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

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At least 1,693 records · Page 94

Real breakthrough in detection of radioactive sources by portal monitors with plastic detectors and New Advanced Source Identification Algorithm (ASIA-New)

Radiation Portal Monitors (RPM) with plastic detectors represent the main instruments used for primary border (customs) radiation control. RPM are widely used because they are simple, reliable, relatively inexpensive and have a high sensitivity. However, experience using the RPM in various countries has revealed the systems have some grave shortcomings. There is a dramatic decrease of the probability of detection of radioactive sources under high suppression of the natural gamma background (radiation control of heavy cargoes, containers and, especially, trains). NORM (Naturally Occurring Radioactive Material) existing in objects under control trigger the so-called 'nuisance alarms', requiring a secondary inspection for source verification. At a number of sites, the rate of such alarms is so high it significantly complicates the work of customs and border officers. This paper presents a brief description of new variant of algorithm ASIA-New (New Advanced Source Identification Algorithm), which was developed by the Rapiscan company. It also demonstrates results of different tests and the capability of a new system to overcome the shortcomings stated above. New electronics and ASIA-New enables RPM to detect radioactive sources under a high background suppression (tested at 15-30%) and to verify the detected NORM (KCl) and the artificial isotopes (Co- 57, Ba-133 and other). New variant of ASIA is based on physical principles, a phenomenological approach and analysis of some important parameter changes during the vehicle passage through the monitor control area. Thanks to this capability main advantage of new system is that this system can be easily installed into any RPM with plastic detectors. Taking into account that more than 4000 RPM has been installed worldwide their upgrading by ASIA-New may significantly increase probability of detection and verification of radioactive sources even masked by NORM. This algorithm was tested for 1,395 passages of different transports (cars, trucks and trailers) without radioactive sources. It also was tested for 4,015 passages of these transports with radioactive sources of different activity (Co-57, Ba-133, Cs-137, Co-60, Ra-226, Th-232) and these sources masked by NORM (K-40) as well. (authors)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Investigation of Multiple Data Streams for Gearbox Bearing Fault Prediction Through Machine-Learning Models

Operations and maintenance (O&M) cost of wind plant accounts up to 30% of total energy cost, which can be reduced through continuous monitoring and successfully detecting incipient wind turbine failures. To accomplish this, condition monitoring and predictive maintenance systems are being implemented in wind industry to support O&M decision making. A wide range of approaches for condition monitoring and fault prediction have been developed. These approaches generally use historical data of wind turbines collected by Supervisory Control and Data Acquisition (SCADA) system to identify patterns that lead to failure. These SCADA data show the overall condition of a wind turbine and can be leveraged to detect when the turbine's performance is degrading and to identify if a fault is developing. However, it becomes challenging to predict the failure of a specific wind turbine gearbox bearing, because the SCADA data are often not directly linked to the component. To bridge the gap, we have investigated features calculated from SCADA data using physics-based models and the gearbox design over the years. The damaged metric we used in the physics domain is frictional energy. Combining these physics domain variables with SCADA data as inputs to various machine learning models for gearbox bearing fault prediction, we have demonstrated the benefits of leveraging both physics and data domain models. It was an attempt to improve frictional-energy-based damage metric by adding data domain inputs, as we had learned that the frictional-energy-based damage metric alone is not sufficient to single out failed bearings from healthy. As condition monitoring data (either vibration or oil debris data) has become available at more and more wind plants, we would like to evaluate whether by adding the condition monitoring data can help further improve the performance of frictional-energy-based damage metric for gearbox bearing fault prediction. Both cases by modeling through various machine learning algorithms are discussed in this study along with some observations.

fault prediction↗

Development of a multiplexed bypass control system for aerospace batteries

A breadboard bypass control system was developed to control a battery comprised of 26 JPL-developed negative limited Ni-Cd cells. The system was designed to automatically remove cells from the circuit when their voltages exceeded a fixed limit on charge and fell below a fixed limit on discharge. Major components of the system consisted of a cell voltage monitor, a multiplexing circuit, and individual electromechanical relays for each cell. The system was found to function well in controlling the battery during a simulated 10-month MM-71 mission and a 2-month simulated low earth orbit cycling mission. A flight version of the bypass system was estimated to have a total parts count of 150 and total weight of 1.63 kg. When fully developed, the system shows promise for improving life and reliability of spacecraft batteries.

Frank, H. A.↗

The Chesapeake Lighthouse and Aircraft Measurements for Satellites (CLAMS) Experiment

NASA has developed an Earth Observing System (EOS) consisting of a series of satellites designed to study global change from space. The EOS flagship is the EOS TERRA satellite, launched in December 1999, equipped with five unique sensors to monitor and study the Earth s heat budget and many of the key controlling variables governing the Earth's climate system. CLAMS, the Chesapeake Lighthouse and Aircraft Measurements for Satellites field campaign was conducted from NASA Wallops Flight Facility and successfully executed over the middle Atlantic eastern seaboard from July 10 August 2, 2001. CLAMS is primarily a shortwave closure experiment designed to validate and improve EOS TERRA satellite data products being derived from three sensors: CERES (Clouds and Earth's Radiant Energy System), MISR (Multi-angle Imaging Spectro-Radiometer) and MODIS (MODerate Resolution Imaging Spectroradiometer). CLAMS is jointly sponsored by the CERES, MISR and MODIS instrument teams and the NASA GEWEX Global Aerosol Climatology Project (GACP). CLAMS primary objectives are to validate satellite-based retrievals of aerosol properties and vertical profiles of radiative flux, temperature and water vapor. Central to CLAMS measurement strategy is the Chesapeake Lighthouse, a stable sea platform located in the Atlantic Ocean, 13 miles east of Virginia Beach near the mouth of the Chesapeake Bay and the site of an ongoing CERES Ocean Validation Experiment (COVE). Six research aircraft were deployed to make detailed measurements of the atmosphere and ocean surface in the vicinity of COVE, over the surrounding ocean, over nearby NOAA buoys and over a few land sites. The measurements are used to validate and provide ground truth for simultaneous products being derived from TERRA data, a key step toward an improved understanding and ability to predict changes in the Earth's climate. One of the two CERES instruments on-board TERRA was programmed for Rotating Azimuth Plane Scans (RAPS) during CLAMS, increasing the CERES coverage over COVE by a factor of 10. Nine coordinated aircraft missions and numerous additional sorties were flown under a variety of atmospheric conditions and aerosol loadings. On one golden day, July 17, all six aircraft flew coordinated patterns, vertically stacked between 100 ft and 65,000 ft over the COVE site as the TERRA satellite orbited overhead. A summary of CLAMS measurement campaign and a description of the platforms and measurements is given.

Smith, William L., Jr.↗

Hydronic Heating Retrofits for Low-Rise Multifamily Buildings: Boiler Control Replacement and Monitoring

The ARIES Collaborative, a U.S. Department of Energy Building America research team, partnered with NeighborWorks America affiliate Homeowners' Rehab Inc. of Cambridge, Massachusetts, to implement and study improvements to the central hydronic heating system in one of the nonprofit's housing developments. The heating control systems in the three-building, 42-unit Columbia Cambridge Alliance for Spanish Tenants housing development were upgraded.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Hydronic Heating Retrofits for Low-Rise Multifamily Buildings: Boiler Control Replacement and Monitoring

The ARIES Collaborative, a U.S. Department of Energy Building America research team, partnered with NeighborWorks America affiliate Homeowners' Rehab Inc. of Cambridge, Massachusetts, to implement and study improvements to the central hydronic heating system in one of the nonprofit's housing developments. The heating control systems in the three-building, 42-unit Columbia Cambridge Alliance for Spanish Tenants housing development were upgraded.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Elucidating Microbial Adaptation Dynamics via Autonomous Exposure and Sampling

The adaptation of micro-organisms to their environments is a complex process of interaction between the pressures of the environment and of competition. Reducing this multifactorial process to environmental exposure in the laboratory is a common tool for elucidating individual mechanisms of evolution, such as mutation rates. Although such studies inform fundamental questions about the way adaptation and even speciation occur, they are often limited by labor-intensive manual techniques. Current methods for controlled study of microbial adaptation limit the length of time, the depth of collected data, and the breadth of applied environmental conditions. Small idiosyncrasies in manual techniques can have large effects on outcomes; for example, there are significant variations in induced radiation resistances following similar repeated exposure protocols. We describe here a project under development to allow rapid cycling of multiple types of microbial environmental exposure. The system allows continuous autonomous monitoring and data collection of both single species and sampled communities, independently and concurrently providing multiple types of controlled environmental pressure (temperature, radiation, chemical presence or absence, and so on) to a microbial community in dynamic response to the ecosystem's current status. When combined with DNA sequencing and extraction, such a controlled environment can cast light on microbial functional development, population dynamics, inter- and intra-species competition, and microbe-environment interaction. The project's goal is to allow rapid, repeatable iteration of studies of both natural and artificial microbial adaptation. As an example, the same system can be used both to increase the pH of a wet soil aliquot over time while periodically sampling it for genetic activity analysis, or to repeatedly expose a culture of bacteria to the presence of a toxic metal, automatically adjusting the level of toxicity based on the number or growth rate of surviving cells. We are on our second prototype iteration, with demonstrated functions of microbial growth monitoring and dynamic exposure to UV-C radiation and temperature. We plan to add functionality for general chemical presence or absence by Nov. 2013. By making the project low-cost and open-source, we hope to encourage others to use it as a basis for future development of a common microbial environmental adaptation testbed.

Microbiology↗

Low-cost wireless voltage & current grid monitoring

This report describes the development and demonstration of a novel low-cost wireless power distribution line monitoring system. This system measures voltage, current, and relative phase on power lines of up to 35 kV-class. The line units operate without any batteries, and without harvesting energy from the power line. Thus, data on grid condition is provided even in outage conditions, when line current is zero. This enhances worker safety by detecting the presence of voltage and current that may appear from stray sources on nominally isolated lines. Availability of low-cost power line monitoring systems will enable widespread monitoring of the distribution grid. Real-time data on local grid operating conditions will enable grid operators to optimize grid operation, implement grid automation, and understand the impact of solar and other distributed sources on grid stability. The latter will enable utilities to implement eneygy storage and control systems to enable greater penetration of solar into the grid.

14 SOLAR ENERGY↗

Human Factors in Automated and Robotic Space Systems: Proceedings of a symposium. Part 2

Human factors research likely to produce results applicable to the development of a NASA space station is discussed. The particular sessions covered in Part 2 include: (1) computer aided monitoring and decision making; (2) telepresence and supervisory control; (3) social factors in productivity and performance; and (4) the human role in space systems. Papers from each subject area are reproduced and the discussions from each area are summarized.

Source record↗

Development and Demonstration of a Prototype Molten Salt Sampling System

Molten salt reactors (MSRs) offer potential operability and safety advantages when compared to commercial light water reactors (LWRs). However, operating experience with MSRs is sparse in comparison to what exists for LWRs. Further, the chemical and isotopic composition of the fuel and/or coolant salt is dynamic and difficult to characterize continuously, posing potential safety, operability, and safeguards unknowns that need to be addressed. A molten salt sampling system (MSSS) is regarded as a necessary subsystem within first generation MSRs used to obtain samples of salt for chemical and isotopic analysis in support of the need to monitor and control salt composition during operation. The MSSS is being developed using the Safety-in-Design (SiD) methodology, which incorporates incremental integration of safety analysis into the design process. The MSSS conceptual design emerging from the application of the early stages of the SiD methodology consists of a sample collection system and its housing, a freeze port, and inert gas control and delivery systems. This article describes the prototypes developed to test the functions of these MSSS subsystems, presents the results of testing in both dry and molten salt environments (including reliability data collection performed in accordance with the principles of SiD and the development of a semiquantitative fault tree model), and summarizes the opportunities for future design and testing enhancements based on the results of prototype testing.

molten salt reactor↗

MODIS information, data and control system (MIDACS) operations concepts

The MODIS Information, Data, and Control System (MIDACS) Operations Concepts Document provides a basis for the mutual understanding between the users and the designers of the MIDACS, including the requirements, operating environment, external interfaces, and development plan. In defining the concepts and scope of the system, how the MIDACS will operate as an element of the Earth Observing System (EOS) within the EosDIS environment is described. This version follows an earlier release of a preliminary draft version. The individual operations concepts for planning and scheduling, control and monitoring, data acquisition and processing, calibration and validation, data archive and distribution, and user access do not yet fully represent the requirements of the data system needed to achieve the scientific objectives of the MODIS instruments and science teams. The teams are not yet formed; however, it is possible to develop the operations concepts based on the present concept of EosDIS, the level 1 and level 2 Functional Requirements Documents, and through interviews and meetings with key members of the scientific community. The operations concepts were exercised through the application of representative scenarios.

Han, D.↗

Pulse control of single degree-of-freedom system

The possibility of using active control for structural and mechanical systems is examined. Open loop adaptive control of structural systems subjected to deterministic and stochastic excitations is considered by means of an algorithm for a single-degree-of-freedom oscillator. The algorithm is heuristic and requires continuous monitoring of the state variables, with a pulse control applied when some prespecified level of control is exceeded. The control algorithm is based on the principle that the gradual rhythmic increase of the structural response can be eliminated by applying a pulse of suitable magnitude in the proper direction, thereby avoiding the application of large forces over sustained periods of time. The optimum pulse magnitude is determined as the minimum rms response of the system. Application to linear and nonlinear systems, as well as in chatter suppression, are outlined.

Udwadia, F. E.↗

Gaussian process for calibration and control of GlueX Central Drift Chamber

We have developed and implemented a machine learning based system to calibrate and control the GlueX Central Drift Chamber at Jefferson Lab, VA, in near real-time. The system monitors environmental and experimental conditions during data taking and uses those as inputs to a Gaussian process (GP) with learned prior. The GP predicts calibration constants in order to recommend a high voltage (HV) setting for the detector that maintains consistent detector performance (gain and resolution) throughout data taking. This approach is in stark contrast to traditional detector operations in which the detector operates at fixed HV and its calibration parameters vary quite considerably with time. Additionally, the ML based system utilizes uncertainty quantification to correct the recommended control parameters when appropriate. We will present results from the ML system autonomously during the Charged Pion Polarizability (CPP) experiment conducted in Hall D at Jefferson Lab.

McSpadden, Helen↗

Gaussian process for calibration and control of GlueX Central Drift Chamber

We have developed and implemented a machine learning based system to calibrate and control the GlueX Central Drift Chamber at Jefferson Lab, VA, in near real-time. The system monitors environmental and experimental conditions during data taking and uses those as inputs to a Gaussian process (GP) with learned prior. The GP predicts calibration constants in order to recommend a high voltage (HV) setting for the detector that maintains consistent detector performance (gain and resolution) throughout data taking. This approach is in stark contrast to traditional detector operations in which the detector operates at fixed HV and its calibration parameters vary quite considerably with time. Additionally, the ML based system utilizes uncertainty quantification to correct the recommended control parameters when appropriate. We will present results from the ML system autonomously during the Charged Pion Polarizability (CPP) experiment conducted in Hall D at Jefferson Lab.

McSpadden, Helen↗

Assessment of Some IASMS-relevant Data Sources for Aviation Safety

An In-time Aviation Safety Management System (IASMS) [1,2] is a set of services, functions, and capabilities (SFCs) necessary for monitoring known hazards and emergent risks, assessing safety data for anomalies, precursors, and trends, mitigating hazards that reach safety thresholds, and assuring efficacy of controls in mitigating hazards. An IASMS will continually monitor the NAS to collect data on the status of aircraft, air traffic management systems, weather, and airports. Within the NASA Aeronautics Research Mission Directorate (ARMD) System-Wide Safety (SWS) project’s technical challenge called In-time Aviation Safety Management Systems (IASMS) for Commercial Aviation Operations, which we often refer to as Technical Challenge 6 (TC-6), we have performed an assessment of several aviation data sources we have found that are relevant to assessing the safety of the National Airspace System (NAS) in the context of an IASMS. This assessment includes understanding the nature of the data themselves and using some data analytics tools on these data to show how they can be used to identify potential safety issues. We also describe how the data and analytics are part of a system that can allow for other data and analytics to be performed and for the results to be visualized for use by appropriate operators to identify potential safety issues and develop mitigations. This report is a step toward the ultimate goal of TC-6, which is to develop a prototype IASMS system that demonstrates the potential of an IASMS and inspire operators to build analogous systems to make the best possible use of the significant investments that they make in collecting, storing, and managingdata related to their operations.

aviation safety↗

Tool coupling for the design and operation of building energy and control systems based on the Functional Mock-up Interface standard

This paper describes software tools developed at the Lawrence Berkeley National Laboratory (LBNL) that can be coupled through the Functional Mock-up Interface standard in support of the design and operation of building energy and control systems. These tools have been developed to address the gaps and limitations encountered in legacy simulation tools. These tools were originally designed for the analysis of individual domains of buildings, and have been difficult to integrate with other tools for runtime data exchange. The coupling has been realized by use of the Functional Mock-up Interface for co-simulation, which standardizes an application programming interface for simulator interoperability that has been adopted in a variety of industrial domains. As a variety of coupling scenarios are possible, this paper provides users with guidance on what coupling may be best suited for their application. Furthermore, the paper illustrates how tools can be integrated into a building management system to support the operation of buildings. These tools may be a design model that is used for real-time performance monitoring, a fault detection and diagnostics algorithm, or a control sequence, each of which may be exported as a Functional Mock-up Unit and made available in a building management system as an input/output block. We anticipate that this capability can contribute to bridging the observed performance gap between design and operational energy use of buildings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Development of a tether deployment monitoring system

The feasibility of monitoring the position of a tether during orbital deployment is discussed. Attention is given to the techniques for attaching reflectors to the tether at periodic intervals during the deployment process, which could then be tracked visually or with a radar unit that is pointed towards the targets by the control system. Consideration is also given to a method for tether attitude and tension detection, and a launching device to attach small instrumentation platforms onto the tether during deployment. The configuration of a tether deployment monitoring system (TEDEMS) and the equipment developed to perform the above tasks are described, along with an analysis of requirements for the construction of a family of space-borne TEDEMS suitable for use on the Space Shuttle, Expendable Launch Vehicles, or the Space Station. The potential uses of the TEDEMS for launching small tether-borne experimental packages are discussed. Design and block diagrams are included.

Ibanez, P.↗

Closing the Certification Gaps in Adaptive Flight Control Software

Over the last five decades, extensive research has been performed to design and develop adaptive control systems for aerospace systems and other applications where the capability to change controller behavior at different operating conditions is highly desirable. Although adaptive flight control has been partially implemented through the use of gain-scheduled control, truly adaptive control systems using learning algorithms and on-line system identification methods have not seen commercial deployment. The reason is that the certification process for adaptive flight control software for use in national air space has not yet been decided. The purpose of this paper is to examine the gaps between the state-of-the-art methodologies used to certify conventional (i.e., non-adaptive) flight control system software and what will likely to be needed to satisfy FAA airworthiness requirements. These gaps include the lack of a certification plan or process guide, the need to develop verification and validation tools and methodologies to analyze adaptive controller stability and convergence, as well as the development of metrics to evaluate adaptive controller performance at off-nominal flight conditions. This paper presents the major certification gap areas, a description of the current state of the verification methodologies, and what further research efforts will likely be needed to close the gaps remaining in current certification practices. It is envisioned that closing the gap will require certain advances in simulation methods, comprehensive methods to determine learning algorithm stability and convergence rates, the development of performance metrics for adaptive controllers, the application of formal software assurance methods, the application of on-line software monitoring tools for adaptive controller health assessment, and the development of a certification case for adaptive system safety of flight.

Jacklin, Stephen A.↗