A Michelson interferometer for detecting grating table rotation
Michelson interferometer to detect grating table rotation in infrared spectrometer
Cole, W. L.↗
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Automatic recognition system for document digitization in nuclear power plants
With the increasing number of data-driven models in nuclear applications, large volumes of numerical data are required to accurately model and predict the health status of a plant component. However, many historical operation logs that contain useful information are not fully utilized due to the lack of a systematic approach of digitization. To overcome this issue, this study proposes an automatic pipeline for extracting information from handwritten tabular documents collected from nuclear power plants. In our pipeline, we first denoise scanned documents with morphological operations, and then extract relevant parts from individual pages using both traditional computer vision and neural network methods. Handwriting recognition is applied to obtain text and numbers. As the most challenging step is how to crop only relevant information, the main focus of our paper is to detect tables and cells from scanned handwritten documents. Here we evaluate the efficiency and accuracy of our proposed method on handwritten operational reports obtained from a real-world case study. The results demonstrate the high accuracy and practicality of our proposed method.
21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
Common Column Identification for Table Similarity Detection in Electrified Transportation Data Lakes
Electrified transportation often requires researchers and operators to interact with datasets from a wide range of sources and disciplines, such as transportation, power systems, public health, policies, and regulations. These datasets vary in quality and format, making it difficult to understand, preprocess, and identify key columns representing real-world entities or values for indexing and joining, which can negatively impact downstream analysis and operation. Existing solutions are limited, requiring extensive manual customization or data expertise to utilize. In this article, we propose a multi-layered approach to automatically identify key columns to expedite preprocessing and aid in analysis of electrified transportation data. Our method leverages a dynamic ontology to identify common fields and an information theory-based strategy for edge cases that are difficult to generalize. Evaluations on a number of datasets from data.gov and kaggle.com show improved performance of our methods over several baseline techniques, and our ablation analyses illustrate the efficacy of individual components of our method. Our case studies also demonstrate that our methods have the potential to improve analysis of electrified transportation data and aid in automatic integration of such datasets.
33 ADVANCED PROPULSION SYSTEMS↗
The feasibility of thermal inertia mapping for detection of perched water tables in semi-arid irrigated lands
The thermal inertia mapping remote sensing technique is evaluated as a potential method for delineating areas of shallow perched water tables and related salinization problems on a regional basis. This method for detecting shallow water tables is based on the existence of significant differences in soil thermal properties between wet and dry soil profiles. Ground observations were conducted at two different test sites in California along the flight line, with one site located in a perched water table area and the other site in a well drained area. Measurements were taken hourly during a four day period (two days before and two days after the flight) for variables such as radiometric, meteorologic, soil moisture and temperature profiles, and surface characteristics. Results indicate that it is not feasible using present apparent thermal inertia remote sensing techniques to reliably delineate regional patterns of very shallow water tables due to the complex environmental system. However, some features within specific fields which may be directly related to the local presence of shallow water tables, such as differences in evaporative cooling due to soil moisture effects between and within fields, can be detected using the thermal inertia technique.
Ezra, C. E.↗
Tables of square-law signal detection statistics for Hann spectra with 50 percent overlap
The Search for Extraterrestrial Intelligence, currently being planned by NASA, will require that an enormous amount of data be analyzed in real time by special purpose hardware. It is expected that overlapped Hann data windows will play an important role in this analysis. In order to understand the statistical implication of this approach, it has been necessary to compute detection statistics for overlapped Hann spectra. Tables of signal detection statistics are given for false alarm rates from 10(exp -14) to 10(exp -1) and signal detection probabilities from 0.50 to 0.99; the number of computed spectra ranges from 4 to 2000.
Deans, Stanley R.↗
Development of an X-ray surface analyzer for planetary exploration
An ultraminiature X-ray fluorescence spectrometer was developed which can obtain data on element composition not provided by present spacecraft instrumentation. The apparatus employs two radioisotope sources (Fe-55 and Cd-109) which irradiate adjacent areas on a soil sample. Fluorescent X-rays emitted by the sample are detected by four thin-window proportional counters. Using pulse-height discrimination, the energy spectra are determined. Virtually all elements above sodium in the periodic table are detected if present at sufficient levels. Minimum detection limits range from 30 ppm to several percent, depending upon the element and the matrix. For most elements, they are below 0.5 percent. Accuracies likewise depend upon the matrix, but are generally better than plus or minus 0.5 percent for all elements of atomic number greater than 14. Elements below sodium are also detected, but as a single group.
Clark, B. C.↗
Ultraminiature X-ray fluorescence spectrometer for in-situ geochemical analysis on Mars.
A spectrometer based upon the X-ray fluorescence method of elemental analysis has been developed in an ultraminiature, rugged form suitable for a spacecraft mission to Mars. The instrument employs two radioisotope sources (Fe-55 and Cd-109) which irradiate adjacent areas on a regolith sample. Fluorescent X rays emitted by the sample are detected by four thin-window proportional counters. Using pulse-height discrimination, the energy spectra are determined. Virtually all elements above sodium in the periodic table are detected if present at sufficient levels. Minimum detection limits range from 30 ppm to 2% depending upon the element and the matrix. For most elements, they are below 0.5%. Accuracies also depend upon the matrix, but are generally better than plus or minus 0.5% for all elements of atomic number greater than 14. Elements below sodium are also detected, but as a single group. Ambiguities of identification of the elements producing the observed spectra are minimal.
Clark, B. C.↗
HCMM energy budget data as a model input for assessing regions of high potential groundwater pollution
The author has identified the following significant results. Evidence of a heat sink produced by perched water tables was detected with HCMM night thermal data. The region of shallow water was not visible on HCMM visible or day IR imagery. The results are consistant with previous aircraft investigations.
Moore, D. G.↗
A comparison of machine learning methods to classify radioactive elements using prompt-gamma-ray neutron activation data
The detection of illicit radiological materials is critical to establishing a robust second line of defence in nuclear security. Neutron-capture prompt-gamma activation analysis (PGAA) can be used to detect multiple radioactive materials across the entire Periodic Table. However, long detection times and a high rate of false positives pose a significant hindrance in the deployment of PGAA-based systems to identify the presence of illicit substances in nuclear forensics. In the present work, six different machine-learning algorithms were developed to classify radioactive elements based on the PGAA energy spectra. The model performance was evaluated using standard classification metrics and trend curves with an emphasis on comparing the effectiveness of algorithms that are best suited for classifying imbalanced datasets. We analyse the classification performance based on Precision, Recall, F1-score, Specificity, Confusion matrix, ROC-AUC curves, and Geometric Mean Score (GMS) measures. The tree-based algorithms (Decision Trees, Random Forest and AdaBoost) have consistently outperformed Support Vector Machine and K-Nearest Neighbours. Based on the results presented, AdaBoost is the preferred classifier to analyse data containing PGAA spectral information due to the high recall and minimal false negatives reported in the minority class.
97 MATHEMATICS AND COMPUTING↗
Positioning and Microvibration Control by Electromagnets of an Air Spring Vibration Isolation System
Active positioning and microvibration control has been attempted by electromagnets equipped in a bellows-type, air-spring vibration isolation system. Performance tests have been carried out to study the effects. The main components of the system's isolation table were four electromagnetic actuators and controllers. The vibration isolation table was also equipped with six acceleration sensors for detecting microvibration of the table. The electromagnetic actuators were equipped with bellows-type air springs for passive support of the weight of the item placed on the table, with electromagnets for active positioning, as well as for microvibration control, and relative displacement sensors. The controller constituted a relative feedback system for positioning control and an absolute feedback system for vibration isolation control. In the performance test, a 1,490 kg load (net weight of 1,820 kg) was placed on the vibration isolation table, and both the positioning and microvibration control were carried out electromagnetically. Test results revealed that the vibration transmission was reduced by 95%.
Watanabe, Katsuhide↗
Air Monitoring for Hazardous Gas Detection
The Hazardous Gas Detection Lab (HGDL) at Kennedy Space Center is involved in the design and development of instrumentation that can detect and quantify various hazardous gases. Traditionally these systems are designed for leak detection of the cryogenic gases used for the propulsion of the Shuttle and other vehicles. Mass spectrometers are the basis of these systems, which provide excellent quantitation, sensitivity, selectivity, response times and detection limits. A Table lists common gases monitored for aerospace applications. The first five gases, hydrogen, helium, nitrogen, oxygen, and argon are historically the focus of the HGDL.
Arkin, C. Richard↗
The Effect of Temperature on the Preservation of Volatile-Rich Lunar Samples
Introduction. The Moon’s south pole is a high-priority target for human exploration and scientific study. This interest is, in part, due to the presence of Permanently Shadowed Regions (PSRs), which could contain high concentrations of unique volatiles at cryogenic temperatures [1]. Returned samples from PSRs may include a unique combination of rocks, regolith, and volatile species, providing unprecedented insights into the history of the Solar System and the potential for resource utilization on the Moon. However, because PSR samples are cryogenic up-on collection, lunar polar sample return will eventually require cold stowage for the journey from the Moon to Earth. Without cold stowage, PSR sample return will likely result in phase changes and chemical reactions within the volatile component of the sample, which would negatively impact the resulting scientific studies of those samples. This abstract summarizes the initial results from an ongoing characterization of analog PSR samples at a range of temperatures, with the goal of defining the temperatures needed for a flight cold stowage freezer. Background. Based on remote sensing observations of the Moon [2], south polar PSRs range in temperature from ~120K for small and/or shallow PSRs to ~20K at the most extreme locations in large, deep PSRs. A range of volatiles have been hypothesized to exist at the surface or subsurface of the lunar poles [3-5 and others]. This hypothesis was verified when the LCROSS mission impacted the <50-K PSR in the crater Cabeus, detecting a range of volatiles from water to low condensation temperature species such as H2S and methane [6]. Species such as H2S and ammonia (also detected by LCROSS) are also highly reactive, and increase the likelihood of chemical reactions at elevated (non-cryogenic) temperatures. At the Johnson Space Center’s Planetary Exploration and Astromaterials Research Laboratory (JSC-PEARL), we have developed a volatile-bearing lunar simulant that incorporates several of the species detected by LCROSS [Table 1] mixed cryogenically with the USGS Lunar Highlands Type (LHT) regolith simulant. The new volatile-regolith simulant will be used to assess the degree of sample alteration at room temperature, -20°C, -80°C, and -196°C (liquid nitro-gen), over a two-week period. Room temperature samples represent those likely to be returned during initial missions without cold stowage, -20°C provides an analog to Apollo cold curated samples, -80°C is the temperature of multiple flight payload freezers (e.g., MELFI), and -196°C is analogous to lunar PSRs. Two weeks is an approximation of the time between sample collection and Earth return for initial Artemis missions. Over this period of time, sample head-space gases will be analyzed using a Universal Gas Analyzer (UGA, a type of mass spectrometer) coupled with a Baratron pressure sensor. After testing, the regolith component of the simulant will be purged of volatiles and preserved for future electron beam and/or FTIR analysis. Experimental Procedure. Volatile-regolith simulants will be produced as an initial homogenous batch; this batch will then be distributed into aliquots (gas chromatography/GC vials or cryo vials), ensuring that each sample has the same starting composition and conditions [Fig. 1]. In addition to the “full” simulant shown in Table 1, less complex simulant compositions will be used as baseline and control samples [Table 2]. Aliquots will be produced in triplicate for each simulant composition, storage temperature, and date of sampling. Headspace gases in all Day 0 samples will be analyzed by the UGA immediately. Cold storage samples for future analytical days will be placed in freezers appropriate to their target temperatures (-20°C, -80°C, -196°C). For ambient-temperature samples, regolith and regolith-water samples will be stored in a fume hood, while the full simulant will be stored in a sealed Parr vessel for safety; no other simulants (RWCM/ RWCM+) will be stored at ambient temperature for this test. Samples will be analyzed by UGA in this manner on each Analysis Day outlined in Table 2. Analytical Data. The UGA measures the partial pressures in a single sample aliquot over a set mass range of 0-105 atomic mass units (AMU) [Figure 2]; this set range was selected to slightly exceed the mass of the highest-mass expected reaction product (H2SO4). The Baratron complements the UGA by measuring the total pressure in the headspace of a sample vial. Coupled together, the quantitative abundances of gases will be monitored throughout the test. UGA analyses of the triplicate samples for each storage temperature, day, and simulant composition will be averaged, and standard deviations for each will be calculated. The compositions of starting species (shown in Table 1) will be characterized as a function of time, and the presence of any new compounds (reaction products) will be monitored as well. Total pressures will be recorded for each sample analysis, and any samples that show signs of leakage (e.g., a significant reduction in pressure or simulant volatiles) will be discarded. Anticipated Results. Testing is planned to begin in January 2022. The resulting data will allow compositional and phase changes in the volatile component of the simulants to be determined. Both the reduction in initial compounds and the addition of reaction products are expected to be observed. In addition, the relative efficacy of the different temperatures at pre-serving the initial composition of the simulants will be quantified. Finally, the regolith component of each sample will be argon-purged and stored in a controlled environment for future laboratory analysis. Compositional and morphological changes in the regolith are expected for samples above 0°C. This test will be repeated three times over the course of 2022. Understanding the effect of temperature on both the volatile and regolith components of analog lunar materials will allow requirements for a cold stowage freezer to be developed. The implementation of cold stowage for lunar polar missions will maximize the preservation of returned samples, enabling ground-breaking lunar and Solar System volatiles science for decades to come.
J L Mitchell↗
Network for the Detection of Stratospheric Change (NDSC) FTIR Intercomparison at Table Mountain Facility, November 1996
An intercomparison of four Fourier Transform Infrared (FTIR) spectrometers, operated side by side by JPL, NCAR, and NPL groups, using two different spectral fitting algorithms, was conducted at JPL's Table Mountain Facility (TMF) during November 1996.
infrared atomic composition↗
Relative-Motion Sensors and Actuators for Two Optical Tables
Optoelectronic sensors and magnetic actuators have been developed as parts of a system for controlling the relative position and attitude of two massive optical tables that float on separate standard air suspensions that attenuate ground vibrations. In the specific application for which these sensors and actuators were developed, one of the optical tables holds an optical system that mimics distant stars, while the other optical table holds a test article that simulates a spaceborne stellar interferometer that would be used to observe the stars. The control system is designed to suppress relative motion of the tables or, on demand, to impose controlled relative motion between the tables. The control system includes a sensor system that detects relative motion of the tables in six independent degrees of freedom and a drive system that can apply force to the star-simulator table in the six degrees of freedom. The sensor system includes (1) a set of laser heterodyne gauges and (2) a set of four diode lasers on the star-simulator table, each aimed at one of four quadrant photodiodes at nominal corresponding positions on the test-article table. The heterodyne gauges are used to measure relative displacements along the x axis.
Gursel, Yekta↗
Predicted star counts in selected fields and photometric bands Applications to galactic structure, the disk luminosity function, and the detection of a massive halo
Tables are presented of predicted star counts in 17 selected directions on the sky as a function of apparent B, V, R, and I magnitudes and absolute visual magnitudes calculated from the Bahcall-Soneira Galaxy model. It is noted that eight of the fields were selected ab initio for their usefulness in determining from star counts either parameters of galactic structure, the faint end of the disk luminosity function, or the detection of a massive stellar halo. Star counts in specified fields to m sub I = 19 mag are able to reveal the faint end of the disk luminosity function down to the end of the hydrogen-burning main sequence. It is thought that star counts at high galactic latitudes to m sub I = 22 mag should reveal the stellar constituents of a massive halo if they are massive enough to be on the hydrogen-burning main sequence.
Bahcall, J. N.↗
EQ_phase_detection
The EQ_phase_detection software is designed to scan continuous daily waveforms to detect earthquake phase arrivals from local to regional (150 km) events. The detections are made with a deep learning encoder-decoder model. When the model detects an earthquake in the waveforms, a second model is implemented to classify the first arriving motions. Both deep learning models are trained with the Tensorflow package using publicly available benchmark data sets. The software input is a path to a directory that contains waveforms in mseed format and the associated response files in xml format. The output is a data table of time stamped detections, signal amplitude, signal-to-noise ratio, and softmax probability of the detection in a generic format applicable to post-processing association algorithms for event locations. Additionally, the p-wave and s-wave waveforms are saved in a data table for rapid access when producing improved locations using correlation-based techniques. The software is designed for multiprocessing with multiple GPU’s for rapid processing of large data sets. The configuration file provides flexibility in the trained models implemented and allows access to multiple models trained for different sampling rates or input dimensions. This is particularly useful for regions with multiple networks that do not have the same data parameters.
Johnson, Christopher↗
Product Consistency Test and Vapor Hydration Test Comparisons of a Radioactive Hanford Waste Glass with its Non-Radioactive Simulant Glass
Product Consistency Tests (PCT) and Vapor Hydration Tests (VHT) were performed on a radioactive glass made from Hanford tank AP-107 waste (i.e., R-AP-107) and its non-radioactive equivalent glass made from simulated tank waste (i.e., S-AP-107). The radioactive and non-radioactive experiments were conducted in parallel with identical equipment, protocols, and staff to remove additional experimental uncertainties. PCT and VHT results are reported for all samples and are shown in Table S.1. Average normalized mass loss of B ( NL B ) and Na ( NL Na ) calculated from the three replicate test results for each glass with their respective standard deviations (SD) are presented for PCT results while individual VHT rates ( r VHT ) with their propagated errors ( σ r prop ) from individual thickness measurements on each sample are presented for the VHT results. Some VHT samples experienced more than 50% evaporation loss during the experiments. However, no visible alteration was detected on any VHT samples regardless on the amount of evaporation loss detected as shown in Table S.1.
12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
Two-sample discrimination of Poisson means
This paper presents a statistical test for detecting significant differences between two random count accumulations. The null hypothesis is that the two samples share a common random arrival process with a mean count proportional to each sample's exposure. The model represents the partition of N total events into two counts, A and B, as a sequence of N independent Bernoulli trials whose partition fraction, f, is determined by the ratio of the exposures of A and B. The detection of a significant difference is claimed when the background (null) hypothesis is rejected, which occurs when the observed sample falls in a critical region of (A, B) space. The critical region depends on f and the desired significance level, alpha. The model correctly takes into account the fluctuations in both the signals and the background data, including the important case of small numbers of counts in the signal, the background, or both. The significance can be exactly determined from the cumulative binomial distribution, which in turn can be inverted to determine the critical A(B) or B(A) contour. This paper gives efficient implementations of these tests, based on lookup tables. Applications include the detection of clustering of astronomical objects, the detection of faint emission or absorption lines in photon-limited spectroscopy, the detection of faint emitters or absorbers in photon-limited imaging, and dosimetry.
Lampton, M.↗