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NASA NTRS2000

Remote sensing and human health: new sensors and new opportunities

Since the launch of Landsat-1 28 years ago, remotely sensed data have been used to map features on the earth's surface. An increasing number of health studies have used remotely sensed data for monitoring, surveillance, or risk mapping, particularly of vector-borne diseases. Nearly all studies used data from Landsat, the French Systeme Pour l'Observation de la Terre, and the National Oceanic and Atmospheric Administration's Advanced Very High Resolution Radiometer. New sensor systems are in orbit, or soon to be launched, whose data may prove useful for characterizing and monitoring the spatial and temporal patterns of infectious diseases. Increased computing power and spatial modeling capabilities of geographic information systems could extend the use of remote sensing beyond the research community into operational disease surveillance and control. This article illustrates how remotely sensed data have been used in health applications and assesses earth-observing satellites that could detect and map environmental variables related to the distribution of vector-borne and other diseases.

Satellite Communications↗

NASA NTRS2008

Multichannel Networked Phasemeter Readout and Analysis

Netmeter software reads a data stream from up to 250 networked phasemeters, synchronizes the data, saves the reduced data to disk (after applying a low-pass filter), and provides a Web server interface for remote control. Unlike older phasemeter software that requires a special, real-time operating system, this program can run on any general-purpose computer. It needs about five percent of the CPU (central processing unit) to process 20 channels because it adds built-in data logging and network-based GUIs (graphical user interfaces) that are implemented in Scalable Vector Graphics (SVG). Netmeter runs on Linux and Windows. It displays the instantaneous displacements measured by several phasemeters at a user-selectable rate, up to 1 kHz. The program monitors the measure and reference channel frequencies. For ease of use, levels of status in Netmeter are color coded: green for normal operation, yellow for network errors, and red for optical misalignment problems. Netmeter includes user-selectable filters up to 4 k samples, and user-selectable averaging windows (after filtering). Before filtering, the program saves raw data to disk using a burst-write technique.

Edmonds, Karina↗

NASA NTRS2011

Prominences: The Key to Understanding Solar Activity

Prominences are spectacular manifestations of both quiescent and eruptive solar activity. The largest examples can be seen with the naked eye during eclipses, making prominences among the first solar features to be described and catalogued. Steady improvements in temporal and spatial resolution from both ground- and space-based instruments have led us to recognize how complex and dynamic these majestic structures really are. Their distinguishing characteristics - cool knots and threads suspended in the hot corona, alignment along inversion lines in the photospheric magnetic field within highly sheared filament channels, and a tendency to disappear through eruption - offer vital clues as to their origin and dynamic evolution. Interpreting these clues has proven to be contentious, however, leading to fundamentally different models that address the basic questions: What is the magnetic structure supporting prominences, and how does so much cool, dense plasma appear in the corona? Despite centuries of increasingly detailed observations, the magnetic and plasma structures in prominences are poorly known. Routine measurements of the vector magnetic field in and around prominences have become possible only recently, while long-term monitoring of the underlying filament-channel formation process also remains scarce. The process responsible for prominence mass is equally difficult to establish, although we have long known that the chromosphere is the only plausible source. As I will discuss, however, the motions and locations of prominence material can be used to trace the coronal field, thus defining the magnetic origins of solar eruptions. A combination of observations, theory, and numerical modeling must be used to determine whether any of the competing theories accurately represents the physics of prominences. I will discuss the criteria for a successful prominence model, compare the leading models, and present in detail one promising, comprehensive scenario for prominence formation and evolution that could answer the two questions posed above.

Karpen, Judy T.↗

NASA NTRS2013

3D Radiative Transfer Effects in Multi-Angle/Multi-Spectral Radio-Polarimetric Signals from a Mixture of Clouds and Aerosols Viewed by a Non-Imaging Sensor

When observing a spatially complex mix of aerosols and clouds in a single relatively large field-of-view, nature entangles their signals non-linearly through polarized radiation transport processes that unfold in the 3D position and direction spaces. In contrast, any practical forward model in a retrieval algorithm will use only 1D vector radiative transfer (vRT) in a linear mixing technique. We assess the difference between the observed and predicted signals using synthetic data from a high-fidelity 3D vRT model with clouds generated using a Large Eddy Simulation model and an aerosol climatology. We find that this difference is signal--not noise--for the Aerosol Polarimetry Sensor (APS), an instrument developed by NASA. Moreover, the worst case scenario is also the most interesting case, namely, when the aerosol burden is large, hence hase the most impact on the cloud microphysics and dynamics. Based on our findings, we formulate a mitigation strategy for these unresolved cloud adjacency effects assuming that some spatial information is available about the structure of the clouds at higher resolution from "context" cameras, as was planned for NASA's ill-fated Glory mission that was to carry the APS but failed to reach orbit. Application to POLDER (POLarization and Directionality of Earth Reflectances) data from the period when PARASOL (Polarization and Anisotropy of Reflectances for Atmospheric Sciences coupled with Observations from a Lidar) was in the A-train is briefly discussed.

APS↗

DOE OSTI2026

CONTROL AND DATA ACQUISITION IN A CYBER-PHYSICAL MIDSTREAM TESTBED

This thesis presents the development of a laboratory-scale cyber–physical midstream pipeline testbed designed to address this gap and support research in industrial control systems security. The platform integrates pumps, valves, sensors, programmable logic controllers (PLCs), and a human–machine interface (HMI) to emulate the monitoring and control architecture of real pipeline operations. The physical process is implemented as a closed-loop liquid circulation system designed to replicate flow behavior characteristic of midstream pipeline infrastructure. The testbed enables real-time data acquisition of key process variables, including flow rate and pressure facilitating the generation of datasets representative of normal pipeline operation. A threat model encompassing common ICS attack vectors was developed, including sensor spoofing, command injection, false data injection, denial-of-service attacks, and relay manipulation. Multiple attack scenarios were implemented and evaluated to demonstrate how cyber intrusions targeting sensors, actuators, networks, and software propagate into measurable physical consequences in pipeline flow and pressure. The developed platform serves as a practical, cost-effective environment for experimentation, education, and future cybersecurity research in midstream pipeline systems.

42 ENGINEERING↗

DOE OSTI2019

Classifiers for Dissolution Events in Processing Facility Using Effluents Measurements

Inferring occurrences of dissolutions at a radiochemical processing facility using measurements from an independent monitoring system has potential for verifying operator declarations and compliance with nuclear technology use agreements. We consider the identification of such dissolution events using measurements of radioactive effluents collected at the facility’s off-gas stack. By using simple models for the source term based on radioactive decay-chains and sensor measurements of transported effluents, we formulate a simplified on/off classification problem. There are many available machine learning classification methods applicable to this problem, but they are subject to potential over-fitting. We mitigate this effect by fusing four promising but disparate classifiers: the ensemble of trees, support vector machines, naive Bayes, and k-nearest neighbors. Each classifier is trained to distinguish using effluents measurements between dissolutions of irradiated 237Np/238Pu and Cm/Cf targets from other (or no) radiochemical processing activities. We present Chow and ensemble of trees methods to fuse the classifier outputs to produce a single classification output, and thereby incorporate their diversity of design. We study the performance of these classifiers and fusers using measurements of87Kr,135Xe,138Xe, and138Cs isotopes,and present their training accuracy estimates using individual isotope measurements and all four isotopes taken together.

Rao, Nageswara S.↗

DOE OSTI2021

Scalable In Situ Computation of Lagrangian Representations via Local Flow Maps

In situ computation of Lagrangian flow maps to enable post hoc time-varying vector field analysis has recently become an active area of research. However, the current literature is largely limited to theoretical settings and lacks a solution to address scalability of the technique in distributed memory. To improve scalability, we propose and evaluate the benefits and limitations of a simple, yet novel, performance optimization. Our proposed optimization is a communication-free model resulting in local Lagrangian flow maps, requiring no message passing or synchronization between processes, intrinsically improving scalability, and thereby reducing overall execution time and alleviating the encumbrance placed on simulation codes from communication overheads. To evaluate our approach, we computed Lagrangian flow maps for four time-varying simulation vector fields and investigated how execution time and reconstruction accuracy are impacted by the number of GPUs per compute node, the total number of compute nodes, particles per rank, and storage intervals. Our study consisted of experiments computing Lagrangian flow maps with up to 67M particle trajectories over 500 cycles and used as many as 2048 GPUs across 512 compute nodes. In all, our study contributes an evaluation of a communication-free model as well as a scalability study of computing distributed Lagrangian flow maps at scale using in situ infrastructure on a modern supercomputer.

Sane, Sudhanshu↗

NASA NTRS1979

NASF transposition network: A computing network for unscrambling p-ordered vectors

The viewpoints of design, programming, and application of the transportation network (TN) is presented. The TN is a programmable combinational logic network that connects 521 memory modules to 512 processors. The unscrambling of p-ordered vectors to 1-ordered vectors in one cycle is described. The TN design is based upon the concept of cyclic groups from abstract algebra and primitive roots and indices from number theory. The programming of the TN is very simple, requiring only 20 bits: 10 bits for offset control and 10 bits for barrel switch shift control. This simple control is executed by the control unit (CU), not the processors. Any memory access by a processor must be coordinated with the CU and wait for all other processors to come to a synchronization point. These wait and synchronization events can be a degradation in performance to a computation. The TN application is for multidimensional data manipulation, matrix processing, and data sorting, and can also perform a perfect shuffle. Unlike other more complicated and powerful permutation networks, the TN cannot, if possible at all, unscramble non-p-ordered vectors in one cycle.

Lim, R. S.↗

NASA NTRS2018

Orion Optical Navigation Progress Toward Exploration: Mission 1

Optical navigation of human spacecraft was proposed on Gemini and implemented successfully on Apollo as a means of autonomously operating the vehicle in the event of lost communication with controllers on Earth. It shares a history with the "method of lunar distances" that was used in the 18th century and gained some notoriety after its use by Captain James Cook during his 1768 Pacific voyage of the HMS Endeavor. The Orion emergency return system utilizing optical navigation has matured in design over the last several years, and is currently undergoing the final implementation and test phase in preparation for Exploration Mission 1 (EM-1) in 2019. The software development is being worked as a Government Furnished Equipment (GFE) project delivered as an application within the Core Flight Software of the Orion camera controller module. The mathematical formulation behind the initial ellipse fit in the image processing is detailed in Christian. The non-linear least squares refinement then follows the technique of Mortari as an estimation process of the planetary limb using the sigmoid function. The Orion optical navigation system uses a body fixed camera, a decision that was driven by mass and mechanism constraints. The general concept of operations involves a 2-hour pass once every 24 hours, with passes specifically placed before all maneuvers to supply accurate navigation information to guidance and targeting. The pass lengths are limited by thermal constraints on the vehicle since the OpNav attitude generally deviates from the thermally stable tail-to-sun attitude maintained during the rest of the orbit coast phase. Calibration is scheduled prior to every pass due to the unknown nature of thermal effects on the lens distortion and the mounting platform deformations between the camera and star trackers. The calibration technique is described in detail by Christian, et al. and simultaneously estimates the Brown-Conrady coefficients and the Star Tracker/Camera interlock angles. Accurate attitude information is provided by the star trackers during each pass. Figure 1 shows the various phases of lunar return navigation when the vehicle is in autonomous operation with lost ground communication. The midcourse maneuvers are placed to control the entry interface conditions to the desired corridor for safe landing. The general form of optical navigation on Orion is where still images of the Moon or Earth are processed to find the apparent angular diameter and centroid in the camera focal plane. This raw data is transformed into range and bearing angle measurements using planetary data and precise star tracker inertial attitude. The measurements are then sent to the main flight computer's Kalman filter to update the onboard state vector. The images are, of course, collected over an arc to converge the state and estimate velocity. The same basic technique was used by Apollo to satisfy loss-of-comm, but Apollo used manual crew sightings with a vehicle-integral sextant instead of autonomously processing optical imagery. The software development is past its Critical Design Review, and is progressing through test and certification for human rating. In support of this, a hardware-in-the-loop test rig was developed in the Johnson Space Center Electro-Optics Lab to exercise the OpNav system prior to integrated testing on the Orion vehicle. Figure 2 shows the rig, which the test team has dubbed OCILOT (Orion Camera In the Loop Optical Testbed). Analysis performed to date shows a delivery that satisfies an allowable entry corridor as shown in Figure 3.

Holt, Greg N.↗

DOE OSTI2026

Time-resolved spray characterization via unified optical flow and binarization technique

This work leverages an unsupervised machine learning and advanced image processing techniques to characterize the breakup of fuel sprays in a small-scale combustor under reacting conditions, providing valuable insights into near-nozzle flow phenomenology. The proposed methodology integrates an improved optical flow model on a convolutional neural network to extract flow vectors with a binarization technique to assess droplets’ size and shape across the region of interest. The velocimetry approach demonstrates superior performance compared to a state-of-the-art optical flow model when applied to high-speed X-ray phase contrast spray images, achieving more accurate and reliable flow predictions. Moreover, breakup processes are quantified by breakup length and sphericity in accordance with velocity estimations, allowing a more complete characterization of the flow. This study establishes a robust methodology for analyzing spray morphology and primary breakup in compact combustors, contributing valuable means of understanding and optimizing fuel spray behavior in advanced combustion systems.

42 ENGINEERING↗

DOE OSTI2018

Search for dark matter in events with a hadronically decaying vector boson and missing transverse momentum in pp collisions at $\sqrt{s}=13$ TeV with the ATLAS detector

A search for dark matter (DM) particles produced in association with a hadronically decaying vector boson is performed using pp collision data at a centre-of-mass energy of s√=13 TeV corresponding to an integrated luminosity of 36.1 fb -1 , recorded by the ATLAS detector at the Large Hadron Collider. This analysis improves on previous searches for processes with hadronic decays of W and Z bosons in association with large missing transverse momentum (mono-W/Z searches) due to the larger dataset and further optimization of the event selection and signal region definitions. In addition to the mono-W/Z search, the as yet unexplored hypothesis of a new vector boson Z' produced in association with dark matter is considered (mono-Z' search). No significant excess over the Standard Model prediction is observed. The results of the mono-W/Z search are interpreted in terms of limits on invisible Higgs boson decays into dark matter particles, constraints on the parameter space of the simplified vector-mediator model and generic upper limits on the visible cross sections for W/Z+DM production. The results of the mono-Z' search are shown in the framework of several simplified-model scenarios involving DM production in association with the Z' boson.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

NASA NTRS1992

Development of a residual acceleration data reduction and dissemination plan

A major obstacle in evaluating the residual acceleration environment in an orbiting space laboratory is the amount of data collected during a given mission: gigabytes of data will be available as SAMS units begin to fly regularly. Investigators taking advantage of the reduced gravity conditions of space should not be overwhelmed by the accelerometer data which describe these conditions. We are therefore developing a data reduction and analysis plan that will allow principal investigators of low-g experiments to create experiment-specific residual acceleration data bases for post-flight analysis. The basic aspects of the plan can also be used to characterize the acceleration environment of earth orbiting laboratories. Our development of the reduction plan is based on the following program of research: the identification of experiment sensitivities by order of magnitude estimates and numerical modelling; evaluation of various signal processing techniques appropriate for the reduction, supplementation, and dissemination of residual acceleration data; and testing and implementation of the plan on existing acceleration data bases. The orientation of the residual acceleration vector with respect to some set of coordinate axes is important for experiments with known directional sensitivity. Orientation information can be obtained from the evaluation of direction cosines. Fourier analysis is commonly used to transform time history data into the frequency domain. Common spectral representations are the amplitude spectrum which gives the average of the components of the time series at each frequency and the power spectral density which indicates the power or energy present in the series per unit frequency interval. The data reduction and analysis scheme developed involves a two tiered structure to: (1) identify experiment characteristics and mission events that can be used to limit the amount of accelerator data an investigator should be interested in; and (2) process the data in a way that will be meaningful to the experiment objectives. A general outline of the plan is given.

Rogers, Melissa J. B.↗

DOE OSTI2021

Volumetric and shear strain localization throughout triaxial compression experiments on rocks

Deformation localization is a widely observed, but rarely quantified process in the crust. Recent observations suggest that the localization of seismicity and fracture networks can help identify the approach to catastrophic failure. Here, we quantify the localization processes of the volumetric and deviatoric strain components in twelve triaxial compression experiments imaged with X-ray tomography. We capture three-dimensional images of the rock cores during triaxial compressing toward failure, and then calculate the local strain components using digital volume correlation. The divergence and curl of the incremental displacement vector field provide the volumetric and deviatoric components of the strain field. We quantify localization using the proportion of the rock occupied by high magnitudes of the volumetric and deviatoric strains, and the Gini coefficient of these high magnitude strains, which measures the deviation from a uniform process. We find that the vast majority, but not all, of the experiments experience strain localization toward failure. The rocks typically experience their maximum degree of strain localization not immediately preceding failure, but on average at 90% of the failure stress. The volumetric strain tends to localize more than the deviatoric strain. Finally, these observations support using the localization of the volumetric strain, along with the deviatoric strain, to identify the evolution of the precursory phase preceding earthquakes.

58 GEOSCIENCES↗

DOE OSTI2023

Measurement of electroweak $Z\left(\nu \overline{\nu}\right)\gamma jj$ production and limits on anomalous quartic gauge couplings in pp collisions at $\sqrt{s}$ = 13 TeV with the ATLAS detector

The electroweak production of $Z\left(\nu \overline{\nu}\right)\gamma jj$ in association with two jets is studied in a regime with a photon of high transverse momentum above 150 GeV using proton–proton collisions at a centre-of-mass energy of 13 TeV at the Large Hadron Collider. The analysis uses a data sample with an integrated luminosity of 139 fb –1 collected by the ATLAS detector during the 2015–2018 LHC data-taking period. This process is an important probe of the electroweak symmetry breaking mechanism in the Standard Model and is sensitive to quartic gauge boson couplings via vector-boson scattering. The fiducial $Z\left(\nu \overline{\nu}\right)\gamma jj$ cross section for electroweak production is measured to be ${0.77}_{-0.30}^{+0.34}$ fb and is consistent with the Standard Model prediction. Evidence of electroweak $Z\left(\nu \overline{\nu}\right)\gamma jj$ production is found with an observed significance of 3.2σ for the background-only hypothesis, compared with an expected significance of 3.7σ. The combination of this result with the previously published ATLAS observation of electroweak $Z\left(\nu \overline{\nu}\right)\gamma jj$ production yields an observed (expected) signal significance of 6.3σ (6.6σ). Limits on anomalous quartic gauge boson couplings are obtained in the framework of effective field theory with dimension-8 operators.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

Short-Term Probabilistic Solar Forecasting via Reinforcement Learning over ECMWF

In this paper, we present an innovative reinforcement learning approach for short-term solar forecasting, leveraging data from the European Centre for Medium-Range Weather Forecasts (ECMWF). The methodology begins with the application of the System Advisor Model (SAM) to transform various ECMWF numerical weather prediction members into predictive photovoltaic power generation. To enhance the precision of deterministic forecasting, we introduce a dynamic model selection algorithm based on Q-learning. This algorithm dynamically identifies and utilizes the most accurate ensemble member for forecasting purposes. Furthermore, we employ a support vector regression surrogate model with a Gaussian distribution to generate probabilistic forecasts, providing a holistic view of solar energy generation uncertainty. To expedite the training process and make it more practical for real-world applications, we integrate a rolling update workflow. This innovative workflow reduces the training period from months to a mere 19 days, making our method highly efficient. Numerical results of the case study show that in comparison to benchmark models, the proposed method improves the deterministic and probabilistic solar forecasting accuracy by up to 40.84% and 48.42%, respectively.

ensemble forecasting↗

DOE OSTI2018

Analysis of the Switching Characteristics of MRAM Cells Based on Materials with Uniaxial Anisotropy

Magnetoresistive random access memory (MRAM) has some advantages over other types of memory. However, MRAM has one substantial drawback: the current density and magnetic field that must be applied to switch the spin-valve free layer inside an MRAM cell are too high. The dependence of the current density and switching magnetic field on the magnetic parameters of the material from which the ferromagnetic layers of a spin valve are fabricated is therefore analyzed. A comparison of the critical characteristics of a spin valve with longitudinal anisotropy shows that cobalt, iron, and alloys of them; cobalt ferroborates; and alloys of cobalt with gadolinium, are promising materials for fabricating spin valves. Bifurcation diagrams of equations that describe the valve switching process are presented and analyzed. The four optimum switching modes of a valve are selected, based on an investigation of the dynamics of the magnetization vector. The magnitudes of the external magnetic field and controlling injection current that correspond to stable MRAM cell switching are compared for a variety of materials. The switching time of an MRAM cell is estimated numerically, and the conditions for its optimum speed are determined. It is established that the most promising materials for spin-valve fabrication are Fe{sub 40}Co{sub 40}B{sub 20} and Co{sub 80}Gd{sub 20}, annealed at 300 and 200°C, respectively.

36 MATERIALS SCIENCE↗

NASA NTRS1980

Local distributed estimation

Based on partial differential equations of motion the closed form solution for the optimal estimation of a spatially continuous state vector is derived, using a continuously distributed sensor. Local control is shown to be the feedback that minimizes a quadratic performance index of sensor and process disturbances. A detailed example of the control of a string in tension is presented.

Schaechter, D. B.↗

NASA NTRS1982

Application of a recursive distortion estimator to the geodetic correction of thematic mapper imagery

It is pointed out that the higher resolution provided by the Thematic Mapper increases the demands on the accuracy needed by the ground processing in correcting for geodetic errors deriving from internal misalignments and uncertainties in the knowledge of spacecraft ephemeris and attitude. In addition, the Thematic Mapper will also process longer imagery intervals than previous missions. The recursive distortion estimator to be used is a Kalman filter. Here, a minimum variance spacecraft state error vector is estimated for known initial covariance of the elements of that vector and known image noise. Tests of the recursive distortion estimator with various spacecraft models carried out using a simulation of real world state vector dynamics are described. A determination is made of the density of control points needed to meet specified geometric correction requirements; it is expressed as a function of imagery interval length and control point measurement error.

Arnold, P.↗