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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Extraterrestrial Molecular Indicators of Life Investigation (EMILI)

Future missions to Enceladus, Europa, Mars, and beyond may seek the molecular signs of extraterrestrial life through chemical analysis of acquired samples. Particularly on ocean worlds such as Enceladus and Europa, samples may contain trace ocean-borne molecular biosignatures of extant life that may or may not share similarities to those of terrestrial life. In situ analyses must be prepared to detect and characterize a wide range of possible molecular species, structures, and patterns, typically with exquisite sensitivity and within a complex, poorly-characterized planetary environment. The Extraterrestrial Molecular Indicators of Life Investigation (EMILI) is designed to meet or exceed the requirements of such missions for organic molecular analysis through a powerful combination of dual chemical separation and both optical and mass spectrometry detection techniques, realized in an integrated, compact instrument package fully compatible with anticipated flight resources and conditions. The full EMILI instrument combines two sample analysis subsystems to provide wide-ranging and complementary detection of organic compounds and inorganic salts. The Gas Analysis Processing System (GAPS) uses a chemical derivatization protocol with gas chromatography (GC) separation prior to detection in an ion trap mass spectrometer (ITMS) to enable full characterization of lower-polarity, volatile and semi-volatile molecules such as fatty acids and hydrocarbons. The Organic Capillary Electrophoresis ANalysis System (OCEANS) uses a liquid-based extraction protocol with CE separation to enable precise analysis of more water-soluble/polar compounds. OCEANS features a laser-induced fluorescence detection mode to perform ultra-sensitive quantitative analysis of chiral amino acids. In EMILI, OCEANS is additionally coupled to the same ITMS through a novel electrospray ionization interface. The common ITMS allows EMILI to identify and cross-correlate molecular species and patterns, detected through either or both protocols, of molecular weights to over 1000 u, potentially even revealing complex biosignatures such as alien oligopeptides and informational polymers.

Europa↗
NASA NTRS1994

UV laser long-path absorption spectroscopy

Long path Differential Optical Absorption Spectroscopy (DOAS) using a picosecond UV laser as a light source was developed in our institute. Tropospheric OH radicals are measured by their rotational absorption lines around 308 nm. The spectra are obtained using a high resolution spectrograph. The detection system has been improved over the formerly used optomechanical scanning device by application of a photodiode array which increased the observed spectral range by a factor of 6 and which utilizes the light much more effectively leading to a considerable reduction of the measurement time. This technique provides direct measurements of OH because the signal is given by the product of the absorption coefficient and the OH concentration along the light path according to Lambert-Beers law. No calibration is needed. Since the integrated absorption coefficient is well known the accuracy of the measurement essentially depends on the extent to which the OH absorption pattern can be detected in the spectra. No interference by self generated OH radicals in the detection lightpath has been observed. The large bandwidth (greater than 0.15 nm) and the high spectral resolution (1.5 pm) allows absolute determination of interferences by other trace gas absorptions. The measurement error is directly accessible from the absorption-signal to baseline-noise ratio in the spectra. The applicability of the method strongly depends on visibility. Elevated concentrations of aerosols lead to considerable attenuation of the laser light which reduces the S/N-ratio. In the moderately polluted air of Julich, where we performed a number of OH measurement spectra. In addition absorption features of unidentified species were frequently detected. A quantitative deconvolution even of the known species is not easy to achieve and can leave residual structures in the spectra. Thus interferences usually increase the noise and deteriorate the OH detection sensitivity. Using diode arrays for sensitive absorption measurements some specific problems of those detectors have to be solved experimentally (i.e. fixed pattern noise, dark signal noise, nonuniform efficiency of individual elements, spatial sensitivity variations). In order to improve the low spatial resolution we performed laboratory studies using a multiple reflection cell to convert the long path technique to a real in situ point measurement. Under the conditions of field experiments in Julich residual absorbance signals at present are about 1.5x10(exp -4) corresponding to an OH detection sensitivity of 2x10(exp 6) OH/cm(exp 3) using a light path of 5.8 km. Total integration times for one measurement point vary between a few minutes and an hour.

Dorn, Hans-Peter↗
NASA NTRS2007

Collocation and Pattern Recognition Effects on System Failure Remediation

Previous research found that operators prefer to have status, alerts, and controls located on the same screen. Unfortunately, that research was done with displays that were not designed specifically for collocation. In this experiment, twelve subjects evaluated two displays specifically designed for collocating system information against a baseline that consisted of dial status displays, a separate alert area, and a controls panel. These displays differed in the amount of collocation, pattern matching, and parameter movement compared to display size. During the data runs, subjects kept a randomly moving target centered on a display using a left-handed joystick and they scanned system displays to find a problem in order to correct it using the provided checklist. Results indicate that large parameter movement aided detection and then pattern recognition is needed for diagnosis but the collocated displays centralized all the information subjects needed, which reduced workload. Therefore, the collocated display with large parameter movement may be an acceptable display after familiarization because of the possible pattern recognition developed with training and its use.

Trujillo, Anna C.↗
DOE OSTI2025

Unsupervised anomaly clustering via offset alignment in multivariate grid sensing data

Modern industries increasingly rely on multi-sensor technologies to acquire complex, high-dimensional data streams, enabling advanced monitoring and control systems. One critical application is online anomaly detection in electrical smart grids, where multivariate and multimodal sensing technologies play a vital role. However, detecting anomalies in such time-series data is challenging due to their inherent temporal dependencies and stochastic behavior. Traditional approaches based on supervised and semi-supervised learning methods depend on labeled datasets, which are often unavailable in real-world scenarios. While unsupervised methods have emerged as promising alternatives, these methods are highly susceptible to noise and outliers commonly present in sensing applications. Furthermore, deep learning-based anomaly detection methods, despite their performance, are often criticized for their black-box nature, limiting their applicability in safety-critical and online environments where interpretability and explainability are paramount. In this work, we propose an unsupervised anomaly clustering method leveraging a cyclic alignment-based offset detection algorithm for multivariate time-series signals. The proposed method is applied to multivariate data collected from vibrational, voltage, and magnetic field sensors deployed in a local grid substation. Our results demonstrate the robustness of the algorithm in accurately clustering various anomalies/events across different sensing modalities. Additionally, we compare the effectiveness of the proposed approach against a simple pattern-based anomaly detection method, which performs well for univariate data but fails to generalize to multivariate and multimodal time-series data.

Mukherjee, Subrata [ORNL] (ORCID:0000000309930338)↗
DOE OSTI2017

Deep Learning-Based Data Forgery Detection in Automatic Generation Control

Automatic Generation Control (AGC) is a key control system in the power grid. It is used to calculate the Area Control Error (ACE) based on frequency and tie-line power flow between balancing areas, and then adjust power generation to maintain the power system frequency in an acceptable range. However, attackers might inject malicious frequency or tie-line power flow measurements to mislead AGC to do false generation correction which will harm the power grid operation. Such attacks are hard to be detected since they do not violate physical power system models. In this work, we propose algorithms based on Neural Network and Fourier Transform to detect data forgery attacks in AGC. Different from the few previous work that rely on accurate load prediction to detect data forgery, our solution only uses the ACE data already available in existing AGC systems. In particular, our solution learns the normal patterns of ACE time series and detects abnormal patterns caused by artificial attacks. Evaluations on the real ACE dataset show that our methods have high detection accuracy.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1997

Satellite Sensed Skin Sea Surface Temperature

Quantitative predictions of spatial and temporal changes the global climate rely heavily on the use of computer models. Unfortunately, such models cannot provide the basis for climate prediction because key physical processes are inadequately treated. Consequently, fine tuning procedures are often used to optimize the fit between model output and observational data and the validation of climate models using observations is essential if model based predictions of climate change are to be treated with any degree of confidence. Satellite Sea Surface Temperature (SST) observations provide high spatial and temporal resolution data which is extremely well suited to the initialization, definition of boundary conditions and, validation of climate models. In the case of coupled ocean-atmosphere models, the SST (or more correctly the 'Skin' SST (SSST)) is a fundamental diagnostic variable to consider in the validation process. Daily global SST maps derived from satellite sensors also provide adequate data for the detection of global patterns of change which, unlike any other SST data set, repeatedly extend into the southern hemisphere extra-tropical regions. Such data are essential to the success of the spatial 'fingerprint' technique, which seeks to establish a north-south asymmetry where warming is suppressed in the high latitude Southern Ocean. Some estimates suggest that there is a greater than 80% chance of directly detecting significant change (97.5 % confidence level) after 10-12 years of consistent global observations of mean sea surface temperature. However, these latter statements should be qualified with the assumption that a negligible drift in the observing system exists and that biases between individual instruments required to derive a long term data set are small. Given that current estimates for the magnitude of global warming of 0.015 K yr(sup -1) - 0.025 K yr(sup -1), satellite SST data sets need to be both accurate and stable if such a warming trend is to be confidently detected. Some of these activities are focussed to develop and deploy instrumentation suitable for the collection of precise in situ measurements of the SSST which can be used to improve the accuracy of satellite measurements, while others develop techniques to generate improved global analyses of sea surface temperature using historical data.

Donlon, Craig↗
DOE OSTI2019

DORI Reveals the Influence of Noncovalent Interactions on Covalent Bonding Patterns in Molecular Crystals Under Pressure

The study of organic molecular crystals under high pressure provides fundamental insight into crystal packing distortions and reveals mechanisms of phase transitions and the crystallization of polymorphs. These solid-state transformations can be monitored directly by analyzing electron charge densities that are experimentally obtained at high pressure. However, restricting the analysis to the featureless electron density does not reveal the chemical bonding nature and the existence of intermolecular interactions. This shortcoming can be resolved by the use of the DORI (density overlap region indicator) descriptor, which is capable of simultaneously detecting both covalent patterns and noncovalent interactions from electron density and its derivatives. Using the biscarbonyl[14]annulene crystal under pressure as an example, we demonstrate how DORI can be exploited on experimental electron densities to reveal and monitor changes in electronic structure patterns resulting from molecular compression. A novel approach based on a flood-fill-type algorithm is proposed for analyzing the topology of the DORI isosurface. This approach avoids the arbitrary selection of DORI isovalues and provides an intuitive way to assess how compression packing affects covalent bonding in organic solids.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Statistical Modeling and Analysis of k -Layer Coverage of Two-Dimensional Materials in Inkjet Printing Processes

Two-dimensional layered materials/flakes, also known as crystalline atom-thick layer nanosheets, have recently been receiving great attention in electronics fabrication due to their unique and intriguing properties. The k-layer coverage area (i.e., the area covered by k number of overlapping layers) of the printed flake pattern significantly impacts on the properties of the printed electronics. In this work, we constructed a statistical model to describe the k-layer coverage of randomly distributed two-dimensional materials. A series of results are obtained to provide not only the expectation but also the variance of the coverage area. The boundary effects on the random flakes coverage are also studied. In addition, an approximated statistical testing approach is also developed in this work to detect abnormal coverage patterns. Furthermore, the case studies based on simulated data and real flakes images obtained from the inkjet printing process demonstrate the accuracy and effectiveness of the proposed model and analysis methods.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Information Connections among Multiple Investors: Evolutionary Local Patterns Revealed by Motifs

The concept of motifs provides a fresh perspective for studying local patterns, which is useful for understanding the essence of a network structure. However, few previous studies have focused on the evolutionary characteristics of weighted motifs while further considering participants’ differences. We study how information connections differ among multiple investors. The evolutionary 10-year trend of weighted 3-motifs in China’s energy stock markets is explored for the networks of co-holding behaviors among shareholders, who are classified as companies, funds and individuals. Our works allow us to detect the preferential local patterns distributed among different agents as their fluctuate involvement in networks. We find that the diversity of shareholders contributes to the statistical significance of local patterns, while homophily always exist among individuals. Modules of information connections are stable among reserved investors, which is especially apparent among companies. Individuals prefer to keep their connections with companies and funds. Unsteady modules happen owing to strengthen links among funds during the time that they are main participants in stock markets. More details about multiple investors informationally connected in evolutionary local patterns can be detected by our work.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2016

HIGH-RESOLUTION SPECTROSCOPY OF EXTREMELY METAL-POOR STARS IN THE LEAST EVOLVED GALAXIES: BOÖTES II

We present high-resolution Magellan/MIKE spectra of the four brightest confirmed red giant stars in the ultra-faint dwarf galaxy Boötes II (Boo II). These stars all inhabit the metal-poor tail of the Boo II metallicity distribution function. The chemical abundance pattern of all detectable elements in these stars is consistent with that of the Galactic halo. However, all four stars have undetectable amounts of neutron-capture elements Sr and Ba, with upper limits comparable to the lowest ever detected in the halo or in other dwarf galaxies. One star exhibits significant radial velocity variations over time, suggesting it to be in a binary system. Its variable velocity has likely increased past determinations of the Boo II velocity dispersion. Our four stars span a limited metallicity range, but their enhanced α-abundances and low neutron-capture abundances are consistent with the interpretation that Boo II has been enriched by very few generations of stars. The chemical abundance pattern in Boo II confirms the emerging trend that the faintest dwarf galaxies have neutron-capture abundances distinct from the halo, suggesting the dominant source of neutron-capture elements in halo stars may be different than in ultra-faint dwarfs.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Optical readout of singlet fission biexcitons in a heteroacene with photoluminescence detected magnetic resonance

Molecular spin systems based on photoexcited triplet pairs formed via singlet fission (SF) are attractive as carriers of quantum information because of their potentially pure and controllable spin polarization, but developing systems that offer optical routes to readout as well as initialization is challenging. Herein, we characterize the electron spin magnetic resonance change in the photoluminescence intensity for a tailored organic molecular crystal while sweeping a microwave drive up to 10 GHz in a broadband loop structure. We observe resonant transitions for both triplet and quintet spin sublevel populations showing their optical sensitivity and revealing the zero-field parameters for each. We map the evolution of these spectra in both microwave frequency and magnetic field, producing a pattern of optically detected magnetic resonance (ODMR) peaks. Fits to these data using a suitable model suggest significant spin polarization in this system with orientation selectivity. Unusual excitation intensity dependence is also observed, which inverts the sign of the ODMR signal for the triplet features, but not for the quintet. These observations demonstrate optical detection of the spin sublevel population dictated by SF and intermolecular geometry, and highlight anisotropic and multi-scale dynamics of triplet pairs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Synchrotron Radiation in Analysis of Structural Transformations Under Friction Conditions of Carbon Steel

The paper presents results of the structural transformations in the surface of carbon steel specimens during the first tens of cycles of the friction loading with a hard-alloy indenter. The widespread type AISI 1020 carbon steel is used in the experiments which are carried out on the Microfocus Beamline ID13 of the European Synchrotron Radiation Facility. The experimental setup is designed to record the diffraction patterns during the friction. It is shown that at the initial stage of friction, the diffraction maxima significantly broaden due to the defect accumulation in the crystal lattice and, as a consequence, the growth in elastic micro-distortions and the size reduction of the coherent scattering areas. A serious increase is observed in the intensity of reflection from planes of {110} family due to the formation of the respective texture in the surface layers of steel specimens. A non-destructive method is used to detect the diffraction patterns both for non-moving and moving specimens.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2016

Conserved patterns hidden within group A Streptococcus M protein hypervariability recognize human C4b-binding protein

No vaccine exists against group A Streptococcus (GAS), a leading cause of worldwide morbidity and mortality. A severe hurdle is the hypervariability of its major antigen, the M protein, with >200 different M types known. Neutralizing antibodies typically recognize M protein hypervariable regions (HVRs) and confer narrow protection. In stark contrast, human C4b-binding protein (C4BP), which is recruited to the GAS surface to block phagocytic killing, interacts with a remarkably large number of M protein HVRs (apparently ~90%). Such broad recognition is rare, and we discovered a unique mechanism for this through the structure determination of four sequence-diverse M proteins in complexes with C4BP. The structures revealed a uniform and tolerant ‘reading head’ in C4BP, which detected conserved sequence patterns hidden within hypervariability. Our results open up possibilities for rational therapies that target the M–C4BP interaction, and also inform a path towards vaccine design.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Stability-driven nonnegative matrix factorization to interpret spatial gene expression and build local gene networks

Spatial gene expression patterns enable the detection of local covariability and are extremely useful for identifying local gene interactions during normal development. The abundance of spatial expression data in recent years has led to the modeling and analysis of regulatory networks. The inherent complexity of such data makes it a challenge to extract biological information. We developed staNMF, a method that combines a scalable implementation of nonnegative matrix factorization (NMF) with a new stability-driven model selection criterion. When applied to a set of Drosophila early embryonic spatial gene expression images, one of the largest datasets of its kind, staNMF identified 21 principal patterns (PP). Providing a compact yet biologically interpretable representation of Drosophila expression patterns, PP are comparable to a fate map generated experimentally by laser ablation and show exceptional promise as a data-driven alternative to manual annotations. Our analysis mapped genes to cell-fate programs and assigned putative biological roles to uncharacterized genes. Finally, we used the PP to generate local transcription factor regulatory networks. Spatially local correlation networks were constructed for six PP that span along the embryonic anterior-posterior axis. Using a two-tail 5% cutoff on correlation, we reproduced 10 of the 11 links in the well-studied gap gene network. In conclusion, the performance of PP with the Drosophila data suggests that staNMF provides informative decompositions and constitutes a useful computational lens through which to extract biological insight from complex and often noisy gene expression data.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1971

Pattern recognition technique

Technique operates regardless of pattern rotation, translation or magnification and successfully detects out-of-register patterns. It improves accuracy and reduces cost of various optical character recognition devices and page readers and provides data input to computer.

Hong, J. P.↗
NASA NTRS1994

The design and implementation of EPL: An event pattern language for active databases

The growing demand for intelligent information systems requires closer coupling of rule-based reasoning engines, such as CLIPS, with advanced data base management systems (DBMS). For instance, several commercial DBMS now support the notion of triggers that monitor events and transactions occurring in the database and fire induced actions, which perform a variety of critical functions, including safeguarding the integrity of data, monitoring access, and recording volatile information needed by administrators, analysts, and expert systems to perform assorted tasks; examples of these tasks include security enforcement, market studies, knowledge discovery, and link analysis. At UCLA, we designed and implemented the event pattern language (EPL) which is capable of detecting and acting upon complex patterns of events which are temporally related to each other. For instance, a plant manager should be notified when a certain pattern of overheating repeats itself over time in a chemical process; likewise, proper notification is required when a suspicious sequence of bank transactions is executed within a certain time limit. The EPL prototype is built in CLIPS to operate on top of Sybase, a commercial relational DBMS, where actions can be triggered by events such as simple database updates, insertions, and deletions. The rule-based syntax of EPL allows the sequences of goals in rules to be interpreted as sequences of temporal events; each goal can correspond to either (1) a simple event, or (2) a (possibly negated) event/condition predicate, or (3) a complex event defined as the disjunction and repetition of other events. Various extensions have been added to CLIPS in order to tailor the interface with Sybase and its open client/server architecture.

Giuffrida, G.↗
DOE OSTI2016

All-electrical detection of spin dynamics in magnetic antidot lattices by the inverse spin Hall effect

The understanding of spin dynamics in laterally confined structures on sub-micron length scales has become a significant aspect of the development of novel magnetic storage technologies. Numerous ferromagnetic resonance measurements, optical characterization by Kerr microscopy and Brillouin light scattering spectroscopy and x-ray studies were carried out to detect the dynamics in patterned magnetic antidot lattices. Here, we investigate Oersted-field driven spin dynamics in rectangular Ni80Fe20/Pt antidot lattices with different lattice parameters by electrical means. When the system is driven to resonance, a dc voltage across the length of the sample is detected that changes its sign upon field reversal, which is in agreement with a rectification mechanism based on the inverse spin Hall effect. Furthermore, we show that the voltage output scales linearly with the applied microwave drive in the investigated range of powers. Lastly, our findings have direct implications on the development of engineered magnonics applications and devices.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2019

CSK hopping pattern model for visible light communication networks

This paper proposes a new channel access method for visible light communications. The transmitter uses the CSK hopping pattern mode to load data to the R, G, and B light-emitting diodes of LEDs and establishes the network access point (AP) of the LEDs for the illumination coverage area. The coordinator controls the work of each AP to ensure that it simultaneously uses different color patterns to distinguish its respective networks. When the receiver (mobile terminal) detects a particular color pattern in the illumination coverage area, it establishes a communication access network process with the AP that is transmitting the particular color pattern. The advantage of this method is that interference between adjacent APs can be avoided. In addition, due to the simplification of the access network, the proposed CSK hopping model can shorten delays in the terminal’s access network. Through modeling and simulation, it is found that this method can effectively support network power and reduce network delay. Moreover, the fairness and stability of terminals that access the network are improved to a certain extent.

42 ENGINEERING↗