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At least 541 records · Page 30

Inertial-space disturbance rejection for space-based manipulators

The implementation of a disturbance rejection controller for a 6-DOF PUMA manipulator mounted on a 3-DOF platform was described. A control algorithm is designed to track the desired position and attitude of the end-effector in inertial space, subject to unknown disturbances in the platform axes. Experimental results are presented for step, sinusoidal, and random disturbances in the platform rotational axis and in the neighborhood of kinematic singularities. Robotic manipulators were proposed as a means of reducing the amount of extra vehicular activity time required for space station assembly and maintenance. The proposed scenario involves a robotic manipulator attached to some mobile platform, such as a spacecraft, satellite, or the space station itself. Disturbances in the platform position and attitude may prevent the manipulator from successfully completing the task. The possibility of using the manipulator to compensate for platform disturbances was explored. The problem of controlling a robotic manipulator on a mobile platform has received considerable attention in the past few years. Joshi and Desrochers designed a nonlinear feedback control law to carry out tasks (with respect to the robot base frame) in the presence of roll, pitch and yaw disturbances in the platform axes. Dubowsky, Vance, and Torres proposed a time-optimal planning algorithm for a robotic manipulator mounted on a spacecraft, subject to saturation limits in the attitude control reaction jets. Papadopoulos and Dubowsky developed a general framework for analyzing the control of free-floating space manipulator systems. Most recently, Torres and Dubowsky have presented a technique called the enhanced disturbance map to find manipulator trajectories that reduce the effect of disturbances in the spacecraft position and attitude. One common assumption in the literature is that the disturbance signal is exactly known. If this is the case, then the end-effector location can be calculated without relying on direct end-point sensing. However, this assumption is invalid if there is a significant delay in the platform position and attitude measurements, or if the kinematics of the platform are not well known, or if the platform is a non-rigid structure. In the more likely case that only the nominal platform location and upper bound on the disturbance signal are known, direct end-point sensing is needed to measure the end-effector location.

Holt, Kevin↗

Analysis and Review of NASA Earth Science Metadata: How Automation Plays a Role

The Analysis and Review of the Common Metadata Repository (CMR ARC) Team reviews all EOSDIS metadata. The team’s objective is to achieve consistency, correctness, and completeness for all metadata records in the CMR, as well as improve the discoverability of NASA's Earth Science data within the CMR framework. This work is currently being completed at Marshall Space Flight Center. CMR makes a single discovery point possible for NASA's Earth Science data users. The CMR team, in collaboration with three other core metadata teams, contributes to the stewardship of NASA's Earth Science data through a process of continual curation and the ongoing development of the Unified Metadata Model (UMM). A key tool now used in the curation process, referred to as the NASA CMR Dashboard, is an online curation dashboard developed in collaboration with software development company, Element 84. This tool facilitates the review of Earth Science metadata records and subsequent stakeholder collaboration on the resolution of identified issues. A key capability of the new tool is a suite of automated compliance checks written in Python 3.6 that verify the integrity of various metadata elements across multiple standards.

Staton, Patrick↗

Joint ESA-NASA Multi-Mission Algorithm and Analysis Platform (MAAP)

The scientific community is faced with a need for greatly improved data sharing, analysis, visualization and advanced collaboration based firmly on open science principles. Recent and upcoming launches of new satellite missions with more complex and voluminous data, as well as the ever more urgent need to better understand the global carbon budget and related ecological processes, provided the immediate rational for the ESA-NASA Multi-mission Algorithm and Analysis Platform (MAAP). This highly collaborative joint project of ESA and NASA established a framework between ESA and NASA to share data, science algorithms and compute resources in order to foster and accelerate scientific research conducted by ESA and NASA EO data users. Presented to the public in October 2021, the current version of MAAP provides a common cloud-based platform with computing capabilities co-located with the data, a collaborative coding and analysis environment, and a set of interoperable tools and algorithms developed to support the estimation and visualization of global above-ground biomass. Data from the Global Ecosystem Dynamics Investigation (GEDI) mission on the International Space Station and the Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) have been instrumental in the first products of MAAP including the first comprehensive map of Boreal above-ground Biomass and a current Global Biomass Harmonization Activity, but the platform is also being specifically designed to support the forthcoming ESA Biomass mission and incorporate data from the upcoming NASA-ISRO SAR (NISAR) mission. While these missions and the corresponding research which includes airborne, field, and calibration/validation data collection and analyses, provide a wealth of data and information relating to global biomass estimation, they also present data storing, processing and sharing challenges. The NISAR mission alone will produce about 80TB/day. These large data volumes present a challenge that would otherwise place accessibility limits on the scientific community and impact scientific progress. Other challenges being addressed by MAAP include: 1) Enabling researchers to easily discover, process, visualize and analyze large volumes of data from both agencies; 2) Providing a wide variety of data in the same coordinate reference frame to enable comparison, analysis, data evaluation, and data generation; 3) Providing a version-controlled science algorithm development environment that supports tools, co-located data and processing resources; and 4) Addressing intellectual property and sharing challenges related to collaborative algorithm development and sharing of data and algorithms. MAAP products can be explored on the MAAP Dashboard at https://earthdata.nasa.gov/maap-biomass or the joint platform entrance at scimaap.net. MAAP also can be accessed through individual NASA (https://maap-project.org) and ESA (https://esa-maap.org/) landing pages.

cloud computing↗

Use of the SPoRT Stoplight Product to Support NWS Decision Support Services

The National Weather Service Forecast Offices (NWSFOs) use many weather tools and observational datasets to provide support for critical decision-making by core partners such as public safety officials, emergency managers, and first responders. These core partners who need weather decision support services (DSS) for outdoor events require up-to-the-minute weather information to ensure the safety and protection of attendees and workers. Storms and lightning, potentially deadly, pose a significant threat during outdoor events and are among the weather phenomena frequently cited as a DSS requirement. According to the National Lightning Safety Council, from 2014 up to August 2024, lightning resulted in 222 fatalities in the U.S. For outdoor events with hundreds to thousands of attendees, having the right tools to detect and monitor lightning activity is of utmost importance to protect lives. Common guidelines for lightning safety include moving inside a substantial structure at the first sight of threatening skies or the first sound of thunder, and waiting 30 minutes after the last lightning flash or thunder before returning outside. Using this guidance as a framework, scientists at the NASA Short-term Prediction Research and Transition (SPoRT) center have developed the Geostationary Lightning Mapper (GLM) Stoplight tool. This experimental tool uses the GLM Flash Extent Density imagery to display the location and recency of lightning flashes. To simplify interpretation, these lightning pixels are color-coded in 10-minute bins, ranging from red (lightning detected 0 to 10 minutes ago) to yellow (10 to 20 minutes ago) to green (20 to 30 minutes ago). The Stoplight tool also allows users to place markers at the location of outdoor events with range rings around the location to help in assessing the location and relative age of lightning flashes near and upstream of the event. The goal is to help NWS forecasters provide core partners with the necessary information to make the best decisions possible. While the Stoplight tool is experimental, forecasters at NWSFO Raleigh, NC, have periodically used the Stoplight guidance to evaluate its utility within NWS DSS. This presentation will discuss how the Stoplight tool was successfully used for DSS for four outdoor events in central NC in 2023 and 2024. Future improvements to this tool, including the addition of AI applications and the merging of ground-based lightning data with GLM data, will be reviewed.

Gail Hartfield↗

Engineering Design Tools for Shape Memory Alloy Actuators: CASMART Collaborative Best Practices and Case Studies

The primary goal of the Consortium for the Advancement of Shape Memory Alloy Research and Technology (CASMART) is to enable the design of revolutionary applications based on shape memory alloy (SMA) technology. In order to help realize this goal and reduce the development time and required experience for the fabrication of SMA actuation systems, several modeling tools have been developed for common actuator types and are discussed herein along with case studies, which highlight the capabilities and limitations of these tools. Due to their ability to sustain high stresses and recover large deformations, SMAs have many potential applications as reliable, lightweight, solid-state actuators. Their advantage over classical actuators can also be further improved when the actuator geometry is modified to fit the specific application. In this paper, three common actuator designs are studied: wires, which are lightweight, low-profile, and easily implemented; springs, which offer actuation strokes upwards of 200 at reduced mechanical loads; and torque tubes, which can provide large actuation forces in small volumes and develop a repeatable zero-load actuation response (known as the two-way shape memory effect). The modeling frameworks, which have been implemented in the design tools, are developed for each of these frequently used SMA actuator types. In order to demonstrate the versatility and flexibility of the presented design tools, as well as validate their modeling framework, several design challenges were completed. These case studies include the design and development of an active hinge for the deployment of a solar array or foldable space structure, an adaptive solar array deployment and positioning system, a passive air temperature controller for regulation flow temperatures inside of a jet engine, and a redesign of the Corvette active hatch, which allows for pressure equalization of the car interior. For each of the presented case studies, a prototype or proof-of-concept was fabricated and the experimental results and lessons learned are discussed. This analysis presents a collection of CASMART collaborative best practices in order to allow readers to utilize the available design tools and understand their modeling principles. These design tools, which are based on engineering models, can provide first-order optimal designs and are a basic and efficient method for either demonstrating design feasibility or refining design parameters. Although the design and integration of an SMA-based actuation system always requires application- and environment-specific engineering considerations, common modeling tools can significantly reduce the investment required for actuation system development and provide valuable engineering insight.

Design tools↗

SO(3)-invariant PCA with application to molecular data

Principal component analysis (PCA) is a fundamental technique for dimensionality reduction and denoising; however, its application to three-dimensional data with arbitrary orientations -- common in structural biology -- presents significant challenges. A naive approach requires augmenting the dataset with many rotated copies of each sample, incurring prohibitive computational costs. In this paper, we extend PCA to 3D volumetric datasets with unknown orientations by developing an efficient and principled framework for SO(3)-invariant PCA that implicitly accounts for all rotations without explicit data augmentation. By exploiting underlying algebraic structure, we demonstrate that the computation involves only the square root of the total number of covariance entries, resulting in a substantial reduction in complexity. We validate the method on real-world molecular datasets, demonstrating its effectiveness and opening up new possibilities for large-scale, high-dimensional reconstruction problems.

Fraiman, Michael [Tel Aviv Univ., Tel Aviv (Israel↗

Second-order closure models for rotating turbulent flows

The physical properties of the commonly used second-order closure models are examined theoretically for rotating turbulent flows. Comparisons are made with results which are a rigorous consequence of the Navier-Stokes equations for the problem of fully-developed turbulent channel flow in a rapidly rotating framework. It is demonstrated that all existing second-order closures yield spurious physical results for this test problem of rotating channel flow. In fact, the results obtained are shown to be substantially more unphysical than those obtained from the simpler k-epsilon and k-l models. Modifications in the basic structure of these second-order closure models are proposed which can alleviate this problem.

Speziale, Charles G.↗

Simultaneous Ginga and IUE observations of the Seyfert galaxy NGC 3516

A possible connection between the variable X-ray and UV absorption features in NGC 3516 is presently investigated in view of simultaneous X-ray and UV observations. A common origin of the UV and X-ray absorption could not be established, due to the absence of variability in either the X-ray or UV absorption. On the basis of the absorbing properties of a low-luminosity AGN, in the framework of broad absorption-line (BAL) theories, it is suggested that NGC 3516 is consistent with a low-luminosity equivalent of a BAL QSO.

Kolman, Michiel↗

Presentation, Analysis, and Simulation of Active Alignment Strategies for the James Webb Space Telescope

This paper presents three characteristics in the simulated active alignment strategy of the James Webb Space Telescope. The first includes the analysis and comparison of a baseline active alignment strategy with a damped least squares strategy. This baseline utilizes prior knowledge by means of direct human operator interaction to engage sets of telescope compensators to target specific aberration signatures. The baseline is compared to a damped least-squares strategy that utilizes simultaneous engagement of all telescope compensators without explicit human operator inter<actiori to achieve a least-squares telescope compensation. Second, we discuss how the active alignment of the JWST is encapsulated in a linear optical model developed at the Space Telescope Science Institute. This linear optical model provides a framework for an efficient and robust description of the optical control properties of the JWST and clearly articulates the necessity for having a multi-instrument multi-field wavefront sensing strategy to overcome control system non independence and the effects of non-common path errors in the main wavefront sensing camera. Finally. we present analytical results that explicitly map the telescope wavefront responses to the telescope control modes, and we present Monte-Carlo optical performance simulation results that demonstrate the efficacy of the damped least-squares active alignment and the prior-knowledge active alignment schemes.

Upton, Robert S.↗

Context and future directions for integrating forest carbon into sub-national climate mitigation planning in the RGGI region of the U.S.

International frameworks for climate mitigation that build from national actions have been developed under the United National Framework Convention on Climate Change and advanced most recently through the Paris Climate Agreement. In parallel, sub-national actors have set greenhouse gas (GHG) reduction goals and developed corresponding climate mitigation plans. Within the U.S., multi-state coalitions have formed to facilitate coordination of related science and policy. Here, utilizing the forum of the NASA Carbon Monitoring System’s Multi-State Working Group, we collected and reviewed climate mitigation plans for 11 states in the Regional Greenhouse Gas Initiative region of the Eastern U.S. For each state we reviewed the (a) policy framework for climate mitigation, (b) GHG reduction goals, (c) inclusion of forest activities in the state’s climate action plan, (d) existing science used to quantify forest carbon estimates, and (e) stated needs for forest carbon monitoring science. Across the region, we found important differences across all categories. While all states have GHG reduction goals and framework documents, nearly three-quarters of all states do not account for forest carbon when planning GHG reductions; those that do account for forest carbon use a variety of scientific methods with various levels of planning detail and guidance. We suggest that a common, efficient, standardized forest carbon monitoring system would provide important benefits to states and the geographic region as a whole. In addition, such a system would allow for more effective transparency and progress tracking to support state, national, and international efforts to increase ambition and implementation of climate goals.

Rachel L Lamb↗

Second-order closure models for rotating turbulent flows

The physical properties of the commonly used second-order closure models are examined theoretically for rotating turbulent flows. Comparisons are made with results which are a rigorous consequence of the Navier-Stokes equations for the problem of a fully-developed turbulent channel flow in a rapidly rotating framework. It is demonstrated that all existing second-order closures yield spurious physical results for this test problem of rotating channel flow. In fact, the results obtained are shown to be substantially more unphysical than those obtained from the simpler K-epsilon and K-l models. Modifications in the basic structure of these second-order closure models are proposed which can alleviate this problem.

Speziale, C. G.↗

Natural Language Query System Design for Interactive Information Storage and Retrieval Systems

The currently developed multi-level language interfaces of information systems are generally designed for experienced users. These interfaces commonly ignore the nature and needs of the largest user group, i.e., casual users. This research identifies the importance of natural language query system research within information storage and retrieval system development; addresses the topics of developing such a query system; and finally, proposes a framework for the development of natural language query systems in order to facilitate the communication between casual users and information storage and retrieval systems.

Dominick, Wayne D.↗

An Evaluation of Representation Learning Methods in Particle Physics Foundation Models

We present a systematic evaluation of representation learning objectives for particle physics within a unified framework. Our study employs a shared transformer-based particle-cloud encoder with standardized preprocessing, matched sampling, and a consistent evaluation protocol on a jet classification dataset. We compare contrastive (supervised and self-supervised), masked particle modeling, and generative reconstruction objectives under a common training regimen. In addition, we introduce targeted supervised architectural modifications that achieve state-of-the-art performance on benchmark evaluations. This controlled comparison isolates the contributions of the learning objective, highlights their respective strengths and limitations, and provides reproducible baselines. We position this work as a reference point for the future development of foundation models in particle physics, enabling more transparent and robust progress across the community.

Chen, Michael [Caltech]↗

Machine learning-enhanced MPC for demand flexibility in small commercial buildings: An experimental study

Small- and medium-sized commercial buildings (SMCBs) represent the majority of U.S. commercial building stock and a significant share of peak electricity demand, yet they often lack centralized building automation systems, representing a significant untapped resource for urban energy management. This infrastructure gap makes advanced control implementation challenging, limiting the potential for widespread demand flexibility. Model Predictive Control (MPC) has shown strong potential for load shifting, peak demand reduction, and cost savings, but its effectiveness is hindered by unmeasured disturbances such as internal heat gains. This paper presents a Hybrid MPC framework that integrates a physics-based gray-box building thermal model, identified using a lumped disturbance (LD) approach, with a machine learning (ML) model for forecasting unmeasured disturbances. The hybrid approach is designed for buildings with multiple individually controlled heat pump and thermostat pairs, common in SMCBs, and aims to optimize coordinated scheduling of multiple heat pumps under dynamic electricity pricing while respecting comfort constraints. The methodology is validated through both simulations of case study buildings and experimental studies at a highly-instrumented test facility. Simulation results show that the Hybrid MPC achieves substantial load shifting and peak demand reduction, approaching the performance of an ideal MPC with perfect disturbance knowledge, and outperforming a conventional MPC without disturbance forecasting. In experiments, the Hybrid MPC reduced daily HVAC energy costs by 8.7%, peak-price time load (load shifting) by 41.7%, and peak demand by 29.2% compared to baseline control, demonstrating comparable benefits to the 11.6% cost savings, 42.9% load shifting, and 23.2% peak reduction of the ideal MPC. These results demonstrate that the proposed hybrid modeling approach can significantly improve MPC performance in real-world SMCB applications without requiring additional disturbance measurements.

Demand Flexibility↗

Adaptation of Wallace's approach to the specific heat of elemental solids with significant intrinsic anharmonicity, particularly the light actinide metals

The quasiharmonic approximation is the most common method for modeling the specific heat of solids; however, it fails to capture the effects of intrinsic anharmonicity. In this study, we introduce the “elastic softening approximation,” an alternative approach to modeling intrinsic anharmonic effects on thermodynamic quantities, which is grounded in Wallace's thermodynamic framework that tracks entropy changes resulting from the continuous change (e.g., softening) of phonons as a function of temperature. A key finding of our study is a correlation between Poisson's ratio and the differential rate of phonon softening at finite frequencies, compared to lower frequencies relevant to elastic moduli measurements. We observe that elemental solids such as α -Be, diamond, Al, Cu, In, W, Au, and Pb, which span a wide range of Poisson's ratios and exhibit varying degrees of intrinsic anharmonicity, consistently follow this trend. When applied to α -U, α -Pu, and δ -Pu, our method reveals unusually large anharmonic phonon contributions at elevated temperatures across all three light actinide metals. These findings are attributed to the unique combination of enhanced covalency and softer elastic moduli inherent in the actinides, potentially influenced by their 5 f -electron bonding. Published by the American Physical Society 2025

36 MATERIALS SCIENCE↗

Uncertainty quantification for inverse problems with application to ptychographic reconstruction

Inverse problems in imaging are commonly solved by optimization or learned surrogates that return a single reconstruction, while uncertainty information is often unavailable. In many experimental settings, however, uncertainty is required to assess reliability, guide downstream analysis, and prioritize additional measurements. In this note, we present a compact uncertainty-quantification framework based on local objective curvature, and then specialize it to ptychographic reconstruction. We further show how repeated reconstructions can be aggregated in a statistically principled way, including a practical implementation path for PtychoNN.

97 MATHEMATICS AND COMPUTING↗

Qubit Regularization of Quantum Field Theories

To study quantum field theories on a quantum computer, we must begin with Hamiltonians defined on a finite-dimensional Hilbert space and then take appropriate limits. This approach can be seen as a new type of regularization for quantum field theories, which we refer to as qubit regularization. A related finite-dimensional regularization, known as the D-theory approach, was proposed long ago as a general framework for all quantum field theories. In this framework, the dimensionality of the local Hilbert space at each spatial point can increase as needed through an additional flavor index. To reproduce asymptotically free QFTs, most studies assume that qubit-regularized theories require extending the local Hilbert space to infinity. However, contrary to this common belief, recent discoveries in (1+1) dimensions have revealed two examples where asymptotic freedom appears to emerge within a strictly finite-dimensional local Hilbert space through a novel renormalization group (RG) flow. These findings motivate further investigation into whether asymptotically free gauge theories could also emerge within a strictly finite-dimensional local Hilbert space. To support these explorations, we propose an orthonormal basis called the monomer-dimer-tensor-network (MDTN) basis and use it to construct new types of qubit-regularized lattice gauge theories.

Chandrasekharan, Shailesh [Duke Univ., Durham, NC ↗

Topology of three-dimensional separated flows

Based on the hypothesis that patterns of skin-friction lines and external streamlines reflect the properties of continuous vector fields, topology rules define a small number of singular points (nodes, saddle points, and foci) that characterize the patterns on the surface and on particular projections of the flow (e.g., the crossflow plane). The restricted number of singular points and the rules that they obey are considered as an organizing principle whose finite number of elements can be combined in various ways to connect together the properties common to all steady three dimensional viscous flows. Introduction of a distinction between local and global properties of the flow resolves an ambiguity in the proper definition of a three dimensional separated flow. Adoption of the notions of topological structure, structural stability, and bifurcation provides a framework to describe how three dimensional separated flows originate and succeed each other as the relevant parameters of the problem are varied.

Tobak, M.↗