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At least 811 records · Page 45

Generic trending and analysis system

The Generic Trending and Analysis System (GTAS) is a generic spacecraft performance monitoring tool developed by NASA Code 511 and Loral Aerosys. It is designed to facilitate quick anomaly resolution and trend analysis. Traditionally, the job of off-line analysis has been performed using hardware and software systems developed for real-time spacecraft contacts; then, the systems were supplemented with a collection of tools developed by Flight Operations Team (FOT) members. Since the number of upcoming missions is increasing, NASA can no longer afford to operate in this manner. GTAS improves control center productivity and effectiveness because it provides a generic solution across multiple missions. Thus, GTAS eliminates the need for each individual mission to develop duplicate capabilities. It also allows for more sophisticated tools to be developed because it draws resources from several projects. In addition, the GTAS software system incorporates commercial off-the-shelf tools software (COTS) packages and reuses components of other NASA-developed systems wherever possible. GTAS has incorporated lessons learned from previous missions by involving the users early in the development process. GTAS users took a proactive role in requirements analysis, design, development, and testing. Because of user involvement, several special tools were designed and are now being developed. GTAS users expressed considerable interest in facilitating data collection for long term trending and analysis. As a result, GTAS provides easy access to large volumes of processed telemetry data directly in the control center. The GTAS archival and retrieval capabilities are supported by the integration of optical disk technology and a COTS relational database management system.

Keehan, Lori↗

A high resolution atlas of the galactic plane at 12 microns and 25 microns

High resolution images of the 12 micron and 25 micron IRAS survey data from each HCON crossing the Galactic Plane are being created for those regions that the original IRAS processing labeled as confused. This encompasses the area within 100 deg longitude of the Galactic Center and within 3 deg to 10 deg of the Plane. The procedures used to create the images preserve the spatial resolution inherent in the IRAS instrument. The images are separated into diffuse and point source components and candidate sources are extracted from the point source image after non-linear spatial sharpening. Fluxes are estimated by convolving the candidate sources with the point response function and cross-correlating with the original point source image. A source is considered real if it is seen on at least two HCON's with a rather generous flux match but a stringent position criterion. A number of fields spanning a range of source densities from low to high have been examined. Initial analysis indicates that the imaging and extraction works quite well up to a source density of about 100 sources per square degree or down to roughly 0.8 Janskys.

Price, Stephan D.↗

System Wide Joint Position Sensor Fault Tolerance in Robot Systems Using Cartesian Accelerometers

Joint position sensors are necessary for most robot control systems. A single position sensor failure in a normal robot system can greatly degrade performance. This paper presents a method to obtain position information from Cartesian accelerometers without integration. Depending on the number and location of the accelerometers. the proposed system can tolerate the loss of multiple position sensors. A solution technique suitable for real-time implementation is presented. Simulations were conducted using 5 triaxial accelerometers to recover from the loss of up to 4 joint position sensors on a 7 degree of freedom robot moving in general three dimensional space. The simulations show good estimation performance using non-ideal accelerometer measurements.

Aldridge, Hal A.↗

Coding for Communication Channels with Dead-Time Constraints

Coding schemes have been designed and investigated specifically for optical and electronic data-communication channels in which information is conveyed via pulse-position modulation (PPM) subject to dead-time constraints. These schemes involve the use of error-correcting codes concatenated with codes denoted constrained codes. These codes are decoded using an interactive method. In pulse-position modulation, time is partitioned into frames of Mslots of equal duration. Each frame contains one pulsed slot (all others are non-pulsed). For a given channel, the dead-time constraints are defined as a maximum and a minimum on the allowable time between pulses. For example, if a Q-switched laser is used to transmit the pulses, then the minimum allowable dead time is the time needed to recharge the laser for the next pulse. In the case of bits recorded on a magnetic medium, the minimum allowable time between pulses depends on the recording/playback speed and the minimum distance between pulses needed to prevent interference between adjacent bits during readout. The maximum allowable dead time for a given channel is the maximum time for which it is possible to satisfy the requirement to synchronize slots. In mathematical shorthand, the dead-time constraints for a given channel are represented by the pair of integers (d,k), where d is the minimum allowable number of zeroes between ones and k is the maximum allowable number of zeroes between ones. A system of the type to which the present schemes apply is represented by a binary- input, real-valued-output channel model illustrated in the figure. At the transmitting end, information bits are first encoded by use of an error-correcting code, then further encoded by use of a constrained code. Several constrained codes for channels subject to constraints of (d,infinity) have been investigated theoretically and computationally. The baseline codes chosen for purposes of comparison were simple PPM codes characterized by M-slot PPM frames separated by d-slot dead times.

Moision, Bruce↗

Inelastic Light Scattering Processes

Five different inelastic light scattering processes will be denoted by, ordinary Raman scattering (ORS), resonance Raman scattering (RRS), off-resonance fluorescence (ORF), resonance fluorescence (RF), and broad fluorescence (BF). A distinction between fluorescence (including ORF and RF) and Raman scattering (including ORS and RRS) will be made in terms of the number of intermediate molecular states which contribute significantly to the scattered amplitude, and not in terms of excited state lifetimes or virtual versus real processes. The theory of these processes will be reviewed, including the effects of pressure, laser wavelength, and laser spectral distribution on the scattered intensity. The application of these processes to the remote sensing of atmospheric pollutants will be discussed briefly. It will be pointed out that the poor sensitivity of the ORS technique cannot be increased by going toward resonance without also compromising the advantages it has over the RF technique. Experimental results on inelastic light scattering from I(sub 2) vapor will be presented. As a single longitudinal mode 5145 A argon-ion laser line was tuned away from an I(sub 2) absorption line, the scattering was observed to change from RF to ORF. The basis, of the distinction is the different pressure dependence of the scattered intensity. Nearly three orders of magnitude enhancement of the scattered intensity was measured in going from ORF to RF. Forty-seven overtones were observed and their relative intensities measured. The ORF cross section of I(sub 2) compared to the ORS cross section of N2 was found to be 3 x 10(exp 6), with I(sub 2) at its room temperature vapor pressure.

Fouche, Daniel G.↗

Relating Land Cover Change to Runoff Distribution Using NASA Earth Observations in Riley County, Kansas

In recent years, Riley County, Kansas experienced high levels of flooding potentially due to changes in land use and impervious surface. To analyze the increase in floods and runoff patterns over time, this study contrasted two methods of curve number (CN) calculation, which estimated runoff from rainfall events, from 2006-2020. The conventional calculation method used a look-up table and tracked land use/land cover change. This method resulted in static tables from various inputs such as soil type, surface imperviousness, slope, and crop phenology to estimate runoff versus infiltration. These tables allowed for phenology specific curve numbers and accounted for various farming techniques but required many inputs and lacked flexibility to include seasonal variations in vegetation. In contrast, the dynamic method is a more modern and simple calculation employing normalized difference vegetation index (NDVI) data from Landsat 5, Landsat 7, and Landsat 8 satellites compiled over the rainy season each year to calculate curve numbers based off seasonal vegetation. This dynamic method allowed for more precise analysis of runoff variability because NDVI is a more accurate, real-time measurement for land cover and it could be calculated with greater temporal detail. The results will allow decision makers to make more informed decisions on resiliency strategies to address future flooding.

Trista Brophy↗

Enhancing the sensitivity of the LUX-ZEPLIN (LZ) dark matter experiment to low energy signals

Two-phase xenon detectors, such as that at the core of the forthcoming LZ dark matter experiment, use photomultiplier tubes to sense the primary (S1) and secondary (S2) scintillation signals resulting from particle interactions in their liquid xenon target. This paper describes a simulation study exploring two techniques to lower the energy threshold of LZ to gain sensitivity to low-mass dark matter and astrophysical neutrinos, which will be applicable to other liquid xenon detectors. The energy threshold is determined by the number of detected S1 photons; typically, these must be recorded in three or more photomultiplier channels to avoid dark count coincidences that mimic real signals. To lower this threshold: a) we take advantage of the double photoelectron emission effect, whereby a single vacuum ultraviolet photon has a $\sim20\%$ probability of ejecting two photoelectrons from a photomultiplier tube photocathode; and b) we drop the requirement of an S1 signal altogether, and use only the ionization signal, which can be detected more efficiently. For both techniques we develop signal and background models for the nominal exposure, and explore accompanying systematic effects, including the dependence on the free electron lifetime in the liquid xenon. When incorporating double photoelectron signals, we predict a factor of $\sim 4$ sensitivity improvement to the dark matter-nucleon scattering cross-section at $2.5$ GeV/c$^2$, and a factor of $\sim1.6$ increase in the solar $^8$B neutrino detection rate. Dropping the S1 requirement may allow sensitivity gains of two orders of magnitude in both cases. Finally, we apply these techniques to even lower masses by taking into account the atomic Migdal effect; this could lower the dark matter particle mass threshold to $80$ MeV/c$^2$.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Enhancing the sensitivity of the LUX-ZEPLIN (LZ) dark matter experiment to low energy signals

Two-phase xenon detectors, such as that at the core of the forthcoming LZ dark matter experiment, use photomultiplier tubes to sense the primary (S1) and secondary (S2) scintillation signals resulting from particle interactions in their liquid xenon target. This paper describes a simulation study exploring two techniques to lower the energy threshold of LZ to gain sensitivity to low-mass dark matter and astrophysical neutrinos, which will be applicable to other liquid xenon detectors. The energy threshold is determined by the number of detected S1 photons; typically, these must be recorded in three or more photomultiplier channels to avoid dark count coincidences that mimic real signals. To lower this threshold: a) we take advantage of the double photoelectron emission effect, whereby a single vacuum ultraviolet photon has a $\sim20\%$ probability of ejecting two photoelectrons from a photomultiplier tube photocathode; and b) we drop the requirement of an S1 signal altogether, and use only the ionization signal, which can be detected more efficiently. For both techniques we develop signal and background models for the nominal exposure, and explore accompanying systematic effects, including the dependence on the free electron lifetime in the liquid xenon. When incorporating double photoelectron signals, we predict a factor of $\sim 4$ sensitivity improvement to the dark matter-nucleon scattering cross-section at $2.5$ GeV/c$^2$, and a factor of $\sim1.6$ increase in the solar $^8$B neutrino detection rate. Dropping the S1 requirement may allow sensitivity gains of two orders of magnitude in both cases. Finally, we apply these techniques to even lower masses by taking into account the atomic Migdal effect; this could lower the dark matter particle mass threshold to $80$ MeV/c$^2$.

Akerib, DS↗

Nonparametric Multiparticle Set Methods for Interpreting Environmental Samples

Collection and analysis of environmental samples is commonly used by a range of stakeholders in nuclear safeguards and security contexts. While the ubiquity of samples and their transport in the environment allow regular collection, developing and demonstrating methods for analyzing these samples is difficult. In this work, an environmental sample consists of a set of one or more individual particles. Recent advances in reactor simulation have allowed us to generate data that are more representative of real-world environmental samples, enabling statistically defensible method development and testing. The most notable of these advances is a drastic increase in the number of material depletion regions, which allows our simulations to capture the variation in isotopic composition seen at length scales consistent with environmental samples. Traditional approaches for handling multiparticle samples treat each particle in the sample individually, estimating the quantity of interest (e.g., core-average burnup) resulting from measurement and analysis of signatures (e.g., nuclide assays) from each individual particle. Individual estimates are then averaged to generate a single estimate of the quantity of interest over the entire sample. In this presentation, we introduce two novel approaches for interpreting environmental samples that comprise of multiple particles: (1) the Quantile-Quantile Comparator, which uses a multivariate generalization of quantile-quantile plots for comparing unknown statistical distributions, and (2) the Set Transformer, an attention-based neural network module designed to model interactions among elements (particles) in the input set (sample). Statistically representative sampling cannot be guaranteed as samples are passively collected and are beholden to what particles are available in the environment. These new analysis methods for set-input problems are expected to be more robust than traditional approaches to issues of sampling bias where particles are not uniformly distributed throughout regions of interest, as well as generally outperform traditional approaches by jointly considering all elements in the set. We will present results comparing the performance of traditional single particle approaches and the novel Quantile-Quantile Comparator and Set Transformer for interpretation of simulated environmental samples.

Phathanapirom, Birdy↗

Towards Run-Time Search for Real-World Multi-Agent Systems

Multi-agent systems (MAS) may encounter uncertainties in the form of unexpected environmental conditions, sub-optimal system configurations, and unplanned interactions between autonomous agents. The number of combinations of such uncertainties may be innumerable, however run-time testing may reduce the issues impacting such a system. We posit that search heuristics can augment a run-time testing process, in-situ, for a MAS. To support our position we discuss our in-progress experimental testbed to realize this goal and highlight challenges we anticipate for this domain.

Abigail C. Diller↗

How to handle 6GBytes a night and not get swamped

The Macho Project has undertaken a 5 year effort to search for dark matter in the halo of the Galaxy by scanning the Magellanic Clouds for micro-lensing events. Each evening's raw image data will be reduced in real-time into the observed stars' photometric measurements. The actual search for micro-lensing events will be a post-processing operation. The theoretical prediction of the rate of such events necessitates the collection of a large number of repeated exposures. The project designed camera subsystem delivers 64 Mbytes per exposure with exposures typically occurring every 500 seconds. An ideal evening's observing will provide 6 Gbytes of raw image data and 40 Mbytes of reduced photometric measurements. Recognizing the difficulty of digging out from a snowballing cascade of raw data, the project requires the real-time reduction of each evening's data. The software team's implementation strategy centered on this non-negotiable mandate. Accepting the reality that 2 full time people needed to implement the core real-time control and data management system within 6 months, off-the-shelf vendor components were explored to provide quick solutions to the classic needs for file management, data management, and process control. Where vendor solutions were lacking, state-of-the-art models were used for hand tailored subsystems. In particular, petri nets manage process control, memory mapped bulletin boards provide interprocess communication between the multi-tasked processes, and C++ class libraries provide memory mapped, disk resident databases. The differences between the implementation strategy and the final implementation reality are presented. The necessity of validating vendor product claims are explored. Both the successful and hindsight decisions enabling the collection and processing of the nightly data barrage are reviewed.

Allsman, R.↗

Mining and Validating Social Media Data for COVID-19–Related Human Behaviors Between January and July 2020: Infodemiology Study

Background: Health authorities can minimize the impact of an emergent infectious disease outbreak through effective and timely risk communication, which can build trust and adherence to subsequent behavioral messaging. Monitoring the psychological impacts of an outbreak, as well as public adherence to such messaging, is also important for minimizing long-term effects of an outbreak. Objective: We used social media data from Twitter to identify human behaviors relevant to COVID-19 transmission, as well as the perceived impacts of COVID-19 on individuals, as a first step toward real-time monitoring of public perceptions to inform public health communications. Methods: We developed a coding schema for 6 categories and 11 subcategories, which included both a wide number of behaviors as well codes focused on the impacts of the pandemic (eg, economic and mental health impacts). We used this to develop training data and develop supervised learning classifiers for classes with sufficient labels. Classifiers that performed adequately were applied to our remaining corpus, and temporal and geospatial trends were assessed. We compared the classified patterns to ground truth mobility data and actual COVID-19 confirmed cases to assess the signal achieved here. Results: We applied our labeling schema to approximately 7200 tweets. The worst-performing classifiers had F1 scores of only 0.18 to 0.28 when trying to identify tweets about monitoring symptoms and testing. Classifiers about social distancing, however, were much stronger, with F1 scores of 0.64 to 0.66. We applied the social distancing classifiers to over 228 million tweets. We showed temporal patterns consistent with real-world events, and we showed correlations of up to –0.5 between social distancing signals on Twitter and ground truth mobility throughout the United States. Conclusions: Behaviors discussed on Twitter are exceptionally varied. Twitter can provide useful information for parameterizing models that incorporate human behavior, as well as for informing public health communication strategies by describing awareness of and compliance with suggested behaviors.

60 APPLIED LIFE SCIENCES↗

Development of Virtual Airspace Simulation Technology - Real-Time (VAST-RT) Capability 2 and Experimental Plans

The Virtual Airspace Simulation Technology - Real-Time (VAST-RT) Project, an element cf NASA's Virtual Airspace Modeling and Simulation (VAMS) Project, has been developing a distributed simulation capability that supports an extensible and expandable real-time, human-in-the-loop airspace simulation environment. The VAST-RT system architecture is based on DoD High Level Architecture (HLA) and the VAST-RT HLA Toolbox, a common interface implementation that incorporates a number of novel design features. The scope of the initial VAST-RT integration activity (Capability 1) included the high-fidelity human-in-the-loop simulation facilities located at NASA/Ames Research Center and medium fidelity pseudo-piloted target generators, such as the Airspace Traffic Generator (ATG) being developed as part of VAST-RT, as well as other real-time tools. This capability has been demonstrated in a gate-to-gate simulation. VAST-RT's (Capability 2A) has been recently completed, and this paper will discuss the improved integration of the real-time assets into VAST-RT, including the development of tools to integrate data collected across the simulation environment into a single data set for the researcher. Current plans for the completion of the VAST-RT distributed simulation environment (Capability 2B) and its use to evaluate future airspace capacity enhancing concepts being developed by VAMS will be discussed. Additionally, the simulation environment's application to other airspace and airport research projects is addressed.

Lehmer, R.↗

Atomistic Method Applied to Computational Modeling of Surface Alloys

The formation of surface alloys is a growing research field that, in terms of the surface structure of multicomponent systems, defines the frontier both for experimental and theoretical techniques. Because of the impact that the formation of surface alloys has on surface properties, researchers need reliable methods to predict new surface alloys and to help interpret unknown structures. The structure of surface alloys and when, and even if, they form are largely unpredictable from the known properties of the participating elements. No unified theory or model to date can infer surface alloy structures from the constituents properties or their bulk alloy characteristics. In spite of these severe limitations, a growing catalogue of such systems has been developed during the last decade, and only recently are global theories being advanced to fully understand the phenomenon. None of the methods used in other areas of surface science can properly model even the already known cases. Aware of these limitations, the Computational Materials Group at the NASA Glenn Research Center at Lewis Field has developed a useful, computationally economical, and physically sound methodology to enable the systematic study of surface alloy formation in metals. This tool has been tested successfully on several known systems for which hard experimental evidence exists and has been used to predict ternary surface alloy formation (results to be published: Garces, J.E.; Bozzolo, G.; and Mosca, H.: Atomistic Modeling of Pd/Cu(100) Surface Alloy Formation. Surf. Sci., 2000 (in press); Mosca, H.; Garces J.E.; and Bozzolo, G.: Surface Ternary Alloys of (Cu,Au)/Ni(110). (Accepted for publication in Surf. Sci., 2000.); and Garces, J.E.; Bozzolo, G.; Mosca, H.; and Abel, P.: A New Approach for Atomistic Modeling of Pd/Cu(110) Surface Alloy Formation. (Submitted to Appl. Surf. Sci.)). Ternary alloy formation is a field yet to be fully explored experimentally. The computational tool, which is based on the BFS (Bozzolo, Ferrante, and Smith) method for the calculation of the energetics, consists of a small number of simple PCbased computer codes that deal with the different aspects of surface alloy formation. Two analysis modes are available within this package. The first mode provides an atom-by-atom description of real and virtual stages 1. during the process of surface alloying, based on the construction of catalogues of configurations where each configuration describes one possible atomic distribution. BFS analysis of this catalogue provides information on accessible states, possible ordering patterns, and details of island formation or film growth. More importantly, it provides insight into the evolution of the system. Software developed by the Computational Materials Group allows for the study of an arbitrary number of elements forming surface alloys, including an arbitrary number of surface atomic layers. The second mode involves large-scale temperature-dependent computer 2. simulations that use the BFS method for the energetics and provide information on the dynamic processes during surface alloying. These simulations require the implementation of Monte-Carlo-based codes with high efficiency within current workstation environments. This methodology capitalizes on the advantages of the BFS method: there are no restrictions on the number or type of elements or on the type of crystallographic structure considered. This removes any restrictions in the definition of the configuration catalogues used in the analytical calculations, thus allowing for the study of arbitrary ordering patterns, ultimately leading to the actual surface alloy structure. Moreover, the Monte Carlo numerical technique used for the large-scale simulations allows for a detailed visualization of the simulated process, the main advantage of this type of analysis being the ability to understand the underlying features that drive these processes. Because of the simplicity of the BFS method for e energetics used in these calculations, a detailed atom-by-atom analysis can be performed at any point in the simulation, providing necessary insight on the details of the process. The main objective of this research program is to develop a tool to guide experimenters in understanding and interpreting often unexpected results in alloy formation experiments. By reducing the computational effort without losing physical accuracy, we expect that powerful simulation tools will be developed in the immediate future, which will allow material scientists to easily visualize and analyze processes at a level not achievable experimentally.

Bozzolo, Guillermo H.↗

A fast, programmable hardware architecture for the processing of spaceborne SAR data

The development of high-throughput SAR processors (HTSPs) for the spaceborne SARs being planned by NASA, ESA, DFVLR, NASDA, and the Canadian Radarsat Project is discussed. The basic parameters and data-processing requirements of the SARs are listed in tables, and the principal problems are identified as real-operations rates in excess of 2 x 10 to the 9th/sec, I/O rates in excess of 8 x 10 to the 6th samples/sec, and control computation loads (as for range cell migration correction) as high as 1.4 x 10 to the 6th instructions/sec. A number of possible HTSP architectures are reviewed; host/array-processor (H/AP) and distributed-control/data-path (DCDP) architectures are examined in detail and illustrated with block diagrams; and a cost/speed comparison of these two architectures is presented. The H/AP approach is found to be adequate and economical for speeds below 1/200 of real time, while DCDP is more cost-effective above 1/50 of real time.

Bennett, J. R.↗

Fast calculation of the tokamak vertical instability

There has been recent interest in fast calculations of the tokamak axisymmetric vertical instability for real time feedback control purposes. It is shown that the maximum eigenvalue for the basic rigid version of this stability problem can be obtained by finding the positive root to a simple scalar function. This function can be generalized to include plasma mass and has complexity linear in the number of conductive elements. The formulation is based on standard matrix decompositions of the fixed-geometry part of the eigenproblem. The calculation bottleneck is the summary of mutual inductances from the reconstructed equilibrium current density. The with-mass spectrum can be made fully real-valued by the addition of a critical amount of damping with negligible effect on the vertical growth rate. Furthermore, the calculation has been implemented in the plasma control system at the DIII-D tokamak and used in experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Unique Results and Lessons Learned from the TSS Missions

In 1924, Irvin Langmuir and H. M. Mott-Smith published a theoretical model for the complex plasma sheath phenomenon in which they identified some very special cases which greatly simplified the sheath and allowed a closed solution to the problem. The most widely used application is for an electrostatic, or "Langmuir," probe in laboratory plasma. Although the Langmuir probe is physically simple (a biased wire) the theory describing its functional behavior and its current-voltage characteristic is extremely complex and, accordingly, a number of assumptions and approximations are used in the LMS model. These simplifications, correspondingly, place limits on the model's range of application. Adapting the LMS model to real-life conditions is the subject of numerous papers and dissertations. The Orbit-Motion Limited (OML) model that is widely used today is one of these adaptions that is a convenient means of calculating sheath effects. The OML equation for electron current collection by a positively biased body is simply: I is approximately equal to A x j(sub eo) x 2/√𝜋(phi)(exp ½) where A is the area of the body and phi is the electric potential on the body with respect to the plasma. Since the Langmuir probe is a simple biased wire immersed in plasma, it is particularly tempting to use the OML equation in calculating the characteristics of the long, highly biased wires of an Electric Sail in the solar wind plasma. However, in order to arrive at the OML equation, a number of additional simplifying assumptions and approximations (beyond those made by Langmuir-Mott-Smith) are necessary. The OML equation is a good approximation when all conditions are met, but it would appear that the Electric Sail problem lies outside of the limits of applicability.

Stone, Nobie H.↗

The Surface-Topography Challenge: A Multi-Laboratory Benchmark Study to Advance the Characterization of Topography

Surface performance is critically influenced by topography in virtually all real-world applications. The current standard practice is to describe topography using one of a few industry-standard parameters. The most commonly reported number is Ra, the average absolute deviation of the height from the mean line (at some, not necessarily known or specified, lateral length scale). However, other parameters, particularly those that are scale-dependent, influence surface and interfacial properties; for example the local surface slope is critical for visual appearance, friction, and wear. The present Surface-Topography Challenge was launched to raise awareness for the need of a multi-scale description, but also to assess the reliability of different metrology techniques. In the resulting international collaborative effort, 153 scientists and engineers from 64 research groups and companies across 20 countries characterized statistically equivalent samples from two different surfaces: a “rough” and a “smooth” surface. The results of the 2088 measurements constitute the most comprehensive surface description ever compiled. We find wide disagreement across measurements and techniques when the lateral scale of the measurement is ignored. Consensus is established through scale-dependent parameters while removing data that violates an established resolution criterion and deviates from the majority measurements at each length scale. Our findings suggest best practices for characterizing and specifying topography. The public release of the accumulated data and presented analyses enables global reuse for further scientific investigation and benchmarking.

42 ENGINEERING↗