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At least 343 records · Page 19

Scattering from nonspherical Chebyshev particles. II - Means of angular scattering patterns

The calculated angular scattering properties of over 250 randomly oriented nonspherical Chebyshev particles are examined for the effect of three factors: size; concavity vs convexity; and amount of deformation from a sphere. Both shape and size averaging are performed to reveal general features of the angular scattering not discernible for particular shapes and sizes. Comparisons with a comparably extensive experimental study published by Zerull in 1976 reveal remarkable qualitative similarities, even though Zerull used greatly different shapes from ours. This augurs well for the eventual development of a general theory of nonspherical scattering, although such a theory must account for concavity in addition to the amount of deviation from a sphere; and it cannot be entirely deterministic, as the third paper in this series will argue.

Wiscombe, Warren J.↗

Detecting And Characterizing Archetypes of Unintended Consequences in Engineered Systems

When designing engineered systems, the potential for unintended consequences of design policies or design decisions exists despite best intentions. Conditions that might cause the formation of unintended consequences are often known only in hindsight. However, since these conditions are associated with a single event, it is difficult to uncover the general patterns of conditions leading to unintended consequences. In this research, patterns of conditions associated with unintended consequences are learned from historical data and represented in the form of archetypes. While previous work using systems theoretic modeling has identified high-level archetypes, this work leverages a self-organizing map to learn archetypes of unintended consequences from human-tagged risk factors in a large data set of lessons learned from adverse events at NASA. The sixty-six identified archetypes contain patterns of conditions such as complexity and human-machine interaction associated with the formation of unintended consequences. To validate the archetypes, a sample of the archetypes is represented using system dynamics in order to illustrate that the identified archetypes are specialized versions of known high-level archetypes of unintended consequences. While the research is based upon a specific dataset, the archetypes apply to any engineered system and the pattern of leading indicators open a new path to manage unintended consequences and mitigate the magnitude of potentially adverse outcomes.

Hannah S Walsh↗

Field evaluation of zone temperature response to control actions in cooling systems of small and medium-sized office buildings

The response of zone temperature to control actions in heating, ventilation, and air conditioning (HVAC) systems, known as zone temperature response, has been a central focus of building control research owing to its crucial role in determining control performance. However, existing studies often overlook the representativeness of the buildings being studied, resulting in unclear generalizations. In addition, those studies tend to focus on a single aspect of the response. Furthermore, this paper provides the first comprehensive characterization of zone temperature response applicable to a clearly defined building sector—small and medium-sized office (SMO) buildings (<5000 m 2 ) in the US. Specifically, two representative SMO buildings, selected based on the US Department of Energy’s commercial prototype buildings, were studied. Field tests were conducted over a 2-month period during summer, and the collected data were analyzed with two key metrics—delay time and nonlinearity index—to quantify zone temperature response, capturing both short- and long-term patterns. Beyond this quantitative characterization, the analysis reveals that the HVAC system type, rather than factors like floor area or zone location, is the primary determinant of the zone temperature response. Drawing on the field test results, we recommend that building control strategies monitor zone temperatures at intervals shorter than 10 minutes, configure controls independently for VAV- and RTU-served zones, and implement nonlinear methods at the zone level—particularly for VAV zones—rather than across the entire building.

Building control↗

Deep learning model for fast, science-based forecasting of fluid migration along faults in geologic carbon storage scenarios

Effective long-term geologic storage depends on robust site selection and credible, science-based forecasting of subsurface behavior to ensure storage integrity. For this work, we develop a deep learning–based reduced-order model (ROM) to quantify potential carbon dioxide (CO₂) and brine migration through geological faults. The ROM combines a Transformer model for binary classification and a Stacked Ensemble for regression, trained on a comprehensive dataset generated from 1400 physics-based reservoir simulations. Key geologic and operational parameters—including fault geometry, reservoir structure, and injection conditions—were systematically varied to capture a wide range of fluid migration scenarios. The ROM accurately predicts the onset of migration, cumulative migration volumes of both CO₂ and brine, and associated migration rates, as compared to an independent set of validation simulations, while significantly reducing computational cost compared to traditional simulation methods. Model performance was evaluated across diverse fault configurations, revealing that shallow reservoir geometry and fault angle are among the most influential factors governing migration behavior. Sensitivity analysis using SHapley Additive exPlanations (SHAP) provided interpretability, revealing distinct patterns in how geological and operational features drive transient versus cumulative migration outcomes. The ROM’s ability to rapidly simulate fault migration scenarios enables efficient sensitivity analyses, scenario evaluations, and decision support for site selection and monitoring design. This approach enhances the safety, scalability, and long-term operational performance of geologic carbon storage (GCS) systems by providing a robust, interpretable tool for predicting subsurface fluid migration and assessing fault-related migration potential.

42 ENGINEERING↗

The low frequency sound from multipole sources in axisymmetric shear flows, with applications to jet noise

A closed-form solution for the sound radiation from multipole sources imbedded in an infinite cylindrical jet with an arbitrary velocity profile is obtained. It is valid in the limit where the wavelength is large compared with the jet radius. Simple formulae for the acoustic pressure field due to convected point sources are also obtained. The results show (in a simple way) how the mean flow affects the radiation pattern from the sources. For convected lateral quadrupoles it causes the exponent of the Doppler factor multiplying the far-field pressure signal to be increased from the value of 3 used by Lighthill to 5.

Goldstein, M. E.↗

The anatomy of an anomaly

An anomalous tonal pattern, apparently associated with the Beaver Creek oil field in central Wyoming, was identified using an MSS Band 5 to 4 ratio image made from digital LANDSAT data. This pattern was attributed to an increase in iron with rocks and/or soils which might have resulted from escaping hydrocarbons. The nature of this anomaly was investigated by producing several different combinations of band ratios and by conducting appropriate field studies. The results indicated (1) the existence of a well-defined oval feature related to exposure of iron-cemented red sandstones in a badlands topography, (2) a broader iron-influenced anomaly surrounding this feature, and (3) a spectral response of the rocks, soils, and alluvium making up this iron-colored surface that is readily distinguishable from that of iron-rich reddish Chugwater siltstones exposed in nearby anticlines. The general pattern of the broad anomaly extending beyond the Beaver Creek field is controlled by several factors including variations in vegetation (mainly sage and tall grasses), soil composition and moisture, and topography in addition to variations in iron content of the rock materials. From the available evidence, there is no provable correlation between the oval or the broad anomalies and the distribution of petroleum-producing structures or possible surface alteration effects related to uranium deposits known to occur within this region.

Short, N. M.↗

Low-level water vapor fields from the VAS split-window channels at 11 and 12 microns

Originally, the VAS split window channels were designed to use the differential water vapor absorption between 11 and 12 microns to estimate sea surface temperature by correcting for the radiometric losses caused by atmospheric moisture. It is shown that it is possible to reverse the procedure in order to estimate the vertically integrated low level moisture content with the background surface (skin) temperature removed, even over the bright, complex background of the land. Because the lower troposphere's water vapor content is an important factor in convective instability, the derived fields are of considerable value to mesoscale meteorology. Moisture patterns are available as quantitative fields (centimeters of precipitable water) at full VAS resolution (as fine as 7 kilometers horizontal resolution every 15 minutes), and are readily converted to image format for false color movies. The technique, demonstrated with GOES-5, uses a sequence of split window radiances taken once every 3 hours from dawn to dusk over the Eastern and Central United States. The algorithm is calibrated with the morning radiosonde sites embedded within the first VAS radiance field; then, entire moisture fields are calculated at all five observation times. Cloud contamination is removed by rejecting any pixel having a radiance less than the atmospheric brightness determined at the radiosonde sites.

Chesters, D.↗

Diagnosis of vertical motions from VAS retrievals during a convective outbreak

GOES-VAS satellite retrievals are used to investigate an intense convective outbreak over the Mississippi River Valley on 21-22 July 1982. The primary goals are to assess the strengths and weaknesses of three methods for computing vertical motion using satellite retrievals and to determine the effects of short interval observations on the calculations. Then, the vertical motions are incorporated with thermodynamic parameters to assess the usefulness of VAS data in delineating factors leading to storm formation. Results indicate that the quasi-geotrophic omega equation provided patterns and magnitudes most consistent with observed weather events and the 12 h radiosonde-derived motions. The vorticity method generally produced reasonable patterns, especially over the convective outbreak, although magnitudes were large due to its time derivative.

Funk, T. W.↗

Optical Detection Of Deformations Of An Antenna

Proposed control subsystem generates small aiming-bias signals to correct for deviations of 70-m-diameter reflector of microwave antenna from its ideal shape. Takes optical measurements to determine deformations produced by such environmental factors as wind, gravity, and thermal differentials. Using these measurements, subsystem estimates misalignment of radiation pattern caused by deformations. Signals to correct for estimated misalignment added to angle-command signals of main antenna-aiming system. To measure deviations laser ranging devices placed at base of feed on rigid intermediate reference structure, white retroreflectors placed on parts that deviate from assigned positions relative to intermediate reference structure.

Schumacher, L. L.↗

Heat and moisture flux modeling of the FIFE grassland canopy aided by satellite derived canopy variables

Satellite data corresponding to radiance variables are used to derive three canopy properties which describe slowly modulating boundary conditions of the interface between the biosphere and the atmosphere. The canopy properties are key factors in the regulation of heat and moisture transfer and are found to be radiance patterns within a homogeneous ecosystem. The physical modeling technique is enhanced by the satellite data, and the surface fluxes are represented more accurately in the resulting biosphere-interface model.

Smith, Eric A.↗

Aircraft Exceedances Vary According to Time of Day and Workload

The Flight Operational Quality Assurance (FOQA) programs have been implemented in US and Europe to identify anomalous flights based on data recorded on board an aircraft in an effort to improve flight safety. Numerous methods have been developed to support the analysis of FOQA data. However, it is unclear how FOQA data relates to the performance of the pilot. We sought to characterize the frequency and type of flight exceedances extracted from FOQA data during a controlled pilot schedule in order to determine whether patterns of exceedances related to human control of the aircraft would change according to scheduling factors.

flight data↗

Runway Configuration Management with Offline Reinforcement Learning

Runway configuration management (RCM) is a challenging task, and it affects the efficiency of the National Airspace System (NAS) and airport surface operations significantly. Each airport, depending on the geometry, capacity, local climate patterns, etc. has multiple configurations for the runway usage for arriving and departing flights. Many factors such as the incoming/outgoing traffic load, wind direction and speed, convective weather, cloud ceiling and other environmental factors might affect the choice of a runway configuration at any point in time. However, other factors such as safety measures and regulations, noise abatement, capacity of each configuration, and preference of the air traffic controllers (ATCs) can also play a significant role in selecting the configuration. A sub-optimal selection of the runway configuration, or delay in making configuration changes might result in significant increase in taxi times for aircraft on the surface of the airport, fuel and energy use of the aircraft, and maintenance costs. It can also lead to safety concerns, such as an aircraft performing one or more go-arounds before being able to land. All these factors make RCM an extremely important and challenging decision-making process for the ATCs. The current state of practice sets the runway configuration by the ATCs based on relevant information available at the time including weather, traffic, noise abatement, safety bounds, etc. This makes the decision-making process subjective based on the accuracy of the available information and the bias in human decision making. Unfortunately, this approach yields poor results (e.g., significant delays) if the predicted outcomes are uncertain and their relative impact is not well understood. This is especially evident when the uncertainty increases the size of possible predicted outcomes (combinatorial explosion in possible scenarios) that cannot be handled by human reasoning. On the other hand, an automated approach based on machine intelligence can make use of historical data and search through all (or significant amount of) possible scenarios under uncertainty and make well-informed decisions.

Milad Memarzadeh↗

Passenger Aggregation Network with Very Efficient Listing (PANVEL) Ridesharing Model for Urban Air Mobility

This paper introduces a ridesharing model useful for examining the role of ridesharing in advancing Urban Air Mobility (UAM) operations. Although the success of UAM will likely require a host of new technologies in aircraft design, airspace management, autonomy, and more, operational innovations like ridesharing may also be key, especially to lower operating costs and attract a broader market. The ridesharing algorithm introduced, termed the Passenger Aggregation Network with Very Efficient Listing (PANVEL) model, estimates trip numbers and passenger occupancy aboard particular aircraft within a UAM network in a metropolitan area. This algorithm is applied within a transportation computational framework to determine the impact of ridesharing on mode choice, passenger travel patterns, and transportation costs. The algorithm aggregates passengers traveling between identical origin-destination pairs, factoring in individual-specific metrics, such as value of time and alternative mode options, to generate high load factors on UAM aircraft. The computational framework simulates passenger mode-choice selections using an effective-cost approach to determine the number of ridesharing UAM-preferred trips, and results with ridesharing are representative of a rough upper bound on UAM ridership potential for a given metro area. A case study in the Cleveland metro area is presented to demonstrate the algorithm and assess ridesharing potential.

advanced air mobility↗

Passenger Aggregation Network with Very Efficient Listing (PANVEL) Ridesharing Model for Urban Air Mobility

This presentation introduces a ridesharing model useful for examining the role of ridesharing in advancing Urban Air Mobility (UAM) operations. Although the success of UAM will likely require a host of new technologies in aircraft design, airspace management, autonomy, and more, operational innovations like ridesharing may also be key, especially to lower operating costs and attract a broader market. The ridesharing algorithm introduced, termed the Passenger Aggregation Network with Very Efficient Listing (PANVEL) model, estimates trip numbers and passenger occupancy aboard particular aircraft within a UAM network in a metropolitan area. This algorithm is applied within a transportation computational framework to determine the impact of ridesharing on mode choice, passenger travel patterns, and transportation costs. The algorithm aggregates passengers traveling between identical origin-destination pairs, factoring in individual-specific metrics, such as value of time and alternative mode options, to generate high load factors on UAM aircraft. The computational framework simulates passenger mode-choice selections using an effective-cost approach to determine the number of ridesharing UAM-preferred trips, and results with ridesharing are representative of a rough upper bound on UAM ridership potential for a given metro area. A case study in the Cleveland metro area is presented to demonstrate the algorithm and assess ridesharing potential.

advanced air mobility↗

Cell-Mediated Immune Function and Cytokine Regulation During Space Flight

The changes in immune function which occur during space flight potentially expose the crews to an increased risk for development of illness. Decreased cellular immune function has been repeatedly documented after space flight and confirmed during flight by in vivo delayed-type hypersensitivity testing. However, correlation of immune changes with a clinically significant risk factor has not yet been performed. Our hypothesis is that space flight induces a decrease in cell-mediated immune function accompanied by a shift from a type 1 cytokine pattern (favoring cell-mediated immunity) to a type 2 cytokine pattern (favoring humoral immunity). We further hypothesize that reactivation of latent viruses will occur during space flight in association with the decreased cellular immunity. To test these hypotheses, we will determine the effects of space flight on cell-mediated immunity and viral reactivation. We will utilize delayed-type hypersensitivity testing as an in vivo measure of integrated cell-mediated immune function. The production of cytokines and immunoregulatory factors by lymphocytes and monocytes will be measured to determine whether changes in cytokine patterns are associated with the space flight-induced immune dysregulation. Correlation of antigen-specific immune changes with reactivation of latent herpes viruses will be determined by measuring peripheral levels of viral (CMV, VZV, EBV) antigen-specific T cells and comparing to the levels of EBV-infected B-cells by fluorescence in situ hybridization and flow cytometry. A comparison of cell-mediated immune function, cytokine regulation and viral reactivation will provide new insights into crew member health risks during flight.

Sams, Clarence F.↗

Detectability of Varied Hybridization Scenarios Using Genome-Scale Hybrid Detection Methods

Hybridization events complicate the accurate reconstruction of phylogenies, as they lead to patterns of genetic heritability that are unexpected under traditional, bifurcating models of species trees. This phenomenon has led to the development of methods to infer these varied hybridization events, both methods that reconstruct networks directly, as well as summary methods that predict individual hybridization events from a subset of taxa. However, a lack of empirical comparisons between methods – especially those pertaining to large networks with varied hybridization scenarios – hinders their practical use. Here, we provide a comprehensive review of popular summary methods: TICR, MSCquartets, HyDe, Patterson’s D-Statistic (ABBA-BABA), D3, and Dp. TICR and MSCquartets are based on quartet concordance factors gathered from gene tree topologies and HyDe, Patterson’s D-Statistic, D3, and Dp use site pattern frequencies to identify hybridization events between sets of three taxa. We then use simulated data to address questions of method accuracy and ideal use scenarios by testing methods against complex networks which depict gene flow events that differ in depth (timing), quantity (single vs. multiple, overlapping hybridizations), and rate of gene flow (γ). We find that deeper or multiple hybridization events may introduce noise and weaken the signal of hybridization, leading to higher relative false negative rates across all methods. Despite some forms of hybridization eluding quartet-based detection methods, MSCquartets displays high precision in most scenarios. While HyDe results in high false negative rates when tested on hybridizations involving extinct or unsampled ghost lineages, HyDe is the only method able to identify the direction of hybridization, distinguishing the source parental lineages from recipient hybrid lineages. Lastly, we test the methods on a dataset of ultraconserved elements from the bee subfamily Nomiinae, finding possible hybridization events between clades which correspond to regions of poor support in the species tree estimated in a previous study.

Bjorner, Marianne B.↗

Patterns of megafloral change across the Cretaceous-Tertiary boundary in the Northern Great Plains and Rocky Mountains

The spatial and temporal distribution of vegetation in the terminal Cretaceous of Western Interior North America was a complex mosaic resulting from the interaction of factors including a shifting coastline, tectonic activity, a mild, possibly deteriorating climate, dinosaur herbivory, local facies effects, and a hypothesized bolide impact. In order to achieve sufficient resolution to analyze this vegetational pattern, over 100 megafloral collecting sites were established, yielding approximately 15,000 specimens, in Upper Cretaceous and lower Paleocene strata in the Williston, Powder River, and Bighorn basins in North Dakota, Montana, and Wyoming. These localities were integrated into a lithostratigraphic framework that is based on detailed local reference sections and constrained by vertebrate and palynomorph biostratigraphy, magnetostratigraphy, and sedimentary facies analysis. A regional biostratigraphy based on well located and identified plant megafossils that can be used to address patterns of floral evolution, ecology, and extinction is the goal of this research. Results of the analyses are discussed.

Johnson, Kirk R.↗

Integrated Strategies for Overcoming Resolution Limits in Electron Beam Lithography of Chemically Amplified Resists

Electron beam lithography (EBL) of chemically amplified resists (CARs) faces fundamental challenges, including stochastic electron scattering and acid diffusion, that limit resolution and reproducibility. Using SU-8 as a model CAR, this study systematically investigated complementary strategies to address these challenges, combining multipass exposure, proximity effect correction (PEC) with midrange correction factors, base quencher incorporation, and post-exposure bake (PEB) suppression. Monte Carlo simulations and calibrated PEC modeling revealed that extending the point spread function to include a midrange scattering component significantly improved critical dimension (CD) control across varying pattern densities, correcting deviations that conventional two-term PEC failed to capture. Multipass exposure, particularly 4-pass writing with a 25% offset, redistributed the dose to average stochastic beam and scattering fluctuations, reducing line-width roughness by more than 50% and yielding more uniform nanoscale features. Photoacid confinement was investigated by adding urea as a base quencher, which successfully reduced acid diffusion but introduced substantial sensitivity penalties without improving ultimate resolution or Z-factor performance, underscoring the trade-offs of chemical versus physical confinement. Suppressing PEB most directly minimized acid diffusion, resulting in improved Z-factors and reproducible 30 nm half-pitch dense line/space patterns. Overall, these results demonstrated that PEC with midrange correction, multipass strategies, quencher additives, and PEB-free processing addresses different aspects of the EBL process window and that their integration provides a comprehensive framework for managing stochastic scattering, diffusion, and chemical amplification effects. This framework advances dense nanoscale patterning in CARs and establishes guiding principles for optimizing resist design and process strategies in high-resolution EBL and potentially other advanced lithographies, such as extreme ultraviolet (EUV) lithography.

36 MATERIALS SCIENCE↗