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At least 37 records · Page 2

Thrust Augmentation of a Turbojet Engine at Simulated Flight Conditions by Introduction of a Water-Alcohol Mixture into the Compressor

An investigation was conducted at simulated high-altitude flight conditions to evaluate the use of compressor evaporative cooling as a means of turbojet-engine thrust augmentation. Comparison of the performance of the engine with water-alcohol injection at the compressor inlet, at the sixth stage of the compressor, and at the sixth and ninth stages was made. From consideration of the thrust increases achieved, the interstage injection of the coolant was considered more desirable preferred over the combined sixth- and ninth-stage injection because of its relative simplicity. A maximum augmented net-thrust ratio of 1.106 and a maximum augmented jet-thrust ratio of 1.062 were obtained at an augmented liquid ratio of 2.98 and an engine-inlet temperature of 80 F. At lower inlet temperatures (-40 to 40 F), the maximum augmented net-thrust ratios ranged from 1.040 to 1.076 and the maximum augmented jet-thrust ratios ranged from 1.027 to 1.048, depending upon the inlet temperature. The relatively small increase in performance at the lower inlet-air temperatures can be partially attributed to the inadequate evaporation of the water-alcohol mixture, but the more significant limitation was believed to be caused by the negative influence of the liquid coolant on engine- component performance. In general, it is concluded that the effectiveness of the injection of a coolant into the compressor as a means of thrust augmentation is considerably influenced by the design characteristics of the components of the engine being used.

Useller, James W.↗

Studies of Operating Frequency Effects On Ejector-based Thrust Augmentation in a Pulse Detonation Engine

Studies were performed in order to characterize the thrust augmentation potential of an ejector in a Pulse Detonation Engine application. A 49-mm diameter tube of 0.914-m length was constructed with one open end and one closed end. Ethylene, oxygen, and nitrogen were introduced into the tube at the closed end through the implementation of a fast mixing injector. The tube was completely filled with a stoichiometric mixture containing a one to one molar ratio of nitrogen to oxygen. Ethylene was selected as the fuel due to its detonation sensitivity and the molar ratio of the oxidizer was chosen for heat transfer purposes. Detonations were initiated in the tube through the use of a spark ignition system. The PDE was operated in a multi-cycle mode at frequencies ranging from 20-Hz to 50-Hz. Baseline thrust measurements with no ejector present were performed while operating the engine at various frequencies and compared to theoretical estimates. The baseline values were observed to agree with the theoretical model at low operating frequencies and proved to be increasingly lower than the predicted values as the operating frequency was increased. The baseline thrust measurements were observed to agree within 15 percent of the model for all operating frequencies. A straight 152-mm diameter ejector was installed and thrust augmentation percentages were measured. The length of the ejector was varied while the overlap percentage (percent of the ejector length which overlapped the tube) was maintained at 25 percent for all tests. In addition, the effect of ejector inlet geometry was investigated by comparing results with a straight inlet to those of a 38-mm inlet diameter. The thrust augmentation of the straight inlet ejector proved to be independent of engine operating frequency, augmenting thrust by 40 percent for the 0.914-m length ejector. In contrast, the rounded lip ejector of the same length seemed to be highly dependent on the engine operating frequency. An optimum operating frequency observed with the rounded inlet occurred at an operating frequency of 30-Hz, resulting in thrust augmentation percentages greater than 100 percent. The effect that the engine operating frequency had on thrust augmentation levels attained with an ejector was characterized and optimum performance parameters were established. Insight into the frequency dependent nature of the ejector performance was pursued. Suggestions for future experiments which are needed to fully understand the means in which thrust augmentation is achieved in a PDE-ejector configuration were noted.

Landry, K.↗

Augmented Reality for Managing Nuclear Infrastructure and Operations - 19605

Emerging augmented reality tools offer great promise for helping manage nuclear infrastructure throughout its life cycle. These tools have the ability to provide operators with actionable holographic information as they work. Perhaps more excitingly these tools also feature sensors that provide the ability to document work at very high spatial resolution. These sensors include onboard cameras as well as active infrared sensors that can capture 3D geometry information on-the-fly. Coupling the visualization and sensing tools provided by augmented reality headsets with computational intelligence opens up many exciting new possibilities for managing nuclear infrastructure throughout its life cycle. In this presentation we show a number of examples of how augmented reality tools can be incorporated into the management of nuclear infrastructure. We show examples of using augmented reality as a human-machine interface for robotic control, and we show examples of augmented reality being interfaced with external sensors. Finally, we show how these sensing and visualization capabilities of augmented reality can be interfaced with intelligent algorithms to help operators perform their work in nuclear facilities. The goal of the work is to spark discussions on how emerging augmented reality tools can help enable the next generation of efficient, high-performance nuclear infrastructure. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Making Invisible Visible: Data-Driven Seismic Inversion With Spatio-Temporally Constrained Data Augmentation

Deep learning and data-driven approaches have shown great potential in scientific domains. The promise of data-driven techniques relies on the availability of a large volume of high-quality training datasets. Due to the high cost of obtaining data through expensive physical experiments, instruments, and simulations, data augmentation techniques for scientific applications have emerged as a new direction for obtaining scientific data recently. However, existing data augmentation techniques originating from computer vision yield physically unacceptable data samples that are not helpful for the domain problems that we are interested in. In this article, we develop new data augmentation techniques based on convolutional neural networks. Specifically, our generative models leverage different physics knowledge (such as governing equations, observable perception, and physics phenomena) to improve the quality of the synthetic data. To validate the effectiveness of our data augmentation techniques, we apply them to solve a subsurface seismic full-waveform inversion using simulated CO 2 leakage data. Our interest is to invert for subsurface velocity models associated with very small CO 2 leakage. We validate the performance of our methods using comprehensive numerical tests. Here via comparison and analysis, we show that data-driven seismic imaging can be significantly enhanced by using our data augmentation techniques. Particularly, the imaging quality has been improved by 15% in test scenarios of general-sized leakage and 17% in small-sized leakage when using an augmented training set obtained with our techniques.

58 GEOSCIENCES↗

Orion MPCV Continuum RCS Heating Augmentation Model Development

The reaction control system jets of the Orion Multi Purpose Crew Vehicle can have a significant impact on the magnitude and distribution of the surface heat flux on the leeside of the aft-body, when they are fired. Changes in surface heating are expressed in terms of augmentation factor over the baseline smooth body heating. Wind tunnel tests revealed heating augmentation factors as high as 13.0, 7.6, 2.8, and 5.8 for the roll, pitch down, pitch up, and yaw jets respectively. Heating augmentation factor models, based almost exclusively on data from a series of wind tunnel tests have been developed, for the purposes of thermal protection system design. The wind tunnel tests investigated several potential jet-to-freestream similarity parameters, and heating augmentation factors derived from the data showed correlation with the jet-to-freestream momentum ratio. However, this correlation was not utilized in the developed models. Instead augmentation factors were held constant throughout the potential trajectory space. This simplification was driven by the fact that ground to flight traceability and sting effects are not well understood. Given the sensitivity of the reaction control system jet heating augmentation to configuration, geometry, and orientation the focus in the present paper is on the methodology used to develop the models and the lessons learned from the data. The models that are outlined in the present work are specific to the aerothermal database used to design the thermal protection system for the Exploration Flight Test 1 vehicle.

Heating Augmentation↗

Intercellular adhesion molecule-1 expression by skeletal muscle cells augments myogenesis

We previously demonstrated that the expression of intercellular adhesion molecule-1 (ICAM-1) by skeletal muscle cells after muscle overload contributes to ensuing regenerative and hypertrophic processes in skeletal muscle. The objective of the present study is to reveal mechanisms through which skeletal muscle cell expression of ICAM-1 augments regenerative and hypertrophic processes of myogenesis. This was accomplished by genetically engineering C2C12 myoblasts to stably express ICAM-1, and by inhibiting the adhesive and signaling functions of ICAM-1 through the use of a neutralizing antibody or cell penetrating peptide, respectively. Expression of ICAM-1 by cultured skeletal muscle cells augmented myoblast–myoblast adhesion, myotube formation, myonuclear number, myotube alignment, myotube–myotube fusion, and myotube size without influencing the ability of myoblasts to proliferate or differentiate. ICAM-1 augmented myotube formation, myonuclear accretion, and myotube alignment through a mechanism involving adhesion-induced activation of ICAM-1 signaling, as these dependent measures were reduced via antibody and peptide inhibition of ICAM-1. The adhesive and signaling functions of ICAM-1 also facilitated myotube hypertrophy through a mechanism involving myotube–myotube fusion, protein synthesis, and Akt/p70s6k signaling. Our findings demonstrate that ICAM-1 expression by skeletal muscle cells augments myogenesis, and establish a novel mechanism through which the inflammatory response facilitates growth processes in skeletal muscle. - Highlights: • We examined mechanisms through which skeletal muscle cell expression of ICAM-1 facilitates events of in vitro myogenesis. • Expression of ICAM-1 by cultured myoblasts did not influence their ability to proliferate or differentiate. • Skeletal muscle cell expression of ICAM-1 augmented myoblast fusion, myotube alignment, myotube–myotube fusion, and myotube size. • ICAM-1 augmented myogenic processes through mechanisms involving its adhesive and signaling functions.

60 APPLIED LIFE SCIENCES↗

Molecular phylogenetic trees - On the validity of the Goodman-Moore augmentation algorithm

A response is made to the reply of Nei and Tateno (1979) to the letter of Holmquist (1978) supporting the validity of the augmentation algorithm of Moore (1977) in reconstructions of nucleotide substitutions by means of the maximum parsimony principle. It is argued that the overestimation of the augmented numbers of nucleotide substitutions (augmented distances) found by Tateno and Nei (1978) is due to an unrepresentative data sample and that it is only necessary that evolution be stochastically uniform in different regions of the phylogenetic network for the augmentation method to be useful. The importance of the average value of the true distance over all links is explained, and the relative variances of the true and augmented distances are calculated to be almost identical. The effects of topological changes in the phylogenetic tree on the augmented distance and the question of the correctness of ancestral sequences inferred by the method of parsimony are also clarified.

Holmquist, R.↗

Cooperative synthesis of control and display augmentation for a STOL aircraft in the approach and landing task

Application of the Cooperative methodology to synthesize control/display augmentation systems for the piloted longitudinal landing task with a modern, statically-unstable, fighter aircraft is considered. Starting with a control augmentation law which yields augmented vehicle dynamics that meet Level I handling qualities specifications, the effect of time-delay in the Head-up-display is studied using model-based criterion. This evaluation showed that even with 'good' conventional dynamics, a realistic value of display time-delay will cause significant deterioration in pilot workload and piloted-system performance. Application of the Cooperative methodology to control augmentation alone resulted in augmented vehicle dynamics which provide direct control of the flight path from the pilot stick. Analytical evaluation of these dynamics indicates that such dynamics might lead to improved pilot ratings over conventional dynamics, especially in the presence of time-delays in the system. Also, application of the methodology to simultaneous synthesis of control augmentation and flight director laws revealed that it might be advantageous to consider the control/display trade-off in the early design stages.

Garg, Sanjay↗

Low-Speed Wind-Tunnel Investigation to Determine the Aerodynamic Characteristics of a Rectangular Wing Equipped with a Full-Span and an Inboard Half-Span Jet-Augmented Flap Deflected 55 deg

An investigation to determine the aerodynamic characteristics of a rectangular wing equipped with a full-span and an inboard half-span jet-augmented flap has been made in the Langley 300 MPH 7- by 10-foot tunnel. The wing had an aspect ratio of 8.3 and a thickness-chord ratio of 0.167. A jet of air was blown backward through a small gap, tangentially to the upper surface of a round trailing edge, and was separated from the trailing edge by a very small flap at an angle of 55 deg with respect to the wing-chord plane. The results of the investigation showed that the ratio of total lift to jet-reaction lift for the wing was about 35 percent less for the half-span jet-augmented flap than for the full-span jet-augmented flap. The reduction of the span of the jet-augmented flap from full to half span reduced the maximum value of jet-circulation lift coefficient that could be produced from about 6.8 to a value of about 2.2. The half-span jet- augmented flap gave thrust recoveries considerably poorer than those obtained with the full-span jet-augmented flap. Large nose-down pitching- moment coefficients were produced by the half-span flap, with the greater part of these being the result of the larger jet reactions required to produce a given lift for the half-spin flap compared with that required for the full-span flap.

Gainer, Thomas G.↗

Parametric Investigation of Thrust Augmentation by Ejectors on a Pulsed Detonation Tube

A parametric investigation has been made of thrust augmentation of a 1 inch diameter pulsed detonation tube by ejectors. A set of ejectors was used which permitted variation of the ejector length, diameter, and nose radius, according to a statistical design of experiment scheme. The maximum augmentations for each ejector were fitted using a polynomial response surface, from which the optimum ejector diameters, and nose radius, were found. Thrust augmentations above a factor of 2 were measured. In these tests, the pulsed detonation device was run on approximately stoichiometric air-hydrogen mixtures, at a frequency of 20 Hz. Later measurements at a frequency of 40 Hz gave lower values of thrust augmentation. Measurements of thrust augmentation as a function of ejector entrance to detonation tube exit distance showed two maxima, one with the ejector entrance upstream, and one downstream, of the detonation tube exit. A thrust augmentation of 2.5 was observed using a tapered ejector.

Wilson, Jack↗

Parametric Investigation of Thrust Augmentation by Ejectors on a Pulsed Detonation Tube

A parametric investigation has been made of thrust augmentation of a 1 in. diameter pulsed detonation tube by ejectors. A set of ejectors was used which permitted variation of the ejector length, diameter, and nose radius, according to a statistical design of experiment scheme. The maximum augmentation ratios for each ejector were fitted using a polynomial response surface, from which the optimum ratios of ejector diameter to detonation tube diameter, and ejector length and nose radius to ejector diameter, were found. Thrust augmentation ratios above a factor of 2 were measured. In these tests, the pulsed detonation device was run on approximately stoichiometric air-hydrogen mixtures, at a frequency of 20 Hz. Later measurements at a frequency of 40 Hz gave lower values of thrust augmentation. Measurements of thrust augmentation as a function of ejector entrance to detonation tube exit distance showed two maxima, one with the ejector entrance upstream, and one downstream, of the detonation tube exit. A thrust augmentation of 2.5 was observed using a tapered ejector.

Wilson, Jack↗

Performance Evaluation of Augmented Teleoperation of Contact Manipulation Tasks

At Argonne National Laboratory, an enhanced telerobotic concept has been suggested by providing augmented virtual fixtures for precise and dexterous manipulation. The proposed technology incorporated a human-robot interface that can assist personnel on the processes of Deactivation and Decommissioning in sites of high radiation. It has been implemented on a dual-arm robot system, known as Baxter, by integrating the Robotic Operating System (ROS) with 3D sensors and visual-haptic operator interface. However, what remained before its practical utilization is the capability for precisely placing the virtual fixtures. To this end, the objectives involved camera calibration, which required hardware fabrication and setup, as well as modification and implementation of ROS. The goal of this Research and Development is to develop an augmented-reality- based operator interface for human-inclusive, intelligent, and autonomous robotic system for the Deactivation and Decommissioning (D and D) of radioactive sites. The objectives are to develop: Collaborative Robot; Multi-modal Mixed-Reality Human-Robot Interface; Intelligent and Autonomous Behaviors. In order to achieve this, Baxter's Head-Kinect camera and Left-Hand camera need to be calibrated to overlap the real environment with the simulated environment. Camera calibration, which is crucial for precisely placing the virtual fixtures, was successful after running the simulations. The real and simulated environments overlapped, permitting the utilization of augmented teleoperation and the dexterous manipulation of Baxter for D and D applications in nuclear sites. Future steps: Performance evaluation of augmented teleoperation of contact manipulation tasks: Multiple-Camera 3D Reconstruction and Automation. Oculus Interface: Augmented reality and machine learning for enhanced telerobotic operation (Augmented Tele-autonomy): Machine-learning techniques for complex and flexible autonomous robotic behaviors. Interactive remote operation of robotic systems. Mesh cutting with simulation and real robot.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

An adaptive sampling augmented Lagrangian method for stochastic optimization with deterministic constraints

The primary goal of this paper is to provide an efficient solution algorithm based on the augmented Lagrangian framework for optimization problems with a stochastic objective function and deterministic constraints. Our main contribution is combining the augmented Lagrangian framework with adaptive sampling, resulting in an efficient optimization methodology validated with practical examples. To achieve the presented efficiency, here we consider inexact solutions for the augmented Lagrangian subproblems, and through an adaptive sampling mechanism, we control the variance in the gradient estimates. Furthermore, we analyze the theoretical performance of the proposed scheme by showing equivalence to a gradient descent algorithm on a Moreau envelope function, and we prove sublinear convergence for convex objectives and linear convergence for strongly convex objectives with affine equality constraints. The worst-case sample complexity of the resulting algorithm, for an arbitrary choice of penalty parameter in the augmented Lagrangian function, is $\mathscr{O}$(ϵ -3-δ ) , where ϵ > 0 is the expected error of the solution and δ > 0 is a user-defined parameter. If the penalty parameter is chosen to be $\mathscr{O}$(ϵ -1 ), we demonstrate that the result can be improved to $\mathscr{O}$(ϵ -2 ) , which is competitive with the other methods employed in the literature. Moreover, if the objective function is strongly convex with affine equality constraints, we obtain $\mathscr{O}$(ϵ -1 log(1/ϵ)) complexity. Finally, we empirically verify the performance of our adaptive sampling augmented Lagrangian framework in machine learning optimization and engineering design problems, including topology optimization of a heat sink with environmental uncertainty.

97 MATHEMATICS AND COMPUTING↗

Deep learning with mixup augmentation for improved pore detection during additive manufacturing

In additive manufacturing (AM), process defects such as keyhole pores are difficult to anticipate, affecting the quality and integrity of the AM-produced materials. Hence, considerable efforts have aimed to predict these process defects by training machine learning (ML) models using passive measurements such as acoustic emissions. This work considered a dataset in which keyhole pores of a laser powder bed fusion (LPBF) experiment were identified using X-ray radiography and then registered both in space and time to acoustic measurements recorded during the LPBF experiment. Due to AM’s intrinsic process controls, where a pore-forming event is relatively rare, the acoustic datasets collected during monitoring include more non-pores than pores. In other words, the dataset for ML model development is imbalanced. Moreover, this imbalanced and sparse data phenomenon remains ubiquitous across many AM monitoring schemes since training data is nontrivial to collect. Hence, we propose a machine learning approach to improve this dataset imbalance and enhance the prediction accuracy of pore-labeled data. Specifically, we investigate how data augmentation helps predict pores and non-pores better. This imbalance is improved using recent advances in data augmentation called Mixup, a weak-supervised learning method. Convolutional neural networks (CNNs) are trained on original and augmented datasets, and an appreciable increase in performance is reported when testing on five different experimental trials. When ML models are trained on original and augmented datasets, they achieve an accuracy of 95% and 99% on test datasets, respectively. We also provide information on how dataset size affects model performance. Lastly, we investigate the optimal Mixup parameters for augmentation in the context of CNN performance.

36 MATERIALS SCIENCE↗

AMPS: An Augmented Matrix Formulation for Principal Submatrix Updates with Application to Power Grids

We present an augmented matrix approach to update the solution to a linear system of equations when the coefficient matrix is modified by a few elements within a principal submatrix. This problem arises in the dynamic security analysis of a power grid, where operators need to perform $N-x$ contingency analysis, i.e., determine the state of the system when up to $x$ links from $N$ fail. Our algorithms augment the coefficient matrix to account for the changes in it, and then compute the solution to the augmented system without refactoring the modified matrix. We provide two algorithms, a direct method, and a hybrid direct-iterative method for solving the augmented system. We also exploit the sparsity of the matrices and vectors to accelerate the overall computation. Our algorithms are compared on three power grids with PARDISO, a parallel direct solver, and CHOLMOD, a direct solver with the ability to modify the Cholesky factors of the coefficient matrix. We show that our augmented algorithms outperform PARDISO (by two orders of magnitude), and CHOLMOD (by a factor of up to 5). Further, our algorithms scale better than CHOLMOD as the number of elements updated increases. The solutions are computed with high accuracy. Our algorithms are capable of computing $N-x$ contingency analysis on a $778K$ bus grid, updating a solution with $x=20$ elements in $1.6 \times 10^{-2}$ seconds on an Intel Xeon processor.

Yeung, Yu-Hong↗

Enabling human–infrastructure interfaces for inspection using augmented reality

Decaying infrastructure maintenance cost allocation depends heavily on accurate and safe inspection in the field. New tools to conduct inspections can assist in prioritizing investments in maintenance and repairs. The industrial revolution termed as “Industry 4.0” is based on the intelligence of machines working with humans in a collaborative workspace. Contrarily, infrastructure management has relied on the human for making day-to-day decisions. New emerging technologies can assist during infrastructure inspections, to quantify structural condition with more objective data. However, today’s owners agree in trusting the inspector’s decision in the field over data collected with sensors. If data collected in the field is accessible during the inspections, the inspector decisions can be improved with sensors. New research opportunities in the human–infrastructure interface would allow researchers to improve the human awareness of their surrounding environment during inspections. This article studies the role of Augmented Reality (AR) technology as a tool to increase human awareness of infrastructure in their inspection work. The domains of interest of this research include both infrastructure inspections (emphasis on the collection of data of structures to inform management decisions) and emergency management (focus on the data collection of the environment to inform human actions). This article describes the use of a head-mounted device to access real-time data and information during their field inspection. The authors leverage the use of low-cost smart sensors and QR code scanners integrated with Augmented Reality applications for augmented human interface with the physical environment. This article presents a novel interface architecture for developing Augmented Reality–enabled inspection to assist the inspector’s workflow in conducting infrastructure inspection works with two new applications and summarizes the results from various experiments. The main contributions of this work to computer-aided community are enabling inspectors to visualize data files from database and real-time data access using an Augmented Reality environment.

Maharjan, D.↗

Deep learning with mixup augmentation for improved pore detection during additive manufacturing

In additive manufacturing (AM), process defects such as keyhole pores are difficult to anticipate, affecting the quality and integrity of the AM-produced materials. Hence, considerable efforts have aimed to predict these process defects by training machine learning (ML) models using passive measurements such as acoustic emissions. This work considered a dataset in which keyhole pores of a laser powder bed fusion (LPBF) experiment were identified using X-ray radiography and then registered both in space and time to acoustic measurements recorded during the LPBF experiment. Due to AM’s intrinsic process controls, where a pore-forming event is relatively rare, the acoustic datasets collected during monitoring include more non-pores than pores. In other words, the dataset for ML model development is imbalanced. Moreover, this imbalanced and sparse data phenomenon remains ubiquitous across many AM monitoring schemes since training data is nontrivial to collect. Hence, we propose a machine learning approach to improve this dataset imbalance and enhance the prediction accuracy of pore-labeled data. Specifically, we investigate how data augmentation helps predict pores and non-pores better. This imbalance is improved using recent advances in data augmentation called Mixup, a weak-supervised learning method. Convolutional neural networks (CNNs) are trained on original and augmented datasets, and an appreciable increase in performance is reported when testing on five different experimental trials. When ML models are trained on original and augmented datasets, they achieve an accuracy of 95% and 99% on test datasets, respectively. We also provide information on how dataset size affects model performance. Lastly, we investigate the optimal Mixup parameters for augmentation in the context of CNN performance.

42 ENGINEERING↗

A lifting surface theory for thrust augmenting ejectors

The circulation theory of airfoil lift has been applied to calculate the performance of thrust augmenting ejectors. The ejector shroud is considered to be 'flying' in the secondary velocity field induced by the entrainment of the primary jet, so that the augmenting thrust is viewed as analogous to the lift on an airfoil. Vortex lattice methods are utilized to compute the thrust augmentation from the force on the flaps. The augmentation is shown to be a function of the length and shape of the flaps, as well as their position and orientation. Predictions of this new theory are compared with the results of classical methods of calculating the augmentation by integration of the stream thrust.

Bevilaqua, P. M.↗