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DOE OSTI2024

Nonstationarity in the global terrestrial water cycle and its interlinkages in the Anthropocene

Climate change and human activities alter the global freshwater cycle, causing nonstationary processes as its distribution shifting over time, yet a comprehensive understanding of these changes remains elusive. Here, we develop a remote sensing–informed terrestrial reanalysis and assess the nonstationarity of and interconnections among global water cycle components from 2003 to 2020. We highlight 20 hotspot regions where terrestrial water storage exhibits strong nonstationarity, impacting 35% of the global population and 45% of the area covered by irrigated agriculture. Emerging long-term trends dominate the most often (48.2%), followed by seasonal shifts (32.8%) and changes in extremes (19%). Notably, in mid-latitudes, this encompasses 34% of Asia and 27% of North America. The patterns of nonstationarity and their dominant types differ across other water cycle components, including precipitation, evapotranspiration, runoff, and gross primary production. These differences also manifest uniquely across hotspot regions, illustrating the intricate ways in which each component responds to climate change and human water management. Our findings emphasize the importance of considering nonstationarity when assessing water cycle information toward the development of strategies for sustainable water resource usage, enhancing resilience to extreme events, and effectively addressing other challenges associated with climate change.

Science & Technology - Other Topics↗

DOE OSTI2022

2022 AI Testbed Expeditions Report

By exploiting the coherent properties of a light source, coherent diffraction imaging (CDI) is able to obtain the sample image at a nanoscale resolution using the measured diffraction pattern. Bragg Coherent Diffraction Imaging (BCDI) has become valuable for recovering the displacement and strain field of crystals, providing a valuable tool in material science and solid-state physics. X-ray ptychography is another emerging CDI technique that can produce a high-resolution image of the extended sample and has become popular in many research areas (e.g., materials science, biology, electronics, and optics characterization). CDI including BCDI and ptychography has become an established technique in Synchrotron Facilities including the Advanced Photon Source (APS) and will greatly benefit from the 100x coherent flux increase of the upcoming APS Upgrade (APSU). The current image formation process in CDI employs iterative phase retrieval algorithms, which is a time-consuming and computationally expensive process. Especially after APSU, the traditional iterative methods will not be able to match the experimental data acquisition speed. We employ deep learning (DL) approach to replace the iterative approaches, therefore allowing hundreds of times faster recovery of the object. We developed AutoPhaseNN, a DL-based approach which learns to solve the inverse problem without labeled data. Taking 3D BCDI as a representative technique, AutoPhaseNN has been demonstrated to be one hundred times faster than traditional iterative phase retrieval methods while providing comparable image quality. The current network is trained with 64 x 64 x 64 data size, to achieve higher resolution imaging, we will need to scale the network to input and train/infer 3D arrays of size 256 x 256 x 256 (today) and of size 2560x2560x2560 (APSU). However, the scalability of the network is restricted due to the memory-intensive training process. To perform the training for a 256 x 256 x 256 data size, the required memory exceeds the capacity of the current machine. In this project, we explore using Sambanova system to train the network for the direct data inversion for CDI.

36 MATERIALS SCIENCE↗

NASA NTRS1985

Post-IOC space station: Models of operation and their implications for organizational behavior, performance and effectiveness

Issues of crew productivity during design work on space station are discussed. The crew productivity is defined almost exclusively in terms of human factors engineering and habitability design concerns. While such spatial environmental conditions are necessary to support crew performance and productivity, they are not sufficient to ensure high levels of crew performance and productivity on the post-Initial Operational Configurations (IOC) space station. The role of the organizational environment as a complement to the spatial environment for influencing crew performance in such isolated and confined work settings is examined. Three possible models of operation for post-IOC space station's organizational environment are identified and it is explained how they and space station's spatial environment will combine and interact to occasion patterns of crew behavior is suggested. A three phase program of research design: (1) identify patterns of crew behavior likely to be occasioned on post-IOC space station for each of the three models of operation; and (2) to determine proactive/preventative management strategies which could be adopted to maximize the emergence of preferred outcomes in crew behavior under each of the several spatial and organizational environment combinations.

Danford, S.↗

NASA NTRS2003

Simple gain probability functions for large reflector antennas of JPL/NASA

Simple models for the patterns as well as their cumulative gain probability and probability density functions of the Deep Space Network antennas are developed. These are needed for the study and evaluation of interference from unwanted sources such as the emerging terrestrial system, High Density Fixed Service, with the Ka-band receiving antenna systems in Goldstone Station of the Deep Space Network.

large reflector antenna probability density functi↗

NASA NTRS2018

Observations from Exploration of VTOL Urban Air Mobility Designs

NASA is exploring rotorcraft designs for VTOL air taxi operations, also known as urban air mobility (UAM) or on-demand mobility (ODM) applications. Several concept vehicles have been developed, intended to focus and guide NASA research activities in support of aircraft development for this emerging market. This paper summarizes the work conducted to date. To initially explore the broad design trade-space, three concept vehicles were designed: a quadrotor with electric propulsion; a side-by-side helicopter with hybrid propulsion; and a tiltwing with turbo-electric propulsion. Next a specific UAM mission was developed, accounting for the existing geography, population patterns, infrastructure, and weather in twenty-eight markets across the United States of America. Then in order to quantify the tradeoffs and performance targets necessary for practical implementation of the UAM vision, aircraft were designed to perform this mission, considering a range of aircraft types and propulsion system architectures: quadrotor aircraft, with turboshaft and all-electric propulsion; side-by-side aircraft, with turboshaft and all-electric propulsion; and lift+cruise aircraft with all-electric and turbo-electric propulsion. In examining these vehicles, performance targets and recurring technology themes emerged, which can guide investments in research and development within NASA, other government agencies, academia, and industry. In addition, results from the designs support observations about the trade-offs and key design decisions.

Observations from Exploration↗

DOE OSTI2024

Efficient distributed continual learning for steering experiments in real-time

Deep learning has emerged as a powerful method for extracting valuable information from large volumes of data. However, when new training data arrives continuously (i.e., is not fully available from the beginning), incremental training suffers from catastrophic forgetting (i.e., new patterns are reinforced at the expense of previously acquired knowledge). Training from scratch each time new training data becomes available would result in extremely long training times and massive data accumulation. Rehearsal-based continual learning has shown promise for addressing the catastrophic forgetting challenge, but research to date has not addressed performance and scalability. To fill this gap, we propose an approach based on a distributed rehearsal buffer that efficiently complements data-parallel training on multiple GPUs to achieve high accuracy, short runtime, and scalability. It leverages a set of buffers (local to each GPU) and uses several asynchronous techniques for updating these local buffers in an embarrassingly parallel fashion, all while handling the communication overheads necessary to augment input minibatches using unbiased, global sampling. We further propose a generalization of rehearsal buffers to support both classification and generative learning tasks, as well as more advanced rehearsal strategies (notably Dark Experience Replay, leveraging knowledge distillation). We illustrate this approach with a real-life HPC streaming application from the domain of ptychographic image reconstruction. Furthermore, we run extensive experiments on up to 128 GPUs of the ThetaGPU supercomputer to compare our approach with baselines representative of training-from-scratch (the upper bound in terms of accuracy) and incremental training (the lower bound). Results show that rehearsal-based continual learning achieves a top-5 validation accuracy close to the upper bound, while simultaneously exhibiting a runtime close to the lower bound.

Asynchronous data management↗

DOE OSTI2023

Manipulation of self-organized multi-vortical states in active magnetic roller suspensions

Ensembles of active magnetic colloids demonstrate complex collective behavior and self-organization when driven out of equilibrium by external magnetic fields. The interplay between magnetic and hydrodynamic interactions often result in spontaneous self-assembly and the emergence of localized vortices in ensembles of ferromagnetic rollers. We report experimental and computational study of the self-organized multi-vortical state in ensembles of magnetic rollers under the imposed external confining potential realized by patterned substrates. We explore the behavior of the system on a substrate patterned with shallow wells ordered in a lattice with square symmetry and lattice spacing smaller than the wells’ diameter. Here we demonstrate, that ensembles of active magnetic rollers evolve in response to changes in the geometry of the confining lattice from a globally correlated state characterized by anti-ferromagnetic vortex ordering to a state with rapidly changing particle flows and self-organized vortical states with a lattice constant larger than one of the confining pattern. Our experimental observations are accompanied by numerical simulations based on phenomenological coarse grained particle dynamics coupled to Navier–Stokes hydrodynamics in shallow water approximation. The reported results provide insights into the collective behavior of active magnetic rollers under confinement and suggest strategies for the manipulation of collective dynamic states in active magnetic liquids.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Phase and contrast moiré signatures in two-dimensional cone beam interferometry

Neutron interferometry has played a distinctive role in fundamental science and characterization of materials. Moiré neutron interferometers are candidate next-generation instruments: they offer microscopy-like magnification of the signal, enabling direct camera recording of interference patterns across the full neutron wavelength spectrum. Here we demonstrate the extension of phase-grating moiré interferometry to two-dimensional geometries. Our fork-dislocation phase gratings reveal phase singularities in the moiré pattern, and we explore orthogonal moiré patterns with two-dimensional phase gratings. Our measurements of phase topologies and gravitationally induced phase shifts are in good agreement with theory. These techniques can be implemented in existing neutron instruments to advance interferometric analyses of emerging materials and precision measurements of fundamental constants. Published by the American Physical Society 2024

Sarenac, D. (ORCID:0000000185753367)↗

NASA NTRS1990

Estimates of daily rainfall over the Amazon basin

Five geostationary satellite rain estimation techniques were tested over Amazonia. Individually, the techniques explained 1/4 to 1/3 of the variance of daily gage rainfall. Based in large part on cost, one technique, which involves a nonlinear relation in temperature, was selected to provide a mapping of daily Amazonia rainfall between May 6 and 12, 1987. Accumulated over the 7 days, rainfall by this technique averaged 40 mm. It varied from zero in the southeast to more than 150 mm in the northwest. To the southwest the predominantly convective pattern of the rain image was overlaid by a streakines, implying some baroclinic influence. In maps combining gage observations with satellite estimates, rainfall varied significantly from day to day. Only over the largest scale did a trend emerge: a tendency for rain to withdraw from south to north.

Martin, David W.↗

NASA NTRS1992

Self-organization via active exploration in robotic applications

We describe a neural network based robotic system. Unlike traditional robotic systems, our approach focussed on non-stationary problems. We indicate that self-organization capability is necessary for any system to operate successfully in a non-stationary environment. We suggest that self-organization should be based on an active exploration process. We investigated neural architectures having novelty sensitivity, selective attention, reinforcement learning, habit formation, flexible criteria categorization properties and analyzed the resulting behavior (consisting of an intelligent initiation of exploration) by computer simulations. While various computer vision researchers acknowledged recently the importance of active processes (Swain and Stricker, 1991), the proposed approaches within the new framework still suffer from a lack of self-organization (Aloimonos and Bandyopadhyay, 1987; Bajcsy, 1988). A self-organizing, neural network based robot (MAVIN) has been recently proposed (Baloch and Waxman, 1991). This robot has the capability of position, size rotation invariant pattern categorization, recognition and pavlovian conditioning. Our robot does not have initially invariant processing properties. The reason for this is the emphasis we put on active exploration. We maintain the point of view that such invariant properties emerge from an internalization of exploratory sensory-motor activity. Rather than coding the equilibria of such mental capabilities, we are seeking to capture its dynamics to understand on the one hand how the emergence of such invariances is possible and on the other hand the dynamics that lead to these invariances. The second point is crucial for an adaptive robot to acquire new invariances in non-stationary environments, as demonstrated by the inverting glass experiments of Helmholtz. We will introduce Pavlovian conditioning circuits in our future work for the precise objective of achieving the generation, coordination, and internalization of sequence of actions.

Ogmen, H.↗

NASA NTRS2013

A Short-Range Distance Sensor with Exceptional Linearity

A sensor has been demonstrated that can measure distance over a total range of about 300 microns to an accuracy of about 0.1 nm (resolution of about 0.01 nm). This represents an exceptionally large dynamic range of operation - over 1,000,000. The sensor is optical in nature, and requires the attachment of a mirror to the object whose distance is being measured. This work resulted from actively developing a white light interferometric system to be used to measure the depths of defects in the Space Shuttle Orbiter windows. The concept was then applied to measuring distance. The concept later expanded to include spectrometer calibration. In summary, broadband (i.e., white) light is launched into a Michelson interferometer, one mirror of which is fixed and one of which is attached to the object whose distance is to be measured. The light emerging from the interferometer has traveled one of two distances: either the distance to the fixed mirror and back, or the distance to the moving mirror and back. These two light beams mix and produce an interference pattern where some wavelengths interfere constructively and some destructively. Sending this light into a spectrometer allows this interference pattern to be analyzed, yielding the net distance difference between the two paths. The unique feature of this distance sensor is its ability to measure accurately distance over a dynamic range of more than one million, the ratio of its range (about 300 microns) to its accuracy (about 0.1 nanometer). Such a large linear operating range is rare and arises here because both amplitude and phase-matching algorithms contribute to the performance. The sensor is limited by the need to attach a mirror of some kind to the object being tracked, and by the fairly small total range, but the exceptional dynamic range should make it of interest.

Simmons, Steven↗

DOE OSTI2021

Resilient Information Architecture Platform for Smart Grid (RIAPS)

A number of emerging trends will substantially alter the operation and control of the electric grid over the next several decades. These trends include ensuring resiliency under severe weather events, increasing integration of renewable electricity generation, supporting changing electricity demand patterns, and the improving cost effectiveness of distributed energy resources. To address these challenges, the future “Smart Grid” management will need to transition from centralized to coordinated distributed control paradigm. Reliable operation of the Smart Grid depends on distributed intelligence realized through software applications that run on distributed computing devices attached to the power system to collect data and collaboratively manage resources. However, much of the existing software for Smart Grid-enabled devices is either proprietary or developed with custom solutions, which limits interoperability among the heterogeneous devices and hinders the ability to manage system-level reliability, security, and resiliency requirements. Additionally, this approach makes Smart Grid applications hard to maintain, evolve, verify, and replace; resulting in high development and deployment costs. Further development of the Smart Grid requires a reusable software base-layer to move from hard-coded functionality to a plug-and-play architecture capable of managing system-level objectives and constraints in addition to providing consistent common services across heterogeneous devices and applications. Vanderbilt University, in collaboration with North Carolina State University and Washington State University has developed a foundation ‘software platform’ for developing and deploying robust, reliable, effective and secure software applications for the Smart Grid. The Resilient Information Architecture Platform for the Smart Grid (RIAPS) provides core services for building effective and powerful smart grid applications. It offers unique services for real-time data dissemination, fault tolerance, and coordination across apps distributed over the network.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2022

Megadrought: A Series of Unfortunate La Niña Events?

Megadroughts are multidecadal periods of aridity more persistent than most droughts during the instrumental period. Paleoclimate evidence suggests that megadroughts occur in many parts of the world, including North America, Central America, western Europe, eastern Asia, and northern Africa. It remains unclear to what extent such megadroughts require external forcing or whether they can arise from internal climate variability alone. A novel statistical–dynamical approach is used to evaluate the possibility that such events arise solely as a function of interannual tropical sea surface temperature (SST) variations. A statistical emulator of tropical SST variations is constructed by using an empirical moving-blocks bootstrap approach that randomly samples multiyear sequences of the observational SST record. This approach preserves the power spectrum, seasonal cycle, and spatial pattern of El Niño-Southern Oscillation (ENSO) but removes longer timescale fluctuations embedded in the observational record. These resampled SST anomalies are then used to force an atmospheric model (the Community Atmosphere Model Version 5). As megadroughts emerge in this run, they should, therefore, be solely a consequence of La Niña sequences combined with internal atmospheric variability and persistence driven by soil moisture storage and other land-surface processes. We indeed find that megadroughts in this simulation have an amplitude-duration rate that is generally indistinguishable from the rate documented in paleoclimate records of the western United States. Our findings support the idea that megadroughts may occur randomly when the unforced climate system evolves freely over a sufficiently long period of time, implying that an unforced unusual but statistically plausible series of La Niña events may be sufficient to generate megadrought.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Near field excited state imaging via stimulated electron energy gain spectroscopy of localized surface plasmon resonances in plasmonic nanorod antennas

Continuous wave (cw) photon stimulated electron energy loss and gain spectroscopy (sEELS and sEEGS) is used to image the near field of optically stimulated localized surface plasmon resonance (LSPR) modes in nanorod antennas. An optical delivery system equipped with a nanomanipulator and a fiber-coupled laser diode is used to simultaneously irradiate plasmonic nanostructures in a (scanning) transmission electron microscope. The nanorod length is varied such that the m = 1, 2, and 3 LSPR modes are resonant with the laser energy and the optically stimulated near field spectra and images of these modes are measured. Various nanorod orientations are also investigated to explore retardation effects. Optical and electron beam simulations are used to rationalize the observed patterns. As expected, the odd modes are optically bright and result in observed sEEG responses. The m = 2 dark mode does not produce a sEEG response, however, when tilted such that retardation effects are operative, the sEEG signal emerges. Thus, we demonstrate that cw sEEGS is an effective tool in imaging the near field of the full set of nanorod plasmon modes of either parity.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Vibronic coupling in energy transfer dynamics and two-dimensional electronic–vibrational spectra

We introduce a heterodimer model in which multiple mechanisms of vibronic coupling and their impact on energy transfer can be explicitly studied. We consider vibronic coupling that arises through either Franck-Condon activity in which each site in the heterodimer has a local electron-phonon coupling or Herzberg-Teller activity in which the transition dipole moment coupling the sites has an explicit vibrational mode-dependence. We have computed two-dimensional electronic-vibrational (2DEV) spectra for this model while varying the magnitude of these two effects and find that 2DEV spectra contain static and dynamic signatures of both types of vibronic coupling. Franck-Condon activity emerges through a change in the observed excitonic structure, while Herzberg-Teller activity is evident in the appearance of significant side-band transitions that mimic the lower-energy excitonic structure. A comparison of quantum beating patterns obtained from analysis of the simulated 2DEV spectra shows that this technique can report on the mechanism of energy transfer, elucidating a means of experimentally determining the role of specific vibronic coupling mechanisms in such processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS2007

Detection and enforcement of failure-to-yield in an emergency vehicle preemption system

An intersection controlled by an intersection controller receives trigger signals from on-coming emergency vehicles responding to an emergency call. The intersection controller initiates surveillance of the intersection via cameras installed at the intersection in response to a received trigger signal. The surveillance may begin immediately upon receipt of the trigger signal from an emergency vehicle, or may wait until the intersection controller determines that the signaling emergency vehicle is in the field of view of the cameras at the intersection. Portions of the captured images are tagged by the intersection controller based on tag signals transmitted by the vehicle or based on detected traffic patterns that indicate a potential traffic violation. The captured images are downloaded to a processing facility that analyzes the images and automatically issues citations for captured traffic violations.

Bachelder, Aaron↗

NASA NTRS2011

Marine Microbial Mats and the Search for Evidence of Life in Deep Time and Space

Cyanobacterial mats in extensive seawater evaporation ponds at Guerrero Negro, Baja California, Mexico, have been excellent subjects for microbial ecology research. The studies reviewed here have documented the steep and rapidly changing environmental gradients experienced by mat microorganisms and the very high rates of biogeochemical processes that they maintained. Recent genetic studies have revealed an enormous diversity of bacteria as well as the spatial distribution of Bacteria, Archaea and Eukarya. These findings, together with emerging insights into the intimate interactions between these diverse populations, have contributed substantially to our understanding of the origins, environmental impacts, and biosignatures of photosynthetic microbial mats. The biosignatures (preservable cells, sedimentary fabrics, organic compounds, minerals, stable isotope patterns, etc.) potentially can serve as indicators of past life on early Earth. They also can inform our search for evidence of any life on Mars. Mars exploration has revealed evidence of evaporite deposits and thermal spring deposits; similar deposits on Earth once hosted ancient microbial mat ecosystems.

Des Marais, David J.↗

NASA NTRS2012

Emission Patterns of Solar Type III Radio Bursts: Stereoscopic Observations

Simultaneous observations of solar type III radio bursts obtained by the STEREO A, B, and WIND spacecraft at low frequencies from different vantage points in the ecliptic plane are used to determine their directivity. The heliolongitudes of the sources of these bursts, estimated at different frequencies by assuming that they are located on the Parker spiral magnetic field lines emerging from the associated active regions into the spherically symmetric solar atmosphere, and the heliolongitudes of the spacecraft are used to estimate the viewing angle, which is the angle between the direction of the magnetic field at the source and the line connecting the source to the spacecraft. The normalized peak intensities at each spacecraft Rj = Ij /[Sigma]Ij (the subscript j corresponds to the spacecraft STEREO A, B, and WIND), which are defined as the directivity factors are determined using the time profiles of the type III bursts. It is shown that the distribution of the viewing angles divides the type III bursts into: (1) bursts emitting into a very narrow cone centered around the tangent to the magnetic field with angular width of approximately 2 deg and (2) bursts emitting into a wider cone with angular width spanning from [approx] -100 deg to approximately 100 deg. The plots of the directivity factors versus the viewing angles of the sources from all three spacecraft indicate that the type III emissions are very intense along the tangent to the spiral magnetic field lines at the source, and steadily fall as the viewing angles increase to higher values. The comparison of these emission patterns with the computed distributions of the ray trajectories indicate that the intense bursts visible in a narrow range of angles around the magnetic field directions probably are emitted in the fundamental mode, whereas the relatively weaker bursts visible to a wide range of angles are probably emitted in the harmonic mode.

Thejappa, G.↗