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At least 505 records · Page 28

Viking 1975 Mars lander interactive computerized video stereophotogrammetry

A novel computerized interactive video stereophotogrammetry system has been developed for analysis of Viking 1975 lander imaging data. Prompt, accurate, and versatile performance is achieved. Earth-returned digital imagery data are driven from a computer to a pair of video monitors. Powerful computer support enables a photogrammetrist, stereoscopically viewing the video displays, to create diverse topographic products. Profiles, representing the intersection of any definable surface with the Martian relief, are readily generated. Vertical profiles and elevation contour maps, including stereo versions, are produced. Computer overlays of map products on stereo images aid map interpretation and permit independent quality evaluation. Slaved monitors enable parallel viewing. Maps span from the immediate foreground to the remote limits of ranging capability. Surface sampler arm specific vertical profiles enable direct reading of arm commands required for sample acquisition, rock rolling, and trenching. The ranging accuracy of plus or minus 2 cm throughout the sample area degrades to plus or minus 20 m at 100-m range.

Liebes, S., Jr.↗

Combining Disparate Measures of Metabolic Rate During Simulated Spacewalks

Scientists from NASA's Extravehicular Activities (EVA) Physiology Systems and Performance Project help design space suits for future missions, during which astronauts are expected to perform EVA activities on the Lunar or Martian surface. During an EVA, an astronaut's integrated metabolic rate is used to predict how much longer the activity can continue and still provide a safe margin of remaining consumables. For EVAs in the Apollo era, NASA physicians monitored live data feeds of heart rate, O 2 consumption, and liquid cooled garment (LCG) temperatures, which were subjectively combined or compared to produce an estimate of metabolic rate. But these multiple data feeds sometimes provided conflicting estimates of metabolic rate, making real-time calculations of remaining time difficult for physician/monitors. Currently, designs planned for the Constellation Program EVAs utilize an automated, but largely heuristic methodology for incorporating the above three measurements, plus an additional one - CO 2 production, ignoring data that appears in conflict; however a more rigorous model-based approach is desirable. In this study, we show how principal axis factor analysis, in combination with OLS regression and LOWESS smoothing can be used to estimate metabolic rate as a data-driven weighted average of heart rate, O 2 consumption, LCG temperature data, and CO 2 production. Preliminary results suggest less sensitivity to occasional spikes in observed data feeds, and reasonable within-subject reproducibility when applied to subsequent tasks. These methods do not require physician monitoring and as such can be automated in the electronic components of future space suits. With additional validation, our models show promise for increasing astronaut safety, while reducing the need for and potential errors associated with human monitoring of multiple systems.

Alan H Feiveson↗

A Pilot Project for Quantifying the Effect of Medical Provider Knowledge, Skills, and Abilities on Outcomes for Spaceflight Using a Probabilistic Risk Assessment Tool

In order to enable the future of long-duration deep space exploration we must confront the uncertainty in medical risk. Limitations of communication, resupply, and evacuation in deep space will require a high degree of crew autonomy and accurate risk assessment will be critical to ensure adequate crew training and medical system design. To address this, NASA’s Human Research Program Exploration Medical Capability Element has developed the Informing Mission Planning via Analysis of Complex Tradespaces Tool (IMPACT). IMPACT is a suite of tools that can provide evidence-based, data-driven trade space assessments between available medical resources in the mass- and volume-constrained environment of a deep space exploration vehicle. In the current model, medical conditions either can or cannot be treated based on the availability of medical system resources and equipment. However, medical outcomes often depend just as much on the knowledge, skills, and abilities (KSA) of the provider operating the system. This paper presents a method for modeling and quantifying the effect of medical officer KSA on medically relevant mission risk outcomes during spaceflight.

capabilities↗

Gaussian Process for Flight Delay Prediction: Learning a Stochastic Process

This paper presents a machine-learning approach to predict flight delays. Whereas neural networks are extensively studied for predictive capabilities, they involve non-intuitive design and extensive analysis, particularly in training and optimization processes. Instead, the proposed framework employs Gaussian Processes as a supervised learning technique for flight delay prediction. This data-driven approach trains the model using prior information, specifically the mean and covariance tied to existing data. The proposed Gaussian Process Regression (GPR) model employs the day of flight as a pivotal feature for delay forecasting. We analyze flights from various routes and gauge the accuracy of the presented learning technique by comparing the predicted delays with the actual ones. Given the inherent challenges in precisely forecasting delays, we predict the delays with a 95 % confidence interval. Also, an error propagation analysis in the prediction horizon is carried out to determine the optimal time frame for prediction. The proposed method for flight delay prediction is important as airlines can strategize flight operations and issue timely advisories.

stochastic↗

Tonian Carbonates Record Phosphate-Rich Shallow Seas

The early-middle Neoproterozoic is thought to have witnessed significant perturbations to marine P cycling, in turn facilitating the rise of eukaryote-dominated primary production. However, with few robust constraints on aqueous P concentrations, current understanding of Neoproterozoic P cycling is generally model-dependent. To provide new geochemical constraints, we combined microanalytical data sets with solid-state Nuclear Magnetic Resonance, synchrotron-based X-ray Absorption Near Edge Structure spectroscopy, and micro-X-ray Fluorescence imaging to characterize the speciation and distribution of P in Tonian shallow-water carbonate rocks. These data reflect shallow water phosphate concentrations 10–100× higher than modern systems, supporting the hypothesis that tectonically-driven influxes in P periodically initiated kinetically-controlled CaCO 3 deposition, in turn destabilizing marine carbonate chemistry, climate, and nutrient inventories. Alongside these observations, a new compilation and statistical analysis of mudstone geochemistry data indicates that, in parallel, C org and P burial increased across later Tonian continental margins until becoming decoupled at the close of the Tonian, implicating widespread N-limitation triggered by increasing atmospheric O 2 .

58 GEOSCIENCES↗

Small-Signal ac Analysis

Program simulates power circuits and systems. Small Signal A.C. Analysis program (SSAC) valuable tool for design and analysis of electrical-power-system circuits. By combining "black box" power-system components operating in specified manner, user characterizes system modeled. Menu-driven program proved simple and cost effective in development and modification of arbitrary power-system configurations. Package includes sample data from Dynamic Explorer satellite family. Results compared favorable to calculations from such general circuit-analysis programs as SPICE. Written in FORTRAN 77.

Jagielski, James M.↗

Aerosol Observability and Predictability: From Research to Operations for Chemical Weather Forecasting. Lagrangian Displacement Ensembles for Aerosol Data Assimilation

A challenge common to many constituent data assimilation applications is the fact that one observes a much smaller fraction of the phase space that one wishes to estimate. For example, remotely sensed estimates of the column average concentrations are available, while one is faced with the problem of estimating 3D concentrations for initializing a prognostic model. This problem is exacerbated in the case of aerosols because the observable Aerosol Optical Depth (AOD) is not only a column integrated quantity, but it also sums over a large number of species (dust, sea-salt, carbonaceous and sulfate aerosols. An aerosol transport model when driven by high-resolution, state-of-the-art analysis of meteorological fields and realistic emissions can produce skillful forecasts even when no aerosol data is assimilated. The main task of aerosol data assimilation is to address the bias arising from inaccurate emissions, and Lagrangian misplacement of plumes induced by errors in the driving meteorological fields. As long as one decouples the meteorological and aerosol assimilation as we do here, the classic baroclinic growth of error is no longer the main order of business. We will describe an aerosol data assimilation scheme in which the analysis update step is conducted in observation space, using an adaptive maximum-likelihood scheme for estimating background errors in AOD space. This scheme includes e explicit sequential bias estimation as in Dee and da Silva. Unlikely existing aerosol data assimilation schemes we do not obtain analysis increments of the 3D concentrations by scaling the background profiles. Instead we explore the Lagrangian characteristics of the problem for generating local displacement ensembles. These high-resolution state-dependent ensembles are then used to parameterize the background errors and generate 3D aerosol increments. The algorithm has computational complexity running at a resolution of 1/4 degree, globally. We will present the result of assimilating AOD retrievals from MODIS (on both Aqua and TERRA satellites) from AERONET for validation. The impact on the GEOS-5 Aerosol Forecasting will be fully documented.

da Silva, Arlindo↗

Lightfall v0.0.1

Lightfall is a desktop application for synchrotron beamline instrument control, data acquisition, and live analysis at the Advanced Light Source (ALS). Built on Python and Qt, it provides a native graphical interface for operating beamline hardware, configuring and executing experimental scans, and visualizing results in real time. Key features include direct integration with EPICS control systems, a built-in electronic logbook, remote beamline access over secure tunnels, and an interprocess communication (IPC) architecture that coordinates with external analysis applications via ZMQ and EPICS process variables. This IPC approach allows Lightfall to orchestrate specialized analysis tools—including GPU-accelerated streaming correlators—without embedding them, avoiding the dependency conflicts common in monolithic scientific software platforms. Compared to prior approaches such as Xi-CAM's plugin-based architecture, Lightfall's design cleanly separates instrument control from domain-specific analysis, enabling feedback-driven acquisition where live analysis results can adjust scan parameters during an experiment. Its native Qt interface provides responsive performance for real-time data visualization that web-based alternatives struggle to match. Lightfall is designed for use by beamline scientists and staff operating synchrotron instruments at national user facilities.

Pandolfi, Ronald [Lawrence Berkeley National Labor↗

ChemML : A machine learning and informatics program package for the analysis, mining, and modeling of chemical and materials data

ChemML is an open machine learning (ML) and informatics program suite that is designed to support and advance the data-driven research paradigm that is currently emerging in the chemical and materials domain. ChemML allows its users to perform various data science tasks and execute ML workflows that are adapted specifically for the chemical and materials context. Key features are automation, general-purpose utility, versatility, and user-friendliness in order to make the application of modern data science a viable and widely accessible proposition in the broader chemistry and materials community. Finally, ChemML is also designed to facilitate methodological innovation, and it is one of the cornerstones of the software ecosystem for data-driven in silico research.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Phase Coherent Timing of the Ultra-compact Candidates V407 Vul and RX J0806.3+1527

I report on the results of ongoing campaigns with Chandra to precisely time the X-ray pulsations from two candidate ultra-compact white dwarf systems; V407 Vu1 and RX J0806.3+1527. If these objects are ultra-compact binaries, then the gravitational radiation-driven evolution of the orbital period can be probed with precise X-ray timing observations. Recent Chandra data have confirmed that the X-ray frequency of V407 Vu1 is increasing at a mean rate of about 8 x 10-18 Hz s-1, a value consistent with loss of gravitational radition from the system. However, the frequency derivative, X-ray variability and phase timing noise could also be explained in an accretion driven, intermediate polar scenario. Previous studies suggested that RX J0806.3+1527 is spinning up at an even faster rate than V407 Vul, however, preliminary analysis of Chandra data do not confirm this. Indeed, the present evidence suggests we may be seeing a torque reversal in this source.

Strohmayer, T. E.↗

Stratigraphy of the Apollo 17 Landslide Core 73002 From FMR Maturity and VNIR and Mössbauer Spectroscopy

A suite of samples from the Apollo missions to the Moon (1969-1973) were set aside and stored under controlled conditions to have unexamined lunar samples available decades later for analyses that take advantage of evolved sample handling techniques, maturation of then existing instrumentation, and development of new analytical techniques and instrumentation [e.g., 1]. One preserved sample is the Apollo 17 double drive tube core (73001/2) that was driven into the lunar surface on the landslide deposit at Station 3 on the South Massif in the Taurus-Littrow valley [2]. The deeper section (73001) was stored frozen in a Core Sample Vacuum Container (CSVC) to maximize preservation of lunar volatiles. We report here, as a part of the Apollo Next Generation Sample Analysis (ANGSA) Initiative [1,3], stratigraphy for the upper core section (73002) with respect to maturity (ferromagnetic resonance (FMR) maturity index Is/FeO [4-6]), visible-near-IR (VNIR) spectroscopy, and, for representative samples, grain-size analysis and Mössbauer spectroscopy. Stratigraphy provides data to model the dynamics of lunar landslide deposits and their post-emplacement evolution in comparison to impact-driven mixing on an airless body and stratigraphic context for volatile and (if any) organic behavior. Reported by [7] are preliminary results for multispectral imaging and hyperspectral scanning of the first dissection pass of 73002.

R. V. Morris↗

MtrA modulates Mycobacterium tuberculosis cell division in host microenvironments to mediate intrinsic resistance and drug tolerance

The success of Mycobacterium tuberculosis (Mtb) is largely attributed to its ability to physiologically adapt and withstand diverse localized stresses within host microenvironments. Here, we present a data-driven model (EGRIN 2.0) that captures the dynamic interplay of environmental cues and genome-encoded regulatory programs in Mtb. Analysis of EGRIN 2.0 shows how modulation of the MtrAB two-component signaling system tunes Mtb growth in response to related host microenvironmental cues. Disruption of MtrAB by tunable CRISPR interference confirms that the signaling system regulates multiple peptidoglycan hydrolases, among other targets, that are important for cell division. Further, MtrA decreases the effectiveness of antibiotics by mechanisms of both intrinsic resistance and drug tolerance. Together, the model-enabled dissection of complex MtrA regulation highlights its importance as a drug target and illustrates how EGRIN 2.0 facilitates discovery and mechanistic characterization of Mtb adaptation to specific host microenvironments within the host.

59 BASIC BIOLOGICAL SCIENCES↗

Investigating shear flow through continuum gyrokinetic simulations of limiter biasing in the Texas Helimak

Previous limiter-biasing experiments on the Texas Helimak, a simple magnetized torus, have been inconclusive on the effect of flow shear on turbulence levels. To explore this, the first gyrokinetic simulations of limiter biasing in the Helimak using the plasma physics code Gkeyll have been carried out, and results are presented here. For the scenarios considered, turbulence is mostly driven by the interchange instability, which depends on gradients of steady state density profiles. An analysis of both experimental and simulation data demonstrates that shear rates are mostly less than than local linear growth rates, and not all requirements for shear stabilization are met. Yet, the mostly vertical shear flow has an important effect on bulk transport and experimental steady-state density profiles, and changes to the gradients correspond to changes in turbulence levels.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Beam-ion Studies in NSTX and NSTX-U (Final Technical Report)

The confinement of high energy "fast ions" is crucial for the success of magnetic fusion as a practical energy source. The research performed by UC Irvine on NSTX and NSTX-U provided new information about this important topic in the configuration known as a "spherical tokamak." Injected neutral beams provided the fast ions (also known as "beam ions"). There were five overarching goals of the research. One objective was to measure the confinement of beam ions in order to ascertain if they were accomplishing their desired purpose of transferring their energy to the bulk plasma. A second goal was to better understand instabilities that are driven unstable by the fast ions. A related goal was to use the similarities and differences between NSTX and the DIII-D conventional tokamak to better understand the fast-ion driven instabilities. A fourth goal was to develop new instruments to measure fast ions and techniques that facilitate analysis of the data. The fifth objective was to measure and understand acceleration of beam ions by RF waves. Much was accomplished in all of these five areas. In the first, it was shown that the large magnetic moment of the beam ions did not harm confinement but instabilities known as the "sawtooth" and "long-lived mode" do. In the second area, much attention was devoted to the fast-ion instabilities known as "Alfvén eigenmodes." In particular, Alfvén eigenmode "avalanches" can cause ~ 30% of the fast ions to be lost in a single explosive burst. The comparative studies with DIII-D showed that an instability discovered on NSTX is also important in conventional tokamaks. In the fourth category, several instruments were developed, a number of effects that complicate interpretation of the data were understood, and progress toward a new method to infer the fast-ion distribution function from the data was made. In the fifth category, the measured profile of accelerated fast ions was initially much broader than theoretical predictions but subsequent improvements in the theoretical modeling achieved good agreement with the data.

43 PARTICLE ACCELERATORS↗

Interregional Renewable Energy Zones in National Transmission Analysis

This report describes the interregional renewable energy zone (IREZ) methodology for national application in the United States. The aim is to develop a data-driven, replicable methodology for use in long-term regional and interregional transmission planning. An IREZ is best understood as a conceptual transmission collection point that is easily accessible to a very high volume of low-cost developable wind and solar energy potential. The objective is to identify opportunities for new high-volume long-distance interregional transmission corridors: a limited number of lines with higher voltages, with reduced total cost per megawatt of transfer capability.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

The solar array-induced disturbance of the Hubble Space Telescope pointing system

The investigation of the vibrational disturbances of the Hubble Space Telescope that were discovered soon after deployment in orbit is described in detail. It was found that the disturbances were particularly evident during orbital day-night crossings, and that the magnitudes of the disturbances were considerably larger than the design jitter requirements. This paper describes the process by which the vibrations were characterized and isolated to a particular mechanism. The analysis of the flight data and comparisons with computer simulation results showed that the source of the disturbances was the thermally driven deformation of the solar arrays in conjunction with frictional effects in the array mechanisms. The control system was successfully modified to attenuate the disturbances to tolerable levels pending mechanical and thermal redesign of the solar arrays. The new arrays were installed during the first space telescope servicing mission and, in combination with the enhanced control system algorithm, reduced the disturbances to satisfactory levels.

Foster, C. L.↗

Solar-Array-Induced Disturbance of the Hubble Space Telescope Pointing System

The investigation of the vibrational disturbances of the Hubble Space Telescope that were discovered soon after deployment in orbit is described in detail. It was found that the disturbances were particularly evident during orbital day-night crossings, and that the magnitude of the disturbances was considerably larger than the design jitter requirement. This paper describes the process by which the vibrations were characterized and isolated to a particular mechanism. The analysis of the flight data and comparisons with computer simulation results showed that the source of the disturbances was the thermally driven deformation of the solar arrays in conjunction with frictional effects in the array mechanisms. The control system was successfully modified to attenuate the disturbances to tolerable levels pending mechanical and thermal redesign of the solar arrays. The new arrays were installed during the first Space Telescope servicing mission, and in combination with the enhanced control system algorithm reduced the disturbances to satisfactory levels.

Foster, Carlton L.↗

Verification, Validation, and Calibration Through a Causal Lens

While typical validation and verification approaches focus on identifying the associations between data elements using statistical and machine learning methods, the novel methods in this paper focus instead on identifying causal relationships between data elements. Statistical and machine-learning-based approaches are strictly data-driven, meaning that they provide quantitative comparison measures between data sets without explicitly considering the hypotheses behind them. This can lead to the erroneous conclusion that, if two data sets are close enough, the models that generated them are similar. In addition, when experimental and simulated data differ to an extent that fails to meet the acceptance criteria, calibration techniques are used to tweak simulation model parameters to reduce the gap between the two types of data. This produces the false expectation that a simulation model will match reality. The methods presented in this paper move away from these strictly data-driven methods for validation and calibration toward more robust, model-driven methods based on causal inference. Causal inference aims to identify the possible mechanisms that might have generated data. Thus, this analysis targets the prediction of the effects when one (or more) of the identified mechanisms are altered. There are many approaches to identify, quantify, and illustrate causal relationships. For the scope of this paper, directed graphs are employed as causal models. If the directed graph lacks cycles, it is known as a directed acyclic graph. A node in such a graph represents an observed data element while a directed edge connecting two nodes represents a causal relationship between two variables. The developed causal methods are designed to extract causal models from simulation models and experimental data. Causal models capture the causal relationships between data elements (e.g., simulated and experimental data). In this context, validation and verification are performed by comparing causal models. The proposed approach does not only inform system analysts on how a simulation model matches real-world data, but also identifies elements of the simulation model that should be revised when discrepancies between simulation and experimental data are observed. Through these causal methods, analysts can identify the portion of the model equation(s) that are behind an edge connecting two variables. Hence, once the structural differences between causal models have been determined, model calibration can occur by changing only those model parameters that impact the identified causal relationships.

97 MATHEMATICS AND COMPUTING↗