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

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At least 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Molecularly Imprinted Polymer Sensor Empowered by Bound States in the Continuum for Selective Trace-Detection of TGF-beta

The integration of advanced materials and photonic nanostructures can lead to enhanced biodetection capabilities, crucial in clinical scenarios and point-of-care diagnostics, where simplified strategies are essential. Herein, a molecularly imprinted polymer (MIP) photonic nanostructure is demonstrated, which selectively binding to transforming growth factor-beta (TGF-β), in which the sensing transduction is enhanced by bound states in the continuum (BICs). The MIP operating as a synthetic antibody matrix and coupled with BIC resonance, enhances the optical response to TGF-β at imprinted sites, leading to an augmented detection capability, thoroughly evaluated through spectral shift and optical lever analogue readout. The validation underscores the MIP-BIC sensor capability to detect TGF-β in spiked saliva, achieving a limit of detection of 10 fM and a resolution of 0.5 pM at physiological concentrations, with a precision of two orders of magnitude above discrimination threshold in patients. The MIP tailored selectivity is highlighted by an imprinting factor of 52, showcasing the sensor resistance to interference from other analytes. The MIP-BIC sensor architecture streamlines the detection process eliminating the need for complex sandwich immunoassays and demonstrates the potential for high-precision quantification. This positions the system as a robust tool for biomarker detection, especially in real-world diagnostic scenarios.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
NASA NTRS1995

The effect of sensor sheltering and averaging techniques on wind measurements at the Shuttle Landing Facility

This document presents results of a field study of the effect of sheltering of wind sensors by nearby foliage on the validity of wind measurements at the Space Shuttle Landing Facility (SLF). Standard measurements are made at one second intervals from 30-feet (9.1-m) towers located 500 feet (152 m) from the SLF centerline. The centerline winds are not exactly the same as those measured by the towers. A companion study, Merceret (1995), quantifies the differences as a function of statistics of the observed winds and distance between the measurements and points of interest. This work examines the effect of nearby foliage on the accuracy of the measurements made by any one sensor, and the effects of averaging on interpretation of the measurements. The field program used logarithmically spaced portable wind towers to measure wind speed and direction over a range of conditions as a function of distance from the obstructing foliage. Appropriate statistics were computed. The results suggest that accurate measurements require foliage be cut back to OFCM standards. Analysis of averaging techniques showed that there is no significant difference between vector and scalar averages. Longer averaging periods reduce measurement error but do not otherwise change the measurement in reasonably steady flow regimes. In rapidly changing conditions, shorter averaging periods may be required to capture trends.

Merceret, Francis J.↗
NASA NTRS2022

Ten Years of VIIRS On-Orbit Geolocation Calibration and Performance

The first innovative Visible Infrared Imaging Radiometer Suite (VIIRS) sensor aboard the Suomi National Polar-orbiting Partnership (SNPP) satellite has been in operation for 10 years since its launch on 28 October 2011. The second VIIRS sensor aboard the first Join Polar Satellite System (JPSS-1) satellite has been in operation for 4 years since its launch on 18 November 2017, which became NOAA-20. Well-geolocated and radiometrically calibrated Level-1 sensor data records (SDRs) from VIIRS are crucial to numerical weather prediction (NWP) and Level-2+ environmental data record (EDR) algorithms and products. The high quality of Level-2+ EDRs is a requirement for the continuity of NASA Earth science data records (ESDRs) and climate data records (CDRs), one of the two objectives of the SNPP mission and one of the three elements in the JPSS mission objective. The other objective of the SNPP mission is risk reduction for the follow-on JPSS missions. This paper summarizes the on-orbit geolocation calibration and validation (Cal/Val) activities for both VIIRS sensors onboard SNPP and NOAA-20 in the past 10 years. These activities include nominal geolocation Cal/Val activities, risk reduction activities, and improvements for the on-orbit VIIRS sensor operations. After these activities, sub-pixel geolocation accuracy is achieved. Nadir equivalent geolocation uncertainty is generally within 75 m (1-σ), or 20% imagery band pixels, in either the along-scan or along-track direction for both SNPP and NOAA-20 VIIRS sensors. The worst 16-day measured geolocation errors (radial, 3-σ) are 280 m and 267 m, respectively, in the latest SNPP and NOAA-20 VIIRS data collections, which are better than the required accuracy of 375 m (radial, 3-σ). The risk reduction activities also improved VIIRS builds for JPSS-3 and JPSS-4 satellites, and provide lessons learned for other VIIRS-like sensor builds.

VIIRS↗
NASA NTRS1980

Multispectral data acquisition and classification - Computer modeling for smart sensor design

In this paper a model of the processes involved in multispectral remote sensing and data classification is developed as a tool for designing and evaluating smart sensors. The model has both stochastic and deterministic elements and accounts for solar radiation, atmospheric radiative transfer, surface reflectance, sensor spectral reponses, and classification algorithms. Preliminary results are presented which indicate the validity and usefulness of this approach. Future capabilities of smart sensors will ultimately be limited by the accuracy with which multispectral remote sensing processes and their error sources can be computationally modeled.

Park, S. K.↗
NASA NTRSDate not supplied

Comparing Low-Cost Sensors with Ground-Based and Airborne In-Situ and Column Observations of NO2 and HCHO during the FRAPPE Field Campaign in Colorado, USA

Even in the presence of more reliable air quality tools, low-cost sensors have the benefit of recording data on highly localized spatial and temporal scales, allowing for multiple measurements within a single satellite pixel and on pixel boundaries. However, they are less accurate than their regulatory-grade counterparts, requiring regular co-locations with accepted instruments to ensure their validity. Thus, the addition of low-cost sensors to a field campaign – where reference-grade air quality instruments are abundant – not only provides ample opportunities for low-cost sensor co-location and calibration, but also allows the low-cost instruments to be used for sub-pixel validation, covering more surface area than the regulatory instruments alone with a network of sensors. During the summer of 2014, our low-cost sensor network was deployed during the Front Range Air Pollution and Photochemistry Experiment (FRAPPÉ) campaign conducted to sample the composition of air at and above ground level in northeastern Colorado, USA. The low-cost sensor platform included a suite of gas-phase sensors, notably NO2 and two generalized volatile organic compound (VOC) sensors, which were leveraged together to quantify speciated hydrocarbons such as formaldehyde. These key pollutants were chosen for their impacts on human health and climate change, as well as their inclusion on the TEMPO satellite launching this year. Airborne campaign measurements included slant column optical observations of formaldehyde (HCHO), nitrogen dioxide (NO2), and ozone (O3). Myriad additional in-situ instruments described chemical composition up to approximately 5 km above surface level. Ground-based instrumentation included both stationary and mobile regulatory-grade instruments, which were used for sensor calibration. Machine learning techniques such as artificial neural networks (ANNs) were used to match the low-cost signals to that of the reference-grade instruments. Here, we compare calibrated low-cost sensor data collected at ground level in a variety of locations along Colorado’s Front Range to various data sources from the FRAPPÉ campaign to better understand how well airborne and regulatory ground-based measurements can be extrapolated to other locations. Further, as the slant column measurements act as satellite simulators, we explore how low-cost instruments can be used for satellite validation purposes. Comparisons among these different data types also have important implications in data fusion.

Kristen Okorn↗
NASA NTRS1992

High-temperature strain measurement techniques: Current developments and challenges

Since 1987, a very substantial amount of R&D has been conducted in an attempt to develop reliable strain sensors for the measurements of structural strains during ground testing and hypersonic flight, at temperatures up to at least 2000 deg F. Much of the effort has been focused on requirements of the NASP Program. This presentation is limited to the current sensor development work and characterization studies carried out within that program. It is basically an assessment as to where we are now and what remains to be done in the way of technical accomplishments to meet the technical challenges posed by the requirements and constraints established for the NASP Program. The approach for meeting those requirements and constraints has been multi-disciplinary in nature. It was recognized early on that no one sensor could meet all these requirements and constraints, largely because of the large temperature range (cryogenic to at least 2000 deg F) and many other factors, including the most challenging requirement that the sensor system be capable of obtaining valid 'first cycle data'. Present candidate alloys for resistance-type strain gages include Fe-Cr-Al and Pd-Cr. Although they have superior properties regarding withstanding very high temperatures, they exhibit large apparent strains that must either be accounted for or cancelled out by various techniques, including the use of a dual-element, half-bridge dummy gage, or electrical compensation networks. A significant effort is being devoted to developing, refining, and evaluating the effectiveness of those techniques over a broad range in temperature and time. In the quest to obtain first-cycle data, ways must be found to eliminate the need to prestabilize or precondition the strain gage, before it is attached to the test article. It should be noted that present NASP constraints do not permit prestabilization of the sensor, in situ. Gages are currently being 'heat treated' during manufacture in both the wire- and foil-type resistance strain gages, and evaluation is in progress. In addition, the 'gage-on-shim' concept is being revisited. That concept will permit heat treatment of the gage during manufacture, before attachment on the test article. Also, it may permit the individual calibration of each gage regarding gage factor and apparent strain. Candidate alloys for the NASP include titanium metal-matrix and carbon-carbon composites. Although those materials have very attractive properties at elevated temperatures in terms of strength and weight, they pose significant attachment problems. Methods for making reliable strain gage and thermocouple attachments to them are currently under development. Experience to date indicates that Rokide attachment of the sensor directly to the protective coating is easier than to the base material itself. However, interpreting strain data from gages attached in this way may prove difficult because of possible cracks in the coating that form 'islands' and the mobility of those 'islands'. It is concluded, therefore, that major technical challenges lie ahead as we proceed to meet the stringent strain sensor requirements and constraints of the NASP Program.

Lemcoe, M. M.↗
DOE OSTI2022

Development of a Radiation-Tolerant Front End Digitizer

High-radiation and high-temperature environments represent notoriously detrimental conditions for electronics. Yet sensors and instrumentation are critically important for the safe operation of nuclear reactors and for the validity of the scientific experiments conducted within them. Traditionally, sensors in such extreme environments operate with few active components, resulting in small signals (mV–V, nA–µA range) that must be transmitted through long cable runs before digitization by sensitive data acquisition systems located in clean, less-harsh environments. Long cables are prone to picking up noise through electromagnetic interference and distortion caused by their parasitic impedances, resulting in signal degradation. The Front End Digitizer (FREND) system described and demonstrated herein seeks to address these issues by enabling the placement of a radiation-resistant analog front end within reactor containment, or other high-radiation environments. FREND will enable early signal pre-amplification, digitization, and optical encoding within the high-radiation field to transmit sensor signals over an optical fiber to the non-nuclear environment of an instrument room. Early signal pre-amplification and digitization maintain signal integrity, whereas optical transmission renders the system blind to induced electromagnetic noise over the long cable runs. This report describes the FREND initial prototype, which can multiplex and optically encode data from up to four sensor inputs, though, in principle, this can be extended to any number of sensor inputs. The end result is an extremely flexible, high-fidelity system.

42 ENGINEERING↗
NASA NTRS2016

Uncertainties in Coastal Ocean Color Products: Impacts of Spatial Sampling

With increasing demands for ocean color (OC) products with improved accuracy and well characterized, per-retrieval uncertainty budgets, it is vital to decompose overall estimated errors into their primary components. Amongst various contributing elements (e.g., instrument calibration, atmospheric correction, inversion algorithms) in the uncertainty of an OC observation, less attention has been paid to uncertainties associated with spatial sampling. In this paper, we simulate MODIS (aboard both Aqua and Terra) and VIIRS OC products using 30 m resolution OC products derived from the Operational Land Imager (OLI) aboard Landsat-8, to examine impacts of spatial sampling on both cross-sensor product intercomparisons and in-situ validations of R(sub rs) products in coastal waters. Various OLI OC products representing different productivity levels and in-water spatial features were scanned for one full orbital-repeat cycle of each ocean color satellite. While some view-angle dependent differences in simulated Aqua-MODIS and VIIRS were observed, the average uncertainties (absolute) in product intercomparisons (due to differences in spatial sampling) at regional scales are found to be 1.8%, 1.9%, 2.4%, 4.3%, 2.7%, 1.8%, and 4% for the R(sub rs)(443), R(sub rs)(482), R(sub rs)(561), R(sub rs)(655), Chla, K(sub d)(482), and b(sub bp)(655) products, respectively. It is also found that, depending on in-water spatial variability and the sensor's footprint size, the errors for an in-situ validation station in coastal areas can reach as high as +/- 18%. We conclude that a) expected biases induced by the spatial sampling in product intercomparisons are mitigated when products are averaged over at least 7 km × 7 km areas, b) VIIRS observations, with improved consistency in cross-track spatial sampling, yield more precise calibration/validation statistics than that of MODIS, and c) use of a single pixel centered on in-situ coastal stations provides an optimal sampling size for validation efforts. These findings will have implications for enhancing our understanding of uncertainties in ocean color retrievals and for planning of future ocean color missions and the associated calibration/validation exercises.

Coastal ocean color↗
DOE OSTI2017

Enhancing workload assessments for validation activities associated with DBA and BDBA scenarios - 165

After the Fukushima Daiichi accident, nuclear regulators around the world have required that power reactor licensees develop more extensive emergency mitigating responses and severe accident management provisions beyond the defense-in-depth measures for design basis accidents (DBAs), previously in place. Workload assessments represent common validation techniques that are used to demonstrate that workers are able to perform tasks without unacceptable performance degradation. High workload is known to induced stress and fatigue and may severely diminish a worker's capacity to perceive, recognize, and respond appropriately during emergency or unanticipated events, which may result in undesirable consequences. In estimating workload during emergency and severe accident scenarios, power reactor licensees tend to rely on subjective measures of workload, such as NASA-TLX. Due to reported mismatches in the literature between subjective and physiologically-derived estimates of workload, it is prudent to see what more can be done to improve the current state of practice, in the context of emergency and severe accident conditions. To improve confidence in workload estimates, it is advocated that the nuclear industry integrate physiological-based measures into current practices by making use of 'on-body' or 'wearable' physiological sensors. In this paper, an overview of three different types of empirical workload approaches is provided. The advantages of wearable physiological sensors are considered in the context of extreme environments and occupations, with tangible examples including heat stress and pupillometry. Suggestions for a consensus forum on workload are provided and a research plan directed at improving the current practice of workload estimation is offered for consideration. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS1991

NASA team algorithm for sea ice concentration retrieval from Defense Meteorological Satellite Program special sensor microwave imager - Comparison with Landsat satellite imagery

The present study describes the validation of the the NASA team algorithm for the determination of sea ice concentrations from the Defense Meteorological Satellite Program special sensor microwave imager (SSM/I). A total of 28 cloud-free Landsat scenes were selected to permit validation of the passive microwave ice concentration algorithm for a range of ice concentrations and ice types. The sensitivity of the NASA team algorithm to the selection of locally and seasonally adjusted algorithm parameters is discussed. Mean absolute differences between SSM/I and Landsat ice concentrations are within 1 percent during fall using local and global tie points (standard deviations of the difference are +/-3.1 and +/-6.2 percent, respectively). In areas with greater amounts of nilas and young ice, the NASA team algorithm was found to underestimate ice concentrations by as much as 9 percent. It is inferred that the standard deviation between SSM/I and Landsat ice concentrations decreases from +/-7 to +/-5 percent with local tie points compared to the global ones for spring and fall.

Steffen, Konrad↗
DOE OSTI2016

Design and development of a probe-based multiplexed multi-species absorption spectroscopy sensor for characterizing transient gas-parameter distributions in the intake systems of I.C. engines

We designed and developed a 4-probe multiplexed multi-species absorption spectroscopy sensor system for gas property measurements on the intake side of commercial multi-cylinder internal-combustion (I.C.) engines; the resulting cycle- and cylinder-resolved concentration, temperature and pressure measurements are applicable for assessing spatial and temporal variations in the recirculated exhaust gas (EGR) distribution at various locations along the intake gas path, which in turn is relevant to assessing cylinder charge uniformity, control strategies, and CFD models. Furthermore, the diagnostic is based on absorption spectroscopy and includes an H 2 O absorption system (utilizing a 1.39 m distributed feedback (DFB) diode laser) for measuring gas temperature, pressure, and H 2 O concentration, and a CO 2 absorption system (utilizing a 2.7 m DFB laser) for measuring CO 2 concentration. The various lasers, optical components and detectors were housed in an instrument box, and the 1.39- m and 2.7- m lasers were guided to and from the engine-mounted probes via optical fibers and hollow waveguides, respectively. The 5kHz measurement bandwidth allows for near-crank angle resolved measurements, with a resolution of 1.2 crank angle degrees at 1000 RPM. Our use of compact stainless steel measurement probes enables simultaneous multi-point measurements at various locations on the engine with minimal changes to the base engine hardware; in addition to resolving large-scale spatial variations via simultaneous multi-probe measurements, local spatial gradients can be resolved by translating individual probes. Along with details of various sensor design features and performance, we also demonstrate validation of the spectral parameters of the associated CO 2 absorption transitions using both a multi-pass heated cell and the sensor probes.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRS2013

Multi-sensor Cloud Retrieval Simulator and Remote Sensing from Model Parameters : Synthetic Sensor Radiance Formulation - Pt. 1

In this paper we describe a general procedure for calculating synthetic sensor radiances from variable output from a global atmospheric forecast model. In order to take proper account of the discrepancies between model resolution and sensor footprint, the algorithm takes explicit account of the model subgrid variability, in particular its description of the probability density function of total water (vapor and cloud condensate.) The simulated sensor radiances are then substituted into an operational remote sensing algorithm processing chain to produce a variety of remote sensing products that would normally be produced from actual sensor output. This output can then be used for a wide variety of purposes such as model parameter verification, remote sensing algorithm validation, testing of new retrieval methods and future sensor studies.We show a specific implementation using the GEOS-5 model, the MODIS instrument and the MODIS Adaptive Processing System (MODAPS) Data Collection 5.1 operational remote sensing cloud algorithm processing chain (including the cloud mask, cloud top properties and cloud optical and microphysical properties products). We focus on clouds because they are very important to model development and improvement.

Simulations↗
NASA NTRS2013

Equivalent Sensor Radiance Generation and Remote Sensing from Model Parameters: Equivalent Sensor Radiance Formulation - Part 1

In this paper we describe a general procedure for calculating equivalent sensor radiances from variables output from a global atmospheric forecast model. In order to take proper account of the discrepancies between model resolution and sensor footprint the algorithm takes explicit account of the model subgrid variability, in particular its description of the probably density function of total water (vapor and cloud condensate.) The equivalent sensor radiances are then substituted into an operational remote sensing algorithm processing chain to produce a variety of remote sensing products that would normally be produced from actual sensor output. This output can then be used for a wide variety of purposes such as model parameter verification, remote sensing algorithm validation, testing of new retrieval methods and future sensor studies. We show a specific implementation using the GEOS-5 model, the MODIS instrument and the MODIS Adaptive Processing System (MODAPS) Data Collection 5.1 operational remote sensing cloud algorithm processing chain (including the cloud mask, cloud top properties and cloud optical and microphysical properties products.) We focus on clouds and cloud/aerosol interactions, because they are very important to model development and improvement.

Simulations↗
NASA NTRSDate not supplied

GOES-T Goddard Magnetometer Sensor Unit Flight Thermal Predictions and On-Orbit Thermal Performance

The GOES-T Goddard Magnetometer (GMAG) sensor unit (SU) thermal design was validated by SU level thermal balance (TB) testing. The correlated SU thermal model was integrated to the observatory thermal model to predict the outboard SU temperatures and operating heater duty cycles in the worst cold case and worst hot case orbits. An orbit with the highest solar beta angle (23.5°) and an orbit with the lowest solar beta angle (0°) were run for each case. A comparison in the SU temperature predictions and heater duty cycles were made. The Autumnal Equinox (AE) cold case orbit is slightly colder than the Winter Solstice (WS) cold case orbit. The WS hot case orbit is slightly warmer than the March Equinox (VE) hot case orbit. Additionally, the lunar eclipse cold case orbit was run. It is the coldest environment. Using a 23°C set point for the SU cover heater controller, there is positive heater control for all the orbits. The heater duty cycle predictions for the AE worst cold case orbit and WS worst hot case orbit were 44.4% and 33% respectively. During the lunar eclipse, the heater cycle increases to 68.8% at the end of the eclipse. The temperature predictions for the bobbins are in the 21.9°C to 22.8°C range in the AE worst cold case orbit and in the 21.8°C to 23.0°C range in the WS worst hot case orbit. The SU temperatures during nominal operation on orbit were expected to be within the design goal, despite seasonal variations in solar beta angle and solar irradiance, and no solar flux in a lunar eclipse. The maximum operating SU cover flight heater duty cycle was expected to comply with GOLD Rule 4.25. The SU thermal design is now flight proven based on its long-term (>1 year) thermal performance on orbit.

GOES-T↗
NASA NTRS2011

Effects of Data Quality on the Characterization of Aerosol Properties from Multiple Sensors

Cross-comparison of aerosol properties between ground-based and spaceborne measurements is an important validation technique that helps to investigate the uncertainties of aerosol products acquired using spaceborne sensors. However, it has been shown that even minor differences in the cross-characterization procedure may significantly impact the results of such validation. Of particular consideration is the quality assurance I quality control (QA/QC) information - an auxiliary data indicating a "confidence" level (e.g., Bad, Fair, Good, Excellent, etc.) conferred by the retrieval algorithms on the produced data. Depending on the treatment of available QA/QC information, a cross-characterization procedure has the potential of filtering out invalid data points, such as uncertain or erroneous retrievals, which tend to reduce the credibility of such comparisons. However, under certain circumstances, even high QA/QC values may not fully guarantee the quality of the data. For example, retrievals in proximity of a cloud might be particularly perplexing for an aerosol retrieval algorithm, resulting in an invalid data that, nonetheless, could be assigned a high QA/QC confidence. In this presentation, we will study the effects of several QA/QC parameters on cross-characterization of aerosol properties between the data acquired by multiple spaceborne sensors. We will utilize the Multi-sensor Aerosol Products Sampling System (MAPSS) that provides a consistent platform for multi-sensor comparison, including collocation with measurements acquired by the ground-based Aerosol Robotic Network (AERONET), The multi-sensor spaceborne data analyzed include those acquired by the Terra-MODIS, Aqua-MODIS, Terra-MISR, Aura-OMI, Parasol-POLDER, and CalipsoCALIOP satellite instruments.

Petrenko, Maksym↗
NASA NTRSDate not supplied

Uninhabited Aerial System Drop-in Balloon-Borne Radiosonde Alternative for Lower Tropospheric Flights

Balloon-borne radiosonde sensors are a well characterized way of gathering data into the stratosphere; however, balloon launches have limitations such as the need to replace the balloon and sensors after each flight, as well the overall drift of the balloon over the course of the launch. Using sensors mounted on an uninhabited aerial system (UAS) allows for higher temporal-resolution vertical profiles in the lower troposphere and allows for full control of the flight profile of the sensors. This paper presents a drop-in solution for a balloon-borne radiosonde in which it is mounted on an uninhabited aerial system in lieu of a balloon with an additional connection to a 3D anemometer streaming atmospheric and wind data in near real-time to a ground station. This alternative platform for balloon-borne radiosondes has undergone extensive flight testing with the wind results being compared against a ground-based wind LiDAR for validation and the atmospheric results undergoing further data analysis against a wide variety of sensors for future validation. Indoor tests were also conducted and are discussed in order to determine the propeller’s influence on the anemometer. This alternative platform will allow for higher temporal and spatial resolution of atmospheric data collection in near-real time.

Tyler L. Willhite↗
DOE OSTI2019

Acoustic emission Bayesian source location: Onset time challenge

Robust identification of the most accurate observed input data among a pool of observations is key in modeling and decision making. A statistically biased observed measurement deteriorates the predictive power of a model and affects decision-making ability based on the prediction of the model. When two competing methods of measurement are available, such as methods which identify arrival times in acoustic emission (AE) signals, a principal question is whether one of the two obtained datasets, or a combination of the two, should be used later on, for example, to localize an AE source. This question becomes more important when collecting not repeatable data such as AE signals created by a propagating crack. Here this paper considers an inverse source location problem in a concrete block to address the mentioned issue, a proposed methodology which also has wider application in competitive data selection. Elastic energy released by an AE event, such as a propagating crack, is recorded by acoustic emission data acquisition system. The onset time of AE signals is often used to locate the source of the event, and its accuracy directly affects the precision of source identification. This research proposes an innovative approach to select the most probable onset time obtained from two automatic picker methods. The proposed method selects the most probable onset times, which are observed by each picker for each sensor, in a probabilistic fashion. To validate the proposed method, the most accurate onset time observed by each picker is identified by visual inspection and is compared with the one is selected by the proposed method. Finally, the dataset is used for source location identification. Results show that picked onset times determined by the proposed method generate more accurate source identification when compared with coordinates obtained using each dataset individually.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Datasets of a Multizone Office Building under Different HVAC System Operation Scenarios

Abstract This study provides an open-source dataset of the measured weather data, building indoor data, and system data under the different test settings. The test building is the two-story Flexible Research Platform building at the US Department of Energy’s Oak Ridge National Laboratory, in Oak Ridge, Tennessee. Four heating tests and three cooling tests were conducted. The 1-min interval of weather, building indoor data, and system data from each test setting are provided. Actual weather data were collected from a weather station installed on the roof. This paper describes information on the test building and installed sensors, data collection method, and data validation. The provided dataset can be employed to understand HVAC system conditions and building indoor conditions under different HVAC system operations and the performance of building envelope without HVAC system operation using free-floating test data. Additionally, it can be used for empirical validation of the building energy modelling engine.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗