Search NASA⌕ Search

SEARCH · Search NASA

Results for “building 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 73 records · Page 4

A Review of Diagnostic Techniques for ISHM Applications

System diagnosis is an integral part of any Integrated System Health Management application. Diagnostic applications make use of system information from the design phase, such as safety and mission assurance analysis, failure modes and effects analysis, hazards analysis, functional models, fault propagation models, and testability analysis. In modern process control and equipment monitoring systems, topological and analytic , models of the nominal system, derived from design documents, are also employed for fault isolation and identification. Depending on the complexity of the monitored signals from the physical system, diagnostic applications may involve straightforward trending and feature extraction techniques to retrieve the parameters of importance from the sensor streams. They also may involve very complex analysis routines, such as signal processing, learning or classification methods to derive the parameters of importance to diagnosis. The process that is used to diagnose anomalous conditions from monitored system signals varies widely across the different approaches to system diagnosis. Rule-based expert systems, case-based reasoning systems, model-based reasoning systems, learning systems, and probabilistic reasoning systems are examples of the many diverse approaches ta diagnostic reasoning. Many engineering disciplines have specific approaches to modeling, monitoring and diagnosing anomalous conditions. Therefore, there is no "one-size-fits-all" approach to building diagnostic and health monitoring capabilities for a system. For instance, the conventional approaches to diagnosing failures in rotorcraft applications are very different from those used in communications systems. Further, online and offline automated diagnostic applications are integrated into an operations framework with flight crews, flight controllers and maintenance teams. While the emphasis of this paper is automation of health management functions, striking the correct balance between automated and human-performed tasks is a vital concern.

Patterson-Hine, Ann↗

Development of electrostatic sensors for scout systems evaluation vehicle, 131r

In the course of a Scout vehicle mission, a static charge may build up on the vehicle and reach sufficiently high values to become potentially dangerous to the vehicle mission. The development of electrostatic sensors for monitoring the potential build-up on a Scout vehicle is discussed in this report. The investigation and studies, which produced the theories tor the electrostatic sensor concepts, are also discussed. The sensors were designed, fabricated and installed on Scout vehicle 131R. Results of the sensor development program are discussed in full; however, at the time this report was completed, the flight experiment had not been accomplished.

Scout Project↗

Real-time robot deliberation by compilation and monitoring of anytime algorithms

Anytime algorithms are algorithms whose quality of results improves gradually as computation time increases. Certainty, accuracy, and specificity are metrics useful in anytime algorighm construction. It is widely accepted that a successful robotic system must trade off between decision quality and the computational resources used to produce it. Anytime algorithms were designed to offer such a trade off. A model of compilation and monitoring mechanisms needed to build robots that can efficiently control their deliberation time is presented. This approach simplifies the design and implementation of complex intelligent robots, mechanizes the composition and monitoring processes, and provides independent real time robotic systems that automatically adjust resource allocation to yield optimum performance.

Zilberstein, Shlomo↗

Review and Performance Testing of the Optical Power Monitor (PMON)

The LISA mission requires a high precision optical power monitoring and control system that combines high reliability and measurement accuracy with extremely low disturbance to the core interferometric detection system. NASA is working with Avo Photonics to design and build this optical power monitor, known as PMON. The high-level design requirements take into account detector redundancy, mechanical rigidity, stability against temperature and input alignment changes, parasitic scatter and reflection artifacts, as well as low magnetic field. Gamma and Proton radiation tests have been performed on the photodiodes from a few vendors to verify radiation tolerance. Engineering development units of the PMON have been fabricated, delivered and evaluated at NASA.

Hua Jiao↗

Self-calibrating models for dynamic monitoring and diagnosis

A method for automatically building qualitative and semi-quantitative models of dynamic systems, and using them for monitoring and fault diagnosis, is developed and demonstrated. The qualitative approach and semi-quantitative method are applied to monitoring observation streams, and to design of non-linear control systems.

Kuipers, Benjamin↗

Expert systems for real-time monitoring and fault diagnosis

Methods for building real-time onboard expert systems were investigated, and the use of expert systems technology was demonstrated in improving the performance of current real-time onboard monitoring and fault diagnosis applications. The potential applications of the proposed research include an expert system environment allowing the integration of expert systems into conventional time-critical application solutions, a grammar for describing the discrete event behavior of monitoring and fault diagnosis systems, and their applications to new real-time hardware fault diagnosis and monitoring systems for aircraft.

Edwards, S. J.↗

RAPID: Collaboration Results from Three NASA Centers in Commanding/Monitoring Lunar Assets

Three NASA centers are working together to address the challenge of operating robotic assets in support of human exploration of the Moon. This paper describes the combined work to date of the Ames Research Center (ARC), Jet Propulsion Laboratory (JPL) and Johnson Space Center (JSC) on a common support framework to control and monitor lunar robotic assets. We discuss how we have addressed specific challenges including time-delayed operations, and geographically distributed collaborative monitoring and control, to build an effective architecture for integrating a heterogeneous collection of robotic assets into a common work. We describe the design of the Robot Application Programming Interface Delegate (RAPID) architecture that effectively addresses the problem of interfacing a family of robots including the JSC Chariot, ARC K-10 and JPL ATHLETE rovers. We report on lessons learned from the June 2008 field test in which RAPID was used to monitor and control all of these assets. We conclude by discussing some future directions to extend the RAPID architecture to add further support for NASA's lunar exploration program.

Torres, R. Jay↗

OSS-1/contamination monitor

A 20-cm high, 18-cm wide, and 30-cm long (8x7x12 inch) box weighing about 7 kg (15 lbs) and consuming about 7 watts of power was carried on the OSS-1 pallet to monitor the mass build-up or accretion of condensible, volatile materials on surfaces in the shuttle bay during all phases of ascent, on-orbit, and descent. Passively thermally controlled, the box holds two witness samples and four actively temperature controlled quartz crystal microbalances (TQCM) whose temperature can vary from -60 C to +80 C. Graphs show the accretion indicated by the TQCM during the launch and early orbital phase. Conditions during tail to the Sun, nose to the Sun, and bay to the Sun attitudes of the shuttle during STS-3 are reflected in temperatures indicated by the OSS-1 thermistor. These temperatures influence outgassing rates of various materials as well as measurements made by the contamination monitor package. The parameters that bear on TQCM measurements data are shown in graphs and discussed.

Kruger, R.↗

Hydrogen Leak Modeling for Development of Smart Distributed Monitoring Under Unintended Releases

Hydrogen is a versatile and clean energy carrier that can be produced from various renewable sources such as wind, solar, and hydropower. Hydrogen has the potential to play a crucial role in decarbonizing industrial processes that are currently reliant on fossil fuels and provide long-duration and/or seasonal energy storage to enable electricity decarbonization. Hydrogen can also be used as a fuel for fuel cell vehicles, providing a zero-emission alternative to traditional internal combustion engines. DOE launched the Hydrogen Energy Earthshot (Hydrogen Shot) in June 2021 to reduce the cost of clean hydrogen by 80% to $1 per 1 kilogram in 1 decade ("1 1 1"). While promising, Hydrogen is highly-flammable, and in the presence of oxygen, it can form explosive mixtures. . Therefore, understanding leak scenarios is essential to evaluate and mitigate the safety risks associated with potential hydrogen leaks. An increased understanding of leak behavior, and having tools to model leaks, can help assess how hydrogen would disperse in different environments, influencing emergency response plans and safety measures, and identify potential issues with materials and design systems that can withstand the challenges posed by hydrogen. Recently, researchers have attempted to study hydrogen leaks for development of risk management strategies. However, the focus has been on closed or semi-closed spaces like storage rooms, vehicles, garages, and fueling stations - all promising locations for future hydrogen infrastructure. In this presentation, the modeling environment extends the span of research further by modeling hydrogen leak in an outdoor, open space. We will present the key challenges with modeling hydrogen leaks in an uncontrollable environment, how they were handled, and how modeling results informed sensor selection and placement. A Hydrogen research facility at the National Renewable Energy Laboratory (NREL) was used as a case study to model hydrogen leaks. In the future, Hydrogen wide area detection methodologies will be developed and tested at this site to monitor for unintended and operational hydrogen releases. The data generated from modeling will be used to develop a predictive model to detect hydrogen leak location based on concentration measured by sensors in this open space. Furthermore, the facility was also chosen because controlled hydrogen releases can be performed. A computational fluid dynamics (CFD) based modeling approach was taken to model hydrogen leak. The full-scale hydrogen facility was modeled with a large ambient domain. The electrolyzer at the facility can produce a controlled release rate of 27 kg-H2/hr. Site-specific atmospheric and weather condition data such as wind direction, wind speed at various altitudes, and temperature were used as inputs to the model. To capture the variability of weather conditions, a subset of the weather conditions experienced during daytime hours without precipitation over the course of three months was generated; using established data clustering techniques, a total of 100 condition sets were chosen. The results show statistical distributions and ranges of hydrogen concentrations at locations throughout the domain. These distributions are compared to experimental data from a constant mass flow, controlled hydrogen release at the facility. The stochastic wind conditions of the release make direct validation difficult, therefore, statistical comparison approaches were used. Wind conditions are found to significantly impact the release behavior, including direction and concentration. Sensor selection and placement is proposed for the facility and is now based on release behavior predicted for the facility given its weather patterns; this is much more informed than without the modeling results. The methodology and analysis procedure can be translated to other facilities using modified geometries and site-specific weather conditions. Hydrogen holds great promise as a renewable energy fuel, but ensuring safety in its production, storage, and use is paramount. Studying potential leak scenarios in an open space will help develop sensors to detect hydrogen on a large spectrum of concentration and eventually build a smart distributed monitoring system.

CFD↗

Low-Cost, Class D Testing of Spacecraft Photovoltaic Systems Can Reduce Risk

The end-to-end verification of a spacecraft photovoltaic power generation system requires light! Specifically, the standard practice for doing so is the Large Area Pulsed Solar Simulation (LAPSS). A LAPSS test can characterize a photovoltaic system's efficiency via its response to rapidly applied impulses of simulated sunlight. However, a Class D program on a constrained budget and schedule may not have the resources to ship an entire satellite for a LAPSS test alone. Such was the case with the Lunar Atmospheric and Dust Environment Explorer (LADEE) program, which was also averse to the risk of hardware damage during shipment. When the Electrical Power System (EPS) team was denied a spacecraft-level LAPSS test, the lack of an end-to-end power generation test elevated to a project-level technical risk. The team pulled together very limited resources to not only eliminate the risk, but build a process to monitor the health of the system through mission operations. We discuss a process for performing a low-cost, end-to-end test of the LADEE photovoltaic system. The approach combines system-level functional test, panel-level performance results, and periodic inspection (and repair) up until launch. Following launch, mission operations tools are utilized to assess system performance based on a scant amount of data. The process starts in manufacturing at the subcontractor. The panel manufacturer provides functional test and LAPSS data on each individual panel. We apply an initial assumption that the per-panel performance is sufficient to meet the power generation requirements. The manufacturer's data is also carried as the performance allocation for each panel during EPS system modeling and initial mission operations. During integration and test, a high-power, professional theater lamp system provides simulated sunlight to each panel on the spacecraft, thereby permitting a true end-to-end system test. A passing test results in a step response to nearly full-rated current at the appropriate solar array switch in the power system. A metal-halide bulb, infrared imagers, and onboard spacecraft measurements are utilized to minimize risk of thermal damage during test. Data is provided to support test results for both passing and marginal panels. Prior to encapsulation in the launch vehicle, each panel is inspected for damage by the panel manufacturer. Cracked cells or other damage is amended on-site. Because the photovoltaic test system is inexpensive and portable, each repaired panel can be re-verified immediately. Post-launch, the photovoltaic system is again characterized for per-panel deviations from the manufacturer's performance test. This proved especially tricky as the LADEE spacecraft performs only one current measurement on the entire array. The algorithm for Matlab tools to assess panel performance based on spacecraft attitude is discussed. While not as precise and comprehensive as LAPSS, the LADEE approach leverages minimal resources into an ongoing assessment program that can be applied through numerous stages of the mission. The project takes a true Class D approach in assessing the technical value of a spacecraft level performance test versus the programmatic risk of shipping the spacecraft to another facility. The resources required are a fraction of that for a LAPSS test, and is easy to repeat. Further, the test equipment can be handed down to future projects without building an on-site facility.

photovoltaic↗

Development of a Real-Time GPS/Seismic Displacement Meter: Applications to Civilian Infrastructure in Orange and Western Riverside Counties, California

We propose a three-year applications project that will develop an Integrated Real-Time GPS/Seismic System and deploy it in Orange and Western Riverside Counties, spanning three major strike-slip faults in southern California (San Andreas, San Jacinto, and Elsinore) and significant populations and civilian infrastructure. The system relying on existing GPS and seismic networks will collect and analyze GPS and seismic data for the purpose of estimating and disseminating real-time positions and total ground displacements (dynamic, as well as static) during all phases of the seismic cycle, from fractions of seconds to years. Besides its intrinsic scientific use as a real-time displacement meter (transducer), the GPS/Seismic System will be a powerful tool for local and state decision makers for risk mitigation, disaster management, and structural monitoring (dams, bridges, and buildings). Furthermore, the GPS/Seismic System will become an integral part of California's spatial referencing and positioning infrastructure, which is complicated by tectonic motion, seismic displacements, and land subsidence. Finally, the GPS/Seismic system will also be applicable to navigation in any environment (land, sea, or air) by combining precise real-time instantaneous GPS positioning with inertial navigation systems. This development will take place under the umbrella of the California Spatial Reference Center, in partnership with local (Counties, Riverside County Flood and Water Conservation District, Metropolitan Water District), state (Caltrans), and Federal agencies (NGS, NASA, USGS), the geophysics community (SCIGN/SCEC2), and the private sector (RBF Consulting). The project will leverage considerable funding, resources, and R&D from SCIGN, CSRC and two NSF-funded IT projects at UCSD and SDSU: RoadNet (Real-Time Observatories, Applications and Data Management Network) and the High Performance Wireless Research and Education Network (HPWREN). These two projects are funded to develop both the wireless networks and the integrated, seamless, and transparent information management system that will deliver seismic, geodetic, oceanographic, hydrological, ecological, and physical data to a variety of end users in real-time in the San Diego region. CSRC is interested in providing users access to real-time, accurate GPS data for a wide variety of applications including RTK surveying/GIS and positioning of moving platforms such as aircraft and emergency vehicles. SCIGN is interested in upgrading sites to high-frequency real-time operations for rapid earthquake response and GPS seismology. The successful outcome of the project will allow the implementation of similar systems elsewhere, particularly in plate boundary zones with significant populations and civilian infrastructure. CSRC would like to deploy the GPS/Seismic System in other parts of California, in particular San Diego, Los Angeles County and the San Francisco Bay Area.

Bock, Yehuda↗

Robotics Algorithms Provide Nutritional Guidelines

On July 5, 1997, a small robot emerged from its lander like an insect from an egg, crawling out onto the rocky surface of Mars. About the size of a child s wagon, NASA s Sojourner robot was the first successful rover mission to the Red Planet. For 83 sols (Martian days, typically about 40 minutes longer than Earth days), Sojourner - largely remote controlled by NASA operators on Earth - transmitted photos and data unlike any previously collected. Sojourner was perhaps the crowning achievement of the NASA Space Telerobotics Program, an Agency initiative designed to push the limits of robotics in space. Telerobotics - devices that merge the autonomy of robotics with the direct human control of teleoperators - was already a part of NASA s efforts; probes like the Viking landers that preceded Sojourner on Mars, for example, were telerobotic applications. The Space Telerobotics Program, a collaboration between Ames Research Center, Johnson Space Center, Jet Propulsion Laboratory (JPL), and multiple universities, focused on developing remote-controlled robotics for three main purposes: on-orbit assembly and servicing, science payload tending, and planetary surface robotics. The overarching goal was to create robots that could be guided to build structures in space, monitor scientific experiments, and, like Sojourner, scout distant planets in advance of human explorers. While telerobotics remains a significant aspect of NASA s efforts, as evidenced by the currently operating Spirit and Opportunity Mars rovers, the Hubble Space Telescope, and many others - the Space Telerobotics Program was dissolved and redistributed within the Agency the same year as Sojourner s success. The program produced a host of remarkable technologies and surprising inspirations, including one that is changing the way people eat

Source record↗

Experimental Evaluation of a High-Performance Cold-Climate Heat Pump Using Tandem Vapor-Injection Compressors

A high-performance cold-climate heat pump (CCHP) was developed and experimentally validated through comprehensive laboratory and field testing. The system utilized two equal-size tandem vapor-injection (VI) compressors with an inter-stage flash tank to improve efficiency and capacity retention under subfreezing conditions. Laboratory testing was conducted on a 3-ton prototype in a controlled environmental chamber equipped with calibrated thermocouples, refrigerant-side mass flow and pressure transducers, and precision airflow measurement for energy balance verification. The prototype achieved heating coefficients of performance (COPs) of 4.4 at 47 °F, 3.1 at 17 °F, and 2.0 at –13 °F, while maintaining 88% of its rated heating capacity at –13°F. These results confirm strong low-temperature performance and indicate the potential for significant reductions in electric resistance backup use. A field prototype was installed and monitored in a residential building in Fairbanks, Alaska, during a heating season. Instrumentation included real-time power, temperature, and refrigerant state measurements to evaluate performance under dynamic outdoor conditions. The heat pump operated reliably down to –30 °F, delivering 75% of its rated heating capacity with a COP of 1.8, while maintaining stable operation, effective defrost control, and indoor comfort without auxiliary heating. The combined laboratory and field results demonstrate that the tandem VI compressor configuration provides a practical and energy-efficient approach for residential heat pumps designed for cold and very cold climate regions.

Hu, Yifeng [ORNL] (ORCID:0000000242875185)↗

The Additive Manufacturing Moment Measure - A Parallel Computation Technique for Determining Build Variance in the Laser Powder Bed Fusion Process

Additive manufacturing (AM) has unique process attributes that facilitate the creation of optimized, complex, and unique parts for aerospace applications. However, the multi-scale and complicated building process for AM parts can cause unexpected build conditions that result in microstructural variability within the deposited material. The need for richer datasets and computational modeling capabilities to improve AM process reliability is a consequence of this microstructural variability. A computational approach, referred to as the Additive Manufacturing Moment Measure (AM3), addresses this need by leveraging the way AM processes fuse material in precise, incremental steps. During the layering sequence, each previous step contributes to the condition of the current step at the center of the heat source. The precise steps can be selected to systematically create a time-space point field with co-located machine input and in-situ sensor data. The sequential nature of the AM process, coupled with nearest neighbor calculations, allows for a fully parallel computation for part-scale build profile analysis. The AM3 concept introduced here enables part-scale assessment directly from build files and in-situ process monitoring sensors alike. The AM moment measures were calculated for build point fields and compared with co-located in-situ and ex-situ nondestructive evaluation and optical microscopy observations. These comparisons permit a better understanding of how the sequential process actions can affect the quality of a laser powder bed fusion (LPBF) build. Details of the AM3technique will be discussed and compared to measured LPBF part characteristics. The AM3 results indicate a strong potential to advance the qualification process for aerospace applications.

Additive Manufacturing↗

Converter Compressor Building, SWMU 089, Hot Spot Areas 1, 2, and 5 Operations, Maintenance, and Monitoring Report, Kennedy Space Center, Florida

This Operations, Maintenance, and Monitoring Report (OMMR) presents the findings, observations, and results from operation of the air sparging (AS) interim measure (IM) for Hot Spot (HS) Areas 1, 2, and 5 at the Converter Compressor Building (CCB) located at Kennedy Space Center (KSC), Florida. The objective of the IM at CCB HS Areas 1, 2, and 5 is to decrease concentrations of volatile organic compounds (VOCs) in groundwater in the treatment zones via AS to levels that will enable a transition to a monitored natural attenuation (MNA) phase. This OMMR presents system operations and maintenance (O&M) information and performance monitoring results since full-scale O&M began in June 2014 (2 months after initial system startup in April 2014), including quarterly performance monitoring events in July and October 2014 and January and May 2015. Based on the results to date, the AS system is operating as designed and is meeting the performance criteria and IM objective. The performance monitoring network is adequately constructed for assessment of IM performance at CCB HS Areas 1, 2, and 5. At the March 2014 KSC Remediation Team (KSCRT) Meeting, team consensus was reached for the design prepared for expansion of the system to treat the HS 4 area, and at the November 2014 KSCRT Meeting, team consensus was reached that HS 3 was adequately delineated horizontally and vertically and for selection of AS for the remedial approach for HS 3. At the July 2015 KSCRT meeting, team consensus was reached to continue IM operations in all zones until HSs 3 and 4 is operational, once HS 3 and 4 zones are operational discontinue operations in HS 1, 2, and 5 zones where concentrations are less than GCTLs to observe whether rebounding conditions occur. Team consensus was also reached to continue quarterly performance monitoring to determine whether operational zones achieve GCTLs and to continue annual IGWM of CCB-MW0012, CCBMW0013, and CCB-MW0056, located south of the treatment area. The next performance monitoring event is scheduled for July 2015.

Converter Compressor Building↗

SERVIR Science Applications for Capacity Building

SERVIR is a regional visualization and monitoring system using Earth observations to support environmental management, climate adaptation, and disaster response in developing countries. SERVIR is jointly sponsored by NASA and the U.S. Agency for International Development (USAID). SERVIR has been instrumental in development of science applications to support the decision-making and capacity building in the developing countries with the help of SERVIR Hubs. In 2011, NASA Research Opportunities in Space and Earth Sciences (ROSES) included a call for proposals to form SERVIR Applied Sciences Team (SERVIR AST) under Applied Sciences Capacity Building Program. Eleven proposals were selected, the Principal Investigators of which comprise the core of the SERVIR AST. The expertise on the Team span several societal benefit areas including agriculture, disasters, public health and air quality, water, climate and terrestrial carbon assessments. This presentation will cover the existing SERVIR science applications, capacity building components, overview of SERVIR AST projects, and anticipated impacts.

Limaye, Ashutosh↗

Ellicott City Disasters II: Enhancing a Statistical Flood Risk Model to Continue Improving Early Warning Systems and Public Safety in Ellicott City, Maryland

As flooding events in the United States grow in frequency and intensity, the use of technological advancements and applied science are increasingly necessary for effective flood monitoring and warning systems. The NASA DEVELOP Ellicott City Disasters II project investigated the use of machine learning for applications in flood risk detection to support the improvement of early warning systems. To strengthen the efforts of the Howard County Office of Emergency Management (OEM) in building a more robust flood monitoring system, the project improved the original statistical flood risk model, FLuME (Flood Learning Model Environment), programmed by the first DEVELOP term. The enhancements incorporated an additional six years of precipitation and soil moisture data from the North American Land Data Assimilation System (NLDAS), modeled using Aqua Advanced Microwave Scanning Radiometer for EOS and Tropical Rainfall Measuring Mission (TRMM) Microwave Imager. These Earth observations were supplemented by stream gauge data from the OEM and the US Geological Survey. The resultant flood risk model FLASH (Flood Learning Environment and Severity Assessment Hub) was trained to evaluate input variables and predict stage height in Ellicott City in real time. The addition of an advanced deep learning framework known as long short-term memory improved the model’s ability to capture relationships between variables. To assess the effectiveness of the new model, FLASH produced a model efficiency metric of 0.99, a significant improvement over the 0.85 value produced by the previous model. The project assisted the OEM in pursuing the integration of open data and NASA Earth observations into a threat matrix capable of informing near real-time decision making.

Disasters↗