Current problems in the dynamics and design of mechanisms and machines

NASA Astrophysics Data System (ADS)

Kestel'Man, V. N.

The papers contained in this volume deal with possible ways of improving the dynamic and structural properties of machines and mechanisms and also with problems associated with the design of aircraft equipment. Topics discussed include estimation of the stressed state of a model of an orbital film structure, a study of the operation of an aerodynamic angle transducer in flow of a hot gas, calculation of the efficiency of aircraft gear drives, and dynamic accuracy of a controlled manipulator. Papers are also presented on optimal synthesis of mechanical systems with variable properties, synthesis of mechanisms using initial kinematic chains, and using shape memory materials in the design of machines and mechanisms. (For individual items see A93-31202 to A93-31214)

Designing Contestability: Interaction Design, Machine Learning, and Mental Health

PubMed Central

Hirsch, Tad; Merced, Kritzia; Narayanan, Shrikanth; Imel, Zac E.; Atkins, David C.

2017-01-01

We describe the design of an automated assessment and training tool for psychotherapists to illustrate challenges with creating interactive machine learning (ML) systems, particularly in contexts where human life, livelihood, and wellbeing are at stake. We explore how existing theories of interaction design and machine learning apply to the psychotherapy context, and identify “contestability” as a new principle for designing systems that evaluate human behavior. Finally, we offer several strategies for making ML systems more accountable to human actors. PMID:28890949

A New Type of Tea Baking Machine Based on Pro/E Design

NASA Astrophysics Data System (ADS)

Lin, Xin-Ying; Wang, Wei

2017-11-01

In this paper, the production process of wulong tea was discussed, mainly the effect of baking on the quality of tea. The suitable baking temperature of different tea was introduced. Based on Pro/E, a new type of baking machine suitable for wulong tea baking was designed. The working principle, mechanical structure and constant temperature timing intelligent control system of baking machine were expounded. Finally, the characteristics and innovation of new baking machine were discussed.The mechanical structure of this baking machine is more simple and reasonable, and can use the heat of the inlet and outlet, more energy saving and environmental protection. The temperature control part adopts fuzzy PID control, which can improve the accuracy and response speed of temperature control and reduce the dependence of baking operation on skilled experience.

Structure design of lower limb exoskeletons for gait training

NASA Astrophysics Data System (ADS)

Li, Jianfeng; Zhang, Ziqiang; Tao, Chunjing; Ji, Run

2015-09-01

Due to the close physical interaction between human and machine in process of gait training, lower limb exoskeletons should be safe, comfortable and able to smoothly transfer desired driving force/moments to the patients. Correlatively, in kinematics the exoskeletons are required to be compatible with human lower limbs and thereby to avoid the uncontrollable interactional loads at the human-machine interfaces. Such requirement makes the structure design of exoskeletons very difficult because the human-machine closed chains are complicated. In addition, both the axis misalignments and the kinematic character difference between the exoskeleton and human joints should be taken into account. By analyzing the DOF(degree of freedom) of the whole human-machine closed chain, the human-machine kinematic incompatibility of lower limb exoskeletons is studied. An effective method for the structure design of lower limb exoskeletons, which are kinematically compatible with human lower limb, is proposed. Applying this method, the structure synthesis of the lower limb exoskeletons containing only one-DOF revolute and prismatic joints is investigated; the feasible basic structures of exoskeletons are developed and classified into three different categories. With the consideration of quasi-anthropopathic feature, structural simplicity and wearable comfort of lower limb exoskeletons, a joint replacement and structure comparison based approach to select the ideal structures of lower limb exoskeletons is proposed, by which three optimal exoskeleton structures are obtained. This paper indicates that the human-machine closed chain formed by the exoskeleton and human lower limb should be an even-constrained kinematic system in order to avoid the uncontrollable human-machine interactional loads. The presented method for the structure design of lower limb exoskeletons is universal and simple, and hence can be applied to other kinds of wearable exoskeletons.

Design Methodology for Automated Construction Machines

DTIC Science & Technology

1987-12-11

along with the design of a pair of machines which automate framework installation.-,, 20. DISTRIBUTION IAVAILABILITY OF ABSTRACT 21. ABSTRACT SECURITY... Development Assistant Professor of Civil Engineering and Laura A . Demsetz, David H. Levy, Bruce Schena Graduate Research Assistants December 11, 1987 U.S...are discussed along with the design of a pair of machines which automate framework installation. Preliminary analysis and testing indicate that these

Design of electric control system for automatic vegetable bundling machine

NASA Astrophysics Data System (ADS)

Bao, Yan

2017-06-01

A design can meet the requirements of automatic bale food structure and has the advantages of simple circuit, and the volume is easy to enhance the electric control system of machine carrying bunch of dishes and low cost. The bundle of vegetable machine should meet the sensor to detect and control, in order to meet the control requirements; binding force can be adjusted by the button to achieve; strapping speed also can be adjusted, by the keys to set; sensors and mechanical line connection, convenient operation; can be directly connected with the plug, the 220V power supply can be connected to a power source; if, can work, by the transmission signal sensor, MCU to control the motor, drive and control procedures for small motor. The working principle of LED control circuit and temperature control circuit is described. The design of electric control system of automatic dish machine.

Technological and economical analysis of salient pole and permanent magnet synchronous machines designed for wind turbines

NASA Astrophysics Data System (ADS)

Gündoğdu, Tayfun; Kömürgöz, Güven

2012-08-01

Chinese export restrictions already reduced the planning reliability for investments in permanent magnet wind turbines. Today the production of permanent magnets consumes the largest proportion of rare earth elements, with 40% of the rare earth-based magnets used for generators and other electrical machines. The cost and availability of NdFeB magnets will likely determine the production rate of permanent magnet generators. The high volatility of rare earth metals makes it very difficult to quote a price. Prices may also vary from supplier to supplier to an extent of up to 50% for the same size, shape and quantity with a minor difference in quality. The paper presents the analysis and the comparison of salient pole with field winding and of peripheral winding synchronous electrical machines, presenting important advantages. A neodymium alloy magnet rotor structure has been considered and compared to the salient rotor case. The Salient Pole Synchronous Machine and the Permanent Magnet Synchronous Machine were designed so that the plate values remain constant. The Eddy current effect on the windings is taken into account during the design, and the efficiency, output power and the air-gap flux density obtained after the simulation were compared. The analysis results clearly indicate that Salient Pole Synchronous Machine designs would be attractive to wind power companies. Furthermore, the importance of the design of electrical machines and the determination of criteria are emphasized. This paper will be a helpful resource in terms of examination and comparison of the basic structure and magnetic features of the Salient Pole Synchronous Machine and Permanent Magnet Synchronous Machine. Furthermore, an economic analysis of the designed machines was conducted.

Man-Machine Integrated Design and Analysis System (MIDAS): Functional Overview

NASA Technical Reports Server (NTRS)

Corker, Kevin; Neukom, Christian

1998-01-01

Included in the series of screen print-outs illustrates the structure and function of the Man-Machine Integrated Design and Analysis System (MIDAS). Views into the use of the system and editors are featured. The use-case in this set of graphs includes the development of a simulation scenario.

Ontological modelling of knowledge management for human-machine integrated design of ultra-precision grinding machine

NASA Astrophysics Data System (ADS)

Hong, Haibo; Yin, Yuehong; Chen, Xing

2016-11-01

Despite the rapid development of computer science and information technology, an efficient human-machine integrated enterprise information system for designing complex mechatronic products is still not fully accomplished, partly because of the inharmonious communication among collaborators. Therefore, one challenge in human-machine integration is how to establish an appropriate knowledge management (KM) model to support integration and sharing of heterogeneous product knowledge. Aiming at the diversity of design knowledge, this article proposes an ontology-based model to reach an unambiguous and normative representation of knowledge. First, an ontology-based human-machine integrated design framework is described, then corresponding ontologies and sub-ontologies are established according to different purposes and scopes. Second, a similarity calculation-based ontology integration method composed of ontology mapping and ontology merging is introduced. The ontology searching-based knowledge sharing method is then developed. Finally, a case of human-machine integrated design of a large ultra-precision grinding machine is used to demonstrate the effectiveness of the method.

A Boltzmann machine for the organization of intelligent machines

NASA Technical Reports Server (NTRS)

Moed, Michael C.; Saridis, George N.

1989-01-01

In the present technological society, there is a major need to build machines that would execute intelligent tasks operating in uncertain environments with minimum interaction with a human operator. Although some designers have built smart robots, utilizing heuristic ideas, there is no systematic approach to design such machines in an engineering manner. Recently, cross-disciplinary research from the fields of computers, systems AI and information theory has served to set the foundations of the emerging area of the design of intelligent machines. Since 1977 Saridis has been developing an approach, defined as Hierarchical Intelligent Control, designed to organize, coordinate and execute anthropomorphic tasks by a machine with minimum interaction with a human operator. This approach utilizes analytical (probabilistic) models to describe and control the various functions of the intelligent machine structured by the intuitively defined principle of Increasing Precision with Decreasing Intelligence (IPDI) (Saridis 1979). This principle, even though resembles the managerial structure of organizational systems (Levis 1988), has been derived on an analytic basis by Saridis (1988). The purpose is to derive analytically a Boltzmann machine suitable for optimal connection of nodes in a neural net (Fahlman, Hinton, Sejnowski, 1985). Then this machine will serve to search for the optimal design of the organization level of an intelligent machine. In order to accomplish this, some mathematical theory of the intelligent machines will be first outlined. Then some definitions of the variables associated with the principle, like machine intelligence, machine knowledge, and precision will be made (Saridis, Valavanis 1988). Then a procedure to establish the Boltzmann machine on an analytic basis will be presented and illustrated by an example in designing the organization level of an Intelligent Machine. A new search technique, the Modified Genetic Algorithm, is presented and proved

Chapter 9: The FTU Machine - Design Construction and Assembly

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pizzuto, A.; Annino, C.; Baldarelli, M.

2004-05-15

The main design features and guidelines for the construction of the 8-T cryogenically cooled Frascati Tokamak Upgrade (FTU) are presented. The main features include the very compact toroidal magnets based on the concept of the 'Bitter' type of coil with wedge-shaped turns, utilized for the first time for the Alcator A and C magnets, and the original configuration of the vacuum vessel (VV) structure, which is fully welded in order to achieve the required high strength and electric resistivity. The present toroidal limiter has been installed following several years of operation, and this installation has required the development of specificmore » remote-handling tools. The toroidal limiter consists of 12 independent sectors made of stainless steel carriers and molybdenum alloy (TZM) tiles. The main fabrication processes developed for the toroidal and poloidal coils as well as for the VV are described. It is to be noted that the assembly procedure has required very accurate machining of all the structures requiring several trials and steps. The machine has shown no problem in operating routinely at its maximum design values (8 T, 1.6 MA)« less

Design and Fabrication of Automatic Glass Cutting Machine

NASA Astrophysics Data System (ADS)

Veena, T. R.; Kadadevaramath, R. S.; Nagaraj, P. M.; Madhusudhan, S. V.

2016-09-01

This paper deals with the design and fabrication of the automatic glass or mirror cutting machine. In order to increase the accuracy of cut and production rate; and decrease the production time and accidents caused due to manual cutting of mirror or glass, this project aims at development of an automatic machine which uses a programmable logic controller (PLC) for controlling the movement of the conveyer and also to control the pneumatic circuit. In this machine, the work of the operator is to load and unload the mirror. The cutter used in this machine is carbide wheel with its cutting edge ground to a V-shaped profile. The PLC controls the pneumatic cylinder and intern actuates the cutter along the glass, a fracture layer is formed causing a mark to be formed below the fracture layer and a crack to be formed below the rib mark. The machine elements are designed using CATIA V5R20 and pneumatic circuit are designed using FESTO FLUID SIM software.

Automated Tape Laying Machine for Composite Structures.

DTIC Science & Technology

The invention comprises an automated tape laying machine, for laying tape on a composite structure. The tape laying machine has a tape laying head...neatly cut. The automated tape laying device utilizes narrow width tape to increase machine flexibility and reduce wastage.

Analysis and design of asymmetrical reluctance machine

NASA Astrophysics Data System (ADS)

Harianto, Cahya A.

Over the past few decades the induction machine has been chosen for many applications due to its structural simplicity and low manufacturing cost. However, modest torque density and control challenges have motivated researchers to find alternative machines. The permanent magnet synchronous machine has been viewed as one of the alternatives because it features higher torque density for a given loss than the induction machine. However, the assembly and permanent magnet material cost, along with safety under fault conditions, have been concerns for this class of machine. An alternative machine type, namely the asymmetrical reluctance machine, is proposed in this work. Since the proposed machine is of the reluctance machine type, it possesses desirable feature, such as near absence of rotor losses, low assembly cost, low no-load rotational losses, modest torque ripple, and rather benign fault conditions. Through theoretical analysis performed herein, it is shown that this machine has a higher torque density for a given loss than typical reluctance machines, although not as high as the permanent magnet machines. Thus, the asymmetrical reluctance machine is a viable and advantageous machine alternative where the use of permanent magnet machines are undesirable.

Design Control Systems of Human Machine Interface in the NTVS-2894 Seat Grinder Machine to Increase the Productivity

NASA Astrophysics Data System (ADS)

Ardi, S.; Ardyansyah, D.

2018-02-01

In the Manufacturing of automotive spare parts, increased sales of vehicles is resulted in increased demand for production of engine valve of the customer. To meet customer demand, we carry out improvement and overhaul of the NTVS-2894 seat grinder machine on a machining line. NTVS-2894 seat grinder machine has been decreased machine productivity, the amount of trouble, and the amount of downtime. To overcome these problems on overhaul the NTVS-2984 seat grinder machine include mechanical and programs, is to do the design and manufacture of HMI (Human Machine Interface) GP-4501T program. Because of the time prior to the overhaul, NTVS-2894 seat grinder machine does not have a backup HMI (Human Machine Interface) program. The goal of the design and manufacture in this program is to improve the achievement of production, and allows an operator to operate beside it easier to troubleshoot the NTVS-2894 seat grinder machine thereby reducing downtime on the NTVS-2894 seat grinder machine. The results after the design are HMI program successfully made it back, machine productivity increased by 34.8%, the amount of trouble, and downtime decreased 40% decrease from 3,160 minutes to 1,700 minutes. The implication of our design, it could facilitate the operator in operating machine and the technician easer to maintain and do the troubleshooting the machine problems.

Design and market considerations for axial flux superconducting electric machine design

NASA Astrophysics Data System (ADS)

Ainslie, M. D.; George, A.; Shaw, R.; Dawson, L.; Winfield, A.; Steketee, M.; Stockley, S.

2014-05-01

In this paper, the authors investigate a number of design and market considerations for an axial flux superconducting electric machine design that uses high temperature superconductors. The axial flux machine design is assumed to utilise high temperature superconductors in both wire (stator winding) and bulk (rotor field) forms, to operate over a temperature range of 65-77 K, and to have a power output in the range from 10s of kW up to 1 MW (typical for axial flux machines), with approximately 2-3 T as the peak trapped field in the bulk superconductors. The authors firstly investigate the applicability of this type of machine as a generator in small- and medium-sized wind turbines, including the current and forecasted market and pricing for conventional turbines. Next, a study is also carried out on the machine's applicability as an in-wheel hub motor for electric vehicles. Some recommendations for future applications are made based on the outcome of these two studies. Finally, the cost of YBCO-based superconducting (2G HTS) wire is analysed with respect to competing wire technologies and compared with current conventional material costs and current wire costs for both 1G and 2G HTS are still too great to be economically feasible for such superconducting devices.

Design of a hydraulic bending machine

Treesearch

Steven G. Hankel; Marshall Begel

2004-01-01

To keep pace with customer demands while phasing out old and unserviceable test equipment, the staff of the Engineering Mechanics Laboratory (EML) at the USDA Forest Service, Forest Products Laboratory, designed and assembled a hydraulic bending test machine. The EML built this machine to test dimension lumber, nominal 2 in. thick and up to 12 in. deep, at spans up to...

Visualization tool for human-machine interface designers

NASA Astrophysics Data System (ADS)

Prevost, Michael P.; Banda, Carolyn P.

1991-06-01

As modern human-machine systems continue to grow in capabilities and complexity, system operators are faced with integrating and managing increased quantities of information. Since many information components are highly related to each other, optimizing the spatial and temporal aspects of presenting information to the operator has become a formidable task for the human-machine interface (HMI) designer. The authors describe a tool in an early stage of development, the Information Source Layout Editor (ISLE). This tool is to be used for information presentation design and analysis; it uses human factors guidelines to assist the HMI designer in the spatial layout of the information required by machine operators to perform their tasks effectively. These human factors guidelines address such areas as the functional and physical relatedness of information sources. By representing these relationships with metaphors such as spring tension, attractors, and repellers, the tool can help designers visualize the complex constraint space and interacting effects of moving displays to various alternate locations. The tool contains techniques for visualizing the relative 'goodness' of a configuration, as well as mechanisms such as optimization vectors to provide guidance toward a more optimal design. Also available is a rule-based design checker to determine compliance with selected human factors guidelines.

Design principles of hair-like structures as biological machines

PubMed Central

2018-01-01

Hair-like structures are prevalent throughout biology and frequently act to sense or alter interactions with an organism's environment. The overall shape of a hair is simple: a long, filamentous object that protrudes from the surface of an organism. This basic design, however, can confer a wide range of functions, owing largely to the flexibility and large surface area that it usually possesses. From this simple structural basis, small changes in geometry, such as diameter, curvature and inter-hair spacing, can have considerable effects on mechanical properties, allowing functions such as mechanosensing, attachment, movement and protection. Here, we explore how passive features of hair-like structures, both individually and within arrays, enable diverse functions across biology. Understanding the relationships between form and function can provide biologists with an appreciation for the constraints and possibilities on hair-like structures. Additionally, such structures have already been used in biomimetic engineering with applications in sensing, water capture and adhesion. By examining hairs as a functional mechanical unit, geometry and arrangement can be rationally designed to generate new engineering devices and ideas. PMID:29848593

Analytical Model-Based Design Optimization of a Transverse Flux Machine

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hasan, Iftekhar; Husain, Tausif; Sozer, Yilmaz

This paper proposes an analytical machine design tool using magnetic equivalent circuit (MEC)-based particle swarm optimization (PSO) for a double-sided, flux-concentrating transverse flux machine (TFM). The magnetic equivalent circuit method is applied to analytically establish the relationship between the design objective and the input variables of prospective TFM designs. This is computationally less intensive and more time efficient than finite element solvers. A PSO algorithm is then used to design a machine with the highest torque density within the specified power range along with some geometric design constraints. The stator pole length, magnet length, and rotor thickness are the variablesmore » that define the optimization search space. Finite element analysis (FEA) was carried out to verify the performance of the MEC-PSO optimized machine. The proposed analytical design tool helps save computation time by at least 50% when compared to commercial FEA-based optimization programs, with results found to be in agreement with less than 5% error.« less

Graphite fiber reinforced structure for supporting machine tools

DOEpatents

Knight, Jr., Charles E.; Kovach, Louis; Hurst, John S.

1978-01-01

Machine tools utilized in precision machine operations require tool support structures which exhibit minimal deflection, thermal expansion and vibration characteristics. The tool support structure of the present invention is a graphite fiber reinforced composite in which layers of the graphite fibers or yarn are disposed in a 0/90.degree. pattern and bonded together with an epoxy resin. The finished composite possesses a low coefficient of thermal expansion and a substantially greater elastic modulus, stiffness-to-weight ratio, and damping factor than a conventional steel tool support utilized in similar machining operations.

Design of apochromatic lens with large field and high definition for machine vision.

PubMed

Yang, Ao; Gao, Xingyu; Li, Mingfeng

2016-08-01

Precise machine vision detection for a large object at a finite working distance (WD) requires that the lens has a high resolution for a large field of view (FOV). In this case, the effect of a secondary spectrum on image quality is not negligible. According to the detection requirements, a high resolution apochromatic objective is designed and analyzed. The initial optical structure (IOS) is combined with three segments. Next, the secondary spectrum of the IOS is corrected by replacing glasses using the dispersion vector analysis method based on the Buchdahl dispersion equation. Other aberrations are optimized by the commercial optical design software ZEMAX by properly choosing the optimization function operands. The optimized optical structure (OOS) has an f-number (F/#) of 3.08, a FOV of φ60  mm, a WD of 240 mm, and a modulated transfer function (MTF) of all fields of more than 0.1 at 320  cycles/mm. The design requirements for a nonfluorite material apochromatic objective lens with a large field and high definition for machine vision detection have been achieved.

Machine-Learning Approach for Design of Nanomagnetic-Based Antennas

NASA Astrophysics Data System (ADS)

Gianfagna, Carmine; Yu, Huan; Swaminathan, Madhavan; Pulugurtha, Raj; Tummala, Rao; Antonini, Giulio

2017-08-01

We propose a machine-learning approach for design of planar inverted-F antennas with a magneto-dielectric nanocomposite substrate. It is shown that machine-learning techniques can be efficiently used to characterize nanomagnetic-based antennas by accurately mapping the particle radius and volume fraction of the nanomagnetic material to antenna parameters such as gain, bandwidth, radiation efficiency, and resonant frequency. A modified mixing rule model is also presented. In addition, the inverse problem is addressed through machine learning as well, where given the antenna parameters, the corresponding design space of possible material parameters is identified.

Statistical Machine Learning for Structured and High Dimensional Data

DTIC Science & Technology

2014-09-17

AFRL-OSR-VA-TR-2014-0234 STATISTICAL MACHINE LEARNING FOR STRUCTURED AND HIGH DIMENSIONAL DATA Larry Wasserman CARNEGIE MELLON UNIVERSITY Final...Re . 8-98) v Prescribed by ANSI Std. Z39.18 14-06-2014 Final Dec 2009 - Aug 2014 Statistical Machine Learning for Structured and High Dimensional...area of resource-constrained statistical estimation. machine learning , high-dimensional statistics U U U UU John Lafferty 773-702-3813 > Research under

Crystalline molecular machines: Encoding supramolecular dynamics into molecular structure

PubMed Central

Garcia-Garibay, Miguel A.

2005-01-01

Crystalline molecular machines represent an exciting new branch of crystal engineering and materials science with important implications to nanotechnology. Crystalline molecular machines are crystals built with molecules that are structurally programmed to respond collectively to mechanic, electric, magnetic, or photonic stimuli to fulfill specific functions. One of the main challenges in their construction derives from the picometric precision required for their mechanic operation within the close-packed, self-assembled environment of crystalline solids. In this article, we outline some of the general guidelines for their design and apply them for the construction of molecular crystals with units intended to emulate macroscopic gyroscopes and compasses. Recent advances in the preparation, crystallization, and dynamic characterization of these interesting systems offer a foothold to the possibilities and help highlight some avenues for future experimentation. PMID:16046543

Design Comparison of Inner and Outer Rotor of Permanent Magnet Flux Switching Machine for Electric Bicycle Application

NASA Astrophysics Data System (ADS)

Jusoh, L. I.; Sulaiman, E.; Bahrim, F. S.; Kumar, R.

2017-08-01

Recent advancements have led to the development of flux switching machines (FSMs) with flux sources within the stators. The advantage of being a single-piece machine with a robust rotor structure makes FSM an excellent choice for speed applications. There are three categories of FSM, namely, the permanent magnet (PM) FSM, the field excitation (FE) FSM, and the hybrid excitation (HE) FSM. The PMFSM and the FEFSM have their respective PM and field excitation coil (FEC) as their key flux sources. Meanwhile, as the name suggests, the HEFSM has a combination of PM and FECs as the flux sources. The PMFSM is a simple and cheap machine, and it has the ability to control variable flux, which would be suitable for an electric bicycle. Thus, this paper will present a design comparison between an inner rotor and an outer rotor for a single-phase permanent magnet flux switching machine with 8S-10P, designed specifically for an electric bicycle. The performance of this machine was validated using the 2D- FEA. As conclusion, the outer-rotor has much higher torque approximately at 54.2% of an innerrotor PMFSM. From the comprehensive analysis of both designs it can be conclude that output performance is lower than the SRM and IPMSM design machine. But, it shows that the possibility to increase the design performance by using “deterministic optimization method”.

Design and analysis of linear fault-tolerant permanent-magnet vernier machines.

PubMed

Xu, Liang; Ji, Jinghua; Liu, Guohai; Du, Yi; Liu, Hu

2014-01-01

This paper proposes a new linear fault-tolerant permanent-magnet (PM) vernier (LFTPMV) machine, which can offer high thrust by using the magnetic gear effect. Both PMs and windings of the proposed machine are on short mover, while the long stator is only manufactured from iron. Hence, the proposed machine is very suitable for long stroke system applications. The key of this machine is that the magnetizer splits the two movers with modular and complementary structures. Hence, the proposed machine offers improved symmetrical and sinusoidal back electromotive force waveform and reduced detent force. Furthermore, owing to the complementary structure, the proposed machine possesses favorable fault-tolerant capability, namely, independent phases. In particular, differing from the existing fault-tolerant machines, the proposed machine offers fault tolerance without sacrificing thrust density. This is because neither fault-tolerant teeth nor the flux-barriers are adopted. The electromagnetic characteristics of the proposed machine are analyzed using the time-stepping finite-element method, which verifies the effectiveness of the theoretical analysis.

Structural design of the Sandia 34-M Vertical Axis Wind Turbine

NASA Astrophysics Data System (ADS)

Berg, D. E.

Sandia National Laboratories, as the lead DOE laboratory for Vertical Axis Wind Turbine (VAWT) development, is currently designing a 34-meter diameter Darrieus-type VAWT. This turbine will be a research test bed which provides a focus for advancing technology and validating design and fabrication techniques in a size range suitable for utility use. Structural data from this machine will allow structural modeling to be refined and verified for a turbine on which the gravity effects and stochastic wind loading are significant. Performance data from it will allow aerodynamic modeling to be refined and verified. The design effort incorporates Sandia's state-of-the-art analysis tools in the design of a complete machine. The analytic tools used in this design are discussed and the conceptual design procedure is described.

Rational design of the column of a heavy multipurpose machining center

NASA Astrophysics Data System (ADS)

Atapin, V. V.; Kurlaev, N. V.

2016-04-01

The main purpose in the design of supporting constructions of heavy multipurpose machining center is the reduction of mass at the given precision and productivity of machining. Accomplish these ends the technology of rational design of supporting constructions is offered. This technology is based on the decomposition method and the finite elements method in the combination with optimization methods. The technology has four stages: 1) calculation of external forces and loads, 2) as a result the boundary conditions (force, kinematics) for individual supporting constructions are formed, 3) a problem about final optimal distribution of a material by the individual supporting constructions with the real cross-section is solved; 4) dynamic analysis. By the example of design of the column of a heavy multipurpose machining center the main stages of rational design of the individual supporting constructions are shown. At a design stage of the carrying system consisting of load-bearing structures with simplified geometry, optimum overall dimensions of the column are identified. For the admitted system of preferences, it is necessary to accept the fact that the carrying system with the column with the sizes of cross section of 1.8 m (along x axis) and 2.6 m (along y axis) is the best. The analysis of the work of the column under the torsion condition with the use of method of mechanics shows that the column with square cross sections = 2.46·2.46 m which rigidity on torsion is 26 % higher in comparison with a production version is the best. The results of calculation show that a production-release design of the column with longitudinal and transverse edges of rigidity is 24 % heavier than the column with the edges located on a diagonally at equal rigidity.

Design and Analysis of Linear Fault-Tolerant Permanent-Magnet Vernier Machines

PubMed Central

Xu, Liang; Liu, Guohai; Du, Yi; Liu, Hu

2014-01-01

This paper proposes a new linear fault-tolerant permanent-magnet (PM) vernier (LFTPMV) machine, which can offer high thrust by using the magnetic gear effect. Both PMs and windings of the proposed machine are on short mover, while the long stator is only manufactured from iron. Hence, the proposed machine is very suitable for long stroke system applications. The key of this machine is that the magnetizer splits the two movers with modular and complementary structures. Hence, the proposed machine offers improved symmetrical and sinusoidal back electromotive force waveform and reduced detent force. Furthermore, owing to the complementary structure, the proposed machine possesses favorable fault-tolerant capability, namely, independent phases. In particular, differing from the existing fault-tolerant machines, the proposed machine offers fault tolerance without sacrificing thrust density. This is because neither fault-tolerant teeth nor the flux-barriers are adopted. The electromagnetic characteristics of the proposed machine are analyzed using the time-stepping finite-element method, which verifies the effectiveness of the theoretical analysis. PMID:24982959

Parallel machine architecture and compiler design facilities

NASA Technical Reports Server (NTRS)

Kuck, David J.; Yew, Pen-Chung; Padua, David; Sameh, Ahmed; Veidenbaum, Alex

1990-01-01

The objective is to provide an integrated simulation environment for studying and evaluating various issues in designing parallel systems, including machine architectures, parallelizing compiler techniques, and parallel algorithms. The status of Delta project (which objective is to provide a facility to allow rapid prototyping of parallelized compilers that can target toward different machine architectures) is summarized. Included are the surveys of the program manipulation tools developed, the environmental software supporting Delta, and the compiler research projects in which Delta has played a role.

Human machine interface display design document.

DOT National Transportation Integrated Search

2008-01-01

The purpose of this document is to describe the design for the human machine interface : (HMI) display for the Next Generation 9-1-1 (NG9-1-1) System (or system of systems) : based on the initial Tier 1 requirements identified for the NG9-1-1 S...

Army-NASA aircrew/aircraft integration program: Phase 4 A(3)I Man-Machine Integration Design and Analysis System (MIDAS) software detailed design document

NASA Technical Reports Server (NTRS)

Banda, Carolyn; Bushnell, David; Chen, Scott; Chiu, Alex; Constantine, Betsy; Murray, Jerry; Neukom, Christian; Prevost, Michael; Shankar, Renuka; Staveland, Lowell

1991-01-01

The Man-Machine Integration Design and Analysis System (MIDAS) is an integrated suite of software components that constitutes a prototype workstation to aid designers in applying human factors principles to the design of complex human-machine systems. MIDAS is intended to be used at the very early stages of conceptual design to provide an environment wherein designers can use computational representations of the crew station and operator, instead of hardware simulators and man-in-the-loop studies, to discover problems and ask 'what if' questions regarding the projected mission, equipment, and environment. This document is the Software Product Specification for MIDAS. Introductory descriptions of the processing requirements, hardware/software environment, structure, I/O, and control are given in the main body of the document for the overall MIDAS system, with detailed discussion of the individual modules included in Annexes A-J.

Machined Titanium Heat-Pipe Wick Structure

NASA Technical Reports Server (NTRS)

Rosenfeld, John H.; Minnerly, Kenneth G.; Gernert, Nelson J.

2009-01-01

Wick structures fabricated by machining of titanium porous material are essential components of lightweight titanium/ water heat pipes of a type now being developed for operation at temperatures up to 530 K in high-radiation environments. In the fabrication of some prior heat pipes, wicks have been made by extruding axial grooves into aluminum unfortunately, titanium cannot be extruded. In the fabrication of some other prior heat pipes, wicks have been made by in-situ sintering of metal powders shaped by the use of forming mandrels that are subsequently removed, but in the specific application that gave rise to the present fabrication method, the required dimensions and shapes of the heat-pipe structures would make it very difficult if not impossible to remove the mandrels due to the length and the small diameter. In the present method, a wick is made from one or more sections that are fabricated separately and assembled outside the tube that constitutes the outer heat pipe wall. The starting wick material is a slab of porous titanium material. This material is machined in its original flat configuration to form axial grooves. In addition, interlocking features are machined at the mating ends of short wick sections that are to be assembled to make a full-length continuous wick structure. Once the sections have been thus assembled, the resulting full-length flat wick structure is rolled into a cylindrical shape and inserted in the heatpipe tube (see figure). This wick-structure fabrication method is not limited to titanium/water heat pipes: It could be extended to other heat pipe materials and working fluids in which the wicks could be made from materials that could be pre-formed into porous slabs.

A 3D Human-Machine Integrated Design and Analysis Framework for Squat Exercises with a Smith Machine.

PubMed

Lee, Haerin; Jung, Moonki; Lee, Ki-Kwang; Lee, Sang Hun

2017-02-06

In this paper, we propose a three-dimensional design and evaluation framework and process based on a probabilistic-based motion synthesis algorithm and biomechanical analysis system for the design of the Smith machine and squat training programs. Moreover, we implemented a prototype system to validate the proposed framework. The framework consists of an integrated human-machine-environment model as well as a squat motion synthesis system and biomechanical analysis system. In the design and evaluation process, we created an integrated model in which interactions between a human body and machine or the ground are modeled as joints with constraints at contact points. Next, we generated Smith squat motion using the motion synthesis program based on a Gaussian process regression algorithm with a set of given values for independent variables. Then, using the biomechanical analysis system, we simulated joint moments and muscle activities from the input of the integrated model and squat motion. We validated the model and algorithm through physical experiments measuring the electromyography (EMG) signals, ground forces, and squat motions as well as through a biomechanical simulation of muscle forces. The proposed approach enables the incorporation of biomechanics in the design process and reduces the need for physical experiments and prototypes in the development of training programs and new Smith machines.

Design of a Versatile, Teleoperable, Towable Lifting Machine with Robotic Capabilities for Use in Nasa's Lunar Base Operations

NASA Technical Reports Server (NTRS)

Harris, Elizabeth; Ogle, James; Schoppe, Dean

1989-01-01

The lifting machine will assist in lifting cargo off of landers sent to the Moon and in the construction of a lunar base. Three possible designs were considered for the overall configuration of the lifting machine: the variable angle crane, the tower crane, and the gantry crane. Alternate designs were developed for the major components of the lifting machine. A teleoperable, variable angle crane was chosen as its final design. The design consists of a telescoping boom mounted to a chassis that is supported by two conical wheels for towing and four outriggers for stability. Attached to the end of the boom is a seven degree of freedom robot arm for light, dexterous, lifting operations. A cable and hook suspends from the end of the boom for heavy, gross, lifting operations. Approximate structural sizes were determined for the lifter and its components. However, further analysis is needed to determine the optimum design dimensions. The design team also constructed a model of the design which demonstrates its features and operating principals.

Vibration Damping Analysis of Lightweight Structures in Machine Tools

PubMed Central

Aggogeri, Francesco; Borboni, Alberto; Merlo, Angelo; Pellegrini, Nicola; Ricatto, Raffaele

2017-01-01

The dynamic behaviour of a machine tool (MT) directly influences the machining performance. The adoption of lightweight structures may reduce the effects of undesired vibrations and increase the workpiece quality. This paper aims to present and compare a set of hybrid materials that may be excellent candidates to fabricate the MT moving parts. The selected materials have high dynamic characteristics and capacity to dampen mechanical vibrations. In this way, starting from the kinematic model of a milling machine, this study evaluates a number of prototypes made of Al foam sandwiches (AFS), Al corrugated sandwiches (ACS) and composite materials reinforced by carbon fibres (CFRP). These prototypes represented the Z-axis ram of a commercial milling machine. The static and dynamical properties have been analysed by using both finite element (FE) simulations and experimental tests. The obtained results show that the proposed structures may be a valid alternative to the conventional materials of MT moving parts, increasing machining performance. In particular, the AFS prototype highlighted a damping ratio that is 20 times greater than a conventional ram (e.g., steel). Its application is particularly suitable to minimize unwanted oscillations during high-speed finishing operations. The results also show that the CFRP structure guarantees high stiffness with a weight reduced by 48.5%, suggesting effective applications in roughing operations, saving MT energy consumption. The ACS structure has a good trade-off between stiffness and damping and may represent a further alternative, if correctly evaluated. PMID:28772653

Responsive materials: A novel design for enhanced machine-augmented composites

PubMed Central

Bafekrpour, Ehsan; Molotnikov, Andrey; Weaver, James C.; Brechet, Yves; Estrin, Yuri

2014-01-01

The concept of novel responsive materials with a displacement conversion capability was further developed through the design of new machine-augmented composites (MACs). Embedded converter machines and MACs with improved geometry were designed and fabricated by multi-material 3D printing. This technique proved to be very effective in fabricating these novel composites with tuneable elastic moduli of the matrix and the embedded machines and excellent bonding between them. Substantial improvement in the displacement conversion efficiency of the new MACs over the existing ones was demonstrated. Also, the new design trebled the energy absorption of the MACs. Applications in energy absorbers as well as mechanical sensors and actuators are thus envisaged. A further type of MACs with conversion ability, viz. conversion of compressive displacements to torsional ones, was also proposed. PMID:24445490

Acquiring Software Design Schemas: A Machine Learning Perspective

NASA Technical Reports Server (NTRS)

Harandi, Mehdi T.; Lee, Hing-Yan

1991-01-01

In this paper, we describe an approach based on machine learning that acquires software design schemas from design cases of existing applications. An overview of the technique, design representation, and acquisition system are presented. the paper also addresses issues associated with generalizing common features such as biases. The generalization process is illustrated using an example.

Nonlinear machine learning in soft materials engineering and design

NASA Astrophysics Data System (ADS)

Ferguson, Andrew

The inherently many-body nature of molecular folding and colloidal self-assembly makes it challenging to identify the underlying collective mechanisms and pathways governing system behavior, and has hindered rational design of soft materials with desired structure and function. Fundamentally, there exists a predictive gulf between the architecture and chemistry of individual molecules or colloids and the collective many-body thermodynamics and kinetics. Integrating machine learning techniques with statistical thermodynamics provides a means to bridge this divide and identify emergent folding pathways and self-assembly mechanisms from computer simulations or experimental particle tracking data. We will survey a few of our applications of this framework that illustrate the value of nonlinear machine learning in understanding and engineering soft materials: the non-equilibrium self-assembly of Janus colloids into pinwheels, clusters, and archipelagos; engineering reconfigurable ''digital colloids'' as a novel high-density information storage substrate; probing hierarchically self-assembling onjugated asphaltenes in crude oil; and determining macromolecular folding funnels from measurements of single experimental observables. We close with an outlook on the future of machine learning in soft materials engineering, and share some personal perspectives on working at this disciplinary intersection. We acknowledge support for this work from a National Science Foundation CAREER Award (Grant No. DMR-1350008) and the Donors of the American Chemical Society Petroleum Research Fund (ACS PRF #54240-DNI6).

Design and Analysis of a Sensor System for Cutting Force Measurement in Machining Processes

PubMed Central

Liang, Qiaokang; Zhang, Dan; Coppola, Gianmarc; Mao, Jianxu; Sun, Wei; Wang, Yaonan; Ge, Yunjian

2016-01-01

Multi-component force sensors have infiltrated a wide variety of automation products since the 1970s. However, one seldom finds full-component sensor systems available in the market for cutting force measurement in machine processes. In this paper, a new six-component sensor system with a compact monolithic elastic element (EE) is designed and developed to detect the tangential cutting forces Fx, Fy and Fz (i.e., forces along x-, y-, and z-axis) as well as the cutting moments Mx, My and Mz (i.e., moments about x-, y-, and z-axis) simultaneously. Optimal structural parameters of the EE are carefully designed via simulation-driven optimization. Moreover, a prototype sensor system is fabricated, which is applied to a 5-axis parallel kinematic machining center. Calibration experimental results demonstrate that the system is capable of measuring cutting forces and moments with good linearity while minimizing coupling error. Both the Finite Element Analysis (FEA) and calibration experimental studies validate the high performance of the proposed sensor system that is expected to be adopted into machining processes. PMID:26751451

Design and Analysis of a Sensor System for Cutting Force Measurement in Machining Processes.

PubMed

Liang, Qiaokang; Zhang, Dan; Coppola, Gianmarc; Mao, Jianxu; Sun, Wei; Wang, Yaonan; Ge, Yunjian

2016-01-07

Multi-component force sensors have infiltrated a wide variety of automation products since the 1970s. However, one seldom finds full-component sensor systems available in the market for cutting force measurement in machine processes. In this paper, a new six-component sensor system with a compact monolithic elastic element (EE) is designed and developed to detect the tangential cutting forces Fx, Fy and Fz (i.e., forces along x-, y-, and z-axis) as well as the cutting moments Mx, My and Mz (i.e., moments about x-, y-, and z-axis) simultaneously. Optimal structural parameters of the EE are carefully designed via simulation-driven optimization. Moreover, a prototype sensor system is fabricated, which is applied to a 5-axis parallel kinematic machining center. Calibration experimental results demonstrate that the system is capable of measuring cutting forces and moments with good linearity while minimizing coupling error. Both the Finite Element Analysis (FEA) and calibration experimental studies validate the high performance of the proposed sensor system that is expected to be adopted into machining processes.

Initial planetary base construction techniques and machine implementation

NASA Technical Reports Server (NTRS)

Crockford, William W.

1987-01-01

Conceptual designs of (1) initial planetary base structures, and (2) an unmanned machine to perform the construction of these structures using materials local to the planet are presented. Rock melting is suggested as a possible technique to be used by the machine in fabricating roads, platforms, and interlocking bricks. Identification of problem areas in machine design and materials processing is accomplished. The feasibility of the designs is contingent upon favorable results of an analysis of the engineering behavior of the product materials. The analysis requires knowledge of several parameters for solution of the constitutive equations of the theory of elasticity. An initial collection of these parameters is presented which helps to define research needed to perform a realistic feasibility study. A qualitative approach to estimating power and mass lift requirements for the proposed machine is used which employs specifications of currently available equipment. An initial, unmanned mission scenario is discussed with emphasis on identifying uncompleted tasks and suggesting design considerations for vehicles and primitive structures which use the products of the machine processing.

Light-operated machines based on threaded molecular structures.

PubMed

Credi, Alberto; Silvi, Serena; Venturi, Margherita

2014-01-01

Rotaxanes and related species represent the most common implementation of the concept of artificial molecular machines, because the supramolecular nature of the interactions between the components and their interlocked architecture allow a precise control on the position and movement of the molecular units. The use of light to power artificial molecular machines is particularly valuable because it can play the dual role of "writing" and "reading" the system. Moreover, light-driven machines can operate without accumulation of waste products, and photons are the ideal inputs to enable autonomous operation mechanisms. In appropriately designed molecular machines, light can be used to control not only the stability of the system, which affects the relative position of the molecular components but also the kinetics of the mechanical processes, thereby enabling control on the direction of the movements. This step forward is necessary in order to make a leap from molecular machines to molecular motors.

A novel hybrid genetic algorithm for optimal design of IPM machines for electric vehicle

NASA Astrophysics Data System (ADS)

Wang, Aimeng; Guo, Jiayu

2017-12-01

A novel hybrid genetic algorithm (HGA) is proposed to optimize the rotor structure of an IPM machine which is used in EV application. The finite element (FE) simulation results of the HGA design is compared with the genetic algorithm (GA) design and those before optimized. It is shown that the performance of the IPMSM is effectively improved by employing the GA and HGA, especially by HGA. Moreover, higher flux-weakening capability and less magnet usage are also obtained. Therefore, the validity of HGA method in IPMSM optimization design is verified.

A Navier-Strokes Chimera Code on the Connection Machine CM-5: Design and Performance

NASA Technical Reports Server (NTRS)

Jespersen, Dennis C.; Levit, Creon; Kwak, Dochan (Technical Monitor)

1994-01-01

We have implemented a three-dimensional compressible Navier-Stokes code on the Connection Machine CM-5. The code is set up for implicit time-stepping on single or multiple structured grids. For multiple grids and geometrically complex problems, we follow the 'chimera' approach, where flow data on one zone is interpolated onto another in the region of overlap. We will describe our design philosophy and give some timing results for the current code. A parallel machine like the CM-5 is well-suited for finite-difference methods on structured grids. The regular pattern of connections of a structured mesh maps well onto the architecture of the machine. So the first design choice, finite differences on a structured mesh, is natural. We use centered differences in space, with added artificial dissipation terms. When numerically solving the Navier-Stokes equations, there are liable to be some mesh cells near a solid body that are small in at least one direction. This mesh cell geometry can impose a very severe CFL (Courant-Friedrichs-Lewy) condition on the time step for explicit time-stepping methods. Thus, though explicit time-stepping is well-suited to the architecture of the machine, we have adopted implicit time-stepping. We have further taken the approximate factorization approach. This creates the need to solve large banded linear systems and creates the first possible barrier to an efficient algorithm. To overcome this first possible barrier we have considered two options. The first is just to solve the banded linear systems with data spread over the whole machine, using whatever fast method is available. This option is adequate for solving scalar tridiagonal systems, but for scalar pentadiagonal or block tridiagonal systems it is somewhat slower than desired. The second option is to 'transpose' the flow and geometry variables as part of the time-stepping process: Start with x-lines of data in-processor. Form explicit terms in x, then transpose so y-lines of data are

Design and Experimental Validation for Direct-Drive Fault-Tolerant Permanent-Magnet Vernier Machines

PubMed Central

Liu, Guohai; Yang, Junqin; Chen, Ming; Chen, Qian

2014-01-01

A fault-tolerant permanent-magnet vernier (FT-PMV) machine is designed for direct-drive applications, incorporating the merits of high torque density and high reliability. Based on the so-called magnetic gearing effect, PMV machines have the ability of high torque density by introducing the flux-modulation poles (FMPs). This paper investigates the fault-tolerant characteristic of PMV machines and provides a design method, which is able to not only meet the fault-tolerant requirements but also keep the ability of high torque density. The operation principle of the proposed machine has been analyzed. The design process and optimization are presented specifically, such as the combination of slots and poles, the winding distribution, and the dimensions of PMs and teeth. By using the time-stepping finite element method (TS-FEM), the machine performances are evaluated. Finally, the FT-PMV machine is manufactured, and the experimental results are presented to validate the theoretical analysis. PMID:25045729

Design and experimental validation for direct-drive fault-tolerant permanent-magnet vernier machines.

PubMed

Liu, Guohai; Yang, Junqin; Chen, Ming; Chen, Qian

2014-01-01

A fault-tolerant permanent-magnet vernier (FT-PMV) machine is designed for direct-drive applications, incorporating the merits of high torque density and high reliability. Based on the so-called magnetic gearing effect, PMV machines have the ability of high torque density by introducing the flux-modulation poles (FMPs). This paper investigates the fault-tolerant characteristic of PMV machines and provides a design method, which is able to not only meet the fault-tolerant requirements but also keep the ability of high torque density. The operation principle of the proposed machine has been analyzed. The design process and optimization are presented specifically, such as the combination of slots and poles, the winding distribution, and the dimensions of PMs and teeth. By using the time-stepping finite element method (TS-FEM), the machine performances are evaluated. Finally, the FT-PMV machine is manufactured, and the experimental results are presented to validate the theoretical analysis.

Machine Learning: A Crucial Tool for Sensor Design

PubMed Central

Zhao, Weixiang; Bhushan, Abhinav; Santamaria, Anthony D.; Simon, Melinda G.; Davis, Cristina E.

2009-01-01

Sensors have been widely used for disease diagnosis, environmental quality monitoring, food quality control, industrial process analysis and control, and other related fields. As a key tool for sensor data analysis, machine learning is becoming a core part of novel sensor design. Dividing a complete machine learning process into three steps: data pre-treatment, feature extraction and dimension reduction, and system modeling, this paper provides a review of the methods that are widely used for each step. For each method, the principles and the key issues that affect modeling results are discussed. After reviewing the potential problems in machine learning processes, this paper gives a summary of current algorithms in this field and provides some feasible directions for future studies. PMID:20191110

Design features and results from fatigue reliability research machines.

NASA Technical Reports Server (NTRS)

Lalli, V. R.; Kececioglu, D.; Mcconnell, J. B.

1971-01-01

The design, fabrication, development, operation, calibration and results from reversed bending combined with steady torque fatigue research machines are presented. Fifteen-centimeter long, notched, SAE 4340 steel specimens are subjected to various combinations of these stresses and cycled to failure. Failure occurs when the crack in the notch passes through the specimen automatically shutting down the test machine. These cycles-to-failure data are statistically analyzed to develop a probabilistic S-N diagram. These diagrams have many uses; a rotating component design example given in the literature shows that minimum size and weight for a specified number of cycles and reliability can be calculated using these diagrams.

How do users design? The case of sugar cane harvester machines.

PubMed

Narimoto, Lidiane Regina; Camarotto, João Alberto

2017-01-01

Design in use and inventiveness are key concepts in ergonomics. It is well-known that users design but is not explored in the literature how they manage to do that. This paper aims to contribute to the discussion of how users actually design, by showing a research conducted in sugar cane harvesting in Brazil and in Australia. Through the methodology of the Ergonomic Work Analysis (EWA), the design modifications made by the harvesting teams were identified as well as their elaboration process. Three categories of modifications in machines' design were identified: structural, functional and operational and they were more numerous in Brazilian situations. It is proposed that two theories underlying the theme are intertwined: the instrument-mediated activity approach and the design as bricolage. It is argued that users design through the articulation of: a) the operators' activity, b) the mechanical technicians' inventory to practice bricolage as a way of designing and c) the work organisation and the existence of social spaces of interaction between these two subjects.

Augmentation of machine structure to improve its diagnosability

NASA Technical Reports Server (NTRS)

Hsieh, L.

1973-01-01

Two methods of augmenting the structure of a sequential machine so that it is diagnosable are presented. The checkable (checking sequences) and repeated symbol distinguishing sequences (RDS) are discussed. It was found that as few as twice the number of outputs of the given machine is sufficient for constructing a state-output augmentation with RDS. Techniques for minimizing the number of states in resolving convergences and in resolving equivalent and nonreduced cycles are developed.

An algorithm for the design and tuning of RF accelerating structures with variable cell lengths

NASA Astrophysics Data System (ADS)

Lal, Shankar; Pant, K. K.

2018-05-01

An algorithm is proposed for the design of a π mode standing wave buncher structure with variable cell lengths. It employs a two-parameter, multi-step approach for the design of the structure with desired resonant frequency and field flatness. The algorithm, along with analytical scaling laws for the design of the RF power coupling slot, makes it possible to accurately design the structure employing a freely available electromagnetic code like SUPERFISH. To compensate for machining errors, a tuning method has been devised to achieve desired RF parameters for the structure, which has been qualified by the successful tuning of a 7-cell buncher to π mode frequency of 2856 MHz with field flatness <3% and RF coupling coefficient close to unity. The proposed design algorithm and tuning method have demonstrated the feasibility of developing an S-band accelerating structure for desired RF parameters with a relatively relaxed machining tolerance of ∼ 25 μm. This paper discusses the algorithm for the design and tuning of an RF accelerating structure with variable cell lengths.

Kinematic design to improve ergonomics in human machine interaction.

PubMed

Schiele, André; van der Helm, Frans C T

2006-12-01

This paper introduces a novel kinematic design paradigm for ergonomic human machine interaction. Goals for optimal design are formulated generically and applied to the mechanical design of an upper-arm exoskeleton. A nine degree-of-freedom (DOF) model of the human arm kinematics is presented and used to develop, test, and optimize the kinematic structure of an human arm interfacing exoskeleton. The resulting device can interact with an unprecedented portion of the natural limb workspace, including motions in the shoulder-girdle, shoulder, elbow, and the wrist. The exoskeleton does not require alignment to the human joint axes, yet is able to actuate each DOF of our redundant limb unambiguously and without reaching into singularities. The device is comfortable to wear and does not create residual forces if misalignments exist. Implemented in a rehabilitation robot, the design features of the exoskeleton could enable longer lasting training sessions, training of fully natural tasks such as activities of daily living and shorter dress-on and dress-off times. Results from inter-subject experiments with a prototype are presented, that verify usability over the entire workspace of the human arm, including shoulder and shoulder girdle.

Design of a Modular E-Core Flux Concentrating Axial Flux Machine

DOE Office of Scientific and Technical Information (OSTI.GOV)

Husain, Tausif; Sozer, Yilmaz; Husain, Iqbal

2015-09-02

In this paper a novel E-Core axial flux machine is proposed. The machine has a double stator-single rotor configuration with flux concentrating ferrite magnets, and pole windings across each leg of an E-Core stator. E-Core stators with the proposed flux-concentrating rotor arrangement result in better magnet utilization and higher torque density. The machine also has a modular structure facilitating simpler construction. This paper presents a single phase and a three-phase version of the E-Core machine. Case study for a 1.1 kW, 400 rpm machine for both the single phase and three-phase axial flux machine is presented. The results are verifiedmore » through 3D finite element analysis.« less

A 3D Human-Machine Integrated Design and Analysis Framework for Squat Exercises with a Smith Machine

PubMed Central

Lee, Haerin; Jung, Moonki; Lee, Ki-Kwang; Lee, Sang Hun

2017-01-01

In this paper, we propose a three-dimensional design and evaluation framework and process based on a probabilistic-based motion synthesis algorithm and biomechanical analysis system for the design of the Smith machine and squat training programs. Moreover, we implemented a prototype system to validate the proposed framework. The framework consists of an integrated human–machine–environment model as well as a squat motion synthesis system and biomechanical analysis system. In the design and evaluation process, we created an integrated model in which interactions between a human body and machine or the ground are modeled as joints with constraints at contact points. Next, we generated Smith squat motion using the motion synthesis program based on a Gaussian process regression algorithm with a set of given values for independent variables. Then, using the biomechanical analysis system, we simulated joint moments and muscle activities from the input of the integrated model and squat motion. We validated the model and algorithm through physical experiments measuring the electromyography (EMG) signals, ground forces, and squat motions as well as through a biomechanical simulation of muscle forces. The proposed approach enables the incorporation of biomechanics in the design process and reduces the need for physical experiments and prototypes in the development of training programs and new Smith machines. PMID:28178184

Natural Fiber Cut Machine Semi-Automatic Linear Motion System for Empty Fiber Bunches: Re-designing for Local Use

NASA Astrophysics Data System (ADS)

Asfarizal; Kasim, Anwar; Gunawarman; Santosa

2017-12-01

Empty Palm bunches of fiber is local ingredient in Indonesia that easy to obtain. Empty Palm bunches of fiber can be obtained from the palm oil industry such as in West Pasaman. The character of the empty Palm bunches of fiber that is strong and pliable has high-potential for particle board. To transform the large quantities of fiber become particles in size 0-10 mm requires a specially designed cut machine. Therefore, the machine is designed in two-stage system that is mechanical system, structure and cutting knife. Components that have been made, assembled and then tested to reveal the ability of the machine to cut. The results showed that the straight back and forth motion cut machine is able to cut out the empty oil palm bunches of fiber with a length 0-1 cm, 2 cm, 8 cm and the surface of the cut is not stringy. The cutting capacity is at a length of 2 cm in the result 24.4 (kg/h) and 8 cm obtained results of up to 84 (kg/h)

Axiomatic Design and Fabrication of Composite Structures - Applications in Robots, Machine Tools, and Automobiles

NASA Astrophysics Data System (ADS)

Lee, Dai Gil; Suh, Nam Pyo

2005-11-01

The idea that materials can be designed to satisfy specific performance requirements is relatively new. With high-performance composites, however, the entire process of designing and fabricating a part can be worked out before manufacturing. The purpose of this book is to present an integrated approach to the design and manufacturing of products from advanced composites. It shows how the basic behavior of composites and their constitutive relationships can be used during the design stage, which minimizes the complexity of manufacturing composite parts and reduces the repetitive "design-build-test" cycle. Designing it right the first time is going to determine the competitiveness of a company, the reliability of the part, the robustness of fabrication processes, and ultimately, the cost and development time of composite parts. Most of all, it should expand the use of advanced composite parts in fields that use composites only to a limited extent at this time. To achieve these goals, this book presents the design and fabrication of novel composite parts made for machine tools and other applications like robots and automobiles. This book is suitable as a textbook for graduate courses in the design and fabrication of composites. It will also be of interest to practicing engineers learning about composites and axiomatic design. A CD-ROM is included in every copy of the book, containing Axiomatic CLPT software. This program, developed by the authors, will assist readers in calculating material properties from the microstructure of the composite. This book is part of the Oxford Series on Advanced Manufacturing.

Design of Ultra-High-Power-Density Machine Optimized for Future Aircraft

NASA Technical Reports Server (NTRS)

Choi, Benjamin B.

2004-01-01

The NASA Glenn Research Center's Structural Mechanics and Dynamics Branch is developing a compact, nonpolluting, bearingless electric machine with electric power supplied by fuel cells for future "more-electric" aircraft with specific power in the projected range of 50 hp/lb, whereas conventional electric machines generate usually 0.2 hp/lb. The use of such electric drives for propulsive fans or propellers depends on the successful development of ultra-high-power-density machines. One possible candidate for such ultra-high-power-density machines, a round-rotor synchronous machine with an engineering current density as high as 20,000 A/sq cm, was selected to investigate how much torque and power can be produced.

Design of a line-VISAR interferometer system for the Sandia Z Machine

NASA Astrophysics Data System (ADS)

Galbraith, J.; Austin, K.; Baker, J.; Bettencourt, R.; Bliss, E.; Celeste, J.; Clancy, T.; Cohen, S.; Crosley, M.; Datte, P.; Fratanduono, D.; Frieders, G.; Hammer, J.; Jackson, J.; Johnson, D.; Jones, M.; Koen, D.; Lusk, J.; Martinez, A.; Massey, W.; McCarville, T.; McLean, H.; Raman, K.; Rodriguez, S.; Spencer, D.; Springer, P.; Wong, J.

2017-08-01

A joint team comprised of Lawrence Livermore National Laboratory (LLNL) and Sandia National Laboratory (SNL) personnel is designing a line-VISAR (Velocity Interferometer System for Any Reflector) for the Sandia Z Machine, Z Line-VISAR. The diagnostic utilizes interferometry to assess current delivery as a function of radius during a magnetically-driven implosion. The Z Line-VISAR system is comprised of the following: a two-leg line-VISAR interferometer, an eight-channel Gated Optical Imager (GOI), and a fifty-meter transport beampath to/from the target of interest. The Z Machine presents unique optomechanical design challenges. The machine utilizes magnetically driven pulsed power to drive a target to elevated temperatures and pressures useful for high energy density science. Shock accelerations exceeding 30g and a strong electromagnetic pulse (EMP) are generated during the shot event as the machine discharges currents of over 25 million amps. Sensitive optical components must be protected from shock loading, and electrical equipment must be adequately shielded from the EMP. The optical design must accommodate temperature and humidity fluctuations in the facility as well as airborne hydrocarbons from the pulsed power components. We will describe the engineering design and concept of operations of the Z Line-VISAR system. Focus will be on optomechanical design.

On Intelligent Design and Planning Method of Process Route Based on Gun Breech Machining Process

NASA Astrophysics Data System (ADS)

Hongzhi, Zhao; Jian, Zhang

2018-03-01

The paper states an approach of intelligent design and planning of process route based on gun breech machining process, against several problems, such as complex machining process of gun breech, tedious route design and long period of its traditional unmanageable process route. Based on gun breech machining process, intelligent design and planning system of process route are developed by virtue of DEST and VC++. The system includes two functional modules--process route intelligent design and its planning. The process route intelligent design module, through the analysis of gun breech machining process, summarizes breech process knowledge so as to complete the design of knowledge base and inference engine. And then gun breech process route intelligently output. On the basis of intelligent route design module, the final process route is made, edited and managed in the process route planning module.

Machine learning for autonomous crystal structure identification.

PubMed

Reinhart, Wesley F; Long, Andrew W; Howard, Michael P; Ferguson, Andrew L; Panagiotopoulos, Athanassios Z

2017-07-21

We present a machine learning technique to discover and distinguish relevant ordered structures from molecular simulation snapshots or particle tracking data. Unlike other popular methods for structural identification, our technique requires no a priori description of the target structures. Instead, we use nonlinear manifold learning to infer structural relationships between particles according to the topology of their local environment. This graph-based approach yields unbiased structural information which allows us to quantify the crystalline character of particles near defects, grain boundaries, and interfaces. We demonstrate the method by classifying particles in a simulation of colloidal crystallization, and show that our method identifies structural features that are missed by standard techniques.

Bearingless AC Homopolar Machine Design and Control for Distributed Flywheel Energy Storage

NASA Astrophysics Data System (ADS)

Severson, Eric Loren

The increasing ownership of electric vehicles, in-home solar and wind generation, and wider penetration of renewable energies onto the power grid has created a need for grid-based energy storage to provide energy-neutral services. These services include frequency regulation, which requires short response-times, high power ramping capabilities, and several charge cycles over the course of one day; and diurnal load-/generation-following services to offset the inherent mismatch between renewable generation and the power grid's load profile, which requires low self-discharge so that a reasonable efficiency is obtained over a 24 hour storage interval. To realize the maximum benefits of energy storage, the technology should be modular and have minimum geographic constraints, so that it is easily scalable according to local demands. Furthermore, the technology must be economically viable to participate in the energy markets. There is currently no storage technology that is able to simultaneously meet all of these needs. This dissertation focuses on developing a new energy storage device based on flywheel technology to meet these needs. It is shown that the bearingless ac homopolar machine can be used to overcome key obstacles in flywheel technology, namely: unacceptable self-discharge and overall system cost and complexity. Bearingless machines combine the functionality of a magnetic bearing and a motor/generator into a single electromechanical device. Design of these machines is particularly challenging due to cross-coupling effects and trade-offs between motor and magnetic bearing capabilities. The bearingless ac homopolar machine adds to these design challenges due to its 3D flux paths requiring computationally expensive 3D finite element analysis. At the time this dissertation was started, bearingless ac homopolar machines were a highly immature technology. This dissertation advances the state-of-the-art of these machines through research contributions in the areas of

The research on construction and application of machining process knowledge base

NASA Astrophysics Data System (ADS)

Zhao, Tan; Qiao, Lihong; Qie, Yifan; Guo, Kai

2018-03-01

In order to realize the application of knowledge in machining process design, from the perspective of knowledge in the application of computer aided process planning(CAPP), a hierarchical structure of knowledge classification is established according to the characteristics of mechanical engineering field. The expression of machining process knowledge is structured by means of production rules and the object-oriented methods. Three kinds of knowledge base models are constructed according to the representation of machining process knowledge. In this paper, the definition and classification of machining process knowledge, knowledge model, and the application flow of the process design based on the knowledge base are given, and the main steps of the design decision of the machine tool are carried out as an application by using the knowledge base.

Re-Design and Beat Testing of the Man-Machine Integration Design and Analysis System: MIDAS

NASA Technical Reports Server (NTRS)

Shively, R. Jay; Rutkowski, Michael (Technical Monitor)

1999-01-01

The Man-machine Design and Analysis System (MIDAS) is a human factors design and analysis system that combines human cognitive models with 3D CAD models and rapid prototyping and simulation techniques. MIDAS allows designers to ask 'what if' types of questions early in concept exploration and development prior to actual hardware development. The system outputs predictions of operator workload, situational awareness and system performance as well as graphical visualization of the cockpit designs interacting with models of the human in a mission scenario. Recently, MIDAS was re-designed to enhance functionality and usability. The goals driving the redesign include more efficient processing, GUI interface, advances in the memory structures, implementation of external vision models and audition. These changes were detailed in an earlier paper. Two Beta test sites with diverse applications have been chosen. One Beta test site is investigating the development of a new airframe and its interaction with the air traffic management system. The second Beta test effort will investigate 3D auditory cueing in conjunction with traditional visual cueing strategies including panel-mounted and heads-up displays. The progress and lessons learned on each of these projects will be discussed.

A Boltzmann machine for the organization of intelligent machines

NASA Technical Reports Server (NTRS)

Moed, Michael C.; Saridis, George N.

1990-01-01

A three-tier structure consisting of organization, coordination, and execution levels forms the architecture of an intelligent machine using the principle of increasing precision with decreasing intelligence from a hierarchically intelligent control. This system has been formulated as a probabilistic model, where uncertainty and imprecision can be expressed in terms of entropies. The optimal strategy for decision planning and task execution can be found by minimizing the total entropy in the system. The focus is on the design of the organization level as a Boltzmann machine. Since this level is responsible for planning the actions of the machine, the Boltzmann machine is reformulated to use entropy as the cost function to be minimized. Simulated annealing, expanding subinterval random search, and the genetic algorithm are presented as search techniques to efficiently find the desired action sequence and illustrated with numerical examples.

Online learning control using adaptive critic designs with sparse kernel machines.

PubMed

Xu, Xin; Hou, Zhongsheng; Lian, Chuanqiang; He, Haibo

2013-05-01

In the past decade, adaptive critic designs (ACDs), including heuristic dynamic programming (HDP), dual heuristic programming (DHP), and their action-dependent ones, have been widely studied to realize online learning control of dynamical systems. However, because neural networks with manually designed features are commonly used to deal with continuous state and action spaces, the generalization capability and learning efficiency of previous ACDs still need to be improved. In this paper, a novel framework of ACDs with sparse kernel machines is presented by integrating kernel methods into the critic of ACDs. To improve the generalization capability as well as the computational efficiency of kernel machines, a sparsification method based on the approximately linear dependence analysis is used. Using the sparse kernel machines, two kernel-based ACD algorithms, that is, kernel HDP (KHDP) and kernel DHP (KDHP), are proposed and their performance is analyzed both theoretically and empirically. Because of the representation learning and generalization capability of sparse kernel machines, KHDP and KDHP can obtain much better performance than previous HDP and DHP with manually designed neural networks. Simulation and experimental results of two nonlinear control problems, that is, a continuous-action inverted pendulum problem and a ball and plate control problem, demonstrate the effectiveness of the proposed kernel ACD methods.

Layout Design of Human-Machine Interaction Interface of Cabin Based on Cognitive Ergonomics and GA-ACA.

PubMed

Deng, Li; Wang, Guohua; Yu, Suihuai

2016-01-01

In order to consider the psychological cognitive characteristics affecting operating comfort and realize the automatic layout design, cognitive ergonomics and GA-ACA (genetic algorithm and ant colony algorithm) were introduced into the layout design of human-machine interaction interface. First, from the perspective of cognitive psychology, according to the information processing process, the cognitive model of human-machine interaction interface was established. Then, the human cognitive characteristics were analyzed, and the layout principles of human-machine interaction interface were summarized as the constraints in layout design. Again, the expression form of fitness function, pheromone, and heuristic information for the layout optimization of cabin was studied. The layout design model of human-machine interaction interface was established based on GA-ACA. At last, a layout design system was developed based on this model. For validation, the human-machine interaction interface layout design of drilling rig control room was taken as an example, and the optimization result showed the feasibility and effectiveness of the proposed method.

Layout Design of Human-Machine Interaction Interface of Cabin Based on Cognitive Ergonomics and GA-ACA

PubMed Central

Deng, Li; Wang, Guohua; Yu, Suihuai

2016-01-01

In order to consider the psychological cognitive characteristics affecting operating comfort and realize the automatic layout design, cognitive ergonomics and GA-ACA (genetic algorithm and ant colony algorithm) were introduced into the layout design of human-machine interaction interface. First, from the perspective of cognitive psychology, according to the information processing process, the cognitive model of human-machine interaction interface was established. Then, the human cognitive characteristics were analyzed, and the layout principles of human-machine interaction interface were summarized as the constraints in layout design. Again, the expression form of fitness function, pheromone, and heuristic information for the layout optimization of cabin was studied. The layout design model of human-machine interaction interface was established based on GA-ACA. At last, a layout design system was developed based on this model. For validation, the human-machine interaction interface layout design of drilling rig control room was taken as an example, and the optimization result showed the feasibility and effectiveness of the proposed method. PMID:26884745

ClearTK 2.0: Design Patterns for Machine Learning in UIMA.

PubMed

Bethard, Steven; Ogren, Philip; Becker, Lee

2014-05-01

ClearTK adds machine learning functionality to the UIMA framework, providing wrappers to popular machine learning libraries, a rich feature extraction library that works across different classifiers, and utilities for applying and evaluating machine learning models. Since its inception in 2008, ClearTK has evolved in response to feedback from developers and the community. This evolution has followed a number of important design principles including: conceptually simple annotator interfaces, readable pipeline descriptions, minimal collection readers, type system agnostic code, modules organized for ease of import, and assisting user comprehension of the complex UIMA framework.

Optimal design method to minimize users' thinking mapping load in human-machine interactions.

PubMed

Huang, Yanqun; Li, Xu; Zhang, Jie

2015-01-01

The discrepancy between human cognition and machine requirements/behaviors usually results in serious mental thinking mapping loads or even disasters in product operating. It is important to help people avoid human-machine interaction confusions and difficulties in today's mental work mastered society. Improving the usability of a product and minimizing user's thinking mapping and interpreting load in human-machine interactions. An optimal human-machine interface design method is introduced, which is based on the purpose of minimizing the mental load in thinking mapping process between users' intentions and affordance of product interface states. By analyzing the users' thinking mapping problem, an operating action model is constructed. According to human natural instincts and acquired knowledge, an expected ideal design with minimized thinking loads is uniquely determined at first. Then, creative alternatives, in terms of the way human obtains operational information, are provided as digital interface states datasets. In the last, using the cluster analysis method, an optimum solution is picked out from alternatives, by calculating the distances between two datasets. Considering multiple factors to minimize users' thinking mapping loads, a solution nearest to the ideal value is found in the human-car interaction design case. The clustering results show its effectiveness in finding an optimum solution to the mental load minimizing problems in human-machine interaction design.

Time-domain prefilter design for enhanced tracking and vibration suppression in machine motion control

NASA Astrophysics Data System (ADS)

Cole, Matthew O. T.; Shinonawanik, Praween; Wongratanaphisan, Theeraphong

2018-05-01

Structural flexibility can impact negatively on machine motion control systems by causing unmeasured positioning errors and vibration at locations where accurate motion is important for task execution. To compensate for these effects, command signal prefiltering may be applied. In this paper, a new FIR prefilter design method is described that combines finite-time vibration cancellation with dynamic compensation properties. The time-domain formulation exploits the relation between tracking error and the moment values of the prefilter impulse response function. Optimal design solutions for filters having minimum H2 norm are derived and evaluated. The control approach does not require additional actuation or sensing and can be effective even without complete and accurate models of the machine dynamics. Results from implementation and testing on an experimental high-speed manipulator having a Delta robot architecture with directionally compliant end-effector are presented. The results show the importance of prefilter moment values for tracking performance and confirm that the proposed method can achieve significant reductions in both peak and RMS tracking error, as well as settling time, for complex motion patterns.

Optimal design of earth-moving machine elements with cusp catastrophe theory application

NASA Astrophysics Data System (ADS)

Pitukhin, A. V.; Skobtsov, I. G.

2017-10-01

This paper deals with the optimal design problem solution for the operator of an earth-moving machine with a roll-over protective structure (ROPS) in terms of the catastrophe theory. A brief description of the catastrophe theory is presented, the cusp catastrophe is considered, control parameters are viewed as Gaussian stochastic quantities in the first part of the paper. The statement of optimal design problem is given in the second part of the paper. It includes the choice of the objective function and independent design variables, establishment of system limits. The objective function is determined as mean total cost that includes initial cost and cost of failure according to the cusp catastrophe probability. Algorithm of random search method with an interval reduction subject to side and functional constraints is given in the last part of the paper. The way of optimal design problem solution can be applied to choose rational ROPS parameters, which will increase safety and reduce production and exploitation expenses.

Large-Scale Linear Optimization through Machine Learning: From Theory to Practical System Design and Implementation

DTIC Science & Technology

2016-08-10

AFRL-AFOSR-JP-TR-2016-0073 Large-scale Linear Optimization through Machine Learning: From Theory to Practical System Design and Implementation ...2016 4.  TITLE AND SUBTITLE Large-scale Linear Optimization through Machine Learning: From Theory to Practical System Design and Implementation 5a...performances on various machine learning tasks and it naturally lends itself to fast parallel implementations . Despite this, very little work has been

Design of a Modular E-Core Flux Concentrating Axial Flux Machine: Preprint

DOE Office of Scientific and Technical Information (OSTI.GOV)

Husain, Tausif; Sozer, Yilmaz; Husain, Iqbal

2015-08-24

In this paper a novel E-Core axial flux machine is proposed. The machine has a double-stator, single-rotor configuration with flux-concentrating ferrite magnets and pole windings across each leg of an E-Core stator. E-Core stators with the proposed flux-concentrating rotor arrangement result in better magnet utilization and higher torque density. The machine also has a modular structure facilitating simpler construction. This paper presents a single-phase and a three-phase version of the E-Core machine. Case studies for a 1.1-kW, 400-rpm machine for both the single-phase and three-phase axial flux machines are presented. The results are verified through 3D finite element analysis. facilitatingmore » simpler construction. This paper presents a single-phase and a three-phase version of the E-Core machine. Case studies for a 1.1-kW, 400-rpm machine for both the single-phase and three-phase axial flux machines are presented. The results are verified through 3D finite element analysis.« less

Design and fabrication of metal briquette machine for shop floor

NASA Astrophysics Data System (ADS)

Pramod, R.; Kumar, G. B. Veeresh; Prashanth B., N.

2017-07-01

Efforts have to be taken to ensure efficient waste management system in shop floors, with minimum utilization of space and energy when it comes to disposing metal chips formed during machining processes. The salvaging of junk metallic chips and the us e of scrap are important for the economic production of a steelworks. For this purpose, we have fabricated a metal chip compaction machine, which can compact the metal chips into small briquettes. The project started with the survey of chips formed in shop floors and the practices involved in waste management. Study was done on the requirements for a better compaction. The heating chamber was designed taking into consideration the temperature required for an easy compaction of the metal chips. The power source for compaction and the pneumatic design for mechanism was done following the appropriate calculations regarding the air pressure provided and thrust required. The processes were tested under different conditions and found effective. The fabrication of the machine has been explained in detail and the results have been discussed.

ClearTK 2.0: Design Patterns for Machine Learning in UIMA

PubMed Central

Bethard, Steven; Ogren, Philip; Becker, Lee

2014-01-01

ClearTK adds machine learning functionality to the UIMA framework, providing wrappers to popular machine learning libraries, a rich feature extraction library that works across different classifiers, and utilities for applying and evaluating machine learning models. Since its inception in 2008, ClearTK has evolved in response to feedback from developers and the community. This evolution has followed a number of important design principles including: conceptually simple annotator interfaces, readable pipeline descriptions, minimal collection readers, type system agnostic code, modules organized for ease of import, and assisting user comprehension of the complex UIMA framework. PMID:29104966

Design Considerations of a Transverse Flux Machine for Direct-Drive Wind Turbine Applications

DOE Office of Scientific and Technical Information (OSTI.GOV)

Husain, Tausif; Hasan, Iftekhar; Sozer, Yilmaz

This paper presents the design considerations of a double-sided transverse flux machine (TFM) for direct-drive wind turbine applications. The proposed TFM has a modular structure with quasi-U stator cores and toroidal ring windings. The rotor is constructed with ferrite magnets in a flux-concentrating setup to achieve high air gap flux density. Pole number selection is critical in the design process of a TFM as it affects both the torque density and power factor under fixed magnetic and changing electrical loading. Several key design ratios are introduced to facilitate the initial design procedure. The effect of pole shaping on back-EMF andmore » inductance is also analyzed. These investigations provide guidance toward the required design of a TFM for direct-drive applications. The analyses are carried out using analytical and three-dimensional finite element analysis (FEA). A proof-of-concept prototype was developed to experimentally validate the FEA results.« less

Design Considerations of a Transverse Flux Machine for Direct-Drive Wind Turbine Applications

DOE PAGES

Husain, Tausif; Hasan, Iftekhar; Sozer, Yilmaz; ...

2018-03-12

This paper presents the design considerations of a double-sided transverse flux machine (TFM) for direct-drive wind turbine applications. The proposed TFM has a modular structure with quasi-U stator cores and toroidal ring windings. The rotor is constructed with ferrite magnets in a flux-concentrating setup to achieve high air gap flux density. Pole number selection is critical in the design process of a TFM as it affects both the torque density and power factor under fixed magnetic and changing electrical loading. Several key design ratios are introduced to facilitate the initial design procedure. The effect of pole shaping on back-EMF andmore » inductance is also analyzed. These investigations provide guidance toward the required design of a TFM for direct-drive applications. The analyses are carried out using analytical and three-dimensional finite element analysis (FEA). A proof-of-concept prototype was developed to experimentally validate the FEA results.« less

Machine learning to design integral membrane channelrhodopsins for efficient eukaryotic expression and plasma membrane localization.

PubMed

Bedbrook, Claire N; Yang, Kevin K; Rice, Austin J; Gradinaru, Viviana; Arnold, Frances H

2017-10-01

There is growing interest in studying and engineering integral membrane proteins (MPs) that play key roles in sensing and regulating cellular response to diverse external signals. A MP must be expressed, correctly inserted and folded in a lipid bilayer, and trafficked to the proper cellular location in order to function. The sequence and structural determinants of these processes are complex and highly constrained. Here we describe a predictive, machine-learning approach that captures this complexity to facilitate successful MP engineering and design. Machine learning on carefully-chosen training sequences made by structure-guided SCHEMA recombination has enabled us to accurately predict the rare sequences in a diverse library of channelrhodopsins (ChRs) that express and localize to the plasma membrane of mammalian cells. These light-gated channel proteins of microbial origin are of interest for neuroscience applications, where expression and localization to the plasma membrane is a prerequisite for function. We trained Gaussian process (GP) classification and regression models with expression and localization data from 218 ChR chimeras chosen from a 118,098-variant library designed by SCHEMA recombination of three parent ChRs. We use these GP models to identify ChRs that express and localize well and show that our models can elucidate sequence and structure elements important for these processes. We also used the predictive models to convert a naturally occurring ChR incapable of mammalian localization into one that localizes well.

Machine learning to design integral membrane channelrhodopsins for efficient eukaryotic expression and plasma membrane localization

PubMed Central

Rice, Austin J.; Gradinaru, Viviana; Arnold, Frances H.

2017-01-01

There is growing interest in studying and engineering integral membrane proteins (MPs) that play key roles in sensing and regulating cellular response to diverse external signals. A MP must be expressed, correctly inserted and folded in a lipid bilayer, and trafficked to the proper cellular location in order to function. The sequence and structural determinants of these processes are complex and highly constrained. Here we describe a predictive, machine-learning approach that captures this complexity to facilitate successful MP engineering and design. Machine learning on carefully-chosen training sequences made by structure-guided SCHEMA recombination has enabled us to accurately predict the rare sequences in a diverse library of channelrhodopsins (ChRs) that express and localize to the plasma membrane of mammalian cells. These light-gated channel proteins of microbial origin are of interest for neuroscience applications, where expression and localization to the plasma membrane is a prerequisite for function. We trained Gaussian process (GP) classification and regression models with expression and localization data from 218 ChR chimeras chosen from a 118,098-variant library designed by SCHEMA recombination of three parent ChRs. We use these GP models to identify ChRs that express and localize well and show that our models can elucidate sequence and structure elements important for these processes. We also used the predictive models to convert a naturally occurring ChR incapable of mammalian localization into one that localizes well. PMID:29059183

Design, development and use of the finite element machine

NASA Technical Reports Server (NTRS)

Adams, L. M.; Voigt, R. C.

1983-01-01

Some of the considerations that went into the design of the Finite Element Machine, a research asynchronous parallel computer are described. The present status of the system is also discussed along with some indication of the type of results that were obtained.

Design of an ultraprecision computerized numerical control chemical mechanical polishing machine and its implementation

NASA Astrophysics Data System (ADS)

Zhang, Chupeng; Zhao, Huiying; Zhu, Xueliang; Zhao, Shijie; Jiang, Chunye

2018-01-01

The chemical mechanical polishing (CMP) is a key process during the machining route of plane optics. To improve the polishing efficiency and accuracy, a CMP model and machine tool were developed. Based on the Preston equation and the axial run-out error measurement results of the m circles on the tin plate, a CMP model that could simulate the material removal at any point on the workpiece was presented. An analysis of the model indicated that lower axial run-out error led to lower material removal but better polishing efficiency and accuracy. Based on this conclusion, the CMP machine was designed, and the ultraprecision gas hydrostatic guideway and rotary table as well as the Siemens 840Dsl numerical control system were incorporated in the CMP machine. To verify the design principles of machine, a series of detection and machining experiments were conducted. The LK-G5000 laser sensor was employed for detecting the straightness error of the gas hydrostatic guideway and the axial run-out error of the gas hydrostatic rotary table. A 300-mm-diameter optic was chosen for the surface profile machining experiments performed to determine the CMP efficiency and accuracy.

Design Considerations of a Transverse Flux Machine for Direct-Drive Wind Turbine Applications

DOE Office of Scientific and Technical Information (OSTI.GOV)

Husain, Tausif; Hasan, Iftekhar; Sozer, Yilmaz

This paper presents the design considerations of a double-sided transverse flux machine (TFM) for direct-drive wind turbine applications. The TFM has a modular structure with quasi-U stator cores and ring windings. The rotor is constructed with ferrite magnets in a flux-concentrating arrangement to achieve high air gap flux density. The design considerations for this TFM with respect to initial sizing, pole number selection, key design ratios, and pole shaping are presented in this paper. Pole number selection is critical in the design process of a TFM because it affects both the torque density and power factor under fixed magnetic andmore » changing electrical loading. Several key design ratios are introduced to facilitate the design procedure. The effect of pole shaping on back-emf and inductance is also analyzed. These investigations provide guidance toward the required design of a TFM for direct-drive applications. The analyses are carried out using analytical and three-dimensional finite element analysis. A prototype is under construction for experimental verification.« less

Classifying Structures in the ISM with Machine Learning Techniques

NASA Astrophysics Data System (ADS)

Beaumont, Christopher; Goodman, A. A.; Williams, J. P.

2011-01-01

The processes which govern molecular cloud evolution and star formation often sculpt structures in the ISM: filaments, pillars, shells, outflows, etc. Because of their morphological complexity, these objects are often identified manually. Manual classification has several disadvantages; the process is subjective, not easily reproducible, and does not scale well to handle increasingly large datasets. We have explored to what extent machine learning algorithms can be trained to autonomously identify specific morphological features in molecular cloud datasets. We show that the Support Vector Machine algorithm can successfully locate filaments and outflows blended with other emission structures. When the objects of interest are morphologically distinct from the surrounding emission, this autonomous classification achieves >90% accuracy. We have developed a set of IDL-based tools to apply this technique to other datasets.

The Design of Finite State Machine for Asynchronous Replication Protocol

NASA Astrophysics Data System (ADS)

Wang, Yanlong; Li, Zhanhuai; Lin, Wei; Hei, Minglei; Hao, Jianhua

Data replication is a key way to design a disaster tolerance system and to achieve reliability and availability. It is difficult for a replication protocol to deal with the diverse and complex environment. This means that data is less well replicated than it ought to be. To reduce data loss and to optimize replication protocols, we (1) present a finite state machine, (2) run it to manage an asynchronous replication protocol and (3) report a simple evaluation of the asynchronous replication protocol based on our state machine. It's proved that our state machine is applicable to guarantee the asynchronous replication protocol running in the proper state to the largest extent in the event of various possible events. It also can helpful to build up replication-based disaster tolerance systems to ensure the business continuity.

Sequence-invariant state machines

NASA Technical Reports Server (NTRS)

Whitaker, Sterling R.; Manjunath, Shamanna K.; Maki, Gary K.

1991-01-01

A synthesis method and an MOS VLSI architecture are presented to realize sequential circuits that have the ability to implement any state machine having N states and m inputs, regardless of the actual sequence specified in the flow table. The design method utilizes binary tree structured (BTS) logic to implement regular and dense circuits. The desired state sequence can be hardwired with power supply connections or can be dynamically reallocated if stored in a register. This allows programmable VLSI controllers to be designed with a compact size and performance approaching that of dedicated logic. Results of ICV implementations are reported and an example sequence-invariant state machine is contrasted with implementations based on traditional methods.

The influence of the focus position on laser machining and laser micro-structuring monocrystalline diamond surface

NASA Astrophysics Data System (ADS)

Wu, Mingtao; Guo, Bing; Zhao, Qingliang; Fan, Rongwei; Dong, Zhiwei; Yu, Xin

2018-06-01

Micro-structured surface on diamond is widely used in microelectronics, optical elements, MEMS and NEMS components, ultra-precision machining tools, etc. The efficient micro-structuring of diamond material is still a challenging task. In this article, the influence of the focus position on laser machining and laser micro-structuring monocrystalline diamond surface were researched. At the beginning, the ablation threshold and its incubation effect of monocrystalline diamond were determined and discussed. As the accumulated laser pulses ranged from 40 to 5000, the laser ablation threshold decreased from 1.48 J/cm2 to 0.97 J/cm2. Subsequently, the variation of the ablation width and ablation depth in laser machining were studied. With enough pulse energy, the ablation width mainly depended on the laser propagation attributes while the ablation depth was a complex function of the focus position. Raman analysis was used to detect the variation of the laser machined diamond surface after the laser machining experiments. Graphite formation was discovered on the machined diamond surface and graphitization was enhanced after the defocusing quantity exceeded 45 μm. At last, several micro-structured surfaces were successfully fabricated on diamond surface with the defined micro-structure patterns and structuring ratios just by adjusting the defocusing quantity. The experimental structuring ratio was consistent with the theoretical analysis.

A strategy for quantum algorithm design assisted by machine learning

NASA Astrophysics Data System (ADS)

Bang, Jeongho; Ryu, Junghee; Yoo, Seokwon; Pawłowski, Marcin; Lee, Jinhyoung

2014-07-01

We propose a method for quantum algorithm design assisted by machine learning. The method uses a quantum-classical hybrid simulator, where a ‘quantum student’ is being taught by a ‘classical teacher’. In other words, in our method, the learning system is supposed to evolve into a quantum algorithm for a given problem, assisted by a classical main-feedback system. Our method is applicable for designing quantum oracle-based algorithms. We chose, as a case study, an oracle decision problem, called a Deutsch-Jozsa problem. We showed by using Monte Carlo simulations that our simulator can faithfully learn a quantum algorithm for solving the problem for a given oracle. Remarkably, the learning time is proportional to the square root of the total number of parameters, rather than showing the exponential dependence found in the classical machine learning-based method.

Creating the New from the Old: Combinatorial Libraries Generation with Machine-Learning-Based Compound Structure Optimization.

PubMed

Podlewska, Sabina; Czarnecki, Wojciech M; Kafel, Rafał; Bojarski, Andrzej J

2017-02-27

The growing computational abilities of various tools that are applied in the broadly understood field of computer-aided drug design have led to the extreme popularity of virtual screening in the search for new biologically active compounds. Most often, the source of such molecules consists of commercially available compound databases, but they can also be searched for within the libraries of structures generated in silico from existing ligands. Various computational combinatorial approaches are based solely on the chemical structure of compounds, using different types of substitutions for new molecules formation. In this study, the starting point for combinatorial library generation was the fingerprint referring to the optimal substructural composition in terms of the activity toward a considered target, which was obtained using a machine learning-based optimization procedure. The systematic enumeration of all possible connections between preferred substructures resulted in the formation of target-focused libraries of new potential ligands. The compounds were initially assessed by machine learning methods using a hashed fingerprint to represent molecules; the distribution of their physicochemical properties was also investigated, as well as their synthetic accessibility. The examination of various fingerprints and machine learning algorithms indicated that the Klekota-Roth fingerprint and support vector machine were an optimal combination for such experiments. This study was performed for 8 protein targets, and the obtained compound sets and their characterization are publically available at http://skandal.if-pan.krakow.pl/comb_lib/ .

Hybrid test on building structures using electrodynamic fatigue test machine

NASA Astrophysics Data System (ADS)

Xu, Zhao-Dong; Wang, Kai-Yang; Guo, Ying-Qing; Wu, Min-Dong; Xu, Meng

2017-01-01

Hybrid simulation is an advanced structural dynamic experimental method that combines experimental physical models with analytical numerical models. It has increasingly been recognised as a powerful methodology to evaluate structural nonlinear components and systems under realistic operating conditions. One of the barriers for this advanced testing is the lack of flexible software for hybrid simulation using heterogeneous experimental equipment. In this study, an electrodynamic fatigue test machine is made and a MATLAB program is developed for hybrid simulation. Compared with the servo-hydraulic system, electrodynamic fatigue test machine has the advantages of small volume, easy operation and fast response. A hybrid simulation is conducted to verify the flexibility and capability of the whole system whose experimental substructure is one spring brace and numerical substructure is a two-storey steel frame structure. Experimental and numerical results show the feasibility and applicability of the whole system.

14. Machine room, building 501, underground structure, May 11, 1956, ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

14. Machine room, building 501, underground structure, May 11, 1956, looking east - Offutt Air Force Base, Strategic Air Command Headquarters & Command Center, Command Center, 901 SAC Boulevard, Bellevue, Sarpy County, NE

Modelling of human-machine interaction in equipment design of manufacturing cells

NASA Astrophysics Data System (ADS)

Cochran, David S.; Arinez, Jorge F.; Collins, Micah T.; Bi, Zhuming

2017-08-01

This paper proposes a systematic approach to model human-machine interactions (HMIs) in supervisory control of machining operations; it characterises the coexistence of machines and humans for an enterprise to balance the goals of automation/productivity and flexibility/agility. In the proposed HMI model, an operator is associated with a set of behavioural roles as a supervisor for multiple, semi-automated manufacturing processes. The model is innovative in the sense that (1) it represents an HMI based on its functions for process control but provides the flexibility for ongoing improvements in the execution of manufacturing processes; (2) it provides a computational tool to define functional requirements for an operator in HMIs. The proposed model can be used to design production systems at different levels of an enterprise architecture, particularly at the machine level in a production system where operators interact with semi-automation to accomplish the goal of 'autonomation' - automation that augments the capabilities of human beings.

Design Considerations of a Transverse Flux Machine for Direct-Drive Wind Turbine Applications: Preprint

DOE Office of Scientific and Technical Information (OSTI.GOV)

Husain, Tausif; Hasan, Iftekhar; Sozer, Yilmaz

This paper presents the design considerations of a double-sided transverse flux machine (TFM) for direct-drive wind turbine applications. The TFM has a modular structure with quasi-U stator cores and ring windings. The rotor is constructed with ferrite magnets in a flux-concentrating arrangement to achieve high air gap flux density. The design considerations for this TFM with respect to initial sizing, pole number selection, key design ratios, and pole shaping are presented in this paper. Pole number selection is critical in the design process of a TFM because it affects both the torque density and power factor under fixed magnetic andmore » changing electrical loading. Several key design ratios are introduced to facilitate the design procedure. The effect of pole shaping on back-emf and inductance is also analyzed. These investigations provide guidance toward the required design of a TFM for direct-drive applications. The analyses are carried out using analytical and three-dimensional finite element analysis. A prototype is under construction for experimental verification.« less

Design and experiment on 2KF-15 type disc cutter and shallow fertilization machine in rubber plantation

NASA Astrophysics Data System (ADS)

Deng, Yiguo; Zhang, Yuan; Wang, Yeqin

2017-12-01

At present, the trenching and fertilization machine has a serious weed plug problem when trenching and fertilization operation in rubber plantation. So a disc cutter and shallow fertilization machine in rubber plantation named 2KF-15 was designed, the design scheme used the front disc cutter cutting the grass, while using the rear of the disc furrow to trenching, the prototype of a disc anti-plugging trenching and shallow fertilization machine was completed. Afterwards, a series of trenching and fertilization field experiments were carried out, and the results showed that the ditching depth of this machine could achieve from 131 to 176 mm, and the average depth could reach 156 mm, the ditching depth stability coefficient could achieve 90.3%; The fertilizer amount of this machine could achieve from 113.2 to 156.4 kg/hm2, the average fertilizer amount reach 134.2kg/hm2, the fertilizer amount stability coefficient could achieve 89.6%, the fertilizer broken rate was 0%, the fertilizer coverage rate of 98.4%;The situation of fertilizer accumulation occurred less by using this machine, and the fertilization performance was relatively stable. This new designed machine for trenching, fertilization and covering the soil were carried out at the same time. So the number of operations could be effectively reduced. This new designed machine does not only meet the agronomic requirements of rubber plantation fertilization, but also provides a reference for the trenching and fertilization operation in other.

Nature versus design: synthetic biology or how to build a biological non-machine.

PubMed

Porcar, M; Peretó, J

2016-04-18

The engineering ideal of synthetic biology presupposes that organisms are composed of standard, interchangeable parts with a predictive behaviour. In one word, organisms are literally recognized as machines. Yet living objects are the result of evolutionary processes without any purposiveness, not of a design by external agents. Biological components show massive overlapping and functional degeneracy, standard-free complexity, intrinsic variation and context dependent performances. However, although organisms are not full-fledged machines, synthetic biologists may still be eager for machine-like behaviours from artificially modified biosystems.

Machinability of nickel based alloys using electrical discharge machining process

NASA Astrophysics Data System (ADS)

Khan, M. Adam; Gokul, A. K.; Bharani Dharan, M. P.; Jeevakarthikeyan, R. V. S.; Uthayakumar, M.; Thirumalai Kumaran, S.; Duraiselvam, M.

2018-04-01

The high temperature materials such as nickel based alloys and austenitic steel are frequently used for manufacturing critical aero engine turbine components. Literature on conventional and unconventional machining of steel materials is abundant over the past three decades. However the machining studies on superalloy is still a challenging task due to its inherent property and quality. Thus this material is difficult to be cut in conventional processes. Study on unconventional machining process for nickel alloys is focused in this proposed research. Inconel718 and Monel 400 are the two different candidate materials used for electrical discharge machining (EDM) process. Investigation is to prepare a blind hole using copper electrode of 6mm diameter. Electrical parameters are varied to produce plasma spark for diffusion process and machining time is made constant to calculate the experimental results of both the material. Influence of process parameters on tool wear mechanism and material removal are considered from the proposed experimental design. While machining the tool has prone to discharge more materials due to production of high energy plasma spark and eddy current effect. The surface morphology of the machined surface were observed with high resolution FE SEM. Fused electrode found to be a spherical structure over the machined surface as clumps. Surface roughness were also measured with surface profile using profilometer. It is confirmed that there is no deviation and precise roundness of drilling is maintained.

Free-form machining for micro-imaging systems

NASA Astrophysics Data System (ADS)

Barkman, Michael L.; Dutterer, Brian S.; Davies, Matthew A.; Suleski, Thomas J.

2008-02-01

While mechanical ruling and single point diamond turning has been a mainstay of optical fabrication for many years, many types of micro-optical devices and structures are not conducive to simple diamond turning or ruling, such as, for example, microlens arrays, and optical surfaces with non-radial symmetry. More recent developments in machining technology have enabled significant expansion of fabrication capabilities. Modern machine tools can generate complex three-dimensional structures with optical quality surface finish, and fabricate structures across a dynamic range of dimensions not achievable with lithographic techniques. In particular, five-axis free-form micromachining offers a great deal of promise for realization of essentially arbitrary surface structures, including surfaces not realizable through binary or analog lithographic techniques. Furthermore, these machines can generate geometric features with optical finish on scales ranging from centimeters to micrometers with accuracies of 10s of nanometers. In this paper, we discuss techniques and applications of free-form surface machining of micro-optical elements. Aspects of diamond machine tool design to realize desired surface geometries in specific materials are discussed. Examples are presented, including fabrication of aspheric lens arrays in germanium for compact infrared imaging systems. Using special custom kinematic mounting equipment and the additional axes of the machine, the lenses were turned with surface finish better than 2 nm RMS and center to center positioning accuracy of +/-0.5 μm.

Machine Shop Lathes.

ERIC Educational Resources Information Center

Dunn, James

This guide, the second in a series of five machine shop curriculum manuals, was designed for use in machine shop courses in Oklahoma. The purpose of the manual is to equip students with basic knowledge and skills that will enable them to enter the machine trade at the machine-operator level. The curriculum is designed so that it can be used in…

Design synthesis and optimization of permanent magnet synchronous machines based on computationally-efficient finite element analysis

NASA Astrophysics Data System (ADS)

Sizov, Gennadi Y.

In this dissertation, a model-based multi-objective optimal design of permanent magnet ac machines, supplied by sine-wave current regulated drives, is developed and implemented. The design procedure uses an efficient electromagnetic finite element-based solver to accurately model nonlinear material properties and complex geometric shapes associated with magnetic circuit design. Application of an electromagnetic finite element-based solver allows for accurate computation of intricate performance parameters and characteristics. The first contribution of this dissertation is the development of a rapid computational method that allows accurate and efficient exploration of large multi-dimensional design spaces in search of optimum design(s). The computationally efficient finite element-based approach developed in this work provides a framework of tools that allow rapid analysis of synchronous electric machines operating under steady-state conditions. In the developed modeling approach, major steady-state performance parameters such as, winding flux linkages and voltages, average, cogging and ripple torques, stator core flux densities, core losses, efficiencies and saturated machine winding inductances, are calculated with minimum computational effort. In addition, the method includes means for rapid estimation of distributed stator forces and three-dimensional effects of stator and/or rotor skew on the performance of the machine. The second contribution of this dissertation is the development of the design synthesis and optimization method based on a differential evolution algorithm. The approach relies on the developed finite element-based modeling method for electromagnetic analysis and is able to tackle large-scale multi-objective design problems using modest computational resources. Overall, computational time savings of up to two orders of magnitude are achievable, when compared to current and prevalent state-of-the-art methods. These computational savings allow

New numerical approach for the modelling of machining applied to aeronautical structural parts

NASA Astrophysics Data System (ADS)

Rambaud, Pierrick; Mocellin, Katia

2018-05-01

The manufacturing of aluminium alloy structural aerospace parts involves several steps: forming (rolling, forging …etc), heat treatments and machining. Before machining, the manufacturing processes have embedded residual stresses into the workpiece. The final geometry is obtained during this last step, when up to 90% of the raw material volume is removed by machining. During this operation, the mechanical equilibrium of the part is in constant evolution due to the redistribution of the initial stresses. This redistribution is the main cause for workpiece deflections during machining and for distortions - after unclamping. Both may lead to non-conformity of the part regarding the geometrical and dimensional specifications and therefore to rejection of the part or additional conforming steps. In order to improve the machining accuracy and the robustness of the process, the effect of the residual stresses has to be considered for the definition of the machining process plan and even in the geometrical definition of the part. In this paper, the authors present two new numerical approaches concerning the modelling of machining of aeronautical structural parts. The first deals with the use of an immersed volume framework to model the cutting step, improving the robustness and the quality of the resulting mesh compared to the previous version. The second is about the mechanical modelling of the machining problem. The authors thus show that in the framework of rolled aluminium parts the use of a linear elasticity model is functional in the finite element formulation and promising regarding the reduction of computation times.

System software for the finite element machine

NASA Technical Reports Server (NTRS)

Crockett, T. W.; Knott, J. D.

1985-01-01

The Finite Element Machine is an experimental parallel computer developed at Langley Research Center to investigate the application of concurrent processing to structural engineering analysis. This report describes system-level software which has been developed to facilitate use of the machine by applications researchers. The overall software design is outlined, and several important parallel processing issues are discussed in detail, including processor management, communication, synchronization, and input/output. Based on experience using the system, the hardware architecture and software design are critiqued, and areas for further work are suggested.

From machine learning to deep learning: progress in machine intelligence for rational drug discovery.

PubMed

Zhang, Lu; Tan, Jianjun; Han, Dan; Zhu, Hao

2017-11-01

Machine intelligence, which is normally presented as artificial intelligence, refers to the intelligence exhibited by computers. In the history of rational drug discovery, various machine intelligence approaches have been applied to guide traditional experiments, which are expensive and time-consuming. Over the past several decades, machine-learning tools, such as quantitative structure-activity relationship (QSAR) modeling, were developed that can identify potential biological active molecules from millions of candidate compounds quickly and cheaply. However, when drug discovery moved into the era of 'big' data, machine learning approaches evolved into deep learning approaches, which are a more powerful and efficient way to deal with the massive amounts of data generated from modern drug discovery approaches. Here, we summarize the history of machine learning and provide insight into recently developed deep learning approaches and their applications in rational drug discovery. We suggest that this evolution of machine intelligence now provides a guide for early-stage drug design and discovery in the current big data era. Copyright © 2017 Elsevier Ltd. All rights reserved.

Effects of Toy Crane Design-Based Learning on Simple Machines

ERIC Educational Resources Information Center

Korur, Fikret; Efe, Gülfem; Erdogan, Fisun; Tunç, Berna

2017-01-01

The aim of this 2-group study was to investigate the following question: Are there significant differences between scaffolded design-based learning controlled using 7 forms and teacher-directed instruction methods for the toy crane project on grade 7 students' posttest scores on the simple machines achievement test, attitude toward simple…

Dissipative structures, machines, and organisms: A perspective

NASA Astrophysics Data System (ADS)

Kondepudi, Dilip; Kay, Bruce; Dixon, James

2017-10-01

Self-organization in nonequilibrium systems resulting in the formation of dissipative structures has been studied in a variety of systems, most prominently in chemical systems. We present a study of a voltage-driven dissipative structure consisting of conducting beads immersed in a viscous medium of oil. In this simple system, we observed remarkably complex organism-like behavior. The dissipative structure consists of a tree structure that spontaneously forms and moves like a worm and exhibits many features characteristic of living organisms. The complex motion of the beads driven by the applied field, the dipole-dipole interaction between the beads, and the hydrodynamic flow of the viscous medium result in a time evolution of the tree structure towards states of lower resistance or higher dissipation and thus higher rates of entropy production. The resulting end-directed evolution manifests as the tree moving to locations seeking higher current, the current that sustains its structure and dynamics. The study of end-directed evolution in the dissipative structure gives us a means to distinguish the fundamental difference between machines and organisms and opens a path for the formulation of physics of organisms.

The optimal design of UAV wing structure

NASA Astrophysics Data System (ADS)

Długosz, Adam; Klimek, Wiktor

2018-01-01

The paper presents an optimal design of UAV wing, made of composite materials. The aim of the optimization is to improve strength and stiffness together with reduction of the weight of the structure. Three different types of functionals, which depend on stress, stiffness and the total mass are defined. The paper presents an application of the in-house implementation of the evolutionary multi-objective algorithm in optimization of the UAV wing structure. Values of the functionals are calculated on the basis of results obtained from numerical simulations. Numerical FEM model, consisting of different composite materials is created. Adequacy of the numerical model is verified by results obtained from the experiment, performed on a tensile testing machine. Examples of multi-objective optimization by means of Pareto-optimal set of solutions are presented.

Cognitive learning: a machine learning approach for automatic process characterization from design

NASA Astrophysics Data System (ADS)

Foucher, J.; Baderot, J.; Martinez, S.; Dervilllé, A.; Bernard, G.

2018-03-01

Cutting edge innovation requires accurate and fast process-control to obtain fast learning rate and industry adoption. Current tools available for such task are mainly manual and user dependent. We present in this paper cognitive learning, which is a new machine learning based technique to facilitate and to speed up complex characterization by using the design as input, providing fast training and detection time. We will focus on the machine learning framework that allows object detection, defect traceability and automatic measurement tools.

Machine learning in the rational design of antimicrobial peptides.

PubMed

Rondón-Villarreal, Paola; Sierra, Daniel A; Torres, Rodrigo

2014-01-01

One of the most important public health issues is the microbial and bacterial resistance to conventional antibiotics by pathogen microorganisms. In recent years, many researches have been focused on the development of new antibiotics. Among these, antimicrobial peptides (AMPs) have raised as a promising alternative to combat antibioticresistant microorganisms. For this reason, many theoretical efforts have been done in the development of new computational tools for the rational design of both better and effective AMPs. In this review, we present an overview of the rational design of AMPs using machine learning techniques and new research fields.

Design of cryogenic tanks for space vehicles shell structures analytical modeling

NASA Technical Reports Server (NTRS)

Copper, Charles; Mccarthy, K.; Pilkey, W. D.; Haviland, J. K.

1991-01-01

The initial objective was to study the use of superplastically formed corrugated hat section stringers and frames in place of integrally machined stringers over separate frames for the tanks of large launch vehicles subjected to high buckling loads. The ALS was used as an example. The objective of the follow-on project was to study methods of designing shell structures subjected to severe combinations of structural loads and thermal gradients, with emphasis on new combinations of structural arrangements and materials. Typical applications would be to fuselage sections of high speed civil transports and to cryogenic tanks on the National Aerospace Plane.

A Function-Behavior-State Approach to Designing Human Machine Interface for Nuclear Power Plant Operators

NASA Astrophysics Data System (ADS)

Lin, Y.; Zhang, W. J.

2005-02-01

This paper presents an approach to human-machine interface design for control room operators of nuclear power plants. The first step in designing an interface for a particular application is to determine information content that needs to be displayed. The design methodology for this step is called the interface design framework (called framework ). Several frameworks have been proposed for applications at varying levels, including process plants. However, none is based on the design and manufacture of a plant system for which the interface is designed. This paper presents an interface design framework which originates from design theory and methodology for general technical systems. Specifically, the framework is based on a set of core concepts of a function-behavior-state model originally proposed by the artificial intelligence research community and widely applied in the design research community. Benefits of this new framework include the provision of a model-based fault diagnosis facility, and the seamless integration of the design (manufacture, maintenance) of plants and the design of human-machine interfaces. The missing linkage between design and operation of a plant was one of the causes of the Three Mile Island nuclear reactor incident. A simulated plant system is presented to explain how to apply this framework in designing an interface. The resulting human-machine interface is discussed; specifically, several fault diagnosis examples are elaborated to demonstrate how this interface could support operators' fault diagnosis in an unanticipated situation.

Quantification of uncertainty in machining operations for on-machine acceptance.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Claudet, Andre A.; Tran, Hy D.; Su, Jiann-Chemg

2008-09-01

Manufactured parts are designed with acceptance tolerances, i.e. deviations from ideal design conditions, due to unavoidable errors in the manufacturing process. It is necessary to measure and evaluate the manufactured part, compared to the nominal design, to determine whether the part meets design specifications. The scope of this research project is dimensional acceptance of machined parts; specifically, parts machined using numerically controlled (NC, or also CNC for Computer Numerically Controlled) machines. In the design/build/accept cycle, the designer will specify both a nominal value, and an acceptable tolerance. As part of the typical design/build/accept business practice, it is required to verifymore » that the part did meet acceptable values prior to acceptance. Manufacturing cost must include not only raw materials and added labor, but also the cost of ensuring conformance to specifications. Ensuring conformance is a substantial portion of the cost of manufacturing. In this project, the costs of measurements were approximately 50% of the cost of the machined part. In production, cost of measurement would be smaller, but still a substantial proportion of manufacturing cost. The results of this research project will point to a science-based approach to reducing the cost of ensuring conformance to specifications. The approach that we take is to determine, a priori, how well a CNC machine can manufacture a particular geometry from stock. Based on the knowledge of the manufacturing process, we are then able to decide features which need further measurements from features which can be accepted 'as is' from the CNC. By calibration of the machine tool, and establishing a machining accuracy ratio, we can validate the ability of CNC to fabricate to a particular level of tolerance. This will eliminate the costs of checking for conformance for relatively large tolerances.« less

Mars vertical axis wind machines. The design of a Darreus and a Giromill for use on Mars

NASA Astrophysics Data System (ADS)

Brach, David; Dube, John; Kelly, Jon; Peterson, Joanna; Bollig, John; Gohr, Lisa; Mahoney, Kamin; Polidori, Dave

1992-05-01

This report contains the design of both a Darrieus and a Giromill for use on Mars. The report has been organized so that the interested reader may read only about one machine without having to read the entire report. Where components for the two machines differ greatly, separate sections have been allotted for each machine. Each section is complete; therefore, no relevant information is missed by reading only the section for the machine of interest. Also, when components for both machines are similar, both machines have been combined into one section. This is done so that the reader interested in both machines need not read the same information twice.

Mars vertical axis wind machines. The design of a Darreus and a Giromill for use on Mars

NASA Technical Reports Server (NTRS)

Brach, David; Dube, John; Kelly, Jon; Peterson, Joanna; Bollig, John; Gohr, Lisa; Mahoney, Kamin; Polidori, Dave

1992-01-01

This report contains the design of both a Darrieus and a Giromill for use on Mars. The report has been organized so that the interested reader may read only about one machine without having to read the entire report. Where components for the two machines differ greatly, separate sections have been allotted for each machine. Each section is complete; therefore, no relevant information is missed by reading only the section for the machine of interest. Also, when components for both machines are similar, both machines have been combined into one section. This is done so that the reader interested in both machines need not read the same information twice.

Atomistic Design and Simulations of Nanoscale Machines and Assembly

NASA Technical Reports Server (NTRS)

Goddard, William A., III; Cagin, Tahir; Walch, Stephen P.

2000-01-01

Over the three years of this project, we made significant progress on critical theoretical and computational issues in nanoscale science and technology, particularly in:(1) Fullerenes and nanotubes, (2) Characterization of surfaces of diamond and silicon for NEMS applications, (3) Nanoscale machine and assemblies, (4) Organic nanostructures and dendrimers, (5) Nanoscale confinement and nanotribology, (6) Dynamic response of nanoscale structures nanowires (metals, tubes, fullerenes), (7) Thermal transport in nanostructures.

A vibro-haptic human-machine interface for structural health monitoring

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mascarenas, David; Plont, Crystal; Brown, Christina

The structural health monitoring (SHM) community’s goal has been to endow physical systems with a nervous system not unlike those commonly found in living organisms. Typically the SHM community has attempted to do this by instrumenting structures with a variety of sensors, and then applying various signal processing and classification procedures to the data in order to detect the presence of damage, the location of damage, the severity of damage, and to estimate the remaining useful life of the structure. This procedure has had some success, but we are still a long way from achieving the performance of nervous systemsmore » found in biology. This is primarily because contemporary classification algorithms do not have the performance required. In many cases expert judgment is superior to automated classification. This work introduces a new paradigm. We propose interfacing the human nervous system to the distributed sensor network located on the structure and developing new techniques to enable human-machine cooperation. Results from the field of sensory substitution suggest this should be possible. This study investigates a vibro-haptic human-machine interface for SHM. The investigation was performed using a surrogate three-story structure. The structure features three nonlinearity-inducing bumpers to simulate damage. Accelerometers are placed on each floor to measure the response of the structure to a harmonic base excitation. The accelerometer measurements are preprocessed. As a result, the preprocessed data is then encoded encoded as a vibro-tactile stimulus. Human subjects were then subjected to the vibro-tactile stimulus and asked to characterize the damage in the structure.« less

A vibro-haptic human-machine interface for structural health monitoring

DOE PAGES

Mascarenas, David; Plont, Crystal; Brown, Christina; ...

2014-11-01

The structural health monitoring (SHM) community’s goal has been to endow physical systems with a nervous system not unlike those commonly found in living organisms. Typically the SHM community has attempted to do this by instrumenting structures with a variety of sensors, and then applying various signal processing and classification procedures to the data in order to detect the presence of damage, the location of damage, the severity of damage, and to estimate the remaining useful life of the structure. This procedure has had some success, but we are still a long way from achieving the performance of nervous systemsmore » found in biology. This is primarily because contemporary classification algorithms do not have the performance required. In many cases expert judgment is superior to automated classification. This work introduces a new paradigm. We propose interfacing the human nervous system to the distributed sensor network located on the structure and developing new techniques to enable human-machine cooperation. Results from the field of sensory substitution suggest this should be possible. This study investigates a vibro-haptic human-machine interface for SHM. The investigation was performed using a surrogate three-story structure. The structure features three nonlinearity-inducing bumpers to simulate damage. Accelerometers are placed on each floor to measure the response of the structure to a harmonic base excitation. The accelerometer measurements are preprocessed. As a result, the preprocessed data is then encoded encoded as a vibro-tactile stimulus. Human subjects were then subjected to the vibro-tactile stimulus and asked to characterize the damage in the structure.« less

Engineering artificial machines from designable DNA materials for biomedical applications.

PubMed

Qi, Hao; Huang, Guoyou; Han, Yulong; Zhang, Xiaohui; Li, Yuhui; Pingguan-Murphy, Belinda; Lu, Tian Jian; Xu, Feng; Wang, Lin

2015-06-01

Deoxyribonucleic acid (DNA) emerges as building bricks for the fabrication of nanostructure with complete artificial architecture and geometry. The amazing ability of DNA in building two- and three-dimensional structures raises the possibility of developing smart nanomachines with versatile controllability for various applications. Here, we overviewed the recent progresses in engineering DNA machines for specific bioengineering and biomedical applications.

Realistic Free-Spins Features Increase Preference for Slot Machines.

PubMed

Taylor, Lorance F; Macaskill, Anne C; Hunt, Maree J

2017-06-01

Despite increasing research into how the structural characteristics of slot machines influence gambling behaviour there have been no experimental investigations into the effect of free-spins bonus features-a structural characteristic that is commonly central to the design of slot machines. This series of three experiments investigated the free-spins feature using slot machine simulations to determine whether participants allocate more wagers to a machine with free spins, and, which components of free-spins features drive this preference. In each experiment, participants were exposed to two computer-simulated slot machines-one with a free-spins feature or similar bonus feature and one without. Participants then completed a testing phase where they could freely switch between the two machines. In Experiment 1, participants did not prefer the machine with a simple free-spins feature. In Experiment 2 the free-spins feature incorporated additional elements such as sounds, animations, and an increased win frequency; participants preferred to gamble on this machine. The Experiment 3 "bonus feature" machine resembled the free spins machine in Experiment 2 except spins were not free; participants showed a clear preference for this machine also. These findings indicate that (1) free-spins features have a major influence over machine choice and (2) the "freeness" of the free-spins bonus features is not an important driver of preference, contrary to self-report and interview research with gamblers.

Structural design and analysis for an ultra low CTE optical bench for the Hubble Space Telescope corrective optics

NASA Technical Reports Server (NTRS)

Neam, Douglas C.; Gerber, John D.

1992-01-01

The stringent stability requirements of the Corrective Optics Space Telescope Axial Replacement (COSTAR) necessitates a Deployable Optical Bench (DOB) with both a low CTE and high resonant frequency. The DOB design consists of a monocoque thin shell structure which marries metallic machined parts with graphite epoxy formed structure. Structural analysis of the DOB has been integrated into the laminate design and optimization process. Also, the structural analytical results are compared with vibration and thermal test data to assess the reliability of the analysis.

Design and finite element analysis of micro punch CNC machine modeling for medical devices

NASA Astrophysics Data System (ADS)

Pranoto, Sigiet Haryo; Mahardika, Muslim

2018-03-01

Research on micromanufacturing has been conducted. Miniaturization and weight reduction of various industrial products continue to be developed, machines with high accuracy and good quality of machining results are needed recently. This research includes design and simulation of Micro Punch CNC Machine using Abaqus with pneumatic system. This article concern of modeling simulation of punching miniplate titanium with 0.6 MPa of pressure and 500 µm of thickness. This study explaining von misses stress, safety factor and displacement analysis while the machine had the load of punching. The result gives the reaction forced of punching is 0.5 MPa on punch tip and maximum displacement is 3.237 × 10-1 mm. The safety factor is over than 12, and considered it safe for manufacturing process.

Design Enhancement and Performance Examination of External Rotor Switched Flux Permanent Magnet Machine for Downhole Application

NASA Astrophysics Data System (ADS)

Kumar, R.; Sulaiman, E.; Soomro, H. A.; Jusoh, L. I.; Bahrim, F. S.; Omar, M. F.

2017-08-01

The recent change in innovation and employments of high-temperature magnets, permanent magnet flux switching machine (PMFSM) has turned out to be one of the suitable contenders for seaward boring, however, less intended for downhole because of high atmospheric temperature. Subsequently, this extensive review manages the design enhancement and performance examination of external rotor PMFSM for the downhole application. Preparatory, the essential design parameters required for machine configuration are computed numerically. At that point, the design enhancement strategy is actualized through deterministic technique. At last, preliminary and refined execution of the machine is contrasted and as a consequence, the yield torque is raised from 16.39Nm to 33.57Nm while depreciating the cogging torque and PM weight up to 1.77Nm and 0.79kg, individually. In this manner, it is inferred that purposed enhanced design of 12slot-22pole with external rotor is convenient for the downhole application.

Structural Design Optimization of Doubly-Fed Induction Generators Using GeneratorSE

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sethuraman, Latha; Fingersh, Lee J; Dykes, Katherine L

2017-11-13

A wind turbine with a larger rotor swept area can generate more electricity, however, this increases costs disproportionately for manufacturing, transportation, and installation. This poster presents analytical models for optimizing doubly-fed induction generators (DFIGs), with the objective of reducing the costs and mass of wind turbine drivetrains. The structural design for the induction machine includes models for the casing, stator, rotor, and high-speed shaft developed within the DFIG module in the National Renewable Energy Laboratory's wind turbine sizing tool, GeneratorSE. The mechanical integrity of the machine is verified by examining stresses, structural deflections, and modal properties. The optimization results aremore » then validated using finite element analysis (FEA). The results suggest that our analytical model correlates with the FEA in some areas, such as radial deflection, differing by less than 20 percent. But the analytical model requires further development for axial deflections, torsional deflections, and stress calculations.« less

Design and Construction Multi Output Power Transmition with Single Prime Mover on Agricultural Products Machine

NASA Astrophysics Data System (ADS)

Koten, V. K.; Tanamal, C. E.

2017-03-01

Manufacturing agricultural products by the farmers, people or person who involve in medium industry, small industry, and households industry still be done in separately. Although the power on primemover is enough, in operations, primemover was only to move one of several agricultural products machine. This study attempts to design and construct power transmition multi output with single primemover; a single construction that allows primemover move some agricultur products machine in the same or not. This study begins with the determination of production capacity and the power to destroy products, the determination of resources and rotation, normalization of resources and rotation, the determination of the type material used, the size determination of each machine elements, construction machine elements, and assemble machine elements into a construction multi output power transmition with single primemover on agricultural products machine. The results show that with a input normalization 4 PK (2984 Watt), rotation 2000 rpm, the strength of material 60 kg/mm2, and several operating consideration, thus obtained size of machine elements through calculation. Based on the size, the machine elements is made through the use of some machine tools and assembled to form a multi output power transmition with single primemover.

Neural architecture design based on extreme learning machine.

PubMed

Bueno-Crespo, Andrés; García-Laencina, Pedro J; Sancho-Gómez, José-Luis

2013-12-01

Selection of the optimal neural architecture to solve a pattern classification problem entails to choose the relevant input units, the number of hidden neurons and its corresponding interconnection weights. This problem has been widely studied in many research works but their solutions usually involve excessive computational cost in most of the problems and they do not provide a unique solution. This paper proposes a new technique to efficiently design the MultiLayer Perceptron (MLP) architecture for classification using the Extreme Learning Machine (ELM) algorithm. The proposed method provides a high generalization capability and a unique solution for the architecture design. Moreover, the selected final network only retains those input connections that are relevant for the classification task. Experimental results show these advantages. Copyright © 2013 Elsevier Ltd. All rights reserved.

Effect of the crown design and interface lute parameters on the stress-state of a machined crown-tooth system: a finite element analysis.

PubMed

Shahrbaf, Shirin; vanNoort, Richard; Mirzakouchaki, Behnam; Ghassemieh, Elaheh; Martin, Nicolas

2013-08-01

The effect of preparation design and the physical properties of the interface lute on the restored machined ceramic crown-tooth complex are poorly understood. The aim of this work was to determine, by means of three-dimensional finite element analysis (3D FEA) the effect of the tooth preparation design and the elastic modulus of the cement on the stress state of the cemented machined ceramic crown-tooth complex. The three-dimensional structure of human premolar teeth, restored with adhesively cemented machined ceramic crowns, was digitized with a micro-CT scanner. An accurate, high resolution, digital replica model of a restored tooth was created. Two preparation designs, with different occlusal morphologies, were modeled with cements of 3 different elastic moduli. Interactive medical image processing software (mimics and professional CAD modeling software) was used to create sophisticated digital models that included the supporting structures; periodontal ligament and alveolar bone. The generated models were imported into an FEA software program (hypermesh version 10.0, Altair Engineering Inc.) with all degrees of freedom constrained at the outer surface of the supporting cortical bone of the crown-tooth complex. Five different elastic moduli values were given to the adhesive cement interface 1.8GPa, 4GPa, 8GPa, 18.3GPa and 40GPa; the four lower values are representative of currently used cementing lutes and 40GPa is set as an extreme high value. The stress distribution under simulated applied loads was determined. The preparation design demonstrated an effect on the stress state of the restored tooth system. The cement elastic modulus affected the stress state in the cement and dentin structures but not in the crown, the pulp, the periodontal ligament or the cancellous and cortical bone. The results of this study suggest that both the choice of the preparation design and the cement elastic modulus can affect the stress state within the restored crown

Human factors model concerning the man-machine interface of mining crewstations

NASA Technical Reports Server (NTRS)

Rider, James P.; Unger, Richard L.

1989-01-01

The U.S. Bureau of Mines is developing a computer model to analyze the human factors aspect of mining machine operator compartments. The model will be used as a research tool and as a design aid. It will have the capability to perform the following: simulated anthropometric or reach assessment, visibility analysis, illumination analysis, structural analysis of the protective canopy, operator fatigue analysis, and computation of an ingress-egress rating. The model will make extensive use of graphics to simplify data input and output. Two dimensional orthographic projections of the machine and its operator compartment are digitized and the data rebuilt into a three dimensional representation of the mining machine. Anthropometric data from either an individual or any size population may be used. The model is intended for use by equipment manufacturers and mining companies during initial design work on new machines. In addition to its use in machine design, the model should prove helpful as an accident investigation tool and for determining the effects of machine modifications made in the field on the critical areas of visibility and control reach ability.

Static characteristics design of hydrostatic guide-ways based on fluid-structure interactions

NASA Astrophysics Data System (ADS)

Lin, Shuo; Yin, YueHong

2016-10-01

With the raising requirements in micro optical systems, the available machines become hard to achieve the process dynamic and accuracy in all aspects. This makes compact design based on fluid/structure interactions (FSI) important. However, there is a difficulty in studying FSI with oil film as fluid domain. This paper aims at static characteristic design of a hydrostatic guide-way with capillary restrictors based on FSI. The pressure distribution of the oil film land is calculated by solving the Reynolds-equation with Galerkin technique. The deformation of structure is calculated by commercial FEM software, MSC. Nastran. A matlab program is designed to realize the coupling progress by modifying the load boundary in the submitting file and reading the deformation result. It's obvious that the stiffness of the hydrostatic bearing decreases with the weakening of the bearing structure. This program is proposed to make more precise prediction of bearing stiffness.

Machine-Thermal Coupling Stresses Analysis of the Fin-Type Structural Thermoelectric Generator

NASA Astrophysics Data System (ADS)

Zhang, Zheng; Yue, Hao; Chen, Dongbo; Qin, Delei; Chen, Zijian

2017-05-01

The design structure and heat-transfer mechanism of a thermoelectric generator (TEG) determine its body temperature state. Thermal stress and thermal deformation generated by the temperature variation directly affect the stress state of thermoelectric modules (TEMs). Therefore, the rated temperature and pressing force of TEMs are important parameters in TEG design. Here, the relationships between structural of a fin-type TEG (FTEG) and these parameters are studied by modeling and "machine-thermal" coupling simulation. An indirect calculation method is adopted in the coupling simulation. First, numerical heat transfer calculations of a three-dimensional FTEG model are conducted according to an orthogonal simulation table. The influences of structural parameters for heat transfer in the channel and outer fin temperature distribution are analyzed. The optimal structural parameters are obtained and used to simulate temperature field of the outer fins. Second, taking the thermal calculation results as the initial condition, the thermal-solid coupling calculation is adopted. The thermal stresses of outer fin, mechanical force of spring-angle pressing mechanism, and clamping force on a TEM are analyzed. The simulation results show that the heat transfer area of the inner fin and the physical parameters of the metal materials are the keys to determining the FTEG temperature field. The pressing mechanism's mechanical force can be reduced by reducing the outer fin angle. In addition, a corrugated cooling water pipe, which has cooling and spring functionality, is conducive to establishing an adaptable clamping force to avoid the TEMs being crushed by the thermal stresses in the body.

Engineering Artificial Machines from Designable DNA Materials for Biomedical Applications

PubMed Central

Huang, Guoyou; Han, Yulong; Zhang, Xiaohui; Li, Yuhui; Pingguan-Murphy, Belinda; Lu, Tian Jian; Xu, Feng

2015-01-01

Deoxyribonucleic acid (DNA) emerges as building bricks for the fabrication of nanostructure with complete artificial architecture and geometry. The amazing ability of DNA in building two- and three-dimensional structures raises the possibility of developing smart nanomachines with versatile controllability for various applications. Here, we overviewed the recent progresses in engineering DNA machines for specific bioengineering and biomedical applications. PMID:25547514

Dual linear structured support vector machine tracking method via scale correlation filter

NASA Astrophysics Data System (ADS)

Li, Weisheng; Chen, Yanquan; Xiao, Bin; Feng, Chen

2018-01-01

Adaptive tracking-by-detection methods based on structured support vector machine (SVM) performed well on recent visual tracking benchmarks. However, these methods did not adopt an effective strategy of object scale estimation, which limits the overall tracking performance. We present a tracking method based on a dual linear structured support vector machine (DLSSVM) with a discriminative scale correlation filter. The collaborative tracker comprised of a DLSSVM model and a scale correlation filter obtains good results in tracking target position and scale estimation. The fast Fourier transform is applied for detection. Extensive experiments show that our tracking approach outperforms many popular top-ranking trackers. On a benchmark including 100 challenging video sequences, the average precision of the proposed method is 82.8%.

Principle and design of small-sized and high-definition x-ray machine

NASA Astrophysics Data System (ADS)

Zhao, Anqing

2010-10-01

The paper discusses the circuit design and working principles of VMOS PWM type 75KV10mA high frequency X-ray machine. The system mainly consists of silicon controlled rectifier, VMOS tube PWM type high-frequency and highvoltage inverter circuit, filament inverter circuit, high-voltage rectifier filter circuit and as X-ray tube. The working process can be carried out under the control of a single-chip microcomputer. Due to the small size and high resolution in imaging, the X-ray machine is mostly adopted for emergent medical diagnosis and specific circumstances where nondestructive tests are conducted.

Review of "Conceptual Structures: Information Processing in Mind and Machine."

ERIC Educational Resources Information Center

Smoliar, Stephen W.

This review of the book, "Conceptual Structures: Information Processing in Mind and Machine," by John F. Sowa, argues that anyone who plans to get involved with issues of knowledge representation should have at least a passing acquaintance with Sowa's conceptual graphs for a database interface. (Used to model the underlying semantics of…

The design and test of collecting device and film purge device joint work of residual film recovery machine based on Solidworks & Adams

NASA Astrophysics Data System (ADS)

Zhai, Haozhou; Jian, Jianming; Hou, Shulin; San, Yunlong; Guo, Wensong; Sun, Yue; Gao, Mingqing

2018-03-01

The twine of residual film is an essential issue in the process of remnant residue recovery of the residual film recovery machine. It is difficult to clean up the residual film in the residual film recovery operation and to influence the subsequent film efficiency. Therefore, in response to this problem a composite tooth pocket residual film recovery device was designed. In this paper, the structure of the film recovery device design, theoretical analysis, simulation experiments, get the most appropriate film recovery device parameters. In addition, the residual film rate of the membrane is dramatically low, reaching about 1.3% only, and the operation of the whole machine is smoother, and the stability of the work is promoted. The operation of the film recovery device is very obvious. Lifting, in addition to the film rate has also been significantly improved to 93.88%

THE DESIGN OF A MAN-MACHINE COUNSELING SYSTEM. A PROFESSIONAL PAPER.

ERIC Educational Resources Information Center

COGSWELL, J.F.; AND OTHERS

TWO PROJECTS ON THE DESIGN, DEVELOPMENT, IMPLEMENTATION, AND EVALUATION OF A MAN-MACHINE SYSTEM FOR COUNSELING IN THE PALO ALTO AND LOS ANGELES SCHOOL DISTRICTS ARE REPORTED. THE EARLIER PHILCO 2000 COMPUTER PROGRAMS SIMULATED A COUNSELOR'S WORK IN THE EDUCATIONAL PLANNING INTERVIEW BY ACCEPTING INPUTS SUCH AS SCHOOL GRADES, TEST SCORES, AND…

The scheme machine: A case study in progress in design derivation at system levels

NASA Technical Reports Server (NTRS)

Johnson, Steven D.

1995-01-01

The Scheme Machine is one of several design projects of the Digital Design Derivation group at Indiana University. It differs from the other projects in its focus on issues of system design and its connection to surrounding research in programming language semantics, compiler construction, and programming methodology underway at Indiana and elsewhere. The genesis of the project dates to the early 1980's, when digital design derivation research branched from the surrounding research effort in programming languages. Both branches have continued to develop in parallel, with this particular project serving as a bridge. However, by 1990 there remained little real interaction between the branches and recently we have undertaken to reintegrate them. On the software side, researchers have refined a mathematically rigorous (but not mechanized) treatment starting with the fully abstract semantic definition of Scheme and resulting in an efficient implementation consisting of a compiler and virtual machine model, the latter typically realized with a general purpose microprocessor. The derivation includes a number of sophisticated factorizations and representations and is also deep example of the underlying engineering methodology. The hardware research has created a mechanized algebra supporting the tedious and massive transformations often seen at lower levels of design. This work has progressed to the point that large scale devices, such as processors, can be derived from first-order finite state machine specifications. This is roughly where the language oriented research stops; thus, together, the two efforts establish a thread from the highest levels of abstract specification to detailed digital implementation. The Scheme Machine project challenges hardware derivation research in several ways, although the individual components of the system are of a similar scale to those we have worked with before. The machine has a custom dual-ported memory to support garbage collection

New computing systems, future computing environment, and their implications on structural analysis and design

NASA Technical Reports Server (NTRS)

Noor, Ahmed K.; Housner, Jerrold M.

1993-01-01

Recent advances in computer technology that are likely to impact structural analysis and design of flight vehicles are reviewed. A brief summary is given of the advances in microelectronics, networking technologies, and in the user-interface hardware and software. The major features of new and projected computing systems, including high performance computers, parallel processing machines, and small systems, are described. Advances in programming environments, numerical algorithms, and computational strategies for new computing systems are reviewed. The impact of the advances in computer technology on structural analysis and the design of flight vehicles is described. A scenario for future computing paradigms is presented, and the near-term needs in the computational structures area are outlined.

Design and Optimization of Ultrasonic Vibration Mechanism using PZT for Precision Laser Machining

NASA Astrophysics Data System (ADS)

Kim, Woo-Jin; Lu, Fei; Cho, Sung-Hak; Park, Jong-Kweon; Lee, Moon G.

As the aged population grows around the world, many medical instruments and devices have been developed recently. Among the devices, a drug delivery stent is a medical device which requires precision machining. Conventional drug delivery stent has problems of residual polymer and decoating because the drug is coated on the surface of stent with the polymer. If the drug is impregnated in the micro sized holes on the surface, the problems can be overcome because there is no need to use the polymer anymore. Micro sized holes are generally fabricated by laser machining; however, the fabricated holes do not have a high aspect ratio or a good surface finish. To overcome these problems, we propose a vibration-assisted machining mechanism with PZT (Piezoelectric Transducers) for the fabrication of micro sized holes. If the mechanism vibrates the eyepiece of the laser machining head, the laser spot on the workpiece will vibrate vertically because objective lens in the eyepiece shakes by the mechanism's vibration. According to the former researches, the vibrating frequency over 20 kHz and amplitude over 500 nm are preferable. The vibration mechanism has cylindrical guide, hollowed PZT and supports. In the cylinder, the eyepiece is mounted. The cylindrical guide has upper and low plates and side wall. The shape of plates and side wall are designed to have high resonating frequency and large amplitude of motion. The PZT is also selected to have high actuating force and high speed of motion. The support has symmetrical and rigid configuration. The mechanism secures linear motion of the eyepiece. This research includes sensitivity analysis and design of ultrasonic vibration mechanism. As a result of design, the requirements of high frequency and large amplitude are achieved.

Predicting primary progressive aphasias with support vector machine approaches in structural MRI data.

PubMed

Bisenius, Sandrine; Mueller, Karsten; Diehl-Schmid, Janine; Fassbender, Klaus; Grimmer, Timo; Jessen, Frank; Kassubek, Jan; Kornhuber, Johannes; Landwehrmeyer, Bernhard; Ludolph, Albert; Schneider, Anja; Anderl-Straub, Sarah; Stuke, Katharina; Danek, Adrian; Otto, Markus; Schroeter, Matthias L

2017-01-01

Primary progressive aphasia (PPA) encompasses the three subtypes nonfluent/agrammatic variant PPA, semantic variant PPA, and the logopenic variant PPA, which are characterized by distinct patterns of language difficulties and regional brain atrophy. To validate the potential of structural magnetic resonance imaging data for early individual diagnosis, we used support vector machine classification on grey matter density maps obtained by voxel-based morphometry analysis to discriminate PPA subtypes (44 patients: 16 nonfluent/agrammatic variant PPA, 17 semantic variant PPA, 11 logopenic variant PPA) from 20 healthy controls (matched for sample size, age, and gender) in the cohort of the multi-center study of the German consortium for frontotemporal lobar degeneration. Here, we compared a whole-brain with a meta-analysis-based disease-specific regions-of-interest approach for support vector machine classification. We also used support vector machine classification to discriminate the three PPA subtypes from each other. Whole brain support vector machine classification enabled a very high accuracy between 91 and 97% for identifying specific PPA subtypes vs. healthy controls, and 78/95% for the discrimination between semantic variant vs. nonfluent/agrammatic or logopenic PPA variants. Only for the discrimination between nonfluent/agrammatic and logopenic PPA variants accuracy was low with 55%. Interestingly, the regions that contributed the most to the support vector machine classification of patients corresponded largely to the regions that were atrophic in these patients as revealed by group comparisons. Although the whole brain approach took also into account regions that were not covered in the regions-of-interest approach, both approaches showed similar accuracies due to the disease-specificity of the selected networks. Conclusion, support vector machine classification of multi-center structural magnetic resonance imaging data enables prediction of PPA subtypes with

Development of a machine vision system for automated structural assembly

NASA Technical Reports Server (NTRS)

Sydow, P. Daniel; Cooper, Eric G.

1992-01-01

Research is being conducted at the LaRC to develop a telerobotic assembly system designed to construct large space truss structures. This research program was initiated within the past several years, and a ground-based test-bed was developed to evaluate and expand the state of the art. Test-bed operations currently use predetermined ('taught') points for truss structural assembly. Total dependence on the use of taught points for joint receptacle capture and strut installation is neither robust nor reliable enough for space operations. Therefore, a machine vision sensor guidance system is being developed to locate and guide the robot to a passive target mounted on the truss joint receptacle. The vision system hardware includes a miniature video camera, passive targets mounted on the joint receptacles, target illumination hardware, and an image processing system. Discrimination of the target from background clutter is accomplished through standard digital processing techniques. Once the target is identified, a pose estimation algorithm is invoked to determine the location, in three-dimensional space, of the target relative to the robots end-effector. Preliminary test results of the vision system in the Automated Structural Assembly Laboratory with a range of lighting and background conditions indicate that it is fully capable of successfully identifying joint receptacle targets throughout the required operational range. Controlled optical bench test results indicate that the system can also provide the pose estimation accuracy to define the target position.

Purely Structural Protein Scoring Functions Using Support Vector Machine and Ensemble Learning.

PubMed

Mirzaei, Shokoufeh; Sidi, Tomer; Keasar, Chen; Crivelli, Silvia

2016-08-24

The function of a protein is determined by its structure, which creates a need for efficient methods of protein structure determination to advance scientific and medical research. Because current experimental structure determination methods carry a high price tag, computational predictions are highly desirable. Given a protein sequence, computational methods produce numerous 3D structures known as decoys. However, selection of the best quality decoys is challenging as the end users can handle only a few ones. Therefore, scoring functions are central to decoy selection. They combine measurable features into a single number indicator of decoy quality. Unfortunately, current scoring functions do not consistently select the best decoys. Machine learning techniques offer great potential to improve decoy scoring. This paper presents two machine-learning based scoring functions to predict the quality of proteins structures, i.e., the similarity between the predicted structure and the experimental one without knowing the latter. We use different metrics to compare these scoring functions against three state-of-the-art scores. This is a first attempt at comparing different scoring functions using the same non-redundant dataset for training and testing and the same features. The results show that adding informative features may be more significant than the method used.

Modeling workflow to design machine translation applications for public health practice

PubMed Central

Turner, Anne M.; Brownstein, Megumu K.; Cole, Kate; Karasz, Hilary; Kirchhoff, Katrin

2014-01-01

Objective Provide a detailed understanding of the information workflow processes related to translating health promotion materials for limited English proficiency individuals in order to inform the design of context-driven machine translation (MT) tools for public health (PH). Materials and Methods We applied a cognitive work analysis framework to investigate the translation information workflow processes of two large health departments in Washington State. Researchers conducted interviews, performed a task analysis, and validated results with PH professionals to model translation workflow and identify functional requirements for a translation system for PH. Results The study resulted in a detailed description of work related to translation of PH materials, an information workflow diagram, and a description of attitudes towards MT technology. We identified a number of themes that hold design implications for incorporating MT in PH translation practice. A PH translation tool prototype was designed based on these findings. Discussion This study underscores the importance of understanding the work context and information workflow for which systems will be designed. Based on themes and translation information workflow processes, we identified key design guidelines for incorporating MT into PH translation work. Primary amongst these is that MT should be followed by human review for translations to be of high quality and for the technology to be adopted into practice. Counclusion The time and costs of creating multilingual health promotion materials are barriers to translation. PH personnel were interested in MT's potential to improve access to low-cost translated PH materials, but expressed concerns about ensuring quality. We outline design considerations and a potential machine translation tool to best fit MT systems into PH practice. PMID:25445922

Analysis of static and dynamic characteristic of spindle system and its structure optimization in camshaft grinding machine

NASA Astrophysics Data System (ADS)

Feng, Jianjun; Li, Chengzhe; Wu, Zhi

2017-08-01

As an important part of the valve opening and closing controller in engine, camshaft has high machining accuracy requirement in designing. Taking the high-speed camshaft grinder spindle system as the research object and the spindle system performance as the optimizing target, this paper firstly uses Solidworks to establish the three-dimensional finite element model (FEM) of spindle system, then conducts static analysis and the modal analysis by applying the established FEM in ANSYS Workbench, and finally uses the design optimization function of the ANSYS Workbench to optimize the structure parameter in the spindle system. The study results prove that the design of the spindle system fully meets the production requirements, and the performance of the optimized spindle system is promoted. Besides, this paper provides an analysis and optimization method for other grinder spindle systems.

Achieving Small Structures in Thin NiTi Sheets for Medical Applications with Water Jet and Micro Machining: A Comparison

NASA Astrophysics Data System (ADS)

Frotscher, M.; Kahleyss, F.; Simon, T.; Biermann, D.; Eggeler, G.

2011-07-01

NiTi shape memory alloys (SMA) are used for a variety of applications including medical implants and tools as well as actuators, making use of their unique properties. However, due to the hardness and strength, in combination with the high elasticity of the material, the machining of components can be challenging. The most common machining techniques used today are laser cutting and electrical discharge machining (EDM). In this study, we report on the machining of small structures into binary NiTi sheets, applying alternative processing methods being well-established for other metallic materials. Our results indicate that water jet machining and micro milling can be used to machine delicate structures, even in very thin NiTi sheets. Further work is required to optimize the cut quality and the machining speed in order to increase the cost-effectiveness and to make both methods more competitive.

A machine learning approach to computer-aided molecular design

NASA Astrophysics Data System (ADS)

Bolis, Giorgio; Di Pace, Luigi; Fabrocini, Filippo

1991-12-01

Preliminary results of a machine learning application concerning computer-aided molecular design applied to drug discovery are presented. The artificial intelligence techniques of machine learning use a sample of active and inactive compounds, which is viewed as a set of positive and negative examples, to allow the induction of a molecular model characterizing the interaction between the compounds and a target molecule. The algorithm is based on a twofold phase. In the first one — the specialization step — the program identifies a number of active/inactive pairs of compounds which appear to be the most useful in order to make the learning process as effective as possible and generates a dictionary of molecular fragments, deemed to be responsible for the activity of the compounds. In the second phase — the generalization step — the fragments thus generated are combined and generalized in order to select the most plausible hypothesis with respect to the sample of compounds. A knowledge base concerning physical and chemical properties is utilized during the inductive process.

Surface structuring of boron doped CVD diamond by micro electrical discharge machining

NASA Astrophysics Data System (ADS)

Schubert, A.; Berger, T.; Martin, A.; Hackert-Oschätzchen, M.; Treffkorn, N.; Kühn, R.

2018-05-01

Boron doped diamond materials, which are generated by Chemical Vapor Deposition (CVD), offer a great potential for the application on highly stressed tools, e. g. in cutting or forming processes. As a result of the CVD process rough surfaces arise, which require a finishing treatment in particular for the application in forming tools. Cutting techniques such as milling and grinding are hardly applicable for the finish machining because of the high strength of diamond. Due to its process principle of ablating material by melting and evaporating, Electrical Discharge Machining (EDM) is independent of hardness, brittleness or toughness of the workpiece material. EDM is a suitable technology for machining and structuring CVD diamond, since boron doped CVD diamond is electrically conductive. In this study the ablation characteristics of boron doped CVD diamond by micro electrical discharge machining are investigated. Experiments were carried out to investigate the influence of different process parameters on the machining result. The impact of tool-polarity, voltage and discharge energy on the resulting erosion geometry and the tool wear was analyzed. A variation in path overlapping during the erosion of planar areas leads to different microstructures. The results show that micro EDM is a suitable technology for finishing of boron doped CVD diamond.

Machine learning strategy for accelerated design of polymer dielectrics

DOE PAGES

Mannodi-Kanakkithodi, Arun; Pilania, Ghanshyam; Huan, Tran Doan; ...

2016-02-15

The ability to efficiently design new and advanced dielectric polymers is hampered by the lack of sufficient, reliable data on wide polymer chemical spaces, and the difficulty of generating such data given time and computational/experimental constraints. Here, we address the issue of accelerating polymer dielectrics design by extracting learning models from data generated by accurate state-of-the-art first principles computations for polymers occupying an important part of the chemical subspace. The polymers are ‘fingerprinted’ as simple, easily attainable numerical representations, which are mapped to the properties of interest using a machine learning algorithm to develop an on-demand property prediction model. Further,more » a genetic algorithm is utilised to optimise polymer constituent blocks in an evolutionary manner, thus directly leading to the design of polymers with given target properties. Furthermore, while this philosophy of learning to make instant predictions and design is demonstrated here for the example of polymer dielectrics, it is equally applicable to other classes of materials as well.« less

A design for living technology: experiments with the mind time machine.

PubMed

Ikegami, Takashi

2013-01-01

Living technology aims to help people expand their experiences in everyday life. The environment offers people ways to interact with it, which we call affordances. Living technology is a design for new affordances. When we experience something new, we remember it by the way we perceive and interact with it. Recent studies in neuroscience have led to the idea of a default mode network, which is a baseline activity of a brain system. The autonomy of artificial life must be understood as a sort of default mode that self-organizes its baseline activity, preparing for its external inputs and its interaction with humans. I thus propose a method for creating a suitable default mode as a design principle for living technology. I built a machine called the mind time machine (MTM), which runs continuously for 10 h per day and receives visual data from its environment using 15 video cameras. The MTM receives and edits the video inputs while it self-organizes the momentary now. Its base program is a neural network that includes chaotic dynamics inside the system and a meta-network that consists of video feedback systems. Using this system as the hardware and a default mode network as a conceptual framework, I describe the system's autonomous behavior. Using the MTM as a testing ground, I propose a design principle for living technology.

Nonlinear machine learning and design of reconfigurable digital colloids.

PubMed

Long, Andrew W; Phillips, Carolyn L; Jankowksi, Eric; Ferguson, Andrew L

2016-09-14

Digital colloids, a cluster of freely rotating "halo" particles tethered to the surface of a central particle, were recently proposed as ultra-high density memory elements for information storage. Rational design of these digital colloids for memory storage applications requires a quantitative understanding of the thermodynamic and kinetic stability of the configurational states within which information is stored. We apply nonlinear machine learning to Brownian dynamics simulations of these digital colloids to extract the low-dimensional intrinsic manifold governing digital colloid morphology, thermodynamics, and kinetics. By modulating the relative size ratio between halo particles and central particles, we investigate the size-dependent configurational stability and transition kinetics for the 2-state tetrahedral (N = 4) and 30-state octahedral (N = 6) digital colloids. We demonstrate the use of this framework to guide the rational design of a memory storage element to hold a block of text that trades off the competing design criteria of memory addressability and volatility.

Your Sewing Machine.

ERIC Educational Resources Information Center

Peacock, Marion E.

The programed instruction manual is designed to aid the student in learning the parts, uses, and operation of the sewing machine. Drawings of sewing machine parts are presented, and space is provided for the student's written responses. Following an introductory section identifying sewing machine parts, the manual deals with each part and its…

A single-phase axially-magnetized permanent-magnet oscillating machine for miniature aerospace power sources

NASA Astrophysics Data System (ADS)

Sui, Yi; Zheng, Ping; Cheng, Luming; Wang, Weinan; Liu, Jiaqi

2017-05-01

A single-phase axially-magnetized permanent-magnet (PM) oscillating machine which can be integrated with a free-piston Stirling engine to generate electric power, is investigated for miniature aerospace power sources. Machine structure, operating principle and detent force characteristic are elaborately studied. With the sinusoidal speed characteristic of the mover considered, the proposed machine is designed by 2D finite-element analysis (FEA), and some main structural parameters such as air gap diameter, dimensions of PMs, pole pitches of both stator and mover, and the pole-pitch combinations, etc., are optimized to improve both the power density and force capability. Compared with the three-phase PM linear machines, the proposed single-phase machine features less PM use, simple control and low controller cost. The power density of the proposed machine is higher than that of the three-phase radially-magnetized PM linear machine, but lower than the three-phase axially-magnetized PM linear machine.

Modeling and Analysis of High Torque Density Transverse Flux Machines for Direct-Drive Applications

NASA Astrophysics Data System (ADS)

Hasan, Iftekhar

Commercially available permanent magnet synchronous machines (PMSM) typically use rare-earth-based permanent magnets (PM). However, volatility and uncertainty associated with the supply and cost of rare-earth magnets have caused a push for increased research into the development of non-rare-earth based PM machines and reluctance machines. Compared to other PMSM topologies, the Transverse Flux Machine (TFM) is a promising candidate to get higher torque densities at low speed for direct-drive applications, using non-rare-earth based PMs. The TFMs can be designed with a very small pole pitch which allows them to attain higher force density than conventional radial flux machines (RFM) and axial flux machines (AFM). This dissertation presents the modeling, electromagnetic design, vibration analysis, and prototype development of a novel non-rare-earth based PM-TFM for a direct-drive wind turbine application. The proposed TFM addresses the issues of low power factor, cogging torque, and torque ripple during the electromagnetic design phase. An improved Magnetic Equivalent Circuit (MEC) based analytical model was developed as an alternative to the time-consuming 3D Finite Element Analysis (FEA) for faster electromagnetic analysis of the TFM. The accuracy and reliability of the MEC model were verified, both with 3D-FEA and experimental results. The improved MEC model was integrated with a Particle Swarm Optimization (PSO) algorithm to further enhance the capability of the analytical tool for performing rigorous optimization of performance-sensitive machine design parameters to extract the highest torque density for rated speed. A novel concept of integrating the rotary transformer within the proposed TFM design was explored to completely eliminate the use of magnets from the TFM. While keeping the same machine envelope, and without changing the stator or rotor cores, the primary and secondary of a rotary transformer were embedded into the double-sided TFM. The proposed

Design of a Smart Ultrasonic Transducer for Interconnecting Machine Applications

PubMed Central

Yan, Tian-Hong; Wang, Wei; Chen, Xue-Dong; Li, Qing; Xu, Chang

2009-01-01

A high-frequency ultrasonic transducer for copper or gold wire bonding has been designed, analyzed, prototyped and tested. Modeling techniques were used in the design phase and a practical design procedure was established and used. The transducer was decomposed into its elementary components. For each component, an initial design was obtained with simulations using a finite elements model (FEM). Simulated ultrasonic modules were built and characterized experimentally through the Laser Doppler Vibrometer (LDV) and electrical resonance spectra. Compared with experimental data, the FEM could be iteratively adjusted and updated. Having achieved a remarkably highly-predictive FEM of the whole transducer, the design parameters could be tuned for the desired applications, then the transducer is fixed on the wire bonder with a complete holder clamping was calculated by the FEM. The approach to mount ultrasonic transducers on wire bonding machines also is of major importance for wire bonding in modern electronic packaging. The presented method can lead to obtaining a nearly complete decoupling clamper design of the transducer to the wire bonder. PMID:22408564

LED light design method for high contrast and uniform illumination imaging in machine vision.

PubMed

Wu, Xiaojun; Gao, Guangming

2018-03-01

In machine vision, illumination is very critical to determine the complexity of the inspection algorithms. Proper lights can obtain clear and sharp images with the highest contrast and low noise between the interested object and the background, which is conducive to the target being located, measured, or inspected. Contrary to the empirically based trial-and-error convention to select the off-the-shelf LED light in machine vision, an optimization algorithm for LED light design is proposed in this paper. It is composed of the contrast optimization modeling and the uniform illumination technology for non-normal incidence (UINI). The contrast optimization model is built based on the surface reflection characteristics, e.g., the roughness, the reflective index, and light direction, etc., to maximize the contrast between the features of interest and the background. The UINI can keep the uniformity of the optimized lighting by the contrast optimization model. The simulation and experimental results demonstrate that the optimization algorithm is effective and suitable to produce images with the highest contrast and uniformity, which is very inspirational to the design of LED illumination systems in machine vision.

Fifth Graders' Learning About Simple Machines Through Engineering Design-Based Instruction Using LEGO™ Materials

NASA Astrophysics Data System (ADS)

Marulcu, Ismail; Barnett, Mike

2013-10-01

This study is part of a 5-year National Science Foundation-funded project, Transforming Elementary Science Learning Through LEGO™ Engineering Design. In this study, we report on the successes and challenges of implementing an engineering design-based and LEGO™-oriented unit in an urban classroom setting and we focus on the impact of the unit on students' content understanding of simple machines. The LEGO™ engineering-based simple machines module, which was developed for fifth graders by our research team, was implemented in an urban school in a large city in the Northeastern region of the USA. Thirty-three fifth grade students participated in the study, and they showed significant growth in content understanding. We measured students' content knowledge by using identical paper tests and semistructured interviews before and after instruction. Our paired t test analysis results showed that students significantly improved their test and interview scores (t = -3.62, p < 0.001 for multiple-choice items and t = -9.06, p < 0.000 for the open-ended items in the test and t = -12.11, p < 0.000 for the items in interviews). We also identified several alternative conceptions that are held by students on simple machines.

Structure prediction of boron-doped graphene by machine learning

NASA Astrophysics Data System (ADS)

M. Dieb, Thaer; Hou, Zhufeng; Tsuda, Koji

2018-06-01

Heteroatom doping has endowed graphene with manifold aspects of material properties and boosted its applications. The atomic structure determination of doped graphene is vital to understand its material properties. Motivated by the recently synthesized boron-doped graphene with relatively high concentration, here we employ machine learning methods to search the most stable structures of doped boron atoms in graphene, in conjunction with the atomistic simulations. From the determined stable structures, we find that in the free-standing pristine graphene, the doped boron atoms energetically prefer to substitute for the carbon atoms at different sublattice sites and that the para configuration of boron-boron pair is dominant in the cases of high boron concentrations. The boron doping can increase the work function of graphene by 0.7 eV for a boron content higher than 3.1%.

A novel diamond micro-/nano-machining process for the generation of hierarchical micro-/nano-structures

NASA Astrophysics Data System (ADS)

Zhu, Zhiwei; To, Suet; Ehmann, Kornel F.; Xiao, Gaobo; Zhu, Wule

2016-03-01

A new mechanical micro-/nano-machining process that combines rotary spatial vibrations (RSV) of a diamond tool and the servo motions of the workpiece is proposed and applied for the generation of multi-tier hierarchical micro-/nano-structures. In the proposed micro-/nano-machining system, the servo motion, as the primary cutting motion generated by a slow-tool-servo, is adopted for the fine generation of the primary surfaces with complex shapes. The RSV, as the tertiary cutting operation, is superimposed on the secondary fundamental rotary cutting motion to construct secondary nano-structures on the primary surface. Since the RSV system generally works at much higher frequencies and motion resolution than the primary and secondary motions, it leads to an inherent hierarchical cutting architecture. To investigate the machining performance, complex micro-/nano-structures were generated and explored by both numerical simulations and actual cutting tests. Rotary vibrations of the diamond tool at a constant rotational distance offer an inherent constant cutting velocity, leading to the ability for the generation of homogeneous micro-/nano-structures with fixed amplitudes and frequencies of the vibrations, even over large-scale surfaces. Furthermore, by deliberately combining the non-resonant three-axial vibrations and the servo motion, the generation of a variety of micro-/nano-structures with complex shapes and with flexibly tunable feature sizes can be achieved.

Investigation of Machine-ability of Inconel 800 in EDM with Coated Electrode

NASA Astrophysics Data System (ADS)

Karunakaran, K.; Chandrasekaran, M.

2017-03-01

The Inconel 800 is a high temperature application alloy which is classified as a nickel based super alloy. It has wide scope in aerospace engineering, gas Turbine etc. The machine-ability studies were found limited on this material. Hence This research focuses on machine-ability studies on EDM of Inconel 800 with Silver Coated Electrolyte Copper Electrode. The purpose of coating on electrode is to reduce tool wear. The factors pulse on Time, Pulse off Time and Peck Current were considered to observe the responses of surface roughness, material removal rate, tool wear rate. Taguchi Full Factorial Design is employed for Design the experiment. Some specific findings were reported and the percentage of contribution of each parameter was furnished

Materials and optimized designs for human-machine interfaces via epidermal electronics.

PubMed

Jeong, Jae-Woong; Yeo, Woon-Hong; Akhtar, Aadeel; Norton, James J S; Kwack, Young-Jin; Li, Shuo; Jung, Sung-Young; Su, Yewang; Lee, Woosik; Xia, Jing; Cheng, Huanyu; Huang, Yonggang; Choi, Woon-Seop; Bretl, Timothy; Rogers, John A

2013-12-17

Thin, soft, and elastic electronics with physical properties well matched to the epidermis can be conformally and robustly integrated with the skin. Materials and optimized designs for such devices are presented for surface electromyography (sEMG). The findings enable sEMG from wide ranging areas of the body. The measurements have quality sufficient for advanced forms of human-machine interface. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Principle of maximum entropy for reliability analysis in the design of machine components

NASA Astrophysics Data System (ADS)

Zhang, Yimin

2018-03-01

We studied the reliability of machine components with parameters that follow an arbitrary statistical distribution using the principle of maximum entropy (PME). We used PME to select the statistical distribution that best fits the available information. We also established a probability density function (PDF) and a failure probability model for the parameters of mechanical components using the concept of entropy and the PME. We obtained the first four moments of the state function for reliability analysis and design. Furthermore, we attained an estimate of the PDF with the fewest human bias factors using the PME. This function was used to calculate the reliability of the machine components, including a connecting rod, a vehicle half-shaft, a front axle, a rear axle housing, and a leaf spring, which have parameters that typically follow a non-normal distribution. Simulations were conducted for comparison. This study provides a design methodology for the reliability of mechanical components for practical engineering projects.

Structural Elements Regulating AAA+ Protein Quality Control Machines.

PubMed

Chang, Chiung-Wen; Lee, Sukyeong; Tsai, Francis T F

2017-01-01

Members of the ATPases Associated with various cellular Activities (AAA+) superfamily participate in essential and diverse cellular pathways in all kingdoms of life by harnessing the energy of ATP binding and hydrolysis to drive their biological functions. Although most AAA+ proteins share a ring-shaped architecture, AAA+ proteins have evolved distinct structural elements that are fine-tuned to their specific functions. A central question in the field is how ATP binding and hydrolysis are coupled to substrate translocation through the central channel of ring-forming AAA+ proteins. In this mini-review, we will discuss structural elements present in AAA+ proteins involved in protein quality control, drawing similarities to their known role in substrate interaction by AAA+ proteins involved in DNA translocation. Elements to be discussed include the pore loop-1, the Inter-Subunit Signaling (ISS) motif, and the Pre-Sensor I insert (PS-I) motif. Lastly, we will summarize our current understanding on the inter-relationship of those structural elements and propose a model how ATP binding and hydrolysis might be coupled to polypeptide translocation in protein quality control machines.

Loop shaping design for tracking performance in machine axes.

PubMed

Schinstock, Dale E; Wei, Zhouhong; Yang, Tao

2006-01-01

A modern interpretation of classical loop shaping control design methods is presented in the context of tracking control for linear motor stages. Target applications include noncontacting machines such as laser cutters and markers, water jet cutters, and adhesive applicators. The methods are directly applicable to the common PID controller and are pertinent to many electromechanical servo actuators other than linear motors. In addition to explicit design techniques a PID tuning algorithm stressing the importance of tracking is described. While the theory behind these techniques is not new, the analysis of their application to modern systems is unique in the research literature. The techniques and results should be important to control practitioners optimizing PID controller designs for tracking and in comparing results from classical designs to modern techniques. The methods stress high-gain controller design and interpret what this means for PID. Nothing in the methods presented precludes the addition of feedforward control methods for added improvements in tracking. Laboratory results from a linear motor stage demonstrate that with large open-loop gain very good tracking performance can be achieved. The resultant tracking errors compare very favorably to results from similar motions on similar systems that utilize much more complicated controllers.

Knowledge-based machine indexing from natural language text: Knowledge base design, development, and maintenance

NASA Technical Reports Server (NTRS)

Genuardi, Michael T.

1993-01-01

One strategy for machine-aided indexing (MAI) is to provide a concept-level analysis of the textual elements of documents or document abstracts. In such systems, natural-language phrases are analyzed in order to identify and classify concepts related to a particular subject domain. The overall performance of these MAI systems is largely dependent on the quality and comprehensiveness of their knowledge bases. These knowledge bases function to (1) define the relations between a controlled indexing vocabulary and natural language expressions; (2) provide a simple mechanism for disambiguation and the determination of relevancy; and (3) allow the extension of concept-hierarchical structure to all elements of the knowledge file. After a brief description of the NASA Machine-Aided Indexing system, concerns related to the development and maintenance of MAI knowledge bases are discussed. Particular emphasis is given to statistically-based text analysis tools designed to aid the knowledge base developer. One such tool, the Knowledge Base Building (KBB) program, presents the domain expert with a well-filtered list of synonyms and conceptually-related phrases for each thesaurus concept. Another tool, the Knowledge Base Maintenance (KBM) program, functions to identify areas of the knowledge base affected by changes in the conceptual domain (for example, the addition of a new thesaurus term). An alternate use of the KBM as an aid in thesaurus construction is also discussed.

Design and Strength check of Large Blow Molding Machine Rack

NASA Astrophysics Data System (ADS)

Fei-fei, GU; Zhi-song, ZHU; Xiao-zhao, YAN; Yi-min, ZHU

Design procedure of large blow moulding machine rack is discussed in the article. A strength checking method is presented. Finite element analysis is conducted in the design procedure by ANSYS software. The actual situation of the rack load bearing is fully considered. The necessary means to simplify the model are done. The dimensional linear element Beam 188 is analyzed. MESH200 is used to mesh. Therefore, it simplifies the analysis process and improves computational efficiency. The maximum deformation of rack is 8.037 mm: it is occurred in the position of accumulator head. The result states: it meets the national standard curvature which is not greater than 0.3% of the total channel length; it also meets strength requirement that the maximum stress was 54.112 MPa.

Apprentice Machine Theory Outline.

ERIC Educational Resources Information Center

Connecticut State Dept. of Education, Hartford. Div. of Vocational-Technical Schools.

This volume contains outlines for 16 courses in machine theory that are designed for machine tool apprentices. Addressed in the individual course outlines are the following topics: basic concepts; lathes; milling machines; drills, saws, and shapers; heat treatment and metallurgy; grinders; quality control; hydraulics and pneumatics;…

A machine for the preliminary investigation of design features influencing the wear behaviour of knee prostheses.

PubMed

McGloughlin, T M; Murphy, D M; Kavanagh, A G

2004-01-01

Degradation of tibial inserts in vivo has been found to be multifactorial in nature, resulting in a complex interaction of many variables. A range of kinematic conditions occurs at the tibio-femoral interface, giving rise to various degrees of rolling and sliding at this interface. The movement of the tibio-femoral contact point may be an influential factor in the overall wear of ultra-high molecular weight polyethylene (UHMWPE) tibial components. As part of this study a three-station wear-test machine was designed and built to investigate the influence of rolling and sliding on the wear behaviour of specific design aspects of contemporary knee prostheses. Using the machine, it is possible to monitor the effect of various slide roll ratios on the performance of contemporary bearing designs from a geometrical and materials perspective.

New computing systems and their impact on structural analysis and design

NASA Technical Reports Server (NTRS)

Noor, Ahmed K.

1989-01-01

A review is given of the recent advances in computer technology that are likely to impact structural analysis and design. The computational needs for future structures technology are described. The characteristics of new and projected computing systems are summarized. Advances in programming environments, numerical algorithms, and computational strategies for new computing systems are reviewed, and a novel partitioning strategy is outlined for maximizing the degree of parallelism. The strategy is designed for computers with a shared memory and a small number of powerful processors (or a small number of clusters of medium-range processors). It is based on approximating the response of the structure by a combination of symmetric and antisymmetric response vectors, each obtained using a fraction of the degrees of freedom of the original finite element model. The strategy was implemented on the CRAY X-MP/4 and the Alliant FX/8 computers. For nonlinear dynamic problems on the CRAY X-MP with four CPUs, it resulted in an order of magnitude reduction in total analysis time, compared with the direct analysis on a single-CPU CRAY X-MP machine.

Machine Learning Toolkit for Extreme Scale

DOE Office of Scientific and Technical Information (OSTI.GOV)

2014-03-31

Support Vector Machines (SVM) is a popular machine learning technique, which has been applied to a wide range of domains such as science, finance, and social networks for supervised learning. MaTEx undertakes the challenge of designing a scalable parallel SVM training algorithm for large scale systems, which includes commodity multi-core machines, tightly connected supercomputers and cloud computing systems. Several techniques are proposed for improved speed and memory space usage including adaptive and aggressive elimination of samples for faster convergence , and sparse format representation of data samples. Several heuristics for earliest possible to lazy elimination of non-contributing samples are consideredmore » in MaTEx. In many cases, where an early sample elimination might result in a false positive, low overhead mechanisms for reconstruction of key data structures are proposed. The proposed algorithm and heuristics are implemented and evaluated on various publicly available datasets« less

Distributed collaborative probabilistic design for turbine blade-tip radial running clearance using support vector machine of regression

NASA Astrophysics Data System (ADS)

Fei, Cheng-Wei; Bai, Guang-Chen

2014-12-01

To improve the computational precision and efficiency of probabilistic design for mechanical dynamic assembly like the blade-tip radial running clearance (BTRRC) of gas turbine, a distribution collaborative probabilistic design method-based support vector machine of regression (SR)(called as DCSRM) is proposed by integrating distribution collaborative response surface method and support vector machine regression model. The mathematical model of DCSRM is established and the probabilistic design idea of DCSRM is introduced. The dynamic assembly probabilistic design of aeroengine high-pressure turbine (HPT) BTRRC is accomplished to verify the proposed DCSRM. The analysis results reveal that the optimal static blade-tip clearance of HPT is gained for designing BTRRC, and improving the performance and reliability of aeroengine. The comparison of methods shows that the DCSRM has high computational accuracy and high computational efficiency in BTRRC probabilistic analysis. The present research offers an effective way for the reliability design of mechanical dynamic assembly and enriches mechanical reliability theory and method.

Reliability-based design optimization of reinforced concrete structures including soil-structure interaction using a discrete gravitational search algorithm and a proposed metamodel

NASA Astrophysics Data System (ADS)

Khatibinia, M.; Salajegheh, E.; Salajegheh, J.; Fadaee, M. J.

2013-10-01

A new discrete gravitational search algorithm (DGSA) and a metamodelling framework are introduced for reliability-based design optimization (RBDO) of reinforced concrete structures. The RBDO of structures with soil-structure interaction (SSI) effects is investigated in accordance with performance-based design. The proposed DGSA is based on the standard gravitational search algorithm (GSA) to optimize the structural cost under deterministic and probabilistic constraints. The Monte-Carlo simulation (MCS) method is considered as the most reliable method for estimating the probabilities of reliability. In order to reduce the computational time of MCS, the proposed metamodelling framework is employed to predict the responses of the SSI system in the RBDO procedure. The metamodel consists of a weighted least squares support vector machine (WLS-SVM) and a wavelet kernel function, which is called WWLS-SVM. Numerical results demonstrate the efficiency and computational advantages of DGSA and the proposed metamodel for RBDO of reinforced concrete structures.

A tubular hybrid Halbach/axially-magnetized permanent-magnet linear machine

NASA Astrophysics Data System (ADS)

Sui, Yi; Liu, Yong; Cheng, Luming; Liu, Jiaqi; Zheng, Ping

2017-05-01

A single-phase tubular permanent-magnet linear machine (PMLM) with hybrid Halbach/axially-magnetized PM arrays is proposed for free-piston Stirling power generation system. Machine topology and operating principle are elaborately illustrated. With the sinusoidal speed characteristic of the free-piston Stirling engine considered, the proposed machine is designed and calculated by finite-element analysis (FEA). The main structural parameters, such as outer radius of the mover, radial length of both the axially-magnetized PMs and ferromagnetic poles, axial length of both the middle and end radially-magnetized PMs, etc., are optimized to improve both the force capability and power density. Compared with the conventional PMLMs, the proposed machine features high mass and volume power density, and has the advantages of simple control and low converter cost. The proposed machine topology is applicable to tubular PMLMs with any phases.

DESIGN AND EVALUATION OF INDIVIDUAL ELEMENTS OF THE INTERFACE FOR AN AGRICULTURAL MACHINE.

PubMed

Rakhra, Aadesh K; Mann, Danny D

2018-01-29

If a user-centered approach is not used to design information displays, the quantity and quality of information presented to the user may not match the needs of the user, or it may exceed the capability of the human operator for processing and using that information. The result may be an excessive mental workload and reduced situation awareness of the operator, which can negatively affect the machine performance and operational outcomes. The increasing use of technology in agricultural machines may expose the human operator to excessive and undesirable information if the operator's information needs and information processing capabilities are ignored. In this study, a user-centered approach was used to design specific interface elements for an agricultural air seeder. Designs of the interface elements were evaluated in a laboratory environment by developing high-fidelity prototypes. Evaluations of the user interface elements yielded significant improvement in situation awareness (up to 11%; overall mean difference = 5.0 (4.8%), 95% CI (6.4728, 3.5939), p 0.0001). Mental workload was reduced by up to 19.7% (overall mean difference = -5.2 (-7.9%), n = 30, a = 0.05). Study participants rated the overall performance of the newly designed user-centered interface elements higher in comparison to the previous designs (overall mean difference = 27.3 (189.8%), 99% CI (35.150, 19.384), p 0.0001. Copyright© by the American Society of Agricultural Engineers.

Insert Design and Manufacturing for Foam-Core Composite Sandwich Structures

NASA Astrophysics Data System (ADS)

Lares, Alan

previous insert designs. A casting process for manufacturing the v.3 inserts was developed. The developed casting process, when producing more than 13 inserts, becomes more economical than machining. An exploratory study was conducted looking at the effects of dynamic loading on the v.3 insert performance. The results of this study highlighted areas for improving dynamic testing of foam-core sandwich structure inserts. Correlations were developed relating design variables such as face-sheet thickness and insert diameter to a failure load for different load cases. This was done through simulations using Computer Aided Engineering (CAE) software, and experimental testing. The resulting correlations were integrated into a computer program which outputs the required insert dimensions given a set of design parameters, and load values.

Design and application of the falling vertical sorting machine

NASA Astrophysics Data System (ADS)

Zuo, Ping; Peng, Tao; Yang, Hai

2018-04-01

In the process of tobacco production, it is necessary to pack the smoke according to the needs of different customers. A sorting machine is used to pick up the cigarette at present, there is a launch channel machine, a percussible vertical machine, But in the sorting process, the rolling channel machine is different in terms of the quality of smoke and the frictional force. It is difficult to ensure the location and posture of the belt sorting line, which causes the manipulator to not grasp. The strike type vertical machine is difficult to control the parallelism of the smoke. Now this team has developed a falling sorting machine, which has solved the smoke drop of a cigarette to the transmission belt. There will not be no code, can satisfy most of the different types of smoke sorting and no damage to smoke status. The dynamic characteristics such as the angular error of the opening and closing mechanism are carried out by ADAMS software. The simulation results show that the maximum angular error is 0.016rad. Through the test of the device, the goods falling speed is 7031/hour, the good of the falling position error within 2mm, meet the crawl accuracy requirements of the palletizing robot.

Application of high speed machining technology in aviation

NASA Astrophysics Data System (ADS)

Bałon, Paweł; Szostak, Janusz; Kiełbasa, Bartłomiej; Rejman, Edward; Smusz, Robert

2018-05-01

Aircraft structures are exposed to many loads during their working lifespan. Every particular action made during a flight is composed of a series of air movements which generate various aircraft loads. The most rigorous requirement which modern aircraft structures must fulfill is to maintain their high durability and reliability. This requirement involves taking many restrictions into account during the aircraft design process. The most important factor is the structure's overall mass, which has a crucial impact on both utility properties and cost-effectiveness. This makes aircraft one of the most complex results of modern technology. Additionally, there is currently an increasing utilization of high strength aluminum alloys, which requires the implementation of new manufacturing processes. High Speed Machining technology (HSM) is currently one of the most important machining technologies used in the aviation industry, especially in the machining of aluminium alloys. The primary difference between HSM and other milling techniques is the ability to select cutting parameters - depth of the cut layer, feed rate, and cutting speed in order to simultaneously ensure high quality, precision of the machined surface, and high machining efficiency, all of which shorten the manufacturing process of the integral components. In this paper, the authors explain the implementation of the HSM method in integral aircraft constructions. It presents the method of the airframe manufacturing method, and the final results. The HSM method is compared to the previous method where all subcomponents were manufactured by bending and forming processes, and then, they were joined by riveting.

Discovering charge density functionals and structure-property relationships with PROPhet: A general framework for coupling machine learning and first-principles methods

DOE PAGES

Kolb, Brian; Lentz, Levi C.; Kolpak, Alexie M.

2017-04-26

Modern ab initio methods have rapidly increased our understanding of solid state materials properties, chemical reactions, and the quantum interactions between atoms. However, poor scaling often renders direct ab initio calculations intractable for large or complex systems. There are two obvious avenues through which to remedy this problem: (i) develop new, less expensive methods to calculate system properties, or (ii) make existing methods faster. This paper describes an open source framework designed to pursue both of these avenues. PROPhet (short for PROPerty Prophet) utilizes machine learning techniques to find complex, non-linear mappings between sets of material or system properties. Themore » result is a single code capable of learning analytical potentials, non-linear density functionals, and other structure-property or property-property relationships. These capabilities enable highly accurate mesoscopic simulations, facilitate computation of expensive properties, and enable the development of predictive models for systematic materials design and optimization. Here, this work explores the coupling of machine learning to ab initio methods through means both familiar (e.g., the creation of various potentials and energy functionals) and less familiar (e.g., the creation of density functionals for arbitrary properties), serving both to demonstrate PROPhet’s ability to create exciting post-processing analysis tools and to open the door to improving ab initio methods themselves with these powerful machine learning techniques.« less

Discovering charge density functionals and structure-property relationships with PROPhet: A general framework for coupling machine learning and first-principles methods

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kolb, Brian; Lentz, Levi C.; Kolpak, Alexie M.

Modern ab initio methods have rapidly increased our understanding of solid state materials properties, chemical reactions, and the quantum interactions between atoms. However, poor scaling often renders direct ab initio calculations intractable for large or complex systems. There are two obvious avenues through which to remedy this problem: (i) develop new, less expensive methods to calculate system properties, or (ii) make existing methods faster. This paper describes an open source framework designed to pursue both of these avenues. PROPhet (short for PROPerty Prophet) utilizes machine learning techniques to find complex, non-linear mappings between sets of material or system properties. Themore » result is a single code capable of learning analytical potentials, non-linear density functionals, and other structure-property or property-property relationships. These capabilities enable highly accurate mesoscopic simulations, facilitate computation of expensive properties, and enable the development of predictive models for systematic materials design and optimization. Here, this work explores the coupling of machine learning to ab initio methods through means both familiar (e.g., the creation of various potentials and energy functionals) and less familiar (e.g., the creation of density functionals for arbitrary properties), serving both to demonstrate PROPhet’s ability to create exciting post-processing analysis tools and to open the door to improving ab initio methods themselves with these powerful machine learning techniques.« less

Literate Specification: Using Design Rationale To Support Formal Methods in the Development of Human-Machine Interfaces.

ERIC Educational Resources Information Center

Johnson, Christopher W.

1996-01-01

The development of safety-critical systems (aircraft cockpits and reactor control rooms) is qualitatively different from that of other interactive systems. These differences impose burdens on design teams that must ensure the development of human-machine interfaces. Analyzes strengths and weaknesses of formal methods for the design of user…

Structural design of morphing trailing edge actuated by SMA

NASA Astrophysics Data System (ADS)

Wang, Qi; Xu, Zhiwei; Zhu, Qian

2013-09-01

In this paper, the morphing trailing edge is designed to achieve the up and down deflection under the aerodynamic load. After a detailed and accurate computational analysis to determine the SMA specifications and layout programs, a solid model is created in CATIA and the structures of the morphing wing trailing edge are produced by CNC machining. A set of DSP measurement and control system is designed to accomplish the controlling experiment of the morphing wing trailing edge. At last, via the force analysis, the trailing edge is fabricated with four sections of aluminum alloy, and the arrangement scheme of SMA wires is determined. Experiment of precise control integral has been performed to survey the control effect. The experiment consists of deflection angle tests of the third joint and the integral structure. Primarily, the ultimate deflection angle is tested in these two experiments. Therefore, the controlling experiment of different angles could be performed within this range. The results show that the deflection error is less than 4%and response time is less than 6.7 s, the precise controlling of the morphing trailing edge is preliminary realized.

Integrated control-structure design

NASA Technical Reports Server (NTRS)

Hunziker, K. Scott; Kraft, Raymond H.; Bossi, Joseph A.

1991-01-01

A new approach for the design and control of flexible space structures is described. The approach integrates the structure and controller design processes thereby providing extra opportunities for avoiding some of the disastrous effects of control-structures interaction and for discovering new, unexpected avenues of future structural design. A control formulation based on Boyd's implementation of Youla parameterization is employed. Control design parameters are coupled with structural design variables to produce a set of integrated-design variables which are selected through optimization-based methodology. A performance index reflecting spacecraft mission goals and constraints is formulated and optimized with respect to the integrated design variables. Initial studies have been concerned with achieving mission requirements with a lighter, more flexible space structure. Details of the formulation of the integrated-design approach are presented and results are given from a study involving the integrated redesign of a flexible geostationary platform.

Technology and Jobs: Computer-Aided Design. Numerical-Control Machine-Tool Operators. Office Automation.

ERIC Educational Resources Information Center

Stanton, Michael; And Others

1985-01-01

Three reports on the effects of high technology on the nature of work include (1) Stanton on applications and implications of computer-aided design for engineers, drafters, and architects; (2) Nardone on the outlook and training of numerical-control machine tool operators; and (3) Austin and Drake on the future of clerical occupations in automated…

The Study of the Relationship between Probabilistic Design and Axiomatic Design Methodology. Volume 2

NASA Technical Reports Server (NTRS)

Onwubiko, Chin-Yere; Onyebueke, Landon

1996-01-01

The structural design, or the design of machine elements, has been traditionally based on deterministic design methodology. The deterministic method considers all design parameters to be known with certainty. This methodology is, therefore, inadequate to design complex structures that are subjected to a variety of complex, severe loading conditions. A nonlinear behavior that is dependent on stress, stress rate, temperature, number of load cycles, and time is observed on all components subjected to complex conditions. These complex conditions introduce uncertainties; hence, the actual factor of safety margin remains unknown. In the deterministic methodology, the contingency of failure is discounted; hence, there is a use of a high factor of safety. It may be most useful in situations where the design structures are simple. The probabilistic method is concerned with the probability of non-failure performance of structures or machine elements. It is much more useful in situations where the design is characterized by complex geometry, possibility of catastrophic failure, sensitive loads and material properties. Also included: Comparative Study of the use of AGMA Geometry Factors and Probabilistic Design Methodology in the Design of Compact Spur Gear Set.

Identifying Structural Flow Defects in Disordered Solids Using Machine-Learning Methods

NASA Astrophysics Data System (ADS)

Cubuk, E. D.; Schoenholz, S. S.; Rieser, J. M.; Malone, B. D.; Rottler, J.; Durian, D. J.; Kaxiras, E.; Liu, A. J.

2015-03-01

We use machine-learning methods on local structure to identify flow defects—or particles susceptible to rearrangement—in jammed and glassy systems. We apply this method successfully to two very different systems: a two-dimensional experimental realization of a granular pillar under compression and a Lennard-Jones glass in both two and three dimensions above and below its glass transition temperature. We also identify characteristics of flow defects that differentiate them from the rest of the sample. Our results show it is possible to discern subtle structural features responsible for heterogeneous dynamics observed across a broad range of disordered materials.

Architectures for intelligent machines

NASA Technical Reports Server (NTRS)

Saridis, George N.

1991-01-01

The theory of intelligent machines has been recently reformulated to incorporate new architectures that are using neural and Petri nets. The analytic functions of an intelligent machine are implemented by intelligent controls, using entropy as a measure. The resulting hierarchical control structure is based on the principle of increasing precision with decreasing intelligence. Each of the three levels of the intelligent control is using different architectures, in order to satisfy the requirements of the principle: the organization level is moduled after a Boltzmann machine for abstract reasoning, task planning and decision making; the coordination level is composed of a number of Petri net transducers supervised, for command exchange, by a dispatcher, which also serves as an interface to the organization level; the execution level, include the sensory, planning for navigation and control hardware which interacts one-to-one with the appropriate coordinators, while a VME bus provides a channel for database exchange among the several devices. This system is currently implemented on a robotic transporter, designed for space construction at the CIRSSE laboratories at the Rensselaer Polytechnic Institute. The progress of its development is reported.

High-intensity fibre laser design for micro-machining applications

NASA Astrophysics Data System (ADS)

Ortiz-Neria, D. I.; Martinez-Piñón, F.; Hernandez-Escamilla, H.; Alvarez-Chavez, J. A.

2010-11-01

This work is focused on the design of a 250W high-intensity continuous-wave fibre optic laser with a 15μm spot size beam and a beam parameter product (BPP) of 1.8 for its use on Laser-assisted Cold Spray process (LCS) in the micro-machining areas. The metal-powder deposition process LCS, is a novel method based on Cold Spray technique (CS) assisted by laser technology. The LCS accelerates metal powders by the use of a high-pressure gas in order to achieve flash welding of particles over substrate. In LCS, the critical velocity of impact is lower with respect with CS while the powder particle is heated before the deposition by a laser beam. Furthermore, LCS does not heat the powder to achieve high temperatures as it happens in plasma processes. This property puts aside cooling problems which normally happen in sintered processes with high oxygen/nitrogen concentration levels. LCS will be used not only in deposition of thin layers. After careful design, proof of concept, experimental data, and prototype development, it should be feasible to perform micro-machining precise work with the use of the highintensity fibre laser presented in this work, and selective deposition of particles, in a similar way to the well-known Direct Metal Laser Sintering process (DMLS). The fibre laser consists on a large-mode area, Yb3+-doped, semi-diffraction limited, 25-m fibre laser cavity, operating in continuous wave regime. The fibre shows an arguably high slope-efficiency with no signs of roll-over. The measured M2 value is 1.8 and doping concentration of 15000ppm. It was made with a slight modification of the traditional MCVD technique. A full optical characterization will be presented.

Structural and Sequence Similarity Makes a Significant Impact on Machine-Learning-Based Scoring Functions for Protein-Ligand Interactions.

PubMed

Li, Yang; Yang, Jianyi

2017-04-24

The prediction of protein-ligand binding affinity has recently been improved remarkably by machine-learning-based scoring functions. For example, using a set of simple descriptors representing the atomic distance counts, the RF-Score improves the Pearson correlation coefficient to about 0.8 on the core set of the PDBbind 2007 database, which is significantly higher than the performance of any conventional scoring function on the same benchmark. A few studies have been made to discuss the performance of machine-learning-based methods, but the reason for this improvement remains unclear. In this study, by systemically controlling the structural and sequence similarity between the training and test proteins of the PDBbind benchmark, we demonstrate that protein structural and sequence similarity makes a significant impact on machine-learning-based methods. After removal of training proteins that are highly similar to the test proteins identified by structure alignment and sequence alignment, machine-learning-based methods trained on the new training sets do not outperform the conventional scoring functions any more. On the contrary, the performance of conventional functions like X-Score is relatively stable no matter what training data are used to fit the weights of its energy terms.

The paradigm compiler: Mapping a functional language for the connection machine

NASA Technical Reports Server (NTRS)

Dennis, Jack B.

1989-01-01

The Paradigm Compiler implements a new approach to compiling programs written in high level languages for execution on highly parallel computers. The general approach is to identify the principal data structures constructed by the program and to map these structures onto the processing elements of the target machine. The mapping is chosen to maximize performance as determined through compile time global analysis of the source program. The source language is Sisal, a functional language designed for scientific computations, and the target language is Paris, the published low level interface to the Connection Machine. The data structures considered are multidimensional arrays whose dimensions are known at compile time. Computations that build such arrays usually offer opportunities for highly parallel execution; they are data parallel. The Connection Machine is an attractive target for these computations, and the parallel for construct of the Sisal language is a convenient high level notation for data parallel algorithms. The principles and organization of the Paradigm Compiler are discussed.

Creation of smart composites using an embroidery machine

NASA Astrophysics Data System (ADS)

Torii, Nobuhiro; Oka, Kosuke; Ikeda, Tadashige

2016-04-01

A smart composite with functional fibers and reinforcement fibers optimally placed with an embroidery machine was created. Fiber orientation affects mechanical properties of composite laminates significantly. Accordingly, if the fibers can be placed along a desired curved path, fiber reinforced plastic (FRP) structures can be designed more lightly and more sophisticatedly. To this end a tailored fiber placement method using the embroidery machine have been studied. To add functions to the FRP structures, shape memory alloy (SMA) wires were placed as functional fibers. First, for a certain purpose the paths of the reinforcement fibers and the SMA wires were simultaneously optimized in analysis. Next, the reinforcement fibers and tubes with the SMA wires were placed on fabrics by using the embroidery machine and this fabric was impregnated with resin by using the vacuum assisted resin transfer molding method. This smart composite was activated by applying voltage to the SMA wires. Fundamental properties of the smart composite were examined and the feasibility of the proposed creation method was shown.

A Simple Universal Turing Machine for the Game of Life Turing Machine

NASA Astrophysics Data System (ADS)

Rendell, Paul

In this chapter we present a simple universal Turing machine which is small enough to fit into the design limits of the Turing machine build in Conway's Game of Life by the author. That limit is 8 symbols and 16 states. By way of comparison we also describe one of the smallest known universal Turing machines due to Rogozhin which has 6 symbols and 4 states.

Designing Semiconductor Heterostructures Using Digitally Accessible Electronic-Structure Data

NASA Astrophysics Data System (ADS)

Shapera, Ethan; Schleife, Andre

Semiconductor sandwich structures, so-called heterojunctions, are at the heart of modern applications with tremendous societal impact: Light-emitting diodes shape the future of lighting and solar cells are promising for renewable energy. However, their computer-based design is hampered by the high cost of electronic structure techniques used to select materials based on alignment of valence and conduction bands and to evaluate excited state properties. We describe, validate, and demonstrate an open source Python framework which rapidly screens existing online databases and user-provided data to find combinations of suitable, previously fabricated materials for optoelectronic applications. The branch point energy aligns valence and conduction bands of different materials, requiring only the bulk density functional theory band structure. We train machine learning algorithms to predict the dielectric constant, electron mobility, and hole mobility with material descriptors available in online databases. Using CdSe and InP as emitting layers for LEDs and CH3NH3PbI3 and nanoparticle PbS as absorbers for solar cells, we demonstrate our broadly applicable, automated method.

Field precision machining technology of target chamber in ICF lasers

NASA Astrophysics Data System (ADS)

Xu, Yuanli; Wu, Wenkai; Shi, Sucun; Duan, Lin; Chen, Gang; Wang, Baoxu; Song, Yugang; Liu, Huilin; Zhu, Mingzhi

2016-10-01

In ICF lasers, many independent laser beams are required to be positioned on target with a very high degree of accuracy during a shot. The target chamber provides a precision platform and datum reference for final optics assembly and target collimation and location system. The target chamber consists of shell with welded flanges, reinforced concrete pedestal, and lateral support structure. The field precision machining technology of target chamber in ICF lasers have been developed based on ShenGuangIII (SGIII). The same center of the target chamber is adopted in the process of design, fabrication, and alignment. The technologies of beam collimation and datum reference transformation are developed for the fabrication, positioning and adjustment of target chamber. A supporting and rotating mechanism and a special drilling machine are developed to bore the holes of ports. An adjustment mechanism is designed to accurately position the target chamber. In order to ensure the collimation requirements of the beam leading and focusing and the target positioning, custom-machined spacers are used to accurately correct the alignment error of the ports. Finally, this paper describes the chamber center, orientation, and centering alignment error measurements of SGIII. The measurements show the field precision machining of SGIII target chamber meet its design requirement. These information can be used on similar systems.

Machine vision systems using machine learning for industrial product inspection

NASA Astrophysics Data System (ADS)

Lu, Yi; Chen, Tie Q.; Chen, Jie; Zhang, Jian; Tisler, Anthony

2002-02-01

Machine vision inspection requires efficient processing time and accurate results. In this paper, we present a machine vision inspection architecture, SMV (Smart Machine Vision). SMV decomposes a machine vision inspection problem into two stages, Learning Inspection Features (LIF), and On-Line Inspection (OLI). The LIF is designed to learn visual inspection features from design data and/or from inspection products. During the OLI stage, the inspection system uses the knowledge learnt by the LIF component to inspect the visual features of products. In this paper we will present two machine vision inspection systems developed under the SMV architecture for two different types of products, Printed Circuit Board (PCB) and Vacuum Florescent Displaying (VFD) boards. In the VFD board inspection system, the LIF component learns inspection features from a VFD board and its displaying patterns. In the PCB board inspection system, the LIF learns the inspection features from the CAD file of a PCB board. In both systems, the LIF component also incorporates interactive learning to make the inspection system more powerful and efficient. The VFD system has been deployed successfully in three different manufacturing companies and the PCB inspection system is the process of being deployed in a manufacturing plant.

Machine-Learned Data Structures of Lipid Marker Serum Concentrations in Multiple Sclerosis Patients Differ from Those in Healthy Subjects.

PubMed

Lötsch, Jörn; Thrun, Michael; Lerch, Florian; Brunkhorst, Robert; Schiffmann, Susanne; Thomas, Dominique; Tegder, Irmgard; Geisslinger, Gerd; Ultsch, Alfred

2017-06-07

Lipid metabolism has been suggested to be a major pathophysiological mechanism of multiple sclerosis (MS). With the increasing knowledge about lipid signaling, acquired data become increasingly complex making bioinformatics necessary in lipid research. We used unsupervised machine-learning to analyze lipid marker serum concentrations, pursuing the hypothesis that for the most relevant markers the emerging data structures will coincide with the diagnosis of MS. Machine learning was implemented as emergent self-organizing feature maps (ESOM) combined with the U*-matrix visualization technique. The data space consisted of serum concentrations of three main classes of lipid markers comprising eicosanoids ( d = 11 markers), ceramides ( d = 10), and lyosophosphatidic acids ( d = 6). They were analyzed in cohorts of MS patients ( n = 102) and healthy subjects ( n = 301). Clear data structures in the high-dimensional data space were observed in eicosanoid and ceramides serum concentrations whereas no clear structure could be found in lysophosphatidic acid concentrations. With ceramide concentrations, the structures that had emerged from unsupervised machine-learning almost completely overlapped with the known grouping of MS patients versus healthy subjects. This was only partly provided by eicosanoid serum concentrations. Thus, unsupervised machine-learning identified distinct data structures of bioactive lipid serum concentrations. These structures could be superimposed with the known grouping of MS patients versus healthy subjects, which was almost completely possible with ceramides. Therefore, based on the present analysis, ceramides are first-line candidates for further exploration as drug-gable targets or biomarkers in MS.

Machine-Learned Data Structures of Lipid Marker Serum Concentrations in Multiple Sclerosis Patients Differ from Those in Healthy Subjects

PubMed Central

Lötsch, Jörn; Thrun, Michael; Lerch, Florian; Brunkhorst, Robert; Schiffmann, Susanne; Thomas, Dominique; Tegder, Irmgard; Geisslinger, Gerd; Ultsch, Alfred

2017-01-01

Lipid signaling has been suggested to be a major pathophysiological mechanism of multiple sclerosis (MS). With the increasing knowledge about lipid signaling, acquired data become increasingly complex making bioinformatics necessary in lipid research. We used unsupervised machine-learning to analyze lipid marker serum concentrations, pursuing the hypothesis that for the most relevant markers the emerging data structures will coincide with the diagnosis of MS. Machine learning was implemented as emergent self-organizing feature maps (ESOM) combined with the U*-matrix visualization technique. The data space consisted of serum concentrations of three main classes of lipid markers comprising eicosanoids (d = 11 markers), ceramides (d = 10), and lyosophosphatidic acids (d = 6). They were analyzed in cohorts of MS patients (n = 102) and healthy subjects (n = 301). Clear data structures in the high-dimensional data space were observed in eicosanoid and ceramides serum concentrations whereas no clear structure could be found in lysophosphatidic acid concentrations. With ceramide concentrations, the structures that had emerged from unsupervised machine-learning almost completely overlapped with the known grouping of MS patients versus healthy subjects. This was only partly provided by eicosanoid serum concentrations. Thus, unsupervised machine-learning identified distinct data structures of bioactive lipid serum concentrations. These structures could be superimposed with the known grouping of MS patients versus healthy subjects, which was almost completely possible with ceramides. Therefore, based on the present analysis, ceramides are first-line candidates for further exploration as drug-gable targets or biomarkers in MS. PMID:28590455

High speed operation of permanent magnet machines

NASA Astrophysics Data System (ADS)

El-Refaie, Ayman M.

This work proposes methods to extend the high-speed operating capabilities of both the interior PM (IPM) and surface PM (SPM) machines. For interior PM machines, this research has developed and presented the first thorough analysis of how a new bi-state magnetic material can be usefully applied to the design of IPM machines. Key elements of this contribution include identifying how the unique properties of the bi-state magnetic material can be applied most effectively in the rotor design of an IPM machine by "unmagnetizing" the magnet cavity center posts rather than the outer bridges. The importance of elevated rotor speed in making the best use of the bi-state magnetic material while recognizing its limitations has been identified. For surface PM machines, this research has provided, for the first time, a clear explanation of how fractional-slot concentrated windings can be applied to SPM machines in order to achieve the necessary conditions for optimal flux weakening. A closed-form analytical procedure for analyzing SPM machines designed with concentrated windings has been developed. Guidelines for designing SPM machines using concentrated windings in order to achieve optimum flux weakening are provided. Analytical and numerical finite element analysis (FEA) results have provided promising evidence of the scalability of the concentrated winding technique with respect to the number of poles, machine aspect ratio, and output power rating. Useful comparisons between the predicted performance characteristics of SPM machines equipped with concentrated windings and both SPM and IPM machines designed with distributed windings are included. Analytical techniques have been used to evaluate the impact of the high pole number on various converter performance metrics. Both analytical techniques and FEA have been used for evaluating the eddy-current losses in the surface magnets due to the stator winding subharmonics. Techniques for reducing these losses have been

Selection of Wire Electrical Discharge Machining Process Parameters on Stainless Steel AISI Grade-304 using Design of Experiments Approach

NASA Astrophysics Data System (ADS)

Lingadurai, K.; Nagasivamuni, B.; Muthu Kamatchi, M.; Palavesam, J.

2012-06-01

Wire electrical discharge machining (WEDM) is a specialized thermal machining process capable of accurately machining parts of hard materials with complex shapes. Parts having sharp edges that pose difficulties to be machined by the main stream machining processes can be easily machined by WEDM process. Design of Experiments approach (DOE) has been reported in this work for stainless steel AISI grade-304 which is used in cryogenic vessels, evaporators, hospital surgical equipment, marine equipment, fasteners, nuclear vessels, feed water tubing, valves, refrigeration equipment, etc., is machined by WEDM with brass wire electrode. The DOE method is used to formulate the experimental layout, to analyze the effect of each parameter on the machining characteristics, and to predict the optimal choice for each WEDM parameter such as voltage, pulse ON, pulse OFF and wire feed. It is found that these parameters have a significant influence on machining characteristic such as metal removal rate (MRR), kerf width and surface roughness (SR). The analysis of the DOE reveals that, in general the pulse ON time significantly affects the kerf width and the wire feed rate affects SR, while, the input voltage mainly affects the MRR.

Using support vector machines to improve elemental ion identification in macromolecular crystal structures

DOE Office of Scientific and Technical Information (OSTI.GOV)

Morshed, Nader; Lawrence Berkeley National Laboratory, Berkeley, CA 94720; Echols, Nathaniel, E-mail: nechols@lbl.gov

2015-05-01

A method to automatically identify possible elemental ions in X-ray crystal structures has been extended to use support vector machine (SVM) classifiers trained on selected structures in the PDB, with significantly improved sensitivity over manually encoded heuristics. In the process of macromolecular model building, crystallographers must examine electron density for isolated atoms and differentiate sites containing structured solvent molecules from those containing elemental ions. This task requires specific knowledge of metal-binding chemistry and scattering properties and is prone to error. A method has previously been described to identify ions based on manually chosen criteria for a number of elements. Here,more » the use of support vector machines (SVMs) to automatically classify isolated atoms as either solvent or one of various ions is described. Two data sets of protein crystal structures, one containing manually curated structures deposited with anomalous diffraction data and another with automatically filtered, high-resolution structures, were constructed. On the manually curated data set, an SVM classifier was able to distinguish calcium from manganese, zinc, iron and nickel, as well as all five of these ions from water molecules, with a high degree of accuracy. Additionally, SVMs trained on the automatically curated set of high-resolution structures were able to successfully classify most common elemental ions in an independent validation test set. This method is readily extensible to other elemental ions and can also be used in conjunction with previous methods based on a priori expectations of the chemical environment and X-ray scattering.« less

[Design and application of medical electric leg-raising machine].

PubMed

Liang, Jintang; Chen, Jinyuan; Zhao, Zixian; Lin, Jinfeng; Li, Juanhong; Zhong, Jingliang

2017-08-01

Passive leg raising is widely used in clinic, but it lacks of specialized mechanical raise equipment. It requires medical staff to raise leg by hand or requires a multi-functional bed to raise leg, which takes time and effort. Therefore we have developed a new medical electric leg-raising machine. The equipment has the following characteristics: simple structure, stable performance, easy operation, fast and effective, safe and comfortable. The height range of the lifter is 50-120 cm, the range of the angle of raising leg is 10degree angle-80degree angle, the maximum supporting weight is 40 kg. Because of raising the height of the lower limbs and making precise angle, this equipment can completely replace the traditional manner of lifting leg by hand with multi-functional bed to lift patients' leg and can reduce the physical exhaustion and time consumption of medical staff. It can change the settings at any time to meet the needs of the patient; can be applied to the testing of PLR and dynamically assessing the hemodynamics; can prevent deep vein thrombosis and some related complications of staying in bed; and the machine is easy to be cleaned and disinfected, which can effectively avoid hospital acquired infection and cross infection; and can also be applied to emergency rescue of various disasters and emergencies.

Discriminative analysis of schizophrenia using support vector machine and recursive feature elimination on structural MRI images.

PubMed

Lu, Xiaobing; Yang, Yongzhe; Wu, Fengchun; Gao, Minjian; Xu, Yong; Zhang, Yue; Yao, Yongcheng; Du, Xin; Li, Chengwei; Wu, Lei; Zhong, Xiaomei; Zhou, Yanling; Fan, Ni; Zheng, Yingjun; Xiong, Dongsheng; Peng, Hongjun; Escudero, Javier; Huang, Biao; Li, Xiaobo; Ning, Yuping; Wu, Kai

2016-07-01

Structural abnormalities in schizophrenia (SZ) patients have been well documented with structural magnetic resonance imaging (MRI) data using voxel-based morphometry (VBM) and region of interest (ROI) analyses. However, these analyses can only detect group-wise differences and thus, have a poor predictive value for individuals. In the present study, we applied a machine learning method that combined support vector machine (SVM) with recursive feature elimination (RFE) to discriminate SZ patients from normal controls (NCs) using their structural MRI data. We first employed both VBM and ROI analyses to compare gray matter volume (GMV) and white matter volume (WMV) between 41 SZ patients and 42 age- and sex-matched NCs. The method of SVM combined with RFE was used to discriminate SZ patients from NCs using significant between-group differences in both GMV and WMV as input features. We found that SZ patients showed GM and WM abnormalities in several brain structures primarily involved in the emotion, memory, and visual systems. An SVM with a RFE classifier using the significant structural abnormalities identified by the VBM analysis as input features achieved the best performance (an accuracy of 88.4%, a sensitivity of 91.9%, and a specificity of 84.4%) in the discriminative analyses of SZ patients. These results suggested that distinct neuroanatomical profiles associated with SZ patients might provide a potential biomarker for disease diagnosis, and machine-learning methods can reveal neurobiological mechanisms in psychiatric diseases.

Design local exhaust ventilation on sieve machine at PT.Perkebunan Nusantara VIII Ciater using design for assembly (DFA) approach with Boothroyd and Dewhurst method

NASA Astrophysics Data System (ADS)

Khalqihi, K. I.; Rahayu, M.; Rendra, M.

2017-12-01

PT Perkebunan Nusantara VIII Ciater is a company produced black tea orthodox more or less 4 tons every day. At the production section, PT Perkebunan Nusantara VIII will use local exhaust ventilation specially at sortation area on sieve machine. To maintain the quality of the black tea orthodox, all machine must be scheduled for maintenance every once a month and takes time 2 hours in workhours, with additional local exhaust ventilation, it will increase time for maintenance process, if maintenance takes time more than 2 hours it will caused production process delayed. To support maintenance process in PT Perkebunan Nusantara VIII Ciater, designing local exhaust ventilation using design for assembly approach with Boothroyd and Dewhurst method, design for assembly approach is choosen to simplify maintenance process which required assembly process. There are 2 LEV designs for this research. Design 1 with 94 components, assembly time 647.88 seconds and assembly efficiency level 23.62%. Design 2 with 82 components, assembly time 567.84 seconds and assembly efficiency level 24.83%. Design 2 is choosen for this research based on DFA goals, minimum total part that use, optimization assembly time, and assembly efficiency level.

Structural health monitoring for bolt loosening via a non-invasive vibro-haptics human-machine cooperative interface

NASA Astrophysics Data System (ADS)

Pekedis, Mahmut; Mascerañas, David; Turan, Gursoy; Ercan, Emre; Farrar, Charles R.; Yildiz, Hasan

2015-08-01

For the last two decades, developments in damage detection algorithms have greatly increased the potential for autonomous decisions about structural health. However, we are still struggling to build autonomous tools that can match the ability of a human to detect and localize the quantity of damage in structures. Therefore, there is a growing interest in merging the computational and cognitive concepts to improve the solution of structural health monitoring (SHM). The main object of this research is to apply the human-machine cooperative approach on a tower structure to detect damage. The cooperation approach includes haptic tools to create an appropriate collaboration between SHM sensor networks, statistical compression techniques and humans. Damage simulation in the structure is conducted by releasing some of the bolt loads. Accelerometers are bonded to various locations of the tower members to acquire the dynamic response of the structure. The obtained accelerometer results are encoded in three different ways to represent them as a haptic stimulus for the human subjects. Then, the participants are subjected to each of these stimuli to detect the bolt loosened damage in the tower. Results obtained from the human-machine cooperation demonstrate that the human subjects were able to recognize the damage with an accuracy of 88 ± 20.21% and response time of 5.87 ± 2.33 s. As a result, it is concluded that the currently developed human-machine cooperation SHM may provide a useful framework to interact with abstract entities such as data from a sensor network.

Design and analysis of a 3D-flux flux-switching permanent magnet machine with SMC cores and ferrite magnets

NASA Astrophysics Data System (ADS)

Liu, Chengcheng; Wang, Youhua; Lei, Gang; Guo, Youguang; Zhu, Jianguo

2017-05-01

Since permanent magnets (PM) are stacked between the adjacent stator teeth and there are no windings or PMs on the rotor, flux-switching permanent magnet machine (FSPMM) owns the merits of good flux concentrating and robust rotor structure. Compared with the traditional PM machines, FSPMM can provide higher torque density and better thermal dissipation ability. Combined with the soft magnetic composite (SMC) material and ferrite magnets, this paper proposes a new 3D-flux FSPMM (3DFFSPMM). The topology and operation principle are introduced. It can be found that the designed new 3DFFSPMM has many merits over than the traditional FSPMM for it can utilize the advantages of SMC material. Moreover, the PM flux of this new motor can be regulated by using the mechanical method. 3D finite element method (FEM) is used to calculate the magnetic field and parameters of the motor, such as flux density, inductance, PM flux linkage and efficiency map. The demagnetization analysis of the ferrite magnet is also addressed to ensure the safety operation of the proposed motor.

X-Ray Backscatter Machine Support Frame

NASA Technical Reports Server (NTRS)

Cannon, Brooke

2010-01-01

This summer at Kennedy Space Center, I spent 10 weeks as an intern working at the Prototype Development Lab. During this time I learned about the design and machining done here at NASA. I became familiar with the process from where a design begins in Pro/Engineer and finishes at the hands of the machinists. As an intern I was given various small jobs to do and then one project of my own. My personal project was a job for the Applied Physics Lab; in their work they use an X-Ray Backscatter machine. Previously it was resting atop a temporary frame that limited the use of the machine. My job was to design a frame for the machine to rest upon that would allow a full range of sample sizes. The frame was required to support the machine and provide a strain relief for the cords attached to the machine as it moved in the x and y directions. Calculations also had to be done to be sure the design would be able to withstand any loads or outside sources of stress. After the calculations proved the design to be ready to withstand the requirements, the parts were ordered or fabricated, as required. This helped me understand the full process of jobs sent to the Prototype Development Lab.

Design of Human-Machine Interface and altering of pelvic obliquity with RGR Trainer.

PubMed

Pietrusinski, Maciej; Unluhisarcikli, Ozer; Mavroidis, Constantinos; Cajigas, Iahn; Bonato, Paolo

2011-01-01

The Robotic Gait Rehabilitation (RGR) Trainer targets secondary gait deviations in stroke survivors undergoing rehabilitation. Using an impedance control strategy and a linear electromagnetic actuator, the device generates a force field to control pelvic obliquity through a Human-Machine Interface (i.e. a lower body exoskeleton). Herein we describe the design of the RGR Trainer Human-Machine Interface (HMI) and we demonstrate the system's ability to alter the pattern of movement of the pelvis during gait in a healthy subject. Results are shown for experiments during which we induced hip-hiking - in healthy subjects. Our findings indicate that the RGR Trainer has the ability of affecting pelvic obliquity during gait. Furthermore, we provide preliminary evidence of short-term retention of the modified pelvic obliquity pattern induced by the RGR Trainer. © 2011 IEEE

Vane Pump Casing Machining of Dumpling Machine Based on CAD/CAM

NASA Astrophysics Data System (ADS)

Huang, Yusen; Li, Shilong; Li, Chengcheng; Yang, Zhen

Automatic dumpling forming machine is also called dumpling machine, which makes dumplings through mechanical motions. This paper adopts the stuffing delivery mechanism featuring the improved and specially-designed vane pump casing, which can contribute to the formation of dumplings. Its 3D modeling in Pro/E software, machining process planning, milling path optimization, simulation based on UG and compiling post program were introduced and verified. The results indicated that adoption of CAD/CAM offers firms the potential to pursue new innovative strategies.

New tool holder design for cryogenic machining of Ti6Al4V

NASA Astrophysics Data System (ADS)

Bellin, Marco; Sartori, Stefano; Ghiotti, Andrea; Bruschi, Stefania

2017-10-01

The renewed demand of increasing the machinability of the Ti6Al4V titanium alloy to produce biomedical and aerospace parts working at high temperature has recently led to the application of low-temperature coolants instead of conventional cutting fluids to increase both the tool life and the machined surface integrity. In particular, the liquid nitrogen directed to the tool rake face has shown a great capability of reducing the temperature at the chip-tool interface, as well as the chemical interaction between the tool coating and the titanium to be machined, therefore limiting the tool crater wear, and improving, at the same time, the chip breakability. Furthermore, the nitrogen is a safe, non-harmful, non-corrosive, odorless, recyclable, non-polluting and abundant gas, characteristics that further qualify it as an environmental friendly coolant to be applied to machining processes. However, the behavior of the system composed by the tool and the tool holder, exposed to the cryogenics temperatures may represent a critical issue in order to obtain components within the required geometrical tolerances. On this basis, the paper aims at presenting the design of an innovative tool holder installed on a CNC lathe, which includes the cryogenic coolant provision system, and which is able to hinder the part possible distortions due to the liquid nitrogen adduction by stabilizing its dimensions through the use of heating cartridges and appropriate sensors to monitor the temperature evolution of the tool holder.

Design and analysis of an unconventional permanent magnet linear machine for energy harvesting

NASA Astrophysics Data System (ADS)

Zeng, Peng

This Ph.D. dissertation proposes an unconventional high power density linear electromagnetic kinetic energy harvester, and a high-performance two-stage interface power electronics to maintain maximum power abstraction from the energy source and charge the Li-ion battery load with constant current. The proposed machine architecture is composed of a double-sided flat type silicon steel stator with winding slots, a permanent magnet mover, coil windings, a linear motion guide and an adjustable spring bearing. The unconventional design of the machine is that NdFeB magnet bars in the mover are placed with magnetic fields in horizontal direction instead of vertical direction and the same magnetic poles are facing each other. The derived magnetic equivalent circuit model proves the average air-gap flux density of the novel topology is as high as 0.73 T with 17.7% improvement over that of the conventional topology at the given geometric dimensions of the proof-of-concept machine. Subsequently, the improved output voltage and power are achieved. The dynamic model of the linear generator is also developed, and the analytical equations of output maximum power are derived for the case of driving vibration with amplitude that is equal, smaller and larger than the relative displacement between the mover and the stator of the machine respectively. Furthermore, the finite element analysis (FEA) model has been simulated to prove the derived analytical results and the improved power generation capability. Also, an optimization framework is explored to extend to the multi-Degree-of-Freedom (n-DOF) vibration based linear energy harvesting devices. Moreover, a boost-buck cascaded switch mode converter with current controller is designed to extract the maximum power from the harvester and charge the Li-ion battery with trickle current. Meanwhile, a maximum power point tracking (MPPT) algorithm is proposed and optimized for low frequency driving vibrations. Finally, a proof

Design and Implementation of a Hypothermic Machine Perfusion Device for Clinical Preservation of Isolated Organs

PubMed Central

Shen, Fei; Yan, Ruqiang

2017-01-01

The imbalance between limited organ supply and huge potential need has hindered the development of organ-graft techniques. In this paper a low-cost hypothermic machine perfusion (HMP) device is designed and implemented to maintain suitable preservation surroundings and extend the survival life of isolated organs. Four necessary elements (the machine perfusion, the physiological parameter monitoring, the thermostatic control and the oxygenation apparatus) involved in this HMP device are introduced. Especially during the thermostatic control process, a modified Bayes estimation, which introduces the concept of improvement factor, is realized to recognize and reduce the possible measurement errors resulting from sensor faults and noise interference. Also, a fuzzy-PID controller contributes to improve the accuracy and reduces the computational load using the DSP. Our experiments indicate that the reliability of the instrument meets the design requirements, thus being appealing for potential clinical preservation applications. PMID:28587173

Amp: A modular approach to machine learning in atomistic simulations

NASA Astrophysics Data System (ADS)

Khorshidi, Alireza; Peterson, Andrew A.

2016-10-01

Electronic structure calculations, such as those employing Kohn-Sham density functional theory or ab initio wavefunction theories, have allowed for atomistic-level understandings of a wide variety of phenomena and properties of matter at small scales. However, the computational cost of electronic structure methods drastically increases with length and time scales, which makes these methods difficult for long time-scale molecular dynamics simulations or large-sized systems. Machine-learning techniques can provide accurate potentials that can match the quality of electronic structure calculations, provided sufficient training data. These potentials can then be used to rapidly simulate large and long time-scale phenomena at similar quality to the parent electronic structure approach. Machine-learning potentials usually take a bias-free mathematical form and can be readily developed for a wide variety of systems. Electronic structure calculations have favorable properties-namely that they are noiseless and targeted training data can be produced on-demand-that make them particularly well-suited for machine learning. This paper discusses our modular approach to atomistic machine learning through the development of the open-source Atomistic Machine-learning Package (Amp), which allows for representations of both the total and atom-centered potential energy surface, in both periodic and non-periodic systems. Potentials developed through the atom-centered approach are simultaneously applicable for systems with various sizes. Interpolation can be enhanced by introducing custom descriptors of the local environment. We demonstrate this in the current work for Gaussian-type, bispectrum, and Zernike-type descriptors. Amp has an intuitive and modular structure with an interface through the python scripting language yet has parallelizable fortran components for demanding tasks; it is designed to integrate closely with the widely used Atomic Simulation Environment (ASE), which

Developing Parametric Models for the Assembly of Machine Fixtures for Virtual Multiaxial CNC Machining Centers

NASA Astrophysics Data System (ADS)

Balaykin, A. V.; Bezsonov, K. A.; Nekhoroshev, M. V.; Shulepov, A. P.

2018-01-01

This paper dwells upon a variance parameterization method. Variance or dimensional parameterization is based on sketching, with various parametric links superimposed on the sketch objects and user-imposed constraints in the form of an equation system that determines the parametric dependencies. This method is fully integrated in a top-down design methodology to enable the creation of multi-variant and flexible fixture assembly models, as all the modeling operations are hierarchically linked in the built tree. In this research the authors consider a parameterization method of machine tooling used for manufacturing parts using multiaxial CNC machining centers in the real manufacturing process. The developed method allows to significantly reduce tooling design time when making changes of a part’s geometric parameters. The method can also reduce time for designing and engineering preproduction, in particular, for development of control programs for CNC equipment and control and measuring machines, automate the release of design and engineering documentation. Variance parameterization helps to optimize construction of parts as well as machine tooling using integrated CAE systems. In the framework of this study, the authors demonstrate a comprehensive approach to parametric modeling of machine tooling in the CAD package used in the real manufacturing process of aircraft engines.

Adaptive machine and its thermodynamic costs

NASA Astrophysics Data System (ADS)

Allahverdyan, Armen E.; Wang, Q. A.

2013-03-01

We study the minimal thermodynamically consistent model for an adaptive machine that transfers particles from a higher chemical potential reservoir to a lower one. This model describes essentials of the inhomogeneous catalysis. It is supposed to function with the maximal current under uncertain chemical potentials: if they change, the machine tunes its own structure fitting it to the maximal current under new conditions. This adaptation is possible under two limitations: (i) The degree of freedom that controls the machine's structure has to have a stored energy (described via a negative temperature). The origin of this result is traced back to the Le Chatelier principle. (ii) The machine has to malfunction at a constant environment due to structural fluctuations, whose relative magnitude is controlled solely by the stored energy. We argue that several features of the adaptive machine are similar to those of living organisms (energy storage, aging).

Complex Approach to Conceptual Design of Machine Mechanically Extracting Oil from Jatropha curcas L. Seeds for Biomass-Based Fuel Production

PubMed Central

Mašín, Ivan

2016-01-01

One of important sources of biomass-based fuel is Jatropha curcas L. Great attention is paid to the biofuel produced from the oil extracted from the Jatropha curcas L. seeds. A mechanised extraction is the most efficient and feasible method for oil extraction for small-scale farmers but there is a need to extract oil in more efficient manner which would increase the labour productivity, decrease production costs, and increase benefits of small-scale farmers. On the other hand innovators should be aware that further machines development is possible only when applying the systematic approach and design methodology in all stages of engineering design. Systematic approach in this case means that designers and development engineers rigorously apply scientific knowledge, integrate different constraints and user priorities, carefully plan product and activities, and systematically solve technical problems. This paper therefore deals with the complex approach to design specification determining that can bring new innovative concepts to design of mechanical machines for oil extraction. The presented case study as the main part of the paper is focused on new concept of screw of machine mechanically extracting oil from Jatropha curcas L. seeds. PMID:27668259

Work stress of women in sewing machine operation.

PubMed

Nag, A; Desai, H; Nag, P K

1992-06-01

The study examined the work stresses of 107 women who were engaged in sewing machine operation in small garment manufacturing units. Of the three types of sewing machines (motor-operated, full and half shuttle foot-operated), 74% of the machines were foot-operated, where throttle action of the lower limb is required to move the shuttle of the machine. The motor-operated machines were faster than the foot-operated machines. The short cycle sewing work involves repetitive action of hand and feet. The women had to maintain a constant seated position on a stool without backrest and the body inclined forward. Long-term sewing work had a cumulative load on the musculo-skeletal structures, including the vertebral column and reflected in the form of high prevalence of discomfort and pain in different body parts. About 68% of the women complained of back pain, among whom 35% reported a persistent low back pain. Common sewing work accident is piercing of the needle through the fingers, particularly the right forefingers. Unsatisfactory man-machine incompatibility, work posture and fatigue, improper coordination of eye, leg and hand are the major problems of the operators. The design mis-match of the work place may be significantly improved by taking women's anthropometric dimensions in modifying the workplace, i.e. the seat surface, seat height, work height, backrest, etc.

Non-conventional rule of making a periodically varying different-pole magnetic field in low-power alternating current electrical machines with using ring coils in multiphase armature winding

NASA Astrophysics Data System (ADS)

Plastun, A. T.; Tikhonova, O. V.; Malygin, I. V.

2018-02-01

The paper presents methods of making a periodically varying different-pole magnetic field in low-power electrical machines. Authors consider classical designs of electrical machines and machines with ring windings in armature, structural features and calculated parameters of magnetic circuit for these machines.

Micromechanical Machining Processes and their Application to Aerospace Structures, Devices and Systems

NASA Technical Reports Server (NTRS)

Friedrich, Craig R.; Warrington, Robert O.

1995-01-01

Micromechanical machining processes are those micro fabrication techniques which directly remove work piece material by either a physical cutting tool or an energy process. These processes are direct and therefore they can help reduce the cost and time for prototype development of micro mechanical components and systems. This is especially true for aerospace applications where size and weight are critical, and reliability and the operating environment are an integral part of the design and development process. The micromechanical machining processes are rapidly being recognized as a complementary set of tools to traditional lithographic processes (such as LIGA) for the fabrication of micromechanical components. Worldwide efforts in the U.S., Germany, and Japan are leading to results which sometimes rival lithography at a fraction of the time and cost. Efforts to develop processes and systems specific to aerospace applications are well underway.

Machine-learning approach for local classification of crystalline structures in multiphase systems

NASA Astrophysics Data System (ADS)

Dietz, C.; Kretz, T.; Thoma, M. H.

2017-07-01

Machine learning is one of the most popular fields in computer science and has a vast number of applications. In this work we will propose a method that will use a neural network to locally identify crystal structures in a mixed phase Yukawa system consisting of fcc, hcp, and bcc clusters and disordered particles similar to plasma crystals. We compare our approach to already used methods and show that the quality of identification increases significantly. The technique works very well for highly disturbed lattices and shows a flexible and robust way to classify crystalline structures that can be used by only providing particle positions. This leads to insights into highly disturbed crystalline structures.

Fault Tolerant State Machines

NASA Technical Reports Server (NTRS)

Burke, Gary R.; Taft, Stephanie

2004-01-01

State machines are commonly used to control sequential logic in FPGAs and ASKS. An errant state machine can cause considerable damage to the device it is controlling. For example in space applications, the FPGA might be controlling Pyros, which when fired at the wrong time will cause a mission failure. Even a well designed state machine can be subject to random errors us a result of SEUs from the radiation environment in space. There are various ways to encode the states of a state machine, and the type of encoding makes a large difference in the susceptibility of the state machine to radiation. In this paper we compare 4 methods of state machine encoding and find which method gives the best fault tolerance, as well as determining the resources needed for each method.

Dynamic impact testing with servohydraulic testing machines

NASA Astrophysics Data System (ADS)

Bardenheier, R.; Rogers, G.

2006-08-01

The design concept of “Crashworthiness” requires the information on material behaviour under dynamic impact loading in order to describe and predict the crash behaviour of structures. Especially the transport related industries, like car, railway or aircraft industry, pursue the concept of lightweight design for a while now. The materials' maximum constraint during loading is pushed to permanently increasing figures. This means in terms of crashworthiness that the process of energy absorption in structures and the mechanical behaviour of materials must well understood and can be described appropriately by material models. In close cooperation with experts from various industries and research institutes Instron has developed throughout the past years a new family of servohydraulic testing machines specifically designed to cope with the dynamics of high rate testing. Main development steps are reflected versus their experimental necessities.

Structural Design of Ares V Interstage Composite Structure

NASA Technical Reports Server (NTRS)

Sleigh, David W.; Sreekantamurthy, Thammaiah; Kosareo, Daniel N.; Martin, Robert A.; Johnson, Theodore F.

2011-01-01

Preliminary and detailed design studies were performed to mature composite structural design concepts for the Ares V Interstage structure as a part of NASA s Advanced Composite Technologies Project. Aluminum honeycomb sandwich and hat-stiffened composite panel structural concepts were considered. The structural design and analysis studies were performed using HyperSizer design sizing software and MSC Nastran finite element analysis software. System-level design trade studies were carried out to predict weight and margins of safety for composite honeycomb-core sandwich and composite hat-stiffened skin design concepts. Details of both preliminary and detailed design studies are presented in the paper. For the range of loads and geometry considered in this work, the hat-stiffened designs were found to be approximately 11-16 percent lighter than the sandwich designs. A down-select process was used to choose the most favorable structural concept based on a set of figures of merit, and the honeycomb sandwich design was selected as the best concept based on advantages in manufacturing cost.

Specimen coordinate automated measuring machine/fiducial automated measuring machine

DOEpatents

Hedglen, Robert E.; Jacket, Howard S.; Schwartz, Allan I.

1991-01-01

The Specimen coordinate Automated Measuring Machine (SCAMM) and the Fiducial Automated Measuring Machine (FAMM) is a computer controlled metrology system capable of measuring length, width, and thickness, and of locating fiducial marks. SCAMM and FAMM have many similarities in their designs, and they can be converted from one to the other without taking them out of the hot cell. Both have means for: supporting a plurality of samples and a standard; controlling the movement of the samples in the +/- X and Y directions; determining the coordinates of the sample; compensating for temperature effects; and verifying the accuracy of the measurements and repeating as necessary. SCAMM and FAMM are designed to be used in hot cells.

Learning surface molecular structures via machine vision

NASA Astrophysics Data System (ADS)

Ziatdinov, Maxim; Maksov, Artem; Kalinin, Sergei V.

2017-08-01

Recent advances in high resolution scanning transmission electron and scanning probe microscopies have allowed researchers to perform measurements of materials structural parameters and functional properties in real space with a picometre precision. In many technologically relevant atomic and/or molecular systems, however, the information of interest is distributed spatially in a non-uniform manner and may have a complex multi-dimensional nature. One of the critical issues, therefore, lies in being able to accurately identify (`read out') all the individual building blocks in different atomic/molecular architectures, as well as more complex patterns that these blocks may form, on a scale of hundreds and thousands of individual atomic/molecular units. Here we employ machine vision to read and recognize complex molecular assemblies on surfaces. Specifically, we combine Markov random field model and convolutional neural networks to classify structural and rotational states of all individual building blocks in molecular assembly on the metallic surface visualized in high-resolution scanning tunneling microscopy measurements. We show how the obtained full decoding of the system allows us to directly construct a pair density function—a centerpiece in analysis of disorder-property relationship paradigm—as well as to analyze spatial correlations between multiple order parameters at the nanoscale, and elucidate reaction pathway involving molecular conformation changes. The method represents a significant shift in our way of analyzing atomic and/or molecular resolved microscopic images and can be applied to variety of other microscopic measurements of structural, electronic, and magnetic orders in different condensed matter systems.

Learning surface molecular structures via machine vision

DOE PAGES

Ziatdinov, Maxim; Maksov, Artem; Kalinin, Sergei V.

2017-08-10

Recent advances in high resolution scanning transmission electron and scanning probe microscopies have allowed researchers to perform measurements of materials structural parameters and functional properties in real space with a picometre precision. In many technologically relevant atomic and/or molecular systems, however, the information of interest is distributed spatially in a non-uniform manner and may have a complex multi-dimensional nature. One of the critical issues, therefore, lies in being able to accurately identify (‘read out’) all the individual building blocks in different atomic/molecular architectures, as well as more complex patterns that these blocks may form, on a scale of hundreds andmore » thousands of individual atomic/molecular units. Here we employ machine vision to read and recognize complex molecular assemblies on surfaces. Specifically, we combine Markov random field model and convolutional neural networks to classify structural and rotational states of all individual building blocks in molecular assembly on the metallic surface visualized in high-resolution scanning tunneling microscopy measurements. We show how the obtained full decoding of the system allows us to directly construct a pair density function—a centerpiece in analysis of disorder-property relationship paradigm—as well as to analyze spatial correlations between multiple order parameters at the nanoscale, and elucidate reaction pathway involving molecular conformation changes. Here, the method represents a significant shift in our way of analyzing atomic and/or molecular resolved microscopic images and can be applied to variety of other microscopic measurements of structural, electronic, and magnetic orders in different condensed matter systems.« less

Learning surface molecular structures via machine vision

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ziatdinov, Maxim; Maksov, Artem; Kalinin, Sergei V.

Recent advances in high resolution scanning transmission electron and scanning probe microscopies have allowed researchers to perform measurements of materials structural parameters and functional properties in real space with a picometre precision. In many technologically relevant atomic and/or molecular systems, however, the information of interest is distributed spatially in a non-uniform manner and may have a complex multi-dimensional nature. One of the critical issues, therefore, lies in being able to accurately identify (‘read out’) all the individual building blocks in different atomic/molecular architectures, as well as more complex patterns that these blocks may form, on a scale of hundreds andmore » thousands of individual atomic/molecular units. Here we employ machine vision to read and recognize complex molecular assemblies on surfaces. Specifically, we combine Markov random field model and convolutional neural networks to classify structural and rotational states of all individual building blocks in molecular assembly on the metallic surface visualized in high-resolution scanning tunneling microscopy measurements. We show how the obtained full decoding of the system allows us to directly construct a pair density function—a centerpiece in analysis of disorder-property relationship paradigm—as well as to analyze spatial correlations between multiple order parameters at the nanoscale, and elucidate reaction pathway involving molecular conformation changes. Here, the method represents a significant shift in our way of analyzing atomic and/or molecular resolved microscopic images and can be applied to variety of other microscopic measurements of structural, electronic, and magnetic orders in different condensed matter systems.« less

Implications of the Turing machine model of computation for processor and programming language design

NASA Astrophysics Data System (ADS)

Hunter, Geoffrey

2004-01-01

A computational process is classified according to the theoretical model that is capable of executing it; computational processes that require a non-predeterminable amount of intermediate storage for their execution are Turing-machine (TM) processes, while those whose storage are predeterminable are Finite Automation (FA) processes. Simple processes (such as traffic light controller) are executable by Finite Automation, whereas the most general kind of computation requires a Turing Machine for its execution. This implies that a TM process must have a non-predeterminable amount of memory allocated to it at intermediate instants of its execution; i.e. dynamic memory allocation. Many processes encountered in practice are TM processes. The implication for computational practice is that the hardware (CPU) architecture and its operating system must facilitate dynamic memory allocation, and that the programming language used to specify TM processes must have statements with the semantic attribute of dynamic memory allocation, for in Alan Turing"s thesis on computation (1936) the "standard description" of a process is invariant over the most general data that the process is designed to process; i.e. the program describing the process should never have to be modified to allow for differences in the data that is to be processed in different instantiations; i.e. data-invariant programming. Any non-trivial program is partitioned into sub-programs (procedures, subroutines, functions, modules, etc). Examination of the calls/returns between the subprograms reveals that they are nodes in a tree-structure; this tree-structure is independent of the programming language used to encode (define) the process. Each sub-program typically needs some memory for its own use (to store values intermediate between its received data and its computed results); this locally required memory is not needed before the subprogram commences execution, and it is not needed after its execution terminates

Cogging Torque Minimization in Transverse Flux Machines

DOE Office of Scientific and Technical Information (OSTI.GOV)

Husain, Tausif; Hasan, Iftekhar; Sozer, Yilmaz

2017-02-16

This paper presents the design considerations in cogging torque minimization in two types of transverse flux machines. The machines have a double stator-single rotor configuration with flux concentrating ferrite magnets. One of the machines has pole windings across each leg of an E-Core stator. Another machine has quasi-U-shaped stator cores and a ring winding. The flux in the stator back iron is transverse in both machines. Different methods of cogging torque minimization are investigated. Key methods of cogging torque minimization are identified and used as design variables for optimization using a design of experiments (DOE) based on the Taguchi method.more » A three-level DOE is performed to reach an optimum solution with minimum simulations. Finite element analysis is used to study the different effects. Two prototypes are being fabricated for experimental verification.« less

Process Approach for Modeling of Machine and Tractor Fleet Structure

NASA Astrophysics Data System (ADS)

Dokin, B. D.; Aletdinova, A. A.; Kravchenko, M. S.; Tsybina, Y. S.

2018-05-01

The existing software complexes on modelling of the machine and tractor fleet structure are mostly aimed at solving the task of optimization. However, the creators, choosing only one optimization criterion and incorporating it in their software, provide grounds on why it is the best without giving a decision maker the opportunity to choose it for their enterprise. To analyze “bottlenecks” of machine and tractor fleet modelling, the authors of this article created a process model, in which they included adjustment to the plan of using machinery based on searching through alternative technologies. As a result, the following recommendations for software complex development have been worked out: the introduction of a database of alternative technologies; the possibility for a user to change the timing of the operations even beyond the allowable limits and in that case the calculation of the incurred loss; the possibility to rule out the solution of an optimization task, and if there is a necessity in it - the possibility to choose an optimization criterion; introducing graphical display of an annual complex of works, which could be enough for the development and adjustment of a business strategy.

Novel model of stator design to reduce the mass of superconducting generators

NASA Astrophysics Data System (ADS)

Kails, Kevin; Li, Quan; Mueller, Markus

2018-05-01

High temperature superconductors (HTS), with much higher current density than conventional copper wires, make it feasible to develop very powerful and compact power generators. Thus, they are considered as one promising solution for large (10 + MW) direct-drive offshore wind turbines due to their low tower head mass. However, most HTS generator designs are based on a radial topology, which requires an excessive amount of HTS material and suffers from cooling and reliability issues. Axial flux machines on the other hand offer higher torque/volume ratios than the radial machines, which makes them an attractive option where space and transportation becomes an issue. However, their disadvantage is heavy structural mass. In this paper a novel stator design is introduced for HTS axial flux machines which enables a reduction in their structural mass. The stator is for the first time designed with a 45° angle that deviates the air gap closing forces into the vertical direction reducing the axial forces. The reduced axial forces improve the structural stability and consequently simplify their structural design. The novel methodology was then validated through an existing design of the HTS axial flux machine achieving a ∼10% mass reduction from 126 tonnes down to 115 tonnes. In addition, the air gap flux density increases due to the new claw pole shapes improving its power density from 53.19 to 61.90 W kg‑1. It is expected that the HTS axial flux machines designed with the new methodology offer a competitive advantage over other proposed superconducting generator designs in terms of cost, reliability and power density.

Design and fabrication of optical homogenizer with micro structure by injection molding process

NASA Astrophysics Data System (ADS)

Chen, C.-C. A.; Chang, S.-W.; Weng, C.-J.

2008-08-01

This paper is to design and fabricate an optical homogenizer with hybrid design of collimator, toroidal lens array, and projection lens for beam shaping of Gaussian beam into uniform cylindrical beam. TracePro software was used to design the geometry of homogenizer and simulation of injection molding was preceded by Moldflow MPI to evaluate the mold design for injection molding process. The optical homogenizer is a cylindrical part with thickness 8.03 mm and diameter 5 mm. The micro structure of toroidal array has groove height designed from 12 μm to 99 μm. An electrical injection molding machine and PMMA (n= 1.4747) were selected to perform the experiment. Experimental results show that the optics homogenizer has achieved the transfer ratio of grooves (TRG) as 88.98% and also the optical uniformity as 68% with optical efficiency as 91.88%. Future study focuses on development of an optical homogenizer for LED light source.

Aeromechanics and man-machine integration technology opportunities for rotorcraft of the 1990s and beyond

NASA Technical Reports Server (NTRS)

Kerr, Andrew W.

1989-01-01

Programs related to rotorcraft aeromechanics and man-machine integration are discussed which will support advanced army rotorcraft design. In aeromechanics, recent advances in computational fluid dynamics will be used to characterize the complex unsteady flowfields of rotorcraft, and a second-generation comprehensive helicopter analysis system will be used along with models of aerodynamics, engines, and control systems to study the structural dynamics of rotor/body configurations. The man-machine integration program includes the development of advanced cockpit design technology and the evaluation of cockpit and mission equipment concepts in a real-time full-combat environment.

Detection of pigment network in dermoscopy images using supervised machine learning and structural analysis.

PubMed

García Arroyo, Jose Luis; García Zapirain, Begoña

2014-01-01

By means of this study, a detection algorithm for the "pigment network" in dermoscopic images is presented, one of the most relevant indicators in the diagnosis of melanoma. The design of the algorithm consists of two blocks. In the first one, a machine learning process is carried out, allowing the generation of a set of rules which, when applied over the image, permit the construction of a mask with the pixels candidates to be part of the pigment network. In the second block, an analysis of the structures over this mask is carried out, searching for those corresponding to the pigment network and making the diagnosis, whether it has pigment network or not, and also generating the mask corresponding to this pattern, if any. The method was tested against a database of 220 images, obtaining 86% sensitivity and 81.67% specificity, which proves the reliability of the algorithm. © 2013 The Authors. Published by Elsevier Ltd. All rights reserved.

RF structure design of the China Material Irradiation Facility RFQ

NASA Astrophysics Data System (ADS)

Li, Chenxing; He, Yuan; Xu, Xianbo; Zhang, Zhouli; Wang, Fengfeng; Dou, Weiping; Wang, Zhijun; Wang, Tieshan

2017-10-01

The radio frequency structure design of the radio frequency quadrupole (RFQ) for the front end of China Material Irradiation Facility (CMIF), which is an accelerator based neutron irradiation facility for fusion reactor material qualification, has been completed. The RFQ is specified to accelerate 10 mA continuous deuteron beams from the energies of 20 keV/u to 1.5 MeV/u within the vane length of 5250 mm. The working frequency of the RFQ is selected to 162.5 MHz and the inter-vane voltage is set to 65 kV. Four-vane cavity type is selected and the cavity structure is designed drawing on the experience of China Initiative Accelerator Driven System (CIADS) Injector II RFQ. In order to reduce the azimuthal asymmetry of the field caused from errors in fabrication and assembly, a frequency separation between the working mode and its nearest dipole mode is reached to 17.66 MHz by utilizing 20 pairs of π-mode stabilizing loops (PISLs) distributed along the longitudinal direction with equal intervals. For the purpose of tuning, 100 slug tuners were introduced to compensate the errors caused by machining and assembly. In order to obtain a homogeneous electrical field distribution along cavity, vane cutbacks are introduced and output endplate is modified. Multi-physics study of the cavity with radio frequency power and water cooling is performed to obtain the water temperature tuning coefficients. Through comparing to the worldwide CW RFQs, it is indicated that the power density of the designed structure is moderate for operation under continuous wave (CW) mode.

Man-machine Integration Design and Analysis System (MIDAS) Task Loading Model (TLM) experimental and software detailed design report

NASA Technical Reports Server (NTRS)

Staveland, Lowell

1994-01-01

This is the experimental and software detailed design report for the prototype task loading model (TLM) developed as part of the man-machine integration design and analysis system (MIDAS), as implemented and tested in phase 6 of the Army-NASA Aircrew/Aircraft Integration (A3I) Program. The A3I program is an exploratory development effort to advance the capabilities and use of computational representations of human performance and behavior in the design, synthesis, and analysis of manned systems. The MIDAS TLM computationally models the demands designs impose on operators to aide engineers in the conceptual design of aircraft crewstations. This report describes TLM and the results of a series of experiments which were run this phase to test its capabilities as a predictive task demand modeling tool. Specifically, it includes discussions of: the inputs and outputs of TLM, the theories underlying it, the results of the test experiments, the use of the TLM as both stand alone tool and part of a complete human operator simulation, and a brief introduction to the TLM software design.

Machine Tool Software

NASA Technical Reports Server (NTRS)

1988-01-01

A NASA-developed software package has played a part in technical education of students who major in Mechanical Engineering Technology at William Rainey Harper College. Professor Hack has been using (APT) Automatically Programmed Tool Software since 1969 in his CAD/CAM Computer Aided Design and Manufacturing curriculum. Professor Hack teaches the use of APT programming languages for control of metal cutting machines. Machine tool instructions are geometry definitions written in APT Language to constitute a "part program." The part program is processed by the machine tool. CAD/CAM students go from writing a program to cutting steel in the course of a semester.

Evaluation of machine learning tools for inspection of steam generator tube structures using pulsed eddy current

NASA Astrophysics Data System (ADS)

Buck, J. A.; Underhill, P. R.; Morelli, J.; Krause, T. W.

2017-02-01

Degradation of nuclear steam generator (SG) tubes and support structures can result in a loss of reactor efficiency. Regular in-service inspection, by conventional eddy current testing (ECT), permits detection of cracks, measurement of wall loss, and identification of other SG tube degradation modes. However, ECT is challenged by overlapping degradation modes such as might occur for SG tube fretting accompanied by tube off-set within a corroding ferromagnetic support structure. Pulsed eddy current (PEC) is an emerging technology examined here for inspection of Alloy-800 SG tubes and associated carbon steel drilled support structures. Support structure hole size was varied to simulate uniform corrosion, while SG tube was off-set relative to hole axis. PEC measurements were performed using a single driver with an 8 pick-up coil configuration in the presence of flat-bottom rectangular frets as an overlapping degradation mode. A modified principal component analysis (MPCA) was performed on the time-voltage data in order to reduce data dimensionality. The MPCA scores were then used to train a support vector machine (SVM) that simultaneously targeted four independent parameters associated with; support structure hole size, tube off-centering in two dimensions and fret depth. The support vector machine was trained, tested, and validated on experimental data. Results were compared with a previously developed artificial neural network (ANN) trained on the same data. Estimates of tube position showed comparable results between the two machine learning tools. However, the ANN produced better estimates of hole inner diameter and fret depth. The better results from ANN analysis was attributed to challenges associated with the SVM when non-constant variance is present in the data.

A manned-machine space station construction concept

NASA Technical Reports Server (NTRS)

Mikulas, M. M., Jr.; Bush, H. G.; Wallsom, R. E.; Dorsey, J. T.; Rhodes, M. D.

1984-01-01

A design concept for the construction of a permanent manned space station is developed and discussed. The main considerations examined in developing the design concept are: (1) the support structure of the station be stiff enough to preclude the need for an elaborate on-orbit system to control structural response, (2) the station support structure and solar power system be compatible with existing technology, and (3) the station be capable of growing in a systematic modular fashion. The concept is developed around the assembly of truss platforms by pressure-suited astronauts operating in extravehicular activity (EVA), assisted by a machine (Assembly and Transport Vehicle, ATV) to position the astronauts at joint locations where they latch truss members in place. The ATV is a mobile platform that is attached to and moves on the station support structure using pegs attached to each truss joint. The operation of the ATV is described and a number of conceptual configurations for potential space stations are developed.

Understanding and Writing G & M Code for CNC Machines

ERIC Educational Resources Information Center

Loveland, Thomas

2012-01-01

In modern CAD and CAM manufacturing companies, engineers design parts for machines and consumable goods. Many of these parts are cut on CNC machines. Whether using a CNC lathe, milling machine, or router, the ideas and designs of engineers must be translated into a machine-readable form called G & M Code that can be used to cut parts to precise…

Multipurpose Prepregging Machine

NASA Technical Reports Server (NTRS)

Johnston, N. J.; Wilkinson, Steven; Marchello, J. M.; Dixon, D.

1995-01-01

Machine designed and built for variety of uses involving coating or impregnating ("prepregging") fibers, tows, yarns, or webs or tapes made of such fibrous materials with thermoplastic or thermosetting resins. Prepreg materials produced used to make matrix/fiber composite materials. Comprises modules operated individually, sequentially, or simultaneously, depending on nature of specific prepreg material and prepregging technique used. Machine incorporates number of safety features.

Design of Human – Machine Interface and Altering of Pelvic Obliquity with RGR Trainer

PubMed Central

Pietrusinski, Maciej; Unluhisarcikli, Ozer; Mavroidis, Constantinos; Cajigas, Iahn; Bonato, Paolo

2012-01-01

The Robotic Gait Rehabilitation (RGR) Trainer targets secondary gait deviations in stroke survivors undergoing rehabilitation. Using an impedance control strategy and a linear electromagnetic actuator, the device generates a force field to control pelvic obliquity through a Human-Machine Interface (i.e. a lower body exoskeleton). Herein we describe the design of the RGR Trainer Human-Machine Interface (HMI) and we demonstrate the system’s ability to alter the pattern of movement of the pelvis during gait in a healthy subject. Results are shown for experiments during which we induced hip-hiking – in healthy subjects. Our findings indicate that the RGR Trainer has the ability of affecting pelvic obliquity during gait. Furthermore, we provide preliminary evidence of short-term retention of the modified pelvic obliquity pattern induced by the RGR Trainer. PMID:22275693

Support Vector Machines Trained with Evolutionary Algorithms Employing Kernel Adatron for Large Scale Classification of Protein Structures.

PubMed

Arana-Daniel, Nancy; Gallegos, Alberto A; López-Franco, Carlos; Alanís, Alma Y; Morales, Jacob; López-Franco, Adriana

2016-01-01

With the increasing power of computers, the amount of data that can be processed in small periods of time has grown exponentially, as has the importance of classifying large-scale data efficiently. Support vector machines have shown good results classifying large amounts of high-dimensional data, such as data generated by protein structure prediction, spam recognition, medical diagnosis, optical character recognition and text classification, etc. Most state of the art approaches for large-scale learning use traditional optimization methods, such as quadratic programming or gradient descent, which makes the use of evolutionary algorithms for training support vector machines an area to be explored. The present paper proposes an approach that is simple to implement based on evolutionary algorithms and Kernel-Adatron for solving large-scale classification problems, focusing on protein structure prediction. The functional properties of proteins depend upon their three-dimensional structures. Knowing the structures of proteins is crucial for biology and can lead to improvements in areas such as medicine, agriculture and biofuels.

Fragment-based quantitative structure-activity relationship (FB-QSAR) for fragment-based drug design.

PubMed

Du, Qi-Shi; Huang, Ri-Bo; Wei, Yu-Tuo; Pang, Zong-Wen; Du, Li-Qin; Chou, Kuo-Chen

2009-01-30

In cooperation with the fragment-based design a new drug design method, the so-called "fragment-based quantitative structure-activity relationship" (FB-QSAR) is proposed. The essence of the new method is that the molecular framework in a family of drug candidates are divided into several fragments according to their substitutes being investigated. The bioactivities of molecules are correlated with the physicochemical properties of the molecular fragments through two sets of coefficients in the linear free energy equations. One coefficient set is for the physicochemical properties and the other for the weight factors of the molecular fragments. Meanwhile, an iterative double least square (IDLS) technique is developed to solve the two sets of coefficients in a training data set alternately and iteratively. The IDLS technique is a feedback procedure with machine learning ability. The standard Two-dimensional quantitative structure-activity relationship (2D-QSAR) is a special case, in the FB-QSAR, when the whole molecule is treated as one entity. The FB-QSAR approach can remarkably enhance the predictive power and provide more structural insights into rational drug design. As an example, the FB-QSAR is applied to build a predictive model of neuraminidase inhibitors for drug development against H5N1 influenza virus. (c) 2008 Wiley Periodicals, Inc.

Ontology-based coupled optimisation design method using state-space analysis for the spindle box system of large ultra-precision optical grinding machine

NASA Astrophysics Data System (ADS)

Wang, Qianren; Chen, Xing; Yin, Yuehong; Lu, Jian

2017-08-01

With the increasing complexity of mechatronic products, traditional empirical or step-by-step design methods are facing great challenges with various factors and different stages having become inevitably coupled during the design process. Management of massive information or big data, as well as the efficient operation of information flow, is deeply involved in the process of coupled design. Designers have to address increased sophisticated situations when coupled optimisation is also engaged. Aiming at overcoming these difficulties involved in conducting the design of the spindle box system of ultra-precision optical grinding machine, this paper proposed a coupled optimisation design method based on state-space analysis, with the design knowledge represented by ontologies and their semantic networks. An electromechanical coupled model integrating mechanical structure, control system and driving system of the motor is established, mainly concerning the stiffness matrix of hydrostatic bearings, ball screw nut and rolling guide sliders. The effectiveness and precision of the method are validated by the simulation results of the natural frequency and deformation of the spindle box when applying an impact force to the grinding wheel.

Modeling and Designing of A Nonlineartemperature-Humidity Controller Using Inmushroom-Drying Machine

NASA Astrophysics Data System (ADS)

Wu, Xiuhua; Luo, Haiyan; Shi, Minhui

Drying-process of many kinds of farm produce in a close room, such as mushroom-drying machine, is generally a complicated nonlinear and timedelay cause, in which the temperature and the humidity are the main controlled elements. The accurate controlling of the temperature and humidity is always an interesting problem. It's difficult and very important to make a more accurate mathematical model about the varying of the two. A math model was put forward after considering many aspects and analyzing the actual working circumstance in this paper. Form the model it can be seen that the changes of temperature and humidity in drying machine are not simple linear but an affine nonlinear process. Controlling the process exactly is the key that influences the quality of the dried mushroom. In this paper, the differential geometry theories and methods are used to analyze and solve the model of these smallenvironment elements. And at last a kind of nonlinear controller which satisfied the optimal quadratic performance index is designed. It can be proved more feasible and practical than the conventional controlling.

A study pertaining to inertial energy storage machine designs for space applications

NASA Technical Reports Server (NTRS)

Zowarka, R. C.

1981-01-01

The preliminary design of a counterrotating fast discharge homopolar generator (HPG) and a counterrotating active rotary flux compressor (CARFC) for space application is reported. The HPG is a counterrotating spool-type homopolar with superconducting field coil excitation. It delivers a 20-ms, 145-kJ pulse to a magnetoplasmahydrodynamic thruster. The peak output current is 42.7 kA at 240 V. After 20 ms the current is 29.7 kA at 167 V. The CARFC delivers ten 50-kJ, 250 microsecond pulses at 50-ms interval to six Xenon flash lamps pumping an Nd glass laser. The flux compressor is counterrotating for torque compensation. Current is started in the machine with a 5-kV, 5-kJ pulse-charged capacitor. Both designs were based upon demonstrated technology. The sensitivity of the designs to technology that may be available in five to ten years was determined.

Nanocomposites for Machining Tools

PubMed Central

Loginov, Pavel; Mishnaevsky, Leon; Levashov, Evgeny

2017-01-01

Machining tools are used in many areas of production. To a considerable extent, the performance characteristics of the tools determine the quality and cost of obtained products. The main materials used for producing machining tools are steel, cemented carbides, ceramics and superhard materials. A promising way to improve the performance characteristics of these materials is to design new nanocomposites based on them. The application of micromechanical modeling during the elaboration of composite materials for machining tools can reduce the financial and time costs for development of new tools, with enhanced performance. This article reviews the main groups of nanocomposites for machining tools and their performance. PMID:29027926

Impact of an engineering design-based curriculum compared to an inquiry-based curriculum on fifth graders' content learning of simple machines

NASA Astrophysics Data System (ADS)

Marulcu, Ismail; Barnett, Michael

2016-01-01

Background: Elementary Science Education is struggling with multiple challenges. National and State test results confirm the need for deeper understanding in elementary science education. Moreover, national policy statements and researchers call for increased exposure to engineering and technology in elementary science education. The basic motivation of this study is to suggest a solution to both improving elementary science education and increasing exposure to engineering and technology in it. Purpose/Hypothesis: This mixed-method study examined the impact of an engineering design-based curriculum compared to an inquiry-based curriculum on fifth graders' content learning of simple machines. We hypothesize that the LEGO-engineering design unit is as successful as the inquiry-based unit in terms of students' science content learning of simple machines. Design/Method: We used a mixed-methods approach to investigate our research questions; we compared the control and the experimental groups' scores from the tests and interviews by using Analysis of Covariance (ANCOVA) and compared each group's pre- and post-scores by using paired t-tests. Results: Our findings from the paired t-tests show that both the experimental and comparison groups significantly improved their scores from the pre-test to post-test on the multiple-choice, open-ended, and interview items. Moreover, ANCOVA results show that students in the experimental group, who learned simple machines with the design-based unit, performed significantly better on the interview questions. Conclusions: Our analyses revealed that the design-based Design a people mover: Simple machines unit was, if not better, as successful as the inquiry-based FOSS Levers and pulleys unit in terms of students' science content learning.

Optimization design and analysis of the pavement planer scraper structure

NASA Astrophysics Data System (ADS)

Fang, Yuanbin; Sha, Hongwei; Yuan, Dajun; Xie, Xiaobing; Yang, Shibo

2018-03-01

By LS-DYNA, it establishes the finite element model of road milling machine scraper, and analyses the dynamic simulation. Through the optimization of the scraper structure and scraper angle, obtain the optimal structure of milling machine scraper. At the same time, the simulation results are verified. The results show that the scraper structure is improved that cemented carbide is located in the front part of the scraper substrate. Compared with the working resistance before improvement, it tends to be gentle and the peak value is smaller. The cutting front angle and the cutting back angle are optimized. The cutting front angle is 6 degrees and the cutting back angle is 9 degrees. The resultant of forces which contains the working resistance and the impact force is the least. It proves accuracy of the simulation results and provides guidance for further optimization work.

The laser micro-machining system for diamond anvil cell experiments and general precision machining applications at the High Pressure Collaborative Access Team

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hrubiak, Rostislav; Sinogeikin, Stanislav; Rod, Eric

We have designed and constructed a new system for micro-machining parts and sample assemblies used for diamond anvil cells and general user operations at the High Pressure Collaborative Access Team, sector 16 of the Advanced Photon Source. The new micro-machining system uses a pulsed laser of 400 ps pulse duration, ablating various materials without thermal melting, thus leaving a clean edge. With optics designed for a tight focus, the system can machine holes any size larger than 3 μm in diameter. Unlike a standard electrical discharge machining drill, the new laser system allows micro-machining of non-conductive materials such as: amorphousmore » boron and silicon carbide gaskets, diamond, oxides, and other materials including organic materials such as polyimide films (i.e., Kapton). An important feature of the new system is the use of gas-tight or gas-flow environmental chambers which allow the laser micro-machining to be done in a controlled (e.g., inert gas) atmosphere to prevent oxidation and other chemical reactions in air sensitive materials. The gas-tight workpiece enclosure is also useful for machining materials with known health risks (e.g., beryllium). Specialized control software with a graphical interface enables micro-machining of custom 2D and 3D shapes. The laser-machining system was designed in a Class 1 laser enclosure, i.e., it includes laser safety interlocks and computer controls and allows for routine operation. Though initially designed mainly for machining of the diamond anvil cell gaskets, the laser-machining system has since found many other micro-machining applications, several of which are presented here.« less

Abnormal brain structure as a potential biomarker for venous erectile dysfunction: evidence from multimodal MRI and machine learning.

PubMed

Li, Lingli; Fan, Wenliang; Li, Jun; Li, Quanlin; Wang, Jin; Fan, Yang; Ye, Tianhe; Guo, Jialun; Li, Sen; Zhang, Youpeng; Cheng, Yongbiao; Tang, Yong; Zeng, Hanqing; Yang, Lian; Zhu, Zhaohui

2018-03-29

To investigate the cerebral structural changes related to venous erectile dysfunction (VED) and the relationship of these changes to clinical symptoms and disorder duration and distinguish patients with VED from healthy controls using a machine learning classification. 45 VED patients and 50 healthy controls were included. Voxel-based morphometry (VBM), tract-based spatial statistics (TBSS) and correlation analyses of VED patients and clinical variables were performed. The machine learning classification method was adopted to confirm its effectiveness in distinguishing VED patients from healthy controls. Compared to healthy control subjects, VED patients showed significantly decreased cortical volumes in the left postcentral gyrus and precentral gyrus, while only the right middle temporal gyrus showed a significant increase in cortical volume. Increased axial diffusivity (AD), radial diffusivity (RD) and mean diffusivity (MD) values were observed in widespread brain regions. Certain regions of these alterations related to VED patients showed significant correlations with clinical symptoms and disorder durations. Machine learning analyses discriminated patients from controls with overall accuracy 96.7%, sensitivity 93.3% and specificity 99.0%. Cortical volume and white matter (WM) microstructural changes were observed in VED patients, and showed significant correlations with clinical symptoms and dysfunction durations. Various DTI-derived indices of some brain regions could be regarded as reliable discriminating features between VED patients and healthy control subjects, as shown by machine learning analyses. • Multimodal magnetic resonance imaging helps clinicians to assess patients with VED. • VED patients show cerebral structural alterations related to their clinical symptoms. • Machine learning analyses discriminated VED patients from controls with an excellent performance. • Machine learning classification provided a preliminary demonstration of DTI

On the decomposition of synchronous state mechines using sequence invariant state machines

NASA Technical Reports Server (NTRS)

Hebbalalu, K.; Whitaker, S.; Cameron, K.

1992-01-01

This paper presents a few techniques for the decomposition of Synchronous State Machines of medium to large sizes into smaller component machines. The methods are based on the nature of the transitions and sequences of states in the machine and on the number and variety of inputs to the machine. The results of the decomposition, and of using the Sequence Invariant State Machine (SISM) Design Technique for generating the component machines, include great ease and quickness in the design and implementation processes. Furthermore, there is increased flexibility in making modifications to the original design leading to negligible re-design time.

Automated discrimination of dementia spectrum disorders using extreme learning machine and structural T1 MRI features.

PubMed

Jongin Kim; Boreom Lee

2017-07-01

The classification of neuroimaging data for the diagnosis of Alzheimer's Disease (AD) is one of the main research goals of the neuroscience and clinical fields. In this study, we performed extreme learning machine (ELM) classifier to discriminate the AD, mild cognitive impairment (MCI) from normal control (NC). We compared the performance of ELM with that of a linear kernel support vector machine (SVM) for 718 structural MRI images from Alzheimer's Disease Neuroimaging Initiative (ADNI) database. The data consisted of normal control, MCI converter (MCI-C), MCI non-converter (MCI-NC), and AD. We employed SVM-based recursive feature elimination (RFE-SVM) algorithm to find the optimal subset of features. In this study, we found that the RFE-SVM feature selection approach in combination with ELM shows the superior classification accuracy to that of linear kernel SVM for structural T1 MRI data.

Fabrication of locally micro-structured fiber Bragg gratings by fs-laser machining

NASA Astrophysics Data System (ADS)

Dutz, Franz J.; Stephan, Valentin; Marchi, Gabriele; Koch, Alexander W.; Roths, Johannes; Huber, Heinz P.

2018-06-01

Here, we describe a method for producing locally micro-structured fiber Bragg gratings (LMFGB) by fs-laser machining. This technique enables the precise and reproducible ablation of cladding material to create circumferential grooves inside the claddings of optical fibers. From initial ablation experiments we acquired optimized process parameters. The fabricated grooves were located in the middle of uniform type I fiber Bragg gratings. LMFBGs with four different groove widths of 48, 85, 135 and 205 μ { {m}} were produced. The grooves exhibited constant depths of about 30 μ {m} and steep sidewall angles. With the combination of micro-structures and fiber Bragg gratings, fiber optic sensor elements with enhanced functionalities can be achieved.

Design considerations for fiber composite structures

NASA Technical Reports Server (NTRS)

Chamis, C. C.

1972-01-01

An overview of the design methodology for designing structural components from fiber composites is presented. In particular, the need for new conceptual structural designs for the future is discussed and the evolution of conceptual design is illustrated. Sources of design data, analysis and design procedures, and the basic components of structural fiber composites are cited and described. Examples of tradeoff studies and optimum designs are discussed and a simple structure is described in some detail.

Energy landscapes for machine learning

NASA Astrophysics Data System (ADS)

Ballard, Andrew J.; Das, Ritankar; Martiniani, Stefano; Mehta, Dhagash; Sagun, Levent; Stevenson, Jacob D.; Wales, David J.

Machine learning techniques are being increasingly used as flexible non-linear fitting and prediction tools in the physical sciences. Fitting functions that exhibit multiple solutions as local minima can be analysed in terms of the corresponding machine learning landscape. Methods to explore and visualise molecular potential energy landscapes can be applied to these machine learning landscapes to gain new insight into the solution space involved in training and the nature of the corresponding predictions. In particular, we can define quantities analogous to molecular structure, thermodynamics, and kinetics, and relate these emergent properties to the structure of the underlying landscape. This Perspective aims to describe these analogies with examples from recent applications, and suggest avenues for new interdisciplinary research.

A New Automated Design Method Based on Machine Learning for CMOS Analog Circuits

NASA Astrophysics Data System (ADS)

Moradi, Behzad; Mirzaei, Abdolreza

2016-11-01

A new simulation based automated CMOS analog circuit design method which applies a multi-objective non-Darwinian-type evolutionary algorithm based on Learnable Evolution Model (LEM) is proposed in this article. The multi-objective property of this automated design of CMOS analog circuits is governed by a modified Strength Pareto Evolutionary Algorithm (SPEA) incorporated in the LEM algorithm presented here. LEM includes a machine learning method such as the decision trees that makes a distinction between high- and low-fitness areas in the design space. The learning process can detect the right directions of the evolution and lead to high steps in the evolution of the individuals. The learning phase shortens the evolution process and makes remarkable reduction in the number of individual evaluations. The expert designer's knowledge on circuit is applied in the design process in order to reduce the design space as well as the design time. The circuit evaluation is made by HSPICE simulator. In order to improve the design accuracy, bsim3v3 CMOS transistor model is adopted in this proposed design method. This proposed design method is tested on three different operational amplifier circuits. The performance of this proposed design method is verified by comparing it with the evolutionary strategy algorithm and other similar methods.

Investigations on high speed machining of EN-353 steel alloy under different machining environments

NASA Astrophysics Data System (ADS)

Venkata Vishnu, A.; Jamaleswara Kumar, P.

2018-03-01

The addition of Nano Particles into conventional cutting fluids enhances its cooling capabilities; in the present paper an attempt is made by adding nano sized particles into conventional cutting fluids. Taguchi Robust Design Methodology is employed in order to study the performance characteristics of different turning parameters i.e. cutting speed, feed rate, depth of cut and type of tool under different machining environments i.e. dry machining, machining with lubricant - SAE 40 and machining with mixture of nano sized particles of Boric acid and base fluid SAE 40. A series of turning operations were performed using L27 (3)13 orthogonal array, considering high cutting speeds and the other machining parameters to measure hardness. The results are compared among the different machining environments, and it is concluded that there is considerable improvement in the machining performance using lubricant SAE 40 and mixture of SAE 40 + boric acid compared with dry machining. The ANOVA suggests that the selected parameters and the interactions are significant and cutting speed has most significant effect on hardness.

Self-Calibrating Surface Measuring Machine

NASA Astrophysics Data System (ADS)

Greenleaf, Allen H.

1983-04-01

A new kind of surface-measuring machine has been developed under government contract at Itek Optical Systems, a Division of Itek Corporation, to assist in the fabrication of large, highly aspheric optical elements. The machine uses four steerable distance-measuring interferometers at the corners of a tetrahedron to measure the positions of a retroreflective target placed at various locations against the surface being measured. Using four interferometers gives redundant information so that, from a set of measurement data, the dimensions of the machine as well as the coordinates of the measurement points can be determined. The machine is, therefore, self-calibrating and does not require a structure made to high accuracy. A wood-structured prototype of this machine was made whose key components are a simple form of air bearing steering mirror, a wide-angle cat's eye retroreflector used as the movable target, and tracking sensors and servos to provide automatic tracking of the cat's eye by the four laser beams. The data are taken and analyzed by computer. The output is given in terms of error relative to an equation of the desired surface. In tests of this machine, measurements of a 0.7 m diameter mirror blank have been made with an accuracy on the order of 0.2µm rms.

Motion Simulation Analysis of Rail Weld CNC Fine Milling Machine

NASA Astrophysics Data System (ADS)

Mao, Huajie; Shu, Min; Li, Chao; Zhang, Baojun

CNC fine milling machine is a new advanced equipment of rail weld precision machining with high precision, high efficiency, low environmental pollution and other technical advantages. The motion performance of this machine directly affects its machining accuracy and stability, which makes it an important consideration for its design. Based on the design drawings, this article completed 3D modeling of 60mm/kg rail weld CNC fine milling machine by using Solidworks. After that, the geometry was imported into Adams to finish the motion simulation analysis. The displacement, velocity, angular velocity and some other kinematical parameters curves of the main components were obtained in the post-processing and these are the scientific basis for the design and development for this machine.

Design of an Adaptive Human-Machine System Based on Dynamical Pattern Recognition of Cognitive Task-Load.

PubMed

Zhang, Jianhua; Yin, Zhong; Wang, Rubin

2017-01-01

This paper developed a cognitive task-load (CTL) classification algorithm and allocation strategy to sustain the optimal operator CTL levels over time in safety-critical human-machine integrated systems. An adaptive human-machine system is designed based on a non-linear dynamic CTL classifier, which maps a set of electroencephalogram (EEG) and electrocardiogram (ECG) related features to a few CTL classes. The least-squares support vector machine (LSSVM) is used as dynamic pattern classifier. A series of electrophysiological and performance data acquisition experiments were performed on seven volunteer participants under a simulated process control task environment. The participant-specific dynamic LSSVM model is constructed to classify the instantaneous CTL into five classes at each time instant. The initial feature set, comprising 56 EEG and ECG related features, is reduced to a set of 12 salient features (including 11 EEG-related features) by using the locality preserving projection (LPP) technique. An overall correct classification rate of about 80% is achieved for the 5-class CTL classification problem. Then the predicted CTL is used to adaptively allocate the number of process control tasks between operator and computer-based controller. Simulation results showed that the overall performance of the human-machine system can be improved by using the adaptive automation strategy proposed.

Design Oriented Structural Modeling for Airplane Conceptual Design Optimization

NASA Technical Reports Server (NTRS)

Livne, Eli

1999-01-01

The main goal for research conducted with the support of this grant was to develop design oriented structural optimization methods for the conceptual design of airplanes. Traditionally in conceptual design airframe weight is estimated based on statistical equations developed over years of fitting airplane weight data in data bases of similar existing air- planes. Utilization of such regression equations for the design of new airplanes can be justified only if the new air-planes use structural technology similar to the technology on the airplanes in those weight data bases. If any new structural technology is to be pursued or any new unconventional configurations designed the statistical weight equations cannot be used. In such cases any structural weight estimation must be based on rigorous "physics based" structural analysis and optimization of the airframes under consideration. Work under this grant progressed to explore airframe design-oriented structural optimization techniques along two lines of research: methods based on "fast" design oriented finite element technology and methods based on equivalent plate / equivalent shell models of airframes, in which the vehicle is modelled as an assembly of plate and shell components, each simulating a lifting surface or nacelle / fuselage pieces. Since response to changes in geometry are essential in conceptual design of airplanes, as well as the capability to optimize the shape itself, research supported by this grant sought to develop efficient techniques for parametrization of airplane shape and sensitivity analysis with respect to shape design variables. Towards the end of the grant period a prototype automated structural analysis code designed to work with the NASA Aircraft Synthesis conceptual design code ACS= was delivered to NASA Ames.

Experimental validation of 3D printed material behaviors and their influence on the structural topology design

NASA Astrophysics Data System (ADS)

Yang, Kai Ke; Zhu, Ji Hong; Wang, Chuang; Jia, Dong Sheng; Song, Long Long; Zhang, Wei Hong

2018-05-01

The purpose of this paper is to investigate the structures achieved by topology optimization and their fabrications by 3D printing considering the particular features of material microstructures and macro mechanical performances. Combining Digital Image Correlation and Optical Microscope, this paper experimentally explored the anisotropies of stiffness and strength existing in the 3D printed polymer material using Stereolithography (SLA) and titanium material using Selective Laser Melting (SLM). The standard specimens and typical structures obtained by topology optimization were fabricated along different building directions. On the one hand, the experimental results of these SLA produced structures showed stable properties and obviously anisotropic rules in stiffness, ultimate strengths and places of fractures. Further structural designs were performed using topology optimization when the particular mechanical behaviors of SLA printed materials were considered, which resulted in better structural performances compared to the optimized designs using `ideal' isotropic material model. On the other hand, this paper tested the mechanical behaviors of SLM printed multiscale lattice structures which were fabricated using the same metal powder and the same machine. The structural stiffness values are generally similar while the strength behaviors show a difference, which are mainly due to the irregular surface quality of the tiny structural branches of the lattice. The above evidences clearly show that the consideration of the particular behaviors of 3D printed materials is therefore indispensable for structural design and optimization in order to improve the structural performance and strengthen their practical significance.

Experimental validation of 3D printed material behaviors and their influence on the structural topology design

NASA Astrophysics Data System (ADS)

Yang, Kai Ke; Zhu, Ji Hong; Wang, Chuang; Jia, Dong Sheng; Song, Long Long; Zhang, Wei Hong

2018-02-01

The purpose of this paper is to investigate the structures achieved by topology optimization and their fabrications by 3D printing considering the particular features of material microstructures and macro mechanical performances. Combining Digital Image Correlation and Optical Microscope, this paper experimentally explored the anisotropies of stiffness and strength existing in the 3D printed polymer material using Stereolithography (SLA) and titanium material using Selective Laser Melting (SLM). The standard specimens and typical structures obtained by topology optimization were fabricated along different building directions. On the one hand, the experimental results of these SLA produced structures showed stable properties and obviously anisotropic rules in stiffness, ultimate strengths and places of fractures. Further structural designs were performed using topology optimization when the particular mechanical behaviors of SLA printed materials were considered, which resulted in better structural performances compared to the optimized designs using `ideal' isotropic material model. On the other hand, this paper tested the mechanical behaviors of SLM printed multiscale lattice structures which were fabricated using the same metal powder and the same machine. The structural stiffness values are generally similar while the strength behaviors show a difference, which are mainly due to the irregular surface quality of the tiny structural branches of the lattice. The above evidences clearly show that the consideration of the particular behaviors of 3D printed materials is therefore indispensable for structural design and optimization in order to improve the structural performance and strengthen their practical significance.

Design oriented structural analysis

NASA Technical Reports Server (NTRS)

Giles, Gary L.

1994-01-01

Desirable characteristics and benefits of design oriented analysis methods are described and illustrated by presenting a synoptic description of the development and uses of the Equivalent Laminated Plate Solution (ELAPS) computer code. ELAPS is a design oriented structural analysis method which is intended for use in the early design of aircraft wing structures. Model preparation is minimized by using a few large plate segments to model the wing box structure. Computational efficiency is achieved by using a limited number of global displacement functions that encompass all segments over the wing planform. Coupling with other codes is facilitated since the output quantities such as deflections and stresses are calculated as continuous functions over the plate segments. Various aspects of the ELAPS development are discussed including the analytical formulation, verification of results by comparison with finite element analysis results, coupling with other codes, and calculation of sensitivity derivatives. The effectiveness of ELAPS for multidisciplinary design application is illustrated by describing its use in design studies of high speed civil transport wing structures.

The Machine Intelligence Hex Project

ERIC Educational Resources Information Center

Chalup, Stephan K.; Mellor, Drew; Rosamond, Fran

2005-01-01

Hex is a challenging strategy board game for two players. To enhance students' progress in acquiring understanding and practical experience with complex machine intelligence and programming concepts we developed the Machine Intelligence Hex (MIHex) project. The associated undergraduate student assignment is about designing and implementing Hex…

Testing Machine for Biaxial Loading

NASA Technical Reports Server (NTRS)

Demonet, R. J.; Reeves, R. D.

1985-01-01

Standard tensile-testing machine applies bending and tension simultaneously. Biaxial-loading test machine created by adding two test fixtures to commercial tensile-testing machine. Bending moment applied by substrate-deformation fixture comprising yoke and anvil block. Pneumatic tension-load fixture pulls up on bracket attached to top surface of specimen. Tension and deflection measured with transducers. Modified test apparatus originally developed to load-test Space Shuttle surface-insulation tiles and particuarly important for composite structures.

Supervised Machine-Learning-Based Determination of Three-Dimensional Structure of Metallic Nanoparticles

DOE PAGES

Timoshenko, Janis; Lu, Deyu; Lin, Yuewei; ...

2017-09-29

Tracking the structure of heterogeneous catalysts under operando conditions remains a challenge due to the paucity of experimental techniques that can provide atomic-level information for catalytic metal species. Here we report on the use of X-ray absorption near edge structure (XANES) spectroscopy and supervised machine learning (SML) for refining the three-dimensional geometry of metal catalysts. SML is used to unravel the hidden relationship between the XANES features and catalyst geometry. To train our SML method, we rely on ab-initio XANES simulations. Our approach allows one to solve the structure of a metal catalyst from its experimental XANES, as demonstrated heremore » by reconstructing the average size, shape and morphology of well-defined platinum nanoparticles. This method is applicable to the determination of the nanoparticle structure in operando studies and can be generalized to other nanoscale systems. In conclusion, it also allows on-the-fly XANES analysis, and is a promising approach for high-throughput and time-dependent studies.« less

Supervised Machine-Learning-Based Determination of Three-Dimensional Structure of Metallic Nanoparticles

DOE Office of Scientific and Technical Information (OSTI.GOV)

Timoshenko, Janis; Lu, Deyu; Lin, Yuewei

Tracking the structure of heterogeneous catalysts under operando conditions remains a challenge due to the paucity of experimental techniques that can provide atomic-level information for catalytic metal species. Here we report on the use of X-ray absorption near edge structure (XANES) spectroscopy and supervised machine learning (SML) for refining the three-dimensional geometry of metal catalysts. SML is used to unravel the hidden relationship between the XANES features and catalyst geometry. To train our SML method, we rely on ab-initio XANES simulations. Our approach allows one to solve the structure of a metal catalyst from its experimental XANES, as demonstrated heremore » by reconstructing the average size, shape and morphology of well-defined platinum nanoparticles. This method is applicable to the determination of the nanoparticle structure in operando studies and can be generalized to other nanoscale systems. In conclusion, it also allows on-the-fly XANES analysis, and is a promising approach for high-throughput and time-dependent studies.« less

Structural design/margin assessment

NASA Technical Reports Server (NTRS)

Ryan, R. S.

1993-01-01

Determining structural design inputs and the structural margins following design completion is one of the major activities in space exploration. The end result is a statement of these margins as stability, safety factors on ultimate and yield stresses, fracture limits (fracture control), fatigue lifetime, reuse criteria, operational criteria and procedures, stability factors, deflections, clearance, handling criteria, etc. The process is normally called a load cycle and is time consuming, very complex, and involves much more than structures. The key to successful structural design is the proper implementation of the process. It depends on many factors: leadership and management of the process, adequate analysis and testing tools, data basing, communications, people skills, and training. This process and the various factors involved are discussed.

Design improvement of permanent magnet flux switching motor with dual rotor structure

NASA Astrophysics Data System (ADS)

Soomro, H. A.; Sulaiman, E.; Kumar, R.; Rahim, N. S.

2017-08-01

This paper presents design enhancement to reduce permanent magnet (PM) volume for 7S-6P-7S dual rotor permanent magnet flux-switching machines (DRPMFSM) for electric vehicle application. In recent years, Permanent magnet flux switching (PMFS) motor and a new member of brushless permanent magnet machine are prominently used for the electric vehicle. Though, more volume of Rare-Earth Permanent Magnet (REPM) is used to increase the cost and weight of these motors. Thus, to overcome the issue, new configuration of 7S-6P- 7S dual rotor permanent magnet flux-switching machine (DRPMFSM) has been proposed and investigated in this paper. Initially proposed 7S-6P-7S DRPMFSM has been optimized using “deterministic optimization” to reduce the volume of PM and to attain optimum performances. In addition, the performances of initial and optimized DRPMFSM have been compared such that back-emf, cogging torque, average torque, torque and power vs speed performances, losses and efficiency have been analysed by 2D-finite element analysis (FEA) using the JMAG- Designer software ver. 14.1. Consequently, the final design 7S-6P-7S DRPMFSM has achieved the efficiency of 83.91% at reduced PM volume than initial design to confirm the better efficient motor for HEVs applications.

OptiCentric lathe centering machine

NASA Astrophysics Data System (ADS)

Buß, C.; Heinisch, J.

2013-09-01

High precision optics depend on precisely aligned lenses. The shift and tilt of individual lenses as well as the air gap between elements require accuracies in the single micron regime. These accuracies are hard to meet with traditional assembly methods. Instead, lathe centering can be used to machine the mount with respect to the optical axis. Using a diamond turning process, all relevant errors of single mounted lenses can be corrected in one post-machining step. Building on the OptiCentric® and OptiSurf® measurement systems, Trioptics has developed their first lathe centering machines. The machine and specific design elements of the setup will be shown. For example, the machine can be used to turn optics for i-line steppers with highest precision.

30 CFR 18.54 - High-voltage continuous mining machines.

Code of Federal Regulations, 2010 CFR

2010-07-01

... and Design Requirements § 18.54 High-voltage continuous mining machines. (a) Separation of high... removed. (c) Circuit-interrupting devices. Circuit-interrupting devices must be designed and installed to... ground. (e) Onboard ungrounded, three-phase power circuit. A continuous mining machine designed with an...

30 CFR 18.54 - High-voltage continuous mining machines.

Code of Federal Regulations, 2013 CFR

2013-07-01

... and Design Requirements § 18.54 High-voltage continuous mining machines. (a) Separation of high... removed. (c) Circuit-interrupting devices. Circuit-interrupting devices must be designed and installed to... ground. (e) Onboard ungrounded, three-phase power circuit. A continuous mining machine designed with an...

30 CFR 18.54 - High-voltage continuous mining machines.

Code of Federal Regulations, 2014 CFR

2014-07-01

... and Design Requirements § 18.54 High-voltage continuous mining machines. (a) Separation of high... removed. (c) Circuit-interrupting devices. Circuit-interrupting devices must be designed and installed to... ground. (e) Onboard ungrounded, three-phase power circuit. A continuous mining machine designed with an...

30 CFR 18.54 - High-voltage continuous mining machines.

Code of Federal Regulations, 2012 CFR

2012-07-01

... and Design Requirements § 18.54 High-voltage continuous mining machines. (a) Separation of high... removed. (c) Circuit-interrupting devices. Circuit-interrupting devices must be designed and installed to... ground. (e) Onboard ungrounded, three-phase power circuit. A continuous mining machine designed with an...

30 CFR 18.54 - High-voltage continuous mining machines.

Code of Federal Regulations, 2011 CFR

2011-07-01

... and Design Requirements § 18.54 High-voltage continuous mining machines. (a) Separation of high... removed. (c) Circuit-interrupting devices. Circuit-interrupting devices must be designed and installed to... ground. (e) Onboard ungrounded, three-phase power circuit. A continuous mining machine designed with an...

FSW of Aluminum Tailor Welded Blanks across Machine Platforms

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hovanski, Yuri; Upadhyay, Piyush; Carlson, Blair

2015-02-16

Development and characterization of friction stir welded aluminum tailor welded blanks was successfully carried out on three separate machine platforms. Each was a commercially available, gantry style, multi-axis machine designed specifically for friction stir welding. Weld parameters were developed to support high volume production of dissimilar thickness aluminum tailor welded blanks at speeds of 3 m/min and greater. Parameters originally developed on an ultra-high stiffness servo driven machine where first transferred to a high stiffness servo-hydraulic friction stir welding machine, and subsequently transferred to a purpose built machine designed to accommodate thin sheet aluminum welding. The inherent beam stiffness, bearingmore » compliance, and control system for each machine were distinctly unique, which posed specific challenges in transferring welding parameters across machine platforms. This work documents the challenges imposed by successfully transferring weld parameters from machine to machine, produced from different manufacturers and with unique control systems and interfaces.« less

Man/Machine Interaction Dynamics And Performance (MMIDAP) capability

NASA Technical Reports Server (NTRS)

Frisch, Harold P.

1991-01-01

The creation of an ability to study interaction dynamics between a machine and its human operator can be approached from a myriad of directions. The Man/Machine Interaction Dynamics and Performance (MMIDAP) project seeks to create an ability to study the consequences of machine design alternatives relative to the performance of both machine and operator. The class of machines to which this study is directed includes those that require the intelligent physical exertions of a human operator. While Goddard's Flight Telerobotic's program was expected to be a major user, basic engineering design and biomedical applications reach far beyond telerobotics. Ongoing efforts are outlined of the GSFC and its University and small business collaborators to integrate both human performance and musculoskeletal data bases with analysis capabilities necessary to enable the study of dynamic actions, reactions, and performance of coupled machine/operator systems.

Design of control system for optical fiber drawing machine driven by double motor

NASA Astrophysics Data System (ADS)

Yu, Yue Chen; Bo, Yu Ming; Wang, Jun

2018-01-01

Micro channel Plate (MCP) is a kind of large-area array electron multiplier with high two-dimensional spatial resolution, used as high-performance night vision intensifier. The high precision control of the fiber is the key technology of the micro channel plate manufacturing process, and it was achieved by the control of optical fiber drawing machine driven by dual-motor in this paper. First of all, utilizing STM32 chip, the servo motor drive and control circuit was designed to realize the dual motor synchronization. Secondly, neural network PID control algorithm was designed for controlling the fiber diameter fabricated in high precision; Finally, the hexagonal fiber was manufactured by this system and it shows that multifilament diameter accuracy of the fiber is +/- 1.5μm.

Machine learnt bond order potential to model metal-organic (Co-C) heterostructures.

PubMed

Narayanan, Badri; Chan, Henry; Kinaci, Alper; Sen, Fatih G; Gray, Stephen K; Chan, Maria K Y; Sankaranarayanan, Subramanian K R S

2017-11-30

A fundamental understanding of the inter-relationships between structure, morphology, atomic scale dynamics, chemistry, and physical properties of mixed metallic-covalent systems is essential to design novel functional materials for applications in flexible nano-electronics, energy storage and catalysis. To achieve such knowledge, it is imperative to develop robust and computationally efficient atomistic models that describe atomic interactions accurately within a single framework. Here, we present a unified Tersoff-Brenner type bond order potential (BOP) for a Co-C system, trained against lattice parameters, cohesive energies, equation of state, and elastic constants of different crystalline phases of cobalt as well as orthorhombic Co 2 C derived from density functional theory (DFT) calculations. The independent BOP parameters are determined using a combination of supervised machine learning (genetic algorithms) and local minimization via the simplex method. Our newly developed BOP accurately describes the structural, thermodynamic, mechanical, and surface properties of both the elemental components as well as the carbide phases, in excellent accordance with DFT calculations and experiments. Using our machine-learnt BOP potential, we performed large-scale molecular dynamics simulations to investigate the effect of metal/carbon concentration on the structure and mechanical properties of porous architectures obtained via self-assembly of cobalt nanoparticles and fullerene molecules. Such porous structures have implications in flexible electronics, where materials with high electrical conductivity and low elastic stiffness are desired. Using unsupervised machine learning (clustering), we identify the pore structure, pore-distribution, and metallic conduction pathways in self-assembled structures at different C/Co ratios. We find that as the C/Co ratio increases, the connectivity between the Co nanoparticles becomes limited, likely resulting in low electrical

Structural brain changes versus self-report: machine-learning classification of chronic fatigue syndrome patients.

PubMed

Sevel, Landrew S; Boissoneault, Jeff; Letzen, Janelle E; Robinson, Michael E; Staud, Roland

2018-05-30

Chronic fatigue syndrome (CFS) is a disorder associated with fatigue, pain, and structural/functional abnormalities seen during magnetic resonance brain imaging (MRI). Therefore, we evaluated the performance of structural MRI (sMRI) abnormalities in the classification of CFS patients versus healthy controls and compared it to machine learning (ML) classification based upon self-report (SR). Participants included 18 CFS patients and 15 healthy controls (HC). All subjects underwent T1-weighted sMRI and provided visual analogue-scale ratings of fatigue, pain intensity, anxiety, depression, anger, and sleep quality. sMRI data were segmented using FreeSurfer and 61 regions based on functional and structural abnormalities previously reported in patients with CFS. Classification was performed in RapidMiner using a linear support vector machine and bootstrap optimism correction. We compared ML classifiers based on (1) 61 a priori sMRI regional estimates and (2) SR ratings. The sMRI model achieved 79.58% classification accuracy. The SR (accuracy = 95.95%) outperformed both sMRI models. Estimates from multiple brain areas related to cognition, emotion, and memory contributed strongly to group classification. This is the first ML-based group classification of CFS. Our findings suggest that sMRI abnormalities are useful for discriminating CFS patients from HC, but SR ratings remain most effective in classification tasks.

Uses of the Westrup brush machine

Treesearch

Jill Barbour

2002-01-01

The Westrup brush machine can be used as the first step in the conditioning process of seeds. Even though there are various sizes of the machine, only the laboratory model (LA-H) is described. The machine is designed to separate seed from pods or flowers, dewing tree seed, remove appendages or hairs from seed, split twin seed, de-lint cotton seed, scarify hard coated...

High-speed scanning of critical structures in aviation using coordinate measurement machine and the laser ultrasonic.

PubMed

Swornowski, Pawel J

2012-01-01

Aviation is one of the know-how spheres containing a great deal of responsible sub-assemblies, in this case landing gear. The necessity for reducing production cycle times while achieving better quality compels metrologists to look for new and improved ways to perform inspection of critical structures. This article describes the ability to determine the shape deviation and location of defects in landing gear using coordinate measuring machines and laser ultrasonic with high-speed scanning. A nondestructive test is the basis for monitoring microcrack and corrosion propagation in the context of a damage-tolerant design approach. This article presents an overview of the basics and of the various metrological aspects of coordinate measurement and a nondestructive testing method in terms of high-speed scanning. The new test method (laser ultrasonic) promises to produce the necessary increase in inspection quality, but this is limited by the wide range of materials, geometries, and structure aeronautic parts used. A technique combining laser ultrasonic and F-SAFT (Fourier-Synthetic Aperture Focusing Technique) processing has been proposed for the detection of small defects buried in landing gear. The experimental results of landing gear inspection are also presented. © Wiley Periodicals, Inc.

[Extension of cardiac monitoring function by used of ordinary ECG machine].

PubMed

Chen, Zhencheng; Jiang, Yong; Ni, Lili; Wang, Hongyan

2002-06-01

This paper deals with a portable monitor system on liquid crystal display (LCD) based on this available ordinary ECG machine, which is low power and suitable for China's specific condition. Apart from developing the overall scheme of the system, this paper also has completed the design of the hardware and the software. The 80c196 single chip microcomputer is taken as the central microprocessor and real time electrocardiac single is data treated and analyzed in the system. With the performance of ordinary monitor, this machine also possesses the following functions: five types of arrhythmia analysis, alarm, freeze, and record of automatic pappering, convenient in carrying, with alternate-current (AC) or direct-current (DC) powered. The hardware circuit is simplified and the software structure is optimized in this paper. Multiple low power designs and LCD unit design are adopted and completed in it. Popular in usage, low in cost price, the portable monitor system will have a valuable influence on China's monitor system field.

29 CFR 1926.1000 - Rollover protective structures (ROPS) for material handling equipment.

Code of Federal Regulations, 2013 CFR

2013-07-01

... two times the weight of the prime mover applied at the point of impact. (i) The design objective shall..., if any; (3) Machine make, model, or series number that the structure is designed to fit. (f) Machines... performance criteria detailed in §§ 1926.1001 and 1926.1002, as applicable or shall be designed, fabricated...

29 CFR 1926.1000 - Rollover protective structures (ROPS) for material handling equipment.

Code of Federal Regulations, 2010 CFR

2010-07-01

... two times the weight of the prime mover applied at the point of impact. (i) The design objective shall..., if any; (3) Machine make, model, or series number that the structure is designed to fit. (f) Machines... performance criteria detailed in §§ 1926.1001 and 1926.1002, as applicable or shall be designed, fabricated...

29 CFR 1926.1000 - Rollover protective structures (ROPS) for material handling equipment.

Code of Federal Regulations, 2014 CFR

2014-07-01

... two times the weight of the prime mover applied at the point of impact. (i) The design objective shall..., if any; (3) Machine make, model, or series number that the structure is designed to fit. (f) Machines... performance criteria detailed in §§ 1926.1001 and 1926.1002, as applicable or shall be designed, fabricated...

29 CFR 1926.1000 - Rollover protective structures (ROPS) for material handling equipment.

Code of Federal Regulations, 2011 CFR

2011-07-01

... two times the weight of the prime mover applied at the point of impact. (i) The design objective shall..., if any; (3) Machine make, model, or series number that the structure is designed to fit. (f) Machines... performance criteria detailed in §§ 1926.1001 and 1926.1002, as applicable or shall be designed, fabricated...

29 CFR 1926.1000 - Rollover protective structures (ROPS) for material handling equipment.

Code of Federal Regulations, 2012 CFR

2012-07-01

... two times the weight of the prime mover applied at the point of impact. (i) The design objective shall..., if any; (3) Machine make, model, or series number that the structure is designed to fit. (f) Machines... performance criteria detailed in §§ 1926.1001 and 1926.1002, as applicable or shall be designed, fabricated...

Designing Educational Social Machines for Effective Feedback

ERIC Educational Resources Information Center

Yee-King, Matthew; Krivenski, Maria; Brenton, Harry; Grimalt-Reynes, Andreu; d'Inverno, Mark

2014-01-01

We report on our development of an educational social machine based on the concept that feedback in communities is an effective means to support the development of communities of learning and practice. Key challenges faced by this work are how best to support educational and social interactions, how to deliver personalised tuition, and how to…

Man-machine interface analysis of the flight design system

NASA Technical Reports Server (NTRS)

Ramsey, H. R.; Atwood, M. E.; Willoughby, J. K.

1978-01-01

The objective of the current effort was to perform a broad analysis of the human factors issues involved in the design of the Flight Design System (FDS). The analysis was intended to include characteristics of the system itself, such as: (1) basic structure and functional capabilities of FDS; (2) user backgrounds, capabilities, and possible modes of use; (3) FDS interactive dialogue, problem solving aids; (4) system data management capabilities; and to include, as well, such system related matters as: (1) flight design team structure; (2) roles of technicians; (3) user training; and (4) methods of evaluating system performance. Wherever possible, specific recommendations are made. In other cases, the issues which seem most important are identified. In some cases, additional analyses or experiments which might provide resolution are suggested.

Design and simulation of a novel high-efficiency cooling heat-sink structure using fluid-thermodynamics

NASA Astrophysics Data System (ADS)

Hongqi, Jing; Li, Zhong; Yuxi, Ni; Junjie, Zhang; Suping, Liu; Xiaoyu, Ma

2015-10-01

A novel high-efficiency cooling mini-channel heat-sink structure has been designed to meet the package technology demands of high power density laser diode array stacks. Thermal and water flowing characteristics have been simulated using the Ansys-Fluent software. Owing to the increased effective cooling area, this mini-channel heat-sink structure has a better cooling effect when compared with the traditional macro-channel heat-sinks. Owing to the lower flow velocity in this novel high efficient cooling structure, the chillers' water-pressure requirement is reduced. Meanwhile, the machining process of this high-efficiency cooling mini-channel heat-sink structure is simple and the cost is relatively low, it also has advantages in terms of high durability and long lifetime. This heat-sink is an ideal choice for the package of high power density laser diode array stacks. Project supported by the Defense Industrial Technology Development Program (No. B1320133033).

AutoQSAR: an automated machine learning tool for best-practice quantitative structure-activity relationship modeling.

PubMed

Dixon, Steven L; Duan, Jianxin; Smith, Ethan; Von Bargen, Christopher D; Sherman, Woody; Repasky, Matthew P

2016-10-01

We introduce AutoQSAR, an automated machine-learning application to build, validate and deploy quantitative structure-activity relationship (QSAR) models. The process of descriptor generation, feature selection and the creation of a large number of QSAR models has been automated into a single workflow within AutoQSAR. The models are built using a variety of machine-learning methods, and each model is scored using a novel approach. Effectiveness of the method is demonstrated through comparison with literature QSAR models using identical datasets for six end points: protein-ligand binding affinity, solubility, blood-brain barrier permeability, carcinogenicity, mutagenicity and bioaccumulation in fish. AutoQSAR demonstrates similar or better predictive performance as compared with published results for four of the six endpoints while requiring minimal human time and expertise.

Machine Accounting. An Instructor's Guide.

ERIC Educational Resources Information Center

Gould, E. Noah, Ed.

Designed to prepare students to operate the types of accounting machines used in many medium-sized businesses, this instructor's guide presents a full-year high school course in machine accounting covering 120 hours of instruction. An introduction for the instructor suggests how to adapt the guide to present a 60-hour module which would be…

Run-time scheduling and execution of loops on message passing machines

NASA Technical Reports Server (NTRS)

Crowley, Kay; Saltz, Joel; Mirchandaney, Ravi; Berryman, Harry

1989-01-01

Sparse system solvers and general purpose codes for solving partial differential equations are examples of the many types of problems whose irregularity can result in poor performance on distributed memory machines. Often, the data structures used in these problems are very flexible. Crucial details concerning loop dependences are encoded in these structures rather than being explicitly represented in the program. Good methods for parallelizing and partitioning these types of problems require assignment of computations in rather arbitrary ways. Naive implementations of programs on distributed memory machines requiring general loop partitions can be extremely inefficient. Instead, the scheduling mechanism needs to capture the data reference patterns of the loops in order to partition the problem. First, the indices assigned to each processor must be locally numbered. Next, it is necessary to precompute what information is needed by each processor at various points in the computation. The precomputed information is then used to generate an execution template designed to carry out the computation, communication, and partitioning of data, in an optimized manner. The design is presented for a general preprocessor and schedule executer, the structures of which do not vary, even though the details of the computation and of the type of information are problem dependent.

Run-time scheduling and execution of loops on message passing machines

NASA Technical Reports Server (NTRS)

Saltz, Joel; Crowley, Kathleen; Mirchandaney, Ravi; Berryman, Harry

1990-01-01

Sparse system solvers and general purpose codes for solving partial differential equations are examples of the many types of problems whose irregularity can result in poor performance on distributed memory machines. Often, the data structures used in these problems are very flexible. Crucial details concerning loop dependences are encoded in these structures rather than being explicitly represented in the program. Good methods for parallelizing and partitioning these types of problems require assignment of computations in rather arbitrary ways. Naive implementations of programs on distributed memory machines requiring general loop partitions can be extremely inefficient. Instead, the scheduling mechanism needs to capture the data reference patterns of the loops in order to partition the problem. First, the indices assigned to each processor must be locally numbered. Next, it is necessary to precompute what information is needed by each processor at various points in the computation. The precomputed information is then used to generate an execution template designed to carry out the computation, communication, and partitioning of data, in an optimized manner. The design is presented for a general preprocessor and schedule executer, the structures of which do not vary, even though the details of the computation and of the type of information are problem dependent.

Design and verification of a novel hollow vibrating module for laser machining.

PubMed

Wang, Zhaozhao; Jang, Seungbong; Kim, EunHee; Jeon, Yongho; Lee, Soo-Hun; Lee, Moon G

2015-04-01

If a vibration module is added on laser machining system, the quality of surface finish and aspect ratio on metals can be significantly enhanced. In this study, a single mobility model of vibrating laser along the path of laser beam was put forward. In order to realize the desired unidirectional motion, a resonance type vibration module with optical lens was designed and manufactured. This cylindrical module was composed of curved-beam flexure elements. The cylindrical coordinate system was established to describe the relationship of a curved-beam flexure element's motion and deformation. In addition, the stiffness matrix of the curved-beam element was obtained. Finite element method and dynamical modeling were provided to analyze the resonance frequency and the displacement of the motion. The feasibility of the design was demonstrated with the help of experiments on frequency response. Experimental results show good agreement with theoretical analysis and simulation predictions.

Delivering key signals to the machine: seeking the electric signal that muscles emanate

NASA Astrophysics Data System (ADS)

Bani Hashim, A. Y.; Maslan, M. N.; Izamshah, R.; Mohamad, I. S.

2014-11-01

Due to the limitation of electric power generation in the human body, present human-machine interfaces have not been successful because of the nature of standard electronics circuit designs, which do not consider the specifications of signals that resulted from the skin. In general, the outcomes and applications of human-machine interfaces are limited to custom-designed subsystems, such as neuroprosthesis. We seek to model the bio dynamical of sub skin into equivalent mathematical definitions, descriptions, and theorems. Within the human skin, there are networks of nerves that permit the skin to function as a multi dimension transducer. We investigate the nature of structural skin. Apart from multiple networks of nerves, there are other segments within the skin such as minute muscles. We identify the segments that are active when there is an electromyography activity. When the nervous system is firing signals, the muscle is being stimulated. We evaluate the phenomena of biodynamic of the muscles that is concerned with the electromyography activity of the nervous system. In effect, we design a relationship between the human somatosensory and synthetic systems sensory as the union of a complete set of the new domain of the functional system. This classifies electromyogram waveforms linked to intent thought of an operator. The system will become the basis for delivering key signals to machine such that the machine is under operator's intent, hence slavery.

Parameter identification and optimization of slide guide joint of CNC machine tools

NASA Astrophysics Data System (ADS)

Zhou, S.; Sun, B. B.

2017-11-01

The joint surface has an important influence on the performance of CNC machine tools. In order to identify the dynamic parameters of slide guide joint, the parametric finite element model of the joint is established and optimum design method is used based on the finite element simulation and modal test. Then the mode that has the most influence on the dynamics of slip joint is found through harmonic response analysis. Take the frequency of this mode as objective, the sensitivity analysis of the stiffness of each joint surface is carried out using Latin Hypercube Sampling and Monte Carlo Simulation. The result shows that the vertical stiffness of slip joint surface constituted by the bed and the slide plate has the most obvious influence on the structure. Therefore, this stiffness is taken as the optimization variable and the optimal value is obtained through studying the relationship between structural dynamic performance and stiffness. Take the stiffness values before and after optimization into the FEM of machine tool, and it is found that the dynamic performance of the machine tool is improved.

Motor imaginary-based brain-machine interface design using programmable logic controllers for the disabled.

PubMed

Jeyabalan, Vickneswaran; Samraj, Andrews; Loo, Chu Kiong

2010-10-01

Aiming at the implementation of brain-machine interfaces (BMI) for the aid of disabled people, this paper presents a system design for real-time communication between the BMI and programmable logic controllers (PLCs) to control an electrical actuator that could be used in devices to help the disabled. Motor imaginary signals extracted from the brain’s motor cortex using an electroencephalogram (EEG) were used as a control signal. The EEG signals were pre-processed by means of adaptive recursive band-pass filtrations (ARBF) and classified using simplified fuzzy adaptive resonance theory mapping (ARTMAP) in which the classified signals are then translated into control signals used for machine control via the PLC. A real-time test system was designed using MATLAB for signal processing, KEP-Ware V4 OLE for process control (OPC), a wireless local area network router, an Omron Sysmac CPM1 PLC and a 5 V/0.3A motor. This paper explains the signal processing techniques, the PLC's hardware configuration, OPC configuration and real-time data exchange between MATLAB and PLC using the MATLAB OPC toolbox. The test results indicate that the function of exchanging real-time data can be attained between the BMI and PLC through OPC server and proves that it is an effective and feasible method to be applied to devices such as wheelchairs or electronic equipment.

Machine learning and data science in soft materials engineering

NASA Astrophysics Data System (ADS)

Ferguson, Andrew L.

2018-01-01

In many branches of materials science it is now routine to generate data sets of such large size and dimensionality that conventional methods of analysis fail. Paradigms and tools from data science and machine learning can provide scalable approaches to identify and extract trends and patterns within voluminous data sets, perform guided traversals of high-dimensional phase spaces, and furnish data-driven strategies for inverse materials design. This topical review provides an accessible introduction to machine learning tools in the context of soft and biological materials by ‘de-jargonizing’ data science terminology, presenting a taxonomy of machine learning techniques, and surveying the mathematical underpinnings and software implementations of popular tools, including principal component analysis, independent component analysis, diffusion maps, support vector machines, and relative entropy. We present illustrative examples of machine learning applications in soft matter, including inverse design of self-assembling materials, nonlinear learning of protein folding landscapes, high-throughput antimicrobial peptide design, and data-driven materials design engines. We close with an outlook on the challenges and opportunities for the field.

Machine learning and data science in soft materials engineering.

PubMed

Ferguson, Andrew L

2018-01-31

In many branches of materials science it is now routine to generate data sets of such large size and dimensionality that conventional methods of analysis fail. Paradigms and tools from data science and machine learning can provide scalable approaches to identify and extract trends and patterns within voluminous data sets, perform guided traversals of high-dimensional phase spaces, and furnish data-driven strategies for inverse materials design. This topical review provides an accessible introduction to machine learning tools in the context of soft and biological materials by 'de-jargonizing' data science terminology, presenting a taxonomy of machine learning techniques, and surveying the mathematical underpinnings and software implementations of popular tools, including principal component analysis, independent component analysis, diffusion maps, support vector machines, and relative entropy. We present illustrative examples of machine learning applications in soft matter, including inverse design of self-assembling materials, nonlinear learning of protein folding landscapes, high-throughput antimicrobial peptide design, and data-driven materials design engines. We close with an outlook on the challenges and opportunities for the field.

Control/structure interaction design methodology

NASA Technical Reports Server (NTRS)

Briggs, Hugh C.; Layman, William E.

1989-01-01

The Control Structure Interaction Program is a technology development program for spacecraft that exhibit interactions between the control system and structural dynamics. The program objectives include development and verification of new design concepts (such as active structure) and new tools (such as a combined structure and control optimization algorithm) and their verification in ground and possibly flight test. The new CSI design methodology is centered around interdisciplinary engineers using new tools that closely integrate structures and controls. Verification is an important CSI theme and analysts will be closely integrated to the CSI Test Bed laboratory. Components, concepts, tools and algorithms will be developed and tested in the lab and in future Shuttle-based flight experiments. The design methodology is summarized in block diagrams depicting the evolution of a spacecraft design and descriptions of analytical capabilities used in the process. The multiyear JPL CSI implementation plan is described along with the essentials of several new tools. A distributed network of computation servers and workstations was designed that will provide a state-of-the-art development base for the CSI technologies.

Engineering molecular machines

NASA Astrophysics Data System (ADS)

Erman, Burak

2016-04-01

Biological molecular motors use chemical energy, mostly in the form of ATP hydrolysis, and convert it to mechanical energy. Correlated thermal fluctuations are essential for the function of a molecular machine and it is the hydrolysis of ATP that modifies the correlated fluctuations of the system. Correlations are consequences of the molecular architecture of the protein. The idea that synthetic molecular machines may be constructed by designing the proper molecular architecture is challenging. In their paper, Sarkar et al (2016 New J. Phys. 18 043006) propose a synthetic molecular motor based on the coarse grained elastic network model of proteins and show by numerical simulations that motor function is realized, ranging from deterministic to thermal, depending on temperature. This work opens up a new range of possibilities of molecular architecture based engine design.

Does the Laser-Microtextured Short Implant Collar Design Reduce Marginal Bone Loss in Comparison with a Machined Collar?

PubMed Central

Sirali, Ali; Gultekin, Pinar; Yalcin, Serdar; Mijiritsky, Eitan

2016-01-01

Purpose. To compare marginal bone loss between subgingivally placed short-collar implants with machined collars and those with machined and laser-microtextured collars. Materials and Methods. The investigators used a retrospective study design and included patients who needed missing posterior teeth replaced with implants. Short-collar implants with identical geometries were divided into two groups: an M group, machined collar; and an L group, machined and laser-microtextured collar. Implants were evaluated according to marginal bone loss, implant success, and probing depth (PD) at 3 years of follow-up. Results. Sixty-two patients received 103 implants (56 in the M group and 47 in the L group). The cumulative survival rate was 100%. All implants showed clinically acceptable marginal bone loss, although bone resorption was lower in the L group (0.49 mm) than in the M group (1.38 mm) at 3 years (p < 0.01). A significantly shallower PD was found for the implants in the L group during follow-up (p < 0.01). Conclusions. Our results suggest predictable outcomes with regard to bone loss for both groups; however, bone resorption was less in the L group than in the M group before and after loading. The laser-microtextured collar implant may provide a shallower PD than the machined collar implant. PMID:27660765

Intelligible machine learning with malibu.

PubMed

Langlois, Robert E; Lu, Hui

2008-01-01

malibu is an open-source machine learning work-bench developed in C/C++ for high-performance real-world applications, namely bioinformatics and medical informatics. It leverages third-party machine learning implementations for more robust bug-free software. This workbench handles several well-studied supervised machine learning problems including classification, regression, importance-weighted classification and multiple-instance learning. The malibu interface was designed to create reproducible experiments ideally run in a remote and/or command line environment. The software can be found at: http://proteomics.bioengr. uic.edu/malibu/index.html.

Man-Machine Integration Design and Analysis System (MIDAS) v5: Augmentations, Motivations, and Directions for Aeronautics Applications

NASA Technical Reports Server (NTRS)

Gore, Brian F.

2011-01-01

As automation and advanced technologies are introduced into transport systems ranging from the Next Generation Air Transportation System termed NextGen, to the advanced surface transportation systems as exemplified by the Intelligent Transportations Systems, to future systems designed for space exploration, there is an increased need to validly predict how the future systems will be vulnerable to error given the demands imposed by the assistive technologies. One formalized approach to study the impact of assistive technologies on the human operator in a safe and non-obtrusive manner is through the use of human performance models (HPMs). HPMs play an integral role when complex human-system designs are proposed, developed, and tested. One HPM tool termed the Man-machine Integration Design and Analysis System (MIDAS) is a NASA Ames Research Center HPM software tool that has been applied to predict human-system performance in various domains since 1986. MIDAS is a dynamic, integrated HPM and simulation environment that facilitates the design, visualization, and computational evaluation of complex man-machine system concepts in simulated operational environments. The paper will discuss a range of aviation specific applications including an approach used to model human error for NASA s Aviation Safety Program, and what-if analyses to evaluate flight deck technologies for NextGen operations. This chapter will culminate by raising two challenges for the field of predictive HPMs for complex human-system designs that evaluate assistive technologies: that of (1) model transparency and (2) model validation.

A predictive machine learning approach for microstructure optimization and materials design

NASA Astrophysics Data System (ADS)

Liu, Ruoqian; Kumar, Abhishek; Chen, Zhengzhang; Agrawal, Ankit; Sundararaghavan, Veera; Choudhary, Alok

2015-06-01

This paper addresses an important materials engineering question: How can one identify the complete space (or as much of it as possible) of microstructures that are theoretically predicted to yield the desired combination of properties demanded by a selected application? We present a problem involving design of magnetoelastic Fe-Ga alloy microstructure for enhanced elastic, plastic and magnetostrictive properties. While theoretical models for computing properties given the microstructure are known for this alloy, inversion of these relationships to obtain microstructures that lead to desired properties is challenging, primarily due to the high dimensionality of microstructure space, multi-objective design requirement and non-uniqueness of solutions. These challenges render traditional search-based optimization methods incompetent in terms of both searching efficiency and result optimality. In this paper, a route to address these challenges using a machine learning methodology is proposed. A systematic framework consisting of random data generation, feature selection and classification algorithms is developed. Experiments with five design problems that involve identification of microstructures that satisfy both linear and nonlinear property constraints show that our framework outperforms traditional optimization methods with the average running time reduced by as much as 80% and with optimality that would not be achieved otherwise.

A predictive machine learning approach for microstructure optimization and materials design

DOE PAGES

Liu, Ruoqian; Kumar, Abhishek; Chen, Zhengzhang; ...

2015-06-23

This paper addresses an important materials engineering question: How can one identify the complete space (or as much of it as possible) of microstructures that are theoretically predicted to yield the desired combination of properties demanded by a selected application? We present a problem involving design of magnetoelastic Fe-Ga alloy microstructure for enhanced elastic, plastic and magnetostrictive properties. While theoretical models for computing properties given the microstructure are known for this alloy, inversion of these relationships to obtain microstructures that lead to desired properties is challenging, primarily due to the high dimensionality of microstructure space, multi-objective design requirement and non-uniquenessmore » of solutions. These challenges render traditional search-based optimization methods incompetent in terms of both searching efficiency and result optimality. In this paper, a route to address these challenges using a machine learning methodology is proposed. A systematic framework consisting of random data generation, feature selection and classification algorithms is developed. In conclusion, experiments with five design problems that involve identification of microstructures that satisfy both linear and nonlinear property constraints show that our framework outperforms traditional optimization methods with the average running time reduced by as much as 80% and with optimality that would not be achieved otherwise.« less

Risk estimation using probability machines.

PubMed

Dasgupta, Abhijit; Szymczak, Silke; Moore, Jason H; Bailey-Wilson, Joan E; Malley, James D

2014-03-01

Logistic regression has been the de facto, and often the only, model used in the description and analysis of relationships between a binary outcome and observed features. It is widely used to obtain the conditional probabilities of the outcome given predictors, as well as predictor effect size estimates using conditional odds ratios. We show how statistical learning machines for binary outcomes, provably consistent for the nonparametric regression problem, can be used to provide both consistent conditional probability estimation and conditional effect size estimates. Effect size estimates from learning machines leverage our understanding of counterfactual arguments central to the interpretation of such estimates. We show that, if the data generating model is logistic, we can recover accurate probability predictions and effect size estimates with nearly the same efficiency as a correct logistic model, both for main effects and interactions. We also propose a method using learning machines to scan for possible interaction effects quickly and efficiently. Simulations using random forest probability machines are presented. The models we propose make no assumptions about the data structure, and capture the patterns in the data by just specifying the predictors involved and not any particular model structure. So they do not run the same risks of model mis-specification and the resultant estimation biases as a logistic model. This methodology, which we call a "risk machine", will share properties from the statistical machine that it is derived from.

ABILITIES OF FIRST-GRADE PUPILS TO LEARN MATERIALS IN TERMS OF ALGEBRAIC STRUCTURES BY TEACHING MACHINES.

ERIC Educational Resources Information Center

CRAWFORD, ROBERT C.; KEISLAR, EVAN R.

THE MAJOR PROBLEM OF THIS INVESTIGATION WAS TO DETERMINE TO WHAT EXTENT FIRST-GRADE PUPILS ARE CAPABLE OF LEARNING ALGEBRAIC STRUCTURES THROUGH PROGRAMED INSTRUCTION. IN THE EXPERIMENT APPROXIMATELY 130 FIRST-GRADERS WERE INSTRUCTED THROUGH AUDIOVISUAL TEACHING MACHINES FOR APPROXIMATELY 15 WEEKS. AT THE END OF THE PROGRAM, THE CHILDREN WERE…

Modified automatic teller machine prototype for older adults: a case study of participative approach to inclusive design.

PubMed

Chan, Chetwyn C H; Wong, Alex W K; Lee, Tatia M C; Chi, Iris

2009-03-01

The goal of this study was to enhance an existing automated teller machine (ATM) human-machine interface in order to accommodate the needs of older adults. Older adults were involved in the design and field test of the modified ATM prototype. The design of the user interface and functionality took the cognitive and physical abilities of older adults into account. The modified ATM system included only "cash withdrawal" and "transfer" functions based on the task demands and needs for services of older adults. One hundred and forty-one older adults (aged 60 or above) participated in the field test by operating modified or existing ATM systems. Those who operated the modified system were found to have significantly higher success rates than those who operated the existing system. The enhancement was most significant among older adults who had lower ATM-related abilities, a lower level of education, and no prior experience of using ATMs. This study demonstrates the usefulness of using a universal design and participatory approach to modify the existing ATM system for use by older adults. However, it also leads to a reduction in functionality of the enhanced system. Future studies should explore ways to develop a universal design ATM system which can satisfy the abilities and needs of all users in the entire population.

Multicutter machining of compound parametric surfaces

NASA Astrophysics Data System (ADS)

Hatna, Abdelmadjid; Grieve, R. J.; Broomhead, P.

2000-10-01

Parametric free forms are used in industries as disparate as footwear, toys, sporting goods, ceramics, digital content creation, and conceptual design. Optimizing tool path patterns and minimizing the total machining time is a primordial issue in numerically controlled (NC) machining of free form surfaces. We demonstrate in the present work that multi-cutter machining can achieve as much as 60% reduction in total machining time for compound sculptured surfaces. The given approach is based upon the pre-processing as opposed to the usual post-processing of surfaces for the detection and removal of interference followed by precise tracking of unmachined areas.

30 CFR 18.49 - Connection boxes on machines.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 1 2011-07-01 2011-07-01 false Connection boxes on machines. 18.49 Section 18... Design Requirements § 18.49 Connection boxes on machines. Connection boxes used to facilitate replacement of cables or machine components shall be explosion-proof. Portable-cable terminals on cable reels...

Ultra-Structure database design methodology for managing systems biology data and analyses

PubMed Central

Maier, Christopher W; Long, Jeffrey G; Hemminger, Bradley M; Giddings, Morgan C

2009-01-01

Background Modern, high-throughput biological experiments generate copious, heterogeneous, interconnected data sets. Research is dynamic, with frequently changing protocols, techniques, instruments, and file formats. Because of these factors, systems designed to manage and integrate modern biological data sets often end up as large, unwieldy databases that become difficult to maintain or evolve. The novel rule-based approach of the Ultra-Structure design methodology presents a potential solution to this problem. By representing both data and processes as formal rules within a database, an Ultra-Structure system constitutes a flexible framework that enables users to explicitly store domain knowledge in both a machine- and human-readable form. End users themselves can change the system's capabilities without programmer intervention, simply by altering database contents; no computer code or schemas need be modified. This provides flexibility in adapting to change, and allows integration of disparate, heterogenous data sets within a small core set of database tables, facilitating joint analysis and visualization without becoming unwieldy. Here, we examine the application of Ultra-Structure to our ongoing research program for the integration of large proteomic and genomic data sets (proteogenomic mapping). Results We transitioned our proteogenomic mapping information system from a traditional entity-relationship design to one based on Ultra-Structure. Our system integrates tandem mass spectrum data, genomic annotation sets, and spectrum/peptide mappings, all within a small, general framework implemented within a standard relational database system. General software procedures driven by user-modifiable rules can perform tasks such as logical deduction and location-based computations. The system is not tied specifically to proteogenomic research, but is rather designed to accommodate virtually any kind of biological research. Conclusion We find Ultra-Structure offers

Model reduction in integrated controls-structures design

NASA Technical Reports Server (NTRS)

Maghami, Peiman G.

1993-01-01

It is the objective of this paper to present a model reduction technique developed for the integrated controls-structures design of flexible structures. Integrated controls-structures design problems are typically posed as nonlinear mathematical programming problems, where the design variables consist of both structural and control parameters. In the solution process, both structural and control design variables are constantly changing; therefore, the dynamic characteristics of the structure are also changing. This presents a problem in obtaining a reduced-order model for active control design and analysis which will be valid for all design points within the design space. In other words, the frequency and number of the significant modes of the structure (modes that should be included) may vary considerably throughout the design process. This is also true as the locations and/or masses of the sensors and actuators change. Moreover, since the number of design evaluations in the integrated design process could easily run into thousands, any feasible order-reduction method should not require model reduction analysis at every design iteration. In this paper a novel and efficient technique for model reduction in the integrated controls-structures design process, which addresses these issues, is presented.

Design of intelligent proximity detection zones to prevent striking and pinning fatalities around continuous mining machines.

PubMed

Bissert, P T; Carr, J L; DuCarme, J P; Smith, A K

2016-01-01

The continuous mining machine is a key piece of equipment used in underground coal mining operations. Over the past several decades these machines have been involved in a number of mine worker fatalities. Proximity detection systems have been developed to avert hazards associated with operating continuous mining machines. Incorporating intelligent design into proximity detection systems allows workers greater freedom to position themselves to see visual cues or avoid other hazards such as haulage equipment or unsupported roof or ribs. However, intelligent systems must be as safe as conventional proximity detection systems. An evaluation of the 39 fatal accidents for which the Mine Safety and Health Administration has published fatality investigation reports was conducted to determine whether the accident may have been prevented by conventional or intelligent proximity. Multiple zone configurations for the intelligent systems were studied to determine how system performance might be affected by the zone configuration. Researchers found that 32 of the 39 fatalities, or 82 percent, may have been prevented by both conventional and intelligent proximity systems. These results indicate that, by properly configuring the zones of an intelligent proximity detection system, equivalent protection to a conventional system is possible.

Sequence invariant state machines

NASA Technical Reports Server (NTRS)

Whitaker, S.; Manjunath, S.

1990-01-01

A synthesis method and new VLSI architecture are introduced to realize sequential circuits that have the ability to implement any state machine having N states and m inputs, regardless of the actual sequence specified in the flow table. A design method is proposed that utilizes BTS logic to implement regular and dense circuits. A given state sequence can be programmed with power supply connections or dynamically reallocated if stored in a register. Arbitrary flow table sequences can be modified or programmed to dynamically alter the function of the machine. This allows VLSI controllers to be designed with the programmability of a general purpose processor but with the compact size and performance of dedicated logic.

Biomarkers of Eating Disorders Using Support Vector Machine Analysis of Structural Neuroimaging Data: Preliminary Results

PubMed Central

Cerasa, Antonio; Castiglioni, Isabella; Salvatore, Christian; Funaro, Angela; Martino, Iolanda; Alfano, Stefania; Donzuso, Giulia; Perrotta, Paolo; Gioia, Maria Cecilia; Gilardi, Maria Carla; Quattrone, Aldo

2015-01-01

Presently, there are no valid biomarkers to identify individuals with eating disorders (ED). The aim of this work was to assess the feasibility of a machine learning method for extracting reliable neuroimaging features allowing individual categorization of patients with ED. Support Vector Machine (SVM) technique, combined with a pattern recognition method, was employed utilizing structural magnetic resonance images. Seventeen females with ED (six with diagnosis of anorexia nervosa and 11 with bulimia nervosa) were compared against 17 body mass index-matched healthy controls (HC). Machine learning allowed individual diagnosis of ED versus HC with an Accuracy ≥ 0.80. Voxel-based pattern recognition analysis demonstrated that voxels influencing the classification Accuracy involved the occipital cortex, the posterior cerebellar lobule, precuneus, sensorimotor/premotor cortices, and the medial prefrontal cortex, all critical regions known to be strongly involved in the pathophysiological mechanisms of ED. Although these findings should be considered preliminary given the small size investigated, SVM analysis highlights the role of well-known brain regions as possible biomarkers to distinguish ED from HC at an individual level, thus encouraging the translational implementation of this new multivariate approach in the clinical practice. PMID:26648660

Structural design and fabrication techniques of composite unmanned aerial vehicles

NASA Astrophysics Data System (ADS)

Hunt, Daniel Stephen

Popularity of unmanned aerial vehicles has grown substantially in recent years both in the private sector, as well as for government functions. This growth can be attributed largely to the increased performance of the technology that controls these vehicles, as well as decreasing cost and size of this technology. What is sometimes forgotten though, is that the research and advancement of the airframes themselves are equally as important as what is done with them. With current computer-aided design programs, the limits of design optimization can be pushed further than ever before, resulting in lighter and faster airframes that can achieve longer endurances, higher altitudes, and more complex missions. However, realization of a paper design is still limited by the physical restrictions of the real world and the structural constraints associated with it. The purpose of this paper is to not only step through current design and manufacturing processes of composite UAVs at Oklahoma State University, but to also focus on composite spars, utilizing and relating both calculated and empirical data. Most of the experience gained for this thesis was from the Cessna Longitude project. The Longitude is a 1/8 scale, flying demonstrator Oklahoma State University constructed for Cessna. For the project, Cessna required dynamic flight data for their design process in order to make their 2017 release date. Oklahoma State University was privileged enough to assist Cessna with the mission of supporting the validation of design of their largest business jet to date. This paper will detail the steps of the fabrication process used in construction of the Longitude, as well as several other projects, beginning with structural design, machining, molding, skin layup, and ending with final assembly. Also, attention will be paid specifically towards spar design and testing in effort to ease the design phase. This document is intended to act not only as a further development of current

Optimization design about gimbal structure of high-precision autonomous celestial navigation tracking mirror system

NASA Astrophysics Data System (ADS)

Huang, Wei; Yang, Xiao-xu; Han, Jun-feng; Wei, Yu; Zhang, Jing; Xie, Mei-lin; Yue, Peng

2016-01-01

High precision tracking platform of celestial navigation with control mirror servo structure form, to solve the disadvantages of big volume and rotational inertia, slow response speed, and so on. It improved the stability and tracking accuracy of platform. Due to optical sensor and mirror are installed on the middle-gimbal, stiffness and resonant frequency requirement for high. Based on the application of finite element modality analysis theory, doing Research on dynamic characteristics of the middle-gimbal, and ANSYS was used for the finite element dynamic emulator analysis. According to the result of the computer to find out the weak links of the structure, and Put forward improvement suggestions and reanalysis. The lowest resonant frequency of optimization middle-gimbal avoid the bandwidth of the platform servo mechanism, and much higher than the disturbance frequency of carrier aircraft, and reduces mechanical resonance of the framework. Reaching provides a theoretical basis for the whole machine structure optimization design of high-precision of autonomous Celestial navigation tracking mirror system.

Research study concerning the 3D printing adittion (FDM-fused deposition modeling) to design UAV (UAV-unconventional aerial vehicle) structures

NASA Astrophysics Data System (ADS)

Pascu, Nicoleta Elisabeta; CǎruÅ£aşu, Nicoleta LuminiÅ£a.; Geambaşu, Gabriel George; Adîr, Victor Gabriel; Arion, Aurel Florin; Ivaşcu, Laura

2018-02-01

Aerial vehicles have become indispensable. There are in this field UAV (Unconventional Aerial vehicle) and transportation airplanes and other aerospace vehicles for spatial tourism. Today, the research and development activity in aerospace industry is focused to obtain a good and efficient design for airplanes, to solve the problem of high pollution and to reduce the noise. For these goals are necessary to realize light and resistant components. The aerospace industry products are, generally, very complex concerning geometric shapes and the costs are high, usually. Due to the progress in this field (products obtained using FDM) was possible to reduce the number of used tools, welding belts, and, of course, to eliminate a lot of machine tools. In addition, the complex shapes are easier product using this high technology, the cost is more attractive and the time is lower. This paper allows to present a few aspects about FDM technology and the obtained structures using it, as follows: computer geometric modeling (different designing softs) to design and redesign complex structures using 3D printing, for this kind of vehicles; finite element analysis to identify what is the influence of design for different structures; testing the structures.

Integrated Controls-Structures Design Methodology: Redesign of an Evolutionary Test Structure

NASA Technical Reports Server (NTRS)

Maghami, Peiman G.; Gupta, Sandeep; Elliot, Kenny B.; Joshi, Suresh M.

1997-01-01

An optimization-based integrated controls-structures design methodology for a class of flexible space structures is described, and the phase-0 Controls-Structures-Integration evolutionary model, a laboratory testbed at NASA Langley, is redesigned using this integrated design methodology. The integrated controls-structures design is posed as a nonlinear programming problem to minimize the control effort required to maintain a specified line-of-sight pointing performance, under persistent white noise disturbance. Static and dynamic dissipative control strategies are employed for feedback control, and parameters of these controllers are considered as the control design variables. Sizes of strut elements in various sections of the CEM are used as the structural design variables. Design guides for the struts are developed and employed in the integrated design process, to ensure that the redesigned structure can be effectively fabricated. The superiority of the integrated design methodology over the conventional design approach is demonstrated analytically by observing a significant reduction in the average control power needed to maintain specified pointing performance with the integrated design approach.

Fatigue strength: effect of welding type and joint design executed in Ti-6Al-4V structures.

PubMed

Pantoja, Juliana M C Nuñez; Farina, Ana P; Vaz, Luis G; Consani, Rafael L X; Nóbilo, Mauro A de Arruda; Mesquita, Marcelo F

2012-06-01

This study evaluated the fatigue strength of Ti-6Al-4V-machined structures submitted to laser (L)-welding and TIG (TIG)-welding procedures, varying the joint designs. Seventy dumbbell rods were machined in Ti-6Al-4V alloy with central diameters of 3.5 mm. The specimens were sectioned and welded using TIG or L and three joint designs {'I' design, varying welding distances [0.0 mm (I00) or 0.6 mm (I06)], or 'X' [X] design}. The combinations of variables created six groups, which, when added to the intact group, made a total of seven groups (n = 10). L was executed as follows: 360 V/8 ms (X) and 390 V/9 ms (I00 and I06), with focus and frequency regulated to zero. TIG was executed using 2:2 (X) and 3:2 (I00 and I06) as welding parameters. Joints were finished, polished and submitted to radiographic examination to be analysed visually for the presence of porosity. The specimens were then subjected to mechanical cyclic tests, and the number of cycles completed until failure was recorded. The fracture surface was examined using a scanning electron microscope. The Kruskal-Wallis and Dunn test (α = 0.05) indicated that the number of cycles resisted for fracture was higher to X for both welding procedures. To L, I06 was as resistant as X. The Mann-Whitney U-test (α = 0.05) indicated that L joints were more resistant than TIG to I00 and I06. Spearman's correlation coefficient (α = 0.05) indicated a negative correlation between the number of cycles and presence of porosity. Thus, to weld Ti-6Al-4V structures, the best condition is X, independent of the welding method employed. © 2011 The Gerodontology Society and John Wiley & Sons A/S.

Structural Optimization in automotive design

NASA Technical Reports Server (NTRS)

Bennett, J. A.; Botkin, M. E.

1984-01-01

Although mathematical structural optimization has been an active research area for twenty years, there has been relatively little penetration into the design process. Experience indicates that often this is due to the traditional layout-analysis design process. In many cases, optimization efforts have been outgrowths of analysis groups which are themselves appendages to the traditional design process. As a result, optimization is often introduced into the design process too late to have a significant effect because many potential design variables have already been fixed. A series of examples are given to indicate how structural optimization has been effectively integrated into the design process.

Machine-learned and codified synthesis parameters of oxide materials

NASA Astrophysics Data System (ADS)

Kim, Edward; Huang, Kevin; Tomala, Alex; Matthews, Sara; Strubell, Emma; Saunders, Adam; McCallum, Andrew; Olivetti, Elsa

2017-09-01

Predictive materials design has rapidly accelerated in recent years with the advent of large-scale resources, such as materials structure and property databases generated by ab initio computations. In the absence of analogous ab initio frameworks for materials synthesis, high-throughput and machine learning techniques have recently been harnessed to generate synthesis strategies for select materials of interest. Still, a community-accessible, autonomously-compiled synthesis planning resource which spans across materials systems has not yet been developed. In this work, we present a collection of aggregated synthesis parameters computed using the text contained within over 640,000 journal articles using state-of-the-art natural language processing and machine learning techniques. We provide a dataset of synthesis parameters, compiled autonomously across 30 different oxide systems, in a format optimized for planning novel syntheses of materials.

Intensification of the Students' Self-Development Process When Performing Design and Settlement Works on the "Machine Parts" Course

ERIC Educational Resources Information Center

Timerbaev, Rais Mingalievich; Muhutdinov, Rafis Habreevich; Danilov, Valeriy Fedorovich

2015-01-01

The article addresses issues related to the methodology of intensifying self-development process when performing design and settlement works on the "Machine Parts" course for the students studying in such areas of training as "Technology" and "Vocational Education" with the use of computer technologies. At the same…

[Research, design and application of model NSE-1 neck muscle training machine for pilots].

PubMed

Cheng, Haiping; Wang, Zhijie; Liu, Songyang; Yang, Yi; Zhao, Guang; Cong, Hong; Han, Xueping; Liu, Min; Yu, Mengsun

2011-04-01

Pain in the cervical region of air force pilots, who are exposed to high G-forces, is a specifically occupational health problem. To minimize neck problems, the cervical muscles need specific strength exercise. It is important that the training for the neck must be carried out with optimal resistance in exercises. The model NSE-1 neck training machine for pilots was designed for neck strengthening exercises under safe and effective conditions. In order to realize the functions of changeable velocity and resistant (CVR) training and neck isometric contractive exercises, the techniques of adaptive hydraulics, sensor, optic and auditory biological feedback, and signal processing were applied to this machine. The training system mainly consists of mechanical parts (including the chair of flexion and extension, the chair of right and left lateral flexion, the components of hydraulics and torque transformer, etc.), and the software of signal processing and biological feedback. Eleven volunteers were selected for the experiments of neck isometric contractive exercises, three times a week for 6 weeks, where CVR training (flexion, extension, right, left lateral flexion) one time a week. The increase in relative strength of the neck (flexion, extension, left and right lateral flexion) was 70.8%, 83.7%, 78.6% and 75.2%, respectively after training. Results show that the strength of the neck can be increased safely, effectively and rapidly with NSE-1 neck training machine to perform neck training.

Diamond turning machine controller implementation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Garrard, K.P.; Taylor, L.W.; Knight, B.F.

The standard controller for a Pnuemo ASG 2500 Diamond Turning Machine, an Allen Bradley 8200, has been replaced with a custom high-performance design. This controller consists of four major components. Axis position feedback information is provided by a Zygo Axiom 2/20 laser interferometer with 0.1 micro-inch resolution. Hardware interface logic couples the computers digital and analog I/O channels to the diamond turning machine`s analog motor controllers, the laser interferometer, and other machine status and control information. It also provides front panel switches for operator override of the computer controller and implement the emergency stop sequence. The remaining two components, themore » control computer hardware and software, are discussed in detail below.« less

Structural Composites Industries 4 kilowatt wind system development. Phase I: design and analysis, technical report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Malkine, N.; Bottrell, G.; Weingart, O.

1981-05-01

A 4 kW small wind energy conversion system (SWECS) has been designed for residential applications in which relatively low (10 mph) mean annual wind speeds prevail. The objectives were to develop such a machine to produce electrical energy at 6 cents per kWh while operating in parallel with a utility grid or auxiliary generator. The Phase I effort began in November, 1979 and was carried through the Final Design Review in February 1981. During this period extensive trade, optimization and analytical studies were performed in an effort to provide the optimum machine to best meet the objectives. Certain components, systemsmore » and manufacturing processes were tested and evaluated and detail design drawings were produced. The resulting design is a 31-foot diameter horizontal axis downwind machine rated 5.7 kW and incorporating the following unique features: Composite Blades; Free-Standing Composite Tower; Torque-Actuated Blade Pitch Control. The design meets or exceeds all contract requirements except that for cost of energy. The target 6 cents per kWh will be achieved in a mean wind speed slightly below 12 mph instead of the specified 10 mph.« less

Multidisciplinary Concurrent Design Optimization via the Internet

NASA Technical Reports Server (NTRS)

Woodard, Stanley E.; Kelkar, Atul G.; Koganti, Gopichand

2001-01-01

A methodology is presented which uses commercial design and analysis software and the Internet to perform concurrent multidisciplinary optimization. The methodology provides a means to develop multidisciplinary designs without requiring that all software be accessible from the same local network. The procedures are amenable to design and development teams whose members, expertise and respective software are not geographically located together. This methodology facilitates multidisciplinary teams working concurrently on a design problem of common interest. Partition of design software to different machines allows each constituent software to be used on the machine that provides the most economy and efficiency. The methodology is demonstrated on the concurrent design of a spacecraft structure and attitude control system. Results are compared to those derived from performing the design with an autonomous FORTRAN program.

Research in Chinese-English Machine Translation. Final Report.

ERIC Educational Resources Information Center

Wang, William S-Y.; And Others

This report documents results of a two-year effort toward the study and investigation of the design of a prototype system for Chinese-English machine translation in the general area of physics. Previous work in Chinese-English machine translation is reviewed. Grammatical considerations in machine translation are discussed and detailed aspects of…

33 CFR 157.124 - COW tank washing machines.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 33 Navigation and Navigable Waters 2 2010-07-01 2010-07-01 false COW tank washing machines. 157... OIL IN BULK Crude Oil Washing (COW) System on Tank Vessels Design, Equipment, and Installation § 157.124 COW tank washing machines. (a) COW machines must be permanently mounted in each cargo tank. (b...

Man-Machine Communication Through a Teletypewriter.

ERIC Educational Resources Information Center

Rubinoff, Morris

A ten-year research study designed a mechanized information system in the information processing field. Special attention was paid to implementation criteria entering into on-line retrieval through man-machine dialog from a remote typewriter or video terminal and four major areas were investigated: search strategies, machine stored indexer aids,…

Design and FPGA Implementation of a Universal Chaotic Signal Generator Based on the Verilog HDL Fixed-Point Algorithm and State Machine Control

NASA Astrophysics Data System (ADS)

Qiu, Mo; Yu, Simin; Wen, Yuqiong; Lü, Jinhu; He, Jianbin; Lin, Zhuosheng

In this paper, a novel design methodology and its FPGA hardware implementation for a universal chaotic signal generator is proposed via the Verilog HDL fixed-point algorithm and state machine control. According to continuous-time or discrete-time chaotic equations, a Verilog HDL fixed-point algorithm and its corresponding digital system are first designed. In the FPGA hardware platform, each operation step of Verilog HDL fixed-point algorithm is then controlled by a state machine. The generality of this method is that, for any given chaotic equation, it can be decomposed into four basic operation procedures, i.e. nonlinear function calculation, iterative sequence operation, iterative values right shifting and ceiling, and chaotic iterative sequences output, each of which corresponds to only a state via state machine control. Compared with the Verilog HDL floating-point algorithm, the Verilog HDL fixed-point algorithm can save the FPGA hardware resources and improve the operation efficiency. FPGA-based hardware experimental results validate the feasibility and reliability of the proposed approach.

Biomorphic architectures for autonomous Nanosat designs

NASA Technical Reports Server (NTRS)

Hasslacher, Brosl; Tilden, Mark W.

1995-01-01

Modern space tool design is the science of making a machine both massively complex while at the same time extremely robust and dependable. We propose a novel nonlinear control technique that produces capable, self-organizing, micron-scale space machines at low cost and in large numbers by parallel silicon assembly. Experiments using biomorphic architectures (with ideal space attributes) have produced a wide spectrum of survival-oriented machines that are reliably domesticated for work applications in specific environments. In particular, several one-chip satellite prototypes show interesting control properties that can be turned into numerous application-specific machines for autonomous, disposable space tasks. We believe that the real power of these architectures lies in their potential to self-assemble into larger, robust, loosely coupled structures. Assembly takes place at hierarchical space scales, with different attendant properties, allowing for inexpensive solutions to many daunting work tasks. The nature of biomorphic control, design, engineering options, and applications are discussed.

Importance of polarity change in the electrical discharge machining

NASA Astrophysics Data System (ADS)

Schulze, H.-P.

2017-10-01

The polarity change in the electrical discharge machining is still a problem and is often performed completely unmotivated or randomly. The polarity must be designated primarily, i.e. the anodic part must be clearly assigned to the tool or the workpiece. Normally, the polarity of the workpiece electrode is named. In paper, will be shown which determine fundamental causes the structural behavior of the cathode and anode, and when it makes sense to change the polarity. The polarity change is primarily dependent on the materials that are used as cathode and anode. This distinction must be made if there are pure metals or complex materials. Secondary of the polarity change is also affected by the process energy source (PES) and the supply line. The polarity change is mostly influenced by the fact that the removal is to be maximized on the workpiece while the tool is minimal removal (wear) occur. A second factor that makes a polarity change needed is the use of electrical discharge in combination with other machining methods, such as electrochemical machining (ECM).

Structural design of Kaohsiung Stadium, Taiwan

USGS Publications Warehouse

Watanabe, Hideyuki; Tanno, Yoshiro; Nakai, Masayoshi; Ohshima, Takashi; Suguichi, Akihiro; Lee, William H.; Wang, Jensen

2013-01-01

This paper presents an outline description of the structural design of the main stadium for the World Games held in Kaohsiung City, Taiwan, in 2009. Three new design concepts, unseen in previous stadiums, were proposed and realized: “an open stadium”, “an urban park”, and “a spiral continuous form”. Based on the open stadium concept, simple cantilever trusses in the roof structure were arranged in a delicate rhythm, and a so-called oscillating hoop of steel tubes was wound around the top and bottom surfaces of a group of cantilever trusses to form a continuous spiral form. Also, at the same time by clearly grouping the structural elements of the roof structure, the dramatic effect of the urban park was highlighted by unifying the landscape and the spectator seating area to form the stadium facade. This paper specifically reports on the overview of the building, concepts of structural design, structural analysis of the roof, roof design, foundation design, and an outline of the construction.

Investigation of Dynamic Force/Vibration Transmission Characteristics of Four-Square Type Gear Durability Test Machines

NASA Technical Reports Server (NTRS)

Kahraman, Ahmet

2002-01-01

In this study, design requirements for a dynamically viable, four-square type gear test machine are investigated. Variations of four-square type gear test machines have been in use for durability and dynamics testing of both parallel- and cross-axis gear set. The basic layout of these machines is illustrated. The test rig is formed by two gear pairs, of the same reduction ratio, a test gear pair and a reaction gear pair, connected to each other through shafts of certain torsional flexibility to form an efficient, closed-loop system. A desired level of constant torque is input to the circuit through mechanical (a split coupling with a torque arm) or hydraulic (a hydraulic actuator) means. The system is then driven at any desired speed by a small DC motor. The main task in hand is the isolation of the test gear pair from the reaction gear pair under dynamic conditions. Any disturbances originated at the reaction gear mesh might potentially travel to the test gearbox, altering the dynamic loading conditions of the test gear mesh, and hence, influencing the outcome of the durability or dynamics test. Therefore, a proper design of connecting structures becomes a major priority. Also, equally important is the issue of how close the operating speed of the machine is to the resonant frequencies of the gear meshes. This study focuses on a detailed analysis of the current NASA Glenn Research Center gear pitting test machine for evaluation of its resonance and vibration isolation characteristics. A number of these machines as the one illustrated has been used over last 30 years to establish an extensive database regarding the influence of the gear materials, processes surface treatments and lubricants on gear durability. This study is intended to guide an optimum design of next generation test machines for the most desirable dynamic characteristics.

Effect of Thermal and Chemical Treatment on the Microstructural, Mechanical and Machining Performance of W319 Al-Si-Cu Cast Alloy Engine Blocks and Directionally Solidified Machinability Test Blocks

NASA Astrophysics Data System (ADS)

Szablewski, Daniel

The research presented in this work is focused on making a link between casting microstructural, mechanical and machining properties for 319 Al-Si sand cast components. In order to achieve this, a unique Machinability Test Block (MTB) is designed to simulate the Nemak V6 Al-Si engine block solidification behavior. This MTB is then utilized to cast structures with in-situ nano-alumina particle master alloy additions that are Mg based, as well as independent in-situ Mg additions, and Sr additions to the MTB. The Universal Metallurgical Simulator and Analyzer (UMSA) Technology Platform is utilized for characterization of each cast structure at different Secondary Dendrite Arm Spacing (SDAS) levels. The rapid quench method and Jominy testing is used to assess the capability of the nano-alumina master alloy to modify the microstructure at different SDAS levels. Mechanical property assessment of the MTB is done at different SDAS levels on cast structures with master alloy additions described above. Weibull and Quality Index statistical analysis tools are then utilized to assess the mechanical properties. The MTB is also used to study single pass high speed face milling and bi-metallic cutting operations where the Al-Si hypoeutectic structure is combined with hypereutectoid Al-Si liners and cast iron cylinder liners. These studies are utilized to aid the implementation of Al-Si liners into the Nemak V6 engine block and bi-metallic cutting of the head decks. Machining behavior is also quantified for the investigated microstructures, and the Silicon Modification Level (SiML) is utilized for microstructural analysis as it relates to the machining behavior.

Rapid Prototyping of Composite Structures

NASA Technical Reports Server (NTRS)

Colton, Jonathan S.

1998-01-01

This progress report for the project Rapid Production of Composite Structures covers the period from July 14, 1997 to June 30, 1998. It will present a short overview of the project, followed by the results to date and plans for the future. The goal of this research is to provide a minimum 100x reduction in the time required to produce arbitrary, laminated products without the need for a separate mold or an autoclave. It will accomplish this by developing the science underlying the rapid production of composite structures, specifically those of carbon fiber-epoxy materials. This scientific understanding will be reduced to practice in a demonstration device that will produce a part on the order of 12" by 12" by 6". Work in the past year has focussed on developing an understanding of the materials issues and of the machine design issues. Our initial goal was to use UV cureable resins to accomplish full cure on the machine. Therefore, we have centered our materials work around whether or not UV cureable resins will work. Currently, the answer seems to be that they will not work, because UV light cannot penetrate the carbon fibers, and because no "shadow" curing seems to occur. As a result, non-UV cureable resins are being investigated. This has resulted in a change in the machine design focus. We are now looking into a "dip and place" machine design, whereby a prepreg layer would have one side coated with a curing agent, and then would be placed onto the previous layer. This would lead to cure at the interface, but not to the top of the layer. The formulation of the resins to accomplish this task at room or slightly elevated temperatures is being investigated, as is the machine design needed to apply the curing agent and then cure or partially cure the part. A final, out-of-autoclave, post-cure may be needed with this strategy, as final cure on the machine may not be possible, as it was for the initial UV cure strategy. The remainder of this report details the progress

Human-like machines: Transparency and comprehensibility.

PubMed

Patrzyk, Piotr M; Link, Daniela; Marewski, Julian N

2017-01-01

Artificial intelligence algorithms seek inspiration from human cognitive systems in areas where humans outperform machines. But on what level should algorithms try to approximate human cognition? We argue that human-like machines should be designed to make decisions in transparent and comprehensible ways, which can be achieved by accurately mirroring human cognitive processes.

Machine Shop. Performance Objectives. Basic Course.

ERIC Educational Resources Information Center

Hilton, Arthur; Lambert, George

Several intermediate performance objectives and corresponding criterion measures are listed for each of 13 terminal objectives for a high school basic machine shop course. The materials were developed for a 36-week course (2 hours daily) designed to enable students to become familiar with the operation of machine shop equipment, to become familiar…

Shape design sensitivity analysis and optimal design of structural systems

NASA Technical Reports Server (NTRS)

Choi, Kyung K.

1987-01-01

The material derivative concept of continuum mechanics and an adjoint variable method of design sensitivity analysis are used to relate variations in structural shape to measures of structural performance. A domain method of shape design sensitivity analysis is used to best utilize the basic character of the finite element method that gives accurate information not on the boundary but in the domain. Implementation of shape design sensitivty analysis using finite element computer codes is discussed. Recent numerical results are used to demonstrate the accuracy obtainable using the method. Result of design sensitivity analysis is used to carry out design optimization of a built-up structure.

21 CFR 870.4220 - Cardiopulmonary bypass heart-lung machine console.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 21 Food and Drugs 8 2010-04-01 2010-04-01 false Cardiopulmonary bypass heart-lung machine console... Cardiopulmonary bypass heart-lung machine console. (a) Identification. A cardiopulmonary bypass heart-lung machine... heart-lung machine. The console is designed to interface with the basic units used in a gas exchange...

21 CFR 870.4220 - Cardiopulmonary bypass heart-lung machine console.

Code of Federal Regulations, 2013 CFR

2013-04-01

... 21 Food and Drugs 8 2013-04-01 2013-04-01 false Cardiopulmonary bypass heart-lung machine console... Cardiopulmonary bypass heart-lung machine console. (a) Identification. A cardiopulmonary bypass heart-lung machine... heart-lung machine. The console is designed to interface with the basic units used in a gas exchange...

21 CFR 870.4220 - Cardiopulmonary bypass heart-lung machine console.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 21 Food and Drugs 8 2012-04-01 2012-04-01 false Cardiopulmonary bypass heart-lung machine console... Cardiopulmonary bypass heart-lung machine console. (a) Identification. A cardiopulmonary bypass heart-lung machine... heart-lung machine. The console is designed to interface with the basic units used in a gas exchange...

21 CFR 870.4220 - Cardiopulmonary bypass heart-lung machine console.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 21 Food and Drugs 8 2011-04-01 2011-04-01 false Cardiopulmonary bypass heart-lung machine console... Cardiopulmonary bypass heart-lung machine console. (a) Identification. A cardiopulmonary bypass heart-lung machine... heart-lung machine. The console is designed to interface with the basic units used in a gas exchange...

21 CFR 870.4220 - Cardiopulmonary bypass heart-lung machine console.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 21 Food and Drugs 8 2014-04-01 2014-04-01 false Cardiopulmonary bypass heart-lung machine console... Cardiopulmonary bypass heart-lung machine console. (a) Identification. A cardiopulmonary bypass heart-lung machine... heart-lung machine. The console is designed to interface with the basic units used in a gas exchange...

Using Pipelined XNOR Logic to Reduce SEU Risks in State Machines

NASA Technical Reports Server (NTRS)

Le, Martin; Zheng, Xin; Katanyoutant, Sunant

2008-01-01

Single-event upsets (SEUs) pose great threats to avionic systems state machine control logic, which are frequently used to control sequence of events and to qualify protocols. The risks of SEUs manifest in two ways: (a) the state machine s state information is changed, causing the state machine to unexpectedly transition to another state; (b) due to the asynchronous nature of SEU, the state machine's state registers become metastable, consequently causing any combinational logic associated with the metastable registers to malfunction temporarily. Effect (a) can be mitigated with methods such as triplemodular redundancy (TMR). However, effect (b) cannot be eliminated and can degrade the effectiveness of any mitigation method of effect (a). Although there is no way to completely eliminate the risk of SEU-induced errors, the risk can be made very small by use of a combination of very fast state-machine logic and error-detection logic. Therefore, one goal of two main elements of the present method is to design the fastest state-machine logic circuitry by basing it on the fastest generic state-machine design, which is that of a one-hot state machine. The other of the two main design elements is to design fast error-detection logic circuitry and to optimize it for implementation in a field-programmable gate array (FPGA) architecture: In the resulting design, the one-hot state machine is fitted with a multiple-input XNOR gate for detection of illegal states. The XNOR gate is implemented with lookup tables and with pipelines for high speed. In this method, the task of designing all the logic must be performed manually because no currently available logic synthesis software tool can produce optimal solutions of design problems of this type. However, some assistance is provided by a script, written for this purpose in the Python language (an object-oriented interpretive computer language) to automatically generate hardware description language (HDL) code from state

Nanomedicine: Tiny Particles and Machines Give Huge Gains

PubMed Central

Tong, Sheng; Fine, Eli J.; Lin, Yanni; Cradick, Thomas J.; Bao, Gang

2014-01-01

Nanomedicine is an emerging field that integrates nanotechnology, biomolecular engineering, life sciences and medicine; it is expected to produce major breakthroughs in medical diagnostics and therapeutics. Nano-scale structures and devices are compatible in size with proteins and nucleic acids in living cells. Therefore, the design, characterization and application of nano-scale probes, carriers and machines may provide unprecedented opportunities for achieving a better control of biological processes, and drastic improvements in disease detection, therapy, and prevention. Recent advances in nanomedicine include the development of nanoparticle-based probes for molecular imaging, nano-carriers for drug/gene delivery, multi-functional nanoparticles for theranostics, and molecular machines for biological and medical studies. This article provides an overview of the nanomedicine field, with an emphasis on nanoparticles for imaging and therapy, as well as engineered nucleases for genome editing. The challenges in translating nanomedicine approaches to clinical applications are discussed. PMID:24297494

Machine & electrical double control air dryer for vehicle air braking system

NASA Astrophysics Data System (ADS)

Zhang, Xuan; Yang, Liu; Wang, Xian Yan; Tan, Xiao Yan; Wang, Wei

2017-09-01

As is known to all, a vehicle air brake system, in which usually contains moisture. To solve the problem, it is common to use air dryer to dry compressed air effectively and completely remove the moisture and oil of braking system. However, the existing air dryer is not suitable for all commercial vehicles. According to the operational status of the new energy vehicles in the initial operating period, the structure design principle of the machine & electric control air dryer is expounded from the aspects of the structure and operating principle, research & development process.

AC Loss Analysis of MgB2-Based Fully Superconducting Machines

NASA Astrophysics Data System (ADS)

Feddersen, M.; Haran, K. S.; Berg, F.

2017-12-01

Superconducting electric machines have shown potential for significant increase in power density, making them attractive for size and weight sensitive applications such as offshore wind generation, marine propulsion, and hybrid-electric aircraft propulsion. Superconductors exhibit no loss under dc conditions, though ac current and field produce considerable losses due to hysteresis, eddy currents, and coupling mechanisms. For this reason, many present machines are designed to be partially superconducting, meaning that the dc field components are superconducting while the ac armature coils are conventional conductors. Fully superconducting designs can provide increases in power density with significantly higher armature current; however, a good estimate of ac losses is required to determine the feasibility under the machines intended operating conditions. This paper aims to characterize the expected losses in a fully superconducting machine targeted towards aircraft, based on an actively-shielded, partially superconducting machine from prior work. Various factors are examined such as magnet strength, operating frequency, and machine load to produce a model for the loss in the superconducting components of the machine. This model is then used to optimize the design of the machine for minimal ac loss while maximizing power density. Important observations from the study are discussed.

Control/structure interaction conceptual design tool

NASA Technical Reports Server (NTRS)

Briggs, Hugh C.

1990-01-01

The JPL Control/Structure Interaction Program is developing new analytical methods for designing micro-precision spacecraft with controlled structures. One of these, the Conceptual Design Tool, will illustrate innovative new approaches to the integration of multi-disciplinary analysis and design methods. The tool will be used to demonstrate homogeneity of presentation, uniform data representation across analytical methods, and integrated systems modeling. The tool differs from current 'integrated systems' that support design teams most notably in its support for the new CSI multi-disciplinary engineer. The design tool will utilize a three dimensional solid model of the spacecraft under design as the central data organization metaphor. Various analytical methods, such as finite element structural analysis, control system analysis, and mechanical configuration layout, will store and retrieve data from a hierarchical, object oriented data structure that supports assemblies of components with associated data and algorithms. In addition to managing numerical model data, the tool will assist the designer in organizing, stating, and tracking system requirements.

29 CFR 1910.212 - General requirements for all machines.

Code of Federal Regulations, 2014 CFR

2014-07-01

..., DEPARTMENT OF LABOR OCCUPATIONAL SAFETY AND HEALTH STANDARDS Machinery and Machine Guarding § 1910.212...) Alligator shears. (d) Power presses. (e) Milling machines. (f) Power saws. (g) Jointers. (h) Portable power...) Anchoring fixed machinery. Machines designed for a fixed location shall be securely anchored to prevent...

29 CFR 1910.212 - General requirements for all machines.

Code of Federal Regulations, 2013 CFR

2013-07-01

..., DEPARTMENT OF LABOR OCCUPATIONAL SAFETY AND HEALTH STANDARDS Machinery and Machine Guarding § 1910.212...) Alligator shears. (d) Power presses. (e) Milling machines. (f) Power saws. (g) Jointers. (h) Portable power...) Anchoring fixed machinery. Machines designed for a fixed location shall be securely anchored to prevent...

29 CFR 1910.212 - General requirements for all machines.

Code of Federal Regulations, 2012 CFR

2012-07-01

..., DEPARTMENT OF LABOR OCCUPATIONAL SAFETY AND HEALTH STANDARDS Machinery and Machine Guarding § 1910.212...) Alligator shears. (d) Power presses. (e) Milling machines. (f) Power saws. (g) Jointers. (h) Portable power...) Anchoring fixed machinery. Machines designed for a fixed location shall be securely anchored to prevent...

Design Optimization of Composite Structures under Uncertainty

NASA Technical Reports Server (NTRS)

Haftka, Raphael T.

2003-01-01

Design optimization under uncertainty is computationally expensive and is also challenging in terms of alternative formulation. The work under the grant focused on developing methods for design against uncertainty that are applicable to composite structural design with emphasis on response surface techniques. Applications included design of stiffened composite plates for improved damage tolerance, the use of response surfaces for fitting weights obtained by structural optimization, and simultaneous design of structure and inspection periods for fail-safe structures.

ASTROS: A multidisciplinary automated structural design tool

NASA Technical Reports Server (NTRS)

Neill, D. J.

1989-01-01

ASTROS (Automated Structural Optimization System) is a finite-element-based multidisciplinary structural optimization procedure developed under Air Force sponsorship to perform automated preliminary structural design. The design task is the determination of the structural sizes that provide an optimal structure while satisfying numerous constraints from many disciplines. In addition to its automated design features, ASTROS provides a general transient and frequency response capability, as well as a special feature to perform a transient analysis of a vehicle subjected to a nuclear blast. The motivation for the development of a single multidisciplinary design tool is that such a tool can provide improved structural designs in less time than is currently needed. The role of such a tool is even more apparent as modern materials come into widespread use. Balancing conflicting requirements for the structure's strength and stiffness while exploiting the benefits of material anisotropy is perhaps an impossible task without assistance from an automated design tool. Finally, the use of a single tool can bring the design task into better focus among design team members, thereby improving their insight into the overall task.

Evolutionary Design of Controlled Structures

NASA Technical Reports Server (NTRS)

Masters, Brett P.; Crawley, Edward F.

1997-01-01

Basic physical concepts of structural delay and transmissibility are provided for simple rod and beam structures. Investigations show the sensitivity of these concepts to differing controlled-structures variables, and to rational system modeling effects. An evolutionary controls/structures design method is developed. The basis of the method is an accurate model formulation for dynamic compensator optimization and Genetic Algorithm based updating of sensor/actuator placement and structural attributes. One and three dimensional examples from the literature are used to validate the method. Frequency domain interpretation of these controlled structure systems provide physical insight as to how the objective is optimized and consequently what is important in the objective. Several disturbance rejection type controls-structures systems are optimized for a stellar interferometer spacecraft application. The interferometric designs include closed loop tracking optics. Designs are generated for differing structural aspect ratios, differing disturbance attributes, and differing sensor selections. Physical limitations in achieving performance are given in terms of average system transfer function gains and system phase loss. A spacecraft-like optical interferometry system is investigated experimentally over several different optimized controlled structures configurations. Configurations represent common and not-so-common approaches to mitigating pathlength errors induced by disturbances of two different spectra. Results show that an optimized controlled structure for low frequency broadband disturbances achieves modest performance gains over a mass equivalent regular structure, while an optimized structure for high frequency narrow band disturbances is four times better in terms of root-mean-square pathlength. These results are predictable given the nature of the physical system and the optimization design variables. Fundamental limits on controlled performance are discussed

Comparisons between designs for single-sided linear electric motors: Homopolar synchronous and induction

NASA Astrophysics Data System (ADS)

Nondahl, T. A.; Richter, E.

1980-09-01

A design study of two types of single sided (with a passive rail) linear electric machine designs, namely homopolar linear synchronous machines (LSM's) and linear induction machines (LIM's), is described. It is assumed the machines provide tractive effort for several types of light rail vehicles and locomotives. These vehicles are wheel supported and require tractive powers ranging from 200 kW to 3735 kW and top speeds ranging from 112 km/hr to 400 km/hr. All designs are made according to specified magnetic and thermal criteria. The LSM advantages are a higher power factor, much greater restoring forces for track misalignments, and less track heating. The LIM advantages are no need to synchronize the excitation frequency precisely to vehicle speed, simpler machine construction, and a more easily anchored track structure. The relative weights of the two machine types vary with excitation frequency and speed; low frequencies and low speeds favor the LSM.

Evaluating the Security of Machine Learning Algorithms

DTIC Science & Technology

2008-05-20

Two far-reaching trends in computing have grown in significance in recent years. First, statistical machine learning has entered the mainstream as a...computing applications. The growing intersection of these trends compels us to investigate how well machine learning performs under adversarial conditions... machine learning has a structure that we can use to build secure learning systems. This thesis makes three high-level contributions. First, we develop a

Program Helps Decompose Complex Design Systems

NASA Technical Reports Server (NTRS)

Rogers, James L., Jr.; Hall, Laura E.

1994-01-01

DeMAID (A Design Manager's Aid for Intelligent Decomposition) computer program is knowledge-based software system for ordering sequence of modules and identifying possible multilevel structure for design problem. Groups modular subsystems on basis of interactions among them. Saves considerable money and time in total design process, particularly in new design problem in which order of modules has not been defined. Available in two machine versions: Macintosh and Sun.

Aircraft empennage structural detail design

NASA Technical Reports Server (NTRS)

Meholic, Greg; Brown, Rhonda; Hall, Melissa; Harvey, Robert; Singer, Michael; Tella, Gustavo

1993-01-01

This project involved the detailed design of the aft fuselage and empennage structure, vertical stabilizer, rudder, horizontal stabilizer, and elevator for the Triton primary flight trainer. The main design goals under consideration were to illustrate the integration of the control systems devices used in the tail surfaces and their necessary structural supports as well as the elevator trim, navigational lighting system, electrical systems, tail-located ground tie, and fuselage/cabin interface structure. Accommodations for maintenance, lubrication, adjustment, and repairability were devised. Weight, fabrication, and (sub)assembly goals were addressed. All designs were in accordance with the FAR Part 23 stipulations for a normal category aircraft.

Applying CBR to machine tool product configuration design oriented to customer requirements

NASA Astrophysics Data System (ADS)

Wang, Pengjia; Gong, Yadong; Xie, Hualong; Liu, Yongxian; Nee, Andrew Yehching

2017-01-01

Product customization is a trend in the current market-oriented manufacturing environment. However, deduction from customer requirements to design results and evaluation of design alternatives are still heavily reliant on the designer's experience and knowledge. To solve the problem of fuzziness and uncertainty of customer requirements in product configuration, an analysis method based on the grey rough model is presented. The customer requirements can be converted into technical characteristics effectively. In addition, an optimization decision model for product planning is established to help the enterprises select the key technical characteristics under the constraints of cost and time to serve the customer to maximal satisfaction. A new case retrieval approach that combines the self-organizing map and fuzzy similarity priority ratio method is proposed in case-based design. The self-organizing map can reduce the retrieval range and increase the retrieval efficiency, and the fuzzy similarity priority ratio method can evaluate the similarity of cases comprehensively. To ensure that the final case has the best overall performance, an evaluation method of similar cases based on grey correlation analysis is proposed to evaluate similar cases to select the most suitable case. Furthermore, a computer-aided system is developed using MATLAB GUI to assist the product configuration design. The actual example and result on an ETC series machine tool product show that the proposed method is effective, rapid and accurate in the process of product configuration. The proposed methodology provides a detailed instruction for the product configuration design oriented to customer requirements.

Integrated design of structures, controls, and materials

NASA Technical Reports Server (NTRS)

Blankenship, G. L.

1994-01-01

In this talk we shall discuss algorithms and CAD tools for the design and analysis of structures for high performance applications using advanced composite materials. An extensive mathematical theory for optimal structural (e.g., shape) design was developed over the past thirty years. Aspects of this theory have been used in the design of components for hypersonic vehicles and thermal diffusion systems based on homogeneous materials. Enhancement of the design methods to include optimization of the microstructure of the component is a significant innovation which can lead to major enhancements in component performance. Our work is focused on the adaptation of existing theories of optimal structural design (e.g., optimal shape design) to treat the design of structures using advanced composite materials (e.g., fiber reinforced, resin matrix materials). In this talk we shall discuss models and algorithms for the design of simple structures from composite materials, focussing on a problem in thermal management. We shall also discuss methods for the integration of active structural controls into the design process.

The Riddle of the Smart Machines

ERIC Educational Resources Information Center

Howell, Dusti D.

2010-01-01

Hundreds of graduate students were introduced to the fields of instructional design and educational technology with the riddle of the smart machines, yet over the years no one has answered it correctly. After revealing the surprising answer to this riddle, both the negative and positive impacts of smart machines are analyzed. An example of this is…

Machine Shop. Instructor Key. Supplementary Units.

ERIC Educational Resources Information Center

Walden, Charles; Cole, Phyllis

These supplementary units are designed to help students with special needs learn and apply machine shop skills. Nine competencies that are difficult for special needs students to grasp or that would help them get a future job in the field were chosen from the regular machine shop curriculum. Specific objectives for these competencies are listed at…

Machine-Learning-Assisted Approach for Discovering Novel Inhibitors Targeting Bromodomain-Containing Protein 4.

PubMed

Xing, Jing; Lu, Wenchao; Liu, Rongfeng; Wang, Yulan; Xie, Yiqian; Zhang, Hao; Shi, Zhe; Jiang, Hao; Liu, Yu-Chih; Chen, Kaixian; Jiang, Hualiang; Luo, Cheng; Zheng, Mingyue

2017-07-24

Bromodomain-containing protein 4 (BRD4) is implicated in the pathogenesis of a number of different cancers, inflammatory diseases and heart failure. Much effort has been dedicated toward discovering novel scaffold BRD4 inhibitors (BRD4is) with different selectivity profiles and potential antiresistance properties. Structure-based drug design (SBDD) and virtual screening (VS) are the most frequently used approaches. Here, we demonstrate a novel, structure-based VS approach that uses machine-learning algorithms trained on the priori structure and activity knowledge to predict the likelihood that a compound is a BRD4i based on its binding pattern with BRD4. In addition to positive experimental data, such as X-ray structures of BRD4-ligand complexes and BRD4 inhibitory potencies, negative data such as false positives (FPs) identified from our earlier ligand screening results were incorporated into our knowledge base. We used the resulting data to train a machine-learning model named BRD4LGR to predict the BRD4i-likeness of a compound. BRD4LGR achieved a 20-30% higher AUC-ROC than that of Glide using the same test set. When conducting in vitro experiments against a library of previously untested, commercially available organic compounds, the second round of VS using BRD4LGR generated 15 new BRD4is. Moreover, inverting the machine-learning model provided easy access to structure-activity relationship (SAR) interpretation for hit-to-lead optimization.

Advances in Machine Technology.

PubMed

Clark, William R; Villa, Gianluca; Neri, Mauro; Ronco, Claudio

2018-01-01

Continuous renal replacement therapy (CRRT) machines have evolved into devices specifically designed for critically ill over the past 40 years. In this chapter, a brief history of this evolution is first provided, with emphasis on the manner in which changes have been made to address the specific needs of the critically ill patient with acute kidney injury. Subsequently, specific examples of technology developments for CRRT machines are discussed, including the user interface, pumps, pressure monitoring, safety features, and anticoagulation capabilities. © 2018 S. Karger AG, Basel.

Precision Robotic Assembly Machine

ScienceCinema

None

2017-12-09

The world's largest laser system is the National Ignition Facility (NIF), located at Lawrence Livermore National Laboratory. NIF's 192 laser beams are amplified to extremely high energy, and then focused onto a tiny target about the size of a BB, containing frozen hydrogen gas. The target must be perfectly machined to incredibly demanding specifications. The Laboratory's scientists and engineers have developed a device called the "Precision Robotic Assembly Machine" for this purpose. Its unique design won a prestigious R&D-100 award from R&D Magazine.

A Comprehensive Review of Permanent Magnet Transverse Flux Machines for Direct Drive Applications

DOE Office of Scientific and Technical Information (OSTI.GOV)

Muljadi, Eduard; Husain, Tausif; Hasan, Iftekhar

The use of direct drive machines in renewable and industrial applications are increasing at a rapid rate. Transverse flux machines (TFM) are ideally suited for direct drive applications due to their high torque density. In this paper, a comprehensive review of the permanent magnet (PM) TFMs for direct drive applications is presented. The paper introduces TFMs and their operating principle and then reviews the different type of TFMs proposed in the literature. The TFMs are categorized according to the number of stator sides, types of stator cores and magnet arrangement in the rotor. The review covers different design topologies, materialsmore » used for manufacturing, structural and thermal analysis, modeling and design optimization and cogging torque minimization in TFMs. The paper also reviews various applications and comparisons for TFMs that have been presented in the literature.« less

Integrated learning in practical machine element design course: a case study of V-pulley design

NASA Astrophysics Data System (ADS)

Tantrabandit, Manop

2014-06-01

To achieve an effective integrated learning in Machine Element Design course, it is of importance to bridge the basic knowledge and skills of element designs. The multiple core learning leads the pathway which consists of two main parts. The first part involves teaching documents of which the contents are number of V-groove formulae, standard of V-grooved pulleys, and parallel key dimension's formulae. The second part relates to the subjects that the students have studied prior to participating in this integrated learning course, namely Material Selection, Manufacturing Process, Applied Engineering Drawing, CAD (Computer Aided Design) animation software. Moreover, an intensive cooperation between a lecturer and students is another key factor to fulfill the success of integrated learning. Last but not least, the students need to share their knowledge within the group and among the other groups aiming to gain knowledge of and skills in 1) the application of CAD-software to build up manufacture part drawings, 2) assembly drawing, 3) simulation to verify the strength of loaded pulley by method of Finite Element Analysis (FEA), 4) the software to create animation of mounting and dismounting of a pulley to a shaft, and 5) an instruction manual. The end product of this integrated learning, as a result of the above 1 to 5 knowledge and skills obtained, the participating students can create an assembly derived from manufacture part drawings and a video presentation with bilingual (English-Thai) audio description of Vpulley with datum diameter of 250 mm, 4 grooves, and type of groove: SPA.

A hybrid approach for nondestructive assessment and design optimisation and testing of in-service machinery

NASA Astrophysics Data System (ADS)

Rahman, Abdul Ghaffar Abdul; Noroozi, Siamak; Dupac, Mihai; Mahathir Syed Mohd Al-Attas, Syed; Vinney, John E.

2013-03-01

Complex rotating machinery requires regular condition monitoring inspections to assess their running conditions and their structural integrity to prevent catastrophic failures. Machine failures can be divided into two categories. First is the wear and tear during operation, they range from bearing defects, gear damage, misalignment, imbalance or mechanical looseness, for which simple condition-based maintenance techniques can easily detect the root cause and trigger remedial action process. The second factor in machine failure is caused by the inherent design faults that usually happened due to many reasons such as improper installation, poor servicing, bad workmanship and structural dynamics design deficiency. In fact, individual machines components are generally dynamically well designed and rigorously tested. However, when these machines are assembled on sight and linked together, their dynamic characteristics will change causing unexpected behaviour of the system. Since nondestructive evaluation provides an excellent alternative to the classical monitoring and proved attractive due to the possibility of performing reliable assessments of all types of machinery, the novel dynamic design verification procedure - based on the combination of in-service operation deflection shape measurement, experimental modal analysis and iterative inverse finite element analysis - proposed here allows quick identification of structural weakness, and helps to provide and verify the solutions.

Risk estimation using probability machines

PubMed Central

2014-01-01

Background Logistic regression has been the de facto, and often the only, model used in the description and analysis of relationships between a binary outcome and observed features. It is widely used to obtain the conditional probabilities of the outcome given predictors, as well as predictor effect size estimates using conditional odds ratios. Results We show how statistical learning machines for binary outcomes, provably consistent for the nonparametric regression problem, can be used to provide both consistent conditional probability estimation and conditional effect size estimates. Effect size estimates from learning machines leverage our understanding of counterfactual arguments central to the interpretation of such estimates. We show that, if the data generating model is logistic, we can recover accurate probability predictions and effect size estimates with nearly the same efficiency as a correct logistic model, both for main effects and interactions. We also propose a method using learning machines to scan for possible interaction effects quickly and efficiently. Simulations using random forest probability machines are presented. Conclusions The models we propose make no assumptions about the data structure, and capture the patterns in the data by just specifying the predictors involved and not any particular model structure. So they do not run the same risks of model mis-specification and the resultant estimation biases as a logistic model. This methodology, which we call a “risk machine”, will share properties from the statistical machine that it is derived from. PMID:24581306

Effects of cutting parameters and machining environments on surface roughness in hard turning using design of experiment

NASA Astrophysics Data System (ADS)

Mia, Mozammel; Bashir, Mahmood Al; Dhar, Nikhil Ranjan

2016-07-01

Hard turning is gradually replacing the time consuming conventional turning process, which is typically followed by grinding, by producing surface quality compatible to grinding. The hard turned surface roughness depends on the cutting parameters, machining environments and tool insert configurations. In this article the variation of the surface roughness of the produced surfaces with the changes in tool insert configuration, use of coolant and different cutting parameters (cutting speed, feed rate) has been investigated. This investigation was performed in machining AISI 1060 steel, hardened to 56 HRC by heat treatment, using coated carbide inserts under two different machining environments. The depth of cut, fluid pressure and material hardness were kept constant. The Design of Experiment (DOE) was performed to determine the number and combination sets of different cutting parameters. A full factorial analysis has been performed to examine the effect of main factors as well as interaction effect of factors on surface roughness. A statistical analysis of variance (ANOVA) was employed to determine the combined effect of cutting parameters, environment and tool configuration. The result of this analysis reveals that environment has the most significant impact on surface roughness followed by feed rate and tool configuration respectively.

An Introduction to Database Structure and Database Machines.

ERIC Educational Resources Information Center

Detweiler, Karen

1984-01-01

Enumerates principal management objectives of database management systems (data independence, quality, security, multiuser access, central control) and criteria for comparison (response time, size, flexibility, other features). Conventional database management systems, relational databases, and database machines used for backend processing are…

Network Modeling and Energy-Efficiency Optimization for Advanced Machine-to-Machine Sensor Networks

PubMed Central

Jung, Sungmo; Kim, Jong Hyun; Kim, Seoksoo

2012-01-01

Wireless machine-to-machine sensor networks with multiple radio interfaces are expected to have several advantages, including high spatial scalability, low event detection latency, and low energy consumption. Here, we propose a network model design method involving network approximation and an optimized multi-tiered clustering algorithm that maximizes node lifespan by minimizing energy consumption in a non-uniformly distributed network. Simulation results show that the cluster scales and network parameters determined with the proposed method facilitate a more efficient performance compared to existing methods. PMID:23202190

Toward best practice in Human Machine Interface design for older drivers: A review of current design guidelines.

PubMed

Young, K L; Koppel, S; Charlton, J L

2017-09-01

Older adults are the fastest growing segment of the driving population. While there is a strong emphasis for older people to maintain their mobility, the safety of older drivers is a serious community concern. Frailty and declines in a range of age-related sensory, cognitive, and physical impairments can place older drivers at an increased risk of crash-related injuries and death. A number of studies have indicated that in-vehicle technologies such as Advanced Driver Assistance Systems (ADAS) and In-Vehicle Information Systems (IVIS) may provide assistance to older drivers. However, these technologies will only benefit older drivers if their design is congruent with the complex needs and diverse abilities of this driving cohort. The design of ADAS and IVIS is largely informed by automotive Human Machine Interface (HMI) guidelines. However, it is unclear to what extent the declining sensory, cognitive and physical capabilities of older drivers are addressed in the current guidelines. This paper provides a review of key current design guidelines for IVIS and ADAS with respect to the extent they address age-related changes in functional capacities. The review revealed that most of the HMI guidelines do not address design issues related to older driver impairments. In fact, in many guidelines driver age and sensory cognitive and physical impairments are not mentioned at all and where reference is made, it is typically very broad. Prescriptive advice on how to actually design a system so that it addresses the needs and limitations of older drivers is not provided. In order for older drivers to reap the full benefits that in-vehicle technology can afford, it is critical that further work establish how older driver limitations and capabilities can be supported by the system design process, including their inclusion into HMI design guidelines. Copyright © 2016 Elsevier Ltd. All rights reserved.

Machine learning for medical images analysis.

PubMed

Criminisi, A

2016-10-01

This article discusses the application of machine learning for the analysis of medical images. Specifically: (i) We show how a special type of learning models can be thought of as automatically optimized, hierarchically-structured, rule-based algorithms, and (ii) We discuss how the issue of collecting large labelled datasets applies to both conventional algorithms as well as machine learning techniques. The size of the training database is a function of model complexity rather than a characteristic of machine learning methods. Crown Copyright © 2016. Published by Elsevier B.V. All rights reserved.

A modular and cost-effective superconducting generator design for offshore wind turbines

NASA Astrophysics Data System (ADS)

Keysan, Ozan; Mueller, Markus

2015-03-01

Superconducting generators have the potential to reduce the tower head mass for large (∼10 MW) offshore wind turbines. However, a high temperature superconductor generator should be as reliable as conventional generators for successful entry into the market. Most of the proposed designs use the superconducting synchronous generator concept, which has a higher cost than conventional generators and suffers from reliability issues. In this paper, a novel claw pole type of superconducting machine is presented. The design has a stationary superconducting field winding, which simplifies the design and increases the reliability. The machine can be operated in independent modules; thus even if one of the sections fails, the rest can operate until the next planned maintenance. Another advantage of the design is the very low superconducting wire requirement; a 10 MW, 10 rpm design is presented which uses 13 km of MgB2 wire at 30 K. The outer diameter of the machine is 6.63 m and it weighs 184 tonnes including the structural mass. The design is thought to be a good candidate for entering the renewable energy market, with its low cost and robust structure.

SAINT: A combined simulation language for modeling man-machine systems

NASA Technical Reports Server (NTRS)

Seifert, D. J.

1979-01-01

SAINT (Systems Analysis of Integrated Networks of Tasks) is a network modeling and simulation technique for design and analysis of complex man machine systems. SAINT provides the conceptual framework for representing systems that consist of discrete task elements, continuous state variables, and interactions between them. It also provides a mechanism for combining human performance models and dynamic system behaviors in a single modeling structure. The SAINT technique is described and applications of the SAINT are discussed.

Machine Learning and Experimental Design for Hydrogen Cosmology

NASA Astrophysics Data System (ADS)

Rapetti, David; Tauscher, Keith A.; Burns, Jack O.; Mirocha, Jordan; Switzer, Eric; Monsalve, Raul A.; Furlanetto, Steven R.; Bowman, Judd D.

2018-06-01

Based on two powerful innovations, we present a new pipeline to analyze the redshifted sky-averaged 21-cm spectrum (~10-200 MHz) of neutral hydrogen from the first stars, galaxies and black holes. First, we combine machine learning and model selection techniques to extract the global 21-cm signal from foreground and instrumental systematics. Second, we employ experimental designs to increase our ability to separate these two components in data sets. For measurements with foreground polarization induced by rotation about the anisotropic low-frequency radio sky on a large beam, we incorporate this information into the likelihood to distinguish the unpolarized 21-cm signal from the rest of the data. For experiments with a drift scan strategy, we take advantage of the varying foreground in time to identify the constant 21-cm signal. This pipeline can be applied to either lunar orbit/surface instruments shielded from terrestrial and solar radio contamination, or existing ground-based observations, such as those from the EDGES collaboration that recently observed an absorption trough potentially consistent with the global 21-cm signal of Cosmic Dawn. Finally, this pipeline allows us to constrain physical parameters for a given model of the first luminous objects plus exotic physics in the early universe, from e.g. dark matter, through an MCMC analysis that uses the extracted signal as a starting point, providing key efficiency for unexplored cosmologies.

Laser Machining of Melt Infiltrated Ceramic Matrix Composite

NASA Technical Reports Server (NTRS)

Jarmon, D. C.; Ojard, G.; Brewer, D.

2012-01-01

As interest grows in considering the use of ceramic matrix composites for critical components, the effects of different machining techniques, and the resulting machined surfaces, on strength need to be understood. This work presents the characterization of a Melt Infiltrated SiC/SiC composite material system machined by different methods. While a range of machining approaches were initially considered, only diamond grinding and laser machining were investigated on a series of tensile coupons. The coupons were tested for residual tensile strength, after a stressed steam exposure cycle. The data clearly differentiated the laser machined coupons as having better capability for the samples tested. These results, along with micro-structural characterization, will be presented.

Automated fiber pigtailing machine

DOEpatents

Strand, Oliver T.; Lowry, Mark E.

1999-01-01

The Automated Fiber Pigtailing Machine (AFPM) aligns and attaches optical fibers to optoelectonic (OE) devices such as laser diodes, photodiodes, and waveguide devices without operator intervention. The so-called pigtailing process is completed with sub-micron accuracies in less than 3 minutes. The AFPM operates unattended for one hour, is modular in design and is compatible with a mass production manufacturing environment. This machine can be used to build components which are used in military aircraft navigation systems, computer systems, communications systems and in the construction of diagnostics and experimental systems.

Automated fiber pigtailing machine

DOEpatents

Strand, O.T.; Lowry, M.E.

1999-01-05

The Automated Fiber Pigtailing Machine (AFPM) aligns and attaches optical fibers to optoelectronic (OE) devices such as laser diodes, photodiodes, and waveguide devices without operator intervention. The so-called pigtailing process is completed with sub-micron accuracies in less than 3 minutes. The AFPM operates unattended for one hour, is modular in design and is compatible with a mass production manufacturing environment. This machine can be used to build components which are used in military aircraft navigation systems, computer systems, communications systems and in the construction of diagnostics and experimental systems. 26 figs.

A Teaching Model for Truss Structures

ERIC Educational Resources Information Center

Bigoni, Davide; Dal Corso, Francesco; Misseroni, Diego; Tommasini, Mirko

2012-01-01

A classroom demonstration model has been designed, machined and successfully tested in different learning environments to facilitate understanding of the mechanics of truss structures, in which struts are subject to purely axial load and deformation. Gaining confidence with these structures is crucial for the development of lattice models, which…

Development of machine learning models to predict inhibition of 3-dehydroquinate dehydratase.

PubMed

de Ávila, Maurício Boff; de Azevedo, Walter Filgueira

2018-04-20

In this study, we describe the development of new machine learning models to predict inhibition of the enzyme 3-dehydroquinate dehydratase (DHQD). This enzyme is the third step of the shikimate pathway and is responsible for the synthesis of chorismate, which is a natural precursor of aromatic amino acids. The enzymes of shikimate pathway are absent in humans, which make them protein targets for the design of antimicrobial drugs. We focus our study on the crystallographic structures of DHQD in complex with competitive inhibitors, for which experimental inhibition constant data is available. Application of supervised machine learning techniques was able to elaborate a robust DHQD-targeted model to predict binding affinity. Combination of high-resolution crystallographic structures and binding information indicates that the prevalence of intermolecular electrostatic interactions between DHQD and competitive inhibitors is of pivotal importance for the binding affinity against this enzyme. The present findings can be used to speed up virtual screening studies focused on the DHQD structure. © 2018 John Wiley & Sons A/S.

LDRD Report: Topological Design Optimization of Convolutes in Next Generation Pulsed Power Devices.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cyr, Eric C.; von Winckel, Gregory John; Kouri, Drew Philip

This LDRD project was developed around the ambitious goal of applying PDE-constrained opti- mization approaches to design Z-machine components whose performance is governed by elec- tromagnetic and plasma models. This report documents the results of this LDRD project. Our differentiating approach was to use topology optimization methods developed for structural design and extend them for application to electromagnetic systems pertinent to the Z-machine. To achieve this objective a suite of optimization algorithms were implemented in the ROL library part of the Trilinos framework. These methods were applied to standalone demonstration problems and the Drekar multi-physics research application. Out of thismore » exploration a new augmented Lagrangian approach to structural design problems was developed. We demonstrate that this approach has favorable mesh-independent performance. Both the final design and the algorithmic performance were independent of the size of the mesh. In addition, topology optimization formulations for the design of conducting networks were developed and demonstrated. Of note, this formulation was used to develop a design for the inner magnetically insulated transmission line on the Z-machine. The resulting electromagnetic device is compared with theoretically postulated designs.« less