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Repeated observation of an uncertain signal

The focus here is on sensory adaptation, or progressively more appropriate attention, as repeated observations yield more information about a signal with an uncertain parameter. The signal was a brief sinusoid; its uncertain parameter was frequency. Detection performance is predicted from data on a signal of known and constant frequency, as a function of the number of frequencies the uncertain signal could assume. A comparison condition presented a signal that varied in a manner not permitting adaptation. Models derived from signal detection theory describe the ideal observation processes for the three signal conditions, and supply quantitative predictions of relative performances. The models are generally supported by the data.

Swets, J. A.

A nonstationary relaxation method for the Cauchy-Riemann and 1-D Euler equations

The Cauchy-Riemann equations and the 1-D Euler equations are expressed in generalized coordinates and then cast in finite difference form by using central differencing throughout. The resulting matrix representation has an eigensystem that permits the development of an annihilation process using complex arithmetic in a block tridiagonal solver. Initial numerical experiments show that the process has potential for use as a relaxation procedure for the Euler equations.

Liu, Y.

Experimental determination of systems suitable for study as monotectic binary metallic alloy solidification models

Transparent binary metallic alloy solidification models are important in attempts to understand the processes causing liquid-liquid and solid-liquid phase transformations in metallic alloy systems. These models permit visual observation of the phase transformation and the processes proceding solidification. The number of these transparent monotectic binary models needs to be expanded to distinguish between the unique and general phenomena observed. The expansion of the number of accurately determined monotectic phase diagrams of model systems, and contribution to a data base for eventual use with UNIFAC group contribution methods is examined.

Smith, J. E., Jr.

Mission planning for space based satellite surveillance experiments with the MSX

The Midcourse Space Experiment is a BMDO-sponsored scientific satellite set for launch within the year. The satellite will collect phenomenology data on missile targets, plumes, earth limb backgrounds and deep space backgrounds in the LWIR, visible and ultra-violet spectral bands. It will also conduct functional demonstrations for space-based space surveillance. The Space-Based Visible sensor, built by Lincoln Laboratory, Massachusetts Institute of Technology, is the primary sensor on board the MSX for demonstration of space surveillance. The SBV Processing, Operations and Control Center (SPOCC) is the mission planning and commanding center for all space surveillance experiments using the SBV and other MSX instruments. The guiding principle in the SPOCC Mission Planning System was that all routine functions be automated. Manual analyst input should be minimal. Major concepts are: (I) A high level language, called SLED, for user interface to the system; (2) A group of independent software processes which would generally be run in a pipe-line mode for experiment commanding but can be run independently for analyst assessment; (3) An integrated experiment cost computation function that permits assessment of the feasibility of the experiment. This paper will report on the design, implementation and testing of the Mission Planning System.

Sridharan, R.

Evaluation of LANDSAT-4 Thematic Mapper Data as Applied to Geologic Exploration: Summary of Results

As with any tool applied to geologic exploration, maximum value results from the innovative integration of optimally processed LANDSAT-4 data with existing pertinent information and perceptive geologic thinking. The synoptic view of the satellite images and the relatively high resolution of the data permits recognization of regional tectonic patterns and their detailed mapping. The refined spatial and spectral characteristics and digital nature surface alterations associated with hydrothermal activity and microseepage of hydrocarbons. In general, as vegetation and soil cover increase, the value of spectral components of TM data decreases with respect to the value of the spatial component of the data. This observation reinforces the experience from working with MSS data that digital processing must be optimized both for the area and for the application.

Dykstra, J. D.

A three-dimensional finite-element thermal/mechanical analytical technique for high-performance traveling wave tubes

Current research in high-efficiency, high-performance traveling wave tubes (TWT's) has led to the development of novel thermal/ mechanical computer models for use with helical slow-wave structures. A three-dimensional, finite element computer model and analytical technique used to study the structural integrity and thermal operation of a high-efficiency, diamond-rod, K-band TWT designed for use in advanced space communications systems. This analysis focused on the slow-wave circuit in the radiofrequency section of the TWT, where an inherent localized heating problem existed and where failures were observed during earlier cold compression, or 'coining' fabrication technique that shows great potential for future TWT development efforts. For this analysis, a three-dimensional, finite element model was used along with MARC, a commercially available finite element code, to simulate the fabrication of a diamond-rod TWT. This analysis was conducted by using component and material specifications consistent with actual TWT fabrication and was verified against empirical data. The analysis is nonlinear owing to material plasticity introduced by the forming process and also to geometric nonlinearities presented by the component assembly configuration. The computer model was developed by using the high efficiency, K-band TWT design but is general enough to permit similar analyses to be performed on a wide variety of TWT designs and styles. The results of the TWT operating condition and structural failure mode analysis, as well as a comparison of analytical results to test data are presented.

Bartos, Karen F.

A three-dimensional finite-element thermal/mechanical analytical technique for high-performance traveling wave tubes

Current research in high-efficiency, high-performance traveling wave tubes (TWT's) has led to the development of novel thermal/mechanical computer models for use with helical slow-wave structures. A three-dimensional, finite element computer model and analytical technique used to study the structural integrity and thermal operation of a high-efficiency, diamond-rod, K-band TWT designed for use in advanced space communications systems. This analysis focused on the slow-wave circuit in the radiofrequency section of the TWT, where an inherent localized heating problem existed and where failures were observed during earlier cold compression, or 'coining' fabrication technique that shows great potential for future TWT development efforts. For this analysis, a three-dimensional, finite element model was used along with MARC, a commercially available finite element code, to simulate the fabrication of a diamond-rod TWT. This analysis was conducted by using component and material specifications consistent with actual TWT fabrication and was verified against empirical data. The analysis is nonlinear owing to material plasticity introduced by the forming process and also to geometric nonlinearities presented by the component assembly configuration. The computer model was developed by using the high efficiency, K-band TWT design but is general enough to permit similar analyses to be performed on a wide variety of TWT designs and styles. The results of the TWT operating condition and structural failure mode analysis, as well as a comparison of analytical results to test data are presented.

Shalkhauser, Kurt A.

Enhancing Fluid Flow Pressure and Saturation Prediction Accuracy and Reducing Uncertainty with Committee Machine – Illinois Basin Decatur Project (IBDP) as a Case Study

Presentation at the 17th International Conference on Greenhouse Gas Control Technologies GHGT-17 held in Calgary, Canada, October 20-24, 2024. Carbon capture and storage (CCS) is a way to play a critical role in the global transition to a low-emission economy. Current progress is hampered by a number of factors, among which the lack of risk-informed design tools and decision support frameworks is seen as a major roadblock. Significant interest exists in using artificial intelligence to accelerate CCS site feasibility studies, as well as to facilitate the permit application process. Existing works commonly train a single deep learning model. This work investigates the feasibility of using a conventional ensemble learning (committee machine) technique to further improve prediction accuracy. Ensemble-based algorithms generally improve over individual base learners in terms of robustness and accuracy. Deep ensembles, however, are time-consuming to create and train. A pragmatic question is whether small-sized ensembles may lead to prediction improvement. Here we evaluated the efficacy of an ensemble learning technique using the latent spectral model (LSM), an efficient deep neural operator algorithm, as base learners. Preliminary results, obtained using the Illinois Basin-Decatur Project (IBDP) carbon sequestration data/model, show that small-sized ensembles can improve prediction over the base learners, achieving prediction accuracy of ~1.6 psi root mean square error (RMSE) on pressure (relative the average reservoir pressure of 3150 psi), and less than 1.3% for saturation.

Sun, Alexander

A data acquisition and handling system for the measurement of radial plasma transport rates

A microcomputer serves as a programmable interface between high frequency transient recorders and a digital incremental tape recorder. An interactive program stored in the microcomputer permits the operator to enter various experimental parameters in response to queries from the system. The microcomputer then stores both the experimental parameters and the raw digital data on tape for later processing by a general purpose computer.

Krawczonek, W. M.

Enhancing Fluid Flow Pressure and Saturation Prediction Accuracy and Reducing Uncertainty with Committee Machine – Illinois Basin Decatur Project (IBDP) as a Case Study

This is the conference paper accompanying an oral presentation at the 17th International Conference on Greenhouse Gas Control Technologies GHGT-17 held in Calgary, Canada, October 20-24, 2024. Carbon capture and storage (CCS) is a way to play a critical role in the global transition to a low-emission economy. Current progress is hampered by a number of factors, among which the lack of risk-informed design tools and decision support frameworks is seen as a major roadblock. Significant interest exists in using artificial intelligence to accelerate CCS site feasibility studies, as well as to facilitate the permit application process. Existing works commonly train a single deep learning model. This work investigates the feasibility of using a conventional ensemble learning (committee machine) technique to further improve prediction accuracy. Ensemble-based algorithms generally improve over individual base learners in terms of robustness and accuracy. Deep ensembles, however, are time-consuming to create and train. A pragmatic question is whether small-sized ensembles may lead to prediction improvement. Here we evaluated the efficacy of an ensemble learning technique using the latent spectral model (LSM), an efficient deep neural operator algorithm, as base learners. Preliminary results, obtained using the Illinois Basin-Decatur Project (IBDP) carbon sequestration data/model, show that small-sized ensembles can improve prediction over the base learners, achieving prediction accuracy of ~1.6 psi root mean square error (RMSE) on pressure (relative the average reservoir pressure of 3150 psi), and less than 1.3% for saturation.

Sun, Alexander

Integrating aerodynamics and structures in the minimum weight design of a supersonic transport wing

An approach is presented for determining the minimum weight design of aircraft wing models which takes into consideration aerodynamics-structure coupling when calculating both zeroth order information needed for analysis and first order information needed for optimization. When performing sensitivity analysis, coupling is accounted for by using a generalized sensitivity formulation. The results presented show that the aeroelastic effects are calculated properly and noticeably reduce constraint approximation errors. However, for the particular example selected, the error introduced by ignoring aeroelastic effects are not sufficient to significantly affect the convergence of the optimization process. Trade studies are reported that consider different structural materials, internal spar layouts, and panel buckling lengths. For the formulation, model and materials used in this study, an advanced aluminum material produced the lightest design while satisfying the problem constraints. Also, shorter panel buckling lengths resulted in lower weights by permitting smaller panel thicknesses and generally, by unloading the wing skins and loading the spar caps. Finally, straight spars required slightly lower wing weights than angled spars.

Barthelemy, Jean-Francois M.

Generalized implementation of software safety policies

As part of a research program in the engineering of software for safety-critical systems, we are performing two case studies. The first case study, which is well underway, is a safety-critical medical application. The second, which is just starting, is a digital control system for a nuclear research reactor. Our goal is to use these case studies to permit us to obtain a better understanding of the issues facing developers of safety-critical systems, and to provide a vehicle for the assessment of research ideas. The case studies are not based on the analysis of existing software development by others. Instead, we are attempting to create software for new and novel systems in a process that ultimately will involve all phases of the software lifecycle. In this abstract, we summarize our results to date in a small part of this project, namely the determination and classification of policies related to software safety that must be enforced to ensure safe operation. We hypothesize that this classification will permit a general approach to the implementation of a policy enforcement mechanism.

Knight, John C.

Advanced composite materials and processes

Composites are generally defined as two or more individual materials, which, when combined into a single material system, results in improved physical and/or mechanical properties. The freedom of choice of the starting components for composites allows the generation of materials that can be specifically tailored to meet a variety of applications. Advanced composites are described as a combination of high strength fibers and high performance polymer matrix materials. These advanced materials are required to permit future aircraft and spacecraft to perform in extended environments. Advanced composite precursor materials, processes for conversion of these materials to structures, and selected applications for composites are reviewed.

Baucom, Robert M.

Development of generalized 3-D braiding machines for composite preforms

The development of prototype braiding machines for the production of generalized braid patterns is described. Mechanical operating principles and control strategies are presented for two prototype machines which have been fabricated and evaluated. Both machines represent advances over current fabrication techniques for composite materials by enabling nearly ideal control of fiber orientations within preform structures. They permit optimum design of parts that might be subjected to complex loads or that have complex forms. Further, they overcome both the lack of general control of produced fiber architectures and the complexity of other weaving processes that have been proposed for the same purpose. One prototype, the Farley braider, consists of an array of turntables that can be made to oscillate in 90 degree steps. Yarn ends are transported about the surface formed by the turntables by motorized tractors which are controlled through an optical link with the turntables and powered through electrical contact with the turntables. The necessary relative motions are produced by a series of linear tractor moves combined with a series of turntable rotations. As the tractors move about, they weave the yarn ends into the desired pattern. The second device, the shuttle plate braider, consists of a braiding surface formed by an array of stationary square sections, each separated from its neighbors by a gap. A plate beneath this surface is caused to reciprocate in two perpendicular directions, first in one direction and then in the other. This movement is made possibly by openings in the plate that clear short columns supporting the surface segments. Yarn ends are moved about the surface and interwoven by shuttles which engage the reciprocating plate as needed to yield the desired movements. Power and control signals are transmitted to the shuttles through electrical contact with the braiding surface. The shuttle plate is a passively driven prime mover that supplies the power to move all shuttles and the shuttles are simple devices that employ only a solenoid to engage the shuttle plate on command. Each shuttle is assigned a unique identity and is controlled independently. When compared to each other, the Farley braider is felt to have the advantage of speed and the shuttle plate braider, the advantage of simplicity.

Huey, Cecil O., Jr.

ORION Code Infrastructure Upgrades

Prior to this update, ORION was capable of processing cases and data that spanned a single UTM zone and assumed that all spatial inputs were given in units of meters. During the 2024 SMART bridge funding period, we completed upgrades to the code that permit general spatial projections, basin-scale datasets, and units.

58 GEOSCIENCES

Apple Image Processing Educator

A software system design is proposed and demonstrated with pilot-project software. The system permits the Apple II microcomputer to be used for personalized computer-assisted instruction in the digital image processing of LANDSAT images. The programs provide data input, menu selection, graphic and hard-copy displays, and both general and detailed instructions. The pilot-project results are considered to be successful indicators of the capabilities and limits of microcomputers for digital image processing education.

Gunther, F. J.

Introduction to a system for implementing neural net connections on SIMD architectures

Neural networks have attracted much interest recently, and using parallel architectures to simulate neural networks is a natural and necessary application. The SIMD model of parallel computation is chosen, because systems of this type can be built with large numbers of processing elements. However, such systems are not naturally suited to generalized communication. A method is proposed that allows an implementation of neural network connections on massively parallel SIMD architectures. The key to this system is an algorithm permitting the formation of arbitrary connections between the neurons. A feature is the ability to add new connections quickly. It also has error recovery ability and is robust over a variety of network topologies. Simulations of the general connection system, and its implementation on the Connection Machine, indicate that the time and space requirements are proportional to the product of the average number of connections per neuron and the diameter of the interconnection network.

Tomboulian, Sherryl

Introduction to a system for implementing neural net connections on SIMD architectures

Neural networks have attracted much interest recently, and using parallel architectures to simulate neural networks is a natural and necessary application. The SIMD model of parallel computation is chosen, because systems of this type can be built with large numbers of processing elements. However, such systems are not naturally suited to generalized elements. A method is proposed that allows an implementation of neural network connections on massively parallel SIMD architectures. The key to this system is an algorithm permitting the formation of arbitrary connections between the neurons. A feature is the ability to add new connections quickly. It also has error recovery ability and is robust over a variety of network topologies. Simulations of the general connection system, and its implementation on the Connection Machine, indicate that the time and space requirements are proportional to the product of the average number of connections per neuron and the diameter of the interconnection network.

Tomboulian, Sherryl