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At least 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Supervisory Control and Data Acquisition for Electrochemical Separation Experimentation

The Python-based program is a laboratory automation tool designed to control and monitor electrochemical systems. The tool was developed for capacitive deionization (CDI) experiments, but it can be used for any system that requires controlled voltage or current segments and multi-parameter monitoring. The program integrates hardware components to run user-defined experimental parameters, providing operational control of a programmable power supply, peristaltic pump, and data acquisition devices. Currently, the program is structured with a workflow that includes an initialization (or pre-run) phase, a main loop, and a post-experiment stabilization (or post-run) phase. The initialization phase prepares and stabilizes the cell, ensuring that the electrodes and solution reach a baseline state before the experiment begins. The main loop consists of multiple voltage segments that repeat, controlling the experiment while recording key parameters such as time, voltage, current, pH, and conductivity. Finally, the post-experiment stabilization phase allows the system to stabilize after the experiment, returning the cell and solution to equilibrium conditions before ending the sequence. The program is designed with four variations, each tailored to different experimental needs. All variations include both the initialization and post-experiment stabilization stages, which run for a set amount of time, voltage, current, and flow rate before and after the main experiment block. The main loop runs for a set number of cycles, as defined by the user input, and each cycle is composed of 2 or 4 segments. The 4 program variations are described as follows: Program 1: The main program includes 2 segments. Each segment is defined to have a set duration, flow rate, voltage, and current. This program measures conductivity, flow rate, voltage, and current. Program 2: The main program expands Program 1 to include 4 segments. Each segment has a specified duration, flow rate, voltage, and current. Like Program 1, it measures conductivity, flow rate, voltage, and current. Program 3: The main program consists of 2 segments, each defined by time, flow rate, voltage, and current. In addition to conductivity, flow rate, voltage, and current, Program 3 collects pH and temperature data through a 4-channel data acquisition device. Program 4: This program independently controls two channels of a multi-channel power supply simultaneously. While conductivity can only be measured for one cell at a time, the dual-channel control makes it possible to operate two cells simultaneously under different voltage/current conditions. The main program includes 2 segments.For each program, all measurements are automatically logged and integrated into a single Excel output file. Data are displayed in numerical format and plotted, both in real time, to track system performance. A key feature of the program is its ability to synchronize all outputs so that every measurement shares a single timestamp, ensuring accurate alignment of voltage, current, pH, conductivity, and pH data.By combining hardware control, real-time monitoring, and unified data collection, this program significantly reduces manual workload and minimizes errors, making it a reliable platform for researchers, engineers, and laboratory technicians conducting CDI experiments, among other electrochemical tests.

Valentino, Lauren [Argonne National Laboratory (AN↗
DOE OSTI2023

Comparison of ozone formation attribution techniques in the northeastern United States

The Integrated Source Apportionment Method (ISAM) has been revised in the Community Multiscale Air Quality (CMAQ) model. This work updates ISAM to maximize its flexibility, particularly for ozone (O 3 ) modeling, by providing multiple attribution options, including products inheriting attribution fully from nitrogen oxide reactants, fully from volatile organic compound (VOC) reactants, equally from all reactants, or dynamically from NO x or VOC reactants based on the indicator gross production ratio of hydrogen peroxide (H 2 O 2 ) to nitric acid (HNO 3 ). The updated ISAM has been incorporated into the most recent publicly accessible versions of CMAQ (v5.3.2 and beyond). This study's primary objective is to document these ISAM updates and demonstrate their impacts on source apportionment results for O 3 and its precursors. Additionally, the ISAM results are compared with the Ozone Source Apportionment Technology (OSAT) in the Comprehensive Air-quality Model with Extensions (CAMx) and the brute-force method (BF). All comparisons are performed for a 4 km horizontal grid resolution application over the northeastern US for a selected 2 d summer case study (9 and 10 August 2018). General similarities among ISAM, OSAT, and BF results add credibility to the new ISAM algorithms. However, some discrepancies in magnitude or relative proportions among tracked sources illustrate the distinct features of each approach, while others may be related to differences in model formulation of chemical and physical processes. Despite these differences, OSAT and ISAM still provide useful apportionment data by identifying the geographical and temporal contributions of O 3 and its precursors. Both OSAT and ISAM attribute the majority of O 3 and NO x contributions to boundary, mobile, and biogenic sources, whereas the top three contributors to VOCs are found to be biogenic, boundary, and area sources.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1986

Cloud-top meridional momentum transports on Saturn and Jupiter

Cloud-tracked wind measurements reported by Sromovsky et al. were analyzed to determine meridional momentum transports in Saturn's northern middle latitudes. Results are expressed in terms of eastward and northward velocity components (u and v), and eddy components u and v. At most latitudes between 13 and 44 deg N (planetocentric), the transport by the mean flow ( ) is measurably southward, tending to support Saturn's large equatorial jet, and completely dominating the eddy transport. Meridional velocities are near zero at the peak of the relatively weak westward jet; along the flanks of that jet, measurements indicate divergent flow out of the jet. In this region the dominant eddy transport ( ) is northward on the north side of the jet, but not resolvable on the south side. Eddy transports at most other latitudes are not significantly different from measurement error. The conversion of eddy kinetic energy to mean kinetic energy, indicated by the correlation between and d /dy (where y is meridional distance) is clearly smaller than various values reported for Jupiter, and not significantly different from zero. Both Jovian and Saturnian results may be biased by the tendency for cloud tracking to favor high contrast features, and thus may not be entirely representative of the cloud level motions as a whole.

Stromovsky, L. A.↗
NASA NTRS1989

Application of precomputed control laws in a reconfigurable aircraft flight control system

A self-repairing flight control system concept in which the control law is reconfigured after actuator and/or control surface damage to preserve stability and pilot command tracking is described. A key feature of the controller is reconfigurable multivariable feedback. The feedback gains are designed off-line and scheduled as a function of the aircraft control impairment status so that reconfiguration is performed simply by updating the gain schedule after detection of an impairment. A novel aspect of the gain schedule design procedure is that the schedule is calculated using a linear quadratic optimization-based simultaneous stabilization algorithm in which the scheduled gain is constrained to stabilize a collection of plant models representing the aircraft in various control failure modes. A description and numerical evaluation of a controller design for a model of a statically unstable high-performance aircraft are given.

Moerder, Daniel D.↗
NASA NTRS1992

Flows around sunspots and pores

Observations are reported yielding high-resolution white-light data regarding the flow pattern of penumbral material and granules around sunspots and pores. The data are culled from optical observations near the limit of the telescope modulation transfer function, and correlation tracking is employed to track the motions of penumbral features and granules. Dark fibrils and bright grains in the sunspots' inner penumbra regions move toward the umbra, and the opposite occurs in the outer penumbra. Before pore formation and during the pores existence granular flows are found to converge on the features. The paper also details the evolution of an emerging flux region, and two types of photospheric dark alignments are described in the region of new flux emergence.

Wang, Haimin↗
NASA NTRS1998

Velocity Estimates of Fast-Moving Outlet Glaciers on the Greenland Ice Sheet

In recent years, airborne laser altimetry has been used with great success to investigate the mass balance characteristics of the Greenland ice sheet. One spinoff of this activity has been the application of these measurements to the study of surface velocities in some of Greenland's fast-moving drainage glaciers. This is accomplished by tracking the motion of elevation features, primarily crevasses, in pairs of aircraft laser altimetry surveys. Detailed elevation measurements are made along or across glaciers of interest with a scanning swath of 150 to 200 meters, and the surveys are repeated several days later, typically to within better than 50 meters of the previous flight line. Surface elevation features are identified in each image, and their offsets are compared yielding detailed velocities over narrow regions. During the 1998 field season, repeat flights were made over three glaciers for the purpose of estimating their surface velocities. These were the Kangerdlugssuaq and Helheim glaciers on the east coast and the Jakobshavn Isbrae on the west coast. Each flows at such high speeds (on the order of a few kilometers per year) that their flow rates are difficult to assess by means of radar interferometry. The flexibility of the aircraft platform, however, allows for detailed measurements of the elevation and flow of these drainage areas, which are responsible for a significant portion of the ice discharge from the Greenland ice sheet. Velocity estimates for transects that span these glaciers will be presented, and where the ice thickness values are available (provided by researchers from the University of Kansas) the fluxes will be calculated.

Abdalati, Waleed↗
NASA NTRS1998

Variablility of Fram Strait Ice Flux

We estimate the winter sea ice export through the Fram Strait using ice motion from satellite passive microwave data. Sea ice motion (October through May)is obtained by tracking the displacement of common features in sequential 85 GHz and 37 GHz brightness temperature fields.

Fram Strait Ice Flux North Atlantic Oscillation↗
NASA NTRS2019

Automatically Finding Ship-Tracks to Enable Large-Scale Analysis of Aerosol-Cloud Interactions

Ship tracks appear as long winding linear features in satellite images and are produced by aerosols from ship exhausts changing low cloud properties. They are one of the best examples of aerosol‐cloud interaction experiments. However, manually finding ship tracks from satellite data on a large scale is prohibitively costly while a large number of samples are required to improve our understanding. Here we train a deep neural network to automate finding ship tracks. The neural network model generalizes well as it not only finds ship tracks labeled by human experts but also detects those that are occasionally missed by humans. It finds more ship tracks than all previous studies combined and produces a map of ship track distributions off the California coast that matches well with known shipping traffic. Our technique will enable studying aerosol effects on low clouds using ship tracks on a large scale, which will potentially narrow the uncertainty of the aerosol‐cloud interactions.

aerosol cloud interactions↗
DOE OSTI2026

NuGraph2 with context-aware inputs: physics-inspired improvements in semantic segmentation

Graph neural networks have recently shown strong promise for event reconstruction tasks in Liquid Argon Time Projection Chambers, yet their performance remains limited for underrepresented classes of particles, such as Michel electrons. In this work, we investigate physics-informed strategies to improve semantic segmentation within the NuGraph2 architecture. We explore three complementary approaches: (i) enriching the input representation with context-aware features derived from detector geometry and track continuity, (ii) introducing auxiliary decoders to capture class-level correlations, and (iii) incorporating energy-based regularization terms motivated by Michel electron energy distributions. Experiments on MicroBooNE public datasets show that physics-inspired feature augmentation yields the largest gains, particularly boosting Michel electron precision and recall by disentangling overlapping latent space regions. In contrast, auxiliary decoders and energy-regularization terms provided limited improvements, partly due to the hit-level nature of NuGraph2, which lacks explicit particle- or event-level representations. Our findings highlight that embedding physics context directly into node-level inputs is more effective than imposing task-specific auxiliary losses, and suggest that future hierarchical architectures such as NuGraph3, with explicit particle- and event-level reasoning, will provide a more natural setting for advanced decoders and physics-based regularization. The code for this work is publicly available on Github at https://github.com/vitorgrizzi/nugraph_phys/tree/main_phys.

Other Experiments↗
DOE OSTI2023

An Explainable Machine-Learning Model for Compensatory Reserve Measurement: Methods for Feature Selection and the Effects of Subject Variability

Tracking vital signs accurately is critical for triaging a patient and ensuring timely therapeutic intervention. The patient’s status is often clouded by compensatory mechanisms that can mask injury severity. The compensatory reserve measurement (CRM) is a triaging tool derived from an arterial waveform that has been shown to allow for earlier detection of hemorrhagic shock. However, the deep-learning artificial neural networks developed for its estimation do not explain how specific arterial waveform elements lead to predicting CRM due to the large number of parameters needed to tune these models. Alternatively, we investigate how classical machine-learning models driven by specific features extracted from the arterial waveform can be used to estimate CRM. More than 50 features were extracted from human arterial blood pressure data sets collected during simulated hypovolemic shock resulting from exposure to progressive levels of lower body negative pressure. A bagged decision tree design using the ten most significant features was selected as optimal for CRM estimation. This resulted in an average root mean squared error in all test data of 0.171, similar to the error for a deep-learning CRM algorithm at 0.159. By separating the dataset into sub-groups based on the severity of simulated hypovolemic shock withstood, large subject variability was observed, and the key features identified for these sub-groups differed. This methodology could allow for the identification of unique features and machine-learning models to differentiate individuals with good compensatory mechanisms against hypovolemia from those that might be poor compensators, leading to improved triage of trauma patients and ultimately enhancing military and emergency medicine.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1998

Pulsing Inertial Oscillation, Supercell Storms, and Surface Mesonetwork Data

The pulsing inertial oscillation (PIO) model is a nonlinear, time-dependent, translating vortex solution of the inviscid, compressible fluid dynamic equations in the middle troposphere. The translation of this vortex during a pulse is strikingly similar to that of a supercell storm -- a rotating thunderstorm that can generate tornadoes and hail. Two studies were performed to test the hypothesis that some supercell storms are manifestations of a PIO pulse. The first study applied the model to an intense interior draft whose buoyancy was bounded by a temperature excess of +/- 12 K. The peak updraft speed achieved was 41.5 m/ s and the peak Rossby number was 92.9. The study also pointed to an advanced concept for attaining higher values. The second study applied the PIO model to a supercell storm as a whole and succeeded in replicating its bulk properties, such as mesocyclonic circulation, net mass and moisture influxes, and time track. This study also identified a critical feature of the PIO model that could be tested against storm data: The average vertical draft is downward before the turn in the storm track and upward afterwards. In the conventional theory, the average vertical draft is upward from storm inception until dissipation. These differing draft predictions were compared with the best available data, which are surface mesonetwork data. These data were found to support the PIO model. However, surface data alone are not conclusive, and further measurements are warranted.

Costen, R. C.↗
NASA NTRS1994

Real-time tracking of objects for space applications using a laser range scanner

Real-time tracking of multiple targets and three dimensional object features was demonstrated using a laser range scanner. The prototype was immune to ambient illumination and sun interference. Tracking error feedback was simultaneously obtained from individual targets, global predicted target position, and the human operator. A more complete study of calibration parameters and temperature variations on the scanner is needed to determine the exact performance of the sensor. Lissajous patterns used in three-dimensional real-time tracking prove helpful given their high resolution. The photogrammetry-based Advanced Space Vision System (ASVS) is discussed in combination with the laser range scanner.

Blais, F.↗
DOE OSTI2020

Generating MCNP Input Files for Unstructured Mesh Geometries

Los Alamos National Laboratory's (LANL) Monte Carlo N-Particle (MCNP) transport code version 6 has the capability for tracking particles on unstructured mesh (UM) geometry models. The MCNP UM feature has been developed for performing calculations of complex geometry models. This capability tracks particles on hybrid geometries where finite element meshes are embedded into constructive solid geometry (CSG) cells. The MCNP UM feature was originally designed to read UM models created by Abaqus/CAE software suite. MCNP versions 6.2.0 and later can process UM models read from Abaqus input les or MCNPUM les converted from Abaqus input les. Sandia National Laboratory's Cubit Toolkit and other finite element analysis software packages may generate UM models and then convert these models into Abaqus input formats.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1972

Comments on the figure of the moon from Apollo landmark tracking.

The selenographic positions of the observed lunar features are solved for, or estimated directly from, angular measurements made from the orbiting spacecraft (Apollo missions 8, 10, 11, 12, 14, and 15) to the landmark, using least-squares techniques. It appears that the radius values derived from the Apollo landmark data provide some proof of the existence of a displacement between the center of figure and center of mass of the moon along the earth-moon line. In addition, all three components of the estimated crater locations should be useful toward establishing a selenodetic reference system for interpreting or reducing earth-based observation data.

Wollenhaupt, W. R.↗
DOE OSTI2023

TROPHY: A Topologically Robust Physics-Informed Tracking Framework for Tropical Cyclones

Tropical cyclones (TCs) are among the most destructive weather systems. Realistically and efficiently detecting and tracking TCs are critical for assessing their impacts and risks. In particular, the eye is a signature feature of a mature TC. Therefore, knowing the eyes’ locations and movements is crucial for both operational weather forecasts and climate risk assessments. Recently, a multilevel robustness framework has been introduced to study the critical points of time-varying vector fields. The framework quantifies the robustness (i.e., structural stability) of critical points across varying neighborhoods. By relating the multilevel robustness with critical point tracking, the framework has demonstrated its potential in cyclone tracking. An advantage is that it identifies cyclonic features using only 2D wind vector fields, which is encouraging as most tracking algorithms require multiple dynamic and thermodynamic variables at different altitudes. A disadvantage is that the framework does not scale well computationally for datasets containing a large number of cyclones. Herein this paper introduces a topologically robust physics-informed tracking framework (TROPHY) for TC tracking. The main idea is to integrate physical knowledge of TC to drastically improve the computational efficiency of multilevel robustness framework for large-scale climate datasets. First, during preprocessing, we propose a physics-informed feature selection strategy to filter 90% of critical points that are short-lived and have low stability, thus preserving good candidates for TC tracking. Second, during in-processing, we impose constraints during the multilevel robustness computation to focus only on physics-informed neighborhoods of TCs. We apply TROPHY to 30 years of 2D wind fields from reanalysis data in ERA5 and generate a number of TC tracks. In comparison with the observed tracks, we demonstrate that TROPHY can capture TC characteristics (e.g., frequency, intensity, duration, latitudes with maximum intensity, and genesis) that are comparable to and sometimes even better than a well-validated TC tracking algorithm that requires multiple dynamic and thermodynamic scalar fields.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

A mesoscopic link-transmission-model able to track individual vehicles

Macroscopic traffic flow is a common choice for large-scale traffic simulations. These models do not provide individual-specific metrics as outputs. However, this treatment is necessary in agent-based-models, as in, for example, assigning routes based on personal characteristics. Here, in this paper, we propose an extension of the link-transmission-model, an efficient and yet accurate discretization of the Lighthill-Whitham-Richards (LWR) model, which allow vehicles to be tracked individually while keeping the main features of the underlying model. The extension comprises modifying the link and node models to ensure that the flow between links is always at discrete levels. Therefore, every unit of flow is associated with one individual vehicle moving from its current to its next link. An upper bound of the discretization error is provided. We show that the proposed model resembles its continuous counterpart on lane drop, merge, and diverge cases. In addition, we apply the model into three different networks to validate its applicability in large networks. Finally, we also confirm the parameter transferability between continuous and discrete models and that both can well reproduce field data.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Future Atmospheric Rivers and Impacts on Precipitation: Overview of the ARTMIP Tier 2 High–Resolution Global Warming Experiment

Atmospheric rivers (ARs) are long, narrow synoptic scale weather features important for Earth’s hydrological cycle typically transporting water vapor poleward, delivering precipitation important for local climates. Understanding ARs in a warming climate is problematic because the AR response to climate change is tied to how the feature is defined. The Atmospheric River Tracking Method Intercomparison Project (ARTMIP) provides insights into this problem by comparing 16 atmospheric river detection tools (ARDTs) to a common data set consisting of high resolution climate change simulations from a global atmospheric general circulation model. ARDTs mostly show increases in frequency and intensity, but the scale of the response is largely dependent on algorithmic criteria. Across ARDTs, bulk characteristics suggest intensity and spatial footprint are inversely correlated, and most focus regions experience increases in precipitation volume coming from extreme ARs. The spread of the AR precipitation response under climate change is large and dependent on ARDT selection.

54 ENVIRONMENTAL SCIENCES↗