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NASA NTRS1992

Perceptual adaptation in the use of night vision goggles

The image intensification (I sup 2) systems studied for this report were the biocular AN/PVS-7(NVG) and the binocular AN/AVS-6(ANVIS). Both are quite impressive for purposes of revealing the structure of the environment in a fairly straightforward way in extremely low-light conditions. But these systems represent an unusual viewing medium. The perceptual information available through I sup 2 systems is different in a variety of ways from the typical input of everyday vision, and extensive training and practice is required for optimal use. Using this sort of system involves a kind of perceptual skill learning, but is may also involve visual adaptations that are not simply an extension of normal vision. For example, the visual noise evident in the goggles in very low-light conditions results in unusual statistical properties in visual input. Because we had recently discovered a strong and enduring aftereffect of perceived texture density which seemed to be sensitive to precisely the sorts of statistical distortions introduced by I sup 2 systems, it occurred to use that visual noise of this sort might be a very adapting stimulus for texture density and produce an aftereffect that extended into normal vision once the goggles were removed. We have not found any experimental evidence that I sup 2 systems produce texture density aftereffects. The nature of the texture density aftereffect is briefly explained, followed by an accounting of our studies of I sup 2 systems and our most recent work on the texture density aftereffect. A test for spatial frequency adaptation after exposure to NVG's is also reported, as is a study of perceived depth from motion (motion parallax) while wearing the biocular goggles. We conclude with a summary of our findings.

Durgin, Frank H.↗

DOE OSTI2021

A database of global storm surge reconstructions

Storm surges are among the deadliest coastal hazards and understanding how they have been affected by climate change and variability in the past is crucial to prepare for the future. However, tide gauge records are often too short to assess trends and perform robust statistical analyses. Here we use a data-driven modeling framework to simulate daily maximum surge values at 882 tide gauge locations across the globe. We use five different atmospheric reanalysis products for the storm surge reconstruction, the longest one going as far back as 1836. The data that we generate can be used, for example, for long-term trend analyses of the storm surge climate and identification of regions where changes in the intensity and/or frequency of storms surges have occurred in the past. It also provides a better basis for robust extreme value analysis, especially for tide gauges where observational records are short. The data are made available for public use through an interactive web-map as well as a public data repository.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2014

Submillimeter Galaxies as Progenitors of Compact Quiescent Galaxies

Three billion years after the big bang (at redshift z = 2), half of the most massive galaxies were already old, quiescent systems with little to no residual star formation and extremely compact with stellar mass densities at least an order of magnitude larger than in low-redshift ellipticals, their descendants. Little is known about how they formed, but their evolved, dense stellar populations suggest formation within intense, compact starbursts 1-2 Gyr earlier (at 3 < z < 6). Simulations show that gas-rich major mergers can give rise to such starbursts, which produce dense remnants. Submillimeter-selected galaxies (SMGs) are prime examples of intense, gas-rich starbursts.With a new, representative spectroscopic sample of compact, quiescent galaxies at z = 2 and a statistically well-understood sample of SMGs, we show that z = 3-6 SMGs are consistent with being the progenitors of z = 2 quiescent galaxies, matching their formation redshifts and their distributions of sizes, stellar masses, and internal velocities. Assuming an evolutionary connection, their space densities also match if the mean duty cycle of SMG starbursts is 42(sup+40) −29 Myr (consistent with independent estimates), which indicates that the bulk of stars in these massive galaxies were formed in a major, early surge of star formation. These results suggest a coherent picture of the formation history of the most massive galaxies in the universe, from their initial burst of violent star formation through their appearance as high stellar-density galaxy cores and to their ultimate fate as giant ellipticals.

Cosmology - Observations↗

NASA NTRS2023

Geometric Analysis and Visualization of Maxillofacial Anthropometry

As part of head borne systems, the maxillofacial and mandibular components are critical for Soldier protection in extreme and dynamic conditions. Often this equipment must not only cover the lower face of the wearer, but also accommodate motion of the lower jaw and resultant deformation of the face shape. Although the application is different, head borne equipmentdesigned for astronauts has similarly critical design requirements including comfort and protection from other environmental hazards while allowing for maximum performance. To improve the design of such systems and to ensure adequate accommodation of the user population, NASA Johnson Space Center is collaborating with the U.S. Army’s Development Command Soldier Center (DEVCOM SC) to statistically analyze facial landmark and measurement data from large Soldier anthropometric databases ( ANSUR 1988 and ANSUR II). Anthropometric measurements were incorporated from 5383 males and 3594 females for analysis, including individuals aged 17-58 across a range of races. Facial landmarks were analyzed, specifically the 3D coordinates of the Menton, Prementon, Gonion, Tragion, Stomion, Zygion, Pronasale, and Subnasale. These data were statistically correlated with demographiccharacteristics, such as sex and population origin. A statistical model of the lower head-face surface geometry is currently in development to describe the variance of head and face shape across the population. The model will be able to visually show the statistical trends of the different shapes and sizes of the head, along with the synthetically represented boundary cases. The specific analytical methods and outcomes will be detailed in the final proceeding. This study will provide a more comprehensive assessment of how face shape varies across the military population compared to traditional linear measurements. The outcome of this study is expected to provide critical insight and recommendations for improved protective equipment design and development, not only with Soldiers but also astronauts in future exploration missions, as well as first responders and others that require critical equipment fitted to the maxillofacial and or mandibular region.

W Green↗

DOE OSTI2026

Model-observation discrepancies in Arctic moisture intrusions: causes and pathways for improved simulation

Arctic moisture intrusions (MIs), narrow filaments of strong moisture transport, are key drivers of poleward moisture flux and Arctic weather extremes, yet their representation in climate models is poorly understood. Using a new Arctic MI detection algorithm, we document persistent biases across three CMIP generations (CMIP3–CMIP6): models overestimate MI occurrence over the Pacific sector and underestimate it over the Atlantic sector. These errors stem from misrepresented midlatitude westerly jets, with an equatorward North Atlantic jet associated with too few Atlantic MIs, and a poleward, weakened North Pacific jet linked to too many Pacific MIs. Experiments that correct sea surface temperature and sea ice concentration biases and increase atmospheric resolution improve jet structure and MI statistics, while a cloud-locking simulation indicates that better high-frequency cloud–radiation–circulation interactions can yield further gains. Our results clarify pathways to reducing long-standing MI and jet biases, providing guidance for improving simulations of Arctic and midlatitude climate.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1973

Effect of lubricant extreme pressure additives on rolling element fatigue life

The effects of surface active additives on rolling-element fatigue life were investigated with the five-ball fatigue tester at conditions where classical subsurface initiated rolling-element fatigue is the sole mode of failure. Test balls of AISI 52100, AISI M-50, and AISI 1018 were run with an acid-treated white oil containing either 2.5 percent sulfurized terpene, 1 percent didodecyl phosphite, or 5 percent chlorinated wax. In general, it was found that the influence of surface active additives was detrimental to rolling-element fatigue life. The chlorinated-wax additive significantly reduced fatigue life by a factor of 7. The base oil with the 2.5 percent sulfurized-terpene additive can reduce fatigue life by as much as 50 percent. No statistical change in fatigue life occurred with the base oil having the 1 percent didodecyl-phosphite additive. The additives used with the base oil did not change the ranking of the bearing steels where rolling-element fatigue life was of subsurface origin.

Parker, R. J.↗

DOE OSTI2024

Advanced Signal Decomposition Analysis and Anomaly Detection in Photovoltaic Systems

With the rapid expansion of large-scale photovoltaic (PV) plants, it is paramount for solar stakeholders to understand the reliability and efficiency of their plants to inform maintenance decisions, increase production, and understand the design factors that impact performance. Diagnosing underperformance in PV plants is challenging due to the relatively few monitoring points with respect to the large geographic footprint of the plant. This work introduces a cutting-edge method that transforms the analysis and management of key factors influencing PV plant performance, including performance loss rate (PLR), recoverable soiling, and major system changes. Identifying these factors is critical for deriving actionable insights. Leveraging advanced analytical techniques such as wavelet transformation, robust regression, and extreme point analysis, this approach provides a nuanced understanding of these factors. This method has been tested across two synthetic datasets and one real dataset, consistently surpassing existing benchmarks by achieving a lower median mean absolute error and reduced error variability across all comparable components.

14 SOLAR ENERGY↗

NASA NTRS1983

Some practical universal noiseless coding techniques, part 2

This report is an extension of earlier work (Part 1) which provided practical adaptive techniques for the efficient noiseless coding of a broad class of data sources characterized by only partially known and varying statistics (JPL Publication 79-22). The results here, while still claiming such general applicability, focus primarily on the noiseless coding of image data. A fairly complete and self-contained treatment is provided. Particular emphasis is given to the requirements of the forthcoming Voyager II encounters of Uranus and Neptune. Performance evaluations are supported both graphically and pictorially. Expanded definitions of the algorithms in Part 1 yield a computationally improved set of options for applications requiring efficient performance at entropies above 4 bits/sample. These expanded definitions include as an important subset, a somewhat less efficient but extremely simple "FAST' compressor which will be used at the Voyager Uranus encounter. Additionally, options are provided which enhance performance when atypical data spikes may be present.

Rice, R. F.↗

DOE OSTI2026

From atomistic models to machine learning: Predictive design of nanocarbons under extreme conditions

The formation of technologically valuable nanocarbon structures under extreme conditions, such as those produced during high-explosive detonations, remains poorly understood but holds significant potential for the development of controlled synthesis pathways. While detonation shockwaves provide the high-pressure, high-temperature environment required for nanodiamond formation, subsequent cooling and decompression dictate whether the diamond phase is preserved or transformed into other nanocarbon structures. Here, in this study, we employ GPU-accelerated reactive molecular dynamics (ReaxFF) simulations to investigate the graphitization and structural remodeling of detonation nanodiamond under nonlinear quench and pressure-release trajectories. We further investigate how the initial nanodiamond morphology; cuboctahedral, octahedral, or hexagonal prism influences the resulting transformation products. Evolution of nanostructure, allotrope (via simulated x-ray diffraction), carbon hybridization, and ring statistics are tracked during a two-stage quench from 5000 K to 60 GPa. Rapid cooling combined with slow decompression optimizes cubic diamond retention, whereas slow cooling with rapid pressure release promotes surface-to-core graphitization, producing concentric sp 2 -hybridized layers and hollowed inner shells. Octahedral nanodiamonds evolve into carbon nano-onions, initially forming bucky diamonds that progressively transform into fully sp 2 -hybridized structures, while hexagonal prisms preferentially form parallel-stacked graphite layers resembling carbon dots. Transient hexagonal diamond (lonsdaleite) emerges as an interfacial phase, suggesting potential reversibility in the shock-induced graphite-to-diamond transformation pathway transformation route. To extend predictive capabilities, we trained machine learning (ML) regressors on over 10 5 node-hours of molecular dynamics (MD) trajectories. A multilayer perceptron (MLP) model reliably predicts the number of graphitized layers from temperature–pressure trajectories with a coefficient of determination (R 2 ) exceeding 0.90. This high predictive fidelity enables efficient, high-throughput mapping of the synthesis parameter space for optimized graphitization outcomes. Collectively, morphological control combined with optimized quench–decompression conditions promote the selective synthesis of nanocarbon allotropes. This work establishes a data-driven framework for the rational, a priori design of carbon nanomaterials for applications in energy storage, sensing, and biomedicine.

Detonation nanodiamond remodeling↗

DOE OSTI2024

Modelling the impact of host galaxy dust on type Ia supernova distance measurements

Type Ia Supernovae (SNe Ia) are a critical tool in measuring the accelerating expansion of the universe. Recent efforts to improve these standard candles have focused on incorporating the effects of dust on distance measurements with SNe Ia. In this paper, we use the state-of-the-art Dark Energy Survey 5 year sample to evaluate two different families of dust models: empirical extinction models derived from SNe Ia data and physical attenuation models from the spectra of galaxies. In this work, we use realistic simulations of SNe Ia to forward-model different models of dust and compare summary statistics in order to test different assumptions and impacts on SNe Ia data. Among the SNe Ia-derived models, we find that a logistic function of the total-to-selective extinction R V best recreates the correlations between supernova distance measurements and host galaxy properties, though an additional 0.02 mag of grey scatter is needed to fully explain the scatter in SNIa brightness in all cases. These empirically derived extinction distributions are highly incompatible with the physical attenuation models from galactic spectral measurements. From these results, we conclude that SNe Ia must either preferentially select extreme ends of galactic dust distributions, or that the characterization of dust along the SNe Ia line-of-sight is incompatible with that of galactic dust distributions.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS1972

Permutation codes for sources.

Source encoding techniques based on permutation codes are investigated. For a broad class of distortion measures it is shown that optimum encoding of a source permutation code is easy to instrument even for very long block lengths. Also, the nonparametric nature of permutation encoding is well suited to situations involving unknown source statistics. For the squared-error distortion measure a procedure for generating good permutation codes of a given rate and block length is described. The performance of such codes for a memoryless Gaussian source is compared both with the rate-distortion function bound and with the performance of various quantization schemes. The comparison reveals that permutation codes are asymptotically ideal for small rates and perform as well as the best entropy-coded quantizers presently known for intermediate rates. They can be made to compare favorably at high rates, too, provided the coding delay associated with extremely long block lengths is tolerable.

Berger, T.↗

NASA NTRS1993

Plasmasphere dynamics in the duskside bulge region: A new look at old topic

Data acquired during several multiday periods in 1982 at ground stations Siple, Halley, and Kerguelen and on satellites Dynamics Explorer 1, International Sun Earth Explorer 1, and GEOS 2 have been used to investigate thermal plasma structure and dynamics in the duskside plasmasphere bulge region of the Earth. The distribution of thermal plasma in the dusk bulge sector is difficult to describe realistically, in part because of the time integral manner in which the thermal plasma distribution depends upon on the effects of bulk cross-B flow and interchange plasma flows along B. While relatively simple MHD models can be useful for qualitatively predicting certain effects of enhanced convection on a quiet plasmasphere, such as an initial sunward entrainment of the outer regions, they are of limited value in predicting the duskside thermal plasma structures that are observed. Furthermore, use of such models can be misleading if one fails to realize that they do not address the question of the formation of the steep plasmapause profile or provide for a possible role of instabilities or other irreversible processes in plasmapause formation. Our specific findings, which are based both upon the present case studies and upon earlier work, include the following: (1) during active periods the plasmasphere appears to become divided into two entities, a main plasmasphere and a duskside bulge region. (2) in the aftermath of an increase in convection activity, the main plasmasphere tends (from a statistical point of view) to become roughly circular in equatorial cross section, with only a slight bulge at dusk; (3) the abrupt westward edge of the duskside bulge observed from whistlers represents a state in the evolution of sunward extending streamers; (4) in the aftermath of a weak magnetic storm, 10 to 30% of the plasma 'removed' from the outer plasmasphere appears to remain in the afternoon-dusk sector beyond the main plasmasphere. (5) outlying dense plasma structures may circulate in the outer duskside magetosphere for many days following an increase in convection, unless there is extremely deep quieting; (6) a day-night plasmatrough boundary may be identified in equatorial satellite data; (7) factor-of-2-to-10 density irregularities appear near the plasmatrough from the ionosphere at L = 4.6, predominantly bidirectional field aligned and equatorially trapped light ion pitch angle distributions give away to a predominantly isotropic distribution (as seen by DE 1) when the plasma density reaches a level a factor of about 3 below the satured plasmasphere level; (9) some outlying dense plasma structures are effectively detached from the main plasmasphere, while others appear to be connected to that body.

Carpenter, D. L.↗

NASA NTRS2008

On the Period-Amplitude and Amplitude-Period Relationships

Examined are Period-Amplitude and Amplitude-Period relationships based on the cyclic behavior of the 12-month moving averages of monthly mean sunspot numbers for cycles 0.23, both in terms of Fisher's exact tests for 2x2 contingency tables and linear regression analyses. Concerning the Period-Amplitude relationship (same cycle), because cycle 23's maximum amplitude is known to be 120.8, the inferred regressions (90-percent prediction intervals) suggest that its period will be 131 +/- 24 months (using all cycles) or 131 +/- 18 months (ignoring cycles 2 and 4, which have the extremes of period, 108 and 164 months, respectively). Because cycle 23 has already persisted for 142 months (May 1996 through February 2008), based on the latter prediction, it should end before September 2008. Concerning the Amplitude-Period relationship (following cycle maximum amplitude versus preceding cycle period), because cycle 23's period is known to be at least 142 months, the inferred regressions (90-percent prediction intervals) suggest that cycle 24's maximum amplitude will be about less than or equal to 96.1 +/- 55.0 (using all cycle pairs) or less than or equal to 91.0 +/- 36.7 (ignoring statistical outlier cycle pairs). Hence, cycle 24's maximum amplitude is expected to be less than 151, perhaps even less than 128, unless cycle pair 23/24 proves to be a statistical outlier.

Wilson, Robert M.↗

NASA NTRS2019

Challenges in Qualification of Thermal Protection Systems in Extreme Entry Environments

Planetary entry vehicles employ ablative TPS materials to shield the aeroshell from entry aeroheating environments. To ensure mission success, it must be demonstrated that the heat shield system, including local features such as seams, does not fail at conditions that are suitably margined beyond those expected in flight. Furthermore, its thermal response must be predictable, with acceptable fidelity, by computational tools used in heat shield design. Mission assurance is accomplished through a combination of ground testing and material response modelling. A material's robustness to failure is verified through arcjet testing while its thermal response is predicted by analytical tools that are verified against experimental data. Due to limitations in flight-like ground testing capability and lack of validated high-fidelity computational models, qualification of heat shield materials is often achieved by piecing together evidence from multiple ground tests and analytical simulations, none of which fully bound the flight conditions and vehicle configuration. Extreme heating environments (>2000 W/sq. cm heat flux and >2 atm pressure), experienced during entries at Venus, Saturn and Ice Giants, further stretch the current testing and modelling capabilities for applicable TPS materials. Fully-dense Carbon Phenolic was the material of choice for these applications; however, since heritage raw materials are no longer available, future uses of re-created Carbon Phenolic will require re-qualification. To address this sustainability challenge, NASA is developing a new dual-layer material based on 3D weaving technology called Heat shield for Extreme Entry Environments (HEEET). Regardless of TPS material, extreme environments pose additional certification challenges beyond what has been typical in recent NASA missions. Scope of this presentation: This presentation will give an overview of challenges faced in verifying TPS performance at extreme heating conditions. Examples include: (1) Bounding aeroheating parameters (heat flux, pressure, shear and enthalpy) in ground facilities. How to certify TPS if environments can't be bounded or aeroheating parameters can't be simultaneously achieved. (2) Higher uncertainties in ground test environments (facility calibration and analytical predictions) at extreme conditions. (3) Testing in flows similar to planetary atmosphere composition (H2/He for Gas and Ice Giants). (4) Test sample size limitations for qualifying seam designs. (5) Lack of computational tools capable of simulating all significant aspects of TPS performance (including initiation and propagation of failures). This presentation will provide recommendations on how the EDL community can address these challenges and mitigate some of the risks involved in flying TPS materials at extreme conditions. Examples include: (1) Dedicated activity to understanding TPS failure modes. Develop computational tools capable of modelling fluid interaction with material's thermostructural response. Validate these tools through failure testing. A better understanding of failure mechanisms may eliminate the need to fully bound all aeroheating parameters in ground testing. (2) Enhancements to current testing facilities to simulate flight-like ablation mechanism (ex. testing in Nitrogen at Ames Interaction Heating Facility to limit oxidation in favor of more sublimation). (3) Improved characterization of test conditions with new diagnostic methods and determination of environment uncertainty through rigorous statistical analysis of available data. (4) Design margin policies that are directly tied to uncertainties in ground test environments and modelling fidelity

Mahzari, Milad↗

NASA NTRS1986

EUV astronomical spectroscopy with CCD detectors

The applicability of CCD detectors to astronomical extreme ultraviolet (EUV) spectroscopy (100-1250 A) is discussed. The advantages of CCDs in this spectral region include internal electron yield, the potential for very high quantum efficiency (about 50-90 percent), and broad wavelength response. Visible light suppression is achieved by a combination of low grating scattering, greater than unity electron yield in the EUV, and various filter techniques. For the current generation of CCDs, detection of only a few EUV photons will rapidly overwhelm the read noise; thus, for all practical S/N ratios used in astronomical spectroscopy, read noise will be negligible compared to the poisson statistics of the detected photons. A model based on experimental data for the quantum efficiency and electron yield of CCDs in the EUV is discussed.

Stern, R. A.↗

NASA NTRSDate not supplied

Toward The Development of Hailstorm Climatologies Derived From Reanalyses and Infared/Passive Microwave Satellite Imagers

Geostationary satellite imagers, such as those of the Geostationary Operational Environmental Satellite (GOES) and Meteosat series, provide both historical and near-real-time observations of cloud top patterns that are commonly associated with severe convection. Environmental conditions favorable for severe weather are thought to be represented well by reanalyses. Predicting exactly where convection and costly storm hazards like hail will occur using models or satellite imagery alone, however, is extremely challenging. The multivariate combination of satellite-observed cloud patterns with reanalysis environmental parameters, linked to United States Next Generation Weather Radar- (NEXRAD-) estimated Maximum Expected Size of Hail (MESH) using a deep neural network (DNN), enables estimation of potentially severe hail likelihood for any observed storm cell. These estimates are specifically designed to make hail likelihood distinctions based on satellite-indicated points of deep convection within environments favorable for storm development. We seek an approach that can be used to estimate climatological hailstorm frequency and risk throughout the historical satellite data record. This presentation demonstrates that statistical distributions of convective parameters from satellite and reanalysis show separation between non-severe/severe hailstorm classes for predictors including overshooting cloud top temperature and area characteristics, convective available potential energy, vertical wind shear, 500 hPa temperature, mid-level lapse rate, precipitable water, and convective inhibition. These complex, multivariate predictor relationships are exploited within a DNN to produce a hail likelihood metric with a critical success index of 0.504 and Heidke skill score of 0.403, which is exceptional among recent analogous hail studies. Furthermore, applications of the DNN to select case studies demonstrate good qualitative agreement between hail likelihood and MESH. These hail classifications are aggregated across an 11-year GOES-12/13 image database to derive a hail frequency and severity climatology, which denotes the Central Plains, the Midwest, and northwestern Mexico as being the most hail-prone regions within the domain studied. Opportunities for training and applying DNN-based hailstorm predictions to recently developed GOES-8/10/12/13/16 and Meteosat Second Generation convective storm detection and characterization climatologies over South America and South Africa, respectively, will also be presented.

Kristopher Bedka↗

DOE OSTI2025

Economic Storage Size Optimization for Electric Vehicle Extreme-Fast Charging Stations

En-route charging infrastructure for electric vehicles is critical to support transportation needs. These charging stations are likely to have high loads and especially sharp peak loads given fast charging capabilities needed to meet transportation schedules. In order to reduce both strain on distribution grid infrastructure and charging station operational costs, many stations are likely to employ behind the meter storage. This paper demonstrates a behind the meter storage sizing optimization that employs an open-source agent-based vehicle behavior model (BEAM) to determine the best sizing across many scenarios. This optimization and analysis is novel in that it examines how storage size impacts not only charging station cost and peak load, but also vehicle queue times. The optimization is also applied across a wide analysis region with sufficient diversity and numbers to provide novel statistical analysis of optimal sizes.

Aka, Julius↗

NASA NTRS2012

Availability Estimation for Facilities in Extreme Geographical Locations

A value added analysis for the Reliability. Availability and Maintainability of McMurdo Ground Station was developed, which will be a useful tool for system managers in sparing, maintenance planning and determining vital performance metrics needed for readiness assessment of the upgrades to the McMurdo System. Output of this study can also be used as inputs and recommendations for the application of Reliability Centered Maintenance (RCM) for the system. ReliaSoft's BlockSim. a commercial Reliability Analysis software package, has been used to model the availability of the system upgrade to the National Aeronautics and Space Administration (NASA) Near Earth Network (NEN) Ground Station at McMurdo Station in the Antarctica. The logistics challenges due to the closure of access to McMurdo Station during the Antarctic winter was modeled using a weighted composite of four Weibull distributions. one of the possible choices for statistical distributions throughout the software program and usually used to account for failure rates of components supplied by different manufacturers. The inaccessibility of the antenna site on a hill outside McMurdo Station throughout one year due to severe weather was modeled with a Weibull distribution for the repair crew availability. The Weibull distribution is based on an analysis of the available weather data for the antenna site for 2007 in combination with the rules for travel restrictions due to severe weather imposed by the administrating agency, the National Science Foundation (NSF). The simulations resulted in an upper bound for the system availability and allowed for identification of components that would improve availability based on a higher on-site spare count than initially planned.

Fischer, Gerd M.↗