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At least 1,387 records · Page 77

Unleashing the Power of Wide-Area Data Analytics for Enhanced Grid Visibility

We report that the operation of modern electric transmission systems relies increasingly on the use of advanced sensing and synchronized-measurement technologies. These technologies collect and collate a wide variety of data from disperse locations to monitor the health of network, obtain fast and accurate diagnosis of systemic changes, and detect signs of anomalies and instabilities at an early stage. In view of the far-reaching blackout risk from potential damages to critical transmission grid assets (due to severe disturbances, physical attacks, and extreme weather events), stealthy activities that compromise the operation of wide-area sensing, communication, and control systems could cripple the entire cyber-physical smart-grid infrastructure. To this end, achieving robust event identification, ensuring bulk system observability, and developing actionable intelligence (by fostering data-driven decision making under imminent threat of complex, multifaceted attacks and disruptions) remain key challenges for sustaining a resilient power grid operation.

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Averaging analysis for discrete time and sampled data adaptive systems

Earlier continuous time averaging theorems are extended to the nonlinear discrete time case. Theorems for the study of the convergence analysis of discrete time adaptive identification and control systems are used. Instability theorems are also derived and used for the study of robust stability and instability of adaptive control schemes applied to sampled data systems. As a by product, the effects of sampling on unmodeled dynamics in continuous time systems are also studied.

Fu, Li-Chen↗

Identification of Program Signatures from Cloud Computing System Telemetry Data

Malicious cloud computing activity can take many forms, including running unauthorized programs in a virtual environment. Detection of these malicious activities while preserving the privacy of the user is an important research challenge. Prior work has shown the potential viability of using cloud service billing metrics as a mechanism for proxy identification of malicious programs. Previously this novel detection method has been evaluated in a synthetic and isolated computational environment. In this paper we demonstrate the ability of billing metrics to identify programs, in an active cloud computing environment, including multiple virtual machines running on the same hypervisor. The open source cloud computing platform OpenStack, is used for private cloud management at Pacific Northwest National Laboratory. OpenStack provides a billing tool (Ceilometer) to collect system telemetry measurements. We identify four different programs running on four virtual machines under the same cloud user account. Programs were identified with up to 95% accuracy. This accuracy is dependent on the distinctiveness of telemetry measurements for the specific programs we tested. Future work will examine the scalability of this approach for a larger selection of programs to better understand the uniqueness needed to identify a program. Additionally, future work should address the separation of signatures when multiple programs are running on the same virtual machine.

Nichols, Nicole M.↗

DeepGhostBusters: Using Mask R-CNN to Detect and Mask Ghosting and Scattered-Light Artifacts from Optical Survey Images

Wide-field astronomical surveys are often affected by the presence of undesirable reflections (often known as "ghosting artifacts" or "ghosts") and scattered-light artifacts. The identification and mitigation of these artifacts is important for rigorous astronomical analyses of faint and low-surface-brightness systems. However, the identification of ghosts and scattered-light artifacts is challenging due to a) the complex morphology of these features and b) the large data volume of current and near-future surveys. In this work, we use images from the Dark Energy Survey (DES) to train, validate, and test a deep neural network (Mask R-CNN) to detect and localize ghosts and scattered-light artifacts. We find that the ability of the Mask R-CNN model to identify affected regions is superior to that of conventional algorithms and traditional convolutional neural networks methods. We propose that a multi-step pipeline combining Mask R-CNN segmentation with a classical CNN classifier provides a powerful technique for the automated detection of ghosting and scattered-light artifacts in current and near-future surveys.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Identification and design of novel polymer-based mechanical transducers: A nano-structural model for thin film indentation

Mechanical characterization is important for understanding small-scale systems and developing devices, particularly at the interface of biology, medicine, and nanotechnology. Yet, monitoring sub-surface forces is challenging with current technologies like atomic force microscopes (AFMs) or optical tweezers due to their probe sizes and sophisticated feedback mechanisms. An alternative transducer design relying on the indentation mechanics of a compressible thin polymer would be an ideal system for more compact and versatile probes, facilitating measurements in situ or in vivo. However, application-specific tuning of a polymer's mechanical properties can be burdensome via experimental optimization. Therefore, efficient transducer design requires a fundamental understanding of how synthetic parameters such as the molecular weight and grafting density influence the bulk material properties that determine the force response. In this work, we apply molecular-level polymer scaling laws to a first order elastic foundation model, relating the conformational state of individual polymer chains to the macroscopic compression of thin film systems. A parameter sweep analysis was conducted to observe predicted model trends under various system conditions and to understand how nano-structural elements influence the material stiffness. We validate the model by comparing predicted force profiles to experimental AFM curves for a real polymer system and show that it has reasonable predictive power for initial estimates of the force response, displaying excellent agreement with experimental force curves. We also present an analysis of the force sensitivity of an example transducer system to demonstrate identification of synthetic protocols based on desired mechanical properties. These results highlight the usefulness of this simple model as an aid for the design of a new class of compact and tunable nanomechanical force transducers.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

CF Neutron Time of Flight Transmission for Material Identification for weapons Trainers

The neutron transmission, elastic scattering, and non-elastic reactions can be used to distinguish various isotopes. Neutron transmission as a function of energy can be used in some cases to identify materials in unknown objects. A time tagged californium source that provides a fission spectrum of neutrons is a useful source for neutron time-of-flight (TOF) transmission measurements. Many nuclear weapons trainer units for a particular weapons system (no fissile, but of same weight and center of gravity) in shipping containers were returned to the National Nuclear Security Administration Y-12 National Security Complex in the mid 1990s. Nuclear Materials Identification System (NMIS) measurements with a time tagged californium neutron source were used to verify that these trainers did not contain fissile material. In these blind tests, the time distributions of neutrons through the containers were measured as a function of position to locate the approximate center of the trainer in the container. Measurements were also performed with an empty container. TOF template matching measurements were then performed at this location for a large number of units. In these measurements, the californium source was located on one end of the container and a proton recoil scintillator was located on the other end. The variations in the TOF transmission for times corresponding to 1 to 5 MeV were significantly larger than statistical. Further examination of the time distribution or the energy dependence revealed that these variations corresponded to the variations in the neutron cross section of aluminum averaged over the energy resolution of the californium TOF measurement with a flight path of about 90 cm. Measurements using different thicknesses of aluminum were also performed with the source and detector separated the same distance as for the trainer measurements. These comparison measurements confirmed that the material in the trainers was aluminum, and the total thickness of aluminum through the trainers was determined. This is an example of how californium transmission TOF measurements can be used to identify materials.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Data dependent systems methodology for lumped mass modeling of structures

Limitations of the frequency domain methods in analyzing structura1 vibrations has created an awareness of the comparative merits of the time domain methods. Although time domain methods would be ideal for modeling large precisions space systems, the popular methods based on fitting theoretical response to actual data by least squares are too sensitive to noise and require too much data to be suitable for orbiting space crafts. This paper briefly reviews the theory and illustrative applications of a time domain methodology called Data Dependent Systems (DDS) that eliminates these limitations. Simulation results are presented to demonstrate a better than 4-place accuracy in the identifications of all system parameters, both modal (frequencies, damping ratios, and mode shapes) and physical (mass, stiffness, and damping matrices).

Pandit, Sudhakar M.↗

The circumstellar environments of intermediate mass main sequence stars

Analysis of archival Infrared Astronomy Satellite (IRAS) and International Ultraviolet Explorer (IUE) data resulted in identification of accreting gas toward a 2.8 Myr post-Herbig Be star in the R CrA star formation region, and identification of accreting gas toward HD 93563, previously identified as a classical Be star. Accreting gas was also detected toward two B(e) stars of previously controversial evolutionary state, resulting in identification of these systems as pre-Main Sequence Herbig Be stars viewed edge-on to their circumstellar disks. In parallel with this effort, accreting gas was detected toward the Herbig Ae star HR 5999, resulting in development of identification criteria for edge-on PMS proto-planetary disk systems. The work on individual stars is described.

Grady, Carol A.↗

Experimental Development of a Failure Detection Scheme for Large Space Structures

Large flexible spacecraft may require control systems consisting of large numbers of sensors and actuators. To assure a viable mission, the control system should tolerate failures of some of the control components. Hence, it is desirable to automate the process of failure detection, identification, and control system reconfiguration (FDI&R). Some of the opportunities to accommodate failure in the spacecraft design are reviewed. Some methods for FDI&R are presented in overview, and the method chosen for experimental testing is described. Finally, the experimental activities leading to the validation of the technique are presented.

Montgomery, R. C.↗

Design for interaction between humans and intelligent systems during real-time fault management

Initial results are reported to provide guidance and assistance for designers of intelligent systems and their human interfaces. The objective is to achieve more effective human-computer interaction (HCI) for real time fault management support systems. Studies of the development of intelligent fault management systems within NASA have resulted in a new perspective of the user. If the user is viewed as one of the subsystems in a heterogeneous, distributed system, system design becomes the design of a flexible architecture for accomplishing system tasks with both human and computer agents. HCI requirements and design should be distinguished from user interface (displays and controls) requirements and design. Effective HCI design for multi-agent systems requires explicit identification of activities and information that support coordination and communication between agents. The effects are characterized of HCI design on overall system design and approaches are identified to addressing HCI requirements in system design. The results include definition of (1) guidance based on information level requirements analysis of HCI, (2) high level requirements for a design methodology that integrates the HCI perspective into system design, and (3) requirements for embedding HCI design tools into intelligent system development environments.

Malin, Jane T.↗

Manned space flight nuclear system safety. Volume 6: Space base nuclear system safety plan

A qualitative identification of the steps required to assure the incorporation of radiological system safety principles and objectives into all phases of a manned space base program are presented. Specific areas of emphasis include: (1) radiological program management, (2) nuclear system safety plan implementation, (3) impact on program, and (4) summary of the key operation and design guidelines and requirements. The plan clearly indicates the necessity of considering and implementing radiological system safety recommendations as early as possible in the development cycle to assure maximum safety and minimize the impact on design and mission plans.

Source record↗

Stochastic control system parameter identifiability

The parameter identification problem of general discrete time, nonlinear, multiple input/multiple output dynamic systems with Gaussian white distributed measurement errors is considered. The knowledge of the system parameterization was assumed to be known. Concepts of local parameter identifiability and local constrained maximum likelihood parameter identifiability were established. A set of sufficient conditions for the existence of a region of parameter identifiability was derived. A computation procedure employing interval arithmetic was provided for finding the regions of parameter identifiability. If the vector of the true parameters is locally constrained maximum likelihood (CML) identifiable, then with probability one, the vector of true parameters is a unique maximal point of the maximum likelihood function in the region of parameter identifiability and the constrained maximum likelihood estimation sequence will converge to the vector of true parameters.

Lee, C. H.↗

Dual-Remote Raman Technology for In-Situ Identification of Tank Waste - 13549

A new Raman spectroscopic system for in-situ identification of the composition of solid nuclear tank waste is being developed by collaborative effort between Pacific Northwest National Laboratory (PNNL) and EIC Laboratories, Inc. The recent advancements in Raman technology allow probing the chemical composition of the tank waste without sample collection. In the newly tested configuration, the Raman probe is installed on the top of the tank riser and sends the incident laser beam to the bottom of the tank, 10 - 70 feet away. The returning light containing chemical information is collected by the Raman probe and is transmitted via fiber optic cable to the spectrometer located outside the tank farm area. This dual remote technology significantly expands currently limited options for the safe rapid in-situ identification of the solid tank waste needed for the retrieval decisions. The developed Raman system was extensively tested for acceptability prior to tank farm deployment. This testing included calibration of the system with respect of the distance between the Raman probe and the sample, incident laser beam angle, and presence of the optical interferences. The Raman system was successfully deployed on Tank C-111 at the US DOE Hanford site. As the result of this deployment, the composition of the hardpan at the bottom of C-111 tank was identified. Further development of the dual-remote Raman technology will provide a significant safety enhancement eliminating the potential of personnel radiation exposure associated with the grab sample collection and expands options of the rapid and cost-effective in-situ chemical analysis of the tank waste. (authors)

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Linear and nonlinear trending and prediction for AVHRR time series data

The variability of AVHRR calibration coefficient in time was analyzed using algorithms of linear and non-linear time series analysis. Specifically we have used the spline trend modeling, autoregressive process analysis, incremental neural network learning algorithm and redundancy functional testing. The analysis performed on available AVHRR data sets revealed that (1) the calibration data have nonlinear dependencies, (2) the calibration data depend strongly on the target temperature, (3) both calibration coefficients and the temperature time series can be modeled, in the first approximation, as autonomous dynamical systems, (4) the high frequency residuals of the analyzed data sets can be best modeled as an autoregressive process of the 10th degree. We have dealt with a nonlinear identification problem and the problem of noise filtering (data smoothing). The system identification and filtering are significant problems for AVHRR data sets. The algorithms outlined in this study can be used for the future EOS missions. Prediction and smoothing algorithms for time series of calibration data provide a functional characterization of the data. Those algorithms can be particularly useful when calibration data are incomplete or sparse.

Smid, J.↗

The Consultative Committee for Space Data Systems Standards program

The objectives of the Consultative Committee for Space Data Systems (CCSDS) include the identification of those common elements of space data systems which, if implemented in a standardized way, will significantly enhance the operation of future cooperative space missions. Recommendations of the CCSDS include packet telemetry and telecommand concepts, coding designs, ancillary data parameters and formats, and data exchange conventions. Consideration is given to the application of CCSDS recommendations.

Costa, S. Richard↗

Estimation of Stability and Control Derivatives of an F-15

A technique for real-time estimation of stability and control derivatives (derivatives of moment coefficients with respect to control-surface deflection angles) was used to support a flight demonstration of a concept of an indirect-adaptive intelligent flight control system (IFCS). Traditionally, parameter identification, including estimation of stability and control derivatives, is done post-flight. However, for the indirect-adaptive IFCS concept, parameter identification is required during flight so that the system can modify control laws for a damaged aircraft. The flight demonstration was carried out on a highly modified F-15 airplane (see Figure 1). The main objective was to estimate the stability and control derivatives of the airplane in nearly real time. A secondary goal was to develop a system to automatically assess the quality of the results, so as to be able to tell a learning neural network which data to use. Parameter estimation was performed by use of Fourier-transform regression (FTR) a technique developed at NASA Langley Research Center. FTR is an equation- error technique that operates in the frequency domain. Data are put into the frequency domain by use of a recursive Fourier transform for a discrete frequency set. This calculation simplifies many subsequent calculations, removes biases, and automatically filters out data beyond the chosen frequency range. FTR as applied here was tailored to work with pilot inputs, which produce correlated surface positions that prevent accurate parameter estimates, by replacing half the derivatives with predicted values. FTR was also set up to work only on a recent window of data, to accommodate changes in flight condition. A system of confidence measures was developed to identify quality-parameter estimates that a learning neural network could use. This system judged the estimates primarily on the basis of their estimated variances and of the level of aircraft response. The resulting FTR system was implemented in the Simulink software system and auto-coded in the C programming language for use on the Airborne Research Test System (ARTS II) computer installed in the F-15 airplane. The Simulink model was also used in a control room that utilizes the Ring Buffered Network Bus hardware and software, making it possible to evaluate test points during flights. In-flight parameter estimation was done for piloted and automated maneuvers, primarily at three test conditions. Figure 2 shows results for pitching moment due to symmetric stabilator actuations for a series of three pitch doublet maneuvers (in a doublet maneuver, a command to change attitude in a given direction by a given amount is followed immediately by a command to change attitude in the opposite direction by the same amount). A time window of 5 seconds was used. The portions of the curves shown in red are those that passed the confidence tests. The technique showed good convergence for most derivatives for both kinds of maneuvers - typically within a few seconds. The confidence tests were marginally successful, and it would be necessary to refine them for use in an IFCS.

Smith, Mark↗

Remote monitoring of Alpha Gamma hot cell facility by ARG-US RFID system - 15177

Argonne National Laboratory (Argonne) has developed a monitoring and tracking system for nuclear materials based on radio frequency identification (RFID) technology. The system, called ARG-US ('Watchful Guardian'), has been in fielding testing and applications at selected U.S. Department of Energy (DOE) sites since 2010. ARG-US utilizes battery-powered tags to remotely and continuously monitor the environmental parameters, e.g., radiation levels, of the tagged items such as containers of radioactive materials. To demonstrate that the system can monitor nuclear and radiological facilities as well, a compact system was installed in the Alpha Gamma Hot Cell Facility (AGHCF) at Argonne in 2013. AGHCF is a Hazard Category 2 non-reactor nuclear facility that is being decommissioned. It is also being used to support de-inventory of other facilities on the Argonne site. As such, large quantities of radioactive materials and wastes are being discharged from the hot cell, loaded into transport containers, and shipped away. The deployed ARG-US system monitors worker areas, material transfer areas, cell exhaust HEPA filters, and?on a rover/robot?in-cell locations of AGHCF. Thus far, the system is performing as designed and yielding results that can be corroborated by existing surveillance means. The in-cell unit is particularly valuable, as it yields information that would otherwise be hard to obtain. In time, the benefits of automated monitoring 24/7 by ARG-US should become apparent and may lead to a fuller system with more distributed tags in the hot cell areas until the facility is fully decommissioned. (authors)

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Robust System Separation Strategy Considering Online Wide-Area Coherency Identification and Uncertainties of Renewable Energy Sources

With the fast growth of renewable energy sources (RES), more and more uncertainties are involved and influencing the stable operation of power systems. Controlled islanding is the last measure to prevent power system blackouts, thus this paper aims to propose a novel model of system separation based on Online Coherency Identification and Adjustable Robust Optimization Programming (OCI-AROP) for minimizing load shedding considering the uncertainties of RES. First, Fuzzy C-Means (FCM) clustering method with F-statistics is utilized to identify the coherent generator groups with the frequency data measured by Phasor Measurement Units (PMUs). Then, the OCI-AROP model considering coherent group constraints, connectivity constraints and robustness constraints about RES are presented. Finally, the case studies on IEEE-39 bus system and WECC-179 bus system are employed to demonstrate the effectiveness of the proposed OCI-AROP model, and comparisons among the OCI-AROP model and the other models are also given to show its superiority.

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