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DOE OSTI2025

The Impact of Cultural Values and Organizational Processes on Nuclear Security Operations

Human performance is a pivotal factor in the design, testing, maintenance, and operation of security systems. The effectiveness of these systems relies not only on the capabilities, limitations, motives, and attitudes of the individuals involved, but also on the quality of training, instructional content, and evaluation methods provided. To uphold security standards, seamless integration between technologies and operators necessitates reliable human input. In security operations, human errors, often attributed to blame, sanctions, low motivation, individual accountability, or complacency, are primary causes of system failures. Complacency, characterized by a false sense of security, reflects a lack of awareness of potential threats and is a significant contributing factor to lapses in security. Security incidents arise from various factors, many extend beyond individual control, highlighting the need for a holistic approach to human performance that integrates organizational processes and team collaboration. Historically, errors have been attributed to individual moral or cognitive failures. However, insights from Operational Experiences (OEs) suggest that organizational processes weakness and deficiencies in nuclear cultural values contribute more significantly to security failures than individual mistakes. This paper consolidates lessons learned from diverse international nuclear security cultures and aims to highlight the importance of security culture in shaping global perspectives on nuclear security. It underscores the role of cultural values in shaping nuclear security practices and enhancing the resilience of security systems in the nuclear sector.

Zineddin, Dr. Z. [ORNL] (ORCID:0009000848740725)↗

NASA NTRS1983

The Snowmelt-Runoff Model (SRM) user's manual

A manual to provide a means by which a user may apply the snowmelt runoff model (SRM) unaided is presented. Model structure, conditions of application, and data requirements, including remote sensing, are described. Guidance is given for determining various model variables and parameters. Possible sources of error are discussed and conversion of snowmelt runoff model (SRM) from the simulation mode to the operational forecasting mode is explained. A computer program is presented for running SRM is easily adaptable to most systems used by water resources agencies.

Martinec, J.↗

NASA NTRS1991

System dynamic simulation of precision segmented reflector

A joint effort was undertaken on a Precision Segmented Reflector (PSR) Project. The missions in which the PSR is to be used will use large (up to 20 m in diameter) telescopes. The essential requirement for the telescopes is that the reflector surface of the primary mirror must be made extremely precise to allow no more than a few microns of errors and, additionally, this high surface precision must be maintained when the telescope is subjected to on-orbital mechanical and thermal disturbances. Based on the mass, size, and stability considerations, reflector surface formed by segmented, probably actively or passively controlled, composite panels are regarded as most suitable for future space based astronomical telescope applications. In addition to the design and fabrication of composite panels with a surface error of less than 3 microns RMS, PSR also develops related reflector structures, materials, control, and sensing technologies. As part of the planning effort for PSR Technology Demonstration, a system model which couples the reflector, consisting of panels, support truss and actuators, and the optical bench was assembled for dynamic simulations. Random vibration analyses using seismic data obtained from actual measurements at the test site designated for PSR Technology Demonstration are described.

Shih, Choon-Foo↗

NASA NTRS1990

Robust, angstrom level circularity profilometry

A noncontacting approach is presented which involves measuring the local circumferential curvature of the test piece by simultaneously measuring its circumferential slope at two slightly displaced locations. A pair of sensing beams is scanned along the circumference, and a profile of curvature is built, from which the circularity profile is deduced. The sensing of curvature makes the approach insensitive to all types of vibration and drift and runout errors in the relative rotation. The special qualities of the approach are summarized which make it well suited to measuring cylindrical optics and enable it to accommodate radii as small as twenty millimeters.

Glenn, Paul↗

NASA NTRS1992

Comet nongravitational forces and meteoritic impacts

We have considered those comets whose original orbits have been determined to be hyperbolic when only planetary perturbations are accounted for. It is found that formally unbound incident trajectories correlate most confidently with orbits that have small perihelion distances and move in a retrograde sense relative to planetary motion. Arguments are presented that these results are not due to measurement error or to selection effects. We conclude that the phenomenon is attributable to enhanced volatility leading to abnormally large nongravitational forces. Since the effect is absent in the prograde small-perihelia population, increased insolation is not the sole explanation. It is suggested that the significance of the retrograde correlation is connected with a larger energy of relative motion between retrograde comets and a population of prograde ecliptic meteoroids which impact the comet mantle exposing the underlying volatiles. The subsequent enhanced outgassing is the cause of the larger nongravitational forces.

Matese, John J.↗

NASA NTRS1997

Statistical Modeling of Landscape Pattern and the Effects of Coarse Spatial Resolution

Analysis of classified satellite imagery was conducted to characterize errors in estimates of area based on coarse resolution satellite imagery which are due to distortions in sizes of small fragments, and to explore the feasibility of correcting for these errors using a statistical modeling approach. Sizes of bodies of open water on European Remote-Sensing (ERS-1) synthetic aperture radar (SAR) and fire scars on Landsat Multispectral Scanner (MSS) imagery were measured using geographic information system (GIS) software. Statistical analysis of the smaller scars and ponds as observed with this imagery of relatively fine resolution demonstrated that the distribution of the sizes could be modeled by either of two types of statistical distributions-a power distribution related to fractal processes or a simple exponential distribution. A comparison of the size distribution of small burn scars as observed with Landsat with the distribution observed with the much coarser Advanced Very High Resolution Radiometer (AVHRR) imagery revealed effects of coarse resolution, each of which were associated with a particular size range, and whose net effect accounted for the bias in total burn area due to coarse spatial resolution. Size dependent area correction procedures are therefore feasible. A statistical modeling approach to area estimation, based models of the underlying and observed size distributions of fragments in the scene, may lead to a procedure which requires little or no ancillary data.

Hlavka, C. A.↗

NASA NTRS2016

High Resolution Image Reconstruction from Projection of Low Resolution Images DIffering in Subpixel Shifts

In this paper, we demonstrate a simple algorithm that projects low resolution (LR) images differing in subpixel shifts on a high resolution (HR) also called super resolution (SR) grid. The algorithm is very effective in accuracy as well as time efficiency. A number of spatial interpolation techniques using nearest neighbor, inverse-distance weighted averages, Radial Basis Functions (RBF) etc. used in projection yield comparable results. For best accuracy of reconstructing SR image by a factor of two requires four LR images differing in four independent subpixel shifts. The algorithm has two steps: i) registration of low resolution images and (ii) shifting the low resolution images to align with reference image and projecting them on high resolution grid based on the shifts of each low resolution image using different interpolation techniques. Experiments are conducted by simulating low resolution images by subpixel shifts and subsampling of original high resolution image and the reconstructing the high resolution images from the simulated low resolution images. The results of accuracy of reconstruction are compared by using mean squared error measure between original high resolution image and reconstructed image. The algorithm was tested on remote sensing images and found to outperform previously proposed techniques such as Iterative Back Projection algorithm (IBP), Maximum Likelihood (ML), and Maximum a posterior (MAP) algorithms. The algorithm is robust and is not overly sensitive to the registration inaccuracies.

0↗

NASA NTRS2012

Active Mirror Predictive and Requirements Verification Software (AMP-ReVS)

This software is designed to predict large active mirror performance at various stages in the fabrication lifecycle of the mirror. It was developed for 1-meter class powered mirrors for astronomical purposes, but is extensible to other geometries. The package accepts finite element model (FEM) inputs and laboratory measured data for large optical-quality mirrors with active figure control. It computes phenomenological contributions to the surface figure error using several built-in optimization techniques. These phenomena include stresses induced in the mirror by the manufacturing process and the support structure, the test procedure, high spatial frequency errors introduced by the polishing process, and other process-dependent deleterious effects due to light-weighting of the mirror. Then, depending on the maturity of the mirror, it either predicts the best surface figure error that the mirror will attain, or it verifies that the requirements for the error sources have been met once the best surface figure error has been measured. The unique feature of this software is that it ties together physical phenomenology with wavefront sensing and control techniques and various optimization methods including convex optimization, Kalman filtering, and quadratic programming to both generate predictive models and to do requirements verification. This software combines three distinct disciplines: wavefront control, predictive models based on FEM, and requirements verification using measured data in a robust, reusable code that is applicable to any large optics for ground and space telescopes. The software also includes state-of-the-art wavefront control algorithms that allow closed-loop performance to be computed. It allows for quantitative trade studies to be performed for optical systems engineering, including computing the best surface figure error under various testing and operating conditions. After the mirror manufacturing process and testing have been completed, the software package can be used to verify that the underlying requirements have been met.

Basinger, Scott A.↗

NASA NTRS2022

Defining Pupil Knowledge Requirements for Roman Space Telescope Integrated Payload Assembly Testing

This thesis examines the use of phase retrieval to characterize an optical system under testing conditions with pupil knowledge error. The purpose of this research is to define pupil knowledge requirements for the integrated payload testing of the Roman Space Telescope (RST). I have conducted a Monte Carlo study to determine how uncertainty in the location of the ground support equipment relative to the payload will affect the ability to use image-based wavefront sensing during the test to characterize system alignment. This test will be conducted in the Space Environment Simulator (SES) with the presence of Wavefront Error (WFE) due to gravity sag on the primary mirror. In this study, I incrementally decentered a piece of ground support equipment, the SubAperture Metrology System (SAMS), and evaluated how the phase retrieval algorithm attempted to fit the wavefront with the pupil mismatch. The results of this study are a factor in the overall Integrated Payload Assembly (IPA) testing WFE budget.

Roman Space Telescope↗

NASA NTRSDate not supplied

Challenges in Remote-Sensing of Hail: Examining the Performance and Biases of Satellite Hail Retrievals Using Aqua MODIS Visible/IR and AMSR-E Passive-Microwave Observations

Hail poses threats to myriad aspects of human life and society, infrastructure, and agriculture. Scientifically, hail can often cause large errors in precipitation retrieval and estimation, posing challenges to establishing the current climatology of severe storms and their future trend in a changing Earth system. Fortunately, hailstorms exhibit distinct signatures in spaceborne remote-sensing datasets (e.g. overshooting cloud tops in visible/IR, or brightness temperature depressions in passive-microwave imagery). Approaches that leverage these signatures, however, are not without their pitfalls,: passive-microwave channels have large footprints and exhibit non-uniform beam filling. Visible/IR instruments have fine horizontal resolution but are limited by their insensitivity to processes occurring below cloud top. Large horizontal areas of smaller scatterers may also meaningfully lower the brightness temperatures, especially if they are able to occupy large portions of the footprint. Radiative transfer simulations show that low frequencies such as 19- and 37-GHz can be scattered to extremely low brightness temperatures by high concentrations of smaller (graupel-sized) ice scatterers, especially in larger features that are more likely to occupy the footprint, which may cause climatologies to overestimate the frequency severe hail. To address this, we investigate the nearly simultaneous and colocated MODIS (visible/IR) and AMSR-E (passive-microwave) onboard the Aqua satellite to leverage both datasets together, pairing AMSR-E and MODIS signatures of severe convection with ground-based weather radar, severe weather reports, and environmental parameters defined by the MERRA-2 reanalysis over CONUS, and then explore the performance and challenges of the algorithm when we expand outside the United States into six different geographical regimes throughout the Aqua domain.

Sarah D Bang↗

NASA NTRS2002

Passive and Active Microwave Remote Sensing of Precipitation and Latent Heating Distributions in the Tropics from TRMM

Passive and active microwave remote sensing data are analyzed to identify signatures of precipitation and vertical motion in tropical convection. A database of cloud/radiative model simulations is used to quantify surface rain rates and latent heating profiles that are consistent with these signatures. At satellite footprint-scale (approximately 10 km), rain rate and latent heating estimates are subject to significant random errors, but by averaging the estimates in space and time, random errors are substantially reduced, Bias errors have been minimized by improving the microphysics in the supporting cloud/radiative model simulations, and by imposing a consistent definition of remotely-sensed and model-simulated convective/stratiform rain coverage. Remotely-sensed precipitation and latent heating distributions in the tropics are derived from Tropical Rainfall Measuring Mission (TRMM) and Special Sensor Microwave/ Imager (SSM/ I) sensor data. The prototype Version 6 TRMM passive microwave algorithm typically yields average heating profiles with maxima between 6 and 7 km altitude for organized mesoscale convective systems. Retrieved heating profiles for individual convective systems are compared to coincident estimates based upon a combination of dual-Doppler radar and rawinsonde data. Also, large-scale latent heating distributions are compared to estimates derived from a simpler technique that utilizes observations of surface rain rate and stratiform rain proportion to infer vertical heating structure. Results of these tests will be presented at the conference.

Olson, William S.↗

NASA NTRS1993

An end-to-end pointing budget approach to planetary observing systems with application to EOS

Previously published error budgets have focused on spacecraft error sources for pointing error and have tended to include only spacecraft pointing rather than the ultimate geolocation of each pixel of dam onto a well-defined spot on the surface of the Earth. A systematic approach to geolocation error budgeting, including all contributors in the geolocation process is presented. Its structure allows simultaneous expression of the needs of instrument teams as well as spacecraft design teams. It allows explicit acknowledgement of approximations made for on-board control as well as the ultimate geolocation accuracy achievable after ground processing and exploits the commonality inherent in the on-board and post-processing error budgets. It also includes the uncontrolled and unmeasured spacecraft jitter. This approach can be used to investigate the mission-wide benefit of a variety of design choices, (such as on-board sensing and ground correction of measurements contrasted with on-board correction of measurements). Additionally, in light of increasing accuracy requirements as sensor resolution improves, numerous non-spacecraft contributors to geolocation error are quantified.

Throckmorton, A.↗

NASA NTRS2003

Stray-Light Correction of the Marine Optical Buoy

In ocean-color remote sensing, approximately 90% of the flux at the sensor originates from atmospheric scattering, with the water-leaving radiance contributing the remaining 10% of the total flux. Consequently, errors in the measured top-of-the atmosphere radiance are magnified a factor of 10 in the determination of water-leaving radiance. Proper characterization of the atmosphere is thus a critical part of the analysis of ocean-color remote sensing data. It has always been necessary to calibrate the ocean-color satellite sensor vicariously, using in situ, ground-based results, independent of the status of the pre-flight radiometric calibration or the utility of on-board calibration strategies. Because the atmosphere contributes significantly to the measured flux at the instrument sensor, both the instrument and the atmospheric correction algorithm are simultaneously calibrated vicariously. The Marine Optical Buoy (MOBY), deployed in support of the Earth Observing System (EOS) since 1996, serves as the primary calibration station for a variety of ocean-color satellite instruments, including the Sea-viewing Wide Field-of-view Sensor (SeaWiFS), the Moderate Resolution Imaging Spectroradiometer (MODIS), the Japanese Ocean Color Temperature Scanner (OCTS) , and the French Polarization and Directionality of the Earth's Reflectances (POLDER). MOBY is located off the coast of Lanai, Hawaii. The site was selected to simplify the application of the atmospheric correction algorithms. Vicarious calibration using MOBY data allows for a thorough comparison and merger of ocean-color data from these multiple sensors.

Brown, Steven W.↗

NASA NTRS2015

Lidar Observations of Atmospheric CO2 Column During 2014 Summer Flight Campaigns

Advanced knowledge in atmospheric CO2 is critical in reducing large uncertainties in predictions of the Earth' future climate. Thus, Active Sensing of CO2 Emissions over Nights, Days, and Seasons (ASCENDS) from space was recommended by the U.S. National Research Council to NASA. As part of the preparation for the ASCENDS mission, NASA Langley Research Center (LaRC) and Exelis, Inc. have been collaborating in development and demonstration of the Intensity-Modulated Continuous-Wave (IM-CW) lidar approach for measuring atmospheric CO2 column from space. Airborne laser absorption lidars such as the Multi-Functional Fiber Laser Lidar (MFLL) and ASCENDS CarbonHawk Experiment Simulator (ACES) operating in the 1.57 micron CO2 absorption band have been developed and tested to obtain precise atmospheric CO2 column measurements using integrated path differential absorption technique and to evaluate the potential of the space ASCENDS mission. This presentation reports the results of our lidar atmospheric CO2 column measurements from 2014 summer flight campaign. Analysis shows that for the 27 Aug OCO-2 under flight over northern California forest regions, significant variations of CO2 column approximately 2 ppm) in the lower troposphere have been observed, which may be a challenge for space measurements owing to complicated topographic condition, heterogeneity of surface reflection and difference in vegetation evapotranspiration. Compared to the observed 2011 summer CO2 drawdown (about 8 ppm) over mid-west, 2014 summer drawdown in the same region measured was much weak (approximately 3 ppm). The observed drawdown difference could be the results of the changes in both meteorological states and the phases of growing seasons. Individual lidar CO2 column measurements of 0.1-s integration were within 1-2 ppm of the CO2 estimates obtained from on-board in-situ sensors. For weak surface reflection conditions such as ocean surfaces, the 1- s integrated signal-to-noise ratio (SNR) of lidar measurements at 11 km altitude reached 376, which was equivalent to a 10-s CO2 error 0.33 ppm. For the entire processed 2014 summer flight campaign data, the mean differences between lidar remote sensed and in-situ estimated CO2 values were about -0.013 ppm. These results indicate that current laser absorption lidar approach could meet space measurement requirements for CO2 science goals.

Lin, Bing↗

DOE OSTI2018

Automatic signal decoding and sensor stability of a 3-electrode mixed-potential sensor for NO x /NH 3 quantification

Sensors to detect mixtures of NO x /NH 3 are needed to monitor emissions of diesel automobiles where a selective catalytic reduction system uses an NH 3 mediated reaction to reduce NO x . We report on the application of a three electrode La 0.8 Sr 0.2 CrO 3 , Au 0.5 Pd 0.5 , Pt mixed potential sensor using yttria-stabilized-zirconia (YSZ) as a solid electrolyte to NO x /NH 3 sensing. Artificial neural networks were used to automatically decode the concentrations of NO x /NH 3 and errors of less than 15% are achieved. The optimal architecture for ANN decoding and the maximum density of training data points are also determined. The stability of the sensor was monitored by electrochemical impedance spectroscopy. The impedance associated with YSZ oxygen ion conduction and the electrochemical reactions at the three-phase interface are tracked for a period of over 100 days.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Optimizing process-based models to predict current and future soil organic carbon stocks at high-resolution

From hillslope to small catchment scales (< 50 km 2 ), soil carbon management and mitigation policies rely on estimates and projections of soil organic carbon (SOC) stocks. Here we apply a process-based modeling approach that parameterizes the MIcrobial-MIneral Carbon Stabilization (MIMICS) model with SOC measurements and remotely sensed environmental data from the Reynolds Creek Experimental Watershed in SW Idaho, USA. Calibrating model parameters reduced error between simulated and observed SOC stocks by 25%, relative to the initial parameter estimates and better captured local gradients in climate and productivity. The calibrated parameter ensemble was used to produce spatially continuous, high-resolution (10 m 2 ) estimates of stocks and associated uncertainties of litter, microbial biomass, particulate, and protected SOC pools across the complex landscape. Here, subsequent projections of SOC response to idealized environmental disturbances illustrate the spatial complexity of potential SOC vulnerabilities across the watershed. Parametric uncertainty generated physicochemically protected soil C stocks that varied by a mean factor of 4.4 × across individual locations in the watershed and a – 14.9 to + 20.4% range in potential SOC stock response to idealized disturbances, illustrating the need for additional measurements of soil carbon fractions and their turnover time to improve confidence in the MIMICS simulations of SOC dynamics.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1968

Miniature pressure transducer for stressed member application

Miniature pressure transducer responds to static or dynamic pressures acting against a structural surface without introducing errors caused by stresses in the structural surface. This is accomplished by a thin stainless steel pressure sensing diaphragm with an attached foil strain gage.

Walker, R. R.↗

NASA NTRS1972

Data processing 1: Advancements in machine analysis of multispectral data

Multispectral data processing procedures are outlined beginning with the data display process used to accomplish data editing and proceeding through clustering, feature selection criterion for error probability estimation, and sample clustering and sample classification. The effective utilization of large quantities of remote sensing data by formulating a three stage sampling model for evaluation of crop acreage estimates represents an improvement in determining the cost benefit relationship associated with remote sensing technology.

Swain, P. H.↗