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At least 217 records · Page 12

Ares I-X Flight Evaluation Tasks in Support of Ares I Development

NASA s Constellation Program successfully launched the Ares I-X Flight Test Vehicle on October 28, 2009. The Ares I-X flight was a development flight test that offered a unique opportunity for early engineering data to impact the design and development of the Ares I crew launch vehicle. As the primary customer for flight data from the Ares I-X mission, the Ares Projects Office established a set of 33 flight evaluation tasks to correlate fight results with prospective design assumptions and models. Included within these tasks were direct comparisons of flight data with pre-flight predictions and post-flight assessments utilizing models and modeling techniques being applied to design and develop Ares I. A discussion of the similarities and differences in those comparisons and the need for discipline-level model updates based upon those comparisons form the substance of this paper. The benefits of development flight testing were made evident by implementing these tasks that used Ares I-X data to partially validate tools and methodologies in technical disciplines that will ultimately influence the design and development of Ares I and future launch vehicles. The areas in which partial validation from the flight test was most significant included flight control system algorithms to predict liftoff clearance, ascent, and stage separation; structural models from rollout to separation; thermal models that have been updated based on these data; pyroshock attenuation; and the ability to predict complex flow fields during time-varying conditions including plume interactions.

Huebner, Lawrence D.

A cheaper, faster, better way to detect water of hydration on Solar System bodies

The 3.0-micrometers water of hydration absorption feature observed in the IR photometry of many low-albedo and some medium-albedo asteroids strongly correlates with the 0.7-micrometers Fe(+2) to Fe(+3) oxidized iron absorption feature observed in narrowband spectrophotometry of these asteroids. Using this relationship, an empirical algorithm for predicting the presence of water of hydration in the surface material of a Solar System body using photometry obtained through the Eight-Color Asteroid Survey nu (0.550 micrometers), w (0.701 micrometers), and x (0.853 micrometers) filters was developed and applied to the ECAS photometry of asteroids and outer planet satellites. The percentage of objects in low-albedo, outer main-belt asteroid classes that test positively for water of hydration increases from P to B to C to G class and correlates linearly with the increasing mean albedos of those objects testing positively. The medium-albedo M-class asteroids do not test positively in large number using this algorithm. Aqueously altered asteroids dominate the Solar System population between heliocentric distances of 2.6 to 3.5 AU, bracketing the Solar System region where the aqueous alteration mechanism operated most strongly. One jovian satellite, J VI Himalia, and one saturnian satellite. Phoebe, tested positively for water of hydration, supporting the hypothesis that these may be captured C-class asteroids from a postaccretional dispersion. The proposed testing technique could be applied to an Earth-based survey of asteroids or a space-probe study of an asteroid's surface characteristic in order to identify a potential water source.

Vilas, Faith

Models and Algorithms for Equilibrium Analysis of Mixed-Material Nucleic Acid Systems

Dynamic programming algorithms within the NUPACK software suite enable analysis of equilibrium base-pairing properties for complex and test tube ensembles containing arbitrary numbers of interacting nucleic acid strands. Currently, calculations are limited to single-material systems that are either all-RNA or all-DNA. Here, to enable analysis of mixed-material systems that are critical for modern applications in vitro, in situ, and in vivo, we develop physical models and dynamic programming algorithms that allow the material of the system to be specified at nucleotide resolution. Free energy parameter sets are constructed for both RNA/DNA and RNA/2'OMe-RNA mixed-material systems by combining available empirical mixed-material parameters with single-material parameter sets to enable treatment of the full complex and test tube ensembles. New dynamic programming recursions account for the material of each nucleotide throughout the recursive process. For a complex with N nucleotides, the mixed-material dynamic programming algorithms maintain the O(N 3 ) time complexity of the single-material algorithms, enabling efficient calculation of diverse physical quantities over complex and test tube ensembles (e.g., complex partition function, equilibrium complex concentrations, equilibrium base-pairing probabilities, minimum free energy secondary structure(s), and Boltzmann-sampled secondary structures) at a cost increase of roughly 2.0-3.5×. The results of existing single-material algorithms are exactly reproduced when applying the new mixed-material algorithms to single-material systems. Accuracy is significantly enhanced using mixed-material models and algorithms to predict RNA/DNA and RNA/2'OMe-RNA duplex melting temperatures from the experimental literature as well as RNA/DNA melt profiles from new experiments. In conclusion, mixed-material analyses can be performed online using the NUPACK web app (www.nupack.org) or locally using the NUPACK Python module.

2′OMe-RNA

Initial Integration of a Conflict Probabilities Service for Upper Class E Traffic Management

This paper outlines the development and integration of a conflict probability calculation-based service designed for Upper Class E Airspace operations. A key aspect of this effort is the integration of the conflict probability calculation algorithm into a simulated situational awareness client application. This application serves as a tool for flight operators to submit operations for Upper Class E Airspace within a simulated environment. The focus is on validating the effectiveness of the service through simulated intentional conflicting scenarios. The paper delves into the practicalities of integrating the conflict probability service into the user interface of the simulated situational awareness client application. This integration aims to enhance the decision-making capabilities of ETM operators within the simulated environment. The experiments and observations conducted in this simulated facility provide insights into the operational effectiveness of the proposed approach. In conclusion, this paper emphasizes the development, integration, and simulation-based validation of a conflict probability calculation service for Upper Class E Airspace. The findings underscore the potential impact of our approach on decision-making within a simulated setting, contributing to the understanding of its practical applications in operational scenarios.

Upper Class E Traffic Management

Trajectory Shaper: A Solution for Disrupted Cooperative Adaptive Cruise Control

Cooperative adaptive cruise control (CACC) can effectively reduce energy consumption, alleviate traffic congestion, and enhance safety. However, communication-related constraints and uncooperative vehicle users can disrupt CACC during real-world operations, significantly undermining the putative benefits of CACC. To alleviate the negative impacts of disrupted CACC, this study develops the trajectory shaper (TS) methods as backup solutions for two scenarios: (i) communication between vehicles is infeasible, and vehicles execute adaptive cruise control (ACC) using local sensor measurements; (ii) follower vehicles reject forming a cooperative platoon and execute their local distributed controllers using the information attained via communication. When communication is infeasible, a distributed TS is devised on each vehicle to modify the sensor measurements, enabling safe and efficient ACC operations. When communication is available but uncooperative agents are involved, the lead vehicle of the platoon executes a centralized TS to modify the information shared with uncooperative agents, achieving optimal platoon-level performance. The centralized and distributed TSs are implemented based on the model predictive control algorithms to yield optimal modifications on input information. Robustness is also factored to tackle model uncertainties during TS operations to ensure safety and efficiency. Numerical experiments validate the control performance of the proposed TSs.

Zhou, Anye [ORNL] (ORCID:0000000301455579)

Discovering type I cis-AT polyketides through computational mass spectrometry and genome mining with Seq2PKS

Type 1 polyketides are a major class of natural products used as antiviral, antibiotic, antifungal, antiparasitic, immunosuppressive, and antitumor drugs. Analysis of public microbial genomes leads to the discovery of over sixty thousand type 1 polyketide gene clusters. However, the molecular products of only about a hundred of these clusters are characterized, leaving most metabolites unknown. Characterizing polyketides relies on bioactivity-guided purification, which is expensive and time-consuming. To address this, we present Seq2PKS, a machine learning algorithm that predicts chemical structures derived from Type 1 polyketide synthases. Seq2PKS predicts numerous putative structures for each gene cluster to enhance accuracy. The correct structure is identified using a variable mass spectral database search. Benchmarks show that Seq2PKS outperforms existing methods. Applying Seq2PKS to Actinobacteria datasets, we discover biosynthetic gene clusters for monazomycin, oasomycin A, and 2-aminobenzamide-actiphenol.

60 APPLIED LIFE SCIENCES

Deep learning based x-ray spectrometer for high repetition rate characterization of betatron radiation

Betatron radiation produced from a laser-wakefield accelerator is a broadband, hard x-ray (>1 keV) source that has been used in a variety of applications in medicine, engineering, and fundamental science. Further development and optimization of stable, high repetition rate (HRR) (>1 Hz) betatron sources will provide a means to extend their application base to include single-shot dynamical measurements of ultrafast processes or dense materials. Recent advances in laser technology used in such experiments have enabled increases in shot-rate and system stability, providing improved statistical analysis and detailed parameter scans. However, unique challenges exist at high repetition rate, where data throughput and source optimization are now limited by diagnostic acquisition rates and analysis. Here, we present the development of a machine-learning algorithm for the real-time analysis of betatron radiation. We report on the fielding of this deep learning algorithm for online source characterization at the Institut National de la Recherche Scientifique's Advanced Laser Light Source. By fine-tuning an algorithm originally trained on a fully synthetic dataset using a subset of experimental data, the algorithm can predict the betatron critical energy with a percent error of 7.2 % with a reconstruction time of 1.5 ms, providing a valuable tool for real-time, multi-objective optimization at HRR.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY

Predictive Control to Further Reduce DC-Link Capacitor Current Stress for Segmented Inverter

Two three-phase interleaved inverters have been used in traction drive applications to reduce the current stress in a DC link capacitor bank. In such applications, either carrier-based or space vector modulation is used to select the optimum switching sequences, and the results show 50% less capacitor current than that of a single three-phase inverter. The switching state selection process for this inverter is tedious, and there has been no research to find the optimal switching state. To overcome this challenge, this research employed a simple finite set model predictive control to select the optimum switching sequence for a dual three-phase interleaved topology, called a segmented inverter. The results show that the predictive control algorithm can provide a simple solution and can reduce the current stress by 27% compared with traditional modulation techniques for the segmented inverters.

Ribeiro, Pedro

Duct liner optimization for turbomachinery noise sources

An acoustical field theory for axisymmetric, multisectioned lined ducts with uniform flow profiles was combined with a numerical minimization algorithm to predict optimal liner configurations having one, two, and three sections. Source models studied include a point source located on the axis of the duct and rotor/outlet-stator viscous wake interaction effects for a typical research compressor operating at an axial flow Mach number of about 0.4. For this latter source, optimal liners for equipartition-of energy, zero-phase, and least-attenuated-mode source variations were also calculated and compared with exact results. It is found that the potential benefits of liner segmentation for the attenuation of turbomachinery noise is greater than would be predicted from point source results. Furthermore, effective liner design requires precise knowledge of the circumferential and radial modal distributions.

Lester, H. C.

Structural assembly in space

A cost algorithm for predicting assembly costs for large space structures is given. Assembly scenarios are summarized which describe the erection, deployment, and fabrication tasks for five large space structures. The major activities that impact total costs for structure assembly from launch through deployment and assembly to scientific instrument installation and checkout are described. Individual cost elements such as assembly fixtures, handrails, or remote minipulators are also presented.

Stokes, J. W.

An attitude reorientation algorithm for the Galileo spacecraft

This paper presents an onboard closed loop attitude reorientation algorithm for a dual-spin spacecraft, Galileo. The basic concept for the design uses the despun stator as a reference and fires a sequence of fixed duration thruster pulses to precess the angular momentum vector to its commanded orientation. The error signals used to despin the stator and to perform the turn are derived from the stator error quaternion which is computed using gyro outputs. Constraints considered in the design include gyro rate saturation, plume impingement effects, system parameter variations, as well as software reliability and flexibility. The performance of the algorithm was predicted by analysis and confirmed by computer simulation results. It was concluded that a reorientation accuracy of better than 1 milliradian with a nutation angle of less than 1 degree during the turn can be achieved.

Lin, H.-S.

Direct solar-pumped iodine laser amplifier

In order to evaluate the feasibility of the solar pumped dye laser, the parametric study of a dye laser amplifier pumped by a solar simulator and flashlamp was carried out, and the amplifier gains were measured at various pump beam irradiances on the dye cell. Rhodamine 6G was considered as a candidate for the solar pumped laser because of its good utilization of the solar spectrum and high quantum efficiency. The measurement shows that a solar concentration of 20,000 is required to reach the threshold of the dye. The work to construct a kinetic model algorithm which predicts the output parameter of laser was progressed. The kinetic model was improved such that there is good agreement between the theoretical model and experimental data for the systems defined previously as flashlamp pumped laser oscillator, and the long path length solar pumped laser.

Han, Kwang S.

Analysis and improvement of the vector quantization in SELP (Stochastically Excited Linear Prediction)

The Stochastically Excited Linear Prediction (SELP) algorithm is described as a speech coding method employing a two-stage vector quantization. The first stage uses an adaptive codebook which efficiently encodes the periodicity of voiced speech, and the second stage uses a stochastic codebook to encode the remainder of the excitation signal. The adaptive codebook performs well when the pitch period of the speech signal is larger than the frame size. An extension is introduced, which increases its performance for the case that the frame size is longer than the pitch period. The performance of the stochastic stage, which improves with frame length, is shown to be best in those sections of the speech signal where a high level of short-term correlations is present. It can be concluded that the SELP algorithm performs best during voiced speech where the pitch period is longer than the frame length.

Kleijn, W. B.

A new method for analysis of limit cycle behavior of the NASA/JPL 70-meter antenna axis servos

A piecewise linear method of analyzing the effects of discontinuous nonlinearities on control system performance is described. The limit cycle oscillatory behavior of the system resulting from the nonlinearities is described in terms of a sequence of linear system transient responses. The equations are derived which relate the initial and the terminal conditions of successive transients and the boundary conditions imposed by the non-linearities. The method leads to a convenient computation algorithm for prediction of limit cycle characteristics resulting from discontinuous nonlinearities such as friction, deadzones, and hysteresis.

Hill, R. E.