Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “performance monitoring”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 559 records · Page 31
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Assessment of SRS ambient air monitoring network

Three methodologies have been used to assess the effectiveness of the existing ambient air monitoring system in place at the Savannah River Site in Aiken, SC. Effectiveness was measured using two metrics that have been utilized in previous quantification of air-monitoring network performance; frequency of detection (a measurement of how frequently a minimum number of samplers within the network detect an event), and network intensity (a measurement of how consistent each sampler within the network is at detecting events). In addition to determining the effectiveness of the current system, the objective of performing this assessment was to determine what, if any, changes could make the system more effective. Methodologies included 1) the Waite method of determining sampler distribution, 2) the CAP88- PC annual dose model, and 3) a puff/plume transport model used to predict air concentrations at sampler locations. Data collected from air samplers at SRS in 2015 compared with predicted data resulting from the methodologies determined that the frequency of detection for the current system is 79.2% with sampler efficiencies ranging from 5% to 45%, and a mean network intensity of 21.5%. One of the air monitoring stations had an efficiency of less than 10%, and detected releases during just one sampling period of the entire year, adding little to the overall network intensity. By moving or removing this sampler, the mean network intensity increased to about 23%. Further work in increasing the network intensity and simulating accident scenarios to further test the ambient air system at SRS is planned

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS1990

An automated environment for multiple spacecraft engineering subsystem mission operations

Flight operations at the Jet Propulsion Laboratory (JPL) are now performed by teams of specialists, each team dedicated to a particular spacecraft. Certain members of each team are responsible for monitoring the performances of their respective spacecraft subsystems. Ground operations, which are very complex, are manual, labor-intensive, slow, and tedious, and therefore costly and inefficient. The challenge of the new decade is to operate a large number of spacecraft simultaneously while sharing limited human and computer resources, without compromising overall reliability. The Engineering Analysis Subsystem Environment (EASE) is an architecture that enables fewer controllers to monitor and control spacecraft engineering subsystems. A prototype of EASE has been installed in the JPL Space Flight Operations Facility for on-line testing. This article describes the underlying concept, development, testing, and benefits of the EASE prototype.

Bahrami, K. A.↗
DOE OSTI2019

Modelling of air handling unit subsystem in a commercial building

To improve energy efficiency of the Air Handling Unit (AHU), there is a need for a system to monitor energy performance of the AHU in real time, to optimize operation for minimum energy consumption and to calculate energy saving. A mechanical model was created to analyze the performance of subsystems in an AHU and was validated using actual data collected from AHU operation via a wireless monitoring system. Algorithms have been developed to identify malfunctions and estimate the savings if malfunctions are corrected. Here, the model detects control related malfunctions, such as simultaneously turning on the cooling coil and the pre-heating coil. According to the mechanical model of the case study system, a total of 63,455 kWh are wasted within the cooling coil and the pre-heating coil due to this type of control malfunction. Furthermore, the mechanical model can identify other energy savings opportunities due to set point changes; in the case study system, this feature revealed a total of 77,141 kWh energy saving during the same study period. The design, integration, and validation of the mechanical model are described, analyzed, and justified in this paper.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2016

Framework for Structural Online Health Monitoring of Aging and Degradation of Secondary Systems due to some Aspects of Erosion

This report describes the current state of research related to critical aspects of erosion and selected aspects of degradation of secondary components in nuclear power plants. The report also proposes a framework for online health monitoring of aging and degradation of secondary components. The framework consists of an integrated multi-sensor modality system which can be used to monitor different piping configurations under different degradation conditions. The report analyses the currently known degradation mechanisms and available predictive models. Based on this analysis, the structural health monitoring framework is proposed. The Light Water Reactor Sustainability Program began to evaluate technologies that could be used to perform online monitoring of piping and other secondary system structural components in commercial NPPs. These online monitoring systems have the potential to identify when a more detailed inspection is needed using real-time measurements, rather than at a pre-determined inspection interval. This transition to condition-based, risk informed automated maintenance will contribute to a significant reduction of operations and maintenance costs that account for the majority of nuclear power generation costs. There is unanimous agreement between industry experts and academic researchers that identifying and prioritizing inspection locations in secondary piping systems (for example, in raw water piping or diesel piping) would eliminate many excessive in-service inspections. The proposed structural health monitoring framework takes aim at answering this challenge by combining long-range guided wave technologies with other monitoring techniques, which can significantly increase the inspection length and pinpoint the locations that degraded the most. More widely, the report suggests research efforts aimed at developing, validating, and deploying online corrosion monitoring techniques for complex geometries, which are pervasive in NPPs.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Real-Time Health Monitoring for Gas Turbine Components Using Online Learning and High-Dimensional Data

Capital-intensive turbomachinery, such as gas turbines and combined cycle plants, are constantly being monitored for performance anomalies, faults, and physical degradation. Although these power-generating assets are equipped with hundreds of sensors, existing monitoring tools can only handle moderate-sized data. As a result, only a handful of aggregate metrics are used to monitor machine health. At the same time, developing advanced tools suitable for large datasets have been restricted by the lack of appropriate data. The objective of this proposal was to demonstrate a Big Data analytics framework for fault detection and diagnosis in gas turbine applications. We develop a predictive analytics framework methodology guided by these experimental data, industrial data from our collaborators, and physics-based models with engineering domain knowledge. Our analytics framework consists of four key components (1) a data curation process that addresses data storage, data quality assessments, and integrity checks, (2) a feature engineering component that utilizes statistical methods and transformation algorithms guided by physics-based models to extract high-fidelity fault features that can be leveraged for fault detection and classifying fault severities, (3) a Machine Learning-based fault detection and diagnostics algorithms for detecting operational and hardware faults in the combustion and the turbines section. We utilize two industry-class gas turbine component test rigs to generate first of its kind data for critical gas turbine faults with varying severity levels. Advanced gas turbine test facilities will be interrogated using state-of-the-art instrumentation techniques to build fault signatures and data trends for key combustor and turbine faults. Data generated from a combustor test rig (Georgia Tech) and a turbine test rig (Penn State) during both normal operation and with seeded faults serve as the basis for the Big Data sets. The test conditions in the two test facilities include common, critical events that occur in the operation. Utilizing the combustor test rig, we examine two common combustor faults: lean blowout and centerbody degradation. For the turbine section we develop analytic models for monitoring cooling faults in the gas turbine

03 NATURAL GAS↗
DOE OSTI2017

FRAMEWORK FOR STRUCTURAL ONLINE HEALTH MONITORING OF AGING AND DEGRADATION OF SECONDARY PIPING SYSTEMS DUE TO SOME ASPECTS OF EROSION

This paper describes the current state of research related to critical aspects of erosion and selected aspects of degradation of secondary components in nuclear power plants (NPPs). The paper also proposes a framework for online health monitoring of aging and degradation of secondary components. The framework consists of an integrated multi-sensor modality system, which can be used to monitor different piping configurations under different degradation conditions. The report analyses the currently known degradation mechanisms and available predictive models. Based on this analysis, the structural health monitoring framework is proposed. The Light Water Reactor Sustainability Program began to evaluate technologies that could be used to perform online monitoring of piping and other secondary system structural components in commercial NPPs. These online monitoring systems have the potential to identify when a more detailed inspection is needed using real time measurements, rather than at a pre-determined inspection interval. This transition to condition-based, risk-informed automated maintenance will contribute to a significant reduction of operations and maintenance costs that account for the majority of nuclear power generation costs. Furthermore, of the operations and maintenance costs in U.S. plants, approximately 80% are labor costs. To address the issue of rising operating costs and economic viability, in 2017, companies that operate the national nuclear energy fleet started the Delivering the Nuclear Promise Initiative, which is a 3 year program aimed at maintaining operational focus, increasing value, and improving efficiency. There is unanimous agreement between industry experts and academic researchers that identifying and prioritizing inspection locations in secondary piping systems (for example, in raw water piping or diesel piping) would eliminate many excessive in-service inspections. The proposed structural health monitoring framework takes aim at answering this challenge by combining long range guided wave technologies with other monitoring techniques, which can significantly increase the inspection length and pinpoint the locations that degraded the most. More widely, the report suggests research efforts aimed at developing, validating, and deploying online corrosion monitoring techniques for complex geometries, which are pervasive in NPPs.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Real-Time Health Monitoring for Gas Turbine Components Using Online Learning and High-Dimensional Data (Final Report)

Capital-intensive turbomachinery, such as gas turbines and combined cycle plants, are constantly being monitored for performance anomalies, faults, and physical degradation. Although these power-generating assets are equipped with hundreds of sensors, existing monitoring tools can only handle moderate-sized data. As a result, only a handful of aggregate metrics are used to monitor machine health. At the same time, developing advanced tools suitable for large datasets have been restricted by the lack of appropriate data. The objective of this proposal was to demonstrate a Big Data analytics framework for fault detection and diagnosis in gas turbine applications. We develop a predictive analytics framework methodology guided by these experimental data, industrial data from our collaborators, and physics-based models with engineering domain knowledge. Our analytics framework consists of four key components: (1) a data curation process that addresses data storage, data quality assessments, and integrity checks, (2) a feature engineering component that utilizes statistical methods and transformation algorithms guided by physics-based models to extract high-fidelity fault features that can be leveraged for fault detection and classifying fault severities, (3) a Machine Learning-based fault detection and diagnostics algorithms for detecting operational and hardware faults in the combustion and the turbines section. We utilize two industry-class gas turbine component test rigs to generate first of its kind data for critical gas turbine faults with varying severity levels. Advanced gas turbine test facilities will be interrogated using state-of-the-art instrumentation techniques to build fault signatures and data trends for key combustor and turbine faults. Data generated from a combustor test rig (Georgia Tech) and a turbine test rig (Penn State) during both normal operation and with seeded faults serve as the basis for the Big Data sets. The test conditions in the two test facilities include common, critical events that occur in the operation. Utilizing the combustor test rig, we examine two common combustor faults: lean blowout and centerbody degradation. For the turbine section we develop analytic models for monitoring cooling faults in the gas turbine.

20 FOSSIL-FUELED POWER PLANTS↗
NASA NTRS1988

A multiprocessing architecture for real-time monitoring

A multitasking architecture for performing real-time monitoring and analysis using knowledge-based problem solving techniques is described. To handle asynchronous inputs and perform in real time, the system consists of three or more distributed processes which run concurrently and communicate via a message passing scheme. The Data Management Process acquires, compresses, and routes the incoming sensor data to other processes. The Inference Process consists of a high performance inference engine that performs a real-time analysis on the state and health of the physical system. The I/O Process receives sensor data from the Data Management Process and status messages and recommendations from the Inference Process, updates its graphical displays in real time, and acts as the interface to the console operator. The distributed architecture has been interfaced to an actual spacecraft (NASA's Hubble Space Telescope) and is able to process the incoming telemetry in real-time (i.e., several hundred data changes per second). The system is being used in two locations for different purposes: (1) in Sunnyville, California at the Space Telescope Test Control Center it is used in the preflight testing of the vehicle; and (2) in Greenbelt, Maryland at NASA/Goddard it is being used on an experimental basis in flight operations for health and safety monitoring.

Schmidt, James L.↗
NASA NTRS1972

Contamination avoidance devices for poppet type shutoff valves

The technology required to provide acceptable contamination damage avoidance characteristics for poppet type shutoff valves is discussed. Evaluation of the contamination avoidance characteristics of the basic 1T32095 propellant shutoff valve, the cycle life performance of these valves in an uncontaminated environment, and the effectiveness of various auxiliary contamination avoidance devices when used in conjunction with these poppet type valves are included. In addition, a secondary objective is to evaluate two methods of monitoring the performance of the test valves during actual operations using acoustical monitoring instrumentation.

Endicott, D. L.↗
NASA NTRS2008

Sixty-four-Channel Inline Cable Tester

Faults in wiring are a serious concern for the aerospace and aeronautics (commercial, military, and civil) industries. A number of accidents have occurred because faulty wiring created shorts or opens that resulted in the loss of control of the aircraft or because arcing led to fires and explosions. Some of these accidents have resulted in the massive loss of lives (such as in the TWA Flight 800 accident). Circuits on the Space Shuttle have also failed because of faulty insulation on wiring. STS-93 lost power when a primary power circuit in one engine failed and a second engine had a backup power circuit fault. Cables are usually tested on the ground after the crew reports a fault encountered during flight. Often such failures result from vibration and cannot be replicated while the aircraft is stationary. It is therefore important to monitor faults while the aircraft is in operation, when cables are more likely to fail. Work is in progress to develop a cable fault tester capable of monitoring up to 64 individual wires simultaneously. Faults can be monitored either inline or offline. In the inline mode of operation, the monitoring is performed without disturbing the normal operation of the wires under test. That is, the operations are performed unintrusively and are essentially undetectable for the test signal levels are below the noise floor. A cable can be monitored several times per second in the offline mode and once a second in the inline mode. The 64-channel inline cable tester not only detects the occurrence of a fault, but also determines the type of fault (short/open) and the location of the fault. This will enable the detection of intermittent faults that can be repaired before they become serious problems.

Source record↗
NASA NTRS2012

Microbial Monitoring Challenges and Needs for Mars Applications

The monitoring of microorganisms will be an important part of a mission to Mars. Microbial monitoring equipment will be needed to look for the presence of microorganisms on the planet, to confirm that planetary protection measures are working, to monitor the health of plants, bioreactors and humans living in a habitat and to monitor the performance of the life support systems that will keep them alive during their stay on Mars. Coordinating the different microbial monitoring needs during the early days of mission planning, can provide NASA with equipment that could meet more than one need while also providing complementary analysis options, which can enhance the research capabilities. The early coordination between the different NASA groups that will need microbial monitoring equipment on the surface of Mars, could also make the mission more affordable, as development of the needed equipment could be potentially cost shared.

Roman, M. C.↗
DOE OSTI2017

Extending Skel to Support the Development and Optimization of Next Generation I/O Systems

As the memory and storage hierarchy get deeper and more complex, it is important to have new benchmarks and evaluation tools that allow us to explore the emerging middleware solutions to use this hierarchy. Skel is a tool aimed at automating and refining this process of studying HPC I/O performance. It works by generating application I/O kernel/benchmarks as determined by a domain-specific model. This paper provides some techniques for extending Skel to address new situations and to answer new research questions. For example, we document use cases as diverse as using Skel to troubleshoot I/O performance issues for remote users, refining an I/O system model, and facilitating the development and testing of a mechanism for runtime monitoring and performance analytics. We also discuss data oriented extensions to Skel to support the study of compression techniques for Exascale scientific data management.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Development and performance evaluation of active insulation systems using solid-state thermal switches

Traditional building envelopes have passive insulation systems that cannot respond to dynamic changes in the environment. An Active Insulation System (AIS) consists of Active Insulation Materials (AIMs) that dynamically vary the thermal conductivity of the insulation system. Several researchers have evaluated the impact of AIS on building thermal and energy performance by using simulation tools. Up to 70% savings in annual heating and cooling energy and significant reductions in peak demand have been predicted for some climates with wall systems employing AIS. However, materials and assembly development still need a cost-effective product that achieves the required performance. Here, in this study, we present the process of developing an AIS that we will install in a test hut for its performance evaluation. Minimum performance criteria of the AIS system are developed based on R-low/R-high ratio, required time and efficiency to switch states, and cost estimates. The following steps during this study are creating the concept to meet the requirements, predicting the performance via simulations, developing the experimental setup for bench-scale testing, and finally, constructing a full-scale wall assembly and monitoring the performance when exposed to environmental chamber tests. The selected approach uses off-the-shelf products to create an AIS that can switch R-value between 0.98 ft 2 ·°F·h/BTU (0.173 m 2 ·K/W) and 5.81 ft 2 ·°F·h/BTU (1.02 m 2 ·K/W) and have a switching time of less than one minute between R-high and R-low.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS2013

MODIS and VIIRS Lunar Observations and Applications

Terra and Aqua MODIS have successfully operated for more than 13 and 11 years since their launch in 1999 and 2002, respectively. The VIIRS instrument on-board the S-NPP launched in 2011 has also operated for nearly 2 years. Both MODIS and VIIRS make observations in the reflective solar and thermal emissive regions and their on-orbit calibration and characterization are provided by a set of on-board calibrators (OBC). In addition, lunar observations have been made on a regular basis to support sensor on-orbit calibration. This paper provides a brief overview of MODIS and VIIRS instrument on-orbit calibration and characterization activities. It describes the approaches and strategies developed to schedule and perform on-orbit lunar observations. Specific applications of MODIS and VIIRS lunar observations discussed in this paper include radiometric calibration stability monitoring and performance assessment of sensor spatial characterization. Results derived from lunar observations, such as sensor response (or gain) trending and band-to-band registration, are compared with that derived from sensor OBC. The methodologies and applications presented in this paper can also be applied to other earth observing sensors.

MODIS↗
DOE OSTI2022

Development and Performance Evaluation of of Active Insulation Systems using Solid-State Thermal Switches

Traditional building envelopes have passive insulation systems that cannot respond to dynamic changes in the environment. An Active Insulation System (AIS) consists of Active Insulation Materials (AIMs), which dynamically vary the thermal conductivity of the insulation system. Several researchers have evaluated the impact of AIS on building thermal and energy performance by using simulation tools. Up to 70% savings in annual heating and cooling energy and significant reductions in peak demand have been predicted for some climates with wall systems employing AIS. Sensitivity studies have provided requirements for the AIS properties and control schemes that can lead to those savings. However, materials and assembly development have not yet achieved a cost-effective product that achieves the required performance. In this study, we present the process to develop an AIS that we will install in a test hut for their performance evaluation. Minimum performance criteria of the AIS system are developed based on Rmin/Rmax ratio, required time and efficiency to switch states and cost estimate. The next step carried out during this study is creating the concept to meet the requirements, predicting the performance by simulations, developing the experimental setup for bench-scale testing, and finally, constructing a full-scale wall assembly and monitoring the performance when exposed to natural weather conditions. The selected approach uses off-the-shelf products to create a materials system that can switch R-value between R~=1 ft2·°F·h/BTU (0.18 m2·K/W) and R~=7 ft2·°F·h/BTU (1.23 m2·K/W and have a switching time of less than one minute between R-high and R-low.

Iffa, Emishaw↗
DOE OSTI2016

Field Performance of Heat Pump Water Heaters in the Northeast

Heat pump water heaters (HPWHs) are finally entering the mainstream residential water heater market. Potential catalysts are increased consumer demand for higher energy efficiency electric water heating and a new Federal water heating standard that effectively mandates use of HPWHs for electric storage water heaters with nominal capacities greater than 55 gallons. When compared to electric resistance water heating, the energy and cost savings potential of HPWHs is tremendous. Converting all electric resistance water heaters to HPWHs could save American consumers 7.8 billion dollars annually ($182 per household) in water heating operating costs and cut annual residential source energy consumption for water heating by 0.70 quads. Steven Winter Associates, Inc. embarked on one of the first in situ studies of these newly released HPWH products through a partnership with two sponsoring electric utility companies, National Grid and NSTAR, and one sponsoring energy efficiency service program administrator, Cape Light Compact. Recent laboratory studies have measured performance of HPWHs under various operating conditions, but publically available field studies have not been as available. This evaluation attempts to provide publicly available field data on new HPWHs by monitoring the performance of three recently released products (General Electric GeoSpring(TM), A.O. Smith Voltex(R), and Stiebel Eltron Accelera(R) 300). Fourteen HPWHs were installed in Massachusetts and Rhode Island and monitored for over a year. Of the 14 units, ten were General Electric models (50 gallon units), two were Stiebel Eltron models (80 gallon units), and two were A.O. Smith models (one 60-gallon and one 80-gallon unit).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Monitoring the long-term performance of organic redox flow battery by a distribution of relaxation time analysis

Organic redox flow batteries hold great promise as an energy storage technology, but their intricate chemistry makes them vulnerable to various degradation mechanisms. Monitoring this degradation is essential for identifying the limiting processes within the cells. Electrochemical impedance spectroscopy (EIS) offers a straightforward, in-situ method for measuring the total resistance of an operating cell. However, to pinpoint the limiting processes during long-term cycling, EIS data must be complemented by other techniques. Distribution of relaxation time (DRT) analysis is particularly effective for differentiating resistance components. Here, in this study, we perform a comprehensive analysis of resistance evolution and the separation of anode and cathode contributions during long-term cycling of a full cell employing 7,8-dihydroxyphenazine-2-sulfonic acid (DHPS) as the anolyte. Separate analyses of the DHPS anolyte and ferri-/ferrocyanide catholyte were conducted using a symmetric cell setup. The relaxation times derived from symmetric cells facilitate the identification of peaks in the DRT profiles from the full cell. Importantly, the DRT profiles indicate a correlation between the evolution of charge transfer resistance and the chemical degradation of DHPS. The methodologies and results outlined in this study offer significant insights for developing diagnostic tools applicable to other types of redox flow batteries.

Distribution of relaxation time↗
NASA NTRSDate not supplied

Differential Mobility Spectrometry on the ISS: Successes and Current Concerns

With the construction of the International Space Station (ISS), crew members moved from the relatively short flights of the Space Shuttle (~ 2 weeks) to missions lasting months to a year. As such, environmental monitoring needs also changed, transitioning from a reliance on archival sampling to a combination of archival sampling and in-flight data collection. In the case of trace volatile organic compound (VOC) monitoring, this in-flight monitoring was performed early on by the Volatile Organic Analyzer (VOA), a gas chromatograph-ion mobility spectrometer, which operated on the ISS for 7 years. This large, fixed-position analyzer was replaced by Air Quality Monitors (AQMs), a pair of small gas chromatograph-differential mobility spectrometers, in the spring of 2013. During their initial half decade of use, and covering multiple sets of units, the AQMs performed well, meeting all of their validation criteria and generally showing excellent accuracy when compared to the now-reduced archival samples. These instruments were also used to perform a survey of the US Operating Segment (US Lab Module, European Columbus Module, and Japanese Pressurized Module), confirming that the atmosphere in this segment is well-mixed. The AQMs were also able to provide important information in contingency situations, such as confirming that no ammonia was present on the ISS following alarms suggesting that the coolant loops had leaked in January 2015. As the fleet of AQMs has aged, though, issues of concern have arisen. These have ranged from pervasive electronics board problems to loss of sensitivity due to carbon dioxide to incorrect identification of compounds. Some of these issues are unavoidable due to the nature of the AQM’s use and preparation prior to flight. However, with the extension of the ISS to 2030 (well past its original 2024 lifetime), the fleet of AQMs will be asked to perform longer, requiring solutions to some of the inherent problems. In this presentation, we will discuss the history of the AQM on the ISS with a focus on more recent results. These results show both the continued usefulness of the AQM for atmospheric monitoring and also the current concerns, including: 1) the incorrect identification of benzene, 2) reporting of elevated isopropanol concentrations, and 3) the loss of the reactant ion peak (RIP) that must be resolved in order for the instrument to continue to serve as the primary trace VOC monitor on the ISS.

W T Wallace↗