A computer model is being developed by the David Taylor Research Center (DTRC) to analyze the tolerance of surface ship combat systems to combat-induced and self-inflicted damage. The work is being done in support of ...
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A computer model is being developed by the David Taylor Research Center (DTRC) to analyze the tolerance of surface ship combat systems to combat-induced and self-inflicted damage. The work is being done in support of the Navy's hull, mechanical and electrical design effort to improve the survivability of surface ship combat systems. The DDG-51 Detailed Design Specifications (Section 072f) and the General Specifications for Ships of the U.S. Navy (1986 Section 072e) both require that damage tolerance analyses be performed. A damage tolerance analysis shows the effect of damage on vital auxiliary and electrical systems and relates these damage effects to the capability of the ship to continue performing its combat mission at a prescribed level. Designated the Computer Aided Design of Survivable Distributed systems (CADSDiS) model, DTRC's deterministic analytical tool consists of portable software to be used by personnel at the activity responsible for the ship design. The model's graphics electrical module is now operating on Digital Equipment Corporation VAX computers at several Navy and commercial activities. Because CADSDiS is highly interactive, it becomes an integral part of the design cycle; this is its major benefit. Thus, damage tolerance analysis information is available to personnel designing the ship within hours or days rather than weeks or months. This computer model will help ensure that the survivability principles of separation and redundancy are incorporated into ship design and are realized in the ship as built.
A nonlinear dynamic model of the Czochralski process, valid throughout the batch growth cycle is derived for use in designing an improved processcontroller. The model is a lumped element representation of the major s...
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A nonlinear dynamic model of the Czochralski process, valid throughout the batch growth cycle is derived for use in designing an improved processcontroller. The model is a lumped element representation of the major system components, and simulates the dynamic system response to disturbances and system inputs. The linearized model is used to determine the system eigenstructure, revealing the system stability, transient response constants, and coupling. Significant results for control design include the identification of the basic time varying nature of the eigenstructure and the disturbances acting on the system, and identification of mechanisms that affect the transient system characteristics. In addition, the growth dynamic effects of liquid encapsulation, low thermal gradient schemes, and magnetic fields are discussed.
This paper outlines the structure and implementational features of the DESIGN-KIT, a software support environment developed to aid processengineering activities such as: synthesis of process flowsheets, configuration...
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This paper outlines the structure and implementational features of the DESIGN-KIT, a software support environment developed to aid processengineering activities such as: synthesis of process flowsheets, configuration of control loops for complete plants, planning and scheduling of plant-wide operations and operational analysis. Based on object-oriented and data-driven programming styles, the paper discusses how the DESIGN-KIT is constructed to provide a rich repertory of declarative and procedural knowledge for the development of analytic- or design-oriented knowledge-based expert systems. A series of illustrations describe the construction of knowledge bases, graphic interface support, equation-oriented simulation and design, order-of-magnitude analysis, reasoning strategies and other facilities of the DESIGN-KIT.
Using simulation, the steady state performance and transient behavior of starved extrusion screws are described. At steady state the filled length of the extruder is controlled by the relative resistance of the screw ...
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Using simulation, the steady state performance and transient behavior of starved extrusion screws are described. At steady state the filled length of the extruder is controlled by the relative resistance of the screw and die to flow, the flow index of the extrudate, and the feed rate to the extruder. For transient situations, small variations in the composition or feed rate of the material being extruded can significantly alter the extruder''s output and filled length. Because of the broader residence time distribution of a twin screw extruder compared to a single screw extruder, the magnitude of the transient effects are seen to be smaller for twin screw extruders. The predicted output transients for extruders operated in the starved condition are of significantly lower magnitude than that for extruders operated in a filled condition. The implications of these effects on the design and operation of extrusion systems are discussed.
A simulation of the transient response of single screw extruders to fluctuations in formula of the extrudate is described. Any changes in extrudate composition, which result in changes in the viscous properties of the...
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A simulation of the transient response of single screw extruders to fluctuations in formula of the extrudate is described. Any changes in extrudate composition, which result in changes in the viscous properties of the extrudate, result in transient behavior in the output of an extruder. Using existing extruder models, a simulation was used to study the transient behavior of an extruder in response to compositional variations in the extrudate. The results of the simulation suggest that for small variations in the composition of the material being extruded, large transient responses in extruder output will be observed. Depending on the relationship between the composition and viscosity of the extrudate, the change in output of the extruder can vary between insignificance and virtual stoppage of flow. The implications of these extruder transients on the design and operation of extrusion systems are discussed.
A variety of low-level radioactive waste streams are being generated from the decontamination and decommissioning of the former nuclear fuel reprocessing plant at West Valley, New York. It is presently planned to remo...
A variety of low-level radioactive waste streams are being generated from the decontamination and decommissioning of the former nuclear fuel reprocessing plant at West Valley, New York. It is presently planned to remove the radioactive contaminants from the solutions by ion exchange. Natural zeolites, such as clinoptilolite, erionite, chabazite, and phillipsite, were felt to provide desired flexibility and capacity under varying conditions. Batch and column testing were conducted on these materials using representative waste streams containing radioactive cesium, strontium, and cobalt. Sorption coefficients, dynamic decontamination factors, capacity, and sorption kinetics were determined. In addition, testing was conducted on prepared zeolites (i.e., Linde IE-95 and A-51) to provide comparative data.
This paper describes the methodological and implementational aspects of an intelligent system which is being developed for the planning of plant-side process operations such as start-up, response to faults, optimizati...
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This paper describes the methodological and implementational aspects of an intelligent system which is being developed for the planning of plant-side process operations such as start-up, response to faults, optimization, etc. In particular, it shows how knowledge is modeled, how the planning methodology is structured, and how current developments in artificial intelligence and LISP computers are being used to provide the implementational framework.
This article outlines the use of artificial intelligence in three areas of biotechnology: (a) exploration of new production routes for various bioproducts; (b) design of mammalian cell biofermentors; and (c) synthesis...
This article outlines the use of artificial intelligence in three areas of biotechnology: (a) exploration of new production routes for various bioproducts; (b) design of mammalian cell biofermentors; and (c) synthesis of downstream processing schemes for the separation and purification of proteins. Until recently, all of these areas have been ‘knowledge intensive’, driven by the incisive expertise of scientists and engineers, and quite resistant to analytic and rigorous mathematical formulations and solutions. Here we describe the ‘prototype intelligent system’ used in the above three areas, and attempt simple projections on the use of artificial intelligence in biotechnology.
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