Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “cloud phase”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Sea spray aerosol as a unique source of ice nucleating particles

Ice nucleating particles (INPs) are vital for ice initiation in, and precipitation from, mixed-phase clouds. A source of INPs from oceans within sea spray aerosol (SSA) emissions has been suggested in previous studies but remained unconfirmed. Here, we show that INPs are emitted using real wave breaking in a laboratory flume to produce SSA. The number concentrations of INPs from laboratory-generated SSA, when normalized to typical total aerosol number concentrations in the marine boundary layer, agree well with measurements from diverse regions over the oceans. Data in the present study are also in accord with previously published INP measurements made over remote ocean regions. INP number concentrations active within liquid water droplets increase exponentially in number with a decrease in temperature below 0 °C, averaging an order of magnitude increase per 5 °C interval. The plausibility of a strong increase in SSA INP emissions in association with phytoplankton blooms is also shown in laboratory simulations. Nevertheless, INP number concentrations, or active site densities approximated using “dry” geometric SSA surface areas, are a few orders of magnitude lower than corresponding concentrations or site densities in the surface boundary layer over continental regions. These findings have important implications for cloud radiative forcing and precipitation within low-level and midlevel marine clouds unaffected by continental INP sources, such as may occur over the Southern Ocean.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Simulated Polarimetric Fields of Ice Vapor Growth Using the Adaptive Habit Model. Part I: Large-Eddy Simulations

Abstract The bulk adaptive habit model (AHM) explicitly predicts ice particle aspect ratio, improving the representation of microphysical processes and properties, including ice–liquid-phase partitioning. With the unique ability to predict ice particle shape and density, the AHM is combined with an offline forward operator to produce fields of simulated polarimetric variables. An evaluation of AHM-forward-simulated dual-polarization radar signatures in an idealized Arctic mixed-phase cloud is presented. Interpretations of those signatures are provided through microphysical model output using the large-eddy simulation mode of the Weather Research and Forecasting Model. Vapor-grown ice properties are associated with distinct observable signatures in polarimetric radar variables, with clear sensitivities to the simulated ice particle properties, including ice number, size, and distribution shape. In contrast, the liquid droplet number has little influence on both polarimetric and microphysical variables in the case presented herein. Polarimetric quantities are sensitive to the dominating crystal habit type in a volume, with enhancements for aspect ratios much lower or higher than unity. This synthesis of a microphysical model and a polarimetric forward simulator is a first step in the evaluation of detailed AHM microphysics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Ice nucleation ability of loess from the northwestern United States

The heterogeneous nucleation of ice processes involving loess particles that influences the formation of mixed-phase clouds are poorly understood. Here, the ice nucleating ability of wind-blown dust or loess accumulated from the past glaciated area was investigated at three temperatures: -26, -30, and -34 °C and at below and above saturation with respect to liquid water conditions. Total six loess samples from different regions across Columbia Basin province, WA, USA were collected, dry dispersed, size-selected at mobility diameter 200 nm, and investigated for their ice nucleation efficiency. To understand the effect of atmospheric processing during long-range transport on their ice nucleating ability, similar experiments were also performed on acid-treated loess samples. Additionally, the ice nucleating properties of Arizona Test Dust (ATD) were investigated as a surrogate for natural mineral dust particles to test the experimental approach. Results show that treated particles have lower ice nucleation efficiency compared to untreated particles at all temperature and saturation with respect to liquid water conditions. Comparison based on ice-active site density ( N s ) metric indicate that loess particles at saturation with respect to liquid water conditions are marginally more efficient than the mineral and soil dust values reported in the literature, but they have lower efficiencies than the predicted N s efficiency of K-feldspar particles at supercooled temperatures greater than -38 °C.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Laboratory Investigation of Contact Freezing and the Aerosol to Ice Crystal Transformation Process

This project has been focused on the following objectives: 1. Investigations of the physical processes governing immersion versus contact nucleation, specifically surface-induced crystallization; 2. Development of a quadrupole particle trap with full thermodynamic control over the temperature range 0 to –40 °C and precisely controlled water vapor saturation ratios for continuous, single-particle measurement of the aerosol to ice crystal transformation process for realistic ice nuclei; 3. Understanding the role of ice nucleation in determining the microphysical properties of mixed-phase clouds, within a framework that allows bridging between laboratory and field measurements.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Development of Cloud and Precipitation Property Retrieval Algorithms and Measurement Simulators from ASR Data

What has made the ASR program unique is the amount of information that is available. The suite of recently deployed instruments significantly expands the scope of the program (Mather and Voyles, 2013). The breadth of this information allows us to pose sophisticated process-level questions. Our ASR project, now entering its third year, has been about developing algorithms that use this information in ways that fully exploit the new capacity of the ARM data streams. Using optimal estimation (OE) and Markov Chain Monte Carlo (MCMC) inversion techniques, we have developed methodologies that allow us to use multiple radar frequency Doppler spectra along with lidar and passive constraints where data streams can be added or subtracted efficiently and algorithms can be reformulated for various combinations of hydrometeors by exchanging sets of empirical coefficients. These methodologies have been applied to boundary layer clouds, mixed phase snow cloud systems, and cirrus.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Marine Ice Nuclei Collections – MAGIC (MAGIC-IN) Final Campaign Summary

This campaign augmented measurements obtained via deployment of the Atmospheric Radiation Measurement (ARM) Climate Research Facility’s ARM Mobile Facility (AMF) in the Marine ARM GPCI1 Investigation of Clouds (MAGIC) field campaign. The measurements, comprised of shipboard aerosol collections obtained during the five legs of the summer 2013 cruises, were sent for offline processing to measure ice nucleating particle (INP) number concentrations. The forty-three sample periods each represented, nominally, 24-hour segments during outbound and inbound transits of the Horizon Spirit. The samples were collected at locations between Los Angeles and Hawaii. Eight samples have been analyzed for immersion freezing temperature spectra thus far, using funding from other grants. Remaining samples are being frozen until support for further processing is obtained. Future analyses will investigate the inorganic/organic proportions of ice nuclei, in addition to determining the genetic composition of the overall biological community associated with INPs. Resulting correlations will be compared with other archived aerosol quantities, meteorological and ocean data (e.g., temperature, wind speed, sea surface temperature, etc…) and satellite ocean color products. These findings will ultimately aid in parameterizing oceanic (e.g., sea spray) INP emissions in regional and global scale models, when illustrating aerosol connections to cloud phases and properties. Independent future analyses of frozen filter samples, as proposed by collaborating investigators at the time of this report, will include single particle analyses of marine boundary layer aerosol compositions and morphology. The MAGIC-IN data are considered representative of the oligotrophic, low Chlorophyll-a (with the exception of near-shore) ocean regions, which exist along the MAGIC transect. Current analyses suggest that INP numbers in the marine boundary layer over this region are typically low, compared to existing measurements over marine areas and those collected in the laboratory as the result of realistic sea spray particle generation. These findings, along with separate studies, confirm the existence of highly variable emission sources for INP from oceans, (though weaker than land-based emissions at modestly cooled temperatures).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Examining the Ice-Nucleating Particles from the Southern Great Plains Field Campaign Report

The recent U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility field campaign, named Examining the Ice-Nucleating Particles from Southern Great Plains (ExINP-SGP), targeted experimentally characterizing abundance and other properties of ambient ice-nucleating particles (INPs) at the SGP site in Oklahoma (36° 36' 18" N, 97° 29' 6" W) during the period of October 1 to November 14, 2019. This campaign was funded through the DOE Office of Science Early Career Research Program (DE-SC0018979) as one of three major campaigns to be conducted at three ARM observatories, including the Eastern North Atlantic (ENA) station in 2020–2021 and North Slope of Alaska (NSA) site in 2021–2023, besides SGP. Different INP episodes were assessed to develop an SGP-relevant ice nucleation parameterization that would help understand convective and mixed-phase cloud systems typically observed in this region.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Ice processes in Antarctica: identification via multi-wavelength active and passive measurements and model evaluation (Final Report)

This project is based on new multi-frequency radar observations collected during the AWARE field campaign in 2016 at McMurdo Station by the ARM Mobile facility. Three scientific goals have been achieved. We have developed ice and mixed-phase cloud microphysics retrievals from multi-wavelength radar observations and ancillary observations, generally applicable at ARM sites. These technique generally better characterize the size of the ice crystals, their equivalent water content and the degree of riming better than using single wavelength techniques. We have characterized ice microphysical properties and ice processes via multi-frequency signatures. We have identified a unique mode in the McMurdo dataset appearing at quite cold temperature that we have attributed to riming processes. Triple frequency radar measurements unfortunately were available only for a short period but our work lays the foundation for building climatological and testing their replicability in models. Simultaneously case studies from the AWARE campaign have been exploited to evaluate and improve the NASA GISS ModelE3 climate model, including selection of case studies for combined goals of (i) running side-by-side using large-eddy simulation (LES) and ModelE3 in single-column model (SCM) mode and (ii) fingerprinting cloud processes in multi-wavelength radar observations. The different components of this work have contributed to 15 published papers with two currently under review.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

A comprehensive laboratory study on the immersion freezing behavior of illite NX particles. A comparison of 17 ice nucleation measurement techniques

Immersion freezing is the most relevant heterogeneous ice nucleation mechanism through which ice crystals are formed in mixed-phase clouds. In recent years, an increasing number of laboratory experiments utilizing a variety of instruments have examined immersion freezing activity of atmospherically relevant ice-nucleating particles. However, an intercomparison of these laboratory results is a difficult task because investigators have used different ice nucleation (IN) measurement methods to produce these results. A remaining challenge is to explore the sensitivity and accuracy of these techniques and to understand how the IN results are potentially influenced or biased by experimental parameters associated with these techniques. Within the framework of INUIT (Ice Nuclei Research Unit), we distributed an illite-rich sample (illite NX) as a representative surrogate for atmospheric mineral dust particles to investigators to perform immersion freezing experiments using different IN measurement methods and to obtain IN data as a function of particle concentration, temperature ( T ), cooling rate and nucleation time. A total of 17 measurement methods were involved in the data intercomparison. Experiments with seven instruments started with the test sample pre-suspended in water before cooling, while 10 other instruments employed water vapor condensation onto dry-dispersed particles followed by immersion freezing. The resulting comprehensive immersion freezing data set was evaluated using the ice nucleation active surface-site density, n s , to develop a representative n s ( T ) spectrum that spans a wide temperature range (-37 °C < T < -11 °C) and covers 9 orders of magnitude in n s . In general, the 17 immersion freezing measurement techniques deviate, within a range of about 8 °C in terms of temperature, by 3 orders of magnitude with respect to n s . In addition, we show evidence that the immersion freezing efficiency expressed in n s of illite NX particles is relatively independent of droplet size, particle mass in suspension, particle size and cooling rate during freezing. A strong temperature dependence and weak time and size dependence of the immersion freezing efficiency of illite-rich clay mineral particles enabled the n s parameterization solely as a function of temperature. We also characterized the n s ( T ) spectra and identified a section with a steep slope between -20 and -27 °C, where a large fraction of active sites of our test dust may trigger immersion freezing. This slope was followed by a region with a gentler slope at temperatures below -27 °C. While the agreement between different instruments was reasonable below ~ -27 °C, there seemed to be a different trend in the temperature-dependent ice nucleation activity from the suspension and dry-dispersed particle measurements for this mineral dust, in particular at higher temperatures. For instance, the ice nucleation activity expressed in n s was smaller for the average of the wet suspended samples and higher for the average of the dry-dispersed aerosol samples between about -27 and -18 °C. Only instruments making measurements with wet suspended samples were able to measure ice nucleation above -18 °C. A possible explanation for the deviation between -27 and -18 °C is discussed. Multiple exponential distribution fits in both linear and log space for both specific surface area-based n s ( T ) and geometric surface area-based n s ( T ) are provided. These new fits, constrained by using identical reference samples, will help to compare IN measurement methods that are not included in the present study and IN data from future IN instruments.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Analysis of isothermal and cooling-rate-dependent immersion freezing by a unifying stochastic ice nucleation model

Immersion freezing is an important ice nucleation pathway involved in the formation of cirrus and mixed-phase clouds. Laboratory immersion freezing experiments are necessary to determine the range in temperature, T , and relative humidity, RH, at which ice nucleation occurs and to quantify the associated nucleation kinetics. Typically, isothermal (applying a constant temperature) and cooling-rate-dependent immersion freezing experiments are conducted. In these experiments it is usually assumed that the droplets containing ice nucleating particles (INPs) all have the same INP surface area (ISA); however, the validity of this assumption or the impact it may have on analysis and interpretation of the experimental data is rarely questioned. Descriptions of ice active sites and variability of contact angles have been successfully formulated to describe ice nucleation experimental data in previous research; however, we consider the ability of a stochastic freezing model founded on classical nucleation theory to reproduce previous results and to explain experimental uncertainties and data scatter. A stochastic immersion freezing model based on first principles of statistics is presented, which accounts for variable ISA per droplet and uses parameters including the total number of droplets, N tot , and the heterogeneous ice nucleation rate coefficient, J het ( T ). This model is applied to address if (i) a time and ISA-dependent stochastic immersion freezing process can explain laboratory immersion freezing data for different experimental methods and (ii) the assumption that all droplets contain identical ISA is a valid conjecture with subsequent consequences for analysis and interpretation of immersion freezing. The simple stochastic model can reproduce the observed time and surface area dependence in immersion freezing experiments for a variety of methods such as: droplets on a cold-stage exposed to air or surrounded by an oil matrix, wind and acoustically levitated droplets, droplets in a continuous-flow diffusion chamber (CFDC), the Leipzig aerosol cloud interaction simulator (LACIS), and the aerosol interaction and dynamics in the atmosphere (AIDA) cloud chamber. Observed time-dependent isothermal frozen fractions exhibiting non-exponential behavior can be readily explained by this model considering varying ISA. An apparent cooling-rate dependence of J het is explained by assuming identical ISA in each droplet. When accounting for ISA variability, the cooling-rate dependence of ice nucleation kinetics vanishes as expected from classical nucleation theory. Finally, the model simulations allow for a quantitative experimental uncertainty analysis for parameters N tot , T , RH, and the ISA variability. We discuss the implications of our results for experimental analysis and interpretation of the immersion freezing process.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Physicochemical characterization and source apportionment of Arctic ice-nucleating particles observed in Ny-Ålesund in autumn 2019

Abstract. Ice-nucleating particles (INPs) initiate primary ice formation in Arctic mixed-phase clouds (MPCs), altering cloud radiative properties and modulating precipitation. For atmospheric INPs, the complexity of their spatiotemporal variations, heterogeneous sources, and evolution via intricate atmospheric interactions challenge the understanding of their impact on microphysical processes in Arctic MPCs and induce an uncertain representation in climate models. In this work, we performed a comprehensive analysis of atmospheric aerosols at the Arctic coastal site in Ny-Ålesund (Svalbard, Norway) from October to November 2019, including their ice nucleation ability, physicochemical properties, and potential sources. Overall, INP concentrations (NINP) during the observation season were approximately up to 3 orders of magnitude lower compared to the global average, with several samples showing degradation of NINP after heat treatment, implying the presence of proteinaceous INPs. Particle fluorescence was substantially associated with INP concentrations at warmer ice nucleation temperatures, indicating that in the far-reaching Arctic, aerosols of biogenic origin throughout the snow- and ice-free season may serve as important INP sources. In addition, case studies revealed the links between elevated NINP and heat lability, fluorescence, high wind speeds originating from the ocean, augmented concentration of coarse-mode particles, and abundant organics. Backward trajectory analysis demonstrated a potential connection between high-latitude dust sources and high INP concentrations, while prolonged air mass history over the ice pack was identified for most scant INP cases. The combination of the above analyses demonstrates that the abundance, physicochemical properties, and potential sources of INPs in the Arctic are highly variable despite its remote location.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Assessing the cloud radiative bias at Macquarie Island in the ACCESS-AM2 model

Abstract. As a long-standing problem in climate models, large positive shortwave radiation biases exist at the surface over the Southern Ocean, impacting the accurate simulation of sea surface temperature, atmospheric circulation, and precipitation. Underestimations of low-level cloud fraction and liquid water content are suggested to predominantly contribute to these radiation biases. Most model evaluations for radiation focus on summer and rely on satellite products, which have their own limitations. In this work, we use surface-based observations at Macquarie Island to provide the first long-term, seasonal evaluation of both downwelling surface shortwave and longwave radiation in the Australian Community Climate and Earth System Simulator Atmosphere-only Model version 2 (ACCESS-AM2) over the Southern Ocean. The capacity of the Clouds and the Earth’s Radiant Energy System (CERES) product to simulate radiation is also investigated. We utilize the novel lidar simulator, the Automatic Lidar and Ceilometer Framework (ALCF), and all-sky cloud camera observations of cloud fraction to investigate how radiation biases are influenced by cloud properties. Overall, we find an overestimation of +9.5±33.5 W m−2 for downwelling surface shortwave radiation fluxes and an underestimation of -2.3±13.5 W m−2 for downwelling surface longwave radiation in ACCESS-AM2 in all-sky conditions, with more pronounced shortwave biases of +25.0±48.0 W m−2 occurring in summer. CERES presents an overestimation of +8.0±18.0 W m−2 for the shortwave and an underestimation of -12.1±12.2 W m−2 for the longwave in all-sky conditions. For the cloud radiative effect (CRE) biases, there is an overestimation of +4.8±28.0 W m−2 in ACCESS-AM2 and an underestimation of -7.9±20.9 W m−2 in CERES. An overestimation of downwelling surface shortwave radiation is associated with an underestimated cloud fraction and low-level cloud occurrence. We suggest that modeled cloud phase is also having an impact on the radiation biases. Our results show that the ACCESS-AM2 model and CERES product require further development to reduce these radiation biases not just in shortwave and in all-sky conditions, but also in longwave and in clear-sky conditions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

The impact of aerosol mixing state on immersion freezing: insights from classical nucleation theory and particle-resolved simulations

Immersion freezing, initiated by ice-nucleating particles (INPs) in supercooled aqueous droplets, plays an important role in the formation of ice crystals within clouds. The efficiency of immersion freezing depends strongly on INP composition and, crucially, on the mixing state – how chemical species are distributed across the particle population. Here, we quantify the impact of aerosol mixing state on immersion freezing using a combined theoretical and particle-resolved modeling approach. We derive analytical expressions for the frozen fraction of internally and externally mixed INP populations based on classical nucleation theory, showing that the frozen fraction is sensitive to whether ice-active species are present in all particles or only in a subset of the population. We introduce a multi-species immersion freezing scheme into the particle-resolved model PartMC, using the water activity-based immersion freezing model (ABIFM) to compute freezing probabilities for mixed-composition particles. To improve computational efficiency, we implement a Binned Tau-Leaping algorithm and demonstrate an order-of-magnitude speedup with minimal accuracy loss. Simulations reproduce the analytical trends in limiting cases and extend the analysis to more general aerosol populations, where mixing state continues to exert a substantial control on frozen fraction. Sensitivity analyses across particle size, species type, and cooling condition reveal that the mixing state effect is most pronounced when small amounts of highly efficient INPs are mixed with less efficient materials. These findings underscore the need to represent aerosol mixing state explicitly in models of heterogeneous ice nucleation to reduce uncertainty in cloud-phase partitioning.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Retrieving microphysical properties of concurrent pristine ice and snow using polarimetric radar observations

Abstract. Ice and mixed-phase clouds play a key role in our climate system because of their strong controls on global precipitation and radiation budget. Their microphysical properties have been characterized commonly by polarimetric radar measurements. However, there remains a lack of robust estimates of microphysical properties of concurrent pristine ice and aggregates because larger snow aggregates often dominate the radar signal and mask contributions of smaller pristine ice crystals. This paper presents a new method that separates the scattering signals of pristine ice embedded in snow aggregates in scanning polarimetric radar observations and retrieves their respective abundances and sizes for the first time. This method, dubbed ENCORE-ice, is built on an iterative stochastic ensemble retrieval framework. It provides the number concentration, ice water content, and effective mean diameter of pristine ice and snow aggregates with uncertainty estimates. Evaluations against synthetic observations show that the overall retrieval biases in the combined total microphysical properties are within 5 % and that the errors with respect to the truth are well within the retrieval uncertainty. The partitioning between pristine ice and snow aggregates also agrees well with the truth. Additional evaluations against in situ cloud probe measurements from a recent campaign for a stratiform cloud system are promising. Our median retrievals have a bias of 98 % in the total ice number concentration and 44 % in the total ice water content. This performance is generally better than the retrieval from empirical relationships. The ability to separate signals of different ice species and to provide their quantitative microphysical properties will open up many research opportunities, such as secondary ice production studies and model evaluations for ice microphysical processes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Leveraging machine learning to enhance aerosol classification using Single-Particle Mass Spectrometry

Advancing automated classification of atmospheric aerosols from Single-Particle Mass Spectrometry (SPMS) data remains challenging due to overlapping ion signatures, compositional diversity, and limited labeled data. This study evaluates supervised and semi-supervised learning frameworks to enhance aerosol identification by jointly leveraging labeled and unlabeled spectra. Four models were compared: a supervised Support Vector Machine (SVM), a self-training SVM, a stacked autoencoder classifier, and a stacked autoencoder trained using a temporal-ensembling Mean Teacher approach. All models achieved high and stable accuracies (90.0 %–91.1 %), surpassing previous results on the same dataset (87 %) and matching the performance of state-of-the-art deep learning methods. Despite small global metric differences (≤ 1 %), semi-supervised variants yielded up to 5 %–10 % improvements for compositionally rare particle types – such as soot (0.77 % of spectra, F1-score: 0.93–0.97) and hazelnut pollen (0.98 % of spectra, F1-score: 0.97–1.00) – equating to roughly ∼ 187 additional correctly classified spectra. These gains are scientifically significant, as such rare particles exert disproportionate influence on radiative absorption and ice nucleation processes; their improved detection reduces modeled uncertainties in aerosol absorption optical depth and mixed-phase cloud ice nucleation rates. The models' residual misclassifications (≈ 9 %) largely arise from true spectral overlap among chemically adjacent species (e.g., Na- vs. K-feldspar, coated vs. uncoated feldspars), reflecting physical compositional continuity rather than algorithmic error. Collectively, these findings demonstrate that leveraging unlabeled data to learn robust spectral representations and refine classification enhances both fidelity and interpretability, bridging data-driven analysis with aerosol–climate process understanding.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

VISSTPX2DRECTG16V4MINNIS (c1)

Satellite-based retrievals of cloud and radiation properties are available in this value-added product provided by Bill Smith’s group at NASA/Langley using the VISST (Visible Infrared Solar-Infrared Split Window Technique) algorithm. This product contains VISST-derived pixel-level products from the GOES-16 satellite, rectilinear projection 2-D array.

broadband LW flux↗
NASA NTRS1984

Natural laminar flow experiments on modern airplane surfaces

Flight and wind-tunnel natural laminar flow experiments have been conducted on various lifting and nonlifting surfaces of several airplanes at unit Reynolds numbers between 0.63 x 10 to the 6th power/ft and 3.08 x 10 to the 6th power/ft, at Mach numbers from 0.1 to 0.7, and at lifting surface leading-edge sweep angles from 0 deg to 63 deg. The airplanes tested were selected to provide relatively stiff skin conditions, free from significant roughness and waviness, on smooth modern production-type airframes. The observed transition locations typically occurred downstream of the measured or calculated pressure peak locations for the test conditions involved. No discernible effects on transition due to surface waviness were observed on any of the surfaces tested. None of the measured heights of surface waviness exceeded the empirically predicted allowable surface waviness. Experimental results consistent with spanwise contamination criteria were observed. Large changes in flight-measured performance and stability and control resulted from loss of laminar flow by forced transition. Rain effects on the laminar boundary layer caused stick-fixed nose-down pitch-trim changes in two of the airplanes tested. No effect on transition was observed for flight through low-altitude liquid-phase clouds. These observations indicate the importance of fixed-transition tests as a standard flight testing procedure for modern smooth airframes.

Holmes, B. J.↗
NASA NTRS1989

Molecular and mass spectroscopic analysis of isotopically labeled organic residues

Experimental studies aimed at understanding the evolution of complex organic molecules on interstellar grains were performed. The photolysis of frozen gas mixtures of various compositions containing H2O, CO, NH3, and CH4 was studied. These species were chosen because of their astrophysical importance as deducted from observational as well as theoretical studies of ice mantles on interstellar grains. These ultraviolet photolyzed ices were warmed up in order to produce refractory organic molecules like the ones formed in molecular clouds when the icy mantles are being irradiated and warmed up either by a nearby stellar source or impulsive heating. The laboratory studies give estimates of the efficiency of production of such organic material under interstellar conditions. It is shown that the gradual carbonization of organic mantles in the diffuse cloud phase leads to higher and higher visual absorptivity - yellow residues become brown in the laboratory. The obtained results can be applied to explaining the organic components of comets and their relevance to the origin of life.

Mendoza-Gomez, Celia X.↗