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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
NASA NTRS2019

X-ray Evaluation of the Marshall Grazing Incidence X-Ray Spectrometer (MaGIXS) Nickel-Replicated Mirrors

X-ray observations of astronomical objects provides diagnostics not available in any other wavelength regime, however the capability of making these observation at a high spatial resolution has proven challenging. Recently, NASA Marshall Space Flight Center (MSFC) has made good progress in employing computer numerical control (CNC) polishing techniques on electroless nickel mandrels as part of our replicated grazing incidence optics program. CNC polishing has afforded the ability to deterministically refine mandrel figure, thereby improving mirror performance. The Marshall Grazing Incidence X-ray Spectrometer (MaGIXS) is a MSFC-led sounding rocket instrument that is designed to make the first ever soft x-ray spectral observations of the Sun spatially resolved along a narrow slit. MaGIXS incorporates some of the first mirrors produced at MSFC using this polishing technique. Here we present the predicted mirror performance obtained from metrology, after completion of CNC polishing, as well as the results of X-ray tests performed on the MaGIXS telescope mirror before and after mounting.

MaGIXS X-ray Tests↗
DOE OSTI2021

Building and experimenting with an agent-based model to study the population-level impact of CommunityRx, a clinic-based community resource referral intervention

CommunityRx (CRx), an information technology intervention, provides patients with a personalized list of healthful community resources (HealtheRx). In repeated clinical studies, nearly half of those who received clinical “doses” of the HealtheRx shared their information with others (“social doses”). Clinical trial design cannot fully capture the impact of information diffusion, which can act as a force multiplier for the intervention. Furthermore, experimentation is needed to understand how intervention delivery can optimize social spread under varying circumstances. To study information diffusion from CRx under varying conditions, we built an agent-based model (ABM). This study describes the model building process and illustrates how an ABM provides insight about information diffusion through in silico experimentation. To build the ABM, we constructed a synthetic population (“agents”) using publicly-available data sources. Using clinical trial data, we developed empirically-informed processes simulating agent activities, resource knowledge evolution and information sharing. Using RepastHPC and chiSIM software, we replicated the intervention in silico, simulated information diffusion processes, and generated emergent information diffusion networks. The CRx ABM was calibrated using empirical data to replicate the CRx intervention in silico. We used the ABM to quantify information spread via social versus clinical dosing then conducted information diffusion experiments, comparing the social dosing effect of the intervention when delivered by physicians, nurses or clinical clerks. The synthetic population (N = 802,191) exhibited diverse behavioral characteristics, including activity and knowledge evolution patterns. In silico delivery of the intervention was replicated with high fidelity. Large-scale information diffusion networks emerged among agents exchanging resource information. Varying the propensity for information exchange resulted in networks with different topological characteristics. Community resource information spread via social dosing was nearly 4 fold that from clinical dosing alone and did not vary by delivery mode. This study, using CRx as an example, demonstrates the process of building and experimenting with an ABM to study information diffusion from, and the population-level impact of, a clinical information-based intervention. While the focus of the CRx ABM is to recreate the CRx intervention in silico, the general process of model building, and computational experimentation presented is generalizable to other large-scale ABMs of information diffusion.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2010

Design Considerations of Polishing Lap for Computer-Controlled Cylindrical Polishing Process

The future X-ray observatory missions, such as International X-ray Observatory, require grazing incidence replicated optics of extremely large collecting area (3 m2) in combination with angular resolution of less than 5 arcsec half-power diameter. The resolution of a mirror shell depends ultimately on the quality of the cylindrical mandrels from which they are being replicated. Mid-spatial-frequency axial figure error is a dominant contributor in the error budget of the mandrel. This paper presents our efforts to develop a deterministic cylindrical polishing process in order to keep the mid-spatial-frequency axial figure errors to a minimum. Simulation studies have been performed to optimize the operational parameters as well as the polishing lap configuration. Furthermore, depending upon the surface error profile, a model for localized polishing based on dwell time approach is developed. Using the inputs from the mathematical model, a mandrel, having conical approximated Wolter-1 geometry, has been polished on a newly developed computer-controlled cylindrical polishing machine. We report our first experimental results and discuss plans for further improvements in the polishing process.

Khan, Gufran S.↗
NASA NTRSDate not supplied

CDISC Remote Design Method to Simulate Aircraft Interference Effects for the CATNLF Flight Test

The Crossflow Attenuated Natural Laminar Flow (CATNLF) flight test is an experimental evaluation of a laminar flow design approach that will be conducted on a small transonic wing-like model suspended from the Centerline Instrumented Pylon (CLIP) underneath an F-15 vehicle. The upcoming flight test is anticipated to provide experimental data that may be useful for transition prediction code calibrations or laminar flow computational studies. For the computational results to be reliable, relevant aerodynamics must be included in the simulations. It has been shown that the F-15 vehicle produces a notable aerodynamic influence on the CATNLF test article, and that removing the F-15 vehicle from the simulation significantly alters the laminar flow behavior. Because the F-15 vehicle is not a publicly-releasable geometry, if the CATNLF flight test dataset is to be widely used by the community, an alternative method to ensure that the CATNLF test article flight configuration aerodynamics is properly modeled is required. The objective of this research is to use the CDISC aerodynamic design tool to perform a remote design of a surface that would replicate the aerodynamic influence on the CATNLF test article. This new design approach, referred to as the Equivalent Loading via Interference Surface Effects (ELISE), is presented in this paper, including the details on the design setup and results. The ELISE design successfully reproduced the F-15 influence on the CATNLF test article, with predicted transition location within an average of 4% chord of the full flight configuration. An off-design assessment is included for small perturbations in Mach and sideslip angle that suggest the ELISE design can cover a reasonable range of expected flight conditions with the same geometry. This paper is intended to explain the design approach, as well as show results that can be expected when utilizing the ELISE design method.

CDISC↗
NASA NTRSDate not supplied

CDISC Remote Design Method to Simulate Aircraft Interference Effects for the CATNLF Flight Test

The Crossflow Attenuated Natural Laminar Flow (CATNLF)flight test is an experimental evaluation of a laminar flow design approach that will be conducted on a small transonic wing-like model suspended from the Centerline Instrumented Pylon (CLIP) underneath an F-15 vehicle. The upcoming flight testis anticipated to provide experimental data that may be useful for transition prediction code calibrations or laminar flow computational studies. For the computational results to be reliable, relevant aerodynamics must be included in the simulations. It has been shown that the F-15 vehicle produces a notable aerodynamic influence on the CATNLF test article, and that removing the F-15 vehicle from the simulation significantly alters the laminar flow behavior. Because the F-15 vehicle is not a publicly-releasable geometry, if the CATNLF flight test dataset is to be widely used by the community, an alternative method to ensure that the CATNLF test article flight configuration aerodynamics is properly modeled is required. The objective of this research is to use the CDISC aerodynamic design tool to perform a remote design of a surface that would replicate the aerodynamic influence on the CATNLF test article. This new design approach, referred to as the Equivalent Loading via Interference Surface Effects (ELISE), is presented in this paper, including the details on the design setup and results. The ELISE design successfully reproduced theF-15 influence on the CATNLF test article, with predicted transition location within an average of 4% chord of the full flight configuration. An off-design assessment is included for small perturbations in Mach and sideslip angle that suggest the ELISE design can cover a reasonable range of expected flight conditions with the same geometry. This paper is intended to explain the design approach, as well as show results that can be expected when utilizing the ELISE design method.

CDISC↗
DOE OSTI2024

A structural equation modeling approach to leveraging the power of extant sentiment analysis tools

Machine-derived sentiment analysis has become a pervasive and useful tool to address a wide array of issues in natural language processing. Leading technology companies such as Google now provide sentiment analysis tools (SATs) as readily accessible online products. Academic researchers develop and make available SATs to support the research enterprise. One of the major challenges with SATs is the inconsistencies in results among the various SATs. Consequently, the selection of a SAT for a specific purpose may significantly impact the application. This study addresses the foregoing problem by utilizing structural equation modeling to merge the outputs of SATs to develop a combined sentiment metric without the need for a labeled training dataset. This method is applicable to a wide range of text-based problems, is data-driven, and replicable. It was tested using three publicly available datasets and compared against seven different SATs. The results indicate that as a continous measure, the proposed method outperformed other SATs in the movie reviews and SemEval datasets, and achieved a tie for first place with IBM Watson on the Sentiment 140 dataset. Also, compared to the published major alternatives, the arithmetic mean solution, this approach performed better across these three datasets.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1993

A method for simulating a flux-locked DC SQUID

The authors describe a computationally efficient and accurate method for simulating a dc SQUID's V-Phi (voltage-flux) and I-V characteristics which has proven valuable in evaluating and improving various SQUID readout methods. The simulation of the SQUID is based on fitting of previously acquired data from either a real or a modeled device using the Fourier transform of the V-Phi curve. This method does not predict SQUID behavior, but rather is a way of replicating a known behavior efficiently with portability into various simulation programs such as SPICE. The authors discuss the methods used to simulate the SQUID and the flux-locking control electronics, and present specific examples of this approach. Results include an estimate of the slew rate and linearity of a simple flux-locked loop using a characterized dc SQUID.

Gutt, G. M.↗
NASA NTRS2000

Evolutionary Cell Computing: From Protocells to Self-Organized Computing

On the path from inanimate to animate matter, a key step was the self-organization of molecules into protocells - the earliest ancestors of contemporary cells. Studies of the properties of protocells and the mechanisms by which they maintained themselves and reproduced are an important part of astrobiology. These studies also have the potential to greatly impact research in nanotechnology and computer science. Previous studies of protocells have focussed on self-replication. In these systems, Darwinian evolution occurs through a series of small alterations to functional molecules whose identities are stored. Protocells, however, may have been incapable of such storage. We hypothesize that under such conditions, the replication of functions and their interrelationships, rather than the precise identities of the functional molecules, is sufficient for survival and evolution. This process is called non-genomic evolution. Recent breakthroughs in experimental protein chemistry have opened the gates for experimental tests of non-genomic evolution. On the basis of these achievements, we have developed a stochastic model for examining the evolutionary potential of non-genomic systems. In this model, the formation and destruction (hydrolysis) of bonds joining amino acids in proteins occur through catalyzed, albeit possibly inefficient, pathways. Each protein can act as a substrate for polymerization or hydrolysis, or as a catalyst of these chemical reactions. When a protein is hydrolyzed to form two new proteins, or two proteins are joined into a single protein, the catalytic abilities of the product proteins are related to the catalytic abilities of the reactants. We will demonstrate that the catalytic capabilities of such a system can increase. Its evolutionary potential is dependent upon the competition between the formation of bond-forming and bond-cutting catalysts. The degree to which hydrolysis preferentially affects bonds in less efficient, and therefore less well-ordered, peptides is also critical to evolution of a non-genomic system. Based on these results, a new computational object called a "molnet" is defined. Like a neural network, it is formed of interconnected units that send "signals" to each other. Like molecules, neural networks have a specific function once their structure is defined. The difference between a molnet and traditional neural networks, is that input to molnets is not simply passed along and processed from input to output units, but rather it is utilized to form and break connections(bonds), and thus to form new structures. Molnets represent a powerful tool that can be used to understand the conditions under which chemical systems can form large molecules, such as proteins, and display ever more complex functions. This has direct applications, for example to the design of smart,synthetic fabrics. Additional information is contained in the original.

Colombano, Silvano↗
NASA NTRSDate not supplied

Computational Fluid Dynamics Models of the NASA White Sands Test Facility Particle Impact Test Nozzles

The particle impact ignition mechanism is considered to be the most effective means for igniting metals in gaseous oxygen environments and is a concern for every oxygen system. For this reason, the National Aeronautics and Space Administration (NASA) commits a large amount of resources attempting to understand and defend against this phenomenon. The most practical means of accomplishing this is through extensive of testing. To this end, over the years NASA has developed and built a facility and various apparatuses to test material or component vulnerability to a particle impact ignition. In testing materials, NASA uses sub-sonic and supersonic nozzles to replicate the conditions that a material is expected to experience in service. However, challenges include obtaining an understanding of the gas dynamics and of the particle behavior through and up to the point of impact at the material under test. One means of addressing these challenges is the use of computational fluid dynamics (CFD). If a CFD model can be built and validated, the model can then be used to confidently interrogate changes to inlet conditions and particle geometries, as well as changes to nozzle geometries to better simulate a material’s in-situ conditions and greatly reduce or eliminate trial-and-error approaches in testing. This paper will show NASA’s approach to and results of using CFD to better understand their particle impact nozzles.

Computational Fluid Dynamics↗
NASA NTRS1974

The manual control of vehicles undergoing slow transitions in dynamic characteristics

The manual control was studied of a vehicle with slowly time-varying dynamics to develop analytic and computer techniques necessary for the study of time-varying systems. The human operator is considered as he controls a time-varying plant in which the changes are neither abrupt nor so slow that the time variations are unimportant. An experiment in which pilots controlled the longitudinal mode of a simulated time-varying aircraft is described. The vehicle changed from a pure double integrator to a damped second order system, either instantaneously or smoothly over time intervals of 30, 75, or 120 seconds. The regulator task consisted of trying to null the error term resulting from injected random disturbances with bandwidths of 0.8, 1.4, and 2.0 radians per second. Each of the twelve experimental conditons was replicated ten times. It is shown that the pilot's performance in the time-varying task is essentially equivalent to his performance in stationary tasks which correspond to various points in the transition. A rudimentary model for the pilot-vehicle-regulator is presented.

Moriarty, T. E.↗
NASA NTRS1995

Mode Transitions in Glass Cockpit Aircraft: Results of a Field Study

One consequence of increased levels of automation in complex control systems is the presence of modes. A mode is a particular configuration of a control system that defines how human command inputs are interpreted. In complex systems, modes also often determine a specific allocation of control authority between the human and automated systems. Even in simple static devices (e.g., electronic watches, word processors), the presence of modes has been found to cause problems in either-the acquisition or production of skilled performance. Many of these problems arise due to the fact that the selection of a mode causes device behavior to be mediated by hidden internal state information. For these simple systems, many of these interaction problems can be solved by the design of appropriate feedback to communicate internal state information to the human operator. In complex dynamic systems, however, the design issues associated with modes seem to trancend the problem of merely communicating internal state information via displayed feedback. In complex supervisory control systems (e.g., aircraft, spacecraft, military command and control), a key function of modes is the selection of a particular configuration of control authority between the human operator and automated control systems. One mode may result in full manual control, another may result in a mix of manual and automatic control, while a third may result in full automatic control over the entire system. The human operator selects an appropriate mode as a function of current goals, operating conditions, and operating procedures. Thus, the operator is put in a position of essentially trying to control two coupled dynamic systems: the target system itself, and also a highly complex suite of automation controlling the target system. From a historical perspective, it should probably not come as a surprise that very little information is available to guide the design of mode-oriented control systems. The topic of function allocation (i.e., the proper division of control authority among human and computer) has a long history in human-machine systems research. Although this research has produced some relevant guidelines, a design approach capable of defining appropriate allocations of control function between the human and automation is not yet available. As a result, the function allocation decision itself has been allocated to the operator, to be performed in real-time, in the operation of mode-oriented control systems. A variety of documented aircraft accidents and incidents suggest that the real-time selection and monitoring of control modes is a weak link in the effective operation of complex supervisory control systems. Research in human-machine systems and human-computer interaction has barely scraped the surface of the problem of understanding how operators manage this task.The purpose of this paper is to present the results of a field study which examined how operators manage mode selection in a complex supervisory control system. Data on mode engagements using the Boeing B757/767 auto-flight system were collected during approach and descent into four major airports in the East Coast of the United States. Protocols documenting mode selection, automatic mode changes, pilot actions, quantitative records of flight-path variables, and verbal reports during and after mode engagements were collected by an observer from the jumpseat. Observations were conducted on two typical trips between three airports. Each trip was be replicated 11 times, which yielded a total of 22 trips and 66 legs on which data were collected. All data collected concerned the same flight numbers, and therefore, the same time of day, same type of aircraft, and identical operational environments (e.g., ATC facilities, weather patterns, traffic flow etc.)

Degani, Asaf↗
NASA NTRS2004

Monte Carlo Technique Used to Model the Degradation of Internal Spacecraft Surfaces by Atomic Oxygen

Atomic oxygen is one of the predominant constituents of Earth's upper atmosphere. It is created by the photodissociation of molecular oxygen (O2) into single O atoms by ultraviolet radiation. It is chemically very reactive because a single O atom readily combines with another O atom or with other atoms or molecules that can form a stable oxide. The effects of atomic oxygen on the external surfaces of spacecraft in low Earth orbit can have dire consequences for spacecraft life, and this is a well-known and much studied problem. Much less information is known about the effects of atomic oxygen on the internal surfaces of spacecraft. This degradation can occur when openings in components of the spacecraft exterior exist that allow the entry of atomic oxygen into regions that may not have direct atomic oxygen attack but rather scattered attack. Openings can exist because of spacecraft venting, microwave cavities, and apertures for Earth viewing, Sun sensors, or star trackers. The effects of atomic oxygen erosion of polymers interior to an aperture on a spacecraft were simulated at the NASA Glenn Research Center by using Monte Carlo computational techniques. A two-dimensional model was used to provide quantitative indications of the attenuation of atomic oxygen flux as a function of the distance into a parallel-walled cavity. The model allows the atomic oxygen arrival direction, the Maxwell Boltzman temperature, and the ram energy to be varied along with the interaction parameters of the degree of recombination upon impact with polymer or nonreactive surfaces, the initial reaction probability, the reaction probability dependence upon energy and angle of attack, degree of specularity of scattering of reactive and nonreactive surfaces, and the degree of thermal accommodation upon impact with reactive and non-reactive surfaces to be varied to allow the model to produce atomic oxygen erosion geometries that replicate actual experimental results from space. The degree of erosion of various interior locations was compared with the erosion that would occur external to the spacecraft. Results of one cavity model indicate that, at depths into a two-dimensional cavity that are equal to 10 cavity widths, the erosion on the walls of the cavity is less than that on the top surface by over 2 orders of magnitude. Wall erosion near the surface of a cavity depends on which wall is receiving direct atomic oxygen attack. However, deep in the cavity little difference is present. Testing of various cavity models such as these gives spacecraft designers an indication of the level of threat to sensitive interior surfaces for different geometries. Even though the Monte Carlo model is two-dimensional, it can be used to provide qualitative information about spacecraft openings that are three-dimensional by offering reasonable insight as to the nature of the attenuation of damage that occurs within a spacecraft in low Earth orbit. As shown, there is more erosion on the side seeing direct atomic oxygen attack until a depth of approximately 5 times the width of the opening, where the erosion is the same on both sides.

Banks, Bruce A.↗
DOE OSTI2026

Uncertainty quantification of fireball features extracted from nuclear test films using computer vision

Films from the US’s historic nuclear testing era comprise the only extensive collection of imagery depicting high-yield detonations. These films offer unique insights into the characteristics of flows occurring on scales that are difficult to replicate experimentally, and they are a valuable source of data for the validation of models used to describe nuclear detonations. In recent work, we implemented modern computer vision and machine learning techniques to extract features of the fireball following nuclear detonation. With a training dataset of fireball films, we fine-tuned a You Only Look Once 11 (YOLO11) model to detect and track the fireball. Applied to a video, the outer bounding box produced in each frame by YOLO11 is used as an input prompt to Meta’s Segment Anything Model 2 (SAM2), which is shown to accurately predict the boundary of the fireball over time with high resolution. These state-of-the-art computer vision foundation models exhibit impressive visual accuracy in their results but lack an output of values that robustly quantify uncertainty in scientific applications. In this paper, we develop procedures for uncertainty quantification of extracted fireball features. We outline the application of a parallel attention mechanism to calculate uncertainty ranges that complement and better pose model validation data. This higher quality fireball validation data may serve to improve prognostic models describing nuclear detonations in support of nuclear forensic and emergency response activities.

Khristy, Joel [ORNL] (ORCID:0000000209963060)↗
DOE OSTI2024

TNet: A Model-Constrained Tikhonov Network Approach for Inverse Problems

Deep learning (DL), in particular deep neural networks, by default is purely data-driven and in general does not require physics. This is the strength of DL but also one of its key limitations when applied to science and engineering problems in which underlying physical properties—such as stability, conservation, and positivity—and accuracy are required. DL methods in their original forms are often not capable of respecting the underlying mathematical models or achieving desired accuracy even in big-data regimes. On the other hand, many data-driven science and engineering problems, such as inverse problems, typically have limited experimental or observational data, and DL would overfit the data in this case. Leveraging information encoded in the underlying mathematical models, we argue, not only compensates for missing information in low data regimes but also provides opportunities to equip DL methods with the underlying physics, hence promoting better generalization. This paper develops a model-constrained DL approach and its variant TNet—a Tikhonov neural network—which are capable of learning not only information hidden in the training data but also in the underlying mathematical models to solve inverse problems governed by partial differential equations in low data regimes. We provide the constructions and some theoretical results for the proposed approaches for both linear and nonlinear inverse problems. Since TNet is designed to learn inverse solutions with Tikhonov regularization, it is interpretable: in fact it recovers Tikhonov solutions for linear cases while potentially approximating Tikhonov solutions for nonlinear inverse problems. We also prove that data randomization can enhance not only the smoothness of the networks but also their generalizations. Comprehensive numerical results confirm the theoretical findings and show that with even as little as 1 training data sample for one-dimensional (1D) deconvolution, 5 for an inverse 2D heat conductivity problem, 100 for inverse initial conditions for a time-dependent 2D Burgers’s equation, and 50 for inverse initial conditions for 2D Navier–Stokes equations, TNet solutions can be as accurate as Tikhonov solutions while being several orders of magnitude faster. Furthermore, this is possible owing to the model-constrained term, replications, and randomization.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2001

Micromachined TWTs for THz Radiation Sources

The Terahertz (THz) region of the electromagnetic spectrum (about 300 - 3000 GHz in frequency or about 0.1 - 1 mm free space wavelength) has enormous potential for high-data-rate communications, spectroscopy, astronomy, space research, medicine, biology, surveillance, remote sensing, industrial process control, etc. It has been characterized as the most scientifically rich, yet under-utilized, region of the electromagnetic spectrum. The most critical roadblock to full exploitation of the THz band is lack of coherent radiation sources that are powerful (0.001 - 1.0 W continuous wave), efficient (> 1%), frequency agile (instantaneously tunable over 1% bandwidths or more), reliable, and comparatively inexpensive. To develop vacuum electron device (VED) radiation sources satisfying these requirements, fabrication and packaging approaches must be heavily considered to minimize costs, in addition to the basic interaction physics and circuit design. To minimize size of the prime power supply, beam voltage must be minimized, preferably 10 kV. Solid state sources satisfy the low voltage requirement, but are many orders of magnitude below power, efficiency, and bandwidth requirements. On the other hand, typical fast-wave VED sources in this regime (e.g., gyrotrons, FELs) tend to be large, expensive, high voltage and very high power devices unsuitable for most of the applications cited above. VEDs based on grating or inter-digital (ID) circuits have been researched and developed. However, achieving forward-wave amplifier operation with instantaneous fractional bandwidths > 1% is problematic for these devices with low-energy (< 15 kV) electron beams. Moreover, the interaction impedance is quite low unless the beam-circuit spacing is kept particularly narrow, often leading to significant beam interception. One solution to satisfy the THz source requirements mentioned above is to develop micromachined VEDs, or "micro-VEDs". Among other benefits, micro-machining technologies provide superior high frequency wall conductivity as a result of superior surface smoothness compared with conventional mechanical or electric discharge machining approaches. Micro-VED technologies are already being applied to the development of millimeter-wave klystrons at Stanford Linear Accelerator Center and submillimeter-wave klystrons at the University of Leeds. We are investigating the use of micro-machining technologies to develop THz regime TWTs, with emphasis on folded-waveguide TWTs. The folded-waveguide TWT (FW-TWT) has several features that make it attractive for THz-regime micro-VED applications. It is a relatively simple circuit to design and fabricate, it is amenable to precision pattern replication by micro-machining, and it is has been demonstrated capable of forward-wave amplification with appreciable bandwidth. We are conducting experimental and computational studies of micro-VED FW-TWTs to examine their feasibility for applications at frequencies from 200 - 1000 GHz.

Booske, John H.↗
DOE OSTI2022

Parked aeroelastic field rotor response for a 20% scaled demonstrator of a 13‐MW downwind turbine

Abstract Aeroelastic parked testing of a unique downwind two‐bladed subscale rotor was completed to characterize the response of an extreme‐scale 13‐MW turbine in high‐wind parked conditions. A 20% geometric scaling was used resulting in scaled 20‐m‐long blades, whose structural and stiffness properties were designed using aeroelastic scaling to replicate the nondimensional structural aeroelastic deflections and dynamics that would occur for a lightweight, downwind 13‐MW rotor. The subscale rotor was mounted and field tested on the two‐bladed Controls Advanced Research Turbine (CART2) at the National Renewable Energy Laboratory's Flatiron Campus (NREL FC). The parked testing of these highly flexible blades included both pitch‐to‐run and pitch‐to‐feather configurations with the blades in the horizontal braked orientation. The collected experimental data includes the unsteady flapwise root bending moments and tip deflections as a function of inflow wind conditions. The bending moments are based on strain gauges located in the root section, whereas the tip deflections are captured by a video camera on the hub of the turbine pointed toward the tip of the blade. The experimental results are compared against computational predictions generated by FAST, a wind turbine simulation software, for the subscale and full‐scale models with consistent unsteady wind fields. FAST reasonably predicted the bending moments and deflections of the experimental data in terms of both the mean and standard deviations. These results demonstrate the efficacy of the first such aeroelastically scaled turbine test and demonstrate that a highly flexible lightweight downwind coned rotor can be designed to withstand extreme loads in parked conditions.

17 WIND ENERGY↗
DOE OSTI2020

Insights into the dynamics between viruses and their hosts in a hot spring microbial mat

Abstract Our current knowledge of host–virus interactions in biofilms is limited to computational predictions based on laboratory experiments with a small number of cultured bacteria. However, natural biofilms are diverse and chiefly composed of uncultured bacteria and archaea with no viral infection patterns and lifestyle predictions described to date. Herein, we predict the first DNA sequence-based host–virus interactions in a natural biofilm. Using single-cell genomics and metagenomics applied to a hot spring mat of the Cone Pool in Mono County, California, we provide insights into virus–host range, lifestyle and distribution across different mat layers. Thirty-four out of 130 single cells contained at least one viral contig (26%), which, together with the metagenome-assembled genomes, resulted in detection of 59 viruses linked to 34 host species. Analysis of single-cell amplification kinetics revealed a lack of active viral replication on the single-cell level. These findings were further supported by mapping metagenomic reads from different mat layers to the obtained host–virus pairs, which indicated a low copy number of viral genomes compared to their hosts. Lastly, the metagenomic data revealed high layer specificity of viruses, suggesting limited diffusion to other mat layers. Taken together, these observations indicate that in low mobility environments with high microbial abundance, lysogeny is the predominant viral lifestyle, in line with the previously proposed “Piggyback-the-Winner” theory.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2002

Flow field measurements in the cell culture unit

The cell culture unit (CCU) is being designed to support cell growth for long-duration life science experiments on the International Space Station (ISS). The CCU is a perfused loop system that provides a fluid environment for controlled cell growth experiments within cell specimen chambers (CSCs), and is intended to accommodate diverse cell specimen types. Many of the functional requirements depend on the fluid flow field within the CSC (e.g., feeding and gas management). A design goal of the CCU is to match, within experimental limits, all environmental conditions, other than the effects of gravity on the cells, whether the hardware is in microgravity ( micro g), normal Earth gravity, or up to 2g on the ISS centrifuge. In order to achieve this goal, two steps are being taken. The first step is to characterize the environmental conditions of current 1g cell biology experiments being performed in laboratories using ground-based hardware. The second step is to ensure that the design of the CCU allows the fluid flow conditions found in 1g to be replicated from microgravity up to 2g. The techniques that are being used to take these steps include flow visualization, particle image velocimetry (PIV), and computational fluid dynamics (CFD). Flow visualization using the injection of dye has been used to gain a global perspective of the characteristics of the CSC flow field. To characterize laboratory cell culture conditions, PIV is being used to determine the flow field parameters of cell suspension cultures grown in Erlenmeyer flasks on orbital shakers. These measured parameters will be compared to PIV measurements in the CSCs to ensure that the flow field that cells encounter in CSCs is within the bounds determined for typical laboratory experiments. Using CFD, a detailed simulation is being developed to predict the flow field within the CSC for a wide variety of flow conditions, including microgravity environments. Results from all these measurements and analyses of the CSC flow environment are presented and discussed. The final configuration of the CSC employs magnetic stir bars with angled paddles to achieve the necessary flow requirements within the CSC.

Cell Culture↗