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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

BOSC 2025, the 26th Bioinformatics Open Source Conference

The 26th annual Bioinformatics Open Source Conference (BOSC 2025, open-bio.org/events/bosc-2025) brought its community-driven focus on open-source bioinformatics and open science to the 2025 conference on Intelligent Systems for Molecular Biology and the European Conference on Computational Biology (ISMB/ECCB 2025). Since its launch in 2000, BOSC has been the premier annual meeting covering open-source bioinformatics and open science. Framed by two keynote addresses and a thought-provoking panel discussion, the two-day conference included sessions dedicated to open data, analytic tools and pipelines, workflow platforms, knowledge representation, and the application of AI/ML. The first keynote talk was delivered by Christine Orengo: “Working together to develop, promote and protect our data resources: Lessons learnt developing CATH and TED.” A joint session with the Bio-Ontologies and Knowledge Representation (BOKR) track the second day of BOSC started with a keynote talk by Chris Mungall entitled “Open Knowledge Bases in the Age of Generative AI”. A closing panel on Data Sustainability, moderated by Mónica Muñoz Torres, featured panelists Scott Edmunds, Varsha Khodiyar, Tony Burdett, Nicky Mulder, and Chris Mungall. This year, the CollaborationFest collaborative work event that typically precedes or follows ISMB was incorporated as part of the main conference and organized by BOSC with help from the Function and 3D-SIG tracks.

bioinformatics↗
NASA NTRS2005

The Beauty and Complexity of the Brunt Ice Shelf from MOA and ICESat

Beginning in February 2003, NASA's Ice, Cloud, and land Elevation Satellite (ICESat) has determined surface elevations from approx. 86degN to 86degS latitude. To date, altimetry data have been acquired in a series of observation periods in repeated track patterns using all three Geoscience Laser Altimeter System (GLAS) lasers. This paper will focus on ice shelf elevation data that were obtained in 2003 across the Brunt Ice Shelf and the Stancomb-Wills Ice Tongue. Integrating the altimetry with the recently available MODIS Mosaic of Antarctica (MOA), quantifies the relative accuracy and precision of the resulting ice shelf elevations. Furthermore, the elevation data was processed onto an elevation grid, by regional interpolation across the area s complex glacial features only. Ice thickness estimation from the altimetry of the floating ice is discussed. ICESat operates at 40Hz and its elevation data is obtained every 172m along track. These elevations have a relative accuracy of about 14cm based on the standard deviation of low-slope crossover differences and a precision of close to 2cm for the Laser 2a, Release 21, GLA12 data used here.

Humbert, Angelika↗
NASA NTRSDate not supplied

Satellite Tracking of Shallow Cumulus during CAMP2Ex: The Aerosol and Organization Connection

Shallow moist convection is ubiquitous throughout the tropics and represents a key player in boundary layer processes. Shallow clouds come in many forms, from scattered, short-lived cumulus to organized features that include cold pool boundaries and lines reaching O(100 km) scale lasting several hours. In this study, we explore how cloud morphology and environmental aerosol affect shallow cumulus lifecycle properties. Measuring such influences requires a broad, detailed view of these cloud fields as they grow and decay. Geostationary satellites provide a means to follow the clouds with enhanced spatiotemporal sampling from space. We apply a cloud-tracking tool to study lifecycle properties of shallow cumulus sampled during the NASA Cloud, Aerosol, and Monsoon Processes Philippines Experiment (CAMP2Ex) field campaign of 2019. The mission conducted airborne and shipborne operations over the West Pacific Ocean, in tandem with Rapid Scan imagery from the Advanced Himawari Imager (AHI) on the Japan Meteorological Agency’s (JMA) Himawari-8 satellite. We segment shallow cumulus on AHI 0.5-km visible reflectance during the daylit hours of several research flights that exhibited ideal atmospheric conditions for tracking. We collect the resulting cloud tracks by regions containing airborne sampling of the cloud environments and by two specific segmentation techniques: one optimized for small, disorganized cumulus and the other for larger, organized clouds using suitable thresholds for reflectance and blurring. We present an analysis of cloud lifecycle properties using our dual segmentation approach for various sampled environments of CAMP2Ex. A total of 7 research flights (RFs) exhibited ideal conditions for generating cloud-track ensembles under similar thermodynamic and kinematic profiles but with varying aerosol load. We consider lifetime, track-achieved metrics, and ensemble-fitted growth rates to evaluate the aerosol effect. Cloud elongation, a factor in cloud morphology, is also considered for any potential influence in observed shifts in growth rates. The results suggest that aerosol affects cloud lifecycles more significantly for clouds with larger areas and independent of the elongation factor.

Cloud Tracking↗
DOE OSTI2023

Two Large-Scale Meteorological Patterns are Associated with Short-Duration Dry Spells in the Northeastern United States

Large-scale meteorological pattern (LSMP)–based analysis is used in a novel way to understand meteorological conditions before and during short-duration dry spells over the northeastern United States. These LSMPs are useful to assess models and select better-performing models for future projections. Dry-spell events are identified from histograms of consecutive dry days below a daily precipitation threshold. Events lasting 12 days or longer, which correspond to ~10% of dry-spell events, are examined. The 500-hPa stream-function anomaly fields for the first 12 days of each event are time averaged, and k -means clustering is applied to isolate the dry-spell-related LSMPs. The first cluster has a strong low pressure anomaly over the Atlantic Ocean, southeast of the region, and is more common in winter and spring. The second cluster has strong high pressure over east-central North America and is most common during autumn. Over the region, both clusters have negative specific humidity anomalies, negative integrated vapor transport from the north, and subsidence associated with a midlatitude jet stream dipole structure that reinforces upper-level convergence. Subsidence is supported by cold-air advection in the first cluster and the location on the east side of the lower-level high pressure in the second cluster. Extratropical cyclone storm tracks are generally shifted southward of the region during the dry spells. Individual events lie on a continuum between two distinct clusters. These clusters have similar local, but different remote, properties. Although dry spells occur with greater frequency during drought months, most dry spells occur during nondrought months. Significance Statement: This study examines the large-scale weather patterns and meteorological conditions associated with dry-spell events lasting at least 2 weeks while affecting the northeastern United States. A statistical approach groups events together on the basis of similar atmospheric features. We find two distinct sets of patterns that we call large-scale meteorological patterns. These patterns reduce moisture, foster localized sinking, and shift the storm track southward along the Atlantic seaboard, all of which reduce precipitation. Besides greater understanding, knowing the meteorological patterns during short-term dryness in the region provides an important tool to assess how well atmospheric models reproduce these specific patterns. More dry spells occur in non-drought months than in drought months, which means that dry spells can occur without preexisting drought conditions.

58 GEOSCIENCES↗
DOE OSTI2024

Aerial drone fleet deployment optimization with endogenous battery replacements for direct delivery of time-sensitive products

Aerial drones offer a distinct potential to reduce the delivery time and energy consumption for the delivery of time-sensitive and small products. However, there is still a need in the relevant industry to understand the performance of drone-based delivery under different business needs and drone operating conditions. We studied a drone deployment optimization problem for direct delivery of time-sensitive products with release dates to customers maintaining a specified time window. This paper presents a new mixed-integer programming model, new valid inequalities, a new greedy heuristic algorithm, and a Genetic algorithm to help business owners optimally schedule and route their drone fleet minimizing the required fleet size, the required number of additional batteries, and total energy consumption. A realistic feature of the optimization method is that instead of replacing the drone battery after each return to the depot, it keeps track of the remaining energy in the drone battery and decides on battery replacements accounting for the drone routing and the user-specified minimum required battery energy. Numerical results based on real data from drone flight tests and prepared food delivery industry provide insights into the effect of different practical drone operating parameters on the required fleet size, the required number of battery replacements, and energy consumption. Here, results demonstrate that the proposed heuristic algorithm substantially outperforms the accelerated CPLEX in runtime while sacrificing the solution quality by a small amount. Additionally, results show that using a mixed fleet of hexacopter and quadcopter drones reduces the total energy consumption by 48.52% compared to using a homogeneous fleet of only hexacopters.

Drone energy consumption↗
DOE OSTI2020

Heterogeneous data-processing optimization with CLARA’s adaptive workflow orchestrator

The hardware landscape used in HEP and NP is changing from homogeneous multi-core systems towards heterogeneous systems with many different computing units, each with their own characteristics. To achieve maximum performance with data processing, the main challenge is to place the right computing on the right hardware. In this paper, we discuss CLAS12 charge particle tracking workflow orchestration that allows us to utilize both CPU and GPU to improve the performance. The tracking application algorithm was decomposed into micro-services that are deployed on CPU and GPU processing units, where the best features of both are intelligently combined to achieve maximum performance. In this heterogeneous environment, CLARA aims to match the requirements of each micro-service to the strength of a CPU or a GPU architecture. A predefined execution of a micro-service on a CPU or a GPU may not be the most optimal solution due to the streaming data-quantum size and the data-quantum transfer latency between CPU and GPU. So, the CLARA workflow orchestrator is designed to dynamically assign micro-service execution to a CPU or a GPU, based on the online benchmark results analyzed for a period of real-time data-processing.

Gyurjyan, Vardan↗
DOE OSTI2020

Evolution of ferroelastic domain walls during phase transitions in barium titanate nanoparticles

In this work, ferroelastic domain walls inside BaTiO 3 (BTO) tetragonal nanocrystals are distinguished by Bragg peak position and studied with Bragg coherent x-ray diffraction imaging (BCDI). Convergence-related features of the BCDI method for strongly phased objects are reported. A ferroelastic domain wall inside a BTO crystal has been tracked and imaged across the tetragonal-cubic phase transition and proves to be reversible. The linear relationship of relative displacement between two twin domains with temperature is measured and shows a different slope for heating and cooling, while the tetragonality reproduces well over temperature changes in both directions. An edge dislocation is also observed and found to annihilate when heating the crystal close to the phase transition temperature.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

ACDC (Automated Campbell Diagram Code) [SWR-26-042]

This application provides a web-based graphical user interface to generating Campbell Diagrams and visualizing mode shapes for OpenFAST turbine models. Determining the aeroelastic stability and dynamic characteristics of wind turbines is a critical step in turbine design and analysis. Historically, extracting natural frequencies and mode shapes from OpenFAST—the industry-standard whole-turbine simulation code—has been a fragmented and tedious process. It required manual model configuration, command-line linearization execution, and complex post-processing via proprietary scripts to handle rotating-frame dynamics. To address these workflow bottlenecks, we present the Automated Campbell Diagram Code (ACDC), an open-source graphical software tool developed by the National Laboratory of the Rockies (NLR) under the DOE-funded Distributed Wind Aeroelastic Modeling (dWAM) project. ACDC streamlines the end-to-end linearization and stability analysis workflow into a single, intuitive cross-platform application. The software guides users through OpenFAST model configuration, definition of operating points, and the automated execution of steady-state trim and linearization simulations. Under the hood, ACDC automates the complex mathematical post-processing steps required for rotating systems, including Multi-Blade Coordinate (MBC) transformations, eigenanalysis, and advanced modal tracking utilizing the Modal Assurance Criterion (MAC) and spectral clustering. Finally, ACDC processes these results to automatically generate Campbell diagrams and features a robust 3D visualization engine to animate full-system mode shapes. By eliminating the reliance on external post-processing environments and manual data manipulation, ACDC significantly accelerates dynamic analysis and lowers the barrier to entry for wind energy researchers and engineers.

Summerville, Brent [National Laboratory of the Roc↗
NASA NTRS1972

Nonlinear and adaptive estimation in reentry.

The problem of real-time estimation of a lifting reentry vehicle trajectory of the shuttle orbiter type is considered. Simulations feature large position and velocity uncertainties at radar acquisition and realistic model errors in lift, drag and other model parameters. Radar tracking and accelerometer data are simulated. Significant nonlinearities are found to exist on spacecraft acquisition. An iterated nonlinear filter is shown to perform optimally during the radar acquisition phase. An adaptive filter is shown to track time-varying model errors, such as errors in the lift and drag coefficients, down to the noise level. Such real-time model tracking (identification) is frequently required for guidance and control implementation.

Jazwinski, A. H.↗
NASA NTRS1983

Remote sensing with spaceborne synthetic aperture imaging radars: A review

A review is given of remote sensing with Spaceborne Synthetic Aperture Radars (SAR's). In 1978, a spaceborne SA was flown on the SEASAT satellite. It acquired high resulution images over many regions in North America and the North Pacific. The acquired data clearly demonstrate the capability of spaceborne SARs to: image and track polar ice floes; image ocean surface patterns including swells, internal waves, current boundaries, weather boundaries and vessels; and image land features which are used to acquire information about the surface geology and land cover. In 1981, another SAR was flown on the second shuttle flight. This Shuttle Imaging Radar (SIR-A) acquired land and ocean images over many areas around the world. The emphasis of the SIR-A experiment was mainly toward geologic mapping. Some of the key results of the SIR-A experiment are given.

Cimino, J. B.↗
NASA NTRS1986

Measurements of hydrogen and helium isotopes in Galactic cosmic rays from 1978 through 1984

The propagation of light cosmic rays is examined using measurements of the relative abundances of the isotopes H-1, H-2 and He-3 and He-4 made with the ISEE 3 instrumentation. It is believed that cosmic ray particles experience spallation in traveling through the interstellar medium, thereby producing the isotopes examined in the present study. The isotopic ratios are therefore expected to yield data on outward migrating particles, which lose energy while moving toward extragalactic space, i.e., the 'leaky box approximation'. The energy ranges covered are 26-138 MeV/nucleon for H-1 and He-4, 24-89 MeV/nucleon for H-2 and 43-146 MeV/nucleon for He-3. Solar activity ranged from minimum to maximum over the observational period. Details of the experimental strategies, instrumentation features and calibration techniques employed with the particle detectors are provided. Histograms were geneated of the energies attributable to each particle track and mass ratios of the various isotopes were calculated over the measured energy ranges. Account was taken of errors introduced by solar modulation, and an escape path length of 5.6-7.8 g/sq cm was estimated for particle propagation through the Galaxy. The projected path length agrees with previous estimates based on data from heavier cosmic ray nuclei.

Kroeger, R.↗
NASA NTRS1997

Wake Vortex Field Measurement Program at Memphis, Tennessee: Data Guide

Eliminating or reducing current restrictions in the air traffic control system due to wake vortex considerations would yield increased capacity, decreased delays, and cost savings. Current wake vortex separation standards are widely viewed as very conservative under most conditions. However, scientific uncertainty about wake vortex behavior under different atmospheric conditions remains a barrier to development of an adaptive vortex spacing system. The objective of the wake vortex field measurement efforts during December, 1994 and August, 1995 at Memphis, TN were to record wake vortex behavior for varying atmospheric conditions and types of aircraft. This effort is part of a larger effort by the NASA Langley Research Center to develop an Aircraft Vortex Spacing System (AVOSS) as an element of the Terminal Area Productivity (TAP) program. The TAP program is being performed in concert with the FAA Terminal Air Traffic Control Automation (TATCA) program and ATC Automation. Wake vortex behavior was observed using a mobile continuous-wave (CW) coherent laser Doppler radar (lidar) developed at Lincoln Laboratory. This lidar features a number of improvements over previous systems, including the first-ever demonstration of an automatic wake vortex detection and tracking algorithm.

Campbell, S. D.↗
NASA NTRS2000

Evaluation of Bogus Vortex Techniques with Four-Dimensional Variational Data Assimilation

The effectiveness of techniques for creating "bogus" vortices in numerical simulations of hurricanes is examined by using the Penn State/NCAR nonhydrostatic mesoscale model (MM5) and its adjoint system. A series of four-dimensional variational data assimilation (4-D VAR) experiments is conducted to generate an initial vortex for Hurricane Georges (1998) in the Atlantic Ocean by assimilating bogus sea-level pressure and surface wind information into the mesoscale numerical model. Several different strategies are tested for improving the vortex representation. The initial vortices produced by the 4-D VAR technique are able to reproduce many of the structural features of mature hurricanes. The vortices also result in significant improvements to the hurricane forecasts in terms of both intensity and track. In particular, with assimilation of only bogus sea-level pressure information, the response in the wind field is contained largely within the divergent component, with strong convergence leading to strong upward motion near the center. Although the intensity of the initial vortex seems to be well represented, a dramatic spin down of the storm occurs within the first 6 h of the forecast. With assimilation of bogus surface wind data only, an expected dominance of the rotational component of the wind field is generated, but the minimum pressure is adjusted inadequately compared to the actual hurricane minimum pressure. Only when both the bogus surface pressure and wind information are assimilated together does the model produce a vortex that represents the actual intensity of the hurricane and results in significant improvements to forecasts of both hurricane intensity and track.

Pu, Zhao-Xia↗
NASA NTRS2006

NASA Solar Array Demonstrates Commercial Potential

A state-of-the-art solar-panel array demonstration site at NASA's Dryden Flight Research Center provides a unique opportunity for studying the latest in high-efficiency solar photovoltaic cells. This five-kilowatt solar-array site (see Figure 1) is a technology-transfer and commercialization success for NASA. Among the solar cells at this site are cells of a type that was developed in Dryden Flight Research Center s Environmental Research Aircraft and Sensor Technology (ERAST) program for use in NASA s Helios solar-powered airplane. This cell type, now denoted as A-300, has since been transferred to SunPower Corporation of Sunnyvale, California, enabling mass production of the cells for the commercial market. High efficiency separates these advanced cells from typical previously commercially available solar cells: Whereas typical previously commercially available cells are 12 to 15 percent efficient at converting sunlight to electricity, these advanced cells exhibit efficiencies approaching 23 percent. The increase in efficiency is due largely to the routing of electrical connections behind the cells (see Figure 2). This approach to increasing efficiency originated as a solution to the problem of maximizing the degree of utilization of the limited space available atop the wing of the Helios airplane. In retrospect, the solar cells in use at this site could be used on Helios, but the best cells otherwise commercially available could not be so used, because of their lower efficiencies. Historically, solar cells have been fabricated by use of methods that are common in the semiconductor industry. One of these methods includes the use of photolithography to define the rear electrical-contact features - diffusions, contact openings, and fingers. SunPower uses these methods to produce the advanced cells. To reduce fabrication costs, SunPower continues to explore new methods to define the rear electrical-contact features. The equipment at the demonstration site includes two fixed-angle solar arrays and one single-axis Sun-tracking array. One of the fixed arrays contains typical less-efficient commercial solar cells and is being used as a baseline for comparison of the other fixed array, which contains the advanced cells. The Sun-tracking array tilts to follow the Sun, using an advanced, real-time tracking device rather than customary pre-programmed mechanisms. Part of the purpose served by the demonstration is to enable determination of any potential advantage of a tracking array over a fixed array. The arrays are monitored remotely on a computer that displays pertinent information regarding the functioning of the arrays.

Creech, Gray↗
NASA NTRS2004

Passive IFF: Autonomous Nonintrusive Rapid Identification of Friendly Assets

A proposed optoelectronic instrument would identify targets rapidly, without need to radiate an interrogating signal, apply identifying marks to the targets, or equip the targets with transponders. The instrument was conceived as an identification, friend or foe (IFF) system in a battlefield setting, where it would be part of a targeting system for weapons, by providing rapid identification for aimed weapons to help in deciding whether and when to trigger them. The instrument could also be adapted to law-enforcement and industrial applications in which it is necessary to rapidly identify objects in view. The instrument would comprise mainly an optical correlator and a neural processor (see figure). The inherent parallel-processing speed and capability of the optical correlator would be exploited to obtain rapid identification of a set of probable targets within a scene of interest and to define regions within the scene for the neural processor to analyze. The neural processor would then concentrate on each region selected by the optical correlator in an effort to identify the target. Depending on whether or not a target was recognized by comparison of its image data with data in an internal database on which the neural processor was trained, the processor would generate an identifying signal (typically, friend or foe ). The time taken for this identification process would be less than the time needed by a human or robotic gunner to acquire a view of, and aim at, a target. An optical correlator that has been under development for several years and that has been demonstrated to be capable of tracking a cruise missile might be considered a prototype of the optical correlator in the proposed IFF instrument. This optical correlator features a 512-by-512-pixel input image frame and operates at an input frame rate of 60 Hz. It includes a spatial light modulator (SLM) for video-to-optical image conversion, a pair of precise lenses to effect Fourier transforms, a filter SLM for digital-to-optical correlation-filter data conversion, and a charge-coupled device (CCD) for detection of correlation peaks. In operation, the input scene grabbed by a video sensor is streamed into the input SLM. Precomputed correlation-filter data files representative of known targets are then downloaded and sequenced into the filter SLM at a rate of 1,000 Hz. When there occurs a match between the input target data and one of the known-target data files, the CCD detects a correlation peak at the location of the target. Distortion- invariant correlation filters from a bank of such filters are then sequenced through the optical correlator for each input frame. The net result is the rapid preliminary recognition of one or a few targets.

Moynihan, Philip↗
NASA NTRS2012

Adaptive Trajectory Prediction Algorithm for Climbing Flights

Aircraft climb trajectories are difficult to predict, and large errors in these predictions reduce the potential operational benefits of some advanced features for NextGen. The algorithm described in this paper improves climb trajectory prediction accuracy by adjusting trajectory predictions based on observed track data. It utilizes rate-of-climb and airspeed measurements derived from position data to dynamically adjust the aircraft weight modeled for trajectory predictions. In simulations with weight uncertainty, the algorithm is able to adapt to within 3 percent of the actual gross weight within two minutes of the initial adaptation. The root-mean-square of altitude errors for five-minute predictions was reduced by 73 percent. Conflict detection performance also improved, with a 15 percent reduction in missed alerts and a 10 percent reduction in false alerts. In a simulation with climb speed capture intent and weight uncertainty, the algorithm improved climb trajectory prediction accuracy by up to 30 percent and conflict detection performance, reducing missed and false alerts by up to 10 percent.

Seperation Assurance↗
NASA NTRS1990

Precise tracking of remote sensing satellites with the Global Positioning System

The Global Positioning System (GPS) can be applied in a number of ways to track remote sensing satellites at altitudes below 3000 km with accuracies of better than 10 cm. All techniques use a precise global network of GPS ground receivers operating in concert with a receiver aboard the user satellite, and all estimate the user orbit, GPS orbits, and selected ground locations simultaneously. The GPS orbit solutions are always dynamic, relying on the laws of motion, while the user orbit solution can range from purely dynamic to purely kinematic (geometric). Two variations show considerable promise. The first one features an optimal synthesis of dynamics and kinematics in the user solution, while the second introduces a novel gravity model adjustment technique to exploit data from repeat ground tracks. These techniques, to be demonstrated on the Topex/Poseidon mission in 1992, will offer subdecimeter tracking accuracy for dynamically unpredictable satellites down to the lowest orbital altitudes.

Yunck, Thomas P.↗
DOE OSTI2023

Modeling of standing wave RF cavities for tracking through multi-pass energy recovery linac

Short bunches, high current and multiple linac pass are all characteristics of Energy Recovery Linacs (ERLs), which may result in collective effects. They in turn, may affect the beam, degrading its quality, or even yield to instabilities causing a beam loss. To study and mitigate these effects one needs a numerical simulation code, that can take into account both the collective effects, as well as, particular ERL features, such as a multi-turn design that does not reach a steady state or the multiple passages of the beam through Radio-Frequency (RF) cavities at different energies. CODAL [1], a code developed by SOLEIL in collaboration with IJCLab, enables such studies. It is a 6 dimensional (6D) tracking code applying 'kicks' based on the integration of the local Hamiltonian for each element of the lattice. It is also capable of simulating space charge, wakefields and coherent synchrotron radiation. However, to correctly take into account the ERL dynamics, an upgrade had to be made to include the effect of a standing wave RF cavity in 6D. In this paper, we will concentrate on the implementation and benchmarking (with DESY’s tracking code ASTRA [2]) of both the longitudinal and the transverse models (by J.B. Rosenzweig and L. Serafini [3]), which we use to carry out tracking of fully analytical 6D RF cavity.

Bogacz, A.↗