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At least 1,081 records · Page 60

Space station contamination considerations

The external induced environment generated by space station activity, or more specifically by gases, particles, and light background is discussed. These contaminant species must be controlled if sensitive systems, such as solar energy collectors or science experiments exposed to the external environment are to function properly. The requirements generally set limits on the level of gas species, matter deposited on surfaces and light background levels over various spectral regions. They also address environment monitoring and contamination controls during manufacturing. Limits on effluent release and system leakages are in turn derived from these requirements.

Leger, L.↗

Plug Load Management System Field Study

In 2018, NREL performed a demonstration of the IBIS InteliNetwork(TM) plug load management system, which includes: intelligent socket devices, which plug into existing electrical outlets and collect energy usage information; a gateway, which manages communication between the intelligent sockets and the PLM cloud service; and a PLM network, which is a cloud-based measurement and control network for the entire system. Two retail stores served as the field study sites. The PLM system was found to be effective at reducing plug load energy use, with a projected annual plug load reduction of 11% and 18% at the test locations. Retail staff reported that the hardware was easy to use, but no one used the online data management system, intended to analyze and control the hardware. This PLM solution shows promise as an effective means to monitor, control, and reduce plug load energy use, but the economics of the system need to be improved.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

General Purpose Data-Driven System Monitoring for Space Operations

Modern space propulsion and exploration system designs are becoming increasingly sophisticated and complex. Determining the health state of these systems using traditional methods is becoming more difficult as the number of sensors and component interactions grows. Data-driven monitoring techniques have been developed to address these issues by analyzing system operations data to automatically characterize normal system behavior. The Inductive Monitoring System (IMS) is a data-driven system health monitoring software tool that has been successfully applied to several aerospace applications. IMS uses a data mining technique called clustering to analyze archived system data and characterize normal interactions between parameters. This characterization, or model, of nominal operation is stored in a knowledge base that can be used for real-time system monitoring or for analysis of archived events. Ongoing and developing IMS space operations applications include International Space Station flight control, satellite vehicle system health management, launch vehicle ground operations, and fleet supportability. As a common thread of discussion this paper will employ the evolution of the IMS data-driven technique as related to several Integrated Systems Health Management (ISHM) elements. Thematically, the projects listed will be used as case studies. The maturation of IMS via projects where it has been deployed, or is currently being integrated to aid in fault detection will be described. The paper will also explain how IMS can be used to complement a suite of other ISHM tools, providing initial fault detection support for diagnosis and recovery.

Satellites↗

Real-time space system control with expert systems

Many aspects of space system operations involve continuous control of real time processes. These processes include electrical power system monitoring, prelaunch and ongoing propulsion system health and maintenance, environmental and life support systems, space suit checkout, onboard manufacturing, and vehicle servicing including satellites, shuttles, orbital maneuvering vehicles, orbital transfer vehicles and remote teleoperators. Traditionally, monitoring of these critical real time processes has been done by trained human experts monitoring telemetry data. However, the long duration of future space missions and the high cost of crew time in space creates a powerful economic incentive for the development of highly autonomous knowledge based expert control procedures for these space systems.

Leinweber, David↗

High-Power Electric Vehicle Charging Hub Integration Platform (eCHIP): Site Energy Management System Platform Development

A site energy management system is a critical component of future high-power EV charging hubs. It monitors and supervises all inter-hub operations, coordinates grid interactions, and implements energy management strategies and load-sharing controls at various levels and time scales. This report provides a comprehensive high-level overview and guidelines on the essential elements of such energy management systems. These elements primarily focus on the core functions, architecture, and monitoring aspects of site energy management. The core functions define the grid services and operational objectives that a charging hub is expected to provide and achieve. The architectural section investigates the coordination between hub assets, different control schemes, and their potential benefits and drawbacks. Lastly, the report discusses the needs, types, and functionalities of a monitoring and visualization system.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Use of treatment log files in spot scanning proton therapy as part of patient-specific quality assurance

Purpose: The purpose of this work was to assess the monitor unit (MU) values and position accuracy of spot scanning proton beams as recorded by the daily treatment logs of the treatment control system, and furthermore establish the feasibility of using the delivered spot positions and MU values to calculate and evaluate delivered doses to patients. Methods: To validate the accuracy of the recorded spot positions, the authors generated and executed a test treatment plan containing nine spot positions, to which the authors delivered ten MU each. The spot positions were measured with radiographic films and Matrixx 2D ion-chambers array placed at the isocenter plane and compared for displacements from the planned and recorded positions. Treatment logs for 14 patients were then used to determine the spot MU values and position accuracy of the scanning proton beam delivery system. Univariate analysis was used to detect any systematic error or large variation between patients, treatment dates, proton energies, gantry angles, and planned spot positions. The recorded patient spot positions and MU values were then used to replace the spot positions and MU values in the plan, and the treatment planning system was used to calculate the delivered doses to patients. The results were compared with the treatment plan. Results: Within a treatment session, spot positions were reproducible within {+-}0.2 mm. The spot positions measured by film agreed with the planned positions within {+-}1 mm and with the recorded positions within {+-}0.5 mm. The maximum day-to-day variation for any given spot position was within {+-}1 mm. For all 14 patients, with {approx}1 500 000 spots recorded, the total MU accuracy was within 0.1% of the planned MU values, the mean (x, y) spot displacement from the planned value was (-0.03 mm, -0.01 mm), the maximum (x, y) displacement was (1.68 mm, 2.27 mm), and the (x, y) standard deviation was (0.26 mm, 0.42 mm). The maximum dose difference between calculated dose to the patient based on the plan and recorded data was within 2%. Conclusions: The authors have shown that the treatment log file in a spot scanning proton beam delivery system is precise enough to serve as a quality assurance tool to monitor variation in spot position and MU value, as well as the delivered dose uncertainty from the treatment delivery system. The analysis tool developed here could be useful for assessing spot position uncertainty and thus dose uncertainty for any patient receiving spot scanning proton beam therapy.

60 APPLIED LIFE SCIENCES↗

Sensor enabled data-driven predictive analytics for modeling and control with high penetration of DERs in distribution systems

The electric power grid is undergoing a tremendous transformation due to the increasing penetration of renewable energy resources beginning with wind and more recently with the distributed energy resources (DERs) such as solar and battery storage. DERs have dramatically changed the role of the distribution systems in the overall power grid, and they are expected to contribute a significant portion of power generation in the future. If current trends for DERs continue, system operation and control will need to change dramatically for improved grid reliability and resiliency. As renewable resources increase in penetration, new and challenging operational, planning, and design problems are expected to emerge. Some of the key challenges that arise in the planning and operation of the future grid are: 1) Quantifying the impact of high DER penetration in distribution systems on bulk grid behavior over multiple time scales. 2) Identifying whether a particular DER configuration/settings have a large impact on the overall grid behavior. These challenges can be addressed in an offline manner using detailed T&D grid models and they can also be addressed in an online manner using sensor measurements. In particular, the advancement and planned growth in sensor technology in power grid over various voltage levels provide us with a unique opportunity to tackle these challenges from a data analytic perspective without needing detailed T&D grid models. A few questions that naturally arise when addressing the challenges from DERs using sensor data are: 1) How can we use limited sensor measurements to monitor & control voltage stability and small signal stability of the bulk system? 2) How can we ensure that the developed data analytic methods are robust to data availability and quality issues? 3) How can we compute the developed analytics in a scalable manner using streaming measurements? In this project, we addressed the aforementioned challenges arising from DERs and answered the questions raised above on how to effectively use the sensor measurements to enhance the reliability and performance of the electric grid. Thus, the overarching goal of this project is to develop effective reduced/representative system models from data that make the computational complexity sufficiently manageable so as to be useful to simulate, analyze, and even control complex non-linear power systems dynamics with large penetrations of DERs. In order to achieve the objective, the project team established a four-fold technical approach 1) Formulated a combined transmission-distribution co-simulation framework for data generation and validation, 2) Derived reduced/representative models of power systems based on data-driven methods for efficient computation and appropriate representation of system behavior, 3) Developed data driven characterization of power system behavior based on transfer operator theory, machine learning and optimization for model estimation, 4) Incorporated a scalable data management and processing architecture using distributed Kafka streaming applications that coordinate input data streams to the developed data analytics. The key accomplishments of the project are: 1) Development of a scalable multi-timescale T&D co-simulation framework (both for steady state and for dynamic co-simulation) using commercial solvers (PSSE and GridLAB-D). The steady-state T&D co-simulation interface is shared with our industry partner (PJM). 2) A structured reduced order dynamic model of distribution systems that can represent partial motor stalling along with a systematic procedure to derive the model parameters. 3) A PMU based online method to monitor, localize and mitigate fault-induced delayed voltage recovery using DER reactive support and load control in distribution systems. 4) Development of linear operator based robust methodologies for dynamic state estimation, uncertainty quantification, system identification and trajectory prediction for power system dynamics. 5) An adaptive damping control for utilizing wind energy resources to provide oscillation damping and system stability. 6) Implementation of Kafka-based framework for efficient processing of streaming data using Linux-based local virtual environment.

DER integration↗

Preliminary Design of Robotic Control Software for Mars Sample Return - Capture, Containment, and Return System

The Mars Sample Return (MSR) campaign aims to acquire and return to Earth a set of Mars samples for investigation in terrestrial laboratories. Mars 2020 has collected an adequate number of samples and deposited them in sealed sample tubes at a designated Martian depot. Sample tubes will be placed in cylindrical containers called Orbiting Samples (OS) by the Perseverance Rover, and later brought to Earth by the Earth Return Orbiter (ERO) and the MSR - Capture, Containment, and Return System (CCRS). Robot Software (RSW) is a set of software processes for commanding and monitoring the avionics that controls robotic mechanisms designed to sterilize and install OS into Earth Entry System (EES) for return to Earth. This paper describes a preliminary design of RSW including motion modes, architecture, and finite state machine. Additionally, software engineering procedures and testing of RSW is provided. A preliminary performance analysis is presented and the paper concludes with future work and a discussion of design decisions.

MSR↗

Metagames and Hypergames for Deception-Robust Control

Cyber-physical systems (CPSs) consist of computing and communication devices integrated with physical components such as sensors and actuators. Increasing connectivity to the Internet for remote monitoring and control has made CPSs more vulnerable to deliberate attacks, which are distinctly different from random perturbations in the system. This provides a way for purely cyber attacks to have physical consequences. Stuxnet is a prominent example of such an attack, one in which the malware acted over an extended period of time while deliberately remaining undetected. Such attacks can be described as Advanced Persistent Threats (APTs) -- long-term, stealthy attacks. Here, we extend our previous work on hypergames to develop defender strategies that are robust to deception and do not rely on attack detection. We prove that the defender can bound the attacker payoff with these strategies even when the attacker can choose between different attack modes, and we numerically demonstrate our approach on a realistic building control system. Finally, we discuss next steps in extending this approach towards an operational capability.

hypergames, cyber-physical systems, robust control↗

Review of water disinfection techniques

Throughout the history of manned space flight the supply of potable water to the astronauts has presented unique problems. Of particular concern has been the microbiological quality of the potable water. This has required the development of both preflight water system servicing procedures to disinfect the systems and inflight disinfectant addition and monitoring devices to ensure continuing microbiological control. The disinfectants successfully used to date have been aqueous chlorine or iodine. Because of special system limitations the use of iodine has been the most successful for inflight use and promises to be the agent most likely to be used in the future. Future spacecraft potable, hygiene, and experiment water systems will utilize recycled water. This will present special problems for water quality control. NASA is currently conducting research and development to solve these problems.

Colombo, Gerald V.↗

A prototype backside purge control system

New light-weight aluminum-lithium alloys are considered for propellant tank and aerospace structural applications. These alloys require more precise control of the welding atmosphere. Atmospheric oxygen contamination must be eliminated by flooding both the front and back sides of the weldment with an inert gas. This gas must be maintained at a desired pressure and flow rate that does not effect the stability of the weld process. The objective of the prototype backside purge control system being developed by Nichols Research Corporation (NRC) is to monitor and regulate the backside purge process and to develop a purge chamber design that enhances process controllability. This project will be conducted in two phases. The objective of Phase 1 is to develop a purge technique concept based on an investigation into the backside purge process. Phase 2 is to evaluate the backside purge concept developed in Phase 1.

Morris, Timothy B.↗

Measurement and Control of the Variability of Scanning Pressure Transducer Measurements

This paper describes the new wall pressure measurement system and data-quality monitoring software installed at 14x22 Ft subsonic tunnel at the NASA Langley Research Center. The monitoring software was developed to enable measurement and control of the variability of the reference pressures and approximately 400 tunnel wall pressure measurements. Variability of the system, based upon data acquired over a year of wind tunnel tests and calibrations, is presented. The level of variation of the wall pressure measurements is shown to be predictable.

Kuhl, David D.↗

Test equipment data package for the KC-135 fiber pulling apparatus

The Fiber Pulling Apparatus (FPA) is a device designed to produce continuous glass fibers from simulated lunar soil, and to determine the effects of reduced gravity, specifically 1/6 g on fiber formation and resultant properties. Briefly, pre-melt simulated lunar soil will be placed in a pint crucible and heated to 1200 C or higher, up to a maximum temperature of 1400 C. At a given temperature, a quartz fiber will be immersed into the melt and then pulled through a chill block and wound onto a cylindrical bobbin using a servo motor control. A high resolution video camera will record the fiber as it is being pulled. This assembly wil be enclosed in Plexiglas. Before fiber pulling commences, the apparatus will be backfilled with dry nitrogen. A separate data acquisition system will support this apparatus. This system will contain a personal computer, video recorder, and monitor. Temperature, acceleration, winding speed, and video images will be controlled and recorded using the data acquisition system. Thus, the FPA will consist of two hardware packages, the fiber production assembly and the data acquisition rack. The primary objective of this test is to determine the effects of 1/6 g on the formation of continuous glass fiber made from simulated lunar soil. Baseline studies using the FPA on the ground will provide a reference for the 1/6 g studies. Of particular interest will be the effect of 1/6 g on the free fluid zone where the fiber exits the crucible. In the fiber spinning parlance this zone is known as the upper jet region, where the boundary slope is greater than one tenth. The properties of the resulting glass fiber will depend on the jet shape as well as distributions of velocity, temperature and tension within the jet. It is unknown at this time how 1/6 g will effect these parameters.

Kosten, Sue↗

Traffic-Light-Preemption Vehicle-Transponder Software Module

A prototype wireless data-communication and control system automatically modifies the switching of traffic lights to give priority to emergency vehicles. The system, which was reported in several NASA Tech Briefs articles at earlier stages of development, includes a transponder on each emergency vehicle, a monitoring and control unit (an intersection controller) at each intersection equipped with traffic lights, and a central monitoring subsystem. An essential component of the system is a software module executed by a microcontroller in each transponder. This module integrates and broadcasts data on the position, velocity, acceleration, and emergency status of the vehicle. The position, velocity, and acceleration data are derived partly from the Global Positioning System, partly from deductive reckoning, and partly from a diagnostic computer aboard the vehicle. The software module also monitors similar broadcasts from other vehicles and from intersection controllers, informs the driver of which intersections it controls, and generates visible and audible alerts to inform the driver of any other emergency vehicles that are close enough to create a potential hazard. The execution of the software module can be monitored remotely and the module can be upgraded remotely and, hence, automatically

Bachelder, Aaron↗

Final Scientific Report: A Scalable Development Environment for Peta-Scale Computing

This document is the final scientific report of the project DE-SC000120 (A scalable Development Environment for Peta-Scale Computing). The objective of this project is the extension of the Parallel Tools Platform (PTP) for applying it to peta-scale systems. PTP is an integrated development environment for parallel applications. It comprises code analysis, performance tuning, parallel debugging and system monitoring. The contribution of the Juelich Supercomputing Centre (JSC) aims to provide a scalable solution for system monitoring of supercomputers. This includes the development of a new communication protocol for exchanging status data between the target remote system and the client running PTP. The communication has to work for high latency. PTP needs to be implemented robustly and should hide the complexity of the supercomputer's architecture in order to provide a transparent access to various remote systems via a uniform user interface. This simplifies the porting of applications to different systems, because PTP functions as abstraction layer between parallel application developer and compute resources. The common requirement for all PTP components is that they have to interact with the remote supercomputer. E.g. applications are built remotely and performance tools are attached to job submissions and their output data resides on the remote system. Status data has to be collected by evaluating outputs of the remote job scheduler and the parallel debugger needs to control an application executed on the supercomputer. The challenge is to provide this functionality for peta-scale systems in real-time. The client server architecture of the established monitoring application LLview, developed by the JSC, can be applied to PTP's system monitoring. LLview provides a well-arranged overview of the supercomputer's current status. A set of statistics, a list of running and queued jobs as well as a node display mapping running jobs to their compute resources form the user display of LLview. These monitoring features have to be integrated into the development environment. Besides showing the current status PTP's monitoring also needs to allow for submitting and canceling user jobs. Monitoring peta-scale systems especially deals with presenting the large amount of status data in a useful manner. Users require to select arbitrary levels of detail. The monitoring views have to provide a quick overview of the system state, but also need to allow for zooming into specific parts of the system, into which the user is interested in. At present, the major batch systems running on supercomputers are PBS, TORQUE, ALPS and LoadLeveler, which have to be supported by both the monitoring and the job controlling component. Finally, PTP needs to be designed as generic as possible, so that it can be extended for future batch systems.

97 MATHEMATICS AND COMPUTING↗

Control room consolidation at Hanford tank farms for improved conduct of operation - 15345

Washington River Protection Solutions (WRPS) manages the underground waste storage tanks at the Hanford site in Washington State on behalf of the DOE Office of River Protection. There are 177 tanks distributed among 18 tank farms spread across an area of desert scrub covering about 20 square miles. A single evaporator facility supports the tanks to provide waste reduction activities. Farms and associated equipment, including exhausters, have been operated locally since installation. Upgrades over time introduced limited automation, but using inconsistent platforms, and providing isolated control locations around the farms. However, as the Tank Farms move from maintenance operations to production operations, with increased numbers of waste transfers and evaporator campaigns, and also prepare for integration with the adjacent Hanford Waste Treatment Plant, then operational improvements were planned and are being implemented. Infrastructure improvement projects included upgrades of control systems to a common platform, and installation of a fiber optic based local area network to the majority of farms, which together provided a distributed control system supporting tank farms. This new infrastructure provided the basis to propose consolidation of control and monitoring operations to a single location. More than a single location, the new Central Control Room was to increase effectiveness of operations by providing full status of all activities being performed across the Tank Farms and the Evaporator. The recent addition of productivity e-tools also would provide capability for management, supervisors and operators to make informed decisions regarding facility operations, through custom online applications designed to provide real time information derived from operational data. For example, tracking turnover activities between shifts, and maintaining compliance with limited conditions for operations. The Central Control Room would also have a single supervisor able to effectively manage the status of all assets and processes. The expected benefits of this arrangement include increased operator utility, increased situational awareness, improved response time for upset conditions, improvement in operator environment, and reductions in operating costs. The projected ROI for the Central Control Room when fully operational was projected to be about two years based on reduced costs from freeing up operations staff to perform other work plus the time and material savings realized by operations being performed with increased situational awareness. So the Central Control Room would become a hub for monitoring and controlling facility operations while responding to real time information affecting productivity and performance, from a centralized location customized to a fresh working environment. Over a 14-month period, WRPS developed the concept and engineering, procured over 500 items, modified and installed in renovated building, and completed transition and testing of this new Central Control Room, turning over the initial phase to Operations for 24/7 use in April 2014. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Wireless Temperature-Monitoring System

A relatively inexpensive instrumentation system that includes units that are connected to thermocouples and that are parts of a radio-communication network has been developed to enable monitoring of temperatures at multiple locations. Because there is no need to string wires or cables for communication, the system is well suited for monitoring temperatures at remote locations and for applications in which frequent changes of monitored or monitoring locations are needed. The system can also be adapted to monitoring of slowly varying physical quantities, other than temperature, that can be transduced by solid-state electronic sensors. electronic sensors. The system comprises any number of transmitting units and a single receiving unit. Each transmitting unit includes connections for as many as four external thermocouples, a signal-conditioning module, a control module, and a radio-communication module. The signal-conditioning module acts as an interface between the thermocouples and the rest of the transmitting unit and includes a built-in solid ambient temperature sensor that is in addition to the external thermocouples. The control module is a system-on-chip embedded processor that includes analog-to-digital converters, serial and parallel data ports, and an interface for local connection to an analog meter that is used during installation to verify correct operation. The radio-communication module contains a commercial spread-spectrum transceiver that operates in the 900-MHz industrial, scientific, and medical (ISM) frequency band. This transceiver transmits data to the receiving unit at a rate of 19,200 baud. The receiving unit includes a transceiver like that of a transmitting unit, plus a control module that contains a system-on-chip processor that includes serial data port for output to a computer that runs monitoring and/or control software, a parallel data port for output to a printer, and a seven-segment light-emitting-diode display. Each transmitting unit is battery-powered and can operate for at least seven days continuously while reporting temperatures every half hour. The receiving unit is powered by a wall-mounted transformer source. The receiving unit responds to each transmitting unit and reports the readings of each of the four thermocouples and of the ambient-temperature sensor of the transmitting unit. The end-to-end accuracy of the system is plus or minus 0.2 C over the temperature range from 0 to 100 C. The radio-communication range between the receiving and transmitting units is approximately equal to 0.5 mile (approximately equal to 0.8 km).

Solano, Wanda↗

Mission Data System Java Edition Version 7

The Mission Data System framework defines closed-loop control system abstractions from State Analysis including interfaces for state variables, goals, estimators, and controllers that can be adapted to implement a goal-oriented control system. The framework further provides an execution environment that includes a goal scheduler, execution engine, and fault monitor that support the expression of goal network activity plans. Using these frameworks, adapters can build a goal-oriented control system where activity coordination is verified before execution begins (plan time), and continually during execution. Plan failures including violations of safety constraints expressed in the plan can be handled through automatic re-planning. This version optimizes a number of key interfaces and features to minimize dependencies, performance overhead, and improve reliability. Fault diagnosis and real-time projection capabilities are incorporated. This version enhances earlier versions primarily through optimizations and quality improvements that raise the technology readiness level. Goals explicitly constrain system states over explicit time intervals to eliminate ambiguity about intent, as compared to command-oriented control that only implies persistent intent until another command is sent. A goal network scheduling and verification process ensures that all goals in the plan are achievable before starting execution. Goal failures at runtime can be detected (including predicted failures) and handled by adapted response logic. Responses can include plan repairs (try an alternate tactic to achieve the same goal), goal shedding, ignoring the fault, cancelling the plan, or safing the system.

Reinholtz, William K.↗