Results for “Data evaluation” — Page 89

NASA NTRS2004

Synergetic use of Aerosol Robotic Network (AERONET) and Moderate Image Spectrometer (MODIS)

I shall describe several distinct modes in which AERONET data are used in conjunction with MODIS data to evaluate the global aerosol system and its impact on climate. These includes: 1) Evaluation of the aerosol diurnal cycle not available from MODIS, and the relationship between the aerosol properties derived from MODIS and the daily average of these properties; 2) Climatology of the aerosol size distribution and single scattering albedo. The climatology is used to formulate the assumptions used in the MODIS look up tables used in the inversion of MODIS data; 3) Measurement of the aerosol effect on irradiation of the surface, this is used in conjunction with the MODIS evaluation of the aerosol effect at the TOA; and 4) Assessment of the aerosol baseline on top off which the satellite data are used to find the amount of dust or anthropogenic aerosol.

Kaufman, Y.↗

NASA NTRS1974

Conical isogrid adapter structural test results. Appendix C: Cylindrical isogrid structures

Analysis techniques and data for evaluating the load carrying capabilities of cylindrical isogrid structures subjected to compression and body bending loads are presented. Structural tests were conducted on a 120-inch diameter by 37-inch long cylindrical adapter. Photographs and drawings of the flanged isogrid adapter structure are included. The subjects considered are: (1) summary of the test data resulting from structural analysis, (2) techniques for predicting local and general instability, (3) a method for predicting extended local instability, (4) the effects of basic parameter and constant variations in extended local stability analysis, and (5) evaluation of effective skin width and compression buckling of skin panels on the basis of test data.

Source record↗

DOE OSTI2016

SNL API-653 In-Service Tank Inspection and Evaluation Tank ID: 981-A2-T0 (West)

An API Standard 653 In-Service inspection was completed on Tank 981-A2-T0 (West) located at the Sandia National Laboratories TAIV tank farm in Albuquerque, NM on September 22, 2015. The inspection was completed to collect data to evaluate the mechanical integrity and fitness for continued service of the tank. No indication or records of any previous inspection were identified for this tank. The inspection and engineering evaluation were completed using API-653, 5 th Edition and conservative engineering practices. The tank was not removed from service, so an internal inspection could not be completed. The tank was also fully insulated. The insulation was removed in specified areas of the tank shell and tank chime to accommodate an acoustic emission scan of the tank and an ultrasonic thickness evaluation of portions of the tank. The acoustic emission scan resulted in a grade of B / I - II indicating an overall TANKPAC grade B and composite grade II indicating minor active damage with highly concentrated sources related to corrosion found in the southeast and west side section of the tank. Eight Potential Localized Damage sources were found mainly in the west side (re-test in 2 years). The tank chime could not be inspected due to the configuration of the insulation welded angle support. An ultrasonic guided bulk wave inspection was completed on the tank shell to assess the lower shell section. At the time of the inspection the limited data collected showed minimal material loss from the shell at the thickness monitoring locations, however, visual inspection and pit depth gauge measurements showed > 3/16” inch pitting and significant general external surface corrosion on the shell at the shell to floor joint. This corrosion is caused by the insulation sheeting support welded angle iron trapping moisture and dirt against the tank shell. This tank should be removed from service, internally inspected, and repaired. Ultrasonic thickness measurement locations were established on this tank and the data is included in this report. The limited data collected indicated minimal material loss at these locations, with the only noted corrosion occurring on the tank shell to floor joint as noted above. An API-653 Annex B Evaluation of Tank Bottom Settlement was completed and the results are included in this report. No significant settlement issues were identified.

42 ENGINEERING↗

NASA NTRS1985

Evaluating software development by analysis of changes - Some data from the Software Engineering Laboratory

Basili and Weiss (1984) have discussed an approach for obtaining valid data which may be used to evaluate software development methodologies in a production environment. The methodology consists of five elements, including the identification of goals, the determination of questions of interest from the goals, the development of a data collection form, the development of data collection procedures, and the validation and analysis of the data. The current investigation is concerned with the presentation of the results from such an evaluation. The presented data were collected as part of studies reported by Basili et al. (1977). These studies had been conducted by NASA's Software Engineering Laboratory (SEL). Attention is given to an overview of the SEL, the application of the considered methodology, the results of a data analysis, and conclusions about the SEL environment.

Weiss, D. M.↗

DOE OSTI2013

Completion Report for Model Evaluation Well ER-11-2: Corrective Action Unit 98: Frenchman Flat

Model Evaluation Well ER-11-2 was drilled for the U.S. Department of Energy, National Nuclear Security Administration Nevada Site Office in support of Nevada Environmental Management Operations at the Nevada National Security Site (formerly known as the Nevada Test Site). The well was drilled in August 2012 as part of a model evaluation program in the Frenchman Flat area of Nye County, Nevada. The primary purpose of the well was to provide detailed geologic, hydrogeologic, chemical, and radionuclide data that can be used to test and build confidence in the applicability of the Frenchman Flat Corrective Action Unit flow and transport models for their intended purpose. In particular, this well was designed to provide data to evaluate the uncertainty in model forecasts of contaminant migration from the upgradient underground nuclear test PIN STRIPE, conducted in borehole U-11b in 1966. Well ER-11-2 will provide information that can be used to refine the Phase II Frenchman Flat hydrostratigraphic framework model if necessary, as well as to support future groundwater flow and transport modeling. The main 31.1-centimeter (cm) hole was drilled to a total depth of 399.6 meters (m). A completion casing string was not set in Well ER-11-2. However, a piezometer string was installed in the 31.1-cm open hole. The piezometer is composed of 7.3-cm stainless-steel tubing hung on 6.0-cm carbon-steel tubing via a crossover sub. The piezometer string was landed at 394.5 m, for monitoring the lower tuff confining unit. Data collected during and shortly after hole construction include composite drill cuttings samples collected every 3.0 m, various geophysical logs, water quality (including tritium and other test-related radionuclides) measurements, and water level measurements. The well penetrated 42.7 m of Quaternary and Tertiary alluvium and 356.9 m of Tertiary volcanic rock. The water-level measured in the piezometer string on September 25, 2012, was 353.8 m below ground surface. No tritium above levels detectable by field methods were encountered in this hole. No well development or hydrologic testing was conducted in this well immediately after completion, and future well development, sampling, and hydrologic testing planned for this well will be limited due to the diameter of the piezometer string. The stratigraphy, general lithology, and the water level are as expected, but the section of geology encountered is higher than expected due to faulting. No tritium above the minimum detection limit of the field equipment was detected because the target aquifer (the Topopah Spring aquifer) at Well ER-11-2 is structurally higher than expected and thus unsaturated.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2020

New measurements of gamma-ray energies and their absolute intensities from the decay of 231 Pa

Accurate nuclear data for the decay of 231 Pa is highly important for non-destructive analysis in the areas of radiochronometry and nuclear forensics. However, the evaluated nuclear data for this isotope is lacking; many previous measurements have large uncertainties and only two measurements are used to determine the absolute intensities. In this work, we present modern measurements of the major gamma-ray emissions from the decay of 231 Pa to 227 Ac including the energies and absolute intensities. For many of these measurements, the error envelopes have been significantly decreased compared to previous measurements, while remaining in good agreement. The absolute intensity of the 283 keV reference line was measured as 0.0163(2).

231Pa↗

NASA NTRS1974

Rhythmic variation in heart rate and respiration rate during space flight - Apollo 15

As part of the operational biomedical monitoring for Apollo manned missions, ECG and respiration rate are telemetered at selected intervals to mission control. The data were collected as part of this monitoring program. These data were evaluated for circadian and ultradian rhythmicity because of their uniqueness. The ability to detect and quantitate biorhythms in living systems during space flight is an important aspect of evaluating hypotheses concerning the underlying mechanisms of these phenomena. Circadian variation in heart rate during space flight is demonstrated here. In analyzing generated time series data it has been found that period discrimination is much better than the theoretical limit.

Rummel, J. A.↗

NASA NTRS1984

Large-scale analysis and forecast experiments with wind data from the Seasat A scatterometer

A series of data assimilation experiments is performed to assess the impact of Seasat A satellite scatterometer (SASS) wind data on Goddard Laboratory for Atmospheric Sciences (GLAS) model forecasts. The SASS data are dealiased as part of an objective analysis system utilizing a three-pass procedure. The impact of the SASS data is evaluated with and without temperature soundings from the NOAA 4 Vertical Temperature Profile Radiometer (VTPR) instrument in order to study possible redundancy between surface wind data and upper air temperature data. In the northern hemisphere the SASS data are generally found to have a negligible effect on the forecasts. In the southern hemisphere the forecast impact from SASS data is somewhat larger and primarily beneficial in the absence of VTPR data. However, the inclusion of VTPR data effectively eliminates the positive impact over Australia and South America. This indicates that SASS data can be beneficial for numerical weather prediction in regions with large data gaps, but in the presence of satellite soundings the usefulness of SASS data is significantly reduced.

Baker, W. E.↗

NASA NTRS2001

Inter-Comparison of GOES-8 Imager and Sounder Skin Temperature Retrievals

Skin temperature (ST) retrievals derived from geostationary satellite observations have both high temporal and spatial resolutions and are therefore useful for applications such as assimilation into mesoscale forecast models, nowcasting, and diagnostic studies. Our retrieval method uses a Physical Split Window technique requiring at least two channels within the longwave infrared window. On current GOES satellites, including GOES-11, there are two Imager channels within the required spectral interval. However, beginning with the GOES-M satellite the 12-um channel will be removed, leaving only one longwave channel. The Sounder instrument will continue to have three channels within the longwave window, and therefore ST retrievals will be derived from Sounder measurements. This research compares retrievals from the two instruments and evaluates the effects of the spatial resolution and sensor calibration differences on the retrievals. Both Imager and Sounder retrievals are compared to ground-truth data to evaluate the overall accuracy of the technique. An analysis of GOES-8 and GOES-11 intercomparisons is also presented.

Haines, Stephanie L.↗

NASA NTRS2004

A Numerical Simulation and Statistical Modeling of High Intensity Radiated Fields Experiment Data

Tests are conducted on a quad-redundant fault tolerant flight control computer to establish upset characteristics of an avionics system in an electromagnetic field. A numerical simulation and statistical model are described in this work to analyze the open loop experiment data collected in the reverberation chamber at NASA LaRC as a part of an effort to examine the effects of electromagnetic interference on fly-by-wire aircraft control systems. By comparing thousands of simulation and model outputs, the models that best describe the data are first identified and then a systematic statistical analysis is performed on the data. All of these efforts are combined which culminate in an extrapolation of values that are in turn used to support previous efforts used in evaluating the data.

Smith, Laura J.↗

DOE OSTI2017

Nuclear Data Sheets for A=40

The experimental nuclear structure data and decay data are evaluated for the known nuclides of mass 40 (Mg, Al, Si, P, S, Cl, Ar, K, Ca, Sc, Ti). Detailed evaluated nuclear structure information is presented with the best values recommended for level energies, half-lives, γ-ray energies and intensities, decay properties (energies, intensities and placement of radiations), and other spectroscopic data. The {sup 40}Ca and {sup 40}K nuclides remain as the most extensively studied from many different reactions and decays; no excited states are known in {sup 40}Mg, {sup 40}Al, {sup 40}P and {sup 40}Ti. This work supersedes the earlier full evaluation of A=40 by J. Cameron and B. Singh (2004Ca38).

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2014

Benchmarking of Methods for Genomic Taxonomy

One of the first issues that emerges when a prokaryotic organism of interest is encountered is the question of what it is—that is, which species it is. The 16S rRNA gene formed the basis of the first method for sequence-based taxonomy and has had a tremendous impact on the field of microbiology. Nevertheless, the method has been found to have a number of shortcomings. In this paper, we trained and benchmarked five methods for whole-genome sequence-based prokaryotic species identification on a common data set of complete genomes: (i) SpeciesFinder, which is based on the complete 16S rRNA gene; (ii) Reads2Type that searches for species-specific 50-mers in either the 16S rRNA gene or the gyrB gene (for the Enterobacteraceae family); (iii) the ribosomal multilocus sequence typing (rMLST) method that samples up to 53 ribosomal genes; (iv) TaxonomyFinder, which is based on species-specific functional protein domain profiles; and finally (v) KmerFinder, which examines the number of cooccurring k-mers (substrings of k nucleotides in DNA sequence data). The performances of the methods were subsequently evaluated on three data sets of short sequence reads or draft genomes from public databases. In total, the evaluation sets constituted sequence data from more than 11,000 isolates covering 159 genera and 243 species. Our results indicate that methods that sample only chromosomal, core genes have difficulties in distinguishing closely related species which only recently diverged. Finally, the KmerFinder method had the overall highest accuracy and correctly identified from 93% to 97% of the isolates in the evaluations sets.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Recent Developments in Hydrogeologic Applications for Strain Tensor Analyses

Changes in fluid pressure deform porous media and this effect occurs in a variety of hydrogeologic processes, from the change in storage during pumping or injection to fluctuations in water levels caused by barometric pressure. We have developed instruments for measuring small strains in porous media, and we have used the resulting strain data to evaluate well testing, hydraulic fracturing, manual loading at the ground surface, and ambient hydrologic processes, like rainfall and evaporation. A particularly important application is the use of strain tensor data measured at shallow depths to analyze well tests or hydraulic fractures conducted at much greater depths. An early demonstration of this technique was conducted at the North Avant Field north of Tulsa, Oklahoma, where Pennsylvanian sandstone creates a confined aquifer and oil reservoir at a depth of 530m. We have showed that the strains caused by injecting into the aquifer could be measured at a depth of 30m and used to evaluate the properties of the aquifer. We recently expanded the array of strainmeters at the North Avant Field by deploying three more instruments at shallow depth (30m) along with a deep instrument at 520m depth in the winter, 2021. The deep instrument is deployed in shale caprock slightly above the aquifer. To our knowledge, the deep strainmeter at the North Avant Field is the deepest strainmeter ever deployed and this required refining methods originally developed for shallow deployments. The instrument was lowered to depth on oil field tubing and cemented in place using techniques and materials developed for use in oil wells. Optical fiber used to communicate with the instrument was cemented in the annulus on the outside of tubing. This is significant because the techniques we used could readily be extended to greater depth, suggesting that strainmeters can be deployed over a wide range of depths for monitoring critical subsurface processes. For example, it suggests that strainmeters could be deployed through the caprock to monitor for leaks from underlying CO2 storage reservoirs. The strainmeter array at the North Avant Field has been used to characterize deformation during a series of injection tests in the spring and summer, 2021. All the new strainmeters respond to pumping, and the strainmeters we installed earlier also responded. To our knowledge, this is the first application of well testing in a deep aquifer that was monitored by an array of strainmeters—our earlier work used strainmeters at a single location. We are currently analyzing the strain data using an analytical solution, a proxy-based Bayesian inversion algorithm, and other methods. Strainmeter data has also been used to characterize periodic pumping tests by us and Riley Blais. A periodically varying pumping rate causes both hydraulic head and strain signals that vary with the same period as the pumping. The peaks and troughs of the head in monitoring wells lag behind the peaks and troughs of the head in the pumping well, and this lag time increases with distance from the pumping well. The lag time of the pressure and the distance to the monitoring well can be used in a simple analysis to estimate the hydraulic diffusivity of the aquifer. The lag time determined from strain data can be used to estimate aquifer properties using the same analysis that works for the pressure only for strain data measured at particular locations. That is because the strain field in a confining unit advances upward, laterally and then downward even though the pressure in the underlying aquifer only advances laterally, according to our recent simulations. We have field data showing that a small periodic signal superimposed on an injection rate at the North Avant Field will create a periodic strain signal at shallow strainmeters. The field data and the recent simulations suggest that including a periodic component to injection or pumping and then monitoring the resulting strain signal could be a way to monitor the subsurface.

Murdoch, Larry↗

DOE OSTI2023

Recent Developments in Hydrogeologic Applications for Strain Tensor Analyses

Changes in fluid pressure deform porous media and this effect occurs in a variety of hydrogeologic processes, from the change in storage during pumping or injection to fluctuations in water levels caused by barometric pressure. We have developed instruments for measuring small strains in porous media, and we have used the resulting strain data to evaluate well testing, hydraulic fracturing, manual loading at the ground surface, and ambient hydrologic processes, like rainfall and evaporation. A particularly important application is the use of strain tensor data measured at shallow depths to analyze well tests or hydraulic fractures conducted at much greater depths. An early demonstration of this technique was conducted at the North Avant Field north of Tulsa, Oklahoma, where Pennsylvanian sandstone creates a confined aquifer and oil reservoir at a depth of 530m. We have showed that the strains caused by injecting into the aquifer could be measured at a depth of 30m and used to evaluate the properties of the aquifer. We recently expanded the array of strainmeters at the North Avant Field by deploying three more instruments at shallow depth (30m) along with a deep instrument at 520m depth in the winter, 2021. The deep instrument is deployed in shale caprock slightly above the aquifer. To our knowledge, the deep strainmeter at the North Avant Field is the deepest strainmeter ever deployed and this required refining methods originally developed for shallow deployments. The instrument was lowered to depth on oil field tubing and cemented in place using techniques and materials developed for use in oil wells. Optical fiber used to communicate with the instrument was cemented in the annulus on the outside of tubing. This is significant because the techniques we used could readily be extended to greater depth, suggesting that strainmeters can be deployed over a wide range of depths for monitoring critical subsurface processes. For example, it suggests that strainmeters could be deployed through the caprock to monitor for leaks from underlying CO2 storage reservoirs. The strainmeter array at the North Avant Field has been used to characterize deformation during a series of injection tests in the spring and summer, 2021. All the new strainmeters respond to pumping, and the strainmeters we installed earlier also responded. To our knowledge, this is the first application of well testing in a deep aquifer that was monitored by an array of strainmeters—our earlier work used strainmeters at a single location. We are currently analyzing the strain data using an analytical solution, a proxy-based Bayesian inversion algorithm, and other methods. Strainmeter data has also been used to characterize periodic pumping tests by us and Riley Blais. A periodically varying pumping rate causes both hydraulic head and strain signals that vary with the same period as the pumping. The peaks and troughs of the head in monitoring wells lag behind the peaks and troughs of the head in the pumping well, and this lag time increases with distance from the pumping well. The lag time of the pressure and the distance to the monitoring well can be used in a simple analysis to estimate the hydraulic diffusivity of the aquifer. The lag time determined from strain data can be used to estimate aquifer properties using the same analysis that works for the pressure only for strain data measured at particular locations. That is because the strain field in a confining unit advances upward, laterally and then downward even though the pressure in the underlying aquifer only advances laterally, according to our recent simulations. We have field data showing that a small periodic signal superimposed on an injection rate at the North Avant Field will create a periodic strain signal at shallow strainmeters. The field data and the recent simulations suggest that including a periodic component to injection or pumping and then monitoring the resulting strain signal could be a way to monitor the subsurface.

Murdoch, Larry↗

NASA NTRSDate not supplied

Rapid Assessment of a Lunar Surface Laboratory Module

Johnson Space Center is piloting an innovation team known as the Forge to perform rapid turnaround, concurrent engineering studies. The Forge is intended to be able to pull together a team of strategically selected domain experts to innovatively solve a specified problem within a short period of time. The Forge’s inaugural project being the development of a Lunar Surface Laboratory Module concept. The lab module is intended as an option for the Artemis program’s Lunar Architecture Team. The lab module may allow for increased science productivity and return on investment than a surface architecture with only the habitat. This paper will discuss the configuration of the Lunar Laboratory module, including the pressure vessel, its placement relative to the Surface Habitat and Pressurized Rover, and internal architecture. In order to determine the suitability of such a design, a human factors evaluation is conducted. Historically, a human factors evaluation of a habitable volume could require a month or longer, including time needed to prepare a test plan, conduct the evaluation, compile the data, and produce a report. The entire Forge effort will only last for five weeks, forcing the creation of a rapid assessment process. This rapid assessment includes three evaluation studies, all conducted and processed in the space of a single day, to determine the acceptability of the resulting design. The first evaluation is a card sort evaluation of the laboratory instruments. A brief discussion of the card sort evaluation is provided. This card sort is focused on the relative positioning of the laboratory instruments, determining whether a given instrument should be adjacent to, or separated from, another. It will use human factors personnel and both life and physical scientists as subject matter experts. The second evaluation is a science productivity tabletop evaluation. This evaluation focuses on the selection of instruments and the number of instruments, attempting to assess the amount of work the crew will be able to use the facility to do. It uses life and physical science personnel as subject matter experts. The third evaluation is a CAD or Virtual Reality human factors walkthrough evaluation. This evaluation focuses on the layout of the lab module and its connectivity to the basecamp’s pressurized elements. If possible, astronauts will be used as subject matter experts. Each of these evaluations will focus primarily on objective data with limited subjective comments, reducing the time required for processing responses. The results of each evaluation and their implications will be discussed. Based on the evaluation data, an overall acceptability of the Lunar Surface Laboratory Module produced by the Forge study can be determined. Lessons learned and recommendations for future use of the human factors rapid assessment process in early design trades will also be provided.

Lunar Laboratory↗

DOE OSTI2024

Self‐Potential Tomography Preconditioned by Particle Swarm Optimization—Application to Monitoring Hyporheic Exchange in a Bedrock River

Abstract A self‐potential (SP) data‐inversion algorithm was developed and tested on an analytical model of electrical‐potential profile data attributed to single and multiple polarized electrical sources. The developed algorithm was then validated by an application to SP‐monitoring field data measured on the floodplain of East Fork Poplar Creek, Oak Ridge, Tennessee, to image electrical sources in areas conducive to preferential flow into the flood plain from the bedrock‐lined riverbed. The algorithm combined stochastic source‐localization by particle‐swarm‐optimization (PSO) of electrical sources characterized by simplified geometries with source tomography by regularized weighted least‐squares minimization of a quadratic objective function. Prior information was incorporated by preconditioning the tomography algorithm by PSO results. Variable percentages of random noise were added to analytical‐model data to evaluate the algorithm performance. Results indicated that true parameters of single‐source models were inverted and approximated with small residual error, whereas inversion of analytical‐model data representing multiple electrical sources accurately approximated the locations of the sources but miscalculated some parameters because of the non‐uniqueness of the inverse‐model solution. Source tomography applied to analytical model data during testing produced a spatially continuous parameter field that identified the locations of point‐scale synthetic dipole sources of electrical current flow with varying degrees of accuracy depending on the prior information incorporated into the tomography. When applied to SP‐monitoring field data, the algorithm imaged electrical sources within a known fault that intersects the bedrock riverbed and flood plain of East Fork Poplar Creek and depicted dynamic electrical conditions attributed to hyporheic exchange.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

MultiTaskDeltaNet: change detection-based image segmentation for operando ETEM with application to carbon gasification kinetics

Transforming in situ transmission electron microscopy (TEM) imaging into a tool for spatially-resolved operando characterization of solid-state reactions requires automated, high-precision semantic segmentation of dynamically evolving features. However, traditional deep learning methods for semantic segmentation often face limitations due to the scarcity of labeled data, visually ambiguous features of interest, and scenarios involving small objects. To tackle these challenges, we introduce MultiTaskDeltaNet (MTDN), a novel deep learning architecture that creatively reconceptualizes the segmentation task as a change detection problem. By implementing a unique Siamese network with a U-Net backbone and using paired images to capture feature changes, MTDN effectively leverages minimal data to produce high-quality segmentations. Furthermore, MTDN utilizes a multi-task learning strategy to exploit correlations between physical features of interest. In an evaluation using data from in situ environmental TEM (ETEM) videos of filamentous carbon gasification, MTDN demonstrated a significant advantage over conventional segmentation models, particularly in accurately delineating fine structural features. Notably, MTDN achieved a 10.22% performance improvement over conventional segmentation models in predicting small and visually ambiguous physical features. This work bridges key gaps between deep learning and practical TEM image analysis, advancing automated characterization of nanomaterials in complex experimental settings.

08 HYDROGEN↗

DOE OSTI2025

Extension of Complex Refractive Index Measurements to the Near-Infrared for Liquids: Methodology and Uncertainty Analysis

Optical identification of liquid droplets, aerosols, or thin films is important for many applications. While reference spectra are sometimes available for such measurements, they are not always applicable to the observed spectrum or the given sample morphology. Reference spectra for many forms can be modeled, however, if the n/k vectors (real and imaginary refractive indices) are available. In previous work we have reported protocols to determine the n/k vectors for dozens of liquids, primarily in the mid-infrared (MIR) spectral range from 7500 to 400 cm –1 . In this work we extend the spectral range into the near-infrared (NIR) region, demonstrating a method to measure and merge the data sets to create composite n/k data ranging from 10 000 to 400 cm –1 (1.0 to 25 µm) with absorbance fidelity spanning over four orders of magnitude, and vastly improved signal-to-noise in the NIR. The precision of the composite data is evaluated for three different liquids, focusing primarily on the steps for converting the raw absorbance spectra to k values. The variability in both MIR and NIR data as well as in the final n/k vectors is also investigated for several liquids. For typical liquids, the overall variability (reported as 2σ) in the final n and k-vectors is determined to be ∼0.4% and 3%, respectively. Finally, the derived n/k data are used to calculate absorbance spectra for aerosol droplets, showing marginal variability due to the typical measurement errors in the final n/k vectors.

47 OTHER INSTRUMENTATION↗