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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

A scalable new mechanism to store, query and serve the ATLAS detector description through a REST web API

Until now, geometry information for the detector description of the ATLAS experiment was only defined in C++ code, stored in online relational databases integrated into the experiment's frameworks or described in files with text-based markup languages. In all cases, to build and use the complete detector geometry, a full software stack was needed. In this paper, we present a new and scalable mechanism to store the geometry data and to query and serve the detector description data through a web interface and a REST API. This new approach decouples the geometry information from the experiment's framework. Moreover, it provides new functionalities to users, who can now search for specific volumes and get partial detector description, or filter geometry data based on custom criteria. We present two approaches to build a REST API to serve geometry data, based on two different technologies used in other fields and communities: The graph database Neo4j and the search engine ElasticSearch. We describe their characteristics, and we compare them in a HEP context.

47 OTHER INSTRUMENTATION↗
DOE OSTI2018

False alarms and the IMS infrasound network: Understanding the factors influencing the creation of false events

The International Monitoring System (IMS) infrasound network has been designed to acquire the necessary data to detect and locate explosions in the atmosphere with a yield equivalent to 1 kiloton of TNT anywhere on Earth. A major associated challenge is the task of automatically processing data from all IMS infrasound stations to identify possible nuclear tests for subsequent review by analysts. This paper is the first attempt to quantify the false alarm rate (FAR) of the IMS network, and in particular to assess how the FAR is affected by the numbers and distributions of detections at each infrasound station. To ensure that the results are sufficiently general, and not dependent entirely on one detection algorithm, the assessment is based on two detection algorithms that can be thought of as end members in their approach to the trade-off between missed detections and false alarms. The results show that the FAR for events formed at only two arrays is extremely high (ranging from 10’s to 100’s of false events per day across the IMS network, depending on the detector tuning). It is further shown that the FAR for events formed at three or more IMS arrays is driven by ocean-generated waves (microbaroms), despite efforts within both detection algorithms for avoiding these signals, indicating that further research into this issue is merited. Overall, the results highlight the challenge of processing data from a globally sparse network of stations to detect and form events. On the basis of these results, it is shown that further work on understanding signal and noise characteristics is needed before attempting to automatically form events detected at only two arrays on the global network. In particular, more work is required to reduce false alarms caused by the detection of microbarom signals.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Quantitative approaches for multiscale structural analysis with atomic resolution electron microscopy

Atomic-resolution imaging with scanning transmission electron microscopy is a powerful tool for characterizing the nanoscale structure of materials, in particular features such as defects, local strains, and symmetry-breaking distortions. In addition to advanced instrumentation, the effectiveness of the technique depends on computational image analysis to extract meaningful features from complex datasets recorded in experiments, which can be complicated by the presence of noise and artifacts, small or overlapping features, and the need to scale analysis over large representative areas. Here, we present image analysis approaches which synergize real and reciprocal space information to efficiently and reliably obtain meaningful structural information with picometer scale precision across hundreds of nanometers of material from atomic-resolution electron microscope images. Damping superstructure peaks in reciprocal space allows symmetry-breaking structural distortions to be disentangled from other sources of inhomogeneity and measured with high precision. Real-space fitting of the wavelike signals resulting from Fourier filtering enables absolute quantification of lattice parameter variations and strain, as well as the uncertainty associated with these measurements. Implementations of these algorithms are made available as an open source python package.

36 MATERIALS SCIENCE↗
DOE OSTI2018

CONTIN XPCS : software for inverse transform analysis of X-ray photon correlation spectroscopy dynamics

X-ray photon correlation spectroscopy (XPCS) and dynamic light scattering (DLS) reveal materials dynamics using coherent scattering, with XPCS permitting the investigation of dynamics in a more diverse array of materials than DLS. Heterogeneous dynamics occur in many material systems. The authors' recent work has shown how classic tools employed in the DLS analysis of heterogeneous dynamics can be extended to XPCS, revealing additional information that conventional Kohlrausch exponential fitting obscures. The present work describes the software implementation of inverse transform analysis of XPCS data. This software, called CONTIN XPCS , is an extension of traditional CONTIN analysis and accommodates the various dynamics encountered in equilibrium XPCS measurements.

36 MATERIALS SCIENCE↗
DOE OSTI2011

Calculation of the performance of {sup 3}He alternative detectors with MCNPX

This paper describes the techniques that are available to calculate the performance of {sup 3}He alternative detectors using MCNPX. Calculations of the performance of safeguards detectors that use {sup 3}He have been successfully carried out for many years. In the case of coincidence or multiplicity counting, specific tallies have been implemented to calculate the Singles, Doubles and Triples counting rates. The implementation of the method was done in such a way that it equates every capture in some nuclide in the detection zone with the production of an electronic pulse from the detector. This is a very good approximation for {sup 3}He detectors and BF{sub 3} detectors. However it is not appropriate for detectors such as boron-lined proportional counters, in which the fraction of capture events leading to an electronic pulse above threshold is very dependent on the geometric arrangement, in particular the thickness and composition of the boron-containing layer. This paper gives calculations of the ideal pulse height distributions to be expected from different detector types and gives values for the probability, as a function of detector energy threshold, that a neutron capture reaction will cause an electronic pulse from the detector. This is termed the electronic efficiency. This electronic detection efficiency depends very little on the energy of the captured neutron, which in most practical cases are heavily weighted towards thermal energies. It does not depend on the position of the source neutron or moderation in the sample. For cases of interest to nuclear safeguards, measurement of uranium and plutonium in specially designed detectors, the spectrum of detected neutrons is fairly constant and thus the electronic detection efficiency becomes a detector constant. The paper discusses how the electronic detection efficiency needs to be included in the calculation of Singles, Doubles and Triples, and describes proposals to improve the tallying capability of MCNPX for such cases. (authors)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2015

Audiovisual Fusion: Challenges and New Approaches

In this study, we review recent results on audiovisual (AV) fusion. We also discuss some of the challenges and report on approaches to address them. One important issue in AV fusion is how the modalities interact and influence each other. This review will address this question in the context of AV speech processing, and especially speech recognition, where one of the issues is that the modalities both interact but also sometimes appear to desynchronize from each other. An additional issue that sometimes arises is that one of the modalities may be missing at test time, although it is available at training time; for example, it may be possible to collect AV training data while only having access to audio at test time. We will review approaches to address this issue from the area of multiview learning, where the goal is to learn a model or representation for each of the modalities separately while taking advantage of the rich multimodal training data. In addition to multiview learning, we also discuss the recent application of deep learning (DL) toward AV fusion. We finally draw conclusions and offer our assessment of the future in the area of AV fusion.

47 OTHER INSTRUMENTATION↗
DOE OSTI2016

Ubiquitous Low-Cost Functionalized Multi-Walled Carbon Nanotube Sensors for Distributed Methane Leak Detection

This paper presents a highly sensitive, energy efficient and low-cost distributed methane (CH 4 ) sensor system (DMSS) for continuous monitoring, detection, and localization of CH 4 leaks in natural gas infrastructure, such as transmission and distribution pipelines, wells, and production pads. The CH 4 sensing element, a key component of the DMSS, consists of a metal oxide nanocrystal (MONC) functionalized multi-walled carbon nanotube (MWCNT) mesh which, in comparison to existing literature, shows stronger relative resistance change while interacting with lower parts per million (ppm) concentration of CH 4 . A Gaussian plume triangulation algorithm has been developed for the DMSS. Given a geometric model of the surrounding environment the algorithm can precisely detect and localize a CH 4 leak as well as estimate its mass emission rate. A UV-based surface recovery technique making the sensor recover 10 times faster than the reported ones is presented for the DMSS. In conclusion, a control algorithm based on the UV-accelerated recovery is developed which facilitates faster leak detection.

47 OTHER INSTRUMENTATION↗
DOE OSTI2018

Domain-Adapted Convolutional Networks for Satellite Image Classification: A Large-Scale Interactive Learning Workflow

Satellite imagery often exhibits large spatial extent areas that encompass object classes with considerable variability. This often limits large-scale model generalization with machine learning algorithms. Notably, acquisition conditions, including dates, sensor position, lighting condition, and sensor types, often translate into class distribution shifts introducing complex nonlinear factors and hamper the potential impact of machine learning classifiers. Here, this article investigates the challenge of exploiting satellite images using convolutional neural networks (CNN) for settlement classification where the class distribution shifts are significant. We present a large-scale human settlement mapping workflow based-off multiple modules to adapt a pretrained CNN to address the negative impact of distribution shift on classification performance. To extend a locally trained classifier onto large spatial extents areas we introduce several submodules: First, a human-in-the-loop element for relabeling of misclassified target domain samples to generate representative examples for model adaptation; second, an efficient hashing module to minimize redundancy and noisy samples from the mass-selected examples; and third, a novel relevance ranking module to minimize the dominance of source example on the target domain. The workflow presents a novel and practical approach to achieve large-scale domain adaptation with binary classifiers that are based-off CNN features. Experimental evaluations are conducted on areas of interest that encompass various image characteristics, including multisensors, multitemporal, and multiangular conditions. Domain adaptation is assessed on source–target pairs through the transfer loss and transfer ratio metrics to illustrate the utility of the workflow.

47 OTHER INSTRUMENTATION↗
DOE OSTI2017

Spatial-Spectral Representation for X-Ray Fluorescence Image Super-Resolution

X-ray fluorescence (XRF) scanning of works of art is becoming an increasing popular nondestructive analyticalmethod. The high quality XRF spectra is necessary to obtain significant information on both major and minor elements used for characterization and provenance analysis. However, there is a tradeoff between the spatial resolution of an XRF scan and the signalto- noise ratio (SNR) of each pixel’s spectrum, due to the limited scanning time. In this project, we propose an XRF image super-resolution method to address this tradeoff; thus, obtaining a high spatial resolution XRF scan with high SNR. We fuse a lowresolution XRF image and a conventional RGB high-resolution image into a product of both high spatial and high spectral resolution XRF image. There is no guarantee of a one to one mapping between XRF spectrum and RGB color since, for instance, paintings with hidden layers cannot be detected in visible but can in X-ray wavelengths. We separate the XRF image into the visible and nonvisible components. The spatial resolution of the visible component is increased utilizing the high-resolution RGB image, whereas the spatial resolution of the non-visible component is increased using a total variation super-resolution method. Finally, the visible and nonvisible components are combined to obtain the final result.

Dai, Qiqin↗
DOE OSTI2018

Gaussian Mixture Model-Based Ensemble Kalman Filter for Machine Parameter Calibration

This letter proposes a novel Gaussian mixture model-based ensemble Kalman filter (GMM-EnKF) approach to the accurate calibration of the parameters of machine dynamic models. This approach aims to overcome some practical challenges of machine parameter calibration. Results show the proposed approach can provide high-accuracy calibrated parameters even when the machine operates under unbalanced network conditions and the measurement noises are non-Gaussian.

Fan, Rui↗
DOE OSTI2025

Improved Gas Plume Identification Using Nearest Neighbor Methods for Background Estimation

Longwave infrared (LWIR) hyperspectral imaging (HSI) can be used for many tasks in remote sensing, including detecting and identifying effluent gases by LWIR sensors on airborne platforms. Identification is used after detection to increase confidence in weakly detected plumes, reduce false positives from detection, and distinguish between similar and confounding material signatures. Background estimation is an important step used to reveal the unique spectral characteristics of the detected gas, allowing the identification model to determine what the gas is specifically. The importance of proper background estimation increases when dealing with weak signals, large libraries of gases of interest, and uncommon or heterogeneous backgrounds. In this article, we propose two methods for background estimation: a novel k-nearest segments (KNS) algorithm and the standard k-nearest neighbors (KNN) algorithm. We test our methods and three existing background estimation methods for comparison against global background estimation to determine which performs best at estimating the true background radiance under a plume and for increasing identification confidence using a neural network classification model. We compare the different methods using 640 simulated weak plumes in an urban environment. For identification, our KNS algorithm improves median neural network identification confidence by 53.2%. For background radiance estimation, the KNN algorithm provides a median of 49 times less RMSE than global background estimation. Furthermore, KNN is the easiest method to tune for different plumes, making it an excellent “out of the box” background estimator.

47 OTHER INSTRUMENTATION↗
DOE OSTI2015

Objective analysis of impressed chisel toolmarks

Historical and recent challenges to the practice of comparative forensic examination have created a driving force for the formation of objective methods for toolmark identification. In this study, fifty sequentially manufactured chisels were used to create impression toolmarks in lead (500 toolmarks total). An algorithm previously used to statistically separate known matching and nonmatching striated screwdriver marks and quasi-striated plier marks was used to evaluate the chisel marks. Impression toolmarks, a more complex form of toolmark, pose a more difficult test for the algorithm that was originally designed for striated toolmarks. Lastly, results show in this instance that the algorithm can separate matching and nonmatching impression marks, providing further validation of the assumption that toolmarks are identifiably unique.

47 OTHER INSTRUMENTATION↗
DOE OSTI2014

Comparison of Second-Order Loads on a Semisubmersible Floating Wind Turbine: Preprint

As offshore wind projects move to deeper waters, floating platforms become the most feasible solution for supporting the turbines. The oil and gas industry has gained experience with floating platforms that can be applied to offshore wind projects. This paper focuses on the analysis of second-order wave loading on semisubmersible platforms. Semisubmersibles, which are being chosen for different floating offshore wind concepts, are particularly prone to slow-drift motions. The slack catenary moorings usually result in large natural periods for surge and sway motions (more than 100 s), which are in the range of the second-order difference-frequency excitation force. Modeling these complex structures requires coupled design codes. Codes have been developed that include turbine aerodynamics, hydrodynamic forces on the platform, restoring forces from the mooring lines, flexibility of the turbine, and the influence of the turbine control system. In this paper two different codes are employed: FAST, which was developed by the National Renewable Energy Laboratory, and aNySIM, which was developed by the Maritime Research Institute Netherlands. The hydrodynamic loads are based on potential-flow theory, up to the second order. Hydrodynamic coefficients for wave excitation, radiation, and hydrostatic forces are obtained with two different panel codes, WAMIT (developed by the Massachusetts Institute of Technology) and DIFFRAC (developed by MARIN). The semisubmersible platform, developed for the International Energy Agency Wind Task 30 Offshore Code Comparison Collaboration Continuation project is used as a reference platform. Irregular waves are used to compare the behavior of this platform under slow-drift excitation loads. The results from this paper highlight the effects of these loads on semisubmersible-type platforms, which represent a promising solution for the commercial development of the offshore deepwater wind resource.

17 WIND ENERGY↗
DOE OSTI2010

A new generic method for the semi-automatic extraction of river and road networks in low and mid-resolution satellite images

This paper addresses the problem of semi-automatic extraction of road or hydrographic networks in satellite images. For that purpose, we propose an approach combining concepts arising from mathematical morphology and hydrology. The method exploits both geometrical and topological characteristics of rivers/roads and their tributaries in order to reconstruct the complete networks. It assumes that the images satisfy the following two general assumptions, which are the minimum conditions for a road/river network to be identifiable and are usually verified in low- to mid-resolution satellite images: (i) visual constraint: most pixels composing the network have similar spectral signature that is distinguishable from most of the surrounding areas; (ii) geometric constraint: a line is a region that is relatively long and narrow, compared with other objects in the image. While this approach fully exploits local (roads/rivers are modeled as elongated regions with a smooth spectral signature in the image and a maximum width) and global (they are structured like a tree) characteristics of the networks, further directional information about the image structures is incorporated. Namely, an appropriate anisotropic metric is designed by using both the characteristic features of the target network and the eigen-decomposition of the gradient structure tensor of the image. Following, the geodesic propagation from a given network seed with this metric is combined with hydrological operators for overland flow simulation to extract the paths which contain most line evidence and identify them with the target network.

47 OTHER INSTRUMENTATION↗
DOE OSTI2015

Global Feedback Simulator

GFS is a simulation engine that is used for the characterization of Accelerator performance parameters based on the machine layout, configuration and noise sources. It combines extensively tested Feedback models with a longitudinal phase space tracking simulator along with the interaction between the two via beam-based feedback using a computationally efficient simulation engine. The models include beam instrumentation, considerations on loop delays for in both the R and beam-based feedback loops, as well as the ability to inject noise (both correlated and uncorrelated) at different points of the machine including a full characterization of the electron gun performance parameters.

Doolittle, Lawrence↗