photon-hadron frame, where the factorization formalism for DIS and semi-inclusive DIS (SIDIS) was derived, ill defined. A new analogous factorization approach has been introduced to separate the leading power process-independent QED radiative contributions to the single photon exchange by introducing lepton distribution functions (LDFs) and lepton fragmentation functions (LFFs), while process-dependent effects are perturbatively calculated with large logarithms removed [J. High Energ. Phys. 2021, 157 (2021)]. These LDFs and LFFs are considered global, as they appear in many different interactions, such as e+e-, DIS and SIDIS, so data from experiments can be used to fit and describe these functions across a wide range of lepton scattering. In this work, I will apply this new hybrid factorization approach to lepton-hadron DIS and SIDIS. For DIS, I derive the NLO short distance perturbative contribution to the cross section and demonstrate the effects the QED radiation has on the cross section using this approach using the CTEQ parameterization for the QCD functions. As part of the SIDIS analysis, I study the cross-section in two different kinematic regions: (1) the scattered lepton and observed hadron are not near back-to-back, and (2) they are close to back-to-back, where collinear QCD factorization works for (1) and TMD QCD factorization for (2) while collinear QED factorization works for both. As part of this work, I show the effects on the SIDIS cross section using fixed order calculations for the unpolarized structure function by first showing the effect of the radiative corrections on the main kinematic variables, especially how the internal transverse momentum is significantly correlated to the external angular dependence, and then the unpolarized structure function (or cross section) with matching between the descriptions for low and high transverse momentum. This work will impact the calculations for predictions for data from COMPASS and various Jefferson Lab experiments.

Cammarota, Justin [Univ. of Kentucky, Lexington, K↗