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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Testing the role of AGN on the star formation and metal enrichment of ‘twin galaxies’

Here, we explore the effect of AGN activity on the star formation history of galaxies by analysing the stellar population properties of 10 pairs of nearby twin galaxies – selected as being visually similar except for the presence of an AGN. The selection of such twin samples represents a method to study AGN feedback, as recently proposed by del Moral Castro et al. We use integral field unit (IFU) data from CALIFA, stacked within three fixed apertures. AGN galaxies in a twin pair suggest more evolved stellar populations than their non-AGN counterpart 90 per cent of the time, regardless of aperture size. A comparison with a large sample from SDSS confirms that most twins are representative of the general population, but in each twin the differences between twin members is significant. A set of targeted line strengths reveal the AGN member of a twin pair is older and more metal-rich than the non-AGN galaxy, suggesting AGN galaxies in our sample may either have an earlier formation time or follow a different star formation and chemical enrichment history. These results are discussed within two simple, contrasting hypotheses for the role played by AGN in galaxy evolution, which can be tested in the future at a greater detail with the use of larger data sets.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

LENS: Learning Enabled Network Synthesis

RTRC and UMD have developed novel machine learning based methods under the ARPA-E DIFFERENTIATE program for rapid acceleration of hypothesis generation in complex architecture design spaces involving both discrete choices of component inclusion and interconnection and continuous parametric decisions. The project named Learning Enabled Network Synthesis (LENS) further demonstrated the developed methods on challenging electrical power converter design problems by identifying the most suitable circuit topologies and simultaneously selecting the most appropriate components to achieve optimized design of power converter with improved performances. We demonstrated that LENS could enable exploration of very large design space of circuit topologies and components by addressing the limitations of conventional design process in non-linear, high switching speed, multi-dimensional power converter design and optimization. The key innovation developed in LENS is the seamless integration of statistical learning and logical reasoning techniques and building on the individual strengths of these techniques for rapid hypothesis discovery. The main component of LENS comprises of: 1) Graph Reasoning Engine (GRE) to enforce composition rules that rapidly reject all discrete architectures that are composed incorrectly and generates an adaptive database of feasible designs which can be used by ML modules, 2) Graph Generative Learning module which is a deep neural network based generative model for graph architectures which can enable design space exploration beyond the dataset generated by the GRE, 3) Graph Reduced Order Model (ROM) for graph domains for accelerating computation of output metrics, and 4) Active learning and Rule Discovery module for sample efficient learning and extracting logical rules from the learned ML models which will be integrated in the GRE to enhance the filtering effectiveness. LENS approach can be applied to any design domains where designs can be represented as multi-attribute graphs. The LENS team integrated the various technical innovations listed above into an optimization pipeline and exercised the optimization pipeline on the converter design problem. The LENS project demonstrated that the developed AI/ML technologies can be used to generate novel converter circuits >45x faster than experts on chosen use-cases. This can enable faster design space exploration and identification of new designs which are not considered by experts due to the increasing design space complexity. This has significant potential impact on the public and energy needs of the country. It is currently estimated that 30% of all electrical powers generated passes through power converters. The future estimate is that 80% of all power generated would be passing through converters. LENS fills a critical gap in this space since by accelerating the design process the designers would be able to generate more efficient converters which can lead to significant energy savings for the country.

42 ENGINEERING↗
NASA NTRS1979

Multiple-sample holder for IC testing

Carrousel tray speeds up testing process by feeding mass spectrometer up to 12 sealed integrated circuit packages in rapid succession for analysis of contaminants and total gas composition.

Haack, R. F.↗
DOE OSTI2019

Isotope effects in liquid water via deep potential molecular dynamics

A comprehensive microscopic understanding of ambient liquid water is a major challenge for ab initio simulations as it simultaneously requires an accurate quantum mechanical description of the underlying potential energy surface (PES) as well as extensive sampling of configuration space. Due to the presence of light atoms (e.g. 𝐻 or 𝐷), nuclear quantum fluctuations lead to observable changes in the structural properties of liquid water (e.g. isotope effects), and therefore provide yet another challenge for ab initio approaches. In this work, we demonstrate that the combination of dispersion-inclusive hybrid density functional theory (DFT), the Feynman discretised path-integral (PI) approach, and machine learning (ML) constitutes a versatile ab initio based framework that enables extensive sampling of both thermal and nuclear quantum fluctuations on a quite accurate underlying PES. In particular, we employ the recently developed deep potential molecular dynamics (DPMD) model – a neural-network representation of the ab initio PES – in conjunction with a PI approach based on the generalised Langevin equation (PIGLET) to investigate how isotope effects influence the structural properties of ambient liquid 𝐻⁢2⁢𝑂 and 𝐷⁢2⁢𝑂. Through a detailed analysis of the interference differential cross sections as well as several radial and angular distribution functions, we demonstrate that this approach can furnish a semi-quantitative prediction of these subtle isotope effects.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2013

RESOLVE Project

The RESOLVE project is a lunar prospecting mission whose primary goal is to characterize water and other volatiles in lunar regolith. The Lunar Advanced Volatiles Analysis (LAVA) subsystem is comprised of a fluid subsystem that transports flow to the gas chromatograph - mass spectrometer (GC-MS) instruments that characterize volatiles and the Water Droplet Demonstration (WDD) that will capture and display water condensation in the gas stream. The LAVA Engineering Test Unit (ETU) is undergoing risk reduction testing this summer and fall within a vacuum chamber to understand and characterize component and integrated system performance. Testing of line heaters, printed circuit heaters, pressure transducers, temperature sensors, regulators, and valves in atmospheric and vacuum environments was done. Test procedures were developed to guide experimental tests and test reports to analyze and draw conclusions from the data. In addition, knowledge and experience was gained with preparing a vacuum chamber with fluid and electrical connections. Further testing will include integrated testing of the fluid subsystem with the gas supply system, near-infrared spectrometer, WDD, Sample Delivery System, and GC-MS in the vacuum chamber. This testing will provide hands-on exposure to a flight forward spaceflight subsystem, the processes associated with testing equipment in a vacuum chamber, and experience working in a laboratory setting. Examples of specific analysis conducted include: pneumatic analysis to calculate the WDD's efficiency at extracting water vapor from the gas stream to form condensation; thermal analysis of the conduction and radiation along a line connecting two thermal masses; and proportional-integral-derivative (PID) heater control analysis. Since LAVA is a scientific subsystem, the near-infrared spectrometer and GC-MS instruments will be tested during the ETU testing phase.

Parker, Ray↗
DOE OSTI2022

Trace Impurities Identified as Forensic Signatures in CMX-5 Fuel Pellets Using X-ray Spectroscopic Techniques

We report that small-particle analysis is a highly promising emerging forensic tool for analysis of interdicted special nuclear materials. Integration of microstructural, morphological, compositional, and molecular impurity signatures could provide significant advancements in forensic capabilities. We have applied rapid, high-sensitivity, hard X-ray synchrotron chemical imaging to analyze impurity signatures in two differently fabricated fuel pellets from the 5th Collaborative Materials Exercise (CMX5) of the IAEA Nuclear Forensics International Working Group. The spatial distributions, chemical compositions, and morphological and molecular characteristics of impurities were evaluated using X-ray absorption near-edge structure (XANES) and X-ray fluorescence chemical imaging to discover principal impurities, their granularity, particle sizes, modes of occurrence (distinct grains vs incorporation in the UO 2 lattice), and sources and mechanisms of incorporation. Differences in UO 2+x stoichiometry were detected at the microscale in nominally identical UO 2 ceramics (CMX5-A and CMX5-B), implying the presence of multiple UO 2 host phases with characteristic microstructures and feedstock compositions. Al, Fe, Ni, W, and Zr impurities and integrated impurity signature analysis identified distinctly different pellet synthesis and processing methods. For example, two different Al, W, and Zr populations in the CMX5-B sample indicated a more complex processing history than the CMX5-A sample. K-edge XANES measurements reveal both metallic and oxide forms of Fe and Ni but with different proportions between each sample. Altogether, these observations suggest multiple sources of impurities, including fabrication (e.g., force-sieving) and feedstock (mineral oxides). This study demonstrates the potential of synchrotron techniques to integrate different signatures across length scales (angstrom to micrometer) to detect and differentiate between contrasting UO 2 fuel fabrication techniques.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1984

Design and Performance of Sampled Data Loops for Subcarrier and Carrier Tracking

Design parameters and resulting performance are presented for the sampled data analogies of continuous time phase locked loops of second and third order containing perfect integrators. Expressions for noise equivalent bandwidth and steady state errors are given. Stability and gain margin are investigated using z plane root loci. Finally, an application is presented for Voyager subcarrier and carrier tracking under the dynamics of the encounters with Uranus and Neptune. For carrier tracking, loop bandwidth narrow enough for satisfactory loop signal to noise ratios can be achieved using third order loops without rate aiding, whereas second order loops would require aiding. For subcarrier tracking, third order loops can be used when the sampling rate is limited to approximately once per second, as in the Baseband Assembly, whereas second order loops sufficiently wide to track the dynamics have stability problems at that sampling rate.

Aguirre, S.↗
NASA NTRS2012

RESOLVE Project

The RESOLVE project is a lunar prospecting mission whose primary goal is to characterize water and other volatiles in lunar regolith. The Lunar Advanced Volatiles Analysis (LAVA) subsystem is comprised of a fluid subsystem that transports flow to the gas chromatograph- mass spectrometer (GC-MS) instruments that characterize volatiles and the Water Droplet Demonstration (WDD) that will capture and display water condensation in the gas stream. The LAVA Engineering Test Unit (ETU) is undergoing risk reduction testing this summer and fall within a vacuum chamber to understand and characterize C!Jmponent and integrated system performance. Ray will be assisting with component testing of line heaters, printed circuit heaters, pressure transducers, temperature sensors, regulators, and valves in atmospheric and vacuum environments. He will be developing procedures to guide these tests and test reports to analyze and draw conclusions from the data. In addition, he will gain experience with preparing a vacuum chamber with fluid and electrical connections. Further testing will include integrated testing of the fluid subsystem with the gas supply system, near-infrared spectrometer, WDD, Sample Delivery System, and GC-MS in the vacuum chamber. This testing will provide hands-on exposure to a flight forward spaceflight subsystem, the processes associated with testing equipment in a vacuum chamber, and experience working in a laboratory setting. Examples of specific analysis Ray will conduct include: pneumatic analysis to calculate the WOO's efficiency at extracting water vapor from the gas stream to form condensation; thermal analysis of the conduction and radiation along a line connecting two thermal masses; and proportional-integral-derivative (PID) heater control analysis. In this Research and Technology environment, Ray will be asked to problem solve real-time as issues arise. Since LAVA is a scientific subsystem, Ray will be utilizing his chemical engineering background to operate the near-infrared spectrometer and GC-MS instruments during ETU testing. Ray will be working with Modified Commercial off the Shelf (MCOTS) instruments and characterizing their analytical behavior for optimization. Ray will be offered the opportunity to suggest testing modifications or configuration changes at any time to improve the experimental effectiveness. He will gain many skills needed for working in a technical team setting requiring flexibility and critical thinking.

Parker, Ray O.↗
DOE OSTI2023

Data Summary Report for Soil and Slab Sampling at Former Building 175

Lawrence Livermore National Security (LLNS) and the U.S. Department of Energy (DOE) are in the process of returning the area where Building 175 existed to beneficial use for future site development. The completed assessment will help LLNS and DOE to outline project scope and costs associated with the removal, characterization, and disposal of materials generated when the concrete slab for the former building and any associated remaining subsurface structures are demolished. Slab removal under the Transition & Disposition process requires full screening for potential site contamination to determine appropriate future land use. Borehole locations and depths were designed to correctly assess DOE’s future liability for characterizing residual vadose zone contamination. If a residual source area is identified at depth, DOE will need to evaluate the additional cost of future subsurface cleanup (with limited access) due to planned development. This is necessary to leave the location in a “ready-to-build” status. As a result, Phase II sampling requirements may in some cases extend beyond the construction zone required for slab removal to ensure the necessary due diligence. To avoid the potential spread of contamination and/or the creation of an environmental release by impacting the integrity of known contamination areas (e.g., pit within room 102 and the east to west boundary seam), these locations were not sampled for this project. During demolition of the slab, these locations and their underlying soils should be further evaluated. The assessment was conducted in accord with the May 2022 Lawrence Livermore National Laboratory Former Building 175 Assessment Soil Sampling and Analysis Plan / Quality Assurance Plan. Thirty-six, direct-push borings were advanced, along with collecting concrete (where present) and soil samples for laboratory analyses. Thirty-two of the borings were advanced to a depth of 25 feet below ground (bgs), and four borings were advanced to a depth of 55 feet bgs. The concrete slab for former Building 175 ranged from approximately 8 inches to over two feet in thickness. Soils encountered during the investigation consisted primarily of clayey silt, with interbeds of sandy gravel and silty sand to the total depth explored of 55 feet bgs. Field photoionization detector readings – checking for volatile organic compound (VOC) vapors in soils, ranged from zero (0) to a peak of 33 parts per million at 25 feet bgs in boring PC-B175- 028. The cause for the peak reading is unknown, however, no visually discolored or odorous soils were encountered during the assessment and all VOC results were below Lawrence Livermore National Laboratory’s (LLNL’s) Soil Screening and Management Plan (SSMP) soil screening levels (SSL). Groundwater was not encountered during the assessment and is expected to occur at roughly 65 feet bgs in the project area. No metals were detected at concentrations of concern in the concrete core samples collected and analyzed. Low gross alpha and beta activity concentrations were detected in the concrete core samples collected and analyzed. The detected activity concentrations would appear to be from naturally occurring radioactive isotopes, i.e., potassium 40, present in the raw materials used to make concrete and not artificially added. Tritium was not detected above the testing laboratory's Method Detection Limit (MDL) in any of the concrete core samples collected and analyzed. The radioactive isotopes - actinium 228, bismuth 214, lead 212, lead 214, potassium 40, radium 226, radium 228, and thallium 208, were detected at low activity concentrations in the concrete core samples analyzed. Based on the detected activity concentrations, the isotopes would appear to be naturally occurring in the raw materials used to make concrete and not artificially added. Acetone – a common laboratory contaminant, was detected in nine of the soil samples collected and analyzed. Concentrations of two other volatile organic compounds (benzene and tetrachloroethene) were detected in five of the soil samples analyzed. All concentrations were below SSLs. Total petroleum hydrocarbons as diesel range organics were detected at 43.9 milligrams per kilogram (mg/kg) in the 20-foot bgs duplicate sample from boring PC-B175-007. Total petroleum hydrocarbons as motor oil were detected at 7.20 mg/kg in the 15-foot bgs routine sample from boring PC-B175-001, and at 20.7 mg/kg in the 20-foot bgs duplicate sample from boring PC-B175-007. The SSL for diesel-range TPHs is 260 mg/kg. LLNL does not have an SSL for motor oil range TPHs. No indications of a release, e.g., visibly stained, or odorous soil, were present at the boring locations. No samples collected contained polychlorinated biphenyls (PCBs) in concentrations above the laboratory reporting limit. Arsenic was detected above its SSL of 8.51 mg/kg in the 25-foot bgs routine sample collected from boring PC-B175-023. Nickel was detected above its SSL of 86.0 mg/kg in the 10-foot bgs routine sample from boing PC-B175-005, the 20-foot bgs routine sample from boring PC-B175-025, and the 25-foot bgs routine sample from boring PC-B175-034. The detected concentrations, however, were well below ten times (10x) their respective STLCs. Gross alpha and/or gross beta were detected above their respective SSL activity concentrations in three routine soil samples. Retesting (two per sample) of the samples showed that the initial reported activity concentrations were anomalous. Tritium was not detected in any of the routine or duplicate soil samples collected and analyzed during the investigation. The radioactive isotopes - actinium 228, bismuth 212 and 214, lead 212 and 214, potassium 40, radium 224, 226 and 228, thallium 208, thorium 234 and uranium, were detected at low activity concentrations in the soil samples analyzed for radioactive constituents. The detected isotopes and their associated activity concentrations are typical of those naturally occurring in the marine-type sedimentary deposits underlying the Livermore Valley. No radiological controls are necessary for the soil evaluated.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Ultrasonic nondestructive evaluation of additively manufactured wear coatings

Here, this work pertains to the nondestructive evaluation of additively deposited coatings using ultrasound measurements. The specific objective was to evaluate using ultrasound surface wave measurements the quality of Stellite 21 coatings deposited on Inconel 718 substrates by the directed energy deposition (DED) additive manufacturing (AM) process. The surface wave speed and diffuse backscatter amplitude of the ultrasound waves were correlated with both cracking and warpage of the coating. This research is important, because, the integrity of DED-processed coatings currently requires a combination of destructive metallographic studies and X-ray computed tomography analysis, which are both expensive and time consuming. Instead of using a normal incidence configuration for the ultrasound measurements, the surface-wave approach allows the inspection of the near surface coating integrity. Three different frequencies were used to excite surface waves because each frequency has a different penetration depth. The signals obtained were used to quantify and compare the surface wave speed and surface wave-diffuse ultrasonic backscatter amplitude from five different DED-processed Stellite coated samples. Considering destructive metallurgical characterization as a reference, surface wave measurements were found to be effective for examining coating integrity. Further, the backscatter amplitude of the surface waves was correlated with the crack density and warpage. These flaws also change the stress state of the Stellite coating and consequently the surface wave propagation speed and its scattering behavior.

36 MATERIALS SCIENCE↗
DOE OSTI2025

AutoTandemML: Active Learning Enhanced Tandem Neural Networks for Inverse Design Problems

Inverse design in science and engineering involves determining optimal design parameters that achieve desired performance outcomes, a process often hindered by the complexity and high dimensionality of design spaces, leading to significant computational costs. To tackle this challenge, we propose a novel hybrid approach that combines active learning with Tandem Neural Networks to enhance the efficiency and effectiveness of solving inverse design problems. Active learning allows to selectively sample the most informative data points, reducing the required dataset size without compromising accuracy. We investigate this approach using three benchmark problems: airfoil inverse design, photonic surface inverse design, and scalar boundary condition reconstruction in diffusion partial differential equations. We demonstrate that integrating active learning with Tandem Neural Networks outperforms standard approaches across the benchmark suite, achieving better accuracy with fewer training samples.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Searches for lepton-flavour-violating decays of the Higgs boson into $eτ$ and $μτ$ in $ \sqrt{s}$ = 13 TeV pp collisions with the ATLAS detector

This paper presents direct searches for lepton flavour violation in Higgs boson decays, H → eτ and H → μτ, performed using data collected with the ATLAS detector at the LHC. The searches are based on a data sample of proton-proton collisions at a centre-of-mass energy $\sqrt{s}$ = 13 TeV, corresponding to an integrated luminosity of 138 fb –1 . Leptonic (τ → ℓν ℓ ν τ ) and hadronic (τ → hadrons ν τ ) decays of the τ-lepton are considered. Two background estimation techniques are employed: the MC-template method, based on data-corrected simulation samples, and the Symmetry method, based on exploiting the symmetry between electrons and muons in the Standard Model backgrounds. No significant excess of events is observed and the results are interpreted as upper limits on lepton-flavour-violating branching ratios of the Higgs boson. The observed (expected) upper limits set on the branching ratios at 95% confidence level, $\mathcal{B}$(H → eτ) < 0.20% (0.12%) and $\mathcal{B}$(H → μτ ) < 0.18% (0.09%), are obtained with the MC-template method from a simultaneous measurement of potential H → eτ and H → μτ signals. The best-fit branching ratio difference, $\mathcal{B}$(H → μτ) → $\mathcal{B}$(H → eτ), measured with the Symmetry method in the channel where the τ-lepton decays to leptons, is (0.25 ± 0.10)%, compatible with a value of zero within 2.5σ.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Parallel Multi-Omics in High-Risk Subjects for the Identification of Integrated Biomarker Signatures of Type 1 Diabetes

Background: Biomarkers are crucial for detecting early type-1 diabetes (T1D) and preventing significant β-cell loss before the onset of clinical symptoms. Here, we present proof-of-concept studies to demonstrate the potential for identifying integrated biomarker signature(s) of T1D using parallel multi-omics. Methods: Blood from human subjects at high risk for T1D (and healthy controls; n = 4 + 4) was subjected to parallel unlabeled proteomics, metabolomics, lipidomics, and transcriptomics. The integrated dataset was analyzed using Ingenuity Pathway Analysis (IPA) software for disturbances in the at-risk subjects compared to controls. Results: The final quadra-omics dataset contained 2292 proteins, 328 miRNAs, 75 metabolites, and 41 lipids that were detected in all samples without exception. Disease/function enrichment analyses consistently indicated increased activation, proliferation, and migration of CD4 T-lymphocytes and macrophages. Integrated molecular network predictions highlighted central involvement and activation of NF-κB, TGF-β, VEGF, arachidonic acid, and arginase, and inhibition of miRNA Let-7a-5p. IPA-predicted candidate biomarkers were used to construct a putative integrated signature containing several miRNAs and metabolite/lipid features in the at-risk subjects. Conclusions: Preliminary parallel quadra-omics provided a comprehensive picture of disturbances in high-risk T1D subjects and highlighted the potential for identifying associated integrated biomarker signatures. With further development and validation in larger cohorts, parallel multi-omics could ultimately facilitate the classification of T1D progressors from non-progressors.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Nanofluidic interfaces in microfluidic networks

The integration of nano- and microfluidic technologies enables the construction of tunable interfaces to physical and biological systems across relevant length scales. The ability to perform chemical manipulations of miniscule sample volumes is greatly enhanced through these technologies and extends the ability to manipulate and sample the local fluidic environments at subcellular, cellular and community or tissue scales. Here we describe the development of a flexible surface micromachining process for the creation of nanofluidic channel arrays integrated within SU-8 microfluidic networks. The use of a semi-porous, silicon rich, silicon nitride structural layer allows rapid release of the sacrificial silicon dioxide during the nanochannel fabrication. Nanochannel openings that form the interface to biological samples are customized using focused ion beam milling. The compatibility of these interfaces with on-chip microbial culture is demonstrated.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2022

Physics-Informed Machine Learning of Dynamical Systems for Efficient Bayesian Inference

Although the no-u-turn sampler (NUTS) is a widely adopted method for performing Bayesian inference, it requires numerous posterior gradients which can be expensive to compute in practice. Recently, there has been a significant interest in physics-based machine learning of dynamical (or Hamiltonian) systems and Hamiltonian neural networks (HNNs) is a noteworthy architecture. But these types of architectures have not been applied to solve Bayesian inference problems efficiently. We propose the use of HNNs for performing Bayesian inference efficiently without requiring numerous posterior gradients. We introduce latent variable outputs to HNNs (L-HNNs) for improved expressivity and reduced integration errors. We integrate L-HNNs in NUTS and further propose an online error monitoring scheme to prevent sampling degeneracy in regions where L-HNNs may have little training data. We demonstrate L-HNNs in NUTS with online error monitoring consider several complex high-dimensional posterior densities and compare its performance to NUTS.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2011

Development of a Novel Self-Enclosed Sample Preparation Device for DNA/RNA Isolation in Space

Modern biology techniques present potentials for a wide range of molecular, cellular, and biochemistry applications in space, including detection of infectious pathogens and environmental contaminations, monitoring of drug-resistant microbial and dangerous mutations, identification of new phenotypes of microbial and new life species. However, one of the major technological blockades in enabling these technologies in space is a lack of devices for sample preparation in the space environment. To overcome such an obstacle, we constructed a prototype of a DNA/RNA isolation device based on our novel designs documented in the NASA New Technology Reporting System (MSC-24811-1/3-1). This device is self-enclosed and pipette free, purposely designed for use in the absence of gravity. Our design can also be modified easily for preparing samples in space for other applications, such as flowcytometry, immunostaining, cell separation, sample purification and separation according to its size and charges, sample chemical labeling, and sample purification. The prototype of our DNA/RNA isolation device was tested for efficiencies of DNA and RNA isolation from various cell types for PCR analysis. The purity and integrity of purified DNA and RNA were determined as well. Results showed that our developed DNA/RNA isolation device offers similar efficiency and quality in comparison to the samples prepared using the standard protocol in the laboratory.

Zhang, Ye↗
NASA NTRS2008

WRATS Integrated Data Acquisition System

The Wing and Rotor Aeroelastic Test System (WRATS) data acquisition system (DAS) is a 64-channel data acquisition display and analysis system specifically designed for use with the WRATS 1/5-scale V-22 tiltrotor model of the Bell Osprey. It is the primary data acquisition system for experimental aeroelastic testing of the WRATS model for the purpose of characterizing the aeromechanical and aeroelastic stability of prototype tiltrotor configurations. The WRATS DAS was also used during aeroelastic testing of Bell Helicopter Textron s Quad-Tiltrotor (QTR) design concept, a test which received international attention. The LabVIEW-based design is portable and capable of powering and conditioning over 64 channels of dynamic data at sampling rates up to 1,000 Hz. The system includes a 60-second circular data archive, an integrated model swashplate excitation system, a moving block damping application for calculation of whirl flutter mode subcritical damping, a loads and safety monitor, a pilot-control console display, data analysis capabilities, and instrumentation calibration functions. Three networked computers running custom-designed LabVIEW software acquire data through National Instruments data acquisition hardware. The aeroelastic model (see figure) was tested with the DAS at two facilities at NASA Langley, the Transonic Dynamics Tunnel (TDT) and the Rotorcraft Hover Test Facility (RHTF). Because of the need for seamless transition between testing at these facilities, DAS is portable. The software is capable of harmonic analysis of periodic time history data, Fast Fourier Transform calculations, power spectral density calculations, and on-line calibration of test instrumentation. DAS has a circular buffer archive to ensure critical data is not lost in event of model failure/incident, as well as a sample-and-hold capability for phase-correct time history data.

Piatak, David J.↗
NASA NTRS1987

Induced star formation in interacting galaxies

Measurements of H alpha emission line fluxes and FIR fluxes in approx. 100 interacting spirals were used to investigate the effects of close tidal interactions on the disk and nuclear star formation rates in galaxies. Two samples of interacting spirals were studied, a complete sample of close pairs, and a set of strongly perturbed systems from the Arp atlas. Both the integrated H alpha luminosities and FIR luminosities are enhanced in the interacting galaxies, indicating that the encounters indeed trigger massive star formation in many cases. The response of individual galaxies is highly variable, however. A majority of the interacting spirals exhibit normal star formation rates, while a small fraction are undergoing bursts with luminosities which are rarely, if ever, observed in noninteracting systems. Virtually all of the latter are in the Arp sample, indicating that the Arp atlas is heavily biased to the most active star forming systems.

Kennicutt, R. C.↗