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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 883 records · Page 49

Precision engineering of biological function with large-scale measurements and machine learning

As synthetic biology expands and accelerates into real-world applications, methods for quantitatively and precisely engineering biological function become increasingly relevant. This is particularly true for applications that require programmed sensing to dynamically regulate gene expression in response to stimuli. However, few methods have been described that can engineer biological sensing with any level of quantitative precision. Here, we present two complementary methods for precision engineering of genetic sensors: in silico selection and machine-learning-enabled forward engineering. Both methods use a large-scale genotype-phenotype dataset to identify DNA sequences that encode sensors with quantitatively specified dose response. First, we show that in silico selection can be used to engineer sensors with a wide range of dose-response curves. To demonstrate in silico selection for precise, multi-objective engineering, we simultaneously tune a genetic sensor’s sensitivity (EC 50 ) and saturating output to meet quantitative specifications. In addition, we engineer sensors with inverted dose-response and specified EC 50 . Second, we demonstrate a machine-learning-enabled approach to predictively engineer genetic sensors with mutation combinations that are not present in the large-scale dataset. We show that the interpretable machine learning results can be combined with a biophysical model to engineer sensors with improved inverted dose-response curves.

59 BASIC BIOLOGICAL SCIENCES↗

Longitudinal-Phase-Space Manipulation for Efficient Beam-Driven Structure Wakefield Acceleration

Collinear beam-driven structure wakefield acceleration (SWFA) is an advanced acceleration technique that could support the compact generation of high-energy beams for future multi-user x-ray free-electron-laser facilities*. Producing an ideal shaped drive beam through phase space manipulation is crucial for an efficient SWFA. Controlling the final longitudinal-phase space of the drive beam necessitate staged beam manipulations during acceleration. This paper describes the preliminary design of an accelerator beamline capable of producing drive beam with tailored current distribution and longitudinal-phase-space correlation. The proposed design is based on simple analytical models combined in a 1-D longitudinal beam-dynamics simulation tracking program supporting forward and backward (time reversal) tracking.

43 PARTICLE ACCELERATORS↗

Hydropower Biological Evaluation Toolset (HBET) Version 3.0: User Guide

The Hydropower Biological Evaluation Tools (HBET) software package, developed by Pacific Northwest National Laboratory (PNNL), is designed to assemble, organize, and process data collected by Sensor Fish and live fish. HBET enable users to characterize the hydraulic conditions of hydropower structures and estimate fish injury and mortality rates from various stressors. Future updates of the software may support other technologies, such as bead tracking in physical models and computational fluid dynamics. The HBET program can be customized to analyze different hydraulic applications, including turbines, spillways, weirs, pumped storage, and other user-defined functions, and therefore, help researchers, turbine designers, hydropower operators, and regulators better evaluate hydropower structures regarding their environmental sustainability and cost-effectiveness. Added content to the user guide about the new feature for predicting absolute injury rates.

13 HYDRO ENERGY↗

Summary

Summary of papers presented at NASA-university program conference on dynamic and other models, control devices, operator performance, and information theory related to manual control

OPERATOR PERFORMANCE↗

A study of the flexible body dynamics of the RAE-A satellite

Spacecraft flight data was compared with simulated data computed by the RAE and IMP dynamics simulator computer programs. There was not sufficient data available to provide definitive data on antenna boom position to the Radio Astronomy experimenter. There was, however, enough data to indicate the trend of antenna boom stiffness and temperature gradient. It was possible to obtain a good fit of simulated data to measured spacecraft attitude data when the antenna booms were extended to 450 feet. The value of the RAE-A antenna boom stiffness appears to be significantly less than the preflight ground measured value. It was confirmed that an improved simulation can be obtained by using values of the root angles of the antenna booms and by using an angle of the damper plane of motion, relative to the plane of the antennas, which differed from preflight ground measurements.

Source record↗

Dynamics and morphology of Beaufort Sea ice determined from satellites, aircraft, and drifting stations

A series of measurements from drifting stations, aircraft, the ERTS-1, Nimbus 4, and Nimbus 5 satellites have jointly provided a new description of the dynamics and morphology of the ice cover of the Beaufort Sea. The combined analysis of these data show that the eastern Beaufort Sea ice cover is made up of large multiyear floes while the western part is made of small, predominantly first-year floes. The analysis suggests that this distribution might be quasi-steady and that the dynamics and thermodynamics of the region are more complex than hitherto known. The measurements consist of: (1) high resolution ERTS-1 imagery which is used to describe floe size and shape distribution, short term floe dynamics, and lead and polynya dynamics; (2) tracking by Nimbus 4 of IRLS drifting buoys to provide ice drift information which enhances the interpretation of the ERTS-1 imagery; (3) Nimbus 5 microwave (1.55 cm wavelength) imagery which provides synoptic, sequential maps on the distribution of multiyear and first-year ice types; (4) airborne microwave surveys and surface based observations made during 1971 and 1972 in conjunction with the AIDJEX (Arctic Ice Dynamics Joint Experiment) program.

Campbell, W. J.↗

RMS massless arm dynamics capability in the SVDS

The equations of motion for the remote manipulator system, assuming that the masses and inertias of the arm can be neglected, are developed for implementation into the space vehicle dynamics simulation (SVDS) program for the Orbiter payload system. The arm flexibility is incorporated into the equations by the computation of flexibility terms for use in the joint servo model. The approach developed in this report is based on using the Jacobian transformation matrix to transform force and velocity terms between the configuration space and the task space to simplify the form of the equations.

Flanders, H. A.↗

Lunar perturbations in columnar electron content and their interpretation in terms of dynamo electrostatic fields

Both the sun and the moon exert influences on the ionosphere, causing fluctuations in its electron content. The small lunar effects, though not negligible, are difficult to analyze because their periodicities differ little from the periodicity of the dominant solar effects. A finite duration impulse response filter was perfected, permitting the efficient splitting of our columnar electron content data into a solar, a lunar, and a residual component. The solar component plus the lunar component and the solar component alone were processed by a dynamic ionospheric simulation program that yields values of vertical plasma drifts when electron content data are used as input. The difference between the two plasma drifts so obtained was taken as being the plasma drift caused by the electric field generated by the lunar tides in the dynamo region. This technique appears to be the first to allow a direct estimation of the lunar-induced electric fields in the ionosphere.

Bernhardt, P. A.↗

Pneumatic servomechanisms

Dynamic analysis computer program analyzes pneumatic servomechanism and the system it controls. System and device to be modeled can contain up to twenty ullage chambers, twenty moving parts, and forty flow lines. Program is easily modified to model larger systems.

Bailey, T. E.↗

Dynamic cross correlation studies of wave particle interactions in ULF phenomena

Magnetic field observations made by satellites in the earth's magnetic field reveal a wide variety of ULF waves. These waves interact with the ambient particle populations in complex ways, causing modulation of the observed particle fluxes. This modulation is found to be a function of species, pitch angle, energy and time. The characteristics of this modulation provide information concerning the wave mode and interaction process. One important characteristic of wave-particle interactions is the phase of the particle flux modulation relative to the magnetic field variations. To display this phase as a function of time a dynamic cross spectrum program has been developed. The program produces contour maps in the frequency time plane of the cross correlation coefficient between any particle flux time series and the magnetic field vector. This program has been utilized in several studies of ULF wave-particle interactions at synchronous orbit.

Mcpherron, R. L.↗

Decision making and problem solving with computer assistance

In modern guidance and control systems, the human as manager, supervisor, decision maker, problem solver and trouble shooter, often has to cope with a marginal mental workload. To improve this situation, computers should be used to reduce the operator from mental stress. This should not solely be done by increased automation, but by a reasonable sharing of tasks in a human-computer team, where the computer supports the human intelligence. Recent developments in this area are summarized. It is shown that interactive support of operator by intelligent computer is feasible during information evaluation, decision making and problem solving. The applied artificial intelligence algorithms comprehend pattern recognition and classification, adaptation and machine learning as well as dynamic and heuristic programming. Elementary examples are presented to explain basic principles.

Kraiss, F.↗