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At least 415 records · Page 23

Tunable Fiber Bragg Grating Ring Lasers using Macro Fiber Composite Actuators

The research reported herein includes the fabrication of a tunable optical fiber Bragg grating (FBG) fiber ring laser (FRL)1 from commercially available components as a high-speed alternative tunable laser source for NASA Langley s optical frequency domain reflectometer (OFDR) interrogator, which reads low reflectivity FBG sensors. A Macro-Fiber Composite (MFC) actuator invented at NASA Langley Research Center (LaRC) was selected to tune the laser. MFC actuators use a piezoelectric sheet cut into uniaxially aligned rectangular piezo-fibers surrounded by a polymer matrix and incorporate interdigitated electrodes to deliver electric fields along the length of the piezo-fibers. This configuration enables MFC actuators to produce displacements larger than the original uncut piezoelectric sheet. The FBG filter was sandwiched between two MFC actuators, and when strained, produced approximately 3.62 nm of wavelength shift in the FRL when biasing the MFC actuators from 500 V to 2000 V. This tunability range is comparable to that of other tunable lasers and is adequate for interrogating FBG sensors using OFDR technology. Three different FRL configurations were studied. Configuration A examined the importance of erbium-doped fiber length and output coupling. Configuration B demonstrated the importance of the FBG filter. Configuration C added an output coupler to increase the output power and to isolate the filter. Only configuration C was tuned because it offered the best optical power output of the three configurations. Use of Plastic Optical Fiber (POF) FBG s holds promise for enhanced tunability in future research.

Geddis, Demetris L.↗

Algorithm for Wavefront Sensing Using an Extended Scene

A recently conceived algorithm for processing image data acquired by a Shack-Hartmann (SH) wavefront sensor is not subject to the restriction, previously applicable in SH wavefront sensing, that the image be formed from a distant star or other equivalent of a point light source. That is to say, the image could be of an extended scene. (One still has the option of using a point source.) The algorithm can be implemented in commercially available software on ordinary computers. The steps of the algorithm are the following: 1. Suppose that the image comprises M sub-images. Determine the x,y Cartesian coordinates of the centers of these sub-images and store them in a 2xM matrix. 2. Within each sub-image, choose an NxN-pixel cell centered at the coordinates determined in step 1. For the ith sub-image, let this cell be denoted as si(x,y). Let the cell of another subimage (preferably near the center of the whole extended-scene image) be designated a reference cell, denoted r(x,y). 3. Calculate the fast Fourier transforms of the sub-sub-images in the central NxN portions (where N < N and both are preferably powers of 2) of r(x,y) and si(x,y). 4. Multiply the two transforms to obtain a cross-correlation function Ci(u,v), in the Fourier domain. Then let the phase of Ci(u, v) constitute a phase function, phi(u,v). 5. Fit u and v slopes to phi (u,v) over a small u,v subdomain. 6. Compute the fast Fourier transform, Si(u,v) of the full NxN cell si(x,y). Multiply this transform by the u and phase slopes obtained in step 4. Then compute the inverse fast Fourier transform of the product. 7. Repeat steps 4 through 6 in an iteration loop, cumulating the u and slopes, until a maximum iteration number is reached or the change in image shift becomes smaller than a predetermined tolerance. 8. Repeat steps 4 through 7 for the cells of all other sub-images.

Sidick, Erkin↗

MimicGAN: Robust Projection onto Image Manifolds with Corruption Mimicking

In the past few years, Generative Adversarial Networks (GANs) have dramatically advanced our ability to represent and parameterize high-dimensional, non-linear image manifolds. As a result, they have been widely adopted across a variety of applications, ranging from challenging inverse problems like image completion, to problems such as anomaly detection and adversarial defense. A recurring theme in many of these applications is the notion of projecting an image observation onto the manifold that is inferred by the generator. In this context, Projected Gradient Descent (PGD) has been the most popular approach, which essentially optimizes for a latent vector that minimizes the discrepancy between a generated image and the given observation. However, PGD is a brittle optimization technique that fails to identify the right projection (or latent vector) when the observation is corrupted, or perturbed even by a small amount. Such corruptions are common in the real world, for example images in the wild come with unknown crops, rotations, missing pixels, or other kinds of non-linear distributional shifts which break current encoding methods, rendering downstream applications unusable. To address this, we propose corruption mimicking—a new robust projection technique, that utilizes a surrogate network to approximate the unknown corruption directly at test time, without the need for additional supervision or data augmentation. The proposed method is significantly more robust than PGD and other competing methods under a wide variety of corruptions, thereby enabling a more effective use of GANs in real-world applications. Finally, more importantly, we show that our approach produces state-of-the-art performance in several GAN-based applications—anomaly detection, domain adaptation, and adversarial defense, that benefit from an accurate projection.

97 MATHEMATICS AND COMPUTING↗

Isospin 0 and 2 two-pion scattering at physical pion mass using all-to-all propagators with periodic boundary conditions in lattice QCD

A study of two-pion scattering for the isospin channels, 𝐼 = 0 and 𝐼 = 2, using lattice QCD is presented. Möbius domain-wall fermions, on top of the Iwasaki-DSDR gauge action for gluons with periodic boundary conditions, are used for the lattice computations, which are carried out on two ensembles of gauge field configurations generated by the RBC and UKQCD Collaborations with physical masses, inverse lattice spacings of 1.023 and 1.378 GeV, and spatial extents of 𝐿 = 4.63 and 4.58 fm, respectively. The all-to-all propagator method is employed to compute a matrix of correlation functions of two-pion operators. The generalized eigenvalue problem (GEVP) is solved for a matrix of correlation functions to extract phase shifts with multiple states—two pions with a nonzero relative momentum, as well as two pions at rest. Our results for phase shifts for both the 𝐼 = 0 and 𝐼 = 2 channels are consistent with the Roy equation and chiral perturbation theory, though at this preliminary stage our errors for 𝐼 = 0 are large. An important outcome of this work is that we are successful in extracting two-pion excited states, which are useful for studying 𝐾 → 𝜋⁢𝜋 decay, on physical-mass ensembles using the GEVP.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Spacecraft Observatory Benchmark Problem for Optical Disturbance Rejection

Since mid-1980s NASA has launched several first-generation interplanetary observatory missions. A salient feature of these missions has been the mounting of the optical payload on top of a large flexible space structure. This imposes challenging control-structure interaction problems (CSI) that have been studied over several decades. The Dec. 2021 launch of the James Webb Telescope marks the latest example of such a mission. One way to encourage development of novel control methods is to provide a benchmark problem for researchers. By the mid-2000s, there were a few well-known benchmark problems developed by the control community with a focus on CSI applications. However, in the past 15 years, the control challenges in optical observation missions have shifted from CSI to line-of-sight (LOS) precision pointing. This is because popular designs of the second-generation (Gen II) space earth missions have eliminated the large structure interface by mounting the optical payload directly on top of a rigid bus platform. The focus now is to achieve accurate pointing with maximum rejection of the surrounding disturbances. The NASA Safety and Engineering Center (NESC) has tasked T he Aerospace Corporation to develop a Benchmark Problem to study the challenging control issues that Gen II observatory missions encounter. This software tool is to be released as a public domain platform aimed at government, academic, and industry researchers. The focus of this benchmark problem is for researchers to design a set of innovative payload control laws with the maximum Optical Disturbance Rejection (ODR) capability to meet a set of pre-defined μrad-level of LOS jitter requirements. This paper describes the development of the benchmark problem. Aerospace/NASA will provide an integrated LOS plant model and disturbance/command profiles for users to run their design and simulation with as well as a user’s guide describing the required interfaces. The Aerospace Corp is also working to develop a hardware fast steering mirror testbed for users to demonstrate their innovative design in real hardware, if so desired.

Spacecraft Observatory Benchmark Problem↗

Biological Research and Space Health Enabled by Machine Learning to Support Deep Space Missions

A key science goal of the NASA “Moon to Mars” campaign is to understand how biology responds to the Lunar, Martian, and deep space environments in order to advance fundamental knowledge, reduce risk, and support safe, productive human space missions. Through the powerful emerging computer science approaches of artificial intelligence (AI) and machine learning (ML), a paradigm shift has begun in biomedical science and engineered astronaut health systems, to enable Earth-independence and autonomy of mission operations. We present a decadal view of AI/ML architecture to support deep space mission goals, developed in concert with leaders in the field. We describe current AI/ML methods to support 1) fundamental biology, 2) in situ analytics, 3) high performance computing hardware, 4) automated science, 5) self-driving labs, 6) remote data management, 7) integrated real-time mission biomonitoring, and 8) a Precision Space Health system. Cutting-edge AI/ML approaches that can be integrated to support these domains include active learning, explainable AI, adaptive learning, causal inference, knowledge graphs, federated learning, transfer learning, and large language models. Finally, we present results from several current ML projects that are underway in the field to address key challenges of small sample n, high feature count, heterogeneity, and sparse data. These include 1) connecting omics data to phenotypic data using an ensemble model to infer causality of spaceflight rodent liver health disruption, 2) usage of explainable ML to interrogate the muscular underpinnings of spaceflight muscle atrophy, 3) ML models analyzing and determining directed acyclic graphs of human space health risk leveraging rodent bone datasets, 4) usage of large pre-trained models connecting biomedical knowledgebases with small spaceflight datasets to understand gene-to-gene interaction networks, and 5) a suite of benchmarked open science datasets (spaceflight mouse liver; radiation DNA damage) enabling programmers to identify the best ML algorithms to answer space biological science questions.

space biology↗

Biological Research and Space Health Enabled by Machine Learning to Support Deep Space Missions

A key science goal of the NASA “Moon to Mars” campaign is to understand how biology responds to the Lunar, Martian, and deep space environments in order to advance fundamental knowledge, reduce risk, and support safe, productive human space missions. Through the powerful emerging computer science approaches of artificial intelligence (AI) and machine learning (ML), a paradigm shift has begun in biomedical science and engineered astronaut health systems, to enable Earth-independence and autonomy of mission operations. We present a decadal view of AI/ML architecture to support deep space mission goals, developed in concert with leaders in the field. We describe current AI/ML methods to support 1) fundamental biology, 2) in situ analytics, 3) high performance computing hardware, 4) automated science, 5) self-driving labs, 6) remote data management, 7) integrated real-time mission biomonitoring, and 8) a Precision Space Health system. Cutting-edge AI/ML approaches that can be integrated to support these domains include active learning, explainable AI, adaptive learning, causal inference, knowledge graphs, federated learning, transfer learning, and large language models. Finally, we present results from several current ML projects that are underway in the field to address key challenges of small sample n, high feature count, heterogeneity, and sparse data. These include 1) connecting omics data to phenotypic data using an ensemble model to infer causality of spaceflight rodent liver health disruption, 2) usage of explainable ML to interrogate the muscular underpinnings of spaceflight muscle atrophy, 3) ML models analyzing and determining directed acyclic graphs of human space health risk leveraging rodent bone datasets, 4) usage of large pre-trained models connecting biomedical knowledgebases with small spaceflight datasets to understand gene-to-gene interaction networks, and 5) a suite of benchmarked open science datasets (spaceflight mouse liver; radiation DNA damage) enabling programmers to identify the best ML algorithms to answer space biological science questions.

space biology↗

Real-Time GPU-Accelerated OFDR With an Integrated Auxiliary Interferometer

A GPU-accelerated optical frequency domain reflectometry (OFDR) system with an improved integrated auxiliary interferometer is proposed. Unlike conventional approaches that require separate auxiliary interferometers and multiple detection channels, the proposed OFDR system embeds this functionality directly into the signal via an intentional beat component. This enables self-calibration of laser nonlinearity while maintaining a cost-effective hardware configuration. Building on this simplified configuration, the system leverages GPU acceleration with an NVIDIA RTX 4070 Ti to achieve real-time performance, delivering high-throughput signal processing for continuous OFDR interrogation. The signal processing pipeline comprises signal capture, resampling for nonlinearity compensation, and frequency shift computation, all optimized for parallel execution. Hardware benchmarking demonstrates substantial acceleration over CPU implementations, achieving up to a 45× speedup for resampling and frequency shift computations and enabling processing latencies below 30 ms. Thermal response validation is conducted under two complementary scenarios: localized heating using a water bath and cryogenic-temperature conditions using liquid nitrogen. Under localized heating, the system achieves an accuracy of 0.249 °C with a thermal sensitivity of 5.971 GHz/°C, while cryogenic-temperature validation demonstrates a frequency shift response with a sensitivity of 2.383 GHz/°C and an accuracy of 2.04 °C. The high acceleration of the proposed GPU-accelerated OFDR system and its accuracy are achieved by exploiting CUDA-based stride indexing, enabling efficient parallel segmentation and processing of large datasets without additional memory copies. The benchmarking results confirm the robustness, accuracy, and deployability of the proposed OFDR system across a wide temperature range, establishing it as a practical platform for real-time distributed fiber sensing in structurally dynamic environments.

Harb, Salah [Lawrence Berkeley National Laboratory↗

Distributed Resources for the Earth System Grid Federation (ESGF) Advanced Management (DREAM). Final Report

Distributed Resources for the Earth System Grid Federation (ESGF) Advanced Management (DREAM) is a proposed system that will enable data from an infinite number of diverse sources to be organized and accessed from anywhere using any handheld or other computer device. The approach offers a powerful roadmap for the creation and integration of a unified knowledge base of an entire ecosystem, including its many geophysical, geographical, social, political, agricultural, energy, transportation, and cyber aspects. The resulting aggregation of data has the potential to generate an informational universe of unprecedented size that has never before been possible due to the prohibitive costs, managerial complexity, and technical barriers associated with ever-changing exponential-growth data flows. We envision that DREAM will accelerate discovery by enabling climate researchers, among other types of researchers, to manage, analyze, and visualize data from earth-scale measurements and simulations. DREAM’s success will be built on proven components that leverage existing services and resources. A key building block for DREAM will be the ESGF, chaired by Dean N. Williams. Expanding on the existing ESGF, the project will ensure that the access, storage, movement, and analysis of the large quantities of data that are processed and produced by diverse science projects can be dynamically distributed with proper resource management. Much of the Office of Science data is currently generated by multiple stand-alone facilities. DREAM can collect data accumulated from these facilities and incorporate it into a fully integrated network accessible from anywhere in the world. The result is a completely new paradigm shift for data management, analysis, and visualization enabling researchers to: Manage their calculations, data, tools, and research results; Ensure that all data are sharable, reproducible and (re)usable—accompanied by appropriate metadata describing its provenance, syntax, and semantics at creation; Advance application performance by selectively adapting APIs and services in response to scientific requirements and architectural complexities; and Provide scalable interactive resource management—navigate data and metadata at multiple levels, provide architecture-aware data integration, analysis and visualization tools. We will engage closely with DOE, NASA, and NOAA science groups working at the leading edge of computing. These engagements—in domains such as biology, climate, and hydrology—will allow us to advance disciplinary science goals and inform our development of technologies that can accelerate discovery across DOE more broadly. We will advertise and promote our technologies via dedicated workshops, tutorials, and sessions at conferences, stand-alone events with broad inter-disciplinary invitation, and engagements with leadership facilities.

54 ENVIRONMENTAL SCIENCES↗

Time-Domain Nuclear Magnetic Resonance Determination of Wettability Alteration: Analysis for Low-Salinity Water

Wettability has been shown to influence oil recovery. This property has become central to low-salinity (LSW) and smart (SWF) water flooding recovery mechanisms research. The challenge lies in the fact that oil recovery results from the combined effects of solid-liquid and liquid-liquid interactions. This demands methods that allow an independent interpretation of wettability alteration contributions. The primary objective of this work is to assess changes in wettability through the application of Time-Domain Nuclear Magnetic Resonance (TD-NMR) T 2 distribution and diffusion coefficient, starting with a well-controlled porous system, that is, glass beads, and then a model rock (Berea), in the presence of one phase, either oil or brine exclusively. Subsequently, two-phase fluid saturation was tested. For the glass beads, dimethyldichlorosilane was used to induce a hydrophobic response, as confirmed by contact angle experiments on slides of the same material. Sodium sulfate was used for its known positive influence on oil recovery during LSW and SWF. In cases where alteration of surface properties was expected, a leftward shift of the average T 2 distribution curve modes, accompanied by a reduction on the diffusion coefficient during the aging process was observed. The results of this work confirm that fluid-solid interactions during LSW and SWF, namely a shift in wettability, take place after the injection of low-salinity water.

42 ENGINEERING↗

Effects of vibration and shock on the performance of gas-bearing space-power Brayton cycle turbomachinery. Part 3: Sinusoidal and random vibration data reduction and evaluation, and random vibration probability analysis

The random vibration response of a gas bearing rotor support system has been experimentally and analytically investigated in the amplitude and frequency domains. The NASA Brayton Rotating Unit (BRU), a 36,000 rpm, 10 KWe turbogenerator had previously been subjected in the laboratory to external random vibrations, and the response data recorded on magnetic tape. This data has now been experimentally analyzed for amplitude distribution and magnetic tape. This data has now been experimentally analyzed for amplitude distribution and frequency content. The results of the power spectral density analysis indicate strong vibration responses for the major rotor-bearing system components at frequencies which correspond closely to their resonant frequencies obtained under periodic vibration testing. The results of amplitude analysis indicate an increasing shift towards non-Gaussian distributions as the input level of external vibrations is raised. Analysis of axial random vibration response of the BRU was performed by using a linear three-mass model. Power spectral densities, the root-mean-square value of the thrust bearing surface contact were calculated for specified input random excitation.

Tessarzik, J. M.↗

The Spatiotemporal Structure of 20th Century Climate Variations in Observations and Reanalyses: Pacific Pan-Decadal Variability - Part 2

The dominant interannual El Nino-Southern Oscillation phenomenon (ENSO) and the short length of climate observation records make it difficult to study long-term climate variations in the spatiotemporal domain. Based on the fact that the ENS0 signal spreads to remote regions and induces delayed climate variation through atmospheric teleconnections, we develop an ENSO-removal method through which the ENS0 signal can be approximately removed at the grid box level from the spatiotemporal field of a climate parameter. After this signal is removed, long-term climate variations, namely, the global warming trend (GW) and the Pacific pan-decadal variability (PDV), are isolated at middle and low latitudes in the climate parameter fields from observed and reanalyses datasets. In this study, we show that one of several PDV interdecadal regime shifts occurred during the 1990s. This significant change in the Pacific basin is comparable but opposite in phase to the 1976 climate regime shift, which results persisting warming in the central-eastern Pacific, and cooling in the North and South Pacific. The 1990s PDV regime shift is consistent with observed changes in ocean biosphere and ocean circulation. A comprehensive picture of PDV as manifested in the troposphere and at the surface is described. In general, the PDV spatial patterns in different parameter fields share some similarities with the patterns associated with ENSO, but important differences exist. First, the PDV atmospheric circulation pattern is shifted westward by about 20deg and its zonal extent is limited to approx.60deg compared to approx.110deg for ENS0 pattern. The westward shift of the PDV wave train produces a different, more west-east oriented, North American teleconnection pattern. The lack of a strong PDV surface temperature (ST) signal in the western equatorial Pacific and the relatively strong ST signal in the subtropical regions are consistent with an atmospheric overturning circulation response that differs from the one associated with ENSO.

Chen, Junye↗

Dimits shift, avalanche-like bursts, and solitary propagating structures in the two-field flux-balanced Hasegawa–Wakatani model for plasma edge turbulence

We show that the recently introduced two-field flux-balanced Hasegawa–Wakatani (BHW) model captures the key features of drift-wave turbulent transport mediated by zonal flows observed in more complete and accurate gyrokinetic simulations, such as the existence of a nonlinear upshift of the threshold for drift wave turbulence driven transport, often called the Dimits shift, as well as non-local transport with avalanche bursts and solitary propagating structures. Because of the approximations made in the BHW model, these observations are made for the particle flux instead of the heat flux more commonly studied in ion temperature gradient (ITG) driven turbulence in fluid or gyrokinetic codes. Many of these features are not seen in other Hasegawa–Wakatani models, which confirm the critical role of the electron dynamics parallel to the magnetic field lines. To address questions regarding the role of boundary conditions on the drift-wave zonal flow dynamics, we apply our model to both a channel domain geometry and the more typical doubly periodic geometry. We only observe strong soliton-like solutions in the particle flux for the channel geometry, in the vicinity of the boundaries, where strong velocity shear and density gradients are generated, which are absent in the doubly periodic simulations. Changing the aspect ratio of the simulation domain also has a significant effect. In domains which are elongated in the radial direction, more complex multi-scale dynamics takes place, with multiple zonal jets interacting with each other, and large scale avalanches.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

An Analysis of Operational Total Lightning Data During Long-Track Tornadoes

The 27 April 2011 tornado outbreak brought three distinct waves of tornadic thunderstorms to portions of Mississippi, Alabama, Tennessee, and Georgia, striking the Tennessee Valley of north Alabama and southern Tennessee particularly hard. A total of 42 tornado paths were surveyed across the fourteen county area covered by the National Weather Service (NWS) forecast office in Huntsville, Alabama. Ten of these tornadoes were on the ground for at least 20 miles, two had total path lengths over 130 miles, and six tornadoes were classified as violent (EF-4 or EF-5 on the Enhanced Fujita Scale). Many of these tornadoes occurred within the domain of the North Alabama Lightning Mapping Array (NALMA), a ground-based total lightning detection network owned and operated by the NASA Marshall Space Flight Center. Since 2003, the NASA Short-term Prediction Research and Transition Center has supplied data from NALMA in real time to NWS forecast offices in Huntsville, Knoxville/Tri-Cities, Birmingham, and Nashville. Previous research has documented the utility of total lightning information in predicting tornadogenesis, particularly when combined with other remote sensing tools. Basic warning decision-making during events such as 27 April is not the most difficult part of the process; instead, the focus of warning meteorologists shifts to looking for changes in intensity or possible particularly dangerous situations, since doppler radar velocity data often cannot distinguish between weak and strong tornadoes. To that end, this research attempts to determine if any correlation exists between flash densities of the longest-tracked tornadoes over time, and the surveyed wind speeds of the tornadoes. The long-track EF-5 tornado which struck the Hackleburg, Phil Campbell, and Tanner communities in north Alabama was the primary focus of this research due to its intensity and extended life cycle. However, not all tornadoes were available for total lightning analysis due to widespread power outages which negatively affected the detection efficiency and operation of the NALMA. Therefore, additional storms from 2008-2010 with tracks of at least 20 miles were analyzed for comparison purposes.

Carcione, Brian C.↗

Characterizing the Non-linear Interactions Between Tide, Storm Surge, and River Flow in the Delaware Bay Estuary, United States

Low-lying coastal areas in the mid-Atlantic region are prone to compound flooding resulting from the co-occurrence of river floods and coastal storm surges. To better understand the contribution of non-linear tide-surge-river interactions to compound flooding, the unstructured-grid Finite Volume Community Ocean Model was applied to simulate coastal storm surge and flooding in the Delaware Bay Estuary in the United States. The model was validated with tide gauge data in the estuary for selected hurricane events. Non-linear interactions between tide-surge-river were investigated using a non-stationary tidal analysis method, which decomposes the interactions’ components at the frequency domain. Model results indicated that tide-river interactions damped semidiurnal tides, while the tide-surge interactions mainly influenced diurnal tides. Tide-river interactions suppressed the water level upstream while tide-surge interaction increased the water level downstream, which resulted in a transition zone of damping and enhancing effects where the tide-surge-river interaction was prominent. Evident compound flooding was observed as a result of non-linear tide-surge-river interactions. Furthermore, sensitivity analysis was carried out to evaluate the effect of river flooding on the non-linear interactions. The transition zone of damping and enhancing effects shifted downstream as the river flow rate increased.

54 ENVIRONMENTAL SCIENCES↗

Cloud adjustments from large-scale smoke–circulation interactions strongly modulate the southeastern Atlantic stratocumulus-to-cumulus transition

Smoke from southern Africa blankets the southeastern Atlantic Ocean from June to October, producing strong and competing aerosol radiative effects. Smoke effects on the transition between overcast stratocumulus and scattered cumulus clouds are investigated along a Lagrangian (air-mass-following) trajectory in regional climate and large eddy simulation models. Results are compared with observations from three recent field campaigns that took place in August 2017: ObseRvations of Aerosols above CLouds and their intEractionS (ORACLES), CLouds and Aerosol Radiative Impacts and Forcing: Year 2017 (CLARIFY), and Layered Atlantic Smoke Interactions with Clouds (LASIC). The case study is set up around the joint ORACLES–CLARIFY flight that took place near Ascension Island on 18 August 2017. Smoke sampled upstream on an ORACLES flight on 15 August 2017 likely entrained into the marine boundary layer later sampled during the joint flight. The case is first simulated with the WRF-CAM5 regional climate model in three distinct setups: (1) FireOn, in which smoke emissions and any resulting smoke–cloud–radiation interactions are included; (2) FireOff, in which no smoke emissions are included; (3) RadOff, in which smoke emissions and their microphysical effects are included but aerosol does not interact directly with radiation. Over the course of the Lagrangian trajectory, differences in free tropospheric thermodynamic properties between FireOn and FireOff are nearly identical to those between FireOn and RadOff, showing that aerosol–radiation interactions are primarily responsible for the free tropospheric effects. These effects are non-intuitive: in addition to the expected heating within the core of the smoke plume, there is also a “banding” effect of cooler temperature (~1–2 K) and greatly enhanced moisture (>2 g kg -1 ) at the plume top. This banding effect is caused by a vertical displacement of the former continental boundary layer in the free troposphere in the FireOn simulation resulting from anomalous diabatic heating due to smoke absorption of sunlight that manifests primarily as a few hundred meters per day reduction in large-scale subsidence over the ocean. A large eddy simulation (LES) is then forced with free tropospheric fields taken from the outputs for the WRF-CAM5 FireOn and FireOff runs. Cases are run by selectively perturbing one variable (e.g., aerosol number concentration, temperature, moisture, vertical velocity) at a time to better understand the contributions from different indirect (microphysical), “large-scale” semi-direct (above-cloud thermodynamic and subsidence changes), and “local” semi-direct (below-cloud smoke absorption) effects. Despite a more than 5-fold increase in cloud droplet number concentration when including smoke aerosol concentrations, minimal differences in cloud fraction evolution are simulated by the LES when comparing the base case with a perturbed aerosol case with identical thermodynamic and dynamic forcings. A factor of 2 decrease in background free tropospheric aerosol concentrations from the FireOff simulation shifts the cloud evolution from a classical entrainment-driven “deepening–warming” transition to trade cumulus to a precipitation-driven “drizzle-depletion” transition to open cells, however. The thermodynamic and dynamic changes caused by the WRF-simulated large-scale adjustments to smoke diabatic heating strongly influence cloud evolution in terms of both the rate of deepening (especially for changes in the inversion temperature jump and in subsidence) and in cloud fraction on the final day of the simulation (especially for the moisture “banding” effect). Such large-scale semi-direct effects would not have been possible to simulate using a small-domain LES model alone.

54 ENVIRONMENTAL SCIENCES↗

Cloud Adjustments From Large-Scale Smoke–Circulation Interactions Strongly Modulate the Southeastern Atlantic Stratocumulus-to-Cumulus Transition

Smoke from southern Africa blankets the southeastern Atlantic Ocean from June to October, producing strong and competing aerosol radiative effects. Smoke effects on the transition between overcast stratocumulus and scattered cumulus clouds are investigated along a Lagrangian (air-mass-following) trajectory in regional climate and large eddy simulation models. Results are compared with observations from three recent field campaigns that took place in August 2017: ObseRvations of Aerosols above CLouds and their intEractionS (ORACLES), CLouds and Aerosol Radiative Impacts and Forcing: Year 2017 (CLARIFY), and Layered Atlantic Smoke Interactions with Clouds (LASIC). The case study is set up around the joint ORACLES–CLARIFY flight that took place near Ascension Island on 18 August 2017. Smoke sampled upstream on an ORACLES flight on 15 August 2017 likely entrained into the marine boundary layer later sampled during the joint flight. The case is first simulated with the WRF-CAM5 regional climate model in three distinct setups: (1) FireOn, in which smoke emissions and any resulting smoke–cloud–radiation interactions are included; (2) FireOff, in which no smoke emissions are included; (3) RadOff, in which smoke emissions and their microphysical effects are included but aerosol does not interact directly with radiation. Over the course of the Lagrangian trajectory, differences in free tropospheric thermodynamic properties between FireOn and FireOff are nearly identical to those between FireOn and RadOff, showing that aerosol–radiation interactions are primarily responsible for the free tropospheric effects. These effects are non-intuitive: in addition to the expected heating within the core of the smoke plume, there is also a “banding” effect of cooler temperature (∼1–2 K) and greatly enhanced moisture (>2 g kg−1) at the plume top. This banding effect is caused by a vertical displacement of the former continental boundary layer in the free troposphere in the FireOn simulation resulting from anomalous diabatic heating due to smoke absorption of sunlight that manifests primarily as a few hundred meters per day reduction in large-scale subsidence over the ocean. A large eddy simulation (LES) is then forced with free tropospheric fields taken from the outputs for the WRF-CAM5 FireOn and FireOff runs. Cases are run by selectively perturbing one variable (e.g., aerosol number concentration, temperature, moisture, vertical velocity) at a time to better understand the contributions from different indirect (microphysical), “large-scale” semi-direct (above-cloud thermodynamic and subsidence changes), and “local” semi-direct (below-cloud smoke absorption) effects. Despite a more than 5-fold increase in cloud droplet number concentration when including smoke aerosol concentrations, minimal differences in cloud fraction evolution are simulated by the LES when comparing the base case with a perturbed aerosol case with identical thermodynamic and dynamic forcings. A factor of 2 decrease in background free tropospheric aerosol concentrations from the FireOff simulation shifts the cloud evolution from a classical entrainment-driven “deepening–warming” transition to trade cumulus to a precipitation-driven “drizzle-depletion” transition to open cells, however. The thermodynamic and dynamic changes caused by the WRF-simulated large-scale adjustments to smoke diabatic heating strongly influence cloud evolution in terms of both the rate of deepening (especially for changes in the inversion temperature jump and in subsidence) and in cloud fraction on the final day of the simulation (especially for the moisture “banding” effect). Such large-scale semi-direct effects would not have been possible to simulate using a small-domain LES model alone.

southeast Atlantic Ocean↗

Ocular Outcomes Comparison Between 14- and 70-day Head-down Tilt Bed Rest

INTRODUCTION: Ophthalmological changes, including optic disc edema with optic nerve sheath distension, posterior globe flattening with hyperopic shift, choroidal folds and cotton wool spots have been detected in some astronauts involved in long-duration spaceflights. (sup 1) It is hypothesized that elevated intracranial pressure resulting from microgravity-induced cephalad fluid shifts may be responsible for most of these findings. Head-down tilt bed rest (HTDBR) is a ground-based microgravity analog which also produces cephalad fluid shifts. It is conceivable that prolonged HDTBR exposure may induce ocular changes similar to those experienced in microgravity. Therefore, the purpose of the present study was to compare structural and functional ocular outcomes between 14- and 70-day HDTBR in healthy human subjects. It is hypothesized that 70-d HDTBR induced ocular changes of greater magnitude as compared to 14-d HDTBR. METHODS: Two HDTBR studies were conducted at the NASA Flight Analogs Research Unit, located at The University of Texas Medical Branch at Galveston, TX. Identical NASA standard screening procedures and BR conditions (e.g., strict sleep-wake cycle, standardized diet, continuous video monitoring) were implemented in both studies. Participants spent 14 and/or 70 consecutive days in a 6deg HDT position and did not engage in exercise. Subjects received weekly ocular examinations before, during, and after HDTBR. Ocular testing included: distance and near best-corrected visual acuity (BCVA), cycloplegic refraction, intraocular pressure (IOP) measurement, color vision, red dot test, modified Amsler grid test, confrontational visual field, color fundus photography and Spectral-domain OCT scans of the macula and the optic disc. Pre/post HDTBR differences between the two studies will be evaluated for BCVA, spherical equivalent, IOP, retinal nerve fiber layer (RNFL) thickness and macular OCT parameters. RESULTS: 16 (12 males and 4 females) and 6 (5 males and 1 female) subjects participated in the 14 and 70-day HDTBR studies, respectively. One subject participated in both studies. The demographic and ophthalmological characteristics of the 14-day HDTBR study have been presented elsewhere.2 In the 70- day study, subjects age averaged 39.5 +/- 7.8 years; pre- and post-HDTBR Goldmann IOP were, on average, 15.4 and 14.6 mmHg in the right eye, and 15.3 and 14.4 mmHg in the left eye, respectively; preand post-HDTBR Spectralis OCT (Heidelberg Engineering, GmbH, Heidelberg, Germany) average RNFL thickness were 103.8 and 106 μm in the right eye, and 103 and 104.3 μm in the left eye, respectively. In both studies, color vision, red dot test, modified Amsler grid test and confrontational visual field were within normal limits at all time points; no changes were detected on stereoscopic color optic disc photography. For the above outcomes, preliminary results of the pre/post HDTBR differences between the two studies will be presented at the 2015 Human Research Program Investigators' Workshop. CONCLUSIONS: Although 14-day HDTBR did not seem to induce clinically relevant ocular changes, (sup 2) a systematic evaluation and comparison with the 70-day HDTBR study results will elucidate whether the magnitude of ocular structural and functional changes is affected by the time spent in the recumbent position. Further research will also address the effects of integrated resistance and aerobic training during HDTBR on the ocular outcomes. REFERENCES: 1. Mader TH et al. Optic disc edema, globe flattening, choroidal folds, and hyperopic shifts observed in astronauts after long-duration space flight. Ophthalmology. 2011;118(10):2058-69. 2. Taibbi G et al. Ocular outcomes evaluation in a 14-day head-down bed rest study. Aviat Space Environ Med. 2014;85(10):983-92.

Cromwell, R.L.↗