Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “statistical change detection”

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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Beyond the 3rd moment: a practical study of using lensing convergence CDFs for cosmology with DES Y3

ABSTRACT Widefield surveys probe clustered scalar fields – such as galaxy counts, lensing potential, etc. – which are sensitive to different cosmological and astrophysical processes. Constraining such processes depends on the statistics that summarize the field. We explore the cumulative distribution function (CDF) as a summary of the galaxy lensing convergence field. Using a suite of N-body light-cone simulations, we show the CDFs’ constraining power is modestly better than the second and third moments, as CDFs approximately capture information from all moments. We study the practical aspects of applying CDFs to data, using the Dark Energy Survey (DES Y3) data as an example, and compute the impact of different systematics on the CDFs. The contributions from the point spread function and reduced shear approximation are $\lesssim 1~{{\ \rm per\ cent}}$ of the total signal. Source clustering effects and baryon imprints contribute 1–10 per cent. Enforcing scale cuts to limit systematics-driven biases in parameter constraints degrade these constraints a noticeable amount, and this degradation is similar for the CDFs and the moments. We detect correlations between the observed convergence field and the shape noise field at 13σ. The non-Gaussian correlations in the noise field must be modelled accurately to use the CDFs, or other statistics sensitive to all moments, as a rigorous cosmology tool.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Remote Sensing of Tundra Ecosystems Using High Spectral Resolution Reflectance: Opportunities and Challenges

Abstract Observing the environment in the vast regions of Earth through remote sensing platforms provides the tools to measure ecological dynamics. The Arctic tundra biome, one of the largest inaccessible terrestrial biomes on Earth, requires remote sensing across multiple spatial and temporal scales, from towers to satellites, particularly those equipped for imaging spectroscopy (IS). We describe a rationale for using IS derived from advances in our understanding of Arctic tundra vegetation communities and their interaction with the environment. To best leverage ongoing and forthcoming IS resources, including National Aeronautics and Space Administration’s Surface Biology and Geology mission, we identify a series of opportunities and challenges based on intrinsic spectral dimensionality analysis and a review of current data and literature that illustrates the unique attributes of the Arctic tundra biome. These opportunities and challenges include thematic vegetation mapping, complicated by low‐stature plants and very fine‐scale surface composition heterogeneity; development of scalable algorithms for retrieval of canopy and leaf traits; nuanced variation in vegetation growth and composition that complicates detection of long‐term trends; and rapid phenological changes across brief growing seasons that may go undetected due to low revisit frequency or be obscured by snow cover and clouds. We recommend improvements to future field campaigns and satellite missions, advocating for research that combines multi‐scale spectroscopy, from lab studies to satellites that enable frequent and continuous long‐term monitoring, to inform statistical and biophysical approaches to model vegetation dynamics.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2019

Recent Results from the Goldstone Orbital Debris Radar: 2016-2017

Since 1993, the NASA Orbital Debris Program Office has used the Goldstone Orbital Debris Radar (Goldstone) to sample statistically the orbital debris environment. Due to the sensitivity of this radar, which can detect an approximately 3 mm-diameter conducting sphere at 1,000 km, it has filled an important role in the characterization of the sub-centimeter-sized orbital debris population. Through the years, the capabilities of this system have increased – recent updates include increased receiver bandwidth and a change in the bi-static observation geometry – both of which enhance the radar’s ability to estimate orbital parameters. In 2016, dual polarization capability was added, making this the first year where both right- and left-hand circularly polarized information was available from this sensor. This additional polarization information may enable better characterization of sub-centimeter-sized particles in low Earth orbit, particularly since the receiver triggers on reflected energy from both left- and right-handed circular polarizations independently. In this paper, we present measurements and results derived from data taken during the calendar years (CY) 2016-2017 by Goldstone and compare this dataset to measurements taken by the Haystack Ultra-wideband Satellite Imaging Radar (HUSIR) during a similar timeframe.

Murray, James↗
NASA NTRSDate not supplied

Detecting Risk and Anomalies in Airplane Dynamics Through Entropic Analysis of Time Series Data

Despite recent efforts to move away from traditional threshold exceedance detection methods for aircraft state monitoring, modern aircraft still rely on safety thresholds to communicate to pilots the identification of an anomaly in the aircraft when a threshold is surpassed. Current anomaly detection methods mainly depend on uninterpretable machine learning models to learn complex patterns and relationships contained in the time series data of aircraft. Although these methods are capable of identifying known anomalies, their deficiency in interpretability presents a challenge when translating them to different aircraft. To overcome this deficiency, entropic analysis of aircraft dynamics seeks to characterize the complexity, or lack thereof, of the aircraft dynamics prior to the development of a risk scenario. This complexity characterization provides a more straightforward summary of state changes in the dynamics of flight variables. To build a foundation for entropic analysis, we analyzed the complexity of unstable approaches, an anomalous event present in many of today’s aviation accidents. The analysis revealed a statistically significant difference in the complexity distribution of flight variables under a stable approach versus an unstable approach. These differences in complexity were especially notable minutes before an approach was identified as unstable. Moreover, the multiscale entropic analysis revealed the presence of signal complexity at multiple time scales across multiple time windows before landing. By capturing state changes and corrections in the aircraft dynamics using entropy, advanced, yet still interpretable, sensor systems based on entropic frameworks from this study can be constructed in the future using classical machine learning approaches.

Risk detection↗
NASA NTRS1977

Pulse profile and refined orbital elements for SMC X-1

Results of a reanalysis of SAS-3 data for SMC X-1, including greatly improved orbital elements, are presented. These elements, when combined with newly available data for the optical companion, Sk 160, yield improved estimates for the masses of SMC X-1 and Sk 160. A significant rate of change of intrinsic pulse period is detected during the course of the four-day observation which is consistent with the average value that was previously deduced from observations separated by 5 years. The X-ray pulse profile, averaged over one orbital cycle and with approximately 15-ms time resolution, is also presented. The pulse profile is found to be constant to within statistics, as a function of orbital phase. The implications of the small observed eccentricities of SMC X-1 and other binary X-ray pulsar systems are discussed.

Primini, F.↗
DOE OSTI2020

Detecting Thermally Induced Spinodal Decomposition with Picosecond Ultrasonics in Cast Austenitic Stainless Steels

Given the existential climate crisis faced by mankind and the world, the lifetime and sustainability of nuclear reactors as a carbon-free source of renewable energy depend on the susceptibility of their structural components to environmental degradation. In particular, critical components for light water reactors (LWRs) evolve over decades in service, losing ductility and toughness due to thermal and irradiation aging. Techniques to monitor their health cannot be easily applied in the field due to their destructive, expensive, or immobile nature. Thus, non-destructive evaluation (NDE) methods are sought to monitor and evaluate the health of major LWR components such as core barrels, steam generator tubes, or primary coolant pipes and are often required by policy, such as NRC policy #10-CFR-50.65. In this work we demonstrate the use of gigahertz, non-contact ultrasonics to gauge the state of cast austenitic stainless steels (CASS), used in some of the largest components in LWR primary systems. We do so by linking changes in their surface acoustic wave (SAW) characteristics using transient grating spectroscopy (TGS) to transmission electron microscopy (TEM)-verified evidence of spinodal decomposition and G-phase precipitation. In this thesis, thermal aging is shown to induce SAW peak splitting in spinodally decomposed CASS alloys, correlated strongly with lowered toughness and decreased ductility. Furthermore, statistical testing on the number of SAW peak splits observed show that the second SAW peak significantly appears more frequently and is significantly different in frequency in comparison to counts and frequencies measured in unaged specimens. The ability of this technique to non-destructively detect microstructural degradation at a distance in a predictive manner in the case of CASS motivates extending gigahertz ultrasonics to detect other LWR material degradation modes as an in-vessel inspection technique, such as reactor pressure vessel (RPV) embrittlement. This allows for the greater use of NDE techniques for confident monitoring of LWR structural material health to 80 years and beyond, saving costs by minimizing structural replacements until needed and maximizing energy production by preventing early decommission until necessary.

36 MATERIALS SCIENCE↗
DOE OSTI2022

An Ensemble Approach to Computationally Efficient Radiological Anomaly Detection and Isotope Identification

Radiological source search is a challenging task involving detection and identification of weak sources in a constantly changing radiological background. As of now, many radiological source detection algorithms have been proposed; however, their computational complexity, and hence reliance on power intensive processing units inhibit low-power applications of radiological source search systems. In this work, we introduce the anomaly filter (AF) algorithm; a computationally light, yet effective time-series source detection algorithm based on exponential weighted moving average (EWMA) and Poisson deviance statistics. Then, we demonstrate that the proposed algorithm can be used in ensemble with other more computationally intensive source detection and identification algorithms to achieve both increased detection performance and reduced power consumption. The proposed AF algorithm and the ensemble algorithms were thoroughly benchmarked against several existing source detection and identification algorithms. The results show that the AF algorithm outperforms existing conventional source detection algorithms, and the ensemble approach improves the overall performance of existing source detection and isotope identification algorithms. Furthermore, the AF algorithm and the Non-negative Matrix Factorization approach based source identification (NMF-ID) algorithm were combined and implemented on a singleboard microcontroller and the power consumption was measured. This ensemble algorithm reduced the power consumption of the NMF-ID algorithm almost by a factor of 100, while improving the detection performance of the overall system.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Self-diagnosis of model suitability for continuous measurements of stream-dissolved organic carbon derived from in situ UV–visible spectroscopy

Application of high-frequency monitoring of dissolved organic carbon (DOC) is difficult in instances where training datasets are challenging to develop (e.g., remote locations) and the relationship between optical features and DOC concentration changes due to environmental or landscape shifts (e.g., climate or land-use change). We developed and compared three partial least squares (PLS) models using in situ water level measurements, conductivity, and UV–Vis spectral attenuation to predict DOC. Two site-specific models were developed using data from a hillslope-dominated forest or a low-relief wetland-pond-dominated stream catchment. The third model, using data from both sites, exhibited the best performance (DOC range = 4–15.5 mg C L −1 , mean = 8.38 mg C L −1 , training RMSE = 0.34 mg C L −1 , internal validation RMSE = 0.50 mg C L −1 , external validation RMSE = 2.43 mg C L −1 ). We further demonstrate using PLS model statistics to monitor performance and elucidate when and how models should be updated. These statistics, Hotelling's T 2 and squared prediction errors, are useful consistency checks for the predictions made and detect underlying inconsistencies that, if undetected, can reduce the robustness of DOC prediction. For example, via the T 2 statistic, we identified the summer–autumn transition as a period when DOC composition differed from what was represented in the training dataset. We also determined that elevated SUVA 254 values contributed to the overall bias observed in predictions made during the subsequent year as part of the external validation. This enabled the application of a bias correction that reduced the RMSE from 2.43 to 0.89 mg C L −1 . The method presented here could be applied to future monitoring programs enabling model updates to monitor DOC fluxes accurately from optical datasets (e.g., attenuance or fluorescence) in the face of developing datasets in remote locations or environmental change. In conclusion, implementation of this approach may also identify possible regime shifts or landscape and hydrologic change associated with climate and other environmental changes relevant to terrestrial to aquatic fluxes.

UV-VIS spectroscopy↗
DOE OSTI2021

Mass Spectrometry Adduct Calculator

We describe the Mass Spectrometry Adduct Calculator (MSAC), an automated Python tool to calculate the adduct ion masses of a parent molecule. Here, adduct refers to a version of a parent molecule [M] that is charged due to addition or loss of atoms and electrons resulting in a charged ion, e.g. [M+H] + . MSAC includes a database of 2,341 potential ions and their mass-to-charge ratios (m/z) as extracted from the NIST/EPA/NIH Mass Spectral Library (NIST17), the Global Natural Products Social Molecular Networking Public Spectral Libraries (GNPS), and MassBank of North America (MoNA). The calculator relies on user-selected subsets of the combined database to calculate expected m/z for adducts of molecules supplied as formulas This tool is intended to help researchers create identification libraries to collect evidence for the presence of molecules in mass spectrometry data. While the included adduct database focuses on adducts typically detected during liquid chromatography-mass spectrometry analyses, users may supply their own lists of adducts and charge states for calculating expected m/z. We also analyzed statistics on adducts from spectra contained in the three selected mass spectral libraries. MSAC is freely available at https://github.com/pnnl/MSAC.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2017

The Resource Prospector Neutron Spectrometer System: RP's Bloodhound

The primary goal of the Resource Prospector Neutron Spectrometer System (NSS) is to locate and characterize hydrogen-bearing volatile deposits, especially subsurface ice, that may exist at the lunar poles. A key objective is to detect water-equivalent hydrogen concentrations of 0.5 wt% or greater while on a moving rover. A second objective is to determine approximate burial depth of enhanced hydrogen-bearing materials up to 1 meter below otherwise dry regolith. The instrument will be carried aboard a landed mobility system at the lunar poles. The instrument operates by measuring the changes in the leakage flux of low energy neutrons out of the regolith. These neutrons are produced by galactic cosmic rays, which are so energetic that they shatter the nuclei in surface materials. The neutrons interact with other nuclei and lose energy, becoming thermalized in the process. Hydrogen is most efficient at thermalizing neutrons owing to protons' similar mass - statistically, neutrons lose half their energy per collision with protons. With hydrogen in the soil, leakage fluxes of neutrons in the 0.5 eV to 500 keV energy range are reduced. A concentration of only1-2 wt% water-equivalent hydrogen results in a decrease in epithermal leakage flux of a factor of two. The leakage flux of thermal neutrons, from 0 to 0.5 eV in energy, can either increase or decrease depending on the hydrogen abundance and stratigraphy. As with the highly successful Lunar Prospector Neutron Spectrometer, the RP NSS detects both thermal and epithermal neutrons by using two helium-3 gas proportional counters, one covered by cadmium and the other uncovered. The former detects only epithermal neutrons with energies above approximately 0.5 eV, the latter detects both thermal (less than 0.5 eV) and epithermal energies (greater than 0.5 eV). When a neutron enters the detector tube and interacts with a helium-3 nucleus, the resulting reaction produces an energetic proton and triton that ionize the gas. The resulting electrons are accelerated toward a high-voltage anode and cascade, amplifying the net charge, which is collected at the anode. The number of electrons produced is proportional to the energy that the triton and proton deposit in the gas. A charge sensitive pre-amplifier converts the total charge to a step voltage output. A shaper amplifier then shapes this step into a uni-polar waveform with peaking time appropriate for the detection depending on the event rate. The integrated shaped waveform, representing the deposited triton/proton energy, is then measured. A histogram, or pulse height analysis, is performed to record the main capture peak and wall effect pulses. A threshold for detection is also required to limit the low amplitude counting rate such as noise floor. The system electronics consists of 2 modules - the Sensor Module (SM) front-end and the Data Processing Module (DPM) back-end circuits. SM is designed as a light-weight and low power front-end housing the two helium-3 proportional counter detectors, preamp and HVPS. It is mounted external to the rover body to detect the thermalized neutron flux with a minimum of host background. The DPM is located inside the rover; it digitizes the SM signals, performs pulse height analysis and accumulates the count rate for each spectral channel. The DPM controls high voltage and thresholding, and sends the science data to the host craft via an RS422 serial asynchronous protocol. The payload host provides all thermal management and control for the SM and DPM.

hydrogen-bearing volatile deposits↗
DOE OSTI2026

CAHS: Context-Aware Homology Search

Protein homology search is foundational to bioinformatics: it supports annotation transfer, structure/function inference, and evolutionary analysis over rapidly expanding sequence repositories (e.g., UniProtKB). Profile hidden Markov models (pHMMs), as implemented in HMMER, remain the most widely trusted approach because they provide statistically calibrated E-values; however, their gap behavior is fixed once a profile is trained, despite biological evidence that insertion/deletion tolerance varies across flexible loops and intrinsically disordered regions. We present CAHS (Context-Aware Homology Search), a lightweight query-time adapter for pHMM search that incorporates learned and biologically motivated signals without changing HMMER's downstream search pipeline or its calibrated E-value reporting. Given a query sequence, CAHS computes per-residue representations from a protein language model and a disorder predictor, maps these to profile coordinates, and modulates only match-state transition rows (gap-open and gap-extension probabilities) while preserving Plan7 constraints. We comprehensively evaluate CAHS across six structurally diverse protein families and multi-domain architectures against a 570k-sequence target corpus. CAHS expands detection capability, retrieving thousands of additional remote homologs at relaxed thresholds by maintaining alignment quality through flexible regions. For multi-domain proteins, context-aware modulation resolves 94% of fragmented alignments. Crucially, CAHS preserves hit-set invariance at stringent operating points (E<10-10), demonstrating increased statistical confidence without inflating false positives. Furthermore, sharper statistical distinction between homologs and background noise during early filter stages yields up to a 3.87× acceleration in end-to-end wall-clock time on high-performance computing clusters. Overall, CAHS illustrates a practical AI-for-science design pattern: augmenting a trusted probabilistic model with query-specific learned signals to improve interpretable, reproducible inference in data-rich biology.

Bhattaram, Swethasree [Georgia Institute of Techno↗
NASA NTRS2011

Analysis of Pulsed Airborne Lidar Measurements of Atmospheric CO2 Column Absorption from 3-13 km Altitudes

We have developed a pulsed lidar technique for measuring the tropospheric CO2 concentrations as a candidate for NASA's ASCENDS space mission [1]. It uses two pulsed laser transmitters allowing simultaneous measurement of a CO2 absorption line in the 1575 nm band, O2 extinction in the Oxygen A-band, surface height and backscatter profile. The lasers are precisely stepped in wavelength across the CO2 line and an O2 line region during the measurement. The direct detection receiver measures the energies of the laser echoes from the surface along with the range profile of scattering in the path. The column densities for the CO2 and O2 gases are estimated from the ratio of the on- and off-line signals via the integrated path differential absorption (IPDA) technique. The time of flight of the laser pulses is used to estimate the height of the scattering surface and to reject laser photons scattered in the atmosphere. We developed an airborne lidar to demonstrate an early version of the CO2 measurement from the NASA Glenn Lear-25 aircraft. The airborne lidar stepped the pulsed laser's wavelength across the selected CO2 line with 20 wavelength steps per scan. The line scan rate is 450 Hz, the laser pulse widths are 1 usec, and laser pulse energy is 24 uJ. The time resolved laser backscatter is collected by a 20 cm telescope, detected by a NIR photomultiplier and is recorded on every other reading by a photon counting system [2]. During August 2009 we made a series of 2.5 hour long flights and measured the atmospheric CO2 absorption and line shapes using the 1572.33 nm CO2 line. Measurements were made at stepped altitudes from 3-13 km over locations in the US, including the SGP ARM site in Oklahoma, central Illinois, north-eastern North Carolina, and over the Chesapeake Bay and the eastern shore of Virginia. Although the received signal energies were weaker than expected for ASCENDS, clear CO2 line shapes were observed at all altitudes, and some measurements were made through thin clouds. The Oklahoma and east coast flights were coordinated with a LaRC/ITT CO2 lidar on the LaRC UC-12 aircraft, and in-situ measurements were made using its CO2 sensor and radiosondes. We have conducted an analysis of the ranging and IPDA lidar measurements from these four flights. Most flights had 5-6 altitude steps with 200-300 seconds of recorded measurements per step. We used a cross-correlation approach to process the laser echo records. This was used to estimate the range to the scattering surface, to define the edges of the laser pulses and to determine echo pulse energy at each wavelength. We used a minimum mean square approach to fit an instrument response function and to solve for the best-fit CO2 absorption line shape. We then calculated the differential optical depth (DOD) of the fitted CO2 line. We computed its statistics at the various altitude steps, and compare them to the DODs calculated from spectroscopy based on HITRAN 2008 and the column conditions calculated from the airborne in-situ readings. The results show the lidar and in-situ measurements have very similar DOD change with altitude and greater than 10 segments per flight where the scatter in the lidar measurements are less than or equal to 1ppm. We also present the results from subsequent CO2 column absorption measurements, which were made with stronger detected signals during three flights on the NASA DC-8 over the southwestern US in during July 2010.

Abshire, James B.↗
DOE OSTI2022

Structural Characterization of a Toppling Rock Slab From Array-Based Ambient Vibration Measurements and Numerical Modal Analysis

Accurate assessments of the internal structure and boundary conditions of unstable rock slopes are imperative for evaluating landslide hazard scenarios. However, instability characterization at depth remains challenging and is often limited by costly or invasive subsurface investigations. Here, we develop a new approach coupling array-based ambient vibration modal analysis and numerical modeling to improve structural characterization of rock slope instabilities at depth. We used ambient noise cross-correlation on 4 hr of seismic data recorded by an array of 30 nodal geophones at a 500-m-long toppling rock slab in Utah, USA to identify modal frequencies between 0.8 and 3.5 Hz and derive modal displacements. We show that transverse and longitudinal bending modes span the length of the instability, indicating an interconnected slab. Further, statistical comparison of field results with outputs from >1,000 finite element models with varying boundary conditions showed that the instability depth varies between 40–70 and 10–20 m in the middle and lateral regions, respectively. Our approach yields new information on the structural conditions of rock cliff and column instabilities at depth, which is not easily obtained by other means but is imperative for change detection monitoring and improved hazard assessments.

58 GEOSCIENCES↗
NASA NTRS2000

Effects of orbital spaceflight on human osteoblastic cell physiology and gene expression

During long-term spaceflight, astronauts lose bone, in part due to a reduction in bone formation. It is not clear, however, whether the force imparted by gravity has direct effects on bone cells. To examine the response of bone forming cells to weightlessness, human fetal osteoblastic (hFOB) cells were cultured during the 17 day STS-80 space shuttle mission. Fractions of conditioned media were collected during flight and shortly after landing for analyses of glucose utilization and accumulation of type I collagen and prostaglandin E(2) (PGE(2)). Total cellular RNA was isolated from flight and ground control cultures after landing. Measurement of glucose levels in conditioned media indicated that glucose utilization occurred at a similar rate in flight and ground control cultures. Furthermore, the levels of type I collagen and PGE(2) accumulation in the flight and control conditioned media were indistinguishable. The steady-state levels of osteonectin, alkaline phosphatase, and osteocalcin messenger RNA (mRNA) were not significantly changed following spaceflight. Gene-specific reductions in mRNA levels for cytokines and skeletal growth factors were detected in the flight cultures using RNase protection assays. Steady-state mRNA levels for interleukin (IL)-1alpha and IL-6 were decreased 8 h following the flight and returned to control levels at 24 h postflight. Also, transforming growth factor (TGF)-beta(2) and TGF-beta(1) message levels were modestly reduced at 8 h and 24 h postflight, although the change was not statistically significant at 8 h. These data suggest that spaceflight did not significantly affect hFOB cell proliferation, expression of type I collagen, or PGE(2) production, further suggesting that the removal of osteoblastic cells from the context of the bone tissue results in a reduced ability to respond to weightlessness. However, spaceflight followed by return to earth significantly impacted the expression of cytokines and skeletal growth factors, which have been implicated as mediators of the bone remodeling cycle. It is not yet clear whether these latter changes were due to weightlessness or to the transient increase in loading resulting from reentry.

Non-NASA Center↗
NASA NTRS2002

Fatigue Crack and Porosity Measurement in Composite Materials by Thermographic and Ultrasonic Methods

Many nondestructive methods exist for the detection of localized material anomalies in an otherwise good composite structure. The problem arises when the material system as a whole has degraded during service or was improperly manufactured. Porosity and intra-ply microcracking are two such conditions that in unlined composite pressure vessels can be very troublesome to detect and when linked through the thickness can be critical to mission success. These leak paths may lead to loss of pressure/propellant, increased risk of explosion and possible cryo-pumping. Research sought nondestructive methods for quantifying porosity and microcracking in composite tankage. Both thermographic and resonance ultrasound methods have been utilized with artificial neural network and statistical approaches to analyze the data. Resonant ultrasound spectroscopy provides measurements, which are sensitive to fine details in the materials character, such as micro-cracking and porosity. Here, the higher frequency (shorter wavelength) components of the signal train provide more significant interaction with the defects causing the spectral characteristics to shift toward lower amplitudes at the higher frequencies. As the density of the defects increases more interactions occur and more drastic amplitude changes are observed. From a thermal perspective, the higher the defect density the lower the through thickness thermal diffusivity will be. Utilizing a point heat source, and thermographically recording the heat profile with time, diffusivity calculations can be made which in turn can be related to the relative quality of the material. Preliminary experiments to verify the measurable effect on the resonance spectrum of the ultrasonic data to detect microcracking and for porosity detection thermographically are presented. Methods involving supervised and unsupervised artificial neural networks as well as other clustering algorithms are developed for signal identification.

Walker, James L.↗
NASA NTRS1973

Identification of interplanetary tangential and rotational discontinuities.

Discontinuities in the interplanetary magnetic field detected by the Mariner 5 magnetometer have been analyzed to distinguish tangential and rotational discontinuities. The method used was based on finding the field component normal to the plane of the discontinuities that vanishes for tangential discontinuities and is nonzero for rotational discontinuities. Slightly less than one half of the 118 discontinuities analyzed could not be classified because neither the normal component nor the changes in field magnitude were statistically significant owing to errors in the field measurements and in finding the normal direction. The 44 rotational discontinuities that were finally identified did not exhibit changes in field magnitude in excess of 20%.-

Smith, E. J.↗
NASA NTRS1974

A practical obstacle detection system for the Mars Rover

Discussion of an obstacle detection system which uses a laser range finder as the principal sensing device. The laser scans the scene ahead and stores the range data for the terrain in a matrix form. This matrix can be thought of as a 'range image'. This range varies from point to point, but sharp changes are caused by the presence of obstacles. Some existing algorithms and one developed by the authors were used to obtain the outlines of obstacles from the 'range image'. All these algorithms end with a thresholding operation. A theoretical analysis shows how a proper value of the threshold may be chosen, given the type of irregularity of the terrain to be detected. The analysis also shows how large the statistics of measurement noise can be allowed without leading to false alarms.

Reed, M.↗
DOE OSTI2021

Analysis of Long-Term Quality Control Data for a 137 Cs Dosimetry Calibration Source

Strict quality assurance programs are required for many radiological applications, but these seldom exist for verifying dosimetry calibration sources. After initial characterization of a dosimetry calibration facility, quality control procedures are recommended to ensure the early detection of any changes or malfunctions. These also result in refined knowledge about average dose rate and experimental variations in dose delivery. This paper describes the implementation of a phase I quality control protocol for a 137 Cs dosimetry calibration source and includes an analysis of the resulting data collected over a 24-mo period. During this time, substantial data was collected to establish trial control limits. Air kerma rate measurements were obtained using an ion chamber and were adjusted for decay, corrected for ambient temperature, pressure and humidity, and then analyzed using quality control charts. Three variations of rational subgrouping methods were used in order to find assignable causes of error, and Nelson's Rules were followed to detect any non-random statistical variations. Measurements were subgrouped according to same-day measurements in order to detect positional errors as well as atmospheric correction errors. Additionally, measurements were subgrouped according to analogous experimental setups in order to detect failure in equipment or incorrect settings. Both were analyzed using the X-bar and R chart method. Similarly, individuals and moving ranges charts were used to carefully examine each position in order to observe any situational errors that may occur which include timing, positional, or interference errors. Each method was successful in identifying unique out-of-control data points that occurred during the phase I application of forming control limits. Furthermore, over the 24-mo period, enough data points were deemed in-control to establish reliable trial limits. Future experiments will include the phase II application of gaining more reliable measurements in order to fine-tune the limits, as well as performing a designed experiment, where variables are purposefully changed in order to test the variation of the data.

61 RADIATION PROTECTION AND DOSIMETRY↗