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At least 289 records · Page 16

Multi-axis transient vibration testing of space objects: Test philosophy, test facility, and control strategy

IABG has been using various servohydraulic test facilities for many years for the reproduction of service loads and environmental loads on all kinds of test objects. For more than 15 years, a multi-axis vibration test facility has been under service, originally designed for earthquake simulation but being upgraded to the demands of space testing. First tests with the DFS/STM showed good reproduction accuracy and demonstrated the feasibility of transient vibration testing of space objects on a multi-axis hydraulic shaker. An approach to structural qualification is possible by using this test philosophy. It will be outlined and its obvious advantages over the state-of-the-art single-axis test will be demonstrated by example results. The new test technique has some special requirements to the test facility exceeding those of earthquake testing. Most important is the high reproduction accuracy demanded for a sophisticated control system. The state-of-the-art approach of analog closed-loop control circuits for each actuator combined with a static decoupling network and an off-line iterative waveform control is not able to meet all the demands. Therefore, the future over-all control system is implemented as hierarchical full digital closed-loop system on a highly parallel transputer network. The innermost layer is the digital actuator controller, the second one is the MDOF-control of the table movement. The outermost layer would be the off-line iterative waveform control, which is dedicated only to deal with the interaction of test table and test object or non-linear effects. The outline of the system will be presented.

Lachenmayr, Georg↗

Neural Generalized Predictive Control: A Newton-Raphson Implementation

An efficient implementation of Generalized Predictive Control using a multi-layer feedforward neural network as the plant's nonlinear model is presented. In using Newton-Raphson as the optimization algorithm, the number of iterations needed for convergence is significantly reduced from other techniques. The main cost of the Newton-Raphson algorithm is in the calculation of the Hessian, but even with this overhead the low iteration numbers make Newton-Raphson faster than other techniques and a viable algorithm for real-time control. This paper presents a detailed derivation of the Neural Generalized Predictive Control algorithm with Newton-Raphson as the minimization algorithm. Simulation results show convergence to a good solution within two iterations and timing data show that real-time control is possible. Comments about the algorithm's implementation are also included.

Soloway, Donald↗

Study and Simulation of Enhancements for TCP (Transmission Control Protocol) Performance Over Noisy, High-Latency Links

The designers of the TCP/IP protocol suite explicitly included support of satellites in their design goals. The goal of the Internet Project was to design a protocol which could be layered over different networking technologies to allow them to be concatenated into an internet. The results of this project included two protocols, IP and TCP. IP is the protocol used by all elements in the network and it defines the standard packet format for IP datagrams. TCP is the end-to-end transport protocol commonly used between end systems on the Internet to derive a reliable bi-directional byte-pipe service from the underlying unreliable IP datagram service. Satellite links are explicitly mentioned in Vint Cerf's 2-page article which appeared in 1980 in CCR [2] to introduce the specifications for IP and TCP. In the past fifteen years, TCP has been demonstrated to work over many differing networking technologies, including over paths including satellites links. So if satellite links were in the minds of the designers from the beginning, what is the problem? The problem is that the performance of TCP has in some cases been disappointing. A goal of the authors of the original specification of TCP was to specify only enough behavior to ensure interoperability. The specification left a number of important decisions, in particular how much data is to be sent when, to the implementor. This was deliberately' done. By leaving performance-related decisions to the implementor, this would allow the protocol TCP to be tuned and adapted to different networks and situations in the future without the need to revise the specification of the protocol, or break interoperability. Interoperability would continue while future implementations would be allowed flexibility to adapt to needs which could not be anticipated at the time of the original protocol design.

Shepard, Timothy J.↗

Microwell Arrays for Studying Many Individual Cells

"Laboratory-on-a-chip" devices that enable the simultaneous culturing and interrogation of many individual living cells have been invented. Each such device includes a silicon nitride-coated silicon chip containing an array of micromachined wells sized so that each well can contain one cell in contact or proximity with a patch clamp or other suitable single-cell-interrogating device. At the bottom of each well is a hole, typically 0.5 m wide, that connects the well with one of many channels in a microfluidic network formed in a layer of poly(dimethylsiloxane) on the underside of the chip. The microfluidic network makes it possible to address wells (and, thus, cells) individually to supply them with selected biochemicals. The microfluidic channels also provide electrical contact to the bottoms of the wells.

Folch, Albert↗

Fault Tolerance in ZigBee Wireless Sensor Networks

Wireless sensor networks (WSN) based on the IEEE 802.15.4 Personal Area Network standard are finding increasing use in the home automation and emerging smart energy markets. The network and application layers, based on the ZigBee 2007 PRO Standard, provide a convenient framework for component-based software that supports customer solutions from multiple vendors. This technology is supported by System-on-a-Chip solutions, resulting in extremely small and low-power nodes. The Wireless Connections in Space Project addresses the aerospace flight domain for both flight-critical and non-critical avionics. WSNs provide the inherent fault tolerance required for aerospace applications utilizing such technology. The team from Ames Research Center has developed techniques for assessing the fault tolerance of ZigBee WSNs challenged by radio frequency (RF) interference or WSN node failure.

Alena, Richard↗

Real-Time Adaptive Color Segmentation by Neural Networks

Artificial neural networks that would utilize the cascade error projection (CEP) algorithm have been proposed as means of autonomous, real-time, adaptive color segmentation of images that change with time. In the original intended application, such a neural network would be used to analyze digitized color video images of terrain on a remote planet as viewed from an uninhabited spacecraft approaching the planet. During descent toward the surface of the planet, information on the segmentation of the images into differently colored areas would be updated adaptively in real time to capture changes in contrast, brightness, and resolution, all in an effort to identify a safe and scientifically productive landing site and provide control feedback to steer the spacecraft toward that site. Potential terrestrial applications include monitoring images of crops to detect insect invasions and monitoring of buildings and other facilities to detect intruders. The CEP algorithm is reliable and is well suited to implementation in very-large-scale integrated (VLSI) circuitry. It was chosen over other neural-network learning algorithms because it is better suited to realtime learning: It provides a self-evolving neural-network structure, requires fewer iterations to converge and is more tolerant to low resolution (that is, fewer bits) in the quantization of neural-network synaptic weights. Consequently, a CEP neural network learns relatively quickly, and the circuitry needed to implement it is relatively simple. Like other neural networks, a CEP neural network includes an input layer, hidden units, and output units (see figure). As in other neural networks, a CEP network is presented with a succession of input training patterns, giving rise to a set of outputs that are compared with the desired outputs. Also as in other neural networks, the synaptic weights are updated iteratively in an effort to bring the outputs closer to target values. A distinctive feature of the CEP neural network and algorithm is that each update of synaptic weights takes place in conjunction with the addition of another hidden unit, which then remains in place as still other hidden units are added on subsequent iterations. For a given training pattern, the synaptic weight between (1) the inputs and the previously added hidden units and (2) the newly added hidden unit is updated by an amount proportional to the partial derivative of a quadratic error function with respect to the synaptic weight. The synaptic weight between the newly added hidden unit and each output unit is given by a more complex function that involves the errors between the outputs and their target values, the transfer functions (hyperbolic tangents) of the neural units, and the derivatives of the transfer functions.

Duong, Tuan A.↗

Synergistic Use of Nighttime Satellite Data, Electric Utility Infrastructure, and Ambient Population to Improve Power Outage Detections in Urban Areas

Natural and anthropogenic hazards are frequently responsible for disaster events, leading to damaged physical infrastructure, which can result in loss of electrical power for affected locations. Remotely-sensed, nighttime satellite imagery from the Suomi National Polar-orbiting Partnership (Suomi-NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB) can monitor power outages in disaster-affected areas through the identification of missing city lights. When combined with locally-relevant geospatial information, these observations can be used to estimate power outages, defined as geographic locations requiring manual intervention to restore power. In this study, we produced a power outage product based on Suomi-NPP VIIRS DNB observations to estimate power outages following Hurricane Sandy in 2012. This product, combined with known power outage data and ambient population estimates, was then used to predict power outages in a layered, feedforward neural network model. We believe this is the first attempt to synergistically combine such data sources to quantitatively estimate power outages. The VIIRS DNB power outage product was able to identify initial loss of light following Hurricane Sandy, as well as the gradual restoration of electrical power. The neural network model predicted power outages with reasonable spatial accuracy, achieving Pearson coefficients (r) between 0.48 and 0.58 across all folds. Our results show promise for producing a continental United States (CONUS)- or global-scale power outage monitoring network using satellite imagery and locally-relevant geospatial data.

da/night band↗

Neural network based prediction of no-wall β N limits due to ideal external kink instabilities

Multi-layer perceptron based neural networks (NNs) are trained to predict the Troyon no-wall beta limits due to the onset of low-n (n = 1 – 3, n is the toroidal mode number) ideal external kink instabilities in tokamak plasmas. It is revealed that a well-trained NN can predict the n = 1 no-wall beta limit within 10% relative error. The NN performance is somewhat worse for the n = 2 and 3 no-wall beta limits, but still a relative error within 20% is achievable. The trained NNs well reproduce the known dependences of the no-wall beta limits on the plasma pressure (pressure peaking factor) and current (plasma internal inductance) profiles. Other scalings are further easily established with NNs, for parametric dependences such as on the aspect ratio, the elongation and triangularity of the plasma boundary shape. These NN-based Troyon beta limit predictors can be incorporated into integrated modeling platforms, or directly implemented as a real time stability estimator for the purpose of disruption avoidance or mitigation during experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Photonics and other approaches to high speed communications

Our research group of 4 faculty and about 10-15 graduate students was actively involved (as a group) in the development of computer communication networks for the last five years. Many of its individuals have been involved in related research for a much longer period. The overall research goal is to extend network performance to higher data rates, to improve protocol performance at most ISO layers and to improve network operational performance. We briefly state our research goals, then discuss the research accomplishments and direct your attention to attached and/or published papers which cover the following topics: scalable parallel communications; high performance interconnection between high data rate networks; and a simple, effective media access protocol system for integrated, high data rate networks.

Maly, Kurt↗

Investigating the hydrolysis of cryogenically layered molybdenum hexafluoride through a disordered hydrogen-bonded network

Molybdenum hexafluoride (MoF6) is used as a non-radioactive substitute for uranium to study the hydrolysis of metal hexafluorides. Molybdenum hexafluoride gas and water vapor, from the air, were sequentially layered onto a diamond substrate kept at liquid nitrogen temperature using a custom designed cryogenic cell with a copper cold finger. Reaction progress was monitored by transmission Fourier Transform Infrared Spectroscopy (FTIR) through the layers and diamond substrate over several hours while allowing the substrate to warm. Changes in the modes in the 500–1000 cm -1 region are tracked as the reaction progresses in order to identify intermediate species. Strong absorption features are also observed in the 1000–3000 cm -1 range, suggesting the presence of ionic dissociation intermediates trapped in a disordered H-bonded network of cryogenic hydrofluoric acid. Here, a possible reaction pathway is proposed and the final hydrolysis product is characterized by FTIR, UV-vis, and scanning electron microscopy/energy dispersive X-ray spectroscopy (SEM/EDS).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Adaptive neural network management system

A method and computer system for managing a neural network. Data is sent into an input layer in a portion of layers of nodes in the neural network. The data moves on an encode path through the portion such that an output layer in the portion outputs encoded data. The encoded data is sent into the output layer on a decode path through the portion back to the input layer to obtain a reconstruction of the data by the input layer. A determination is made as to whether an undesired amount of error has occurred in the output layer based on the data sent into the input layer and the reconstruction of the data. A number of new nodes is added to the output layer when a determination is present that the undesired amount of the error occurred, enabling reducing the error using the number of the new nodes.

Draelos, Timothy J.↗

Criticality analysis of nuclear binding energy neural networks

Machine learning methods, in particular deep learning methods such as artificial neural networks (ANNs) with many layers, have become widespread and useful tools in nuclear physics. However, these ANNs are typically treated as ‘black boxes’, with their architecture (width, depth, and weight/bias initialization) and the training algorithm and parameters chosen empirically by optimizing learning based on limited exploration. We test a non-empirical approach to understanding and optimizing nuclear physics ANNs by adapting a criticality analysis based on renormalization group flows in terms of the hyperparameters for weight/bias initialization, training rates, and the ratio of depth to width. This treatment utilizes the statistical properties of neural network initialization to find a generating functional for network outputs at any layer, allowing for a path integral formulation of the ANN outputs as a Euclidean statistical field theory. We use a prototypical example to test the applicability of this approach: a simple ANN for nuclear binding energies. We find that with training using a stochastic gradient descent optimizer, the predicted criticality behavior is realized, and optimal performance is found with critical tuning. However, the use of an adaptive learning algorithm leads to somewhat superior results without concern for tuning and thus obscures the analysis. Nevertheless, the criticality analysis offers a way to look within the black box of ANNs, which is a first step towards potential improvements in network performance beyond using adaptive optimizers.

artificial neural network↗

Fairness-Aware Distributed Energy Coordination for Voltage Regulation in Power Distribution Systems

The accelerating deployment of solar photovoltaics into low-voltage distribution networks can cause reverse power flow and overvoltage problems. However, if coordinated properly, the real and reactive power flexibility of these resources enables distribution operators to manage their networks more efficiently. Existing literature is rich in droop-based control (Volt-Watt and Volt-VAr) and optimization-based distributed energy coordination for four-quadrant control of photovoltaics to prevent overvoltage issues. While optimal coordination can effectively mitigate overvoltage, it tends to treat resources at sensitive parts of the grid unfairly. Here, to address this concern, we propose a distributed optimal power flow formulation that incorporates fairness in curtailing photovoltaic generation and utilizes the reactive power capability of smart inverters. The proposed distributed formulation allows for scalable resource aggregation that can be leveraged to achieve fairness within a certain segment of the grid and/or fairness across the entire network. Fair curtailment of photovoltaic systems is demonstrated with aggregation at each of two layers in a distribution network: 1) area-level fairness and 2) feeder-level fairness. To explore the trade-off between fairness and optimal utilization, the fairness-aware control actions are compared against the performance of a centralized controller that aims to maximize the aggregate PV generation without incorporating fairness. Simulation results show that introducing area-level fairness increased curtailment by 0.0101 percentage points and feeder-level fairness increased curtailment by 0.0458 percentage points compared to a fairness-agnostic control.

Poudel, Shiva↗

Reliable Transport over SpaceWire for James Webb Space Telescope (JWST) Focal Plane Electronics (FPE) Network

NASA's James Webb Space Telescope (JWST) faces difficult technical and budgetary challenges to overcome before it is scheduled launch in 2010. The Integrated Science Instrument Module (ISIM), shares these challenges. The major challenge addressed in this paper is the data network used to collect, process, compresses and store Infrared data. A total of 114 Mbps of raw information must be collected from 19 sources and delivered to the two redundant data processing units across a twenty meter deployed thermally restricted interface. Further data must be transferred to the solid-state recorder and the spacecraft. The JWST detectors are kept at cryogenic temperatures to obtain the sensitivity necessary to measure faint energy sources. The Focal Plane Electronics (FPE) that sample the detector, generate packets from the samples, and transmit these packets to the processing electronics must dissipate little power in order to help keep the detectors at these cold temperatures. Separating the low powered front-end electronics from the higher-powered processing electronics, and using a simple high-speed protocol to transmit the detector data minimize the power dissipation near the detectors. Low Voltage Differential Signaling (LVDS) drivers were considered an obvious choice for physical layer because of their high speed and low power. The mechanical restriction on the number cables across the thermal interface force the Image packets to be concentrated upon two high-speed links. These links connect the many image packet sources, Focal Plane Electronics (FPE), located near the cryogenic detectors to the processing electronics on the spacecraft structure. From 12 to 10,000 seconds of raw data are processed to make up an image, various algorithms integrate the pixel data Loss of commands to configure the detectors as well as the loss of science data itself may cause inefficiency in the use of the telescope that are unacceptable given the high cost of the observatory. This combination of requirements necessitates a redundant, fault tolerant, high- speed, low mass, low power network with a low Bit error Rate(1E-9- 1E-12). The ISIM systems team performed many studies of the various network architectures that meeting these requirements. The architecture selected uses the Spacewire protocol, with the addition of a new transport and network layer added to implement end-to-end reliable transport. The network and reliable transport mechanism must be implemented in hardware because of the high average information rate and the restriction on the ability of the detectors to buffer data due to power and size restrictions. This network and transport mechanism was designed to be compatible with existing Spacewire links and routers so that existing equipment and designs may be leveraged upon. The transport layer specification is being coordinated with European Space Agency (ESA), Spacewire Working Group and the Consultative Committee for Space Data System (CCSDS) PlK Standard Onboard Interface (SOIF) panel, with the intent of developing a standard for reliable transport for Spacewire. Changes to the protocol presented are likely since negotiations are ongoing with these groups. A block of RTL VHDL that implements a multi-port Spacewire router with an external user interface will be developed and integrated with an existing Spacewire Link design. The external user interface will be the local interface that sources and sinks packets onto and off of the network (Figure 3). The external user interface implements the network and transport layer and handles acknowledgements and re-tries of packets for reliable transport over the network. Because the design is written in RTL, it may be ported to any technology but will initially be targeted to the new Actel Accelerator series (AX) part. Each link will run at 160 Mbps and the power will be about 0.165 Watt per link worst case in the Actel AX.

Rakow, Glenn↗

Smart Pixels: towards on-sensor inference of charged particle track parameters and uncertainties

The combinatorics of track seeding has long been a computational bottleneck for triggering and offline computing in High Energy Physics (HEP), and remains so for the HL-LHC. Next-generation pixel sensors will be sufficiently fine-grained to determine angular information of the charged particle passing through from pixel-cluster properties. This detector technology immediately improves the situation for offline tracking, but any major improvements in physics reach are unrealized since they are dominated by lowest-level hardware trigger acceptance. We will demonstrate track angle and hit position prediction, including errors, using a mixture density network within a single layer of silicon as well as the progress towards and status of implementing the neural network in hardware on both FPGAs and ASICs.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Smart Pixels: towards on-sensor inference of charged particle track parameters and uncertainties

The combinatorics of track seeding has long been a computational bottleneck for triggering and offline computing in High Energy Physics (HEP), and remains so for the HL-LHC. Next-generation pixel sensors will be sufficiently fine-grained to determine angular information of the charged particle passing through from pixel-cluster properties. This detector technology immediately improves the situation for offline tracking, but any major improvements in physics reach are unrealized since they are dominated by lowest-level hardware trigger acceptance. We will demonstrate track angle and hit position prediction, including errors, using a mixture density network within a single layer of silicon as well as the progress towards and status of implementing the neural network in hardware on both FPGAs and ASICs.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Smartpixels: Towards on-sensor inference of charged particle track parameters and uncertainties

The combinatorics of track seeding has long been a computational bottleneck for triggering and offline computing in High Energy Physics (HEP), and remains so for the HL-LHC. Next-generation pixel sensors will be sufficiently fine-grained to determine angular information of the charged particle passing through from pixel-cluster properties. This detector technology immediately improves the situation for offline tracking, but any major improvements in physics reach are unrealized since they are dominated by lowest-level hardware trigger acceptance. We will demonstrate track angle and hit position prediction, including errors, using a mixture density network within a single layer of silicon as well as the progress towards and status of implementing the neural network in hardware on both FPGAs and ASICs.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Defect-Seeded Atomic Layer Deposition of Metal Oxides on the Basal Plane of 2D Layered Materials

Atomic layer deposition (ALD) on mechanically exfoliated 2D layered materials spontaneously produces network patterns of metal oxide nanoparticles in triangular and linear deposits on the basal surface. The network patterns formed under a range of ALD conditions and were independent of the orientation of the substrate in the ALD reactor. The patterns were produced on MoS 2 or HOPG when either tetrakis(dimethylamido)titanium or bis(ethylcyclopentadienyl)manganese were used as precursors, suggesting that the phenomenon is general for 2D materials. Transmission electron microscopy revealed the presence, prior to deposition, of dislocation networks along the basal plane of mechanically exfoliated 2D flakes, indicating that periodical basal plane defects related to disruptions in the van der Waals stacking of layers, such as perfect line dislocations and triangular extended stacking faults networks, introduce a surface reactivity landscape that leads to the emergence of patterned deposition.

36 MATERIALS SCIENCE↗