Search NASA⌕ Search

SEARCH · Search NASA

Results for “sensor data analytics”

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.

618 records · Page 35

Precursor reaction pathway leading to BiFeO 3 formation: insights from text-mining and chemical reaction network analyses

BiFeO 3 (BFO) is a next-generation non-toxic multiferroic material with applications in sensors, memory devices, and spintronics, where its crystallinity and crystal structure directly influence its functional properties. Designing sol–gel syntheses that result in phase-pure BFO remains a challenge due to the complex interactions between metal complexes in the precursor solution. Here, we combine text-mined data and chemical reaction network (CRN) analysis to obtain novel insight into BFO sol–gel precursor chemistry. We perform text-mining analysis of 340 synthesis recipes with the emphasis on phase-pure BFO and identify trends in the use of precursor materials, including that nitrates are the preferred metal salts, 2-methoxyethanol (2 ME) is the dominant solvent, and adding citric acid as a chelating agent frequently leads to phase-pure BFO. Our CRN analysis reveals that the thermodynamically favored reaction mechanism between bismuth nitrate and 2ME interaction involves partial solvation followed by dimerization, contradicting assumptions in previous literature. We suggest that further oligomerization, facilitated by nitrite ion bridging, is critical for achieving the pure BFO phase.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

WISP: Watching grid Infrastructure Stealthily through Proxies (Final Technical Report)

The complex interdependencies of cyber systems (sensors and communications), physical grids and associated electricity market operations make protecting electric power grids a significant challenge. The energy sector is constantly under new, targeted, advanced and dangerous cyber-attacks that have the potential to result in the loss of human life. These threats are further exacerbated by our need to modernize the grid. One focus of cyber security research in smart grids is the securing of the SCADA system through advanced intrusion detection systems (IDS) and bad data detection algorithms in state estimation. These methods either require full knowledge of the system topology and parameters or fail to understand the physical behaviors under attack. WISP (Watching grid Infrastructure Stealthily through Proxies) is designed to provide additional protection to the power grid using only publicly available data. In particular, WISP exploits the spatio-temporal nature of the real time locational marginal prices (LMPs), in conjunction with other information such as bids, weather, outages and load data to analyze anomalous power pricing behaviors and then correlate those observations to localize regions of interest and identify potential cyber events. WISP is non-intrusive as the tool is deployed as a service in the Cloud or on premise and provides reliable information to system operators for enhanced situational awareness, without impeding energy delivery functions. The WISP technology comprises three modules: the data-driven anomaly detection core, the vulnerability and risk analysis and the root cause analysis. The data-driven anomaly detection core performs the tasks of feature selection, anomaly detection and attack region localization. The vulnerability and risk analysis module provides system level information of the vulnerable variables and times, assisting the operators in selecting monitoring and protection nodes. The root cause analysis module takes the detection results and identifies potential operational conditions that contribute to the detected anomalies. In Phase I, we have demonstrated the feasibility and effectiveness of WISP. We developed a realistic electricity market simulator capable of generating normal and attack market data under various operational conditions. We developed a series of cyber-attack detection and analysis algorithms and evaluated them under multiple data sources. Finally, we integrated all modules into an end-to-end software, providing functions for data management, data analytics and visualization. Specifically, we have achieved: (i) real-time data acceptance from external utility interfaces with >99% acceptance rate; (ii) high performance anomaly detection algorithms with >98% detection accuracy and <0.1% false alarm rate; and (iii) ultra-low computing delay <50 milliseconds. Additionally, our team developed algorithms to identify the vulnerable variables in electricity market operations and root cause analysis functions to identify major contributors to the price spikes. These ancillary modules are necessary when deploying WISP in real world industry environment. In Phase II, we have demonstrated the effectiveness of WISP software on realistic largescale power systems. We performed red team testing for the Phase I WISP software and identified software vulnerabilities and implemented corresponding mitigation solutions. We adapted the electricity market simulator for the Texas synthetic 2000-bus system and generated datasets for the false data injection attacks. We created database and visualization interfaces for the Texas system and the ISO New England system. We performed software optimization in terms of operation efficiency, computing speed and detection accuracy. Finally, we tested the software on the Texas system and the ISO New England system and evaluated the detection performance. Overall, we achieved above 89% detection rate, below 3% false alarm rate and below 37 seconds of end-to-end detection delay.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Compressive Classification for TEM-EELS

Acquiring atomic-resolution images of beam sensitive materials or under dynamic conditions (e.g. operando STEM) is very difficult and requires precise dose fractioning to minimize the dose delivered to the sample and acquire the data more rapidly than dynamics present. Typical methods of low-dose STEM imaging include adjusting the beam current, dwell-time, and probe Scanning transmission electron microscopy (STEM) is used routinely to obtain atomic-resolution images of a small selection of radiation tolerant materials under stable conditions.size. All three of these determine the dose over a spatial area in STEM. Recently, compressive sensing [1] has been applied to electron microscopy. The computational imaging method of inpainting [2] has been proposed as a method to reduce dose and increase acquisition speed for STEM. Inpainting is a technique to recover missing pixels in an image. By skipping pixels (randomly) during acquisition, a fourth dose-control mechanism is realized [3]. A few implementations of randomly-subsampled STEM exist (e.g., [4]). To make the concepts of compressive sensing accessible to the microscopy community we begin with an example using atomic resolution images of a GaAs crystal (see Figure 1). Because the crystal is periodic it has a sparse representation in reciprocal space. In fact, a sparse representation is a key component of compressive sensing. If an image is sub-sampled randomly we find that the Fourier transform remains sparse, but becomes increasing noisy as less and less data is acquired. Yet, by finding the peaks in the reciprocal image and removing the noise it is possible to recover atomic resolution images with only 1% of the pixels. Figure 1 shows the reconstruction process for GaAs sub-sampled at 50%, 10%, 5%, and 1%. Periodic images form a special class for which the optimal sampling approach (according to CS theory) is a random selection of pixels. For non-periodic images, such as those arising in in-situ STEM, methods such as dictionary learning are necessary [2,5]. The data can be compressed in time for TEM [5] or pixels can be skipped randomly for STEM. There are several issues that arise in developing a random scan for STEM [4] and a coded aperture for TEM. The remainder of the talk will address these issues. References: [1] E Candes and M Wakin. Signal Processing Magazine, IEEE. 2(25) (2008), pp. 21. [2] A Stevens, Pu Y, Sun Y, et al. Artificial Intelligence & Statistics (AISTATS), 2017. [3] A Stevens, H Yang, L Carin et al. Microscopy 63(1), (2014), pp. 41. [4] L Kovarik, A Stevens, A Liyu et al. Appl. Phys. Lett. 109, 164102 (2016). [5] A Stevens, L Kovarik, P Abellan et al. Adv. Structural and Chemical Imaging 1(10), (2015), pp. 1. [6] Supported by the Chemical Imaging, Signature Discovery, and Analytics in Motion Initiatives at PNNL. PNNL is operated by Battelle Memorial Inst. for the US DOE; contract DE-AC05-76RL01830.

Hao, Weituo↗

Description of the Electronic Structure of Oxyhemoglobin Using Fe L-Edge X-ray Absorption Spectroscopy

The electronic structure of oxyhemoglobin has been controversial since the discovery of the compound’s diamagnetism in 1936. Here, this study uses partial fluorescence yield Fe L-edge X-ray absorption spectroscopy (XAS) in the 3s→2p fluorescence on oxyhemoglobin solutions, measured using a transition-edge sensor detector, to obtain a quantitative experimental description of the electronic structure of the O 2 -bound iron site. The spectrum is very different from typical low-spin Fe II and Fe III heme spectra, and multiplet simulations indicate a mixed ground configuration with ∼57% low-spin Fe III and ∼43% low-spin Fe II character. This is also very different from the Fe II character found for the picket-fence porphyrin model complex. The oxyhemoglobin L-edge XAS data further show that the O 2 ligand engages in a weak σ- but strong π-bond with the iron ion, leading to the overall strong Fe–O 2 bond required for O 2 transport.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Forward Skirt Structural Testing on the Space Launch System (SLS) Program

Structural testing was performed to evaluate heritage forward skirts from the Space Shuttle program for use on the Space Launch System (SLS) program. One forward skirt is located in each solid rocket booster. Heritage forward skirts are aluminum 2219 welded structures. Loads are applied at the forward skirt thrust post and ball assembly. Testing was needed because SLS ascent loads are roughly 40% higher than Space Shuttle loads. Testing objectives were to determine margins of safety, demonstrate reliability, and validate analytical models. Two forward skirts were structurally tested using the test configuration. The test stand applied loads to the thrust post. Four hydraulic actuators were used to apply axial load and two hydraulic actuators were used to apply radial and tangential loads. The first test was referred to as FSTA-1 (Forward Skirt Structural Test Article) and was performed in April/May 2014. The purpose of FSTA-1 was to verify the ultimate capability of the forward skirt subjected to ascent ultimate loads. Testing consisted of two liftoff load cases taken to 100% limit load followed by an ascent load case taken to 110% limit load. The forward skirt was unloaded to no load after each test case. Lastly, the forward skirt was tested to 140% limit and then to failure using the ascent loads. The second test was referred to as FSTA-2 and performed in July/August of 2014. The purpose of FSTA-2 was to verify the ultimate capability of the forward skirt subjected to liftoff ultimate loads. Testing consisted of six liftoff load cases taken to 100% limit load followed by the six liftoff cases taken to 140% limit load. Two ascent load cases were then tested to 100% limit load. The forward skirt was unloaded to no load after each test case. Lastly, the forward skirt was tested to 140% limit and then to failure using the ascent loads. The forward skirts on FSTA-1 and FSTA-2 successfully carried all applied liftoff and ascent load cases. Both FSTA-1 and FSTA-2 were tested to failure by increasing the ascent loads. Failure occurred in the forward skirt thrust post radius. The forward skirts on FSTA-1 and FSTA-2 had nearly identical failure modes. FSTA-1 failed at 1.72 times limit load and FSTA-2 failed at 1.62 times limit load. This difference is primarily attributed to variation in material properties in the thrust post region. Test data were obtained from strain gages, deflection gages, ARAMIS digital strain measurement, acoustic emissions, and high-speed video. Strain gage data and ARAMIS strain were compared to finite element (FE) analysis predictions. Both the forward skirt and tooling were modeled. This allows the analysis to simulate the loading as close as possible to actual test configuration. FSTA-1 and FSTA-2 were instrumented with over 200 strain gages to ensure all possible failure modes could be captured. However, it turned out that three gages provided critical strain data. One was located in the post bore and two on the post radius. More gages were not specified due to space limitations and the desire to not interfere with the use of the ARAMIS system on the post radius. Measured strains were compared to analysis results for the load cycle to failure. Note that FSTA-1 gages were lost before failure was reached. FSTA-2 gages made it to the failure load but one of the radius gages was lost before testing began. This gage was not replaced because of the time and cost associated with disassembly of the test structure. Correlation to analysis was excellent for FSTA-1. FSTA-2 was not quite as good because there was more residual strain from previous load cycles. FSTA-2 was loaded and unloaded with 12 liftoff cases and two ascent cases before taking the skirt to failure. FSTA-1 only had two liftoff cases and one ascent case before taking the skirt to failure. The ARAMIS system was used to determine strain at the post radius by processing digital images of a speckled paint pattern. Digital cameras recorded images of the speckled paint pattern. ARAMIS strain results for FSTA-2 just prior to failure. Note a high strain location develops near the left side. This high strain compares well to analysis prediction for both FSTA-1 and FSTA-2. The strain at this location was also plotted versus limit load. Both FSTA-1 and FSTA-2 had excellent correlation between ARAMIS and analysis strains. Acoustic emission (AE) sensors were used to monitor for damage formation that may occur during testing (e.g., crack formation and growth or propagation). AE was very important because after disassembly of FSTA-1, a crack was observed in the ball fitting radius. The ball fitting did not crack on FSTA-2. AE data was used to reconstruct when the crack occurred. The AE energy versus time plot for FSTA. The energy increased considerably at 850 seconds (152% limit load), indicating a crack could have formed at this point. The only visual evidence found that could have corresponded to this was the crack that initiated in the ball fitting. The cracks in the forward skirt aluminum structures would likely have been lower energy due to a lower modulus and all that were found after failure correlated to occurring after the initial crack in the post radius. This was verified by high-speed cameras used to record the failure.

Lohrer, J. D.↗

Tonopah Test Range Air Monitoring: CY2018 Meteorological, Radiological, and Wind Transported Particulate Observations

In 1963, the U.S. Department of Energy (DOE) (formerly the Atomic Energy Commission [AEC]), implemented Operation Roller Coaster on the Tonopah Test Range (TTR) and an adjacent area of the Nevada Test and Training Range (NTTR) (formerly the Nellis Air Force Range). This operation resulted in radionuclide-contaminated soils at the Double Tracks site and Clean Slate I, II, and III sites. This report documents observations made during ongoing monitoring of radiological, meteorological, and dust conditions at stations installed adjacent to the Clean Slate sites and at the TTR Sandia National Laboratories (SNL) Range Operations Center (ROC). The primary objective of the monitoring effort is to support the DOE Environmental Management Nevada Program (EM NV) in the safe remediation of the environmental legacy of nuclear device development and testing by determining if wind blowing across the Clean Slate sites is transporting particles of radionuclide-contaminated soil beyond the physical and administrative boundaries of the sites, and to provide information for designing long-term monitoring of the sites. The monitoring program in 2018 included five stations. Station 400, located within TTR Area 3 and near the ROC, monitors conditions near the local workforce center. Stations 401 and 403 are located on the northern and southeastern perimeter fence lines, respectively, of the Clean Slate III site. Stations 404 and 405 are along the northern and eastern boundary fence, respectively, at Clean Slate II. The stations are generally downwind of the contaminated areas during either northwesterly or southerly winds, which are the predominant wind directions. The stations—which are similar in design to the Community Environmental Monitoring Program (CEMP) stations operating at locations surrounding the Nevada National Security Site and TTR—include meteorological instruments and continuous-flow, low-volume air samplers. Three pressurized ionization chambers for measuring gamma energy are in use at Stations 400, 401, and 403. Saltation sensors and saltation traps are deployed at the stations adjacent to the Clean Slate sites. Detailed meteorological data are recorded on data loggers, with periodic uploads via a satellite system to the Western Regional Climate Center (WRCC) at Desert Research Institute (DRI), to monitor instrument and site conditions. Air filter samples are collected every two weeks and the deposits in the saltation traps are collected when a sufficient sample mass for analysis has accumulated (generally a six- to eight-month interval). Monitoring at TTR in calendar year (CY) 2018 provided surveillance of both ambient conditions, and ground disturbance associated with remediation activities at Clean Slate II and III. The first half of CY2018 data from Stations 404 and 405 at Clean Slate II were collected during remediation activities at that site, and data collected during the final third of the year at Stations 401 and 403 at Clean Slate III coincided with remediation work at the site. Ambient conditions prevailed at Station 400 throughout the year. Dust transport by suspension and saltation is strongly dependent on wind speed. Concentrations of PM 10 (particulate matter of aerodynamic diameter ≤10 micrometers [μm], a size fraction of small particles that are suspended in the air and can be easily inhaled) remain low until winds exceed approximately 32 kilometers per hour (km/hr) (20 miles per hour [mph]). Saltation particle counts also increase above the same general threshold wind speed. Wind speeds in excess of 32 km/hr (20 mph) occur less than three percent of the time at the sites. Ground disturbing remediation activities were carried out at Clean Slate II from October 31, 2017, until July 26, 2018. Station 404 is located closest to the remediation area and is downwind of the area when winds are from the south. By late November, analysis of dust from the air sampler at Station 404 registered increases in plutonium-239+240 ( 239+240 Pu) concentrations. Peak plutonium concentrations, accompanied by elevated gross alpha concentrations and the detection of americium-241 ( 241 Am) by gamma spectroscopy, occurred between March and May 2018. During spring and early summer of 2018, elevated radionuclide concentrations were also measured in dust collected from the air sampler at Station 405, which is more than twice the distance from the remediation activity as Station 404. A minor but sustained increase in gross alpha concentration of suspended dust collected at Stations 400, 401, and 403 was also observed starting in May 2018 and continuing into August. Stations 401 and 403 are approximately 4.8 to 6.4 km (three to four miles) from Clean Slate II and Station 400 is approximately 13 km (eight miles) from that site. The radionuclide content of material that saltated into the passive Big Spring Number Eight (BSNE) traps during the Clean Slate II remediation period increased in both the traps facing toward and away from the fenced contamination area at Station 404, with the largest increases in concentration (almost five times the previous 239+240 Pu concentration) observed in the traps facing the fenced area. The radionuclide concentration in material in the trap facing away from the fence more than doubled from that measured in 2017. A similar increase was observed for the saltation trap facing away from the fenced area at Station 405, although no increase was observed for material captured in the trap facing the fenced area. Particles ranging in size from 50 to 500 µm generally move by saltation processes and are not expected to significantly contribute to dose for someone breathing in the standard respiratory zone for adult humans (1.5 to 1.7 m [4.9 to 5.6 ft] above ground level) because they are too large to be entrained in the air as suspended dust. Remediation activities at Clean Slate III began on September 5, 2018, and continued until a brief hiatus started on December 20, 2018. Although Station 401 is much closer to the remediation area than Station 403, the first increase in gross alpha and 239+240 Pu concentrations was noted in dust from filters collected at Station 403 in early November 2018. The highest radionuclide concentrations of 2018 at the Clean Slate III stations were recorded in air samples taken from Stations 401 and 403 in late December 2018 and these concentrations were comparable between the two station locations. Gamma rate data measured by the PICs was slightly higher than the annual average at Stations 401 and 403 after remediation activities began, but no single measurement was outside of the range observed in 2018 prior to remediation activities. No increase in radionuclide concentration was observed for the Clean Slate III remediation time period on air filters collected from the other stations. Radiological monitoring at Station 400—which is located at the ROC, and therefore the closest regularly staffed work location to the Clean Slate sites—recorded a higher mean gross alpha activity from dust collected on air sampler filters than in previous years. The individual biweekly air filters yielded measurements of gross alpha that were at or below the mean plus one standard deviation measured in CY2017, except for the period from April 25, 2018, through September 12, 2018. Nonetheless, gamma spectroscopy of all air filters from Station 400 identified only naturally occurring radionuclides, with no detection of americium-241 ( 241 Am) (which is used as an indicator of plutonium-241[ 241 Pu]). Alpha spectroscopy of selected air filters collected at Station 400 did not detect plutonium-238 ( 238 Pu) or 239+240 Pu above the analytical detection limit. Gross beta and gamma exposure rate data were comparable to data from regional CEMP stations. No saltation traps are deployed at Station 400. Considering the ambient monitoring periods during CY2018, the monitoring stations adjacent to the Clean Slate sites recorded above-background 238 Pu and 239+240 Pu concentrations (SNL, 1998; Turner et al., 2003) in samples collected by passive saltation traps and on selected air filters. These observations were consistent with previous years and indicated that radionuclide movement occurred under ambient conditions by processes of both saltation and suspension. The presence of radionuclides in all saltation traps, both upwind and downwind of the fenced contamination areas, was consistent with previous radiological survey results (EG&G, 1979) that show lower concentration radiologically contaminated material dispersed outside the fenced area. Although 239+240 Pu concentrations in the air filter samples were sometimes orders of magnitude higher than background, the concentrations were below risk-based action levels defined for an industrial area worker scenario (U.S. DOE, 2014). The interception of airborne dust with above-background radionuclide concentrations demonstrates that dispersal processes are continuing. Strong winds are the driver for both suspension and saltation of dust and soil. The recorded wind speed and PM10 during remediation activities at Clean Slate II and III identified discrete wind events lasting approximately five to eight hours each, which accounted for the greatest PM 10 concentrations at the monitoring stations. These events captured the effect of winds from the northwest and from the south. The observed differences in dust loading and radionuclide concentrations for the monitoring stations when they were either upwind or downwind of the contamination area identify the remediation area as a source of plutonium contaminated dust. The increase in concentration of radionuclides in airborne dust during the remediation activities, compared with measurements under previous ambient conditions (mean 239+240 Pu concentrations during remediation activities are approximately nine to 40 times higher compared to pre-remediation concentrations, depending on monitoring station), highlights the impact of land disturbance on wind-borne contaminant transport from the Clean Slate test areas. The meteorological and particulate matter monitoring indicated that conditions for wind-borne contaminant movement exist at the Clean Slate sites, and that transport of radionuclide-contaminated soil by both suspension and saltation occurred under ambient conditions and accelerated when the sites were disturbed. The 239+240 Pu alpha spectroscopy results indicated that airborne concentrations during remediation activities ranged from 2 × 10-16 to 380 × 10-16 µCi/ml. These results can be compared to the derived air concentration limit for 239 Pu of 6 × 10-11 µCi/ml for occupational workers contained in Code of Federal Regulations 10 CFR 835, Occupational Radiation Protection. Even though the air sampling results document an increase in concentration during remediation activities, the observed concentrations are less than 0.06 percent of the occupational limit. The Corrective Action Unit (CAU) closure strategy uses a risk-based approach, whereby acceptable contaminant concentrations are determined as a function of anticipated human exposure.

54 ENVIRONMENTAL SCIENCES↗