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The functional, performance, design, and test requirements for the Orbiter power extension package and its associated ground support equipment are defined. Both government and nongovernment standards and specifications are cited for the following subsystems: electrical power, structural/mechanical, avionics, and thermal control. Quality control assurance provisions and preparation for delivery are also discussed.
Designing a high-quality control is crucial for reliable quantum computation. Among the existing approaches, closed-loop leaning control is an effective choice. Its efficiency depends on the learning algorithm employed, thus deserving algorithmic comparisons for its practical applications. Here we assess three representative learning algorithms, including GRadient Ascent Pulse Engineering (GRAPE), improved Nelder-Mead (NMplus), and Differential Evolution (DE), by searching for high-quality control pulses to prepare the Bell state. We first implement each algorithm experimentally in a nuclear magnetic resonance system and then conduct a numerical study considering the impact of some possible significant experimental uncertainties. The experiments report the successful preparation of the high-fidelity target state by the three algorithms, while NMplus converges fastest, and these results coincide with the numerical simulations when potential uncertainties are negligible. However, under certain significant uncertainties, these algorithms possess distinct performance with respect to their resulting precision and efficiency, and DE shows the best robustness. Finally, this study provides insight to aid in the practical application of different closed-loop learning algorithms in realistic physical scenarios.
The current autotuning approaches for quantum dot (QD) devices, while showing some success, lack an assessment of data reliability. This leads to unexpected failures when noisy or otherwise low-quality data is processed by an autonomous system. In this work, we propose a framework for robust autotuning of QD devices that combines a machine learning (ML) state classifier with a data quality control module. The data quality control module acts as a “gatekeeper” system, ensuring that only reliable data are processed by the state classifier. Lower data quality results in either device recalibration or termination. To train both ML systems, we enhance the QD simulation by incorporating synthetic noise typical of QD experiments. We confirm that the inclusion of synthetic noise in the training of the state classifier significantly improves the performance, resulting in an accuracy of 95.0(9)% when tested on experimental data. We then validate the functionality of the data quality control module by showing that the state classifier performance deteriorates with decreasing data quality, as expected. Our results establish a robust and flexible ML framework for autonomous tuning of noisy QD devices.
Handling qualities of the unaugmented advanced supersonic transport (AST) are deficient in the low-speed, landing approach regime. Consequently, improvement in handling with active control augmentation systems has been achieved using implicit model-following techniques. Extensive fixed-based simulator evaluations were used to validate these systems prior to tests with full motion and visual capabilities on a six-axis motion-base simulator (MBS). These tests compared the handling qualities of the unaugmented AST with several augmented configurations to ascertain the effectiveness of these systems. Cooper-Harper ratings, tracking errors, and control activity data from the MBS tests have been analyzed statistically. The results show the fully augmented AST handling qualities have been improved to an acceptable level.
Radar data quality control is a major component to the Tropical Rainfall Measuring Mission (TRMM) Ground Validation (GV) effort. The quality control algorithm utilizes several adjustable height and reflectivity threshold parameters to remove non-precipitation echoes from ground-based radar data. Spurious radar reflectivity returns not removed during the quality control process may create biases in ground validation rainfall products used to evaluate rainfall measurements retrieved from aboard the TRMM satellite. To better evaluate the performance of the quality control algorithm, WSR-88D radar data from one primary GV site, Melbourne, Florida, are used to determine the seasonal characteristics of non-meteorological radar echoes in cast central Florida during the first year of the TRMM mission. It is demonstrated that unique spurious echo regimes develop throughout the year, leading to different levels of successful non-meteorological echo removal by the quality control algorithm. In addition to the type of non- precipitation echoes present, the success of the algorithm is also greatly dependent upon the amount of precipitation present. Less aggressive attempts to remove non-meteorological echoes must be employed when rain is observed so as not to remove these echoes as well. Therefore, precipitation statistics from ground validation monthly rainfall products will be utilized to further document the quality control algorithm performance. Moreover, these precipitation statistics will be used to demonstrate the relationship between dominant spurious echo regimes and rainfall amount. Finally, monthly statistics of contaminated ground validation radar data will be calculated and the effect on rainfall accumulation products will be discussed.
The pulse-flow microencapsulation system (PFMS) is an automated system that continuously produces a stream of liquid-filled microcapsules for delivery of therapeutic agents to target tissues. Prior microencapsulation systems have relied on batch processes that involve transfer of batches between different apparatuses for different stages of production followed by sampling for acquisition of quality-control data, including measurements of size. In contrast, the PFMS is a single, microprocessor-controlled system that performs all processing steps, including acquisition of quality-control data. The quality-control data can be used as real-time feedback to ensure the production of large quantities of uniform microcapsules.
Water vapor imagery from the geostationary satellites such as GOES, Meteosat, and GMS provides synoptic views of dynamical events on a continual basis. Because the imagery represents a non-linear combination of mid- and upper-tropospheric thermodynamic parameters (three-dimensional variations in temperature and humidity), video loops of these image products provide enlightening views of regional flow fields, the movement of tropical and extratropical storm systems, the transfer of moisture between hemispheres and from the tropics to the mid- latitudes, and the dominance of high pressure systems over particular regions of the Earth. Despite the obvious larger scale features, the water vapor imagery contains significant image variability down to the single 8 km GOES pixel. These features can be quantitatively identified and tracked from one time to the next using various image processing techniques. Merrill et al. (1991), Hayden and Schmidt (1992), and Laurent (1993) have documented the operational procedures and capabilities of NOAA and ESOC to produce cloud and water vapor winds. These techniques employ standard correlation and template matching approaches to wind tracking and use qualitative and quantitative procedures to eliminate bad wind vectors from the wind data set. Techniques have also been developed to improve the quality of the operational winds though robust editing procedures (Hayden and Veldon 1991). These quality and control approaches have limitations, are often subjective, and constrain wind variability to be consistent with model derived wind fields. This paper describes research focused on the refinement of objective quality and control parameters for water vapor wind vector data sets. New quality and control measures are developed and employed to provide a more robust wind data set for climate analysis, data assimilation studies, as well as operational weather forecasting. The parameters are applicable to cloud-tracked winds as well with minor modifications. The improvement in winds through use of these new quality and control parameters is measured without the use of rawinsonde or modeled wind field data and compared with other approaches.
The ACT-America project is a NASA Earth Venture Suborbital-2 mission designed to study the transport and fluxes of greenhouse gases. The open and freely available ACT-America data sets provide airborne in situ measurements of atmospheric carbon dioxide, methane, trace gases, aerosols, clouds, and meteorological properties, airborne remote sensing measurements of aerosol backscatter, atmospheric boundary layer height and columnar content of atmospheric carbon dioxide, tower-based measurements, and modeled atmospheric mole fractions and regional carbon fluxes of greenhouse gases over the Central and Eastern United States. In this study, we conducted 121 research flights during five campaigns in four seasons during 2016–2019 over three regions of the US (Mid-Atlantic, Midwest and South) using two NASA research aircraft (B-200 and C-130). We performed three flight patterns (fair weather, frontal crossings, and OCO-2 underflights) and collected more than 1,140 h of airborne measurements via level-leg flights in the atmospheric boundary layer, lower, and upper free troposphere and vertical profiles spanning these altitudes. We also merged various airborne in situ measurements onto a common standard sampling interval, which brings coherence to the data, creates geolocated data products, and makes it much easier for the users to perform holistic analysis of the ACT-America data products. Here, we report on detailed information of data sets collected, the workflow for data sets including storage and processing of the quality controlled and quality assured harmonized observations, and their archival and formatting for users. Finally, we provide some important information on the dissemination of data products including metadata and highlights of applications of ACT-America data sets.
Seismic amplitudes offer vital information about explosion source characteristics, including discrimination and yield estimation. To take advantage of this, we developed an interactive Python package to measure, control data quality, generate broad area propagation models and perform discrimination and estimate yield. Propagation models are essential in support of transportable yield and broad area discrimination. The key benefit of this package will be its ability to continuously integrate data and new techniques. The AmpSuite framework will provide standardized, repeatable, and accurate model generation and characterization routines. The capability is crucial for monitoring agencies tasked with rapid and high-quality seismic event characterization. The AmpSuite software includes a series of independent modules to perform: • Direct Phase Amplitude Measurement and Storage • Coda Envelope Measurement and Storage • Data Quality Control • New Propagation Model Developments • Seismic Discrimination and Analysis • Yield Estimation and supporting utility software. The AmpSuite software provides comprehensive solutions for monitoring agencies seeking to optimize model generation and event analysis within a contemporary Python framework. Stakeholders (AFTAC) have begun to move towards the Python language for scientific analysis as a new workforce emerges.
In the early development of jet engines, it was occasionally found that excessive amounts of coke or other carbonaceous deposits were formed in the combustion chamber. Sometimes a considerable amount of smoke was noted in the-exhaust gases. Excessive coke deposits may adversely affect jet-engine performance in several ways. The formation of excessive amounts of coke on or just downstream of a fuel nozzle (figs. 116(a) and (b)) changes the fuel-spray pattern and possibly affects combustor life and performance. Similar effects on performance can result from the deposition of coke on primary-air entry ports (fig. 116(c)). Sea-level or altitude starting may be impaired by the deposition of coke on spark-plug electrodes (fig. 116(b)), deposits either grounding the electrodes completely or causing the spark to occur at positions other than the intended gap. For some time it was thought that large deposits of coke in turbojet combustion chambers (fig. 116(a)) might break away and damage turbine blades; however, experience has indicated that for metal blades this problem is insignificant. (Cermet turbine blades may be damaged by loose coke deposits.) Finally, the deposition of coke may cause high-temperature areas, which promote liner warping and cracking (fig. 116(d)) from excessive temperature gradients and variations in thermal-expansion rates. Smoke in the exhaust gases does not generally impair engine performance but may be undesirable from a tactical or a nuisance standpoint. Appendix B of reference 1 and references 2 to 4 present data obtained from full-scale engines operated on test stands and from flight tests that indicate some effects on performance caused by coke deposits and smoke. Some information about the mechanism of coke formation is given in reference 5 and chapter IX. The data indicate that (1) high-boiling fuel residuals and partly polymerized products may be mixed with a large amount of smoke formed in the gas phase to account for the consistency, structure, and chemical composition of the soft coke in the dome and (2) the hard deposits on the liner are similar to petroleum coke and may result from the liquid-phase thermal cracking of the fuel. During the early development period of jet engines, it was noted that the excessive coke deposits and exhaust smoke were generally obtained when fuel-oil-type fuels were used. Engines using gasoline-type fuels were relatively free from the deposits and smoke. These results indicated that some type of quality control would be needed in fuel specifications. Also noted was the effect of engine operating conditions on coke deposition. It is possible that, even with a clean-burning fuel, an excessive amount of coke could be formed at some operating conditions. In this case, combustor redesign could possibly reduce the coke to a tolerable level. This chapter is a summary of the various coke-deposition and exhaust-smoke problems connected- with the turbojet combustor. Included are (1) the effect of coke deposition on combustor life or durability and performance; (2) the effect of combustor design, operating conditions, inlet variables, and fuel characteristics on coke deposition; (3) elimination of coke deposits; (4) the effect of operating conditions and fuel characteristics on formation of exhaust smoke; and (5) various bench test methods proposed for determining and controlling fuel quality.
Contractor and NASA technical management for the development and manufacture of the Skylab modules is reviewed with emphasis on the following management controls: configuration and interface management; vendor control; and quality control of workmanship. A review of the modified two-stage Saturn V launch vehicle which focused on modifications to accommodate the Skylab payload; resolution of prior flight anomalies; and changes in personnel and management systems is presented along with an evaluation of the possible age-life and storage problems for the Saturn 1-B launch vehicle. The NASA program management's visibility and control of contractor operations, systems engineering and integration, the review process for the evaluation of design and flight hardware, and the planning process for mission operations are investigated. It is concluded that the technical management system for development and fabrication of the modules, spacecraft, and launch vehicles, the process of design and hardware acceptance reviews, and the risk assessment activities are satisfactory. It is indicated that checkout activity, integrated testing, and preparations for and execution of mission operation require management attention.
The STEALTH code system, which solves large strain, nonlinear continuum mechanics problems, was rigorously structured in both overall design and programming standards. The design is based on the theoretical elements of analysis while the programming standards attempt to establish a parallelism between physical theory, programming structure, and documentation. These features have made it easy to maintain, modify, and transport the codes. It has also guaranteed users a high level of quality control and quality assurance.
A Weld Operator's Remote Monitoring System (WORMS) for remote viewing of manual and automatic GTA welds has been developed for use in Space Shuttle Main Engine (SSME) manufacturing. This system utilizes fiberoptics to transmit images from a receiving lens to a small closed-circuit television (CCTV) camera. The camera converts the image to an electronic signal, which is sent to a videotape recorder (VTR) and a monitor. The overall intent of this system is to provide a clearer, more detailed view of welds than is available by direct observation. This system has six primary areas of application: (1) welder training; (2) viewing of joint penetration; (3) viewing visually inaccessible welds; (4) quality control and quality assurance; (5) remote joint tracking and adjustment of variables in machine welds; and (6) welding research and development. This paper describes WORMS and how it applies to each application listed.