作者：
Cole, R.Brune, C.Physics Department
Learning Skills Center University of California Davis California 95616 Rodney W. Cole:is an Adjunct Lecturer for the Physics Department at the University of California
Davis and a Senior Learning Skills Counselor for the Learning Skills Center. He received his PhD from the University of Wyoming in 1978 and his BS from the University of Illinois in 1973. His research is in teaching physics methodology and computer animation of time domain solutions in electromagnetism. He has been involved with CAEME computer software development. He is a recipient of the UC Davis Instructional Technology Award and has participated in the Summer Computer Graphics Project at Lawrence Livermore National Laboratory. Curtis M. Brune:is a senior majoring in Physics at the University of California
Davis. He is a member of Phi Beta Kappa Phi Kappa Phi and Pi Mu Epsilon a national honorary mathematical society. Recently he has participated in the Instructional Technology Symposium at UC Davis. (Photo not available at this time.)
In this article we explore the role computing can play in an electromagnetics class. Our aim is not to provide answers, but to open a discussion on several topics related to the use of the computer as a learning aid. ...
In this article we explore the role computing can play in an electromagnetics class. Our aim is not to provide answers, but to open a discussion on several topics related to the use of the computer as a learning aid. We provide some examples of what we have done in an introductory electricity and magnetism class using a program called SilverHammer that maps electric and magnetic fields for point charges. However, the point of this article is not to say that this is the only way computers should be used, but rather to point out that we really have only scratched the surface of a very versatile tool. Those who are presently working in this area are the pioneers, and will see the use of the computer go from these first applications to being an indispensable medium for learning. The computer may well let us create virtual scenarios that allow us to explore ideas and relationships with a heretofore unattained proficiency.
作者：
CALVERT, TERODRIGUEZ, FASLEBZAK, JSThomas E. Calvert
P.E.: is a senior project engineer with the Propulsion and Auxiliary Systems Department David Taylor Research Center Annapolis Md. His interests include application of computers to all aspects of engineering with particular emphasis on utilization of small computers. Mr. Calvert is a licensed professional engineer in Maryland. He received a BSEE from Drexel University in 1969 and since that time has completed a number of graduate courses related to machinery acoustics. Francisco A. Rodriguez:is an engineer with the Propulsion and Auxiliary Systems Department
David Taylor Research Center. He was formerly with the Computer-Aided Design/Interactive Graphics Group of the Division of Engineering and Weapons U.S. Naval Academy. His interests include interfacing the computer aided design to the computer aided manufacturing along with related software and hardware development. Mr. Rodriguez received a BSEEfrom the University of Virginia in 1968. James S. Slebzak:is a mechanical engineering technician with the Propulsion and Auxiliary Systems Department
David Taylor Research Center. He received his machinists papers in 1971 after serving his apprenticeship at David Taylor Research Center. He continued his education and became the senior numerical control programmer at the Annapolis Laboratory. He completed his mechanical technology degree from Anne Arundel Community College in 1986. His interests are in the application of numerically controlled manufacturing techniques to prototype machinery components.
The machine shop at the Annapolis Laboratory of the David Taylor researchcenter (DTRC) provides model making and prototype support to a large variety of naval ship related engineering projects. In order to meet these...
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The machine shop at the Annapolis Laboratory of the David Taylor researchcenter (DTRC) provides model making and prototype support to a large variety of naval ship related engineering projects. In order to meet these challenging requirements, computer aided design/computer aided manufacturing (CAD/CAM) techniques are being used to produce “one of a kind” prototypes or very low volume production parts. The use of computer aides in these cases is to facilitate the accurate manufacture of a difficult part, rather than to improve manufacturing efficiencies. In addition, the approach provides the flexibility required to support research and development projects. Several examples of prototype shipboard components manufactured using CAD/CAM techniques are presented in this paper. The hardware and software that facilitated these projects are discussed. The examples described have met the requirements to produce a wide variety of prototype shipboard machinery components quickly and accurately.
作者：
WAGNER, PVAIL, JAPaul Wagner:was born in Vancouver
Canada in 1941 and after engineering studies at Ryerson Polytechnical Institute and the University of British Columbia received a diploma of mechanical technology and completed a Prakticant engineering course with Mannesmann in West Germany. On graduation he joined the firm of Wagner Engineering Ltd. in 1965 and after 10 years of design and manufacturing responsiblity was advanced to vice president of sales. Present responsibilities include management of research and development projects evaluation of new products and marketing. Mr. Wagner is a member of the Society of Naval Architects and Marine Engineers and the Canadian Institute of Marine Engineers. Jeannine A. Vail:is a graduate of the University of Pittsburgh and Wheeling College where she earned M. S. and B. S. degrees in mathematics. She is currently the president of Vail Research and Technology Corporation. Her experience includes 14 years in reliability
maintainability and availability (RMA) engineering software development and cost analysis in the Naval Sea Systems Command the Naval Surface Weapons Center and industry. She developed RMA requirements and performed simulations on a wide variety of naval ships and underwater weapons. Ms. Vail is a member of ASNE IEEE and the Society of Reliability Engineers.
Ships' steering systems have progressed over the ages, driven by the need for more powerful and reliable systems. From simple mechanical devices thousands of years old to the latest electro-hydraulic systems, prog...
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Ships' steering systems have progressed over the ages, driven by the need for more powerful and reliable systems. From simple mechanical devices thousands of years old to the latest electro-hydraulic systems, progress has been relatively slow but constant. Present systems tend to be the result of a series of modifications of older designs in response to a need for increased performance and reliability. This paper decribes the historical development leading to present designs and discusses a new approach which not only eliminates most problems inherent in present designs but also provides a more economical, more compact, and more cost effective solution as verified by detailed reliability and maintainability analysis.
An expert system is described which allows real-time analysis of the noise and vibration signature of vibrating machinery. The system presented consists of an adaptive algorithm which varies the band width of analysis...
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An expert system is described which allows real-time analysis of the noise and vibration signature of vibrating machinery. The system presented consists of an adaptive algorithm which varies the band width of analysis channels as a function of a signal complexity factor and a measure of the rapidity of local signal change. Overall program architecture is presented as well as detailed discussion of signature functional identification and statistical trend modules which are adaptable to a wide variety of input data base configurations. Execution of the program on a “super-mini” in FORTRAN code with direct graphics output and on 68000 series based firmware using ADA is discussed. Results are presented of program execution on Navy hydrophone and propulsion gas turbine data showing current signature and projections of trend to future times compared with failed condition signatures. Correlation results for such predictions are also discussed.
Connected Autonomous Vehicle (CAV) Driving, as a data-driven intelligent driving technology within the Internet of Vehicles (IoV), presents significant challenges to the efficiency and security of real-time data manag...
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Connected Autonomous Vehicle (CAV) Driving, as a data-driven intelligent driving technology within the Internet of Vehicles (IoV), presents significant challenges to the efficiency and security of real-time data management. The combination of web3.0 and edge content caching holds promise in providing low-latency data access for CAVs’ real-time applications. web3.0 enables the reliable pre-migration of frequently requested content from content providers to edge nodes. However, identifying optimal edge node peers for joint content caching and replacement remains challenging due to the dynamic nature of traffic flow in IoV. Addressing these challenges, this article introduces GAMA-Cache, an innovative edge content caching methodology leveraging Graph Attention Networks (GAT) and Multi-Agent Reinforcement Learning (MARL). GAMA-Cache conceptualizes the cooperative edge content caching issue as a constrained Markov decision process. It employs a MARL technique predicated on cooperation effectiveness to discern optimal caching decisions, with GAT augmenting information extracted from adjacent nodes. A distinct collaborator selection mechanism is also developed to streamline communication between agents, filtering out those with minimal correlations in the vector input to the policy network. Experimental results demonstrate that, in terms of service latency and delivery failure, the GAMA-Cache outperforms other state-of-the-art MARL solutions for edge content caching in IoV.
One of the main challenges for underwater applications, such as environmental monitoring and disaster management, is achieving efficient data transmission in environments where conditions change rapidly, and resources...
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One of the main challenges for underwater applications, such as environmental monitoring and disaster management, is achieving efficient data transmission in environments where conditions change rapidly, and resources need for data transport are scarce. The capability of evaluating the Value of information (VoI) enables us to assess these problems by proposing a Value of Information-based Situation-Aware Non-Linear Routing (VoI SANLR/VoI SANL) method. It aims to deal with critical event scenarios using BDI (Belief-Desire-Intention) logic criteria and prioritizing the timely uploading of data-driven information towards the destination. SANLR of VoI is developed to reduce energy consumption, end-to-end latency, jitter, and improve Packet Delivery Ratio (PDR) in underwater communication networks. VoI SANLR introduces principles of priority-based methods and intends to address challenges in terms of underwater environment such as varying channel conditions, lack energy resources, and real-time decision requirements by using SANLR. Energy optimization analysis reveals consistent outperformance, achieving a remarkable 95% reduction in energy consumption compared to other techniques. Low latency is maintained, ranging from 2.5 to 0.5 seconds, showcasing enhanced efficiency and scalability. VoI SANLR demonstrates exceptional performance in both throughput and jitter. It achieves the highest data transfer rates, ranging from 100 kbps to 110 kbps, indicating outstanding efficiency. Additionally, the jitter remains consistently low, between 1.8 ms and 2 ms, ensuring minimal delay variability and improved communication stability. PDR consistently surpasses other techniques, reaching a maximum of 99%. Additionally, network lifetime analysis demonstrates VoI SANLR's superiority, exhibiting the highest network lifetime at each node and a significant 31.25% improvement at Node 100 compared to other methods.
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