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Technique substantially reduces machine complexity, improves injector performance and is useful for products mixed or homogenized by injector process. Method is applicable to pharmaceutical, food, dairy and petrochemical industries.
Decentralized operating systems that control large multicomputers need techniques to schedule competing parallel programs called task forces. Wave scheduling is a probabilistic technique that uses a hierarchical distributed virtual machine to schedule task forces by recursively subdividing and issuing wavefront-like commands to processing elements capable of executing individual tasks. Wave scheduling is highly resistant to processing element failures because it uses many distributed schedulers that dynamically assign scheduling responsibilities among themselves. The scheduling technique is trivially extensible as more processing elements join the host multicomputer. A simple model of scheduling cost is used by every scheduler node to distribute scheduling activity and minimize wasted processing capacity by using perceived workload to vary decentralized scheduling rules. At low to moderate levels of network activity, wave scheduling is only slightly less efficient than a central scheduler in its ability to direct processing elements to accomplish useful work.
The results of the implementation of a Navier-Stokes algorithm on three parallel/vector computers are presented. The object of this research is to determine how well, or poorly, a single numerical algorithm would map onto three different architectures. The algorithm is a compact difference scheme for the solution of the incompressible, two-dimensional, time-dependent Navier-Stokes equations. The computers were chosen so as to encompass a variety of architectures. They are the following: the MPP, an SIMD machine with 16K bit serial processors; Flex/32, an MIMD machine with 20 processors; and Cray/2. The implementation of the algorithm is discussed in relation to these architectures and measures of the performance on each machine are given. The basic comparison is among SIMD instruction parallelism on the MPP, MIMD process parallelism on the Flex/32, and vectorization of a serial code on the Cray/2. Simple performance models are used to describe the performance. These models highlight the bottlenecks and limiting factors for this algorithm on these architectures. Finally, conclusions are presented.
An attempt has been made to improve the high temperature mechanical strength of the B2 cubic crystal structure intermetallic NiAl by dispersion strengthening. Prealloyed Ni-51 at. pct Al was cryomilled with a Y2O3 addition to form an yttria dispersoid within the intermetallic matrix. Following milling, the powder was hot extruded to full density and machined into test coupons. Compression testing between 1200 and 1400 K indicated that the cryogenic process yielded the strongest NiAl based material tested to date. Creep resistance was six times better than NiAl and twice that of a NiAl particulate composite containing 10 vol pct TiB2. Surprisingly, transmission electron microscopy revealed that the second phase was inhomogeneously distributed. Furthermore, X-ray analysis indicated that the second phase was not Y2O3 but rather AlN.
This paper is based on the experience of engineering psychologists advising the U.K. Ministry of Defense (MoD) on the procurement of advanced aviation systems that conform to good human engineering (HE) practice. Traditional approaches to HE in systems procurement focus on the physical nature of the human-machine interface. Advanced aviation systems present increasingly complex design requirements for human functional integration, information processing, and cognitive task performance effectiveness. These developing requirements present new challenges for HE quality assurance (QA) and risk management, requiring focus on design processes as well as on design content or product. A new approach to the application of HE, recently adopted by NATO, provides more systematic ordering and control of HE processes and activities to meet the challenges of advanced aircrew systems design. This systematic approach to HE has been applied by MoD to the procurement of mission systems for the Royal Navy Merlin helicopter. In MoD procurement, certification is a judicial function, essentially independent of the service customer and industry contractor. Certification decisions are based on advice from MoD's appointed Acceptance Agency. Test and evaluation (T&E) conducted by the contractor and by the Acceptance Agency provide evidence for certification. Certification identifies limitations of systems upon release to the service. Evidence of compliance with HE standards traditionally forms the main basis of HE certification and significant non-compliance could restrict release. The systems HE approach shows concern for the quality of processes as well as for the content of the product. Human factors certification should be concerned with the quality of HE processes as well as products. Certification should require proof of process as well as proof of content and performance. QA criteria such as completeness, consistency, timeliness, and compatibility provide generic guidelines for progressive acceptance and certification of HE processes. Threats to the validity of certification arise from problems and assumptions in T&E methods. T&E should seek to reduce the risk of specification non-compliance and certification failure.
We have investigated a method, based on a successful neural network multispectral image classification system, of searching for single patterns in remote sensing databases. While defining the pattern to search for and the feature to be used for that search (spectral, spatial, temporal, etc.) is challenging, a more difficult task is selecting competing patterns to train against the desired pattern. Schemes for competing pattern selection, including random selection and human interpreted selection, are discussed in the context of an example detection of dense urban areas in Landsat Thematic Mapper imagery. When applying the search to multiple images, a simple normalization method can alleviate the problem of inconsistent image calibration. Another potential problem, that of highly compressed data, was found to have a minimal effect on the ability to detect the desired pattern. The neural network algorithm has been implemented using the PVM (Parallel Virtual Machine) library and nearly-optimal speedups have been obtained that help alleviate the long process of searching through imagery.
This paper presents an overview and analysis of learning in Artificial Neural Systems (ANS's). It begins with a general introduction to neural networks and connectionist approaches to information processing. The basis for learning in ANS's is then described, and compared with classical Machine learning. While similar in some ways, ANS learning deviates from tradition in its dependence on the modification of individual weights to bring about changes in a knowledge representation distributed across connections in a network. This unique form of learning is analyzed from two aspects: the selection of an appropriate network architecture for representing the problem, and the choice of a suitable learning rule capable of reproducing the desired function within the given network. The various network architectures are classified, and then identified with explicit restrictions on the types of functions they are capable of representing. The learning rules, i.e., algorithms that specify how the network weights are modified, are similarly taxonomized, and where possible, the limitations inherent to specific classes of rules are outlined.
Computers can create infinite lists of combinations to try to solve a particular problem, a process called "soft-computing." This process uses statistical comparables, neural networks, genetic algorithms, fuzzy variables in uncertain environments, and flexible machine learning to create a system which will allow spacecraft to increase robustness, and metric evaluation. These concepts will allow for the development of a spacecraft which will allow missions to be performed at lower costs.
The research goal is to study the formation in reduced gravity of high quality nanoparticulate of novel materials using plasma synthesis. Particular emphasis will be placed on the production of powders of non-oxide materials like diamond, SiC, SiN, c-BN, etc. The objective of the study is to investigate the effect of gravity on plasma synthesis of these materials, and to determine how the microgravity synthesis can improve the quality and yield of the nanoparticles. It is expected that the reduced gravity will aid in the understanding of the controlling mechanisms of plasma synthesis, and will increase the yield, and quality of the synthesized powder. These materials have properties of interest in several industrial applications, such as high temperature load bearings or high speed metal machining. Furthermore, because of the nano-meter size of the particulate produced in this process, they have specific application in the fabrication of MEMS based combustion systems, and in the development and growth of nano-systems and nano-structures of these materials. These are rapidly advancing research areas, and there is a great need for high quality nanoparticles of different materials. One of the primary systems of interest in the project will be gas-phase synthesis of nanopowder of non-oxide materials.
The authors propose a new approach to THz power generation: the nanoklystron. Utilizing silicon micromachining techniques, the design and fabrication concept of a monolithic THz vacuum-tube reflex-klystron source is described. The nanoklystron employs a separately fabricated cathode structure composed of densely packed carbon nanotube field emitters and an add-in repeller. The nanotube cathode is expected to increase the current density, extend the cathode life and decrease the required oscillation voltage to values below 100 V. The excitation cavity is based on ridged-waveguide and differs from the conventional cylindrical re-entrant structures found in lower frequency klystrons. A quasi-static field analysis of the cavity and output coupling structure show excellent control of the quality factor and desired field distribution. Output power is expected to occur through an iris coupled matched rectangular waveguide and integrated pyramidal feed horn. The entire circuit is designed so as to be formed monolithically from two thermocompression bonded silicon wafers processed using deep reactive ion etching (DRIE) techniques. To expedite prototyping, a 600 GHz mechanically machined structure has been designed and is in fabrication. A complete numeric analysis of the nanoklystron circuit, including the electron beam dynamics has just gotten underway. Separate evaluation of the nanotube cathodes is also ongoing. The authors will describe the progress to date as well as plans for the immediate implementation and testing of nanoklystron prototypes at 640 and 1250 GHz.
This paper provides a technical overview of Integrated System Health Engineering and Management (ISHEM). We define ISHEM as "the paper provides a techniques, and technologies used to design, analyze, build, verify, and operate a system to prevent faults and/or minimize their effects." This includes design and manufacturing techniques as well operational and managerial methods. ISHEM is not a "purely technical issue" as it also involves and must account for organizational, communicative, and cognitive f&ms of humans as social beings and as individuals. Thus the paper will discuss in more detail why all of these elements, h m the technical to the cognitive and social, are necessary to build dependable human-machine systems. The paper outlines a functional homework and architecture for ISHEM operations, describes the processes needed to implement ISHEM in the system life-cycle, and provides a theoretical framework to understand the relationship between the different aspects of the discipline. It then derives from these and the social and cognitive bases a set of design and operational principles for ISHEM.
A detailed knowledge of the formation of carbon-bearing molecules in interstellar ices and in the gas phase of the interstellar medium is of paramount interest to understand the astrochemical evolution of extraterrestrial environments (1). This research also holds strong implications to comprehend the chemical processing of Solar System environments such as icy planets and their moons together with the atmospheres of planets and their satellites (2). Since the present composition of each interstellar and Solar System environment reflects the matter from which it was formed and the processes which have changed the chemical nature since the origin (solar wind, planetary magnetospheres, cosmic ray exposure, photolysis, chemical reactions), a detailed investigation of the physicochemical mechanisms altering the pristine environment is of paramount importance to grasp the contemporary composition. Once these underlying processes have been unraveled, we can identify those molecules, which belonged to the nascent setting, distinguish molecular species synthesized in a later stage, and predict the imminent chemical evolution of, for instance, molecular clouds. Laboratory experiments under controlled physicochemical conditions (temperature, pressure, chemical composition, high energy components) present ideal tools for simulating the chemical evolution of interstellar and Solar System environments. Here, laboratory experiments can predict where and how (reaction mechanisms; chemicals necessary) in extraterrestrial environments and in the interstellar medium complex, carbon bearing molecules can be formed on interstellar grains and in the gas phase. This paper overviews the experimental setups utilized in our laboratory to mimic the chemical processing of gas phase and solid state (ices) environments. These are a crossed molecular beams machine (3) and a surface scattering setup (4). We also present typical results of each setup (formation of amino acids, aldehydes, epoxides; synthesis of hydrogen terminated carbon chains as precursors to complex PAHs and to carbonaceous dust grains in general; nitriles as precursor to amino acids).
It is now possible to fashion transparent crystalline materials into axisymmetric optical components having diameters ranging from hundreds down to tens of micrometers, whereas previously, the smallest attainable diameter was 500 m. A major step in the fabrication process that makes this possible can be characterized as diamond turning or computer numerically controlled machining on an ultrahigh-precision lathe.
Five metallurgical treatments have been tested as means of stabilizing mirrors that are made of aluminum alloy 6061 and are intended for use in cryogenic applications. Aluminum alloy 6061 is favored as a mirror material by many scientists and engineers. Like other alloys, it shrinks upon cool-down from room temperature to cryogenic temperature. This shrinkage degrades the optical quality of the mirror surfaces. Hence, the metallurgical treatments were tested to determine which one could be most effective in minimizing the adverse optical effects of cooldown to cryogenic temperatures. Each of the five metallurgical treatments comprises a multistep process, the steps of which are interspersed with the steps of the mirror-fabrication process. The five metallurgical-treatment/fabrication.- process combinations were compared with each other and with a benchmark fabrication process, in which a mirror is made from an alloy blank by (1) symmetrical rough machining, (2) finish machining to within 0.006 in. (. 0.15 mm) of final dimensions, and finally (3) diamond turning to a mirror finish.
A task overload condition often leads to high stress for an operator, causing performance degradation and possibly disastrous consequences. Just as dangerous, with automated flight systems, an operator may experience a task underload condition (during the en-route flight phase, for example), becoming easily bored and finding it difficult to maintain sustained attention. When an unexpected event occurs, either internal or external to the automated system, the disengaged operator may neglect, misunderstand, or respond slowly/inappropriately to the situation. In this paper, we discuss an approach for Operator Functional State (OFS) monitoring in a typical aviation environment. A systematic ground truth finding procedure has been designed based on subjective evaluations, performance measures, and strong physiological indicators. The derived OFS ground truth is continuous in time compared to a very sparse estimation of OFS based on an expert review or subjective evaluations. It can capture the variations of OFS during a mission to better guide through the training process of the OFS assessment model. Furthermore, an OFS assessment model framework based on advanced machine learning techniques was designed and the systematic approach was then verified and validated with experimental data collected in a high fidelity Boeing 737 simulator. Preliminary results show highly accurate engagement/disengagement detection making it suitable for real-time applications to assess pilot engagement.
A waterless clothes-cleaning machine has been developed that removes loose particulates and deodorizes dirty laundry with regenerative chemical processes to make the clothes more comfortable to wear and have a fresher smell. This system was initially developed for use in zero-g, but could be altered for 1-g environments where water or other re sources are scarce. Some of these processes include, but are not limited to, airflow, filtration, ozone generation, heat, ultraviolet light, and photocatalytic titanium oxide.
High Latitude Dust (HLD, ≥ 50°𝑁 𝑎𝑛𝑑 ≥ 40°𝑆 ) load has implications on the energy budget, ocean biodiversity and economy on a regional and global scale. Current methods of dust detection rely on spectral sensitivity at visible (RGB) and infrared wavelengths. The characteristics of HLD vary according to the sediments and sedimentary processes operating on the land surface that are the source of the dust particles. Leveraging machine learning (ML) methods, we propose a new detection method based on convolutional neural network (CNN) using true color images.
NASA is studying the next generation of space suit for safe operations in space, from the International Space Station to the lunar surface as part of the Exploration Extravehicular Mobility Unit project. The backplate structure of the portable life support system (PLSS) serves as the attachment point for assembly of the PLSS and contains embedded cooling channels. The thermal loop plumbing assembly and backplate are combined into a single component such that the fluid lines run through the midplane of the backplate. The manufacturing of the Ti-6Al-4V backplate consists of machining channels into a plate, welding cover plates on each channel using an electron beam, and additional machining for excess material removal and final detail. Careful control of the electron beam weld process is necessary to completely seal cover plates, produce consistent weld tracks, and produce channels with uniform cross sections free of debris and defects. The backplate contains multiple weld channels with unique geometries. The weld process parameters include choosing the beam current and focus, accelerating voltage, travel speed, pause times between weld tracks, and sequence of weld tracks. A transient finite element thermal analysis was developed to provide support for choosing and controlling the weld process parameters to maintain a consistent melt pool along each of the weld tracks. A moving distributed heat source is modeled to represent the heat input generated by the electron beam. The heat source model is a critical input to the analysis for accurate temperature predictions during the weld process. A modified conical heat source was developed to account for the change in working distance between the backplate and cover plates. The geometry of the material being welded must be accounted for by the heat source model to define the correct energy input. The weld process control is designed according to the predicted thermal history and melt pool dimensions for each of the weld channels. The analysis model, modified heat source, temperature and melt pool predictions, application of the thermal data to the weld parameters, and comparison with micrograph cross-sections from weld trials will be discussed in this presentation.