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At least 1,207 records · Page 67

Removing sulphur oxides from a fluid stream

A process for removing sulphur oxides from a fluid stream, such as flue gas, comprising: providing a non-aqueous absorption liquid containing at least one hydrophobic amine, the liquid being incompletely miscible with water; treating the fluid stream in an absorption zone with the non-aqueous absorption liquid to transfer at least part of the sulphur oxides into the non-aqueous absorption liquid and to form a sulphur oxide-hydrophobic amine-complex; causing the non-aqueous absorption liquid to be in liquid-liquid contact with an aqueous liquid whereby at least part of the sulphur oxide-hydrophobic amine-complex is hydrolyzed to release the hydrophobic amine and sulphurous hydrolysis products, and at least part of the sulphurous hydrolysis products is transferred into the aqueous liquid; separating the aqueous liquid from the non-aqueous absorption liquid. The process mitigates absorbent degradation problems caused by sulphur dioxide and oxygen in flue gas.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

System and method for measuring particles in a sample stream of a flow cytometer using low-power laser source

A system and method for analyzing a particle in a sample stream of a flow cytometer or the like. The system has a light source, such as a laser pointer module, for generating a low powered light beam and a fluidics apparatus which is configured to transport particles in the sample stream at substantially low velocity through the light beam for interrogation. Detectors, such as photomultiplier tubes, are configured to detect optical signals generated in response to the light beam impinging the particles. Signal conditioning circuitry is connected to each of the detectors to condition each detector output into electronic signals for processing and is designed to have a limited frequency response to filter high frequency noise from the detector output signals.

47 OTHER INSTRUMENTATION↗

Modeling In-stream Tidal Energy Extraction and Its Potential Environmental Impacts

In recent years, there has been growing interest in harnessing in-stream tidal energy in response to concerns of increasing energy demand and to mitigate climate change impacts. While many studies have been conducted to assess and map tidal energy resources, efforts for quantifying the associated potential environmental impacts have been limited. This paper presents the development of a tidal turbine module within a three-dimensional unstructured-grid coastal ocean model and its application for assessing the potential environmental impacts associated with tidal energy extraction. The model is used to investigate in-stream tidal energy extraction and associated impacts on estuarine hydrodynamic and biological processes in a tidally dominant estuary. A series of numerical experiments with varying numbers and configurations of turbines installed in an idealized estuary were carried out to assess the changes in the hydrodynamics and biological processes due to tidal energy extraction. Model results indicated that a large number of turbines are required to extract the maximum tidal energy and cause significant reduction of the volume flux. Preliminary model results also indicate that extraction of tidal energy increases vertical mixing and decreases flushing rate in a stratified estuary. The tidal turbine model was applied to simulate tidal energy extraction in Puget Sound, a large fjord-like estuary in the Pacific Northwest coast.

Yang, Zhaoqing↗

Frequent Subgraph Discovery in Large Attributed Streaming Graphs

The problem of finding frequent subgraphs in large dynamic graphs has so far only consid- ered a dynamic graph as being represented by a series of static snapshots taken at various points in time. This representation of a dynamic graph does not lend itself well to real time processing of real world graphs like social networks or internet traffic which consist of a stream of nodes and edges. In this paper we propose an algorithm that discovers the frequent subgraphs present in a graph represented by a stream of labeled nodes and edges. Our algorithm is efficient and consists of tunable parameters that can be tuned by the user to get interesting patterns from various kinds of graph data. In our model updates to the graph arrive in the form of batches which contain new nodes and edges. Our algorithm con- tinuously reports the frequent subgraphs that are estimated to be found in the entire graph as each batch arrives. We evaluate our system using 5 large dynamic graph datasets: the Hetrec 2011 challenge data, Twitter, DBLP and two synthetic. We evaluate our approach against two popular large graph miners, i.e., SUBDUE and GERM. Our experimental re- sults show that we can find the same frequent subgraphs as a non-incremental approach applied to snapshot graphs, and in less time.

Dynamic graph, Frequent subgraph mining, pattern d↗

Selective catalytic reduction system and process for control of NO.sub.x emissions in a sulfur-containing gas stream

An exhaust gas treatment process, apparatus, and system for reducing the concentration of NOx, CO and hydrocarbons in a gas stream, such as an exhaust stream (29), via selective catalytic reduction with ammonia is provided. The process, apparatus and system include a catalytic bed (32) having a reducing only catalyst portion (34) and a downstream reducing-plus-oxidizing portion (36). Each portion (34, 36) includes an amount of tungsten. The reducing-plus-oxidizing catalyst portion (36) advantageously includes a greater amount of tungsten than the reducing catalyst portion (36) to markedly limit ammonia salt formation.

54 ENVIRONMENTAL SCIENCES↗

Oxygen transport membrane based advanced power cycle with low pressure synthesis gas slip stream

A method and system for generating electrical power in which a high pressure synthesis gas stream generated in a gasifier is partially oxidized in an oxygen transport membrane based reactor, expanded and thereafter, is combusted in an oxygen transport membrane based boiler. A low pressure synthesis gas slip stream is split off downstream of the expanders and used as the source of fuel in the oxygen transport membrane based partial oxidation reactors to allow the oxygen transport membrane to operate at low fuel pressures with high fuel utilization. The combustion within the boiler generates heat to raise steam to in turn generate electricity by a generator coupled to a steam turbine. The resultant flue gas can be purified to produce a carbon dioxide product.

42 ENGINEERING↗

System and method for measuring particles in a sample stream of a flow cytometer using low-power laser source

A system and method for analyzing a particle in a sample stream of a flow cytometer or the like. The system has a light source, such as a laser pointer module, for generating a low powered light beam and a fluidics apparatus which is configured to transport particles in the sample stream at substantially low velocity through the light beam for interrogation. Detectors, such as photomultiplier tubes, are configured to detect optical signals generated in response to the light beam impinging the particles. Signal conditioning circuitry is connected to each of the detectors to condition each detector output into electronic signals for processing and is designed to have a limited frequency response to filter high frequency noise from the detector output signals.

Graves, Steven W.↗

Selecting a Classification Ensemble and Detecting Process Drift in an Evolving Data Stream

We characterize the commercial behavior of a group of companies in a common line of business using a small ensemble of classifiers on a stream of records containing commercial activity information. This approach is able to effectively find a subset of classifiers that can be used to predict company labels with reasonable accuracy. Performance of the ensemble, its error rate under stable conditions, can be characterized using an exponentially weighted moving average (EWMA) statistic. The behavior of the EWMA statistic can be used to monitor a record stream from the commercial network and determine when significant changes have occurred. Results indicate that larger classification ensembles may not necessarily be optimal, pointing to the need to search the combinatorial classifier space in a systematic way. Results also show that current and past performance of an ensemble can be used to detect when statistically significant changes in the activity of the network have occurred. The dataset used in this work contains tens of thousands of high level commercial activity records with continuous and categorical variables and hundreds of labels, making classification challenging.

Ensemble classifiers↗

Diagnostic system for measuring temperature, pressure, CO2 concentration and H2O concentration in a fluid stream

A diagnostic system for measuring temperature, pressure, CO.sub.2 concentration and H.sub.2O concentration in a fluid stream is described. The system may include one or more probes that sample the fluid stream spatially, temporally and over ranges of pressure and temperature. Laser light sources are directed down pitch optical cables, through a lens and to a mirror, where the light sources are reflected back, through the lens to catch optical cables. The light travels through the catch optical cables to detectors, which provide electrical signals to a processer. The processer utilizes the signals to calculate CO.sub.2 concentration based on the temperatures derived from H.sub.2O vapor concentration. A probe for sampling CO.sub.2 and H.sub.2O vapor concentrations is also disclosed. Various mechanical features interact together to ensure the pitch and catch optical cables are properly aligned with the lens during assembly and use.

47 OTHER INSTRUMENTATION↗

ON-LINE MONITORING FOR PROCESS CONTROL AND SAFEGUARDING OF RADIOCHEMICAL STREAMS AT SPENT FUEL REPROCESSING PLANTS

The International Atomic Energy Agency (IAEA) has established international safeguards standards for fissionable material at spent nuclear fuel reprocessing plants to ensure that significant quantities of weapons-grade nuclear material are not diverted from these facilities. Currently, methods to verify material control and accountancy (MC&A) at these facilities require time-consuming and resource-intensive destructive assay (DA). Leveraging new on-line non-destructive assay (NDA) techniques in conjunction with the traditional and highly precise DA methods may provide a more timely, cost-effective and resource-efficient means for MC&A verification at such facilities. Pacific Northwest National Laboratory (PNNL) is developing on-line NDA process monitoring technologies, including a spectroscopy-based monitoring system, to potentially reduce the time and resource burden associated with current techniques. The spectroscopic monitor continuously measures chemical compositions of the process streams including actinide metal ions (U, Pu, Np), selected fission products, and major non-radioactive flowsheet chemicals using UV-vis-near infrared and Raman spectroscopy. This paper provides an overview of the methods and reports our on-going efforts to develop and demonstrate the technologies. Our ability to identify material intentionally diverted from a liquid-liquid extraction contactor system was successfully tested using on-line process monitoring as a means to detect the amount of material diverted. A chemical diversion and detection of that diversion, from a solvent extraction scheme was demonstrated using a centrifugal contactor system operating a tributyl phosphate based extraction. A portion of the feed from a counter-current extraction system was diverted while a continuous extraction experiment was underway; the spectroscopic on-line process monitoring system was simultaneously measuring the feed, raffinate and organic products streams. The amount observed to be diverted by on-line spectroscopic process monitoring was in excellent agreement with values based from the known mass of sample directly diverted from system feed solution.

Np↗

Diagnostic system for measuring temperature, pressure, CO.sub.2 concentration and H.sub.2O concentration in a fluid stream

A diagnostic system for measuring temperature, pressure, CO.sub.2 concentration and H.sub.2O concentration in a fluid stream is described. The system may include one or more probes that sample the fluid stream spatially, temporally and over ranges of pressure and temperature. Laser light sources are directed down pitch optical cables, through a lens and to a mirror, where the light sources are reflected back, through the lens to catch optical cables. The light travels through the catch optical cables to detectors, which provide electrical signals to a processer. The processer utilizes the signals to calculate CO.sub.2 concentration based on the temperatures derived from H.sub.2O vapor concentration. A probe for sampling CO.sub.2 and H.sub.2O vapor concentrations is also disclosed. Various mechanical features interact together to ensure the pitch and catch optical cables are properly aligned with the lens during assembly and use.

42 ENGINEERING↗

Adaptive Framework for Classification and Novel Class Detection over Evolving Data Streams with Limited Labeled Data.

Most approaches to classifying evolving data streams either divide the stream of data into fixed-size chunks or use gradual forgetting to address the problems of infinite length and concept drift. Finding the fixed size of the chunks or choosing a forgetting rate without prior knowledge about time-scale of change is not a trivial task. As a result, these approaches suffer from a trade-off between performance and sensitivity. To address this problem, we present a framework which uses change detection techniques on the classifier performance to determine chunk boundaries dynamically. Though this framework exhibits good performance, it is heavily dependent on the availability of true labels of data instances. However, labeled data instances are scarce in realistic settings and not readily available. Therefore, we present a second framework which is unsupervised in nature, and exploits change detection on classifier confidence values to determine chunk boundaries dynamically. In this way, it avoids the use of labeled data while still addressing the problems of infinite length and concept drift. Moreover, both of our proposed frameworks address the concept evolution problem by detecting outliers having similar values for the attributes. We provide theoretical proof that our change detection method works better than other state-of-the-art approaches in this particular scenario. Results from experiments on various benchmark and synthetic data sets also show the efficiency of our proposed frameworks.

97 MATHEMATICS AND COMPUTING↗

Disruption of current filaments and isotropization of magnetic field in counter-streaming plasmas

We study the stability of current filaments produced by the Weibel, or current filamentation, instability in weakly magnetized counter-streaming plasmas. It is shown that a resonance exists between the current-carrying ions and a longitudinal drift-kink mode that strongly deforms and eventually breaks the current filaments. Analytical estimates of the wavelength, growth rate and saturation level of the resonant mode are derived and validated by three-dimensional particle-in-cell simulations. Furthermore, self-consistent simulations of counter-streaming plasmas indicate that this drift-kink mode is dominant in the slow down of the flows and in the isotropization of the magnetic field, playing an important role in the formation of collision less shocks.

Fiuza, Frederico↗

System for detecting objects in streaming 3D images formed from data acquired with a medium penetrating sensor

A detection system that detects subsurface objects within a medium and estimates various features of the objects is provided. The detection system receives a streaming sequence of image frames of the medium at various along-medium locations. An image frame contains voxel values (intensities) representing characteristics of the medium across the medium and in the depth (range) direction. The detection system depth-compensates the intensities for determining which voxels are part of an object using an unsupervised binary classifier. The detection system then connects object voxels into distinct objects and recursively estimates the features of those objects as the image frames stream based on the locations and intensities of the object voxels.

Paglieroni, David W.↗

GoldenEye: stream-based network packet inspection using GPUs

High-performance packet analysis systems have attracted great interest as tools to deal with security concerns in high-speed networks. Recently, researchers have utilized GPUs to improve packet processing performance. However, most existing work has been targeted at per-packet analysis level. Flow-centric operations have been challenging for GPUs because they require sequential operations and large buffers for flow reassembly. In this work, we present the GoldenEye GPU Packet Processing System (GoldenEye), a deep packet inspection (DPI) system that tracks out-of-order TCP packets and provides streambased signature matching. When a batch of packets arrives, GoldenEye sorts packets into flow-reassembled streams and normalizes retransmission through a GPU-implemented reordering module. For signatures that straddle batch boundaries, GoldenEye couples a small set of metadata with a functionallyequivalent minimal regular expression retrieval algorithm to connect the partial matches. Results show that GoldenEye can reassemble tens of millions of packets/sec and conduct stateful DPI operations on TCP streams at multi-ten Gbit/sec rates.

97 MATHEMATICS AND COMPUTING↗

A Software Defined Network Design for Analyzing Streaming Data in Transit

Year after year, network traffic keeps reaching newhighs as unprecedented volumes of data flow between an ever-increasing number of sources and destinations. As part of the Analysis on the Wire project, we aim to develop a network-centric approach for streaming data processing to facilitate scientific data analysis and reduce the overhead in sending big data to a data center. This work discusses our design for programmable network devices to augment network capabilities for streaming data processing, including efforts in progress at Brookhaven National Laboratory and the challenges faced to date.

97 MATHEMATICS AND COMPUTING↗

Deep Learning for Unsupervised Insider Threat Detection in Structured Cybersecurity Data Streams

Situational awareness data is a prototypical example of structured heterogeneous streaming data with asynchronous timing that can quickly scale beyond the cognitive power of a human analyst. We present deep learning methods that can train in real time from unlabeled streams and provide probabilistic anomaly scores. We compare our novel deep and recurrent neural network models to three baseline systems using threat detection recall on the CERT Insider Threat Dataset v6.2. In our experiments, our deep neural network and our recurrent neural network systems outperformed all baselines, and we found that using aggregated activity count features yielded the best performance. Our best model produces on average an anomaly score of 95.53 percentile for the day, suggesting it can facilitate a great reduction in analyst workload. Our models are also interpretable, in that they break down the anomaly score into individual features of user behavior, which could further aid analysts in reviewing potential cases of insider threat.

Tuor, Aaron R.↗

Implementation of Ion Exchange Processes on Industrial Waste Streams for CO 2 Mineralization

Economic development and population growth will lead to an increase in global energy consumption. Large coal-fired power plants (>500 MW) account for almost half of the total CO 2 emissions from fossil fuel combustion, and nearly 26% of the global fossil fuel and industry CO 2 emissions. Long-term management of the more than 36 Gt of CO 2 that is emitted globally per year is urgently needed. CO 2 mineralization is an attractive method of sequestering CO 2 because it captures CO 2 as an insoluble carbonate mineral, mimicking the natural process of rock weathering. Here, we present a pathway for accelerated CO 2 mineralization enabled by divalent cations sourced from liquid streams. In this work, we investigate a mineralization route that converts flue gas CO 2 to precipitated calcium carbonate (PCC) using waste aqueous streams as the calcium source. The proposed mineralization route integrates CO 2 utilization and waste liquid management at coal power plants. Maintaining alkalinity during carbonation is the primary challenge in this process. Instead of relying on the consumption of costly and unsustainable sources of alkalinity (e.g., sodium hydroxide), we used regenerable solids to increase the pH of water by ion exchange. The increase in alkalinity creates a more thermodynamically favorable environment for calcite precipitation. The capacities for ion exchange of various commercially available zeolites and ion exchange resins in CO 2 -saturated water were studied through batch equilibrium and column ion-exchange experiments. During ion exchange, H + in the water exchanges with Na + , Ca 2+ or K + in the zeolite or resin. Batch equilibrium isotherms for H + –Na + exchange were collected by first adding varying amounts of the ion exchange solid (0 – 1.0 kg per kg of water) to CO 2 -saturated water (pCO 2 = 1 atm, pH 4) to determine the maximum H + –Na + exchange achievable. Ion-exchange column studies were performed to determine breakthrough capacity of the system. In both systems, an increase in pH coupled with an increase in Na concentration was observed, demonstrating the feasibility of forward ion exchange. Zeolitic materials increased the alkalinity of the solution from pH 4 to around 10, whereas ion exchange resins containing weakly acidic functional groups (e.g., carboxylic acid) exhibited higher affinity for H + , increasing pH to 11.3 and surpassing the pH shift induced by the zeolitic materials. The extent of calcite precipitation was evaluated by mixing the alkaline CO 3 2- -rich water obtained after passing through the ion-exchange column and a CaCl 2 solution. Calcite yields are as expected from chemical thermodynamics. Calcium carbonate yields found experimentally were about 26 and 8 mmol per kg water for the weakly acidic ion exchange resin and zeolitic materials, respectively. The results from these studies indicate that ion exchange processes can be used as an alternative to the addition of stoichiometric inorganic bases (e.g., sodium hydroxide) to induce alkalinity for the consequent precipitation of CaCO 3 . Instead, weakly acidic ion exchange resins commonly used for water hardness removal were alternatively used to induce pH swings in the aqueous solutions. The high calcium carbonate yields obtained for the materials examined demonstrate the potential application of this process. In addition, the successful operation of the calcium carbonate production process at standard temperature and pressure conditions support its potential for industrial implementation.

Simonetti, Dante↗