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

Science.gov (United States)

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.

Design and Assessment of a Machine Vision System for Automatic Vehicle Wheel Alignment

Directory of Open Access Journals (Sweden)

Rocco Furferi

2013-05-01

Full Text Available Abstract Wheel alignment, consisting of properly checking the wheel characteristic angles against vehicle manufacturers' specifications, is a crucial task in the automotive field since it prevents irregular tyre wear and affects vehicle handling and safety. In recent years, systems based on Machine Vision have been widely studied in order to automatically detect wheels' characteristic angles. In order to overcome the limitations of existing methodologies, due to measurement equipment being mounted onto the wheels, the present work deals with design and assessment of a 3D machine vision-based system for the contactless reconstruction of vehicle wheel geometry, with particular reference to characteristic planes. Such planes, properly referred to as a global coordinate system, are used for determining wheel angles. The effectiveness of the proposed method was tested against a set of measurements carried out using a commercial 3D scanner; the absolute average error in measuring toe and camber angles with the machine vision system resulted in full compatibility with the expected accuracy of wheel alignment systems.

Electromagnetic Analysis and Design of Switched Reluctance Double-Rotor Machine for Hybrid Electric Vehicles

Directory of Open Access Journals (Sweden)

Shouliang Han

2014-10-01

Full Text Available The double-rotor machine is a kind of multiple input and output electromechanical energy transducer with two electrical ports and two mechanical ports, which is an ideal transmission system for hybrid electric vehicles and has a series of advantages such as integration of power and energy, high efficiency and compaction. In this paper, a switched reluctance double-rotor machine (SRDRM is proposed for hybrid electric vehicles, while no conductor or PM in the middle rotor. This machine not only inherits the merits of switched reluctance machine, such as simple salient rotor structure, high reliability and wide speed range, but also can avoid the outer rotor’s cooling problem effectively. By using an equivalent magnetic circuit model, the function of middle rotor yoke is analyzed. Electromagnetic analyses of the SRDRM are performed with analytical calculations and 2-D finite element methods, including the effects of main parameters on performance. Finally, a 4.4 kW prototype machine is designed and manufactured, and the tests are performed, which validate the proposed design method.

Field weakening performance of flux-switching machines for hybrid/electric vehicles

NARCIS (Netherlands)

Tang, Y.; Paulides, J.J.H.; Lomonova, E.A.

2015-01-01

Flux-switching machines (FSMs) are a viable candidate for electric propulsion of hybrid/electric vehicles. This paper investigates the field weakening performance of FSMs. The investigation starts with general torque and voltage expressions, which reveal the relationships between certain parameters

Design of an axial-flux permanent magnet machine for a solar-powered electric vehicle

NARCIS (Netherlands)

Friedrich, L.A.J.; Bastiaens, K.; Gysen, B.L.J.; Krop, D.C.J.; Lomonova, E.A.

2018-01-01

This paper concerns the design optimization of two axial-flux permanent magnet (AFPM) machines, aimed to be used as a direct drive in-wheel motor for the propulsion of a solar-powered electric vehicle. The internal stator twin external rotor AFPM machine topology having either a distributed or

Automated vehicle counting using image processing and machine learning

Science.gov (United States)

Meany, Sean; Eskew, Edward; Martinez-Castro, Rosana; Jang, Shinae

2017-04-01

Vehicle counting is used by the government to improve roadways and the flow of traffic, and by private businesses for purposes such as determining the value of locating a new store in an area. A vehicle count can be performed manually or automatically. Manual counting requires an individual to be on-site and tally the traffic electronically or by hand. However, this can lead to miscounts due to factors such as human error A common form of automatic counting involves pneumatic tubes, but pneumatic tubes disrupt traffic during installation and removal, and can be damaged by passing vehicles. Vehicle counting can also be performed via the use of a camera at the count site recording video of the traffic, with counting being performed manually post-recording or using automatic algorithms. This paper presents a low-cost procedure to perform automatic vehicle counting using remote video cameras with an automatic counting algorithm. The procedure would utilize a Raspberry Pi micro-computer to detect when a car is in a lane, and generate an accurate count of vehicle movements. The method utilized in this paper would use background subtraction to process the images and a machine learning algorithm to provide the count. This method avoids fatigue issues that are encountered in manual video counting and prevents the disruption of roadways that occurs when installing pneumatic tubes

Towards comfortable and efficient man-machine interaction in the cabins of vehicles

NARCIS (Netherlands)

Looze, M.P. de; Roetting, M.; Vink, P.; Luczak, H.

2000-01-01

The comfort of the operators in the cabins of vehicles is getting an increasingly important issue. At first glance, the cabins of professional machines (earth-moving equipment, busses, harvesting equipment) might look modern and highly comfortable. However, this does not imply that the cabins

Integrated assignment and path planning

Science.gov (United States)

Murphey, Robert A.

2005-11-01

A surge of interest in unmanned systems has exposed many new and challenging research problems across many fields of engineering and mathematics. These systems have the potential of transforming our society by replacing dangerous and dirty jobs with networks of moving machines. This vision is fundamentally separate from the modern view of robotics in that sophisticated behavior is realizable not by increasing individual vehicle complexity, but instead through collaborative teaming that relies on collective perception, abstraction, decision making, and manipulation. Obvious examples where collective robotics will make an impact include planetary exploration, space structure assembly, remote and undersea mining, hazardous material handling and clean-up, and search and rescue. Nonetheless, the phenomenon driving this technology trend is the increasing reliance of the US military on unmanned vehicles, specifically, aircraft. Only a few years ago, following years of resistance to the use of unmanned systems, the military and civilian leadership in the United States reversed itself and have recently demonstrated surprisingly broad acceptance of increasingly pervasive use of unmanned platforms in defense surveillance, and even attack. However, as rapidly as unmanned systems have gained acceptance, the defense research community has discovered the technical pitfalls that lie ahead, especially for operating collective groups of unmanned platforms. A great deal of talent and energy has been devoted to solving these technical problems, which tend to fall into two categories: resource allocation of vehicles to objectives, and path planning of vehicle trajectories. An extensive amount of research has been conducted in each direction, yet, surprisingly, very little work has considered the integrated problem of assignment and path planning. This dissertation presents a framework for studying integrated assignment and path planning and then moves on to suggest an exact

Position error compensation via a variable reluctance sensor applied to a Hybrid Vehicle Electric machine.

Science.gov (United States)

Bucak, Ihsan Ömür

2010-01-01

In the automotive industry, electromagnetic variable reluctance (VR) sensors have been extensively used to measure engine position and speed through a toothed wheel mounted on the crankshaft. In this work, an application that already uses the VR sensing unit for engine and/or transmission has been chosen to infer, this time, the indirect position of the electric machine in a parallel Hybrid Electric Vehicle (HEV) system. A VR sensor has been chosen to correct the position of the electric machine, mainly because it may still become critical in the operation of HEVs to avoid possible vehicle failures during the start-up and on-the-road, especially when the machine is used with an internal combustion engine. The proposed method uses Chi-square test and is adaptive in a sense that it derives the compensation factors during the shaft operation and updates them in a timely fashion.

Position Error Compensation via a Variable Reluctance Sensor Applied to a Hybrid Vehicle Electric Machine

Directory of Open Access Journals (Sweden)

İhsan Ömür Bucak

2010-03-01

Full Text Available In the automotive industry, electromagnetic variable reluctance (VR sensors have been extensively used to measure engine position and speed through a toothed wheel mounted on the crankshaft. In this work, an application that already uses the VR sensing unit for engine and/or transmission has been chosen to infer, this time, the indirect position of the electric machine in a parallel Hybrid Electric Vehicle (HEV system. A VR sensor has been chosen to correct the position of the electric machine, mainly because it may still become critical in the operation of HEVs to avoid possible vehicle failures during the start-up and on-the-road, especially when the machine is used with an internal combustion engine. The proposed method uses Chi-square test and is adaptive in a sense that it derives the compensation factors during the shaft operation and updates them in a timely fashion.

A Machine Learning Approach to Pedestrian Detection for Autonomous Vehicles Using High-Definition 3D Range Data

Directory of Open Access Journals (Sweden)

Pedro J. Navarro

2016-12-01

Full Text Available This article describes an automated sensor-based system to detect pedestrians in an autonomous vehicle application. Although the vehicle is equipped with a broad set of sensors, the article focuses on the processing of the information generated by a Velodyne HDL-64E LIDAR sensor. The cloud of points generated by the sensor (more than 1 million points per revolution is processed to detect pedestrians, by selecting cubic shapes and applying machine vision and machine learning algorithms to the XY, XZ, and YZ projections of the points contained in the cube. The work relates an exhaustive analysis of the performance of three different machine learning algorithms: k-Nearest Neighbours (kNN, Naïve Bayes classifier (NBC, and Support Vector Machine (SVM. These algorithms have been trained with 1931 samples. The final performance of the method, measured a real traffic scenery, which contained 16 pedestrians and 469 samples of non-pedestrians, shows sensitivity (81.2%, accuracy (96.2% and specificity (96.8%.

A Machine Learning Approach to Pedestrian Detection for Autonomous Vehicles Using High-Definition 3D Range Data.

Science.gov (United States)

Navarro, Pedro J; Fernández, Carlos; Borraz, Raúl; Alonso, Diego

2016-12-23

This article describes an automated sensor-based system to detect pedestrians in an autonomous vehicle application. Although the vehicle is equipped with a broad set of sensors, the article focuses on the processing of the information generated by a Velodyne HDL-64E LIDAR sensor. The cloud of points generated by the sensor (more than 1 million points per revolution) is processed to detect pedestrians, by selecting cubic shapes and applying machine vision and machine learning algorithms to the XY, XZ, and YZ projections of the points contained in the cube. The work relates an exhaustive analysis of the performance of three different machine learning algorithms: k-Nearest Neighbours (kNN), Naïve Bayes classifier (NBC), and Support Vector Machine (SVM). These algorithms have been trained with 1931 samples. The final performance of the method, measured a real traffic scenery, which contained 16 pedestrians and 469 samples of non-pedestrians, shows sensitivity (81.2%), accuracy (96.2%) and specificity (96.8%).

Single Machine Scheduling and Due Date Assignment with Past-Sequence-Dependent Setup Time and Position-Dependent Processing Time

Directory of Open Access Journals (Sweden)

Chuan-Li Zhao

2014-01-01

Full Text Available This paper considers single machine scheduling and due date assignment with setup time. The setup time is proportional to the length of the already processed jobs; that is, the setup time is past-sequence-dependent (p-s-d. It is assumed that a job's processing time depends on its position in a sequence. The objective functions include total earliness, the weighted number of tardy jobs, and the cost of due date assignment. We analyze these problems with two different due date assignment methods. We first consider the model with job-dependent position effects. For each case, by converting the problem to a series of assignment problems, we proved that the problems can be solved in On4 time. For the model with job-independent position effects, we proved that the problems can be solved in On3 time by providing a dynamic programming algorithm.

Poster abstract: A machine learning approach for vehicle classification using passive infrared and ultrasonic sensors

KAUST Repository

Warriach, Ehsan Ullah; Claudel, Christian G.

2013-01-01

This article describes the implementation of four different machine learning techniques for vehicle classification in a dual ultrasonic/passive infrared traffic flow sensors. Using k-NN, Naive Bayes, SVM and KNN-SVM algorithms, we show that KNN

Human machine interface to manually drive rhombic like vehicles in remote handling operations

International Nuclear Information System (INIS)

Lopes, Pedro; Vale, Alberto; Ventura, Rodrigo

2015-01-01

In the thermonuclear experimental reactor ITER, a vehicle named CTS is designed to transport a container with activated components inside the buildings. In nominal operations, the CTS is autonomously guided under supervision. However, in some unexpected situations, such as in rescue and recovery operations, the autonomous mode must be overridden and the CTS must be remotely guided by an operator. The CTS is a rhombic-like vehicle, with two drivable and steerable wheels along its longitudinal axis, providing omni-directional capabilities. The rhombic kinematics correspond to four control variables, which are difficult to manage in manual mode operation. This paper proposes a Human Machine Interface (HMI) to remotely guide the vehicle in manual mode. The proposed solution is implemented using a HMI with an encoder connected to a micro-controller and an analog 2-axis joystick. Experimental results were obtained comparing the proposed solution with other controller devices in different scenarios and using a software platform that simulates the kinematics and dynamics of the vehicle. (authors)

Human machine interface to manually drive rhombic like vehicles in remote handling operations

Energy Technology Data Exchange (ETDEWEB)

Lopes, Pedro; Vale, Alberto [Instituto de Plasmas e Fusao Nuclear, Instituto Superior Tecnico, Universidade de Lisboa, Av. Rovisco Pais 1, 1049-001 Lisboa (Portugal); Ventura, Rodrigo [Institute for Systems and Robotics, Instituto Superior Tecnico, Universidade de Lisboa, Av. Rovisco Pais 1, 1049-001 Lisboa (Portugal)

2015-07-01

In the thermonuclear experimental reactor ITER, a vehicle named CTS is designed to transport a container with activated components inside the buildings. In nominal operations, the CTS is autonomously guided under supervision. However, in some unexpected situations, such as in rescue and recovery operations, the autonomous mode must be overridden and the CTS must be remotely guided by an operator. The CTS is a rhombic-like vehicle, with two drivable and steerable wheels along its longitudinal axis, providing omni-directional capabilities. The rhombic kinematics correspond to four control variables, which are difficult to manage in manual mode operation. This paper proposes a Human Machine Interface (HMI) to remotely guide the vehicle in manual mode. The proposed solution is implemented using a HMI with an encoder connected to a micro-controller and an analog 2-axis joystick. Experimental results were obtained comparing the proposed solution with other controller devices in different scenarios and using a software platform that simulates the kinematics and dynamics of the vehicle. (authors)

On some special cases of the restricted assignment problem

NARCIS (Netherlands)

Wang, C. (Chao); R.A. Sitters (René)

2016-01-01

textabstractWe consider some special cases of the restricted assignment problem. In this scheduling problem on parallel machines, any job j can only be assigned to one of the machines in its given subset Mj of machines. We give an LP-formulation for the problem with two job sizes and show that it

A Practical Torque Estimation Method for Interior Permanent Magnet Synchronous Machine in Electric Vehicles.

Science.gov (United States)

Wu, Zhihong; Lu, Ke; Zhu, Yuan

2015-01-01

The torque output accuracy of the IPMSM in electric vehicles using a state of the art MTPA strategy highly depends on the accuracy of machine parameters, thus, a torque estimation method is necessary for the safety of the vehicle. In this paper, a torque estimation method based on flux estimator with a modified low pass filter is presented. Moreover, by taking into account the non-ideal characteristic of the inverter, the torque estimation accuracy is improved significantly. The effectiveness of the proposed method is demonstrated through MATLAB/Simulink simulation and experiment.

DOE FreedomCAR and vehicle technologies program advanced power electronic and electrical machines annual review report

Energy Technology Data Exchange (ETDEWEB)

Olszewski, Mitch [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

2006-10-11

This report is a summary of the Review Panel at the FY06 DOE FreedomCAR and Vehicle Technologies (FCVT) Annual Review of Advanced Power Electronics and Electric Machine (APEEM) research activities held on August 15-17, 2006.

Design and Optimization of Permanent Magnet Brushless Machines for Electric Vehicle Applications

Directory of Open Access Journals (Sweden)

Weiwei Gu

2015-12-01

Full Text Available In this paper, by considering and establishing the relationship between the maximum operating speed and d-axis inductance, a new design and optimization method is proposed. Thus, a more extended constant power speed range, as well as reduced losses and increased efficiency, especially in the high-speed region, can be obtained, which is essential for electric vehicles (EVs. In the first step, the initial permanent magnet (PM brushless machine is designed based on the consideration of the maximum speed and performance specifications in the entire operation region. Then, on the basis of increasing d-axis inductance, and meanwhile maintaining constant permanent magnet flux linkage, the PM brushless machine is optimized. The corresponding performance of the initial and optimal PM brushless machines are analyzed and compared by the finite-element method (FEM. Several tests are carried out in an EV simulation model based on the urban dynamometer driving schedule (UDDS for evaluation. Both theoretical analysis and simulation results verify the validity of the proposed design and optimization method.

Electric vehicle charging infrastructure assignment and power grid impacts assessment in Beijing

International Nuclear Information System (INIS)

Liu, Jian

2012-01-01

This paper estimates the charging demand of an early electric vehicle (EV) market in Beijing and proposes an assignment model to distribute charging infrastructure. It finds that each type of charging infrastructure has its limitation, and integration is needed to offer a reliable charging service. It also reveals that the service radius of fast charging stations directly influences the final distribution pattern and an infrastructure deployment strategy with short service radius for fast charging stations has relatively fewer disturbances on the power grid. Additionally, although the adoption of electric vehicles will cause an additional electrical load on the Beijing's power grid, this additional load can be accommodated by the current grid's capacity via the charging time management and the battery swap strategy. - Highlight: ► Charging posts, fast charging stations, and battery swap stations should be integrated. ► Charging posts at home parking places will take a major role in a charging network. ► A service radius of 2 km is proposed for fast charging stations deployment. ► The additional charging load from EVs can be accommodated by charging time management.

Supervised machine learning algorithms to diagnose stress for vehicle drivers based on physiological sensor signals.

Science.gov (United States)

Barua, Shaibal; Begum, Shahina; Ahmed, Mobyen Uddin

2015-01-01

Machine learning algorithms play an important role in computer science research. Recent advancement in sensor data collection in clinical sciences lead to a complex, heterogeneous data processing, and analysis for patient diagnosis and prognosis. Diagnosis and treatment of patients based on manual analysis of these sensor data are difficult and time consuming. Therefore, development of Knowledge-based systems to support clinicians in decision-making is important. However, it is necessary to perform experimental work to compare performances of different machine learning methods to help to select appropriate method for a specific characteristic of data sets. This paper compares classification performance of three popular machine learning methods i.e., case-based reasoning, neutral networks and support vector machine to diagnose stress of vehicle drivers using finger temperature and heart rate variability. The experimental results show that case-based reasoning outperforms other two methods in terms of classification accuracy. Case-based reasoning has achieved 80% and 86% accuracy to classify stress using finger temperature and heart rate variability. On contrary, both neural network and support vector machine have achieved less than 80% accuracy by using both physiological signals.

Investigation of a Co-Axial Dual-Mechanical Ports Flux-Switching Permanent Magnet Machine for Hybrid Electric Vehicles

Directory of Open Access Journals (Sweden)

Wei Hua

2015-12-01

Full Text Available In this paper, a co-axial dual-mechanical ports flux-switching permanent magnet (CADMP-FSPM machine for hybrid electric vehicles (HEVs is proposed and investigated, which is comprised of two conventional co-axial FSPM machines, namely one high-speed inner rotor machine and one low-speed outer rotor machine and a non-magnetic ring sandwiched in between. Firstly, the topology and operation principle of the CADMP-FSPM machine are introduced; secondly, the control system of the proposed electronically-controlled continuously-variable transmission (E-CVT system is given; thirdly, the key design specifications of the CADMP-FSPM machine are determined based on a conventional dual-mechanical ports (DMP machine with a wound inner rotor. Fourthly, the performances of the CADMP-FSPM machine and the normal DMP machine under the same overall volume are compared, and the results indicate that the CADMP-FSPM machine has advantages over the conventional DMP machine in the elimination of brushes and slip rings, improved thermal dissipation conditions for the inner rotor, direct-driven operation, more flexible modes, lower cogging torque and torque ripple, lower total harmonic distortion (THD values of phase PM flux linkage and phase electro-motive force (EMF, higher torque output capability and is suitable for the E-CVT systems. Finally, the pros and cons of the CADMP-FSPM machine are highlighted. This paper lays a theoretical foundation for further research on CADMP-FSPM machines used for HEVs.

Lot-Order Assignment Applying Priority Rules for the Single-Machine Total Tardiness Scheduling with Nonnegative Time-Dependent Processing Times

Directory of Open Access Journals (Sweden)

Jae-Gon Kim

2015-01-01

Full Text Available Lot-order assignment is to assign items in lots being processed to orders to fulfill the orders. It is usually performed periodically for meeting the due dates of orders especially in a manufacturing industry with a long production cycle time such as the semiconductor manufacturing industry. In this paper, we consider the lot-order assignment problem (LOAP with the objective of minimizing the total tardiness of the orders with distinct due dates. We show that we can solve the LOAP optimally by finding an optimal sequence for the single-machine total tardiness scheduling problem with nonnegative time-dependent processing times (SMTTSP-NNTDPT. Also, we address how the priority rules for the SMTTSP can be modified to those for the SMTTSP-NNTDPT to solve the LOAP. In computational experiments, we discuss the performances of the suggested priority rules and show the result of the proposed approach outperforms that of the commercial optimization software package.

Improving machine operation management efficiency via improving the vehicle park structure and using the production operation information database

Science.gov (United States)

Koptev, V. Yu

2017-02-01

The work represents the results of studying basic interconnected criteria of separate equipment units of the transport network machines fleet, depending on production and mining factors to improve the transport systems management. Justifying the selection of a control system necessitates employing new methodologies and models, augmented with stability and transport flow criteria, accounting for mining work development dynamics on mining sites. A necessary condition is the accounting of technical and operating parameters related to vehicle operation. Modern open pit mining dispatching systems must include such kinds of the information database. An algorithm forming a machine fleet is presented based on multi-variation task solution in connection with defining reasonable operating features of a machine working as a part of a complex. Proposals cited in the work may apply to mining machines (drilling equipment, excavators) and construction equipment (bulldozers, cranes, pile-drivers), city transport and other types of production activities using machine fleet.

Optimal Due Date Assignment and Resource Allocation to Minimize the Weighted Number of Tardy Jobs on a Single Machine

OpenAIRE

Dvir Shabtay; George Steiner

2007-01-01

With the increased emphasis on the effective management of operational issues in supply chains, the timely delivery of products has become even more important. Companies have to quote attainable delivery dates and then meet these, or face large tardiness penalties. We study systems that can be modeled by single-machine scheduling problems with due date assignment and controllable job-processing times, which are either linear or convex functions of the amount of a continuously divisible and no...

Poster abstract: A machine learning approach for vehicle classification using passive infrared and ultrasonic sensors

KAUST Repository

Warriach, Ehsan Ullah

2013-01-01

This article describes the implementation of four different machine learning techniques for vehicle classification in a dual ultrasonic/passive infrared traffic flow sensors. Using k-NN, Naive Bayes, SVM and KNN-SVM algorithms, we show that KNN-SVM significantly outperforms other algorithms in terms of classification accuracy. We also show that some of these algorithms could run in real time on the prototype system. Copyright © 2013 ACM.

Developments in the application of underground battery vehicles in the UK coal mining industry

Energy Technology Data Exchange (ETDEWEB)

Fortune, J A.B.; Crawshaw, S A.M. [Long-Airdox International Ltd. (United Kingdom)

1996-10-01

Trackless battery powered haulage vehicles have been in operation in British coal mines principally for longwall face transfer and personnel transportation. Changes within the industry have resulted in the introduction of room and pillar coal mining methods and the introduction of increasingly heavier longwall roof supports. This has resulted in the introduction of: battery powered coal haulage machines, which, without the need for trailing cables, increase productivity within room and pillar mining; and battery powered longwall shield haulers which are capable of carrying the heaviest shield supports currently being utilised within the British coal mining industry. The conventional machines have been adapted from an American design to meet the requirements of European legislation. This has seen the emphasis being placed upon the supplier with the European Machinery Directive being introduced, necessitating the assigning of a `CE` mark to each vehicle. Battery vehicle technology has advanced to meet the demands of the ever changing market and will no doubt be further adapted to meet the requirement of the British coal mining industry. 1 ref., 12 figs., 3 tabs.

Cyclic flow shop scheduling problem with two-machine cells

Directory of Open Access Journals (Sweden)

Bożejko Wojciech

2017-06-01

Full Text Available In the paper a variant of cyclic production with setups and two-machine cell is considered. One of the stages of the problem solving consists of assigning each operation to the machine on which it will be carried out. The total number of such assignments is exponential. We propose a polynomial time algorithm finding the optimal operations to machines assignment.

Machine integrated gearbox for electrical vehicles

NARCIS (Netherlands)

Gerrits, T.; Wijnands, C.G.E.; Paulides, J.J.H.; Duarte, J.L.; Lomonova, E.A.

2014-01-01

The speed range that can be obtained with an electric machine is initially limited due to the finite supply voltage of the inverter. A winding reconfiguration method named dynamic machine operation is presented, capable of increasing the speed range and speed ratio by altering the configuration of

Hybrid three-dimensional and support vector machine approach for automatic vehicle tracking and classification using a single camera

Science.gov (United States)

Kachach, Redouane; Cañas, José María

2016-05-01

Using video in traffic monitoring is one of the most active research domains in the computer vision community. TrafficMonitor, a system that employs a hybrid approach for automatic vehicle tracking and classification on highways using a simple stationary calibrated camera, is presented. The proposed system consists of three modules: vehicle detection, vehicle tracking, and vehicle classification. Moving vehicles are detected by an enhanced Gaussian mixture model background estimation algorithm. The design includes a technique to resolve the occlusion problem by using a combination of two-dimensional proximity tracking algorithm and the Kanade-Lucas-Tomasi feature tracking algorithm. The last module classifies the shapes identified into five vehicle categories: motorcycle, car, van, bus, and truck by using three-dimensional templates and an algorithm based on histogram of oriented gradients and the support vector machine classifier. Several experiments have been performed using both real and simulated traffic in order to validate the system. The experiments were conducted on GRAM-RTM dataset and a proper real video dataset which is made publicly available as part of this work.

Research on Modeling and Control of Regenerative Braking for Brushless DC Machines Driven Electric Vehicles

OpenAIRE

Jian-ping Wen; Chuan-wei Zhang

2015-01-01

In order to improve energy utilization rate of battery-powered electric vehicle (EV) using brushless DC machine (BLDCM), the model of braking current generated by regenerative braking and control method are discussed. On the basis of the equivalent circuit of BLDCM during the generative braking period, the mathematic model of braking current is established. By using an extended state observer (ESO) to observe actual braking current and the unknown disturbances of regenerative braking system, ...

HTS machines as enabling technology for all-electric airborne vehicles

International Nuclear Information System (INIS)

Masson, P J; Brown, G V; Soban, D S; Luongo, C A

2007-01-01

Environmental protection has now become paramount as evidence mounts to support the thesis of human activity-driven global warming. A global reduction of the emissions of pollutants into the atmosphere is therefore needed and new technologies have to be considered. A large part of the emissions come from transportation vehicles, including cars, trucks and airplanes, due to the nature of their combustion-based propulsion systems. Our team has been working for several years on the development of high power density superconducting motors for aircraft propulsion and fuel cell based power systems for aircraft. This paper investigates the feasibility of all-electric aircraft based on currently available technology. Electric propulsion would require the development of high power density electric propulsion motors, generators, power management and distribution systems. The requirements in terms of weight and volume of these components cannot be achieved with conventional technologies; however, the use of superconductors associated with hydrogen-based power plants makes possible the design of a reasonably light power system and would therefore enable the development of all-electric aero-vehicles. A system sizing has been performed both for actuators and for primary propulsion. Many advantages would come from electrical propulsion such as better controllability of the propulsion, higher efficiency, higher availability and less maintenance needs. Superconducting machines may very well be the enabling technology for all-electric aircraft development

HTS machines as enabling technology for all-electric airborne vehicles

Energy Technology Data Exchange (ETDEWEB)

Masson, P J [FAMU-FSU College of Engineering and the Center for Advanced Power Systems, Tallahassee, FL 32310 (United States); Brown, G V [NASA Glenn Research Center, Cleveland, OH (United States); Soban, D S [Aerospace System Design Laboratory/Georgia Tech, Atlanta, GA 32332 (United States); Luongo, C A [FAMU-FSU College of Engineering and the Center for Advanced Power Systems, Tallahassee, FL 32310 (United States)

2007-08-15

Environmental protection has now become paramount as evidence mounts to support the thesis of human activity-driven global warming. A global reduction of the emissions of pollutants into the atmosphere is therefore needed and new technologies have to be considered. A large part of the emissions come from transportation vehicles, including cars, trucks and airplanes, due to the nature of their combustion-based propulsion systems. Our team has been working for several years on the development of high power density superconducting motors for aircraft propulsion and fuel cell based power systems for aircraft. This paper investigates the feasibility of all-electric aircraft based on currently available technology. Electric propulsion would require the development of high power density electric propulsion motors, generators, power management and distribution systems. The requirements in terms of weight and volume of these components cannot be achieved with conventional technologies; however, the use of superconductors associated with hydrogen-based power plants makes possible the design of a reasonably light power system and would therefore enable the development of all-electric aero-vehicles. A system sizing has been performed both for actuators and for primary propulsion. Many advantages would come from electrical propulsion such as better controllability of the propulsion, higher efficiency, higher availability and less maintenance needs. Superconducting machines may very well be the enabling technology for all-electric aircraft development.

Multi-objective component sizing of a power-split plug-in hybrid electric vehicle powertrain using Pareto-based natural optimization machines

Science.gov (United States)

Mozaffari, Ahmad; Vajedi, Mahyar; Chehresaz, Maryyeh; Azad, Nasser L.

2016-03-01

The urgent need to meet increasingly tight environmental regulations and new fuel economy requirements has motivated system science researchers and automotive engineers to take advantage of emerging computational techniques to further advance hybrid electric vehicle and plug-in hybrid electric vehicle (PHEV) designs. In particular, research has focused on vehicle powertrain system design optimization, to reduce the fuel consumption and total energy cost while improving the vehicle's driving performance. In this work, two different natural optimization machines, namely the synchronous self-learning Pareto strategy and the elitism non-dominated sorting genetic algorithm, are implemented for component sizing of a specific power-split PHEV platform with a Toyota plug-in Prius as the baseline vehicle. To do this, a high-fidelity model of the Toyota plug-in Prius is employed for the numerical experiments using the Autonomie simulation software. Based on the simulation results, it is demonstrated that Pareto-based algorithms can successfully optimize the design parameters of the vehicle powertrain.

Vehicle speed prediction via a sliding-window time series analysis and an evolutionary least learning machine: A case study on San Francisco urban roads

Directory of Open Access Journals (Sweden)

Ladan Mozaffari

2015-06-01

Full Text Available The main goal of the current study is to take advantage of advanced numerical and intelligent tools to predict the speed of a vehicle using time series. It is clear that the uncertainty caused by temporal behavior of the driver as well as various external disturbances on the road will affect the vehicle speed, and thus, the vehicle power demands. The prediction of upcoming power demands can be employed by the vehicle powertrain control systems to improve significantly the fuel economy and emission performance. Therefore, it is important to systems design engineers and automotive industrialists to develop efficient numerical tools to overcome the risk of unpredictability associated with the vehicle speed profile on roads. In this study, the authors propose an intelligent tool called evolutionary least learning machine (E-LLM to forecast the vehicle speed sequence. To have a practical evaluation regarding the efficacy of E-LLM, the authors use the driving data collected on the San Francisco urban roads by a private Honda Insight vehicle. The concept of sliding window time series (SWTS analysis is used to prepare the database for the speed forecasting process. To evaluate the performance of the proposed technique, a number of well-known approaches, such as auto regressive (AR method, back-propagation neural network (BPNN, evolutionary extreme learning machine (E-ELM, extreme learning machine (ELM, and radial basis function neural network (RBFNN, are considered. The performances of the rival methods are then compared in terms of the mean square error (MSE, root mean square error (RMSE, mean absolute percentage error (MAPE, median absolute percentage error (MDAPE, and absolute fraction of variances (R2 metrics. Through an exhaustive comparative study, the authors observed that E-LLM is a powerful tool for predicting the vehicle speed profiles. The outcomes of the current study can be of use for the engineers of automotive industry who have been

Emergency Brake for Tracked Vehicles

Science.gov (United States)

Green, G. L.; Hooper, S. L.

1986-01-01

Caliper brake automatically stops tracked vehicle as vehicle nears end of travel. Bar on vehicle, traveling to right, dislodges block between brake pads. Pads then press against bar, slowing vehicle by friction. Emergencybraking system suitable for elevators, amusement rides and machine tools.

15 CFR 5.5 - Vending machines.

Science.gov (United States)

2010-01-01

... 15 Commerce and Foreign Trade 1 2010-01-01 2010-01-01 false Vending machines. 5.5 Section 5.5... machines. (a) The income from any vending machines which are located within reasonable proximity to and are... shall be assigned to the operator of such stand. (b) If a vending machine vends articles of a type...

Congestion avoidance and break scheduling within vehicle routing

NARCIS (Netherlands)

Kok, A.L.

2010-01-01

Vehicle routing is a complex daily task for businesses such as logistic service providers and distribution firms. Planners have to assign many orders to many vehicles and, for each vehicle, assign a delivery sequence. The objective is to minimize total transport costs. These costs typically include

Machine Learning for Treatment Assignment: Improving Individualized Risk Attribution.

Science.gov (United States)

Weiss, Jeremy; Kuusisto, Finn; Boyd, Kendrick; Liu, Jie; Page, David

2015-01-01

Clinical studies model the average treatment effect (ATE), but apply this population-level effect to future individuals. Due to recent developments of machine learning algorithms with useful statistical guarantees, we argue instead for modeling the individualized treatment effect (ITE), which has better applicability to new patients. We compare ATE-estimation using randomized and observational analysis methods against ITE-estimation using machine learning, and describe how the ITE theoretically generalizes to new population distributions, whereas the ATE may not. On a synthetic data set of statin use and myocardial infarction (MI), we show that a learned ITE model improves true ITE estimation and outperforms the ATE. We additionally argue that ITE models should be learned with a consistent, nonparametric algorithm from unweighted examples and show experiments in favor of our argument using our synthetic data model and a real data set of D-penicillamine use for primary biliary cirrhosis.

Design of a high-torque machine with two integrated motors axes reducing the electric vehicle consumption

Directory of Open Access Journals (Sweden)

M. Chaieb

2008-03-01

Full Text Available The motorization of electric vehicle needs to work at a constant power on a wide range of speed. In order to be able to satisfy these requirements, we describe in this paper a solution, which consists in modifying of a simple structure of a permanent magnet motor by a double rotor structure integrating two motor axes into the same machine. This article describes, then, a design methodology of a permanent magnet motor with double rotor, radial flux, and strong starting torque for electric vehicles. This work consists on the analytical dimensioning of the motor by taking into account several operation constraints followed by a modelling by the finite elements method. This study is followed by the comparison between this motor and a motor with one rotor. A global model of the motor- converter is developed for the purpose to answer several optimisation problems

Design and setting up of a system for remote monitoring and control on auxiliary machines in electric vehicles

Directory of Open Access Journals (Sweden)

Dimitrov Vasil

2017-01-01

Full Text Available Systems for remote monitoring and control of the proper operation, energy consumption, and efficiency of the controlled objects are very often used in different spheres of industry, in the electricity distribution network, etc. Various types of intelligent energy meters, PLCs and other control devices are involved in such systems. Proper operation of the auxiliary machines in electric vehicles is of great importance and implementation of a system for their remote monitoring and control is useful and ensures reliability and increased efficiency. A system has been designed and built using contemporary devices. An asynchronous motor is controlled by a soft starter and opportunities for remote monitoring (by an intelligent energy meter and control (by a PLC and Touch panel have been provided. Soft starters are widely used in industry for control on asynchronous drives when speed regulation is not a mandatory requirement. They are cheaper than inverters and frequency converters and allow for temporal reduction of the torque and current surge during start-up, as well as smooth deceleration. Therefore they can also be used in electric vehicles to control auxiliary machines (pumps, fans, air coolers, compressors, etc.. The present paper presents a methodology for their design and setting up.

Competitive Traffic Assignment in Road Networks

Directory of Open Access Journals (Sweden)

Krylatov Alexander Y.

2016-09-01

Full Text Available Recently in-vehicle route guidance and information systems are rapidly developing. Such systems are expected to reduce congestion in an urban traffic area. This social benefit is believed to be reached by imposing the route choices on the network users that lead to the system optimum traffic assignment. However, guidance service could be offered by different competitive business companies. Then route choices of different mutually independent groups of users may reject traffic assignment from the system optimum state. In this paper, a game theoretic approach is shown to be very efficient to formalize competitive traffic assignment problem with various groups of users in the form of non-cooperative network game with the Nash equilibrium search. The relationships between the Wardrop’s system optimum associated with the traffic assignment problem and the Nash equilibrium associated with the competitive traffic assignment problem are investigated. Moreover, some related aspects of the Nash equilibrium and the Wardrop’s user equilibrium assignments are also discussed.

Research on Modeling and Control of Regenerative Braking for Brushless DC Machines Driven Electric Vehicles

Directory of Open Access Journals (Sweden)

Jian-ping Wen

2015-01-01

Full Text Available In order to improve energy utilization rate of battery-powered electric vehicle (EV using brushless DC machine (BLDCM, the model of braking current generated by regenerative braking and control method are discussed. On the basis of the equivalent circuit of BLDCM during the generative braking period, the mathematic model of braking current is established. By using an extended state observer (ESO to observe actual braking current and the unknown disturbances of regenerative braking system, the autodisturbances rejection controller (ADRC for controlling the braking current is developed. Experimental results show that the proposed method gives better recovery efficiency and is robust to disturbances.

Tooth-coil permanent magnet synchronous machine design for special applications

Energy Technology Data Exchange (ETDEWEB)

Ponomarev, P.

2013-11-01

This doctoral thesis presents a study on the design of tooth-coil permanent magnet synchronous machines. The electromagnetic properties of concentrated non-overlapping winding permanent magnet synchronous machines, or simply tooth-coil permanent magnet synchronous machines (TC-PMSMs), are studied in details. It is shown that current linkage harmonics play the deterministic role in the behavior of this type of machines. Important contributions are presented as regards of calculation of parameters of TC-PMSMs,particularly the estimation of inductances. The current linkage harmonics essentially define the air-gap harmonic leakage inductance, rotor losses and localized temporal inductance variation. It is proven by FEM analysis that inductance variation caused by the local temporal harmonic saturation results in considerable torque ripple, and can influence on sensorless control capabilities. Example case studies an integrated application of TC-IPMSMs in hybrid off-highway working vehicles. A methodology for increasing the efficiency of working vehicles is introduced. It comprises several approaches - hybridization, working operations optimization, component optimization and integration. As a result of component optimization and integration, a novel integrated electro-hydraulic energy converter (IEHEC) for off-highway working vehicles is designed. The IEHEC can considerably increase the operational efficiency of a hybrid working vehicle. The energy converter consists of an axial-piston hydraulic machine and an integrated TCIPMSM being built on the same shaft. The compact assembly of the electrical and hydraulic machines enhances the ability to find applications for such a device in the mobile environment of working vehicles.Usage of hydraulic fluid, typically used in working actuators, enables direct-immersion oil cooling of designed electrical machine, and further increases the torque- and power- densities of the whole device. (orig.)

Modeling and design of cooperative braking in electric and hybrid vehicles using induction machine and hydraulic brake

Directory of Open Access Journals (Sweden)

Zaini Dalimus

2016-07-01

Full Text Available In mixed-mode braking applications, the electric motor / generator (M/G and hydraulic pressure valve are controlled to meet the driver’s braking demand. Controlling these braking elements is achieved by modulating the current generated by the M/G and adjusting the fluid pressure to the wheel brake cylinders. This paper aims to model and design combined regenerative and hydraulic braking systems which, comprise an induction electric machine, inverter, NiMH battery, controller, a pressure source, pressure control unit, and brake calipers. A 15 kW 1500 rpm induction machine equipped with a reduction gear having a gear ratio of 4 is used. A hydraulic brake capable to produce fluid pressure up to 40 bar is used. Direct torque control and pressure control are chosen as the control criteria in the M/G and the hydraulic solenoid valve. The braking demands for the system are derived from the Federal Testing Procedure (FTP drive cycle. Two simulation models have been developed in Matlab®/Simulink® to analyze the performance of the control strategy in each braking system. The developed model is validated through experiment. It is concluded that the control system does introduce torque ripple and pressure oscillation in the braking system, but these effects do not affect vehicle braking performance due to the high frequency nature of pressure fluctuation and the damping effect of the vehicle inertia. Moreover, experiment results prove the effectiveness of the developed model.

Dual-Electrical-Port Control of Cascaded Doubly-Fed Induction Machine for EV/HEV Applications

DEFF Research Database (Denmark)

Han, Peng; Cheng, Ming; Chen, Zhe

2017-01-01

that of the power machine in singly-fed operation mode, and only a half of that of the power machine in doubly-fed operation mode, which shows the urgent need for torque density enhancement of brushless doubly-fed machines for electric vehicle/hybrid electric vehicle applications. Computer simulations...

Habit learning and brain-machine interfaces (BMI): a tribute to Valentino Braitenberg's "Vehicles".

Science.gov (United States)

Birbaumer, Niels; Hummel, Friedhelm C

2014-10-01

Brain-Machine Interfaces (BMI) allow manipulation of external devices and computers directly with brain activity without involvement of overt motor actions. The neurophysiological principles of such robotic brain devices and BMIs follow Hebbian learning rules as described and realized by Valentino Braitenberg in his book "Vehicles," in the concept of a "thought pump" residing in subcortical basal ganglia structures. We describe here the application of BMIs for brain communication in totally locked-in patients and argue that the thought pump may extinguish-at least partially-in those people because of extinction of instrumentally learned cognitive responses and brain responses. We show that Pavlovian semantic conditioning may allow brain communication even in the completely paralyzed who does not show response-effect contingencies. Principles of skill learning and habit acquisition as formulated by Braitenberg are the building blocks of BMIs and neuroprostheses.

IPAD applications to the design, analysis, and/or machining of aerospace structures. [Integrated Program for Aerospace-vehicle Design

Science.gov (United States)

Blackburn, C. L.; Dovi, A. R.; Kurtze, W. L.; Storaasli, O. O.

1981-01-01

A computer software system for the processing and integration of engineering data and programs, called IPAD (Integrated Programs for Aerospace-Vehicle Design), is described. The ability of the system to relieve the engineer of the mundane task of input data preparation is demonstrated by the application of a prototype system to the design, analysis, and/or machining of three simple structures. Future work to further enhance the system's automated data handling and ability to handle larger and more varied design problems are also presented.

49 CFR 214.523 - Hi-rail vehicles.

Science.gov (United States)

2010-10-01

... 49 Transportation 4 2010-10-01 2010-10-01 false Hi-rail vehicles. 214.523 Section 214.523..., DEPARTMENT OF TRANSPORTATION RAILROAD WORKPLACE SAFETY On-Track Roadway Maintenance Machines and Hi-Rail Vehicles § 214.523 Hi-rail vehicles. (a) The hi-rail gear of all hi-rail vehicles shall be inspected for...

Applications of random forest feature selection for fine-scale genetic population assignment.

Science.gov (United States)

Sylvester, Emma V A; Bentzen, Paul; Bradbury, Ian R; Clément, Marie; Pearce, Jon; Horne, John; Beiko, Robert G

2018-02-01

Genetic population assignment used to inform wildlife management and conservation efforts requires panels of highly informative genetic markers and sensitive assignment tests. We explored the utility of machine-learning algorithms (random forest, regularized random forest and guided regularized random forest) compared with F ST ranking for selection of single nucleotide polymorphisms (SNP) for fine-scale population assignment. We applied these methods to an unpublished SNP data set for Atlantic salmon ( Salmo salar ) and a published SNP data set for Alaskan Chinook salmon ( Oncorhynchus tshawytscha ). In each species, we identified the minimum panel size required to obtain a self-assignment accuracy of at least 90% using each method to create panels of 50-700 markers Panels of SNPs identified using random forest-based methods performed up to 7.8 and 11.2 percentage points better than F ST -selected panels of similar size for the Atlantic salmon and Chinook salmon data, respectively. Self-assignment accuracy ≥90% was obtained with panels of 670 and 384 SNPs for each data set, respectively, a level of accuracy never reached for these species using F ST -selected panels. Our results demonstrate a role for machine-learning approaches in marker selection across large genomic data sets to improve assignment for management and conservation of exploited populations.

Duality-based algorithms for scheduling on unrelated parallel machines

NARCIS (Netherlands)

van de Velde, S.L.; van de Velde, S.L.

1993-01-01

We consider the following parallel machine scheduling problem. Each of n independent jobs has to be scheduled on one of m unrelated parallel machines. The processing of job J[sub l] on machine Mi requires an uninterrupted period of positive length p[sub lj]. The objective is to find an assignment of

Experimental Semiautonomous Vehicle

Science.gov (United States)

Wilcox, Brian H.; Mishkin, Andrew H.; Litwin, Todd E.; Matthies, Larry H.; Cooper, Brian K.; Nguyen, Tam T.; Gat, Erann; Gennery, Donald B.; Firby, Robert J.; Miller, David P.;

Human machine interface to manually drive rhombic like vehicles such as transport casks in ITER

Energy Technology Data Exchange (ETDEWEB)

Lopes, Pedro; Vale, Alberto [Instituto de Plasmas e Fusao Nuclear, Instituto Superior Tecnico, Universidade de Lisboa, Av. Rovisco Pais 1, 1049-001 Lisboa (Portugal); Ventura, Rodrigo [Institute for Systems and Robotics, Instituto Superior Tecnico, Universidade de Lisboa, Av. Rovisco Pais 1, 1049-001 Lisboa (Portugal)

2015-07-01

The Cask and Plug Remote Handling System (CPRHS) and the respective Cask Transfer System (CTS) are designed to transport activated components between the reactor and the hot cell buildings of ITER during maintenance operations. In nominal operation, the CPRHS/CTS shall operate autonomously under human supervision. However, in some unexpected situations, the automatic mode must be overridden and the vehicle must be remotely guided by a human operator due to the harsh conditions of the environment. The CPRHS/CTS is a rhombic-like vehicle with two independent steerable and drivable wheels along its longitudinal axis, giving it omni-directional capabilities. During manual guidance, the human operator has to deal with four degrees of freedom, namely the orientations and speeds of two wheels. This work proposes a Human Machine Interface (HMI) to manage the degrees of freedom and to remotely guide the CPRHS/CTS in ITER taking the most advantages of rhombic like capabilities. Previous work was done to drive each wheel independently, i.e., control the orientation and speed of each wheel independently. The results have shown that the proposed solution is inefficient. The attention of the human operator becomes focused in a single wheel. In addition, the proposed solution cannot assure that the commands accomplish the physical constrains of the vehicle, resulting in slippage or even in clashes. This work proposes a solution that consists in the control of the vehicle looking at the position of its center of mass and its heading in the world frame. The solution is implemented using a rotational disk to control the vehicle heading and a common analogue joystick to control the vector speed of the center of the mass of the vehicle. The number of degrees of freedom reduces to three, i.e., two angles (vehicle heading and the orientation of the vector speed) and a scalar (the magnitude of the speed vector). This is possible using a kinematic model based on the vehicle Instantaneous

Human machine interface to manually drive rhombic like vehicles such as transport casks in ITER

International Nuclear Information System (INIS)

Lopes, Pedro; Vale, Alberto; Ventura, Rodrigo

2015-01-01

The Cask and Plug Remote Handling System (CPRHS) and the respective Cask Transfer System (CTS) are designed to transport activated components between the reactor and the hot cell buildings of ITER during maintenance operations. In nominal operation, the CPRHS/CTS shall operate autonomously under human supervision. However, in some unexpected situations, the automatic mode must be overridden and the vehicle must be remotely guided by a human operator due to the harsh conditions of the environment. The CPRHS/CTS is a rhombic-like vehicle with two independent steerable and drivable wheels along its longitudinal axis, giving it omni-directional capabilities. During manual guidance, the human operator has to deal with four degrees of freedom, namely the orientations and speeds of two wheels. This work proposes a Human Machine Interface (HMI) to manage the degrees of freedom and to remotely guide the CPRHS/CTS in ITER taking the most advantages of rhombic like capabilities. Previous work was done to drive each wheel independently, i.e., control the orientation and speed of each wheel independently. The results have shown that the proposed solution is inefficient. The attention of the human operator becomes focused in a single wheel. In addition, the proposed solution cannot assure that the commands accomplish the physical constrains of the vehicle, resulting in slippage or even in clashes. This work proposes a solution that consists in the control of the vehicle looking at the position of its center of mass and its heading in the world frame. The solution is implemented using a rotational disk to control the vehicle heading and a common analogue joystick to control the vector speed of the center of the mass of the vehicle. The number of degrees of freedom reduces to three, i.e., two angles (vehicle heading and the orientation of the vector speed) and a scalar (the magnitude of the speed vector). This is possible using a kinematic model based on the vehicle Instantaneous

The machine intelligence Hex project

Science.gov (United States)

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

2005-12-01

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 players and evaluating them in an automated tournament of all programs developed by the class. This article surveys educational aspects of the MIHex project. Additionally, fundamental techniques for game programming as well as specific concepts for Hex board evaluation are reviewed. The MIHex game server and possibilities of tournament organisation are described. We summarise and discuss our experiences from running the MIHex project assignment over four consecutive years. The impact on student motivation and learning benefits are evaluated using questionnaires and interviews.

49 CFR 214.513 - Retrofitting of existing on-track roadway maintenance machines; general.

Science.gov (United States)

2010-10-01

... maintenance machines; general. 214.513 Section 214.513 Transportation Other Regulations Relating to... SAFETY On-Track Roadway Maintenance Machines and Hi-Rail Vehicles § 214.513 Retrofitting of existing on-track roadway maintenance machines; general. (a) Each existing on-track roadway maintenance machine...

Structural Encoding of Static Single Assignment Form

DEFF Research Database (Denmark)

Gal, Andreas; Probst, Christian; Franz, Michael

2005-01-01

Static Single Assignment (SSA) form is often used as an intermediate representation during code optimization in Java Virtual Machines. Recently, SSA has successfully been used for bytecode verification. However, constructing SSA at the code consumer is costly. SSAbased mobile code transport formats...... Java bytecode. While the resulting bytecode sequence can still be directly executed by traditional Virtual Machines, our novel VM can infer SSA form and confirm its safety with virtually no overhead....... have been shown to eliminate this cost by shifting SSA creation to the code producer. These new formats, however, are not backward compatible with the established Java class-file format. We propose a novel approach to transport SSA information implicitly through structural code properties of standard...

Energy conversion loops for flux-switching PM machine analysis

NARCIS (Netherlands)

Ilhan, E.; Motoasca, T.E.; Paulides, J.J.H.; Lomonova, E.

2012-01-01

Induction and synchronous machines have traditionally been the first choice of automotive manufacturers for electric/hybrid vehicles. However, these conventional machines are not able anymore to meet the increasing demands for a higher energy density due to space limitation in cars. Flux-switching

49 CFR 214.515 - Overhead covers for existing on-track roadway maintenance machines.

Science.gov (United States)

2010-10-01

... maintenance machines. 214.515 Section 214.515 Transportation Other Regulations Relating to Transportation... Roadway Maintenance Machines and Hi-Rail Vehicles § 214.515 Overhead covers for existing on-track roadway maintenance machines. (a) For those existing on-track roadway maintenance machines either currently or...

The free-piston Vuilleumier machine: a new refrigerating sink from heat loss recovery?; La machine de Vuilleumier a pistons libres: une nouvelle source de froid par recuperation?

Energy Technology Data Exchange (ETDEWEB)

Rochelle, P. [Laboratoire de Mecanique Physique, UP6, 78 - Saint Cyr l' Ecole (France); Rochelle, P.; Grosu, L. [Laboratoire d' Energetique et d' Economie de l' Energie, UP10, 92 - Ville d' Avray (France)

2002-07-01

The Vuilleumier machine combines two Stirling cycles: a prime mover and a refrigerating cycle. lt could produce cold and heat at low temperature levels from heat loss recovered at the exhaust of heat generating processes (industrial transforming processes, thermal engines,...). Here, these regenerating dual cycle machines and their potential applications, particularly those concerning transportation vehicles, are examined. Towards this purpose, the Vuilleumier machine principles are briefly described along with a more in-depth look at the free-piston configuration type. In principle, these machines are simple to build, but specific starting and continuous running conditions must be met, and here they are established. Then, we discuss the applicability of these systems to vehicles, and the usable geometrical configurations are shortly examined with, as an application, the pre-design calculus of a 'pancake' machine. (authors)

Analyzing the multiple-target-multiple-agent scenario using optimal assignment algorithms

Science.gov (United States)

Kwok, Kwan S.; Driessen, Brian J.; Phillips, Cynthia A.; Tovey, Craig A.

1997-09-01

This work considers the problem of maximum utilization of a set of mobile robots with limited sensor-range capabilities and limited travel distances. The robots are initially in random positions. A set of robots properly guards or covers a region if every point within the region is within the effective sensor range of at least one vehicle. We wish to move the vehicles into surveillance positions so as to guard or cover a region, while minimizing the maximum distance traveled by any vehicle. This problem can be formulated as an assignment problem, in which we must optimally decide which robot to assign to which slot of a desired matrix of grid points. The cost function is the maximum distance traveled by any robot. Assignment problems can be solved very efficiently. Solution times for one hundred robots took only seconds on a silicon graphics crimson workstation. The initial positions of all the robots can be sampled by a central base station and their newly assigned positions communicated back to the robots. Alternatively, the robots can establish their own coordinate system with the origin fixed at one of the robots and orientation determined by the compass bearing of another robot relative to this robot. This paper presents example solutions to the multiple-target-multiple-agent scenario using a matching algorithm. Two separate cases with one hundred agents in each were analyzed using this method. We have found these mobile robot problems to be a very interesting application of network optimization methods, and we expect this to be a fruitful area for future research.

Analyzing the multiple-target-multiple-agent scenario using optimal assignment algorithms

International Nuclear Information System (INIS)

Kwok, K.S.; Driessen, B.J.; Phillips, C.A.; Tovey, C.A.

1997-01-01

This work considers the problem of maximum utilization of a set of mobile robots with limited sensor-range capabilities and limited travel distances. The robots are initially in random positions. A set of robots properly guards or covers a region if every point within the region is within the effective sensor range of at least one vehicle. The authors wish to move the vehicles into surveillance positions so as to guard or cover a region, while minimizing the maximum distance traveled by any vehicle. This problem can be formulated as an assignment problem, in which they must optimally decide which robot to assign to which slot of a desired matrix of grid points. The cost function is the maximum distance traveled by any robot. Assignment problems can be solved very efficiently. Solutions times for one hundred robots took only seconds on a Silicon Graphics Crimson workstation. The initial positions of all the robots can be sampled by a central base station and their newly assigned positions communicated back to the robots. Alternatively, the robots can establish their own coordinate system with the origin fixed at one of the robots and orientation determined by the compass bearing of another robot relative to this robot. This paper presents example solutions to the multiple-target-multiple-agent scenario using a matching algorithm. Two separate cases with one hundred agents in each were analyzed using this method. They have found these mobile robot problems to be a very interesting application of network optimization methods, and they expect this to be a fruitful area for future research

Single Stator Dual PM Rotor Synchronous Machine with two-frequency single-inverter control, for the propulsion of hybrid electric vehicles

Directory of Open Access Journals (Sweden)

Topor Marcel

2017-01-01

Full Text Available This paper introduces a novel brushless, single winding and single stator, dual PM rotor axial-air-gap machine capable to deliver independently torque at the two rotors by adequate dual vector control. The proposed topologies, the circuit model, controlled dynamics simulation and preliminary 3D FEM torque production on a case study constitute the core of the paper. The proposed dual mechanical port system should be instrumental in parallel (with planetary gears or series hybrid electric vehicles (HEV aiming at a more compact and efficient electric propulsion system solution.

Flexible ship loading problem with transfer vehicle assignment and scheduling

DEFF Research Database (Denmark)

Iris, Çağatay; Christensen, Jonas; Pacino, Dario

2018-01-01

This paper presents the flexible containership loading problem for seaport container terminals. The integrated management of loading operations, planning of the transport vehicles to use and their scheduling is what we define as the Flexible Ship Loading Problem (FSLP). The flexibility comes from...

A Novel Vehicle Classification Using Embedded Strain Gauge Sensors

Directory of Open Access Journals (Sweden)

Qi Wang

2008-11-01

Full Text Available Abstract: This paper presents a new vehicle classification and develops a traffic monitoring detector to provide reliable vehicle classification to aid traffic management systems. The basic principle of this approach is based on measuring the dynamic strain caused by vehicles across pavement to obtain the corresponding vehicle parameters – wheelbase and number of axles – to then accurately classify the vehicle. A system prototype with five embedded strain sensors was developed to validate the accuracy and effectiveness of the classification method. According to the special arrangement of the sensors and the different time a vehicle arrived at the sensors one can estimate the vehicle’s speed accurately, corresponding to the estimated vehicle wheelbase and number of axles. Because of measurement errors and vehicle characteristics, there is a lot of overlap between vehicle wheelbase patterns. Therefore, directly setting up a fixed threshold for vehicle classification often leads to low-accuracy results. Using the machine learning pattern recognition method to deal with this problem is believed as one of the most effective tools. In this study, support vector machines (SVMs were used to integrate the classification features extracted from the strain sensors to automatically classify vehicles into five types, ranging from small vehicles to combination trucks, along the lines of the Federal Highway Administration vehicle classification guide. Test bench and field experiments will be introduced in this paper. Two support vector machines classification algorithms (one-against-all, one-against-one are used to classify single sensor data and multiple sensor combination data. Comparison of the two classification method results shows that the classification accuracy is very close using single data or multiple data. Our results indicate that using multiclass SVM-based fusion multiple sensor data significantly improves

Control system and method for a hybrid electric vehicle

Science.gov (United States)

Phillips, Anthony Mark; Blankenship, John Richard; Bailey, Kathleen Ellen; Jankovic, Miroslava

2001-01-01

A vehicle system controller (20) is presented for a LSR parallel hybrid electric vehicle having an engine (10), a motor (12), wheels (14), a transmission (16) and a battery (18). The vehicle system controller (20) has a state machine having a plurality of predefined states (22-32) that represent operating modes for the vehicle. A set of rules is defined for controlling the transition between any two states in the state machine. The states (22-32) are prioritized according to driver demands, energy management concerns and system fault occurrences. The vehicle system controller (20) controls the transitions from a lower priority state to a higher priority state based on the set of rules. In addition, the vehicle system controller (20) will control a transition to a lower state from a higher state when the conditions no longer warrant staying in the current state. A unique set of output commands is defined for each state for the purpose of controlling lower level subsystem controllers. These commands serve to achieve the desire vehicle functionality within each state and insure smooth transitions between states.

Constrained state-feedback control of an externally excited synchronous machine

NARCIS (Netherlands)

Carpiuc, S.C.; Lazar, M.

2013-01-01

State-feedback control of externally excited synchronous machines employed in applications such as hybrid electric vehicles and full electric vehicles is a challenging problem. Indeed, these applications are characterized by fast dynamics that are subject to hard physical and control constraints.

Influence of Different Rotor Teeth Shapes on the Performance of Flux Switching Permanent Magnet Machines Used for Electric Vehicles

Directory of Open Access Journals (Sweden)

Jing Zhao

2014-12-01

Full Text Available This paper investigated a 12-slot/11-pole flux switching permanent magnet (FSPM machine used for electric vehicles (EVs. Five novel rotor teeth shapes are proposed and researched to reduce the cogging torque and torque ripple of the FSPM machine. These rotor teeth shapes are notched teeth, stepped teeth, eccentric teeth, combination of notched and stepped teeth, and combination of notched and eccentric teeth. They are applied on the rotor and optimized, respectively. The influences of different rotor teeth shapes on cogging torque, torque ripple and electromagnetic torque are analyzed by the 2-D finite-element method (FEM. Then, the performance of FSPMs with different rotor teeth shapes are compared and evaluated comprehensively from the points of view of cogging torque, torque ripple, electromagnetic torque, flux linkage, back electromotive force (EMF, and so on. The results show that the presented rotor teeth shapes, especially the combination of stepped and notched teeth, can greatly reduce the cogging torque and torque ripple with only slight changes in the average electromagnetic torque.

49 CFR 214.507 - Required safety equipment for new on-track roadway maintenance machines.

Science.gov (United States)

2010-10-01

... maintenance machines. 214.507 Section 214.507 Transportation Other Regulations Relating to Transportation... Roadway Maintenance Machines and Hi-Rail Vehicles § 214.507 Required safety equipment for new on-track roadway maintenance machines. (a) Each new on-track roadway maintenance machine shall be equipped with: (1...

Integrated Inverter For Driving Multiple Electric Machines

Science.gov (United States)

Su, Gui-Jia [Knoxville, TN; Hsu, John S [Oak Ridge, TN

2006-04-04

An electric machine drive (50) has a plurality of inverters (50a, 50b) for controlling respective electric machines (57, 62), which may include a three-phase main traction machine (57) and two-phase accessory machines (62) in a hybrid or electric vehicle. The drive (50) has a common control section (53, 54) for controlling the plurality of inverters (50a, 50b) with only one microelectronic processor (54) for controlling the plurality of inverters (50a, 50b), only one gate driver circuit (53) for controlling conduction of semiconductor switches (S1-S10) in the plurality of inverters (50a, 50b), and also includes a common dc bus (70), a common dc bus filtering capacitor (C1) and a common dc bus voltage sensor (67). The electric machines (57, 62) may be synchronous machines, induction machines, or PM machines and may be operated in a motoring mode or a generating mode.

Axial flux permanent magnet brushless machines

CERN Document Server

Gieras, Jacek F; Kamper, Maarten J

2008-01-01

Axial Flux Permanent Magnet (AFPM) brushless machines are modern electrical machines with a lot of advantages over their conventional counterparts. They are being increasingly used in consumer electronics, public life, instrumentation and automation system, clinical engineering, industrial electromechanical drives, automobile manufacturing industry, electric and hybrid electric vehicles, marine vessels and toys. They are also used in more electric aircrafts and many other applications on larger scale. New applications have also emerged in distributed generation systems (wind turbine generators

49 CFR 214.511 - Required audible warning devices for new on-track roadway maintenance machines.

Science.gov (United States)

2010-10-01

... roadway maintenance machines. 214.511 Section 214.511 Transportation Other Regulations Relating to... SAFETY On-Track Roadway Maintenance Machines and Hi-Rail Vehicles § 214.511 Required audible warning devices for new on-track roadway maintenance machines. Each new on-track roadway maintenance machine shall...

Vehicle Remote Health Monitoring and Prognostic Maintenance System

Directory of Open Access Journals (Sweden)

Uferah Shafi

2018-01-01

Full Text Available In many industries inclusive of automotive vehicle industry, predictive maintenance has become more important. It is hard to diagnose failure in advance in the vehicle industry because of the limited availability of sensors and some of the designing exertions. However with the great development in automotive industry, it looks feasible today to analyze sensor’s data along with machine learning techniques for failure prediction. In this article, an approach is presented for fault prediction of four main subsystems of vehicle, fuel system, ignition system, exhaust system, and cooling system. Sensor is collected when vehicle is on the move, both in faulty condition (when any failure in specific system has occurred and in normal condition. The data is transmitted to the server which analyzes the data. Interesting patterns are learned using four classifiers, Decision Tree, Support Vector Machine, K Nearest Neighbor, and Random Forest. These patterns are later used to detect future failures in other vehicles which show the similar behavior. The approach is produced with the end goal of expanding vehicle up-time and was demonstrated on 70 vehicles of Toyota Corolla type. Accuracy comparison of all classifiers is performed on the basis of Receiver Operating Characteristics (ROC curves.

Analysis of labor employment assessment on production machine to minimize time production

Science.gov (United States)

Hernawati, Tri; Suliawati; Sari Gumay, Vita

2018-03-01

Every company both in the field of service and manufacturing always trying to pass efficiency of it’s resource use. One resource that has an important role is labor. Labor has different efficiency levels for different jobs anyway. Problems related to the optimal allocation of labor that has different levels of efficiency for different jobs are called assignment problems, which is a special case of linear programming. In this research, Analysis of Labor Employment Assesment on Production Machine to Minimize Time Production, in PT PDM is done by using Hungarian algorithm. The aim of the research is to get the assignment of optimal labor on production machine to minimize time production. The results showed that the assignment of existing labor is not suitable because the time of completion of the assignment is longer than the assignment by using the Hungarian algorithm. By applying the Hungarian algorithm obtained time savings of 16%.

Locomotive Assignment Problem with Heterogeneous Vehicle Fleet and Hiring External Locomotives

Directory of Open Access Journals (Sweden)

Dušan Teichmann

2015-01-01

Full Text Available This paper focuses on solving the problem of how to assign locomotives to assembled trains optimally. To solve the problem, linear programming is applied. The situation we model in the paper occurs in the conditions of a transport operator that provides rail transport in the Czech Republic. In the paper, an extended locomotive assignment problem is modeled; the transport operator can use different classes of the locomotives to serve individual connections, some connections must be served by a predefined locomotive class, and the locomotives can be allocated to several depots at the beginning. The proposed model also takes into consideration the fact that some connections can be served by the locomotives of external transport companies or operators. The presented model is applied to a real example in order to test its functionality.

Evolution of Machine Reliability and Life and Economics of Operational Use

Directory of Open Access Journals (Sweden)

Młynarski Stanisław

2016-12-01

Full Text Available The article presents new assumptions for reliability and life of machines, resulting from the development of technology. The innovative approach to reliability and life design as well as warranty duration planning is presented on an example of vehicle reliability characteristics. A new algorithm is proposed for the replacement of repairable objects costs by the price of life and reliability of new unrepairable ones. For the planning of the life of innovative machines, an effective method of technical progress rate determination is proposed. In conclusion, necessary modifications of machine and vehicle use systems, resulting from technology evolution and technical progress, are indicated. Finally, recommendations and directions of indispensable research in engineering and management of technical means of production are formulated.

A tubular flux-switching permanent magnet machine

Science.gov (United States)

Wang, J.; Wang, W.; Clark, R.; Atallah, K.; Howe, D.

2008-04-01

The paper describes a novel tubular, three-phase permanent magnet brushless machine, which combines salient features from both switched reluctance and permanent magnet machine technologies. It has no end windings and zero net radial force and offers a high power density and peak force capability, as well as the potential for low manufacturing cost. It is, therefore, eminently suitable for a variety of applications, ranging from free-piston energy converters to active vehicle suspensions.

Potential air pollutant emission from private vehicles based on vehicle route

Science.gov (United States)

Huboyo, H. S.; Handayani, W.; Samadikun, B. P.

2017-06-01

Air emissions related to the transportation sector has been identified as the second largest emitter of ambient air quality in Indonesia. This is due to large numbers of private vehicles commuting within the city as well as inter-city. A questionnaire survey was conducted in Semarang city involving 711 private vehicles consisting of cars and motorcycles. The survey was conducted in random parking lots across the Semarang districts and in vehicle workshops. Based on the parking lot survey, the average distance private cars travelled in kilometers (VKT) was 17,737 km/year. The machine start-up number of cars during weekdays; weekends were on average 5.19 and 3.79 respectively. For motorcycles the average of kilometers travelled was 27,092 km/year. The machine start-up number of motorcycles during weekdays and weekends were on average 5.84 and 3.98, respectively. The vehicle workshop survey showed the average kilometers travelled to be 9,510 km/year for motorcycles, while for private cars the average kilometers travelled was 21,347 km/year. Odometer readings for private cars showed a maximum of 3,046,509 km and a minimum of 700 km. Meanwhile, for motorcycles, odometer readings showed a maximum of 973,164 km and a minimum of roughly 54.24 km. Air pollutant emissions on East-West routes were generally higher than those on South-North routes. Motorcycles contribute significantly to urban air pollution, more so than cars. In this study, traffic congestion and traffic volume contributed much more to air pollution than the impact of fluctuating terrain.

Smart mobile in-vehicle systems next generation advancements

CERN Document Server

Abut, Huseyin; Takeda, Kazuya; Hansen, John

2014-01-01

This is an edited collection by world-class experts, from diverse fields, focusing on integrating smart in-vehicle systems with human factors to enhance safety in automobiles. The book presents developments on road safety, in-vehicle technologies and state-of-the art systems. Includes coverage of DSP technologies in adaptive automobiles, algorithms and evaluation of in-car communication systems, driver-status monitoring and stress detection, in-vehicle dialogue systems and human-machine interfaces, challenges in video and audio processing for in-vehicle products, multi-sensor fusion for driver identification and vehicle to infrastructure wireless technologies.

Very Large-Scale Neighborhoods with Performance Guarantees for Minimizing Makespan on Parallel Machines

NARCIS (Netherlands)

Brueggemann, T.; Hurink, Johann L.; Vredeveld, T.; Woeginger, Gerhard

2006-01-01

We study the problem of minimizing the makespan on m parallel machines. We introduce a very large-scale neighborhood of exponential size (in the number of machines) that is based on a matching in a complete graph. The idea is to partition the jobs assigned to the same machine into two sets. This

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

Science.gov (United States)

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.

Support vector machine based battery model for electric vehicles

International Nuclear Information System (INIS)

Wang Junping; Chen Quanshi; Cao Binggang

2006-01-01

The support vector machine (SVM) is a novel type of learning machine based on statistical learning theory that can map a nonlinear function successfully. As a battery is a nonlinear system, it is difficult to establish the relationship between the load voltage and the current under different temperatures and state of charge (SOC). The SVM is used to model the battery nonlinear dynamics in this paper. Tests are performed on an 80Ah Ni/MH battery pack with the Federal Urban Driving Schedule (FUDS) cycle to set up the SVM model. Compared with the Nernst and Shepherd combined model, the SVM model can simulate the battery dynamics better with small amounts of experimental data. The maximum relative error is 3.61%

41 CFR 101-39.204 - Obtaining motor vehicles for indefinite assignment.

Science.gov (United States)

2010-07-01

..., TRANSPORTATION, AND MOTOR VEHICLES 39-INTERAGENCY FLEET MANAGEMENT SYSTEMS 39.2-GSA Interagency Fleet Management... related services of the GSA Interagency Fleet Management System (IFMS) are provided to requesting agencies... have been consolidated into the supporting GSA IFMS fleet management center, and no agency-owned...

Sustainable Electric Vehicle Management using Coordinated Machine Learning

NARCIS (Netherlands)

K. Valogianni (Konstantina)

2016-01-01

markdownabstractThe purpose of this dissertation is to investigate how intelligent algorithms can support electricity customers in their complex decisions within the electricity grid. In particular, we focus on how electric vehicle (EV) owners can be supported in their charging and discharging

Methodology for testing a system for remote monitoring and control on auxiliary machines in electric vehicles

Directory of Open Access Journals (Sweden)

Dimitrov Vasil

2017-01-01

Full Text Available A laboratory system for remote monitoring and control of an asynchronous motor controlled by a soft starter and contemporary measuring and control devices has been developed and built. This laboratory system is used for research and in teaching. A study of the principles of operation, setting up and examination of intelligent energy meters, soft starters and PLC has been made as knowledge of the relevant software products is necessary. This is of great importance because systems for remote monitoring and control of energy consumption, efficiency and proper operation of the controlled objects are very often used in different spheres of industry, in building automation, transport, electricity distribution network, etc. Their implementation in electric vehicles for remote monitoring and control on auxiliary machines is also possible and very useful. In this paper, a methodology of tests is developed and some experiments are presented. Thus, an experimental verification of the developed methodology is made.

49 CFR 214.519 - Floors, decks, stairs, and ladders of on-track roadway maintenance machines.

Science.gov (United States)

2010-10-01

... roadway maintenance machines. 214.519 Section 214.519 Transportation Other Regulations Relating to... SAFETY On-Track Roadway Maintenance Machines and Hi-Rail Vehicles § 214.519 Floors, decks, stairs, and ladders of on-track roadway maintenance machines. Floors, decks, stairs, and ladders of on-track roadway...

PLA realizations for VLSI state machines

Science.gov (United States)

Gopalakrishnan, S.; Whitaker, S.; Maki, G.; Liu, K.

1990-01-01

A major problem associated with state assignment procedures for VLSI controllers is obtaining an assignment that produces minimal or near minimal logic. The key item in Programmable Logic Array (PLA) area minimization is the number of unique product terms required by the design equations. This paper presents a state assignment algorithm for minimizing the number of product terms required to implement a finite state machine using a PLA. Partition algebra with predecessor state information is used to derive a near optimal state assignment. A maximum bound on the number of product terms required can be obtained by inspecting the predecessor state information. The state assignment algorithm presented is much simpler than existing procedures and leads to the same number of product terms or less. An area-efficient PLA structure implemented in a 1.0 micron CMOS process is presented along with a summary of the performance for a controller implemented using this design procedure.

State Machine Modeling of the Space Launch System Solid Rocket Boosters

Science.gov (United States)

Harris, Joshua A.; Patterson-Hine, Ann

2013-01-01

The Space Launch System is a Shuttle-derived heavy-lift vehicle currently in development to serve as NASA's premiere launch vehicle for space exploration. The Space Launch System is a multistage rocket with two Solid Rocket Boosters and multiple payloads, including the Multi-Purpose Crew Vehicle. Planned Space Launch System destinations include near-Earth asteroids, the Moon, Mars, and Lagrange points. The Space Launch System is a complex system with many subsystems, requiring considerable systems engineering and integration. To this end, state machine analysis offers a method to support engineering and operational e orts, identify and avert undesirable or potentially hazardous system states, and evaluate system requirements. Finite State Machines model a system as a finite number of states, with transitions between states controlled by state-based and event-based logic. State machines are a useful tool for understanding complex system behaviors and evaluating "what-if" scenarios. This work contributes to a state machine model of the Space Launch System developed at NASA Ames Research Center. The Space Launch System Solid Rocket Booster avionics and ignition subsystems are modeled using MATLAB/Stateflow software. This model is integrated into a larger model of Space Launch System avionics used for verification and validation of Space Launch System operating procedures and design requirements. This includes testing both nominal and o -nominal system states and command sequences.

Utilization of rotor kinetic energy storage for hybrid vehicles

Science.gov (United States)

Hsu, John S [Oak Ridge, TN

2011-05-03

A power system for a motor vehicle having an internal combustion engine, the power system comprises an electric machine (12) further comprising a first excitation source (47), a permanent magnet rotor (28) and a magnetic coupling rotor (26) spaced from the permanent magnet rotor and at least one second excitation source (43), the magnetic coupling rotor (26) also including a flywheel having an inertial mass to store kinetic energy during an initial acceleration to an operating speed; and wherein the first excitation source is electrically connected to the second excitation source for power cycling such that the flywheel rotor (26) exerts torque on the permanent magnet rotor (28) to assist braking and acceleration of the permanent magnet rotor (28) and consequently, the vehicle. An axial gap machine and a radial gap machine are disclosed and methods of the invention are also disclosed.

Energy Conversion Loops for Flux-Switching PM Machine Analysis

Directory of Open Access Journals (Sweden)

E. Ilhan

2012-10-01

Full Text Available Induction and synchronous machines have traditionally been the first choice of automotive manufacturers for electric/hybrid vehicles. However, these conventional machines are not able anymore to meet the increasing demands for a higher energy density due to space limitation in cars. Flux-switching PM (FSPM machines with their high energy density are very suitable to answer this demand. In this paper, the energy conversion loop technique is implemented on FSPM for the first time. The energy conversion technique is a powerful tool for the visualization of machine characteristics, both linear and nonlinear. Further, the technique provides insight into the torque production mechanism. A stepwise explanation is given on how to create these loops for FSPM along with the machine operation.

Machine Learning for Flapping Wing Flight Control

NARCIS (Netherlands)

Goedhart, Menno; van Kampen, E.; Armanini, S.F.; de Visser, C.C.; Chu, Q.

2018-01-01

Flight control of Flapping Wing Micro Air Vehicles is challenging, because of their complex dynamics and variability due to manufacturing inconsistencies. Machine Learning algorithms can be used to tackle these challenges. A Policy Gradient algorithm is used to tune the gains of a

Effects of pole flux distribution in a homopolar linear synchronous machine

Science.gov (United States)

Balchin, M. J.; Eastham, J. F.; Coles, P. C.

1994-05-01

Linear forms of synchronous electrical machine are at present being considered as the propulsion means in high-speed, magnetically levitated (Maglev) ground transportation systems. A homopolar form of machine is considered in which the primary member, which carries both ac and dc windings, is supported on the vehicle. Test results and theoretical predictions are presented for a design of machine intended for driving a 100 passenger vehicle at a top speed of 400 km/h. The layout of the dc magnetic circuit is examined to locate the best position for the dc winding from the point of view of minimum core weight. Measurements of flux build-up under the machine at different operating speeds are given for two types of secondary pole: solid and laminated. The solid pole results, which are confirmed theoretically, show that this form of construction is impractical for high-speed drives. Measured motoring characteristics are presented for a short length of machine which simulates conditions at the leading and trailing ends of the full-sized machine. Combination of the results with those from a cylindrical version of the machine make it possible to infer the performance of the full-sized traction machine. This gives 0.8 pf and 0.9 efficiency at 300 km/h, which is much better than the reported performance of a comparable linear induction motor (0.52 pf and 0.82 efficiency). It is therefore concluded that in any projected high-speed Maglev systems, a linear synchronous machine should be the first choice as the propulsion means.

49 CFR 565.14 - Motor vehicles imported into the United States.

Science.gov (United States)

2010-10-01

... 49 Transportation 6 2010-10-01 2010-10-01 false Motor vehicles imported into the United States...) REQUIREMENTS VIN Requirements § 565.14 Motor vehicles imported into the United States. (a) Importers shall utilize the VIN assigned by the original manufacturer of the motor vehicle. (b) All passenger cars...

Vehicle routing with dynamic travel times : a queueing approach

NARCIS (Netherlands)

Woensel, van T.; Kerbache, L.; Peremans, H.; Vandaele, N.J.

2008-01-01

Transportation is an important component of supply chain competitiveness since it plays a major role in the inbound, inter-facility, and outbound logistics. In this context, assigning and scheduling vehicle routes is a crucial management problem. In this paper, a vehicle routing problem with dynamic

Flexible Soldier and Machine Interface for Micro Air Vehicles

National Research Council Canada - National Science Library

Costello, Mark; Beyer, Eric

2006-01-01

...) was to provide basic connectivity to the air vehicle sensor suite. This includes the ability to send and receive control parameters, servo calibration parameters, sensor calibration parameters, and mission waypoints...

Encoding Featherweight Java with Assignment and Immutability using The Coq Proof Assistant

DEFF Research Database (Denmark)

Mackay, Julian; Mehnert, Hannes; Potanin, Alex

2012-01-01

We develop a mechanized proof of Featherweight Java with Assignment and Immutability in the Coq proof assistant. This is a step towards more machine-checked proofs of a non-trivial type system. We used object immutability close to that of IGJ [9] . We describe the challenges of the mech- anisation...

Evaluation of machinability and flexural strength of a novel dental machinable glass-ceramic.

Science.gov (United States)

Qin, Feng; Zheng, Shucan; Luo, Zufeng; Li, Yong; Guo, Ling; Zhao, Yunfeng; Fu, Qiang

2009-10-01

To evaluate the machinability and flexural strength of a novel dental machinable glass-ceramic (named PMC), and to compare the machinability property with that of Vita Mark II and human enamel. The raw batch materials were selected and mixed. Four groups of novel glass-ceramics were formed at different nucleation temperatures, and were assigned to Group 1, Group 2, Group 3 and Group 4. The machinability of the four groups of novel glass-ceramics, Vita Mark II ceramic and freshly extracted human premolars were compared by means of drilling depth measurement. A three-point bending test was used to measure the flexural strength of the novel glass-ceramics. The crystalline phases of the group with the best machinability were identified by X-ray diffraction. In terms of the drilling depth, Group 2 of the novel glass-ceramics proves to have the largest drilling depth. There was no statistical difference among Group 1, Group 4 and the natural teeth. The drilling depth of Vita MK II was statistically less than that of Group 1, Group 4 and the natural teeth. Group 3 had the least drilling depth. In respect of the flexural strength, Group 2 exhibited the maximum flexural strength; Group 1 was statistically weaker than Group 2; there was no statistical difference between Group 3 and Group 4, and they were the weakest materials. XRD of Group 2 ceramic showed that a new type of dental machinable glass-ceramic containing calcium-mica had been developed by the present study and was named PMC. PMC is promising for application as a dental machinable ceramic due to its good machinability and relatively high strength.

Non-cable vehicle guidance

Energy Technology Data Exchange (ETDEWEB)

Daugela, G.C.; Willott, A.M.; Chopiuk, R.G.; Thornton, S.E.

1988-06-01

The purpose is to determine the most promising driverless mine vehicle guidance systems that are not dependent on buried cables, and to plan their development. The project is presented in two phases: a preliminary study and literature review to determine whether suitable technologies exist to justify further work; and an in-depth assessment and selection of technologies for vehicle guidance. A large number of guidance elements are involved in a completely automated vehicle. The technologies that hold the best potential for development of guidance systems for mine vehicles are ultrasonics, radar, lasers, dead reckoning, and guidance algorithms. The best approach to adaptation of these technologies is on a step by step basis. Guidance modules that are complete in themselves and are designed to be integrated with other modules can provide short term benefits. Two modules are selected for development: the dragline operations monitor and automated machine control for optimized mining (AMCOM). 99 refs., 20 figs., 40 tabs.

Design Analysis of a Dual Rotor Permanent Magnet Machine driven Electric Vehicle

Directory of Open Access Journals (Sweden)

Izzat Bin Zainuddin Mohd

2018-01-01

Full Text Available Electric bike in urban countries such as Europe and China commonly used the brushless direct current machine (BLDC as it able to produce high torque to transport the user from one place to another. However, BLDC torque density can’t be improving due to limitation magnetic flux generated by the permanent magnet. Therefore, the performance of electric bike can’t be improved. Outer rotor BLDC machine design able to improve the torque density of the motor due to increase radius of the motor which can be explained by simple physics equation (Torque = Force x radius. However, an outer rotor machine only generates constant speed, which is not suitable for operating under tractive load condition, especially electric bike. The proposed model is a new novel of double layer outer rotor BLDCPM machine which able to amplify the magnetic flux density and improve the torque density of the machine. The mutual magnetic coupling between the inner and outer rotor of the proposed model increase the magnetic flux intensity as both of them acts as individual parts. Thus, the magnetic flux generated by both rotors are double which resulted in improving the performance of the E-bike. Designing parameters and analysing the performance of the proposed 2D model is done using FEA tools. Evaluation of the conventional and proposed model by comparing torque performance, magnetic flux density and motor constant square density. Other than that, speed torque graph also is evaluated to justify either it can operate similarly to ICE engine with gears. Two model is designed which is Single Outer Rotor Brushless Direct Current (SORBLDC and Double Outer Rotor Brushless Direct Current (DORBLDC operated with the same cases of 27 Amp current supplied to it and operate under various speed from 500 rpm to 2000 rpm. The average torque produce by the conventional and proposed model are 2.045439 Nm and 3.102648 Nm. Furthermore, improvement of the proposed model to conventional model in

Combined simulation of energy and thermal management for an electric vehicle

Energy Technology Data Exchange (ETDEWEB)

Mohrmann, Bjoern; Jeck, Peter [Institut fuer Kraftfahrzeuge Aachen (Germany); Simon, Carsten [fortiss GmbH, Muenchen (Germany); Ungermann, Jochen [Audi AG, Ingolstadt (Germany)

2012-11-01

The project eperformance, which is funded by the BMBF, is conducted by project partners from RWTH Aachen, Audi, Bosch Engineering and fortiss GmbH, in order to demonstrate the concept of an electric vehicle on the basis of a holistic development approach. To support this, several simulation platforms come into use, i.e. CFD Simulation for cooling concepts, electromagnetic simulations for electric machine design, physical simulation of cooling circuits as well as vehicle mechanics and controller design. To develop an energy efficient vehicle management, some of these simulation domains have to be combined, to simulate interdependencies between for example usage of high-voltage batteries, their thermal response and the impact for controller strategies. Within the project it was decided to use the Tool TISC (TLK Inter Software Connector) to combine as well a physical model, based on Modelica/Dymola to simulate thermal behaviours of components with a longitudinal vehicle model and a controller model, both based in MATLAB/Simulink. Advantages of such a coupled simulation are the re-usability of existing models in both tools with their tool-specific benefits as well as the possibility to cluster the models on different computers. The article will explain how the combined simulation is set up and parameterized, and will show two use cases: the thermal management of the two independent battery systems of the demonstrator vehicle and the torque distribution on the three electric machines in the vehicle, depending on the drive situation and the thermal state of the machines. (orig)

Optimization of line configuration and balancing for flexible machining lines

Science.gov (United States)

Liu, Xuemei; Li, Aiping; Chen, Zurui

2016-05-01

Line configuration and balancing is to select the type of line and allot a given set of operations as well as machines to a sequence of workstations to realize high-efficiency production. Most of the current researches for machining line configuration and balancing problems are related to dedicated transfer lines with dedicated machine workstations. With growing trends towards great product variety and fluctuations in market demand, dedicated transfer lines are being replaced with flexible machining line composed of identical CNC machines. This paper deals with the line configuration and balancing problem for flexible machining lines. The objective is to assign operations to workstations and find the sequence of execution, specify the number of machines in each workstation while minimizing the line cycle time and total number of machines. This problem is subject to precedence, clustering, accessibility and capacity constraints among the features, operations, setups and workstations. The mathematical model and heuristic algorithm based on feature group strategy and polychromatic sets theory are presented to find an optimal solution. The feature group strategy and polychromatic sets theory are used to establish constraint model. A heuristic operations sequencing and assignment algorithm is given. An industrial case study is carried out, and multiple optimal solutions in different line configurations are obtained. The case studying results show that the solutions with shorter cycle time and higher line balancing rate demonstrate the feasibility and effectiveness of the proposed algorithm. This research proposes a heuristic line configuration and balancing algorithm based on feature group strategy and polychromatic sets theory which is able to provide better solutions while achieving an improvement in computing time.

Joint optimization of production scheduling and machine group preventive maintenance

International Nuclear Information System (INIS)

Xiao, Lei; Song, Sanling; Chen, Xiaohui; Coit, David W.

2016-01-01

Joint optimization models were developed combining group preventive maintenance of a series system and production scheduling. In this paper, we propose a joint optimization model to minimize the total cost including production cost, preventive maintenance cost, minimal repair cost for unexpected failures and tardiness cost. The total cost depends on both the production process and the machine maintenance plan associated with reliability. For the problems addressed in this research, any machine unavailability leads to system downtime. Therefore, it is important to optimize the preventive maintenance of machines because their performance impacts the collective production processing associated with all machines. Too lengthy preventive maintenance intervals may be associated with low scheduled machine maintenance cost, but may incur expensive costs for unplanned failure due to low machine reliability. Alternatively, too frequent preventive maintenance activities may achieve the desired high reliability machines, but unacceptably high scheduled maintenance cost. Additionally, product scheduling plans affect tardiness and maintenance cost. Two results are obtained when solving the problem; the optimal group preventive maintenance interval for machines, and the assignment of each job, including the corresponding start time and completion time. To solve this non-deterministic polynomial-time problem, random keys genetic algorithms are used, and a numerical example is solved to illustrate the proposed model. - Highlights: • Group preventive maintenance (PM) planning and production scheduling are jointed. • Maintenance interval and assignment of jobs are decided by minimizing total cost. • Relationships among system age, PM, job processing time are quantified. • Random keys genetic algorithms (GA) are used to solve the NP-hard problem. • Random keys GA and Particle Swarm Optimization (PSO) are compared.

Automation and traction control of articulated vehicles

OpenAIRE

Andersson, Ulf

2013-01-01

Articulated machines such as load-haul-dump machines, wheel loaders and haulers operate in many different environments and driving conditions. In particular they need to be able to perform well with road conditions and loads that can change drastically, setting hard requirements on performances and robustness. The control challenges for off-road vehicles are hence quite different from standard cars or trucks, which mostly drive on regular roads. An important aspect characterising this is the ...

Regulatory adaptation: Accommodating electric vehicles in a petroleum world

International Nuclear Information System (INIS)

Lutsey, Nicholas; Sperling, Daniel

2012-01-01

This paper addresses the policy challenges of adjusting established regulations to accommodate evolving and new technologies. We examine energy and emissions regulations for older petroleum powered vehicles and newer plug-in electric vehicles. Until now, vehicle regulations across the world have ignored energy consumption and emissions upstream of the vehicle (at refineries, pipelines, etc), largely because of the convenient fact that upstream emissions and energy use are nearly uniform across petroleum-fueled vehicles and play a relatively minor role in total lifecycle emissions. Including upstream impacts would greatly complicate the regulations. But because the vast majority of emissions and energy consumption for electric vehicles (and hydrogen and, to a lesser extent, biofuels) are upstream, the old regulatory design is no longer valid. The pressing regulatory question is whether to assign upstream GHG emissions to electric vehicles, or not, and if so, how. We find that assigning zero upstream emissions—as a way of incentivizing the production and sale of PEVs—would eventually lead to an erosion of 20% of the GHG emission benefits from new vehicles, assuming fixed vehicle standards. We suggest alternative policy mechanisms and strategies to account for upstream emissions and energy use. - Highlights: ► We quantify the effects of electric vehicles within greenhouse gas (GHG) regulation. ► Electric vehicle GHG impacts are substantial and vary greatly by grid power sources. ► Existing “zero emission” electric vehicle incentives undermine regulation benefits. ► 10% electric vehicle sales leads to 20% erosion in regulation benefits by 2020–2025. ► Lifecycle crediting improves policy cost-effectiveness and technology neutrality.

Rotating electrical machines part 2 : methods for determining losses and efficiency of rotating electrical machinery form tests (excl. machines for traction vehicles)

CERN Document Server

International Electrotechnical Commission. Geneva

1972-01-01

Applies to d.c. machines and to a.c. synchronous and induction machines. The principles can be applied to other types of machines such as rotary converters, a.c. commutator motors and single-phase induction motors for which other methods of determining losses are used.

Implementation of an agile maintenance mechanic assignment methodology

Science.gov (United States)

Jimenez, Jesus A.; Quintana, Rolando

2000-10-01

The objective of this research was to develop a decision support system (DSS) to study the impact of introducing new equipment into a medical apparel plant from a maintenance organizational structure perspective. This system will enable the company to determine if their capacity is sufficient to meet current maintenance challenges. The DSS contains two database sets that describe equipment and maintenance resource profiles. The equipment profile specifies data such as mean time to failures, mean time to repairs, and minimum mechanic skill level required to fix each machine group. Similarly, maintenance-resource profile reports information about the mechanic staff, such as number and type of certifications received, education level, and experience. The DSS will then use this information to minimize machine downtime by assigning the highest skilled mechanics to machines with higher complexity and product value. A modified version of the simplex method, the transportation problem, was used to perform the optimization. The DSS was built using the Visual Basic for Applications (VBA) language contained in the Microsoft Excel environment. A case study was developed from current existing data. The analysis consisted of forty-two machine groups and six mechanic categories with ten skill levels. Results showed that only 56% of the mechanic workforce was utilized. Thus, the company had available resources for meeting future maintenance requirements.

Implications of Structured Programming for Machine Architecture

NARCIS (Netherlands)

Tanenbaum, A.S.

1978-01-01

Based on an empirical study of more than 10,000 lines of program text written in a GOTO-less language, a machine architecture specifically designed for structured programs is proposed. Since assignment, CALL, RETURN, and IF statements together account for 93 percent of all executable statements,

Changes in motivational and higher level cognitive processes when interacting with in-vehicle automation

OpenAIRE

Beggiato, Matthias

2014-01-01

Many functions that at one time could only be performed by humans can nowadays be carried out by machines. Automation impacts many areas of life including work, home, communication and mobility. In the driving context, in-vehicle automation is considered to provide solutions for environmental, economic, safety and societal challenges. However, automation changes the driving task and the human-machine interaction. Thus, the expected benefit of in-vehicle automation can be undermined by changes...

Changes in motivational and higher level cognitive processes when interacting with in-vehicle automation

OpenAIRE

Beggiato, Matthias

2015-01-01

Many functions that at one time could only be performed by humans can nowadays be carried out by machines. Automation impacts many areas of life including work, home, communication and mobility. In the driving context, in-vehicle automation is considered to provide solutions for environmental, economic, safety and societal challenges. However, automation changes the driving task and the human-machine interaction. Thus, the expected benefit of in-vehicle automation can be undermined by changes...

Design of salient pole PM synchronous machines for a vehicle traction application. Analysis and implementation

Energy Technology Data Exchange (ETDEWEB)

Rilla, M.

2012-07-01

This doctoral thesis presents a study on the development of a liquid-cooled frame salient pole permanent-magnet-exited traction machine for a four-wheel-driven electric car. The emphasis of the thesis is put on a radial flux machine design in order to achieve a light-weight machine structure for traction applications. The design features combine electromagnetic and thermal design methods, because traction machine operation does not have a strict operating point. Arbitrary load cycles and the flexible supply require special attention in the design process. It is shown that accurate modelling of the machine magnetic state is essential for high-performance operation. The saturation effect related to the cross-saturation has to be taken carefully into account in order to achieve the desired operation. Two prototype machines have been designed and built for testing: one totally enclosed machine with a special magnet module pole arrangement and another through-ventilated machine with a more traditional embedded magnet structure. Both structures are built with magnetically salient structures in order to increase the torque production capability with the reluctance torque component. Both machine structures show potential for traction usage. However, the traditional embedded magnet design turns out to be mechanically the more secure one of these two machine options. (orig.)

The image in the machine: portraiture and the typewriter

OpenAIRE

Tullett, Barrie

2016-01-01

Typewriters have been a vehicle for creative image making ever since their invention. Work produced on the machines covers a huge range of themes and styles, including the portrait. Theme: The Form of the Image

Electric Vehicle Preparedness - Implementation Approach for Electric Vehicles at Naval Air Station Whidbey Island. Task 4

Energy Technology Data Exchange (ETDEWEB)

Schey, Stephen [Idaho National Lab. (INL), Idaho Falls, ID (United States); Francfort, Jim [Idaho National Lab. (INL), Idaho Falls, ID (United States)

2015-06-01

Several U.S. Department of Defense base studies have been conducted to identify potential U.S. Department of Defense transportation systems that are strong candidates for introduction or expansion of plug-in electric vehicles (PEVs). This study is focused on the Naval Air Station Whidbey Island (NASWI) located in Washington State. Task 1 consisted of a survey of the non-tactical fleet of vehicles at NASWI to begin the review of vehicle mission assignments and types of vehicles in service. In Task 2, daily operational characteristics of vehicles were identified to select vehicles for further monitoring and attachment of data loggers. Task 3 recorded vehicle movements in order to characterize the vehicles’ missions. The results of the data analysis and observations were provided. Individual observations of the selected vehicles provided the basis for recommendations related to PEV adoption, i.e., whether a battery electric vehicle (BEV) or plug-in hybrid electric vehicle (PHEV) (collectively PEVs) can fulfill the mission requirements. It also provided the basis for recommendations related to placement of PEV charging infrastructure. This report focuses on an implementation plan for the near-term adoption of PEVs into the NASWI fleet.

Genetic programming for evolving due-date assignment models in job shop environments.

Science.gov (United States)

Nguyen, Su; Zhang, Mengjie; Johnston, Mark; Tan, Kay Chen

2014-01-01

Due-date assignment plays an important role in scheduling systems and strongly influences the delivery performance of job shops. Because of the stochastic and dynamic nature of job shops, the development of general due-date assignment models (DDAMs) is complicated. In this study, two genetic programming (GP) methods are proposed to evolve DDAMs for job shop environments. The experimental results show that the evolved DDAMs can make more accurate estimates than other existing dynamic DDAMs with promising reusability. In addition, the evolved operation-based DDAMs show better performance than the evolved DDAMs employing aggregate information of jobs and machines.

Mining protein function from text using term-based support vector machines

Science.gov (United States)

Rice, Simon B; Nenadic, Goran; Stapley, Benjamin J

2005-01-01

Background Text mining has spurred huge interest in the domain of biology. The goal of the BioCreAtIvE exercise was to evaluate the performance of current text mining systems. We participated in Task 2, which addressed assigning Gene Ontology terms to human proteins and selecting relevant evidence from full-text documents. We approached it as a modified form of the document classification task. We used a supervised machine-learning approach (based on support vector machines) to assign protein function and select passages that support the assignments. As classification features, we used a protein's co-occurring terms that were automatically extracted from documents. Results The results evaluated by curators were modest, and quite variable for different problems: in many cases we have relatively good assignment of GO terms to proteins, but the selected supporting text was typically non-relevant (precision spanning from 3% to 50%). The method appears to work best when a substantial set of relevant documents is obtained, while it works poorly on single documents and/or short passages. The initial results suggest that our approach can also mine annotations from text even when an explicit statement relating a protein to a GO term is absent. Conclusion A machine learning approach to mining protein function predictions from text can yield good performance only if sufficient training data is available, and significant amount of supporting data is used for prediction. The most promising results are for combined document retrieval and GO term assignment, which calls for the integration of methods developed in BioCreAtIvE Task 1 and Task 2. PMID:15960835

A Temporal Domain Decomposition Algorithmic Scheme for Large-Scale Dynamic Traffic Assignment

Directory of Open Access Journals (Sweden)

Eric J. Nava

2012-03-01

This paper presents a temporal decomposition scheme for large spatial- and temporal-scale dynamic traffic assignment, in which the entire analysis period is divided into Epochs. Vehicle assignment is performed sequentially in each Epoch, thus improving the model scalability and confining the peak run-time memory requirement regardless of the total analysis period. A proposed self-turning scheme adaptively searches for the run-time-optimal Epoch setting during iterations regardless of the characteristics of the modeled network. Extensive numerical experiments confirm the promising performance of the proposed algorithmic schemes.

49 CFR 214.509 - Required visual illumination and reflective devices for new on-track roadway maintenance machines.

Science.gov (United States)

2010-10-01

... devices for new on-track roadway maintenance machines. 214.509 Section 214.509 Transportation Other... TRANSPORTATION RAILROAD WORKPLACE SAFETY On-Track Roadway Maintenance Machines and Hi-Rail Vehicles § 214.509 Required visual illumination and reflective devices for new on-track roadway maintenance machines. Each new...

Intelligent Vehicle Power Management Using Machine Learning and Fuzzy Logic

National Research Council Canada - National Science Library

Chen, ZhiHang; Masrur, M. A; Murphey, Yi L

2008-01-01

.... A machine learning algorithm, LOPPS, has been developed to learn about optimal power source combinations with respect to minimum power loss for all possible load requests and various system power states...

Modelling and Simulation of Cooperative Control for Bus Rapid Transit Vehicle Platoon in a Connected Vehicle Environment

Directory of Open Access Journals (Sweden)

Jiahui Liu

2017-02-01

Full Text Available The aim of this paper is to develop a cooperative control model for improving the operational efficiency of Bus Rapid Transit (BRT vehicles. The model takes advantage of the emerging connected vehicle technology. A connected vehicle centre is established to assign a specific reservation time interval and transmit the corresponding dynamic speed guidance to each BRT vehicle. Furthermore, a set of constraints have been set up to avoid bus queuing and waiting phenomena in downstream BRT stations. Therefore, many BRT vehicles are strategically guided to form a platoon, which can pass through an intersection with no impedance. An actual signalized intersection along the Guangzhou BRT corridor is employed to verify and assess the cooperative control model in various traffic conditions. The simulation-based evaluation results demonstrate that the proposed approach can reduce delays, decrease the number of stops, and improve the sustainability of the BRT vehicles.

Dual rotor single- stator axial air gap PMSM motor/generator drive for high torque vehicles applications

Science.gov (United States)

Tutelea, L. N.; Deaconu, S. I.; Boldea, I.; Popa, G. N.

2014-03-01

The actual e - continuously variable transmission (e-CVT) solution for the parallel Hybrid Electric Vehicle (HEV) requires two electric machines, two inverters, and a planetary gear. A distinct electric generator and a propulsion electric motor, both with full power converters, are typical for a series HEV. In an effort to simplify the planetary-geared e-CVT for the parallel HEV or the series HEV we hereby propose to replace the basically two electric machines and their two power converters by a single, axial-air-gap, electric machine central stator, fed from a single PWM converter with dual frequency voltage output and two independent PM rotors, destined for hybrid electric vehicles (HEV) and military vehicles applications. The proposed topologies and the magneto-motive force analysis are the core of the paper.

Dual rotor single- stator axial air gap PMSM motor/generator drive for high torque vehicles applications

International Nuclear Information System (INIS)

University of Timisoara, Electrical Engineering Department, Vasile Parvan str., no. 1-2, 300223 Timisoara (Romania))" data-affiliation=" (Politehnica University of Timisoara, Electrical Engineering Department, Vasile Parvan str., no. 1-2, 300223 Timisoara (Romania))" >Tutelea, L N; University of Timisoara, Electrical Engineering Department, Vasile Parvan str., no. 1-2, 300223 Timisoara (Romania))" data-affiliation=" (Politehnica University of Timisoara, Electrical Engineering Department, Vasile Parvan str., no. 1-2, 300223 Timisoara (Romania))" >Boldea, I; University of Timisoara, Department of Electrotechnical Engineering and Industrial Informatics, 5 Revolution Street, Hunedoara, 331128 (Romania))" data-affiliation=" (Politehnica University of Timisoara, Department of Electrotechnical Engineering and Industrial Informatics, 5 Revolution Street, Hunedoara, 331128 (Romania))" >Deaconu, S I; University of Timisoara, Department of Electrotechnical Engineering and Industrial Informatics, 5 Revolution Street, Hunedoara, 331128 (Romania))" data-affiliation=" (Politehnica University of Timisoara, Department of Electrotechnical Engineering and Industrial Informatics, 5 Revolution Street, Hunedoara, 331128 (Romania))" >Popa, G N

2014-01-01

The actual e – continuously variable transmission (e-CVT) solution for the parallel Hybrid Electric Vehicle (HEV) requires two electric machines, two inverters, and a planetary gear. A distinct electric generator and a propulsion electric motor, both with full power converters, are typical for a series HEV. In an effort to simplify the planetary-geared e-CVT for the parallel HEV or the series HEV we hereby propose to replace the basically two electric machines and their two power converters by a single, axial-air-gap, electric machine central stator, fed from a single PWM converter with dual frequency voltage output and two independent PM rotors, destined for hybrid electric vehicles (HEV) and military vehicles applications. The proposed topologies and the magneto-motive force analysis are the core of the paper

Assembly processor program converts symbolic programming language to machine language

Science.gov (United States)

Pelto, E. V.

1967-01-01

Assembly processor program converts symbolic programming language to machine language. This program translates symbolic codes into computer understandable instructions, assigns locations in storage for successive instructions, and computer locations from symbolic addresses.

2016 IFToMM Asian Conference on Mechanism and Machine Science (IFToMM Asian MMS 2016) & 2016 International Conference on Mechanism and Machine Science (CCMMS 2016)

CERN Document Server

Wang, Nianfeng; Huang, Yanjiang

2017-01-01

These proceedings collect the latest research results in mechanism and machine science, intended to reinforce and improve the role of mechanical systems in a variety of applications in daily life and industry. Gathering more than 120 academic papers, it addresses topics including: Computational kinematics, Machine elements, Actuators, Gearing and transmissions, Linkages and cams, Mechanism design, Dynamics of machinery, Tribology, Vehicle mechanisms, dynamics and design, Reliability, Experimental methods in mechanisms, Robotics and mechatronics, Biomechanics, Micro/nano mechanisms and machines, Medical/welfare devices, Nature and machines, Design methodology, Reconfigurable mechanisms and reconfigurable manipulators, and Origami mechanisms. This is the fourth installment in the IFToMM Asian conference series on Mechanism and Machine Science (ASIAN MMS 2016). The ASIAN MMS conference initiative was launched to provide a forum mainly for the Asian community working in Mechanism and Machine Science, in order to ...

A heterogeneous fleet vehicle routing model for solving the LPG distribution problem: A case study

International Nuclear Information System (INIS)

Onut, S; Kamber, M R; Altay, G

2014-01-01

Vehicle Routing Problem (VRP) is an important management problem in the field of distribution and logistics. In VRPs, routes from a distribution point to geographically distributed points are designed with minimum cost and considering customer demands. All points should be visited only once and by one vehicle in one route. Total demand in one route should not exceed the capacity of the vehicle that assigned to that route. VRPs are varied due to real life constraints related to vehicle types, number of depots, transportation conditions and time periods, etc. Heterogeneous fleet vehicle routing problem is a kind of VRP that vehicles have different capacity and costs. There are two types of vehicles in our problem. In this study, it is used the real world data and obtained from a company that operates in LPG sector in Turkey. An optimization model is established for planning daily routes and assigned vehicles. The model is solved by GAMS and optimal solution is found in a reasonable time

A heterogeneous fleet vehicle routing model for solving the LPG distribution problem: A case study

Science.gov (United States)

Onut, S.; Kamber, M. R.; Altay, G.

2014-03-01

Vehicle Routing Problem (VRP) is an important management problem in the field of distribution and logistics. In VRPs, routes from a distribution point to geographically distributed points are designed with minimum cost and considering customer demands. All points should be visited only once and by one vehicle in one route. Total demand in one route should not exceed the capacity of the vehicle that assigned to that route. VRPs are varied due to real life constraints related to vehicle types, number of depots, transportation conditions and time periods, etc. Heterogeneous fleet vehicle routing problem is a kind of VRP that vehicles have different capacity and costs. There are two types of vehicles in our problem. In this study, it is used the real world data and obtained from a company that operates in LPG sector in Turkey. An optimization model is established for planning daily routes and assigned vehicles. The model is solved by GAMS and optimal solution is found in a reasonable time.

Intelligent Hybrid Vehicle Power Control - Part 1: Machine Learning of Optimal Vehicle Power

Science.gov (United States)

2012-06-30

the motor or both can provide the traction power to the drivetrain. During vehicle deceleration, the regenerative braking power is captured to charge...and Amax is the maximum acceleration. The 11 drive cycles are divided into four categories of roadway types and traffic congestion levels, freeway...freeway ramp, arterial, and local. Two of the categories , freeway and arterial, are further divided into subcategories based on a qualitative measure

Electric Motor-Generator for a Hybrid Electric Vehicle

OpenAIRE

Odvářka, Erik; Mebarki, Abdeslam; Gerada, David; Brown, Neil; Ondrůšek, Čestmír

2009-01-01

Several topologies of electrical machines can be used to meet requirements for application in a hybrid electric vehicle. This paper describes process of an electric motor-generator selection, considering electromagnetic, thermal and basic control design. The requested electrical machine must develop 45 kW in continuous operation at 1300 rpm with field weakening capability up to 2500 rpm. Both radial and axial flux topologies are considered as potential candidates. A family of axial flux machi...

Machine vision and mechatronics in practice

CERN Document Server

Brett, Peter

2015-01-01

The contributions for this book have been gathered over several years from conferences held in the series of Mechatronics and Machine Vision in Practice, the latest of which was held in Ankara, Turkey. The essential aspect is that they concern practical applications rather than the derivation of mere theory, though simulations and visualization are important components. The topics range from mining, with its heavy engineering, to the delicate machining of holes in the human skull or robots for surgery on human flesh. Mobile robots continue to be a hot topic, both from the need for navigation and for the task of stabilization of unmanned aerial vehicles. The swinging of a spray rig is damped, while machine vision is used for the control of heating in an asphalt-laying machine.  Manipulators are featured, both for general tasks and in the form of grasping fingers. A robot arm is proposed for adding to the mobility scooter of the elderly. Can EEG signals be a means to control a robot? Can face recognition be ac...

Effective Cost Mechanism for Cloudlet Retransmission and Prioritized VM Scheduling Mechanism over Broker Virtual Machine Communication Framework

OpenAIRE

Raj, Gaurav; Setia, Sonika

2012-01-01

In current scenario cloud computing is most widely increasing platform for task execution. Lot of research is going on to cut down the cost and execution time. In this paper, we propose an efficient algorithm to have an effective and fast execution of task assigned by the user. We proposed an effective communication framework between broker and virtual machine for assigning the task and fetching the results in optimum time and cost using Broker Virtual Machine Communication Framework (BVCF). ...

Mobility Systems For Robotic Vehicles

Science.gov (United States)

Chun, Wendell

1987-02-01

The majority of existing robotic systems can be decomposed into five distinct subsystems: locomotion, control/man-machine interface (MMI), sensors, power source, and manipulator. When designing robotic vehicles, there are two main requirements: first, to design for the environment and second, for the task. The environment can be correlated with known missions. This can be seen by analyzing existing mobile robots. Ground mobile systems are generally wheeled, tracked, or legged. More recently, underwater vehicles have gained greater attention. For example, Jason Jr. made history by surveying the sunken luxury liner, the Titanic. The next big surge of robotic vehicles will be in space. This will evolve as a result of NASA's commitment to the Space Station. The foreseeable robots will interface with current systems as well as standalone, free-flying systems. A space robotic vehicle is similar to its underwater counterpart with very few differences. Their commonality includes missions and degrees-of-freedom. The issues of stability and communication are inherent in both systems and environment.

Smart Bandwidth Assignation in an Underlay Cellular Network for Internet of Vehicles.

Science.gov (United States)

de la Iglesia, Idoia; Hernandez-Jayo, Unai; Osaba, Eneko; Carballedo, Roberto

2017-09-27

The evolution of the IoT (Internet of Things) paradigm applied to new scenarios as VANETs (Vehicular Ad Hoc Networks) has gained momentum in recent years. Both academia and industry have triggered advanced studies in the IoV (Internet of Vehicles), which is understood as an ecosystem where different types of users (vehicles, elements of the infrastructure, pedestrians) are connected. How to efficiently share the available radio resources among the different types of eligible users is one of the important issues to be addressed. This paper briefly analyzes various concepts presented hitherto in the literature and it proposes an enhanced algorithm for ensuring a robust co-existence of the aforementioned system users. Therefore, this paper introduces an underlay RRM (Radio Resource Management) methodology which is capable of (1) improving cellular spectral efficiency while making a minimal impact on cellular communications and (2) ensuring the different QoS (Quality of Service) requirements of ITS (Intelligent Transportation Systems) applications. Simulation results, where we compare the proposed algorithm to the other two RRM, show the promising spectral efficiency performance of the proposed RRM methodology.

Experimental analysis of electro-pneumatic optimization of hot stamping machine control systems with on-delay timer

OpenAIRE

Bankole I. Oladapo; Vincent A. Balogun; Adeyinka O.M. Adeoye; Ige E. Olubunmi; Samuel O. Afolabi

2017-01-01

The sustainability criterion in the manufacturing industries is imperative, especially in the automobile industries. Currently, efforts are being made by the industries to mitigate CO2 emission by the total vehicle weight optimization, machine utilization and resource efficiency. In lieu of this, it is important to understudy the manufacturing machines adopted in the automobile industries. One of such machine is the hot stamping machine that is used for about 35% of the manufacturing operatio...

Convective Heat Transfer Coefficients of Automatic Transmission Fluid Jets with Implications for Electric Machine Thermal Management: Preprint

Energy Technology Data Exchange (ETDEWEB)

Bennion, Kevin; Moreno, Gilberto

2015-09-29

Thermal management for electric machines (motors/ generators) is important as the automotive industry continues to transition to more electrically dominant vehicle propulsion systems. Cooling of the electric machine(s) in some electric vehicle traction drive applications is accomplished by impinging automatic transmission fluid (ATF) jets onto the machine's copper windings. In this study, we provide the results of experiments characterizing the thermal performance of ATF jets on surfaces representative of windings, using Ford's Mercon LV ATF. Experiments were carried out at various ATF temperatures and jet velocities to quantify the influence of these parameters on heat transfer coefficients. Fluid temperatures were varied from 50 degrees C to 90 degrees C to encompass potential operating temperatures within an automotive transaxle environment. The jet nozzle velocities were varied from 0.5 to 10 m/s. The experimental ATF heat transfer coefficient results provided in this report are a useful resource for understanding factors that influence the performance of ATF-based cooling systems for electric machines.

ASCERTAINMENT OF THE EQUIVALENT CIRCUIT PARAMETERS OF THE ASYNCHRONOUS MACHINE

Directory of Open Access Journals (Sweden)

V. S. Safaryan

2015-01-01

Full Text Available The article considers experimental and analytical determination of the asynchronous machine equivalent-circuit parameters with application of the reference data. Transient processes investigation of the asynchronous machines necessitates the equivalent circuit parameters (resistance impedance, inductances and coefficient of the stator-rotor contours mutual inductance that help form the transitory-process mathematical simulation model. The reference books do not provide those parameters; they instead give the rated ones (active power, voltage, slide, coefficient of performance and capacity coefficient as well as the ratio of starting and nominal currents and torques. The noted studies on the asynchronous machine equivalent-circuits parametrization fail to solve the problems ad finem or solve them with admissions. The paper presents experimental and analytical determinations of the asynchronous machine equivalent-circuit parameters: the experimental one based on the results of two measurements and the analytical one where the problem boils down to solving a system of nonlineal algebraic equations. The authors investigate the equivalent asynchronous machine input-resistance properties and adduce the dependence curvatures of the input-resistances on the slide. They present a symbolic model for analytical parameterization of the asynchronous machine equivalent-circuit that represents a system of nonlineal equations and requires one of the rotor-parameters arbitrary assignment. The article demonstrates that for the asynchronous machine equivalent-circuit experimental parameterization the measures are to be conducted of the stator-circuit voltage, current and active power with two different slides and arbitrary assignment of one of the rotor parameters. The paper substantiates the fact that additional measurement does not discard the rotor-parameter choice arbitrariness. The authors establish that in motoring mode there is a critical slide by which the

Peak thrust operation of linear induction machines from parameter identification

Energy Technology Data Exchange (ETDEWEB)

Zhang, Z.; Eastham, T.R.; Dawson, G.E. [Queen`s Univ., Kingston, Ontario (Canada). Dept. of Electrical and Computer Engineering

1995-12-31

Various control strategies are being used to achieve high performance operation of linear drives. To maintain minimum volume and weight of the power supply unit on board the transportation vehicle, peak thrust per unit current operation is a desirable objective. True peak thrust per unit current through slip control is difficult to achieve because the parameters of linear induction machines vary during normal operation. This paper first develops a peak thrust per unit current control law based on the per-phase equivalent circuit for linear induction machines. The algorithm for identification of the variable parameters in induction machines is then presented. Application to an operational linear induction machine (LIM) demonstrates the utility of this algorithm. The control strategy is then simulated, based on an operational transit LIM, to show the capability of achieving true peak thrust operation for linear induction machines.

Brain Machine Interfaces for Robotic Control in Space Applications, Phase I

Data.gov (United States)

National Aeronautics and Space Administration — This SBIR will study the application of a brain machine interface (BMI) to enable crew to remotely operate and monitor robots from inside a flight vehicle, habitat...

Virtual Machine Language Controls Remote Devices

Science.gov (United States)

2014-01-01

Kennedy Space Center worked with Blue Sun Enterprises, based in Boulder, Colorado, to enhance the company's virtual machine language (VML) to control the instruments on the Regolith and Environment Science and Oxygen and Lunar Volatiles Extraction mission. Now the NASA-improved VML is available for crewed and uncrewed spacecraft, and has potential applications on remote systems such as weather balloons, unmanned aerial vehicles, and submarines.

Digital Signal Processing for In-Vehicle Systems and Safety

CERN Document Server

Boyraz, Pinar; Takeda, Kazuya; Abut, Hüseyin

2012-01-01

Compiled from papers of the 4th Biennial Workshop on DSP (Digital Signal Processing) for In-Vehicle Systems and Safety this edited collection features world-class experts from diverse fields focusing on integrating smart in-vehicle systems with human factors to enhance safety in automobiles. Digital Signal Processing for In-Vehicle Systems and Safety presents new approaches on how to reduce driver inattention and prevent road accidents. The material addresses DSP technologies in adaptive automobiles, in-vehicle dialogue systems, human machine interfaces, video and audio processing, and in-vehicle speech systems. The volume also features: Recent advances in Smart-Car technology – vehicles that take into account and conform to the driver Driver-vehicle interfaces that take into account the driving task and cognitive load of the driver Best practices for In-Vehicle Corpus Development and distribution Information on multi-sensor analysis and fusion techniques for robust driver monitoring and driver recognition ...

Smart Bandwidth Assignation in an Underlay Cellular Network for Internet of Vehicles

Directory of Open Access Journals (Sweden)

Idoia de la Iglesia

2017-09-01

Full Text Available The evolution of the IoT (Internet of Things paradigm applied to new scenarios as VANETs (Vehicular Ad Hoc Networks has gained momentum in recent years. Both academia and industry have triggered advanced studies in the IoV (Internet of Vehicles, which is understood as an ecosystem where different types of users (vehicles, elements of the infrastructure, pedestrians are connected. How to efficiently share the available radio resources among the different types of eligible users is one of the important issues to be addressed. This paper briefly analyzes various concepts presented hitherto in the literature and it proposes an enhanced algorithm for ensuring a robust co-existence of the aforementioned system users. Therefore, this paper introduces an underlay RRM (Radio Resource Management methodology which is capable of (1 improving cellular spectral efficiency while making a minimal impact on cellular communications and (2 ensuring the different QoS (Quality of Service requirements of ITS (Intelligent Transportation Systems applications. Simulation results, where we compare the proposed algorithm to the other two RRM, show the promising spectral efficiency performance of the proposed RRM methodology.

Earth – Mars Similarity Criteria for Martian Vehicles

Directory of Open Access Journals (Sweden)

Octavian TRIFU

2010-09-01

Full Text Available In order to select the most efficient kind of a martian exploring vehicle, the similarity criteria are deduced from the equilibrium movement in the terrestrial and martian conditions. Different invariants have been obtained for the existing (entry capsules, parachutes and rovers and potential martian exploring vehicles (lighter-than-air vehicle, airplane, helicopter and Mars Jumper. These similarity criteria, as non dimensional numbers, allow to quickly compare if such a kind of vehicles can operate in the martian environment, the movement performances, the necessary geometrical dimensions and the power consumption. Following this way of study it was concluded what vehicle is most suitable for the near soil Mars exploration. “Mars Rover” has less power consumption on Mars, but due to the rugged terrain the performances are weak. A vacuumed rigid airship is possible to fly with high performances and endurance on Mars, versus the impossibility of such a machine on the Earth. Due to very low density and the low Reynolds numbers in the Mars atmosphere, the power consumption for the martian airplane or helicopter, is substantial higher. The most efficient vehicle for the Mars exploration it seems to be a machine using the in-situ non-chemical propellants: the 95% CO2 atmosphere and the weak solar radiation. A small compressor, electrically driven by photovoltaics, compresses the gas in a storage tank, in time. If the gas is expanded through a nozzle, sufficient lift and control forces are obtained for a VTOL flight of kilometers over the martian soil, in comparison with tens of meters of the actual Mars rovers.

Electric vehicle traction motors - The development of an advanced motor concept

Science.gov (United States)

Campbell, P.

1980-01-01

An axial-field permanent magnet traction motor is described, similar to several advanced motors that are being developed in the United States. This type of machine has several advantages over conventional dc motors, particularly in the electric vehicle application. The rapidly changing cost of magnetic materials, particularly cobalt, makes it important to study the utilization of permanent magnet materials in such machines. The impact of different magnets on machine design is evaluated, and the advantages of using iron powder composites in the armature are assessed.

Decentralized real-time simulation of forest machines

Science.gov (United States)

Freund, Eckhard; Adam, Frank; Hoffmann, Katharina; Rossmann, Juergen; Kraemer, Michael; Schluse, Michael

2000-10-01

To develop realistic forest machine simulators is a demanding task. A useful simulator has to provide a close- to-reality simulation of the forest environment as well as the simulation of the physics of the vehicle. Customers demand a highly realistic three dimensional forestry landscape and the realistic simulation of the complex motion of the vehicle even in rough terrain in order to be able to use the simulator for operator training under close-to- reality conditions. The realistic simulation of the vehicle, especially with the driver's seat mounted on a motion platform, greatly improves the effect of immersion into the virtual reality of a simulated forest and the achievable level of education of the driver. Thus, the connection of the real control devices of forest machines to the simulation system has to be supported, i.e. the real control devices like the joysticks or the board computer system to control the crane, the aggregate etc. Beyond, the fusion of the board computer system and the simulation system is realized by means of sensors, i.e. digital and analog signals. The decentralized system structure allows several virtual reality systems to evaluate and visualize the information of the control devices and the sensors. So, while the driver is practicing, the instructor can immerse into the same virtual forest to monitor the session from his own viewpoint. In this paper, we are describing the realized structure as well as the necessary software and hardware components and application experiences.

On the Determinations of Class-Based Storage Assignments in AS/RS having two I/O Locations

NARCIS (Netherlands)

Ashayeri, J.; Heuts, R.M.J.; Beekhof, M.; Wilhelm, M.R.

2001-01-01

This paper presents the use and extension of a geometrical-based algorithmic approach for determining the expected S/R machine cycle times, and therefore warehouse throughput, for class-based storage assignment layouts in an AS/RS.The approach was designed for the purpose of solving a practical

IMU-to-Segment Assignment and Orientation Alignment for the Lower Body Using Deep Learning.

Science.gov (United States)

Zimmermann, Tobias; Taetz, Bertram; Bleser, Gabriele

2018-01-19

Human body motion analysis based on wearable inertial measurement units (IMUs) receives a lot of attention from both the research community and the and industrial community. This is due to the significant role in, for instance, mobile health systems, sports and human computer interaction. In sensor based activity recognition, one of the major issues for obtaining reliable results is the sensor placement/assignment on the body. For inertial motion capture (joint kinematics estimation) and analysis, the IMU-to-segment (I2S) assignment and alignment are central issues to obtain biomechanical joint angles. Existing approaches for I2S assignment usually rely on hand crafted features and shallow classification approaches (e.g., support vector machines), with no agreement regarding the most suitable features for the assignment task. Moreover, estimating the complete orientation alignment of an IMU relative to the segment it is attached to using a machine learning approach has not been shown in literature so far. This is likely due to the high amount of training data that have to be recorded to suitably represent possible IMU alignment variations. In this work, we propose online approaches for solving the assignment and alignment tasks for an arbitrary amount of IMUs with respect to a biomechanical lower body model using a deep learning architecture and windows of 128 gyroscope and accelerometer data samples. For this, we combine convolutional neural networks (CNNs) for local filter learning with long-short-term memory (LSTM) recurrent networks as well as generalized recurrent units (GRUs) for learning time dynamic features. The assignment task is casted as a classification problem, while the alignment task is casted as a regression problem. In this framework, we demonstrate the feasibility of augmenting a limited amount of real IMU training data with simulated alignment variations and IMU data for improving the recognition/estimation accuracies. With the proposed

IMU-to-Segment Assignment and Orientation Alignment for the Lower Body Using Deep Learning

Directory of Open Access Journals (Sweden)

Tobias Zimmermann

2018-01-01

Full Text Available Human body motion analysis based on wearable inertial measurement units (IMUs receives a lot of attention from both the research community and the and industrial community. This is due to the significant role in, for instance, mobile health systems, sports and human computer interaction. In sensor based activity recognition, one of the major issues for obtaining reliable results is the sensor placement/assignment on the body. For inertial motion capture (joint kinematics estimation and analysis, the IMU-to-segment (I2S assignment and alignment are central issues to obtain biomechanical joint angles. Existing approaches for I2S assignment usually rely on hand crafted features and shallow classification approaches (e.g., support vector machines, with no agreement regarding the most suitable features for the assignment task. Moreover, estimating the complete orientation alignment of an IMU relative to the segment it is attached to using a machine learning approach has not been shown in literature so far. This is likely due to the high amount of training data that have to be recorded to suitably represent possible IMU alignment variations. In this work, we propose online approaches for solving the assignment and alignment tasks for an arbitrary amount of IMUs with respect to a biomechanical lower body model using a deep learning architecture and windows of 128 gyroscope and accelerometer data samples. For this, we combine convolutional neural networks (CNNs for local filter learning with long-short-term memory (LSTM recurrent networks as well as generalized recurrent units (GRUs for learning time dynamic features. The assignment task is casted as a classification problem, while the alignment task is casted as a regression problem. In this framework, we demonstrate the feasibility of augmenting a limited amount of real IMU training data with simulated alignment variations and IMU data for improving the recognition/estimation accuracies. With the

Loft: An Automated Mesh Generator for Stiffened Shell Aerospace Vehicles

Science.gov (United States)

Eldred, Lloyd B.

2011-01-01

Loft is an automated mesh generation code that is designed for aerospace vehicle structures. From user input, Loft generates meshes for wings, noses, tanks, fuselage sections, thrust structures, and so on. As a mesh is generated, each element is assigned properties to mark the part of the vehicle with which it is associated. This property assignment is an extremely powerful feature that enables detailed analysis tasks, such as load application and structural sizing. This report is presented in two parts. The first part is an overview of the code and its applications. The modeling approach that was used to create the finite element meshes is described. Several applications of the code are demonstrated, including a Next Generation Launch Technology (NGLT) wing-sizing study, a lunar lander stage study, a launch vehicle shroud shape study, and a two-stage-to-orbit (TSTO) orbiter. Part two of the report is the program user manual. The manual includes in-depth tutorials and a complete command reference.

Evaluation of man-machine systems - methods and problems

International Nuclear Information System (INIS)

1985-01-01

The symposium gives a survey of the methods of evaluation which permit as quantitive an assessment as possible of the collaboration between men and machines. This complex of problems is of great current significance in many areas of application. The systems to be evaluated are aircraft, land vehicles and watercraft as well as process control systems. (orig./GL) [de

Image Classification, Deep Learning and Convolutional Neural Networks : A Comparative Study of Machine Learning Frameworks

OpenAIRE

Airola, Rasmus; Hager, Kristoffer

2017-01-01

The use of machine learning and specifically neural networks is a growing trend in software development, and has grown immensely in the last couple of years in the light of an increasing need to handle big data and large information flows. Machine learning has a broad area of application, such as human-computer interaction, predicting stock prices, real-time translation, and self driving vehicles. Large companies such as Microsoft and Google have already implemented machine learning in some o...

Machine vision theory, algorithms, practicalities

CERN Document Server

Davies, E R

2005-01-01

In the last 40 years, machine vision has evolved into a mature field embracing a wide range of applications including surveillance, automated inspection, robot assembly, vehicle guidance, traffic monitoring and control, signature verification, biometric measurement, and analysis of remotely sensed images. While researchers and industry specialists continue to document their work in this area, it has become increasingly difficult for professionals and graduate students to understand the essential theory and practicalities well enough to design their own algorithms and systems. This book directl

Central Vehicle Dynamics Control of the Robotic Research Platform ROboMObil

OpenAIRE

Bünte, Tilman; Ho, Lok Man; Satzger, Clemens; Brembeck, Jonathan

2014-01-01

The ROboMObil is DLR’s space-robotics driven by-wire electro-mobile research platform for mechatronic actuators, vehicle dynamics control, human machine interfaces, and autonomous driving (DLR = German Aerospace Center). Due to its four highly integrated identical Wheel Robots it exhibits an extraordinary manoeuvrability even allowing for driving sideward or rotating on the spot. Topics related to vehicle dynamics control are addressed in this article.

Design of a drying system for a rollover carwash machine using CFD

Directory of Open Access Journals (Sweden)

Seyyed M.M. Sabet

2016-10-01

Full Text Available This work describes the design and development of a new drying system for a rollover carwash machine with the support of numerical tools. The drying system is composed of a pair of stationary vertical dryers and a moveable horizontal dryer that can adjust itself to the contour of a vehicle. After the definition of the dryers’ concept, their performance was assessed individually to check their internal flow pattern and to improve their airflow distribution. These issues are expected to provide feedback on redesign and geometric optimization of the dryers. After redesign of the dryers separately, the behaviour of the complete drying system was studied on actual vehicle models, representative of the shortest and tallest dimensions that can be washed with the existing carwash machine sector. The drying efficiency of the whole system was studied by calculation of shear stress distribution on various surfaces of a given vehicle. The results allowed concluding that the overall drying performance of the design system is very good and assure adequate drying on most vehicles surfaces. The results obtained from numerical studies were then validated with experimental measurements and a good agreement was found between the two. The procedure employed in this work can be applied to support the design and analysis of other mechanical drying systems.

NET in-vessel vehicle system

International Nuclear Information System (INIS)

Jones, H.

1991-02-01

The CFFTP/Spar In-vessel Vehicle System concept for in-vessel remote maintenance of the NET/ITER machine is described. It comprises a curved deployable boom, a vehicle which can travel on the boom and an end effector or work unit mounted on the vehicle. The stowed boom, vehicle, and work unit are inserted via the equatorial access port of the torus. Following insertion the boom is deployed and locked in place. The vehicle may then travel along the boom to transport the work unit to any desired location. A novel feature of the concept is the deployable boom. When fully deployed, it closely resembles a conventional curved truss structure in configuration and characteristics. However, the joints of the truss structure are hinged so that it can fold into a compact package, of less than 20% of deployed volume for storage, transportation and insertion into the torus. A full-scale 2-metre long section of this boom was produced for demonstration purposes. As part of the concept definition the work unit for divertor handling was studied to demonstrate that large payloads could be manipulated within the confines of the torus using the in-vessel vehicle system. Principal advantages of the IVVS are its high load capacity and rigidity, low weight and stowed volume, simplicity of control and operation, and its relatively high speed of transportation

Analysis of a Novel Transverse Flux Machine with a Tubular Cross-section for Free Piston Energy Converter Application

Energy Technology Data Exchange (ETDEWEB)

Cosic, Alija

2010-07-01

Constantly growing need for oil, all over the world, has caused oil price to rise rapidly during the last decade. High oil prices have made fuel economy as one of the most important factors when consumers are buying their cars today. Realizing this, many car manufacturers have developed or are looking for some alternative solutions in order to decrease fuel consumption. Combining two different technologies in a vehicle, the so called hybrid vehicle, can be seen as the first step toward a better and more sustainable development.There are several different solutions for hybrid vehicles today, among the best known are the Serie Electric Hybrid Vehicle (SEHV), the Parallel Electric Hybrid Vehicle (PEHV) and the Serie-Parallel Hybrid Electric Vehicle (SPEHV). By integrating a combustion engine with a linear electric machine into one unit, a system that is called Free Piston Energy Converter (FPEC) is achieved. The FPEC is suitable for use in a SEHV. Other application areas like stand alone generator are also possible. In this report a novel Transverse Flux Machine (TFM) with a tubular cross section of the translator has been investigated. Application of the machine in a FPEC has put tough requirement on the translator weight, specific power and force density. Different configurations of the winding arrangements as well as the magnet arrangement have been investigated. It has been concluded that the buried magnet design suffers from high leakage flux and is thus not a suitable TFM concept. Instead the surface mounted magnet design has been chosen for further investigation. An analytical model has been developed and a prototype machine has been built based on the analytical results. In order to have a better understanding of the machine characteristic a 3D-FEM analysis has been performed. The results from the analytical model, FEM model and measurements are analyzed and compared. The comparison between the measured and FEM-simulated results shows very good agreement

Dynamic Coordinated Shifting Control of Automated Mechanical Transmissions without a Clutch in a Plug-In Hybrid Electric Vehicle

Directory of Open Access Journals (Sweden)

Xinlei Liu

2012-08-01

Full Text Available On the basis of the shifting process of automated mechanical transmissions (AMTs for traditional hybrid electric vehicles (HEVs, and by combining the features of electric machines with fast response speed, the dynamic model of the hybrid electric AMT vehicle powertrain is built up, the dynamic characteristics of each phase of shifting process are analyzed, and a control strategy in which torque and speed of the engine and electric machine are coordinatively controlled to achieve AMT shifting control for a plug-in hybrid electric vehicle (PHEV without clutch is proposed. In the shifting process, the engine and electric machine are well controlled, and the shift jerk and power interruption and restoration time are reduced. Simulation and real car test results show that the proposed control strategy can more efficiently improve the shift quality for PHEVs equipped with AMTs.

Intelligent Emergency Response System for Police Vehicles in India

DEFF Research Database (Denmark)

Ganeshan, Ishan; Memon, Nasrullah

2015-01-01

time by the police vehicles. In the proposed system, the administrator can view the performance of all the police vehicles at any time through a web portal. The system used traditional data mining algorithms in order to analyze crimes in different areas of a city and at different times of the day....... Based on this crime mapping, the administrator assigns patrol schedules for different police vehicles throughout the day. The proposed system would make it very easy for people to call for the help, and the police authorities to know the locations of the callers and identify crime hot spots...... and the administrator to keep track of the performance of each police vehicle....

Advances Towards Synthetic Machines at the Molecular and Nanoscale Level

Directory of Open Access Journals (Sweden)

Kristina Konstas

2010-06-01

Full Text Available The fabrication of increasingly smaller machines to the nanometer scale can be achieved by either a “top-down” or “bottom-up” approach. While the former is reaching its limits of resolution, the latter is showing promise for the assembly of molecular components, in a comparable approach to natural systems, to produce functioning ensembles in a controlled and predetermined manner. In this review we focus on recent progress in molecular systems that act as molecular machine prototypes such as switches, motors, vehicles and logic operators.

Formation keeping of unmanned ground vehicles

Directory of Open Access Journals (Sweden)

Muangmin Kamonwan

2017-01-01

Full Text Available Controlling motions of an unmanned ground vehicle becomes more popular in real world practices. Its application is useful for household chores, military services, medical purposes, and industrial revolutions, etc. An analysis of motions by using the Fundamental Equations of Constrained Motion (FECM is one effective tool to determine the motions. Its conceptualization is done in three-step procedure as follows: (I Determining an unconstrained motion (II Assigning constraint equations and (III Computing a constrained motion. The equations of motion obtained are expressed as liner functions of acceleration. Then other kinematical information of the unmanned ground vehicles can be obtained by integration its acceleration. In this work, the FECM is used as a tool to analyze motions of a group of unmanned ground vehicles in various forms. The simulation results show that control forces obtained from the approach can regulate motions of unmanned ground vehicles to maneuver in desired formations.

Machine Learning or Information Retrieval Techniques for Bug Triaging: Which is better?

Directory of Open Access Journals (Sweden)

Anjali Goyal

2017-07-01

Full Text Available Bugs are the inevitable part of a software system. Nowadays, large software development projects even release beta versions of their products to gather bug reports from users. The collected bug reports are then worked upon by various developers in order to resolve the defects and make the final software product more reliable. The high frequency of incoming bugs makes the bug handling a difficult and time consuming task. Bug assignment is an integral part of bug triaging that aims at the process of assigning a suitable developer for the reported bug who corrects the source code in order to resolve the bug. There are various semi and fully automated techniques to ease the task of bug assignment. This paper presents the current state of the art of various techniques used for bug report assignment. Through exhaustive research, the authors have observed that machine learning and information retrieval based bug assignment approaches are most popular in literature. A deeper investigation has shown that the trend of techniques is taking a shift from machine learning based approaches towards information retrieval based approaches. Therefore, the focus of this work is to find the reason behind the observed drift and thus a comparative analysis is conducted on the bug reports of the Mozilla, Eclipse, Gnome and Open Office projects in the Bugzilla repository. The results of the study show that the information retrieval based technique yields better efficiency in recommending the developers for bug reports.

Numerical approach for optimum electromagnetic parameters of electrical machines used in vehicle traction applications

International Nuclear Information System (INIS)

Fodorean, D.; Giurgea, S.; Djerdir, A.; Miraoui, A.

2009-01-01

A large speed variation is an essential request in the automobile industry. In order to compete with diesel engines, the flux weakening technique has to be employed on the electrical machines. In this way, appropriate electromagnetic and geometrical parameters can give the desired speed. Using the inverse problem method coupled with numerical analysis by finite element method (FEM), the authors propose an optimum parameters configuration that maximizes the speed domain operation. Several types of electrical machines are under study: induction, synchronous permanent magnet, variable reluctance and transverse flux machines, respectively. With a proper non-linear model, by using analytical and numerical calculation, the authors propose an optimum solution for the speed variation of the studied drives, which will be standing for a final comparison.

Machine Selection in A Dairy Product Company with Entropy and SAW Method Integration

Directory of Open Access Journals (Sweden)

Aşkın Özdağoğlu

2017-07-01

Full Text Available Machine selection is an important and difficult process for the firms, and its results may generate more problems than anticipated. In order to find the best alternative, managers should define the requirements of the factory and determine the necessary criteria. On the other hand, the decision making criteria in order to choose the right equipment may vary according to the type of the manufacturing facility, market requirements, and consumer assigned criteria. This study aims to find the best machine alternative  among  the three machine offerings according to twelve evaluation criteria by integrating entropy method with SAW method.

Monitoring system for gamma radiation of porch type for vehicles

International Nuclear Information System (INIS)

Vazquez C, R.M.; Molina, G.; Gutierrez O, E.; Ramirez J, F.J.; Garcia H, J.M.; Aguilar B, M.A.; Vilchis P, A.E.; Cruz E, P.; Torres B, M.A.

2005-01-01

A monitoring system of gamma radiation for vehicles of the porch type developed in the ININ is presented. This system carries out the radiological monitoring of the vehicles in continuous form, detecting the bottom radiological environment and the presence of nuclear material transported in vehicles. The vehicles are monitored while they pass to low speed through the porch. The detectors are plastic scintillators of great volume that allow high sensibility detection. The arrangement of detecting is interconnected in net, and the data are concentrated on a personal computer whose interface man-machine can be accessed from any personal computer connected to Internet. The system monitoring in real time with options of sampling times from 50 ms configurable up to 500 ms. (Author)

Introduction to special issue on machine learning approaches to shallow parsing

NARCIS (Netherlands)

Hammerton, J; Osborne, M; Armstrong, S; Daelemans, W

2002-01-01

This article introduces the problem of partial or shallow parsing (assigning partial syntactic structure to sentences) and explains why it is an important natural language processing (NLP) task. The complexity of the task makes Machine Learning an attractive option in comparison to the handcrafting

Vehicle routing with stochastic time-dependent travel times

NARCIS (Netherlands)

Lecluyse, C.; Woensel, van T.; Peremans, H.

2009-01-01

Assigning and scheduling vehicle routes in a stochastic time-dependent environment is a crucial management problem. The assumption that in a real-life environment everything goes according to an a priori determined static schedule is unrealistic. Our methodology builds on earlier work in which the

Vehicle routing with stochastic time-dependent travel times

NARCIS (Netherlands)

Lecluyse, C.; Woensel, van T.; Peremans, H.

2007-01-01

Assigning and scheduling vehicle routes in a stochastic time-dependent environment is a crucial management problem. The assumption that in a real-life environment everything goes according to an a priori determined static schedule is unrealistic. Our methodology builds on earlier work in which the

A method of detecting a structure in a field, a method of steering an agricultural vehicle and an agricultural vehicle

DEFF Research Database (Denmark)

2011-01-01

An agricultural vehicle (2) comprises a steering system providing steering signals, said steering system comprising an imaging device (11) for imaging surroundings of the vehicle and an image processing device (13), said steering system operating to provide by means of the imaging device (11......) an image of the field (21), analyse the image to obtain texture information, assign to a plurality of areas of the image probability-values reflecting the likelihood that the respective area relates to a specific structure (12), assume at least one geometric property of said specific structure (12...

Parametric Design and Rapid Prototyping of Installation Box for Vehicle Terminal PCB

Directory of Open Access Journals (Sweden)

Wang Xingxing

2016-01-01

Full Text Available Installation box for vehicle terminal PCB (Printed Circuit Board was took as research object, which is encountered in the process of project developing. Vehicle terminal PCB in actual development process was set as an example, point cloud data were acquired by three coordinate measuring method; Imageware software was used to reconstruct the vehicle terminal PCB model, basic size parameters of vehicle terminal PCB can be got and then design parameters of installation box for vehicle terminal PCB can be determined. Design of the installation box for vehicle terminal PCB was completed based on Solidworks software, then 3D modeling and 2D drawing of installation box for vehicle terminal PCB was gained. Up Plus 2 rapid prototype machine was used to manufacture installation box for vehicle terminal PCB rapidly based on 3D printing technology, then prototype of installation box for vehicle terminal PCB was obtained. It is of certain engineering significant for single (small amount manufacturing of installation box for general PCB.

Toward efficient task assignment and motion planning for large-scale underwater missions

Directory of Open Access Journals (Sweden)

Somaiyeh MahmoudZadeh

2016-10-01

Full Text Available An autonomous underwater vehicle needs to possess a certain degree of autonomy for any particular underwater mission to fulfil the mission objectives successfully and ensure its safety in all stages of the mission in a large-scale operating field. In this article, a novel combinatorial conflict-free task assignment strategy, consisting of an interactive engagement of a local path planner and an adaptive global route planner, is introduced. The method takes advantage of the heuristic search potency of the particle swarm optimization algorithm to address the discrete nature of routing-task assignment approach and the complexity of nondeterministic polynomial-time-hard path planning problem. The proposed hybrid method is highly efficient as a consequence of its reactive guidance framework that guarantees successful completion of missions particularly in cluttered environments. To examine the performance of the method in a context of mission productivity, mission time management, and vehicle safety, a series of simulation studies are undertaken. The results of simulations declare that the proposed method is reliable and robust, particularly in dealing with uncertainties, and it can significantly enhance the level of a vehicle’s autonomy by relying on its reactive nature and capability of providing fast feasible solutions.

A Machine Approach for Field Weakening of Permanent-Magnet Motors

Energy Technology Data Exchange (ETDEWEB)

Hsu, J.S.

2000-04-02

The commonly known technology of field weakening for permanent-magnet (PM) motors is achieved by controlling the direct-axis current component through an inverter, without using mechanical variation of the air gap, a new machine approach for field weakening of PM machines by direct control of air-gap fluxes is introduced. The demagnetization situation due to field weakening is not an issue with this new method. In fact, the PMs are strengthened at field weakening. The field-weakening ratio can reach 1O:1 or higher. This technology is particularly useful for the PM generators and electric vehicle drives.

Current challenges in autonomous vehicle development

Science.gov (United States)

Connelly, J.; Hong, W. S.; Mahoney, R. B., Jr.; Sparrow, D. A.

2006-05-01

The field of autonomous vehicles is a rapidly growing one, with significant interest from both government and industry sectors. Autonomous vehicles represent the intersection of artificial intelligence (AI) and robotics, combining decision-making with real-time control. Autonomous vehicles are desired for use in search and rescue, urban reconnaissance, mine detonation, supply convoys, and more. The general adage is to use robots for anything dull, dirty, dangerous or dumb. While a great deal of research has been done on autonomous systems, there are only a handful of fielded examples incorporating machine autonomy beyond the level of teleoperation, especially in outdoor/complex environments. In an attempt to assess and understand the current state of the art in autonomous vehicle development, a few areas where unsolved problems remain became clear. This paper outlines those areas and provides suggestions for the focus of science and technology research. The first step in evaluating the current state of autonomous vehicle development was to develop a definition of autonomy. A number of autonomy level classification systems were reviewed. The resulting working definitions and classification schemes used by the authors are summarized in the opening sections of the paper. The remainder of the report discusses current approaches and challenges in decision-making and real-time control for autonomous vehicles. Suggested research focus areas for near-, mid-, and long-term development are also presented.

Micro-machined resonator oscillator

Science.gov (United States)

Koehler, Dale R.; Sniegowski, Jeffry J.; Bivens, Hugh M.; Wessendorf, Kurt O.

1994-01-01

A micro-miniature resonator-oscillator is disclosed. Due to the miniaturization of the resonator-oscillator, oscillation frequencies of one MHz and higher are utilized. A thickness-mode quartz resonator housed in a micro-machined silicon package and operated as a "telemetered sensor beacon" that is, a digital, self-powered, remote, parameter measuring-transmitter in the FM-band. The resonator design uses trapped energy principles and temperature dependence methodology through crystal orientation control, with operation in the 20-100 MHz range. High volume batch-processing manufacturing is utilized, with package and resonator assembly at the wafer level. Unique design features include squeeze-film damping for robust vibration and shock performance, capacitive coupling through micro-machined diaphragms allowing resonator excitation at the package exterior, circuit integration and extremely small (0.1 in. square) dimensioning. A family of micro-miniature sensor beacons is also disclosed with widespread applications as bio-medical sensors, vehicle status monitors and high-volume animal identification and health sensors. The sensor family allows measurement of temperatures, chemicals, acceleration and pressure. A microphone and clock realization is also available.

Full truckload vehicle routing problem with profits

Directory of Open Access Journals (Sweden)

Jian Li

2014-04-01

Full Text Available A new variant of the full truckload vehicle routing problem is studied. In this problem there are more than one delivery points corresponding to the same pickup point, and one order is allowed to be served several times by the same vehicle or different vehicles. For the orders which cannot be assigned because of resource constraint, the logistics company outsources them to other logistics companies at a certain cost. To maximize its profits, logistics company decides which to be transported by private fleet and which to be outsourced. The mathematical model is constructed for the problem. Since the problem is NP-hard and it is difficult to solve the large-scale problems with an exact algorithm, a hybrid genetic algorithm is proposed. Computational results show the effectiveness of the hybrid genetic algorithm.

Electronically commutated motors for vehicle applications

Science.gov (United States)

Echolds, E. F.

1980-02-01

Two permanent magnet electronically commutated motors for electric vehicle traction are discussed. One, based on existing technology, produces 23 kW (peak) at 26,000 rpm, and 11 kW continuous at 18,000 rpm. The motor has a conventional design: a four-pole permanent magnet rotor and a three-phase stator similar to those used on ordinary induction motors. The other, advanced technology motor, is rated at 27 kW (peak) at 14,000 rpm, and 11 kW continuous at 10,500 rpm. The machine employs a permanent magnet rotor and a novel ironless stator design in an axial air gap, homopolar configuration. Comparison of the new motors with conventional brush type machines indicates potential for substantial cost savings.

Gall mite inspection on dormant black currant buds using machine vision

DEFF Research Database (Denmark)

Nielsen, M. R.; Stigaard Laursen, Morten; Jonassen, M. S.

2013-01-01

This paper presents a novel machine vision-based approach detecting and mapping gall mite infection in dormant buds on black currant bushes. A vehicle was fitted with four cameras and RTK-GPS. Results compared automatic detection to human decisions based on the images, and by mapping the results...

Stability control for high speed tracked unmanned vehicles

Science.gov (United States)

Pape, Olivier; Morillon, Joel G.; Houbloup, Philippe; Leveque, Stephane; Fialaire, Cecile; Gauthier, Thierry; Ropars, Patrice

2005-05-01

The French Military Robotic Study Program (introduced in Aerosense 2003), sponsored by the French Defense Procurement Agency and managed by Thales as the prime contractor, focuses on about 15 robotic themes which can provide an immediate "operational add-on value". The paper details the "automatic speed adjustment" behavior (named SYR4), developed by Giat Industries Company, which main goal is to secure the teleoperated mobility of high speed tracked vehicles on rough grounds; more precisely, the validated low level behavior continuously adjusts the vehicle speed taking into account the teleperator wish AND the maximum speed that the vehicle can manage safely according to the commanded radius of curvature. The algorithm is based on a realistic physical model of the ground-tracks relation, taking into account many vehicle and ground parameters (such as ground adherence and dynamic specificities of tracked vehicles). It also deals with the teleoperator-machine interface, providing a balanced strategy between both extreme behaviors: a) maximum speed reduction before initiating the commanded curve; b) executing the minimum possible radius without decreasing the commanded speed. The paper presents the results got from the military acceptance tests performed on tracked SYRANO vehicle (French Operational Demonstrator).

Vehicle Color Recognition with Vehicle-Color Saliency Detection and Dual-Orientational Dimensionality Reduction of CNN Deep Features

Science.gov (United States)

Zhang, Qiang; Li, Jiafeng; Zhuo, Li; Zhang, Hui; Li, Xiaoguang

2017-12-01

Color is one of the most stable attributes of vehicles and often used as a valuable cue in some important applications. Various complex environmental factors, such as illumination, weather, noise and etc., result in the visual characteristics of the vehicle color being obvious diversity. Vehicle color recognition in complex environments has been a challenging task. The state-of-the-arts methods roughly take the whole image for color recognition, but many parts of the images such as car windows; wheels and background contain no color information, which will have negative impact on the recognition accuracy. In this paper, a novel vehicle color recognition method using local vehicle-color saliency detection and dual-orientational dimensionality reduction of convolutional neural network (CNN) deep features has been proposed. The novelty of the proposed method includes two parts: (1) a local vehicle-color saliency detection method has been proposed to determine the vehicle color region of the vehicle image and exclude the influence of non-color regions on the recognition accuracy; (2) dual-orientational dimensionality reduction strategy has been designed to greatly reduce the dimensionality of deep features that are learnt from CNN, which will greatly mitigate the storage and computational burden of the subsequent processing, while improving the recognition accuracy. Furthermore, linear support vector machine is adopted as the classifier to train the dimensionality reduced features to obtain the recognition model. The experimental results on public dataset demonstrate that the proposed method can achieve superior recognition performance over the state-of-the-arts methods.

A new controller for battery-powered electric vehicles

Science.gov (United States)

Belsterling, C. A.; Stone, J.

1980-01-01

This paper describes the development, under a NASA/DOE contract, of a new concept for efficient and reliable control of battery-powered vehicles. It avoids the detrimental effects of pulsed-power controllers like the SCR 'chopper' by using rotating machines to meter continuous currents to the traction motor. The concept is validated in a proof-of-principle demonstration system and a complete vehicle is simulated on an analog computer. Test results show exceptional promise for a full-scale system. Optimum control strategies to minimize controller weight are developed by means of the simulated vehicle. The design for an Engineering Model is then prepared in the form of a practical, compact two-bearing package with forced air cooling. Predicted performance is outstanding, with controller efficiency of over 90% at high speed.

Impacts of Interior Permanent Magnet Machine Technology for Electric Vehicles

Science.gov (United States)

2012-01-01

corrosion constraints of magnets  Minimum gear and more direct drive  Regenerative braking and short charging cycle of batteries  Impulse...be found in limited applications such as, antilock braking system (ABS) of the vehicles. Considering the performance enhancement and reliability of... system forms the backbone of modern society. Electricity and its accessibility is one of the major engineering achievements. In order to maintain and

Ultra-light-weight high torque density brushless PM machine design: considering driving-cycle of a four-wheel drive race car (EVER15-138)

NARCIS (Netherlands)

Paulides, J.J.H.; Encica, L.; Beernaert, T.F.; Velden, van der H.H.F.; Parfant, A.G.P.; Lomonova, E.A.

2015-01-01

This paper explores the design of an ultra-light-weight power and torque dense motor to enhance the performance of a light-weight electric racing vehicle. Such a racing vehicle is to compete in formula student racing events. The state-of-the-art powertrain in these vehicles are axial-field machines

An Integrative Approach to Accurate Vehicle Logo Detection

Directory of Open Access Journals (Sweden)

Hao Pan

2013-01-01

required for many applications in intelligent transportation systems and automatic surveillance. The task is challenging considering the small target of logos and the wide range of variability in shape, color, and illumination. A fast and reliable vehicle logo detection approach is proposed following visual attention mechanism from the human vision. Two prelogo detection steps, that is, vehicle region detection and a small RoI segmentation, rapidly focalize a small logo target. An enhanced Adaboost algorithm, together with two types of features of Haar and HOG, is proposed to detect vehicles. An RoI that covers logos is segmented based on our prior knowledge about the logos’ position relative to license plates, which can be accurately localized from frontal vehicle images. A two-stage cascade classier proceeds with the segmented RoI, using a hybrid of Gentle Adaboost and Support Vector Machine (SVM, resulting in precise logo positioning. Extensive experiments were conducted to verify the efficiency of the proposed scheme.

Minimum Interference Channel Assignment Algorithm for Multicast in a Wireless Mesh Network

Directory of Open Access Journals (Sweden)

Sangil Choi

2016-12-01

Full Text Available Wireless mesh networks (WMNs have been considered as one of the key technologies for the configuration of wireless machines since they emerged. In a WMN, wireless routers provide multi-hop wireless connectivity between hosts in the network and also allow them to access the Internet via gateway devices. Wireless routers are typically equipped with multiple radios operating on different channels to increase network throughput. Multicast is a form of communication that delivers data from a source to a set of destinations simultaneously. It is used in a number of applications, such as distributed games, distance education, and video conferencing. In this study, we address a channel assignment problem for multicast in multi-radio multi-channel WMNs. In a multi-radio multi-channel WMN, two nearby nodes will interfere with each other and cause a throughput decrease when they transmit on the same channel. Thus, an important goal for multicast channel assignment is to reduce the interference among networked devices. We have developed a minimum interference channel assignment (MICA algorithm for multicast that accurately models the interference relationship between pairs of multicast tree nodes using the concept of the interference factor and assigns channels to tree nodes to minimize interference within the multicast tree. Simulation results show that MICA achieves higher throughput and lower end-to-end packet delay compared with an existing channel assignment algorithm named multi-channel multicast (MCM. In addition, MICA achieves much lower throughput variation among the destination nodes than MCM.

Integrated powertrain control for hybrid electric vehicles with electric variable transmission

NARCIS (Netherlands)

Kessels, J.T.B.A.; Foster, D.L.; Bosch, van den P.P.J.

2009-01-01

The electric variable transmission (EVT) offers a powersplit for hybrid electric vehicles by integrating two motor/ generator sets into one electric machine. This double rotor concept implements a continuously variable transmission between the engine and the driveline, including the possibility for

Two wheel speed robust sliding mode control for electric vehicle drive

Directory of Open Access Journals (Sweden)

Abdelfatah Nasri

2008-01-01

Full Text Available Nowadays the uses of electrical power resources are integrated in the modern vehicle motion traction chain so new technologies allow the development of electric vehicles (EV by means of static converters-related electric motors. All mechanical transmission devices are eliminated and vehicle wheel motion can be controlled by means of power electronics. The proposed propulsing system consists of two induction motors (IM that ensure the drive of the two back driving wheels. The proposed control structure-called independent machines- for speed control permit the achievement of an electronic differential. The electronic differential system ensures the robust control of the vehicle behavior on the road. It also allows controlling independently, every driving wheel to turn at different speeds in any curve. This paper presents the study and the sliding mode control strategy of the electric vehicle driving wheels.

Task Assignment and Path Planning for Multiple Autonomous Underwater Vehicles Using 3D Dubins Curves †.

Science.gov (United States)

Cai, Wenyu; Zhang, Meiyan; Zheng, Yahong Rosa

2017-07-11

This paper investigates the task assignment and path planning problem for multiple AUVs in three dimensional (3D) underwater wireless sensor networks where nonholonomic motion constraints of underwater AUVs in 3D space are considered. The multi-target task assignment and path planning problem is modeled by the Multiple Traveling Sales Person (MTSP) problem and the Genetic Algorithm (GA) is used to solve the MTSP problem with Euclidean distance as the cost function and the Tour Hop Balance (THB) or Tour Length Balance (TLB) constraints as the stop criterion. The resulting tour sequences are mapped to 2D Dubins curves in the X - Y plane, and then interpolated linearly to obtain the Z coordinates. We demonstrate that the linear interpolation fails to achieve G 1 continuity in the 3D Dubins path for multiple targets. Therefore, the interpolated 3D Dubins curves are checked against the AUV dynamics constraint and the ones satisfying the constraint are accepted to finalize the 3D Dubins curve selection. Simulation results demonstrate that the integration of the 3D Dubins curve with the MTSP model is successful and effective for solving the 3D target assignment and path planning problem.

Stereoscopic Machine-Vision System Using Projected Circles

Science.gov (United States)

Mackey, Jeffrey R.

2010-01-01

A machine-vision system capable of detecting obstacles large enough to damage or trap a robotic vehicle is undergoing development. The system includes (1) a pattern generator that projects concentric circles of laser light forward onto the terrain, (2) a stereoscopic pair of cameras that are aimed forward to acquire images of the circles, (3) a frame grabber and digitizer for acquiring image data from the cameras, and (4) a single-board computer that processes the data. The system is being developed as a prototype of machine- vision systems to enable robotic vehicles ( rovers ) on remote planets to avoid craters, large rocks, and other terrain features that could capture or damage the vehicles. Potential terrestrial applications of systems like this one could include terrain mapping, collision avoidance, navigation of robotic vehicles, mining, and robotic rescue. This system is based partly on the same principles as those of a prior stereoscopic machine-vision system in which the cameras acquire images of a single stripe of laser light that is swept forward across the terrain. However, this system is designed to afford improvements over some of the undesirable features of the prior system, including the need for a pan-and-tilt mechanism to aim the laser to generate the swept stripe, ambiguities in interpretation of the single-stripe image, the time needed to sweep the stripe across the terrain and process the data from many images acquired during that time, and difficulty of calibration because of the narrowness of the stripe. In this system, the pattern generator does not contain any moving parts and need not be mounted on a pan-and-tilt mechanism: the pattern of concentric circles is projected steadily in the forward direction. The system calibrates itself by use of data acquired during projection of the concentric-circle pattern onto a known target representing flat ground. The calibration- target image data are stored in the computer memory for use as a

Binary pressure-sensitive paint measurements using miniaturised, colour, machine vision cameras

Science.gov (United States)

Quinn, Mark Kenneth

2018-05-01

Recent advances in machine vision technology and capability have led to machine vision cameras becoming applicable for scientific imaging. This study aims to demonstrate the applicability of machine vision colour cameras for the measurement of dual-component pressure-sensitive paint (PSP). The presence of a second luminophore component in the PSP mixture significantly reduces its inherent temperature sensitivity, increasing its applicability at low speeds. All of the devices tested are smaller than the cooled CCD cameras traditionally used and most are of significantly lower cost, thereby increasing the accessibility of such technology and techniques. Comparisons between three machine vision cameras, a three CCD camera, and a commercially available specialist PSP camera are made on a range of parameters, and a detailed PSP calibration is conducted in a static calibration chamber. The findings demonstrate that colour machine vision cameras can be used for quantitative, dual-component, pressure measurements. These results give rise to the possibility of performing on-board dual-component PSP measurements in wind tunnels or on real flight/road vehicles.

Equivalent model of a dually-fed machine for electric drive control systems

Science.gov (United States)

Ostrovlyanchik, I. Yu; Popolzin, I. Yu

2018-05-01

The article shows that the mathematical model of a dually-fed machine is complicated because of the presence of a controlled voltage source in the rotor circuit. As a method of obtaining a mathematical model, the method of a generalized two-phase electric machine is applied and a rotating orthogonal coordinate system is chosen that is associated with the representing vector of a stator current. In the chosen coordinate system in the operator form the differential equations of electric equilibrium for the windings of the generalized machine (the Kirchhoff equation) are written together with the expression for the moment, which determines the electromechanical energy transformation in the machine. Equations are transformed so that they connect the currents of the windings, that determine the moment of the machine, and the voltages on these windings. The structural diagram of the machine is assigned to the written equations. Based on the written equations and accepted assumptions, expressions were obtained for the balancing the EMF of windings, and on the basis of these expressions an equivalent mathematical model of a dually-fed machine is proposed, convenient for use in electric drive control systems.

Optimizing virtual machine placement for energy and SLA in clouds using utility functions

Directory of Open Access Journals (Sweden)

Abdelkhalik Mosa

2016-10-01

Full Text Available Abstract Cloud computing provides on-demand access to a shared pool of computing resources, which enables organizations to outsource their IT infrastructure. Cloud providers are building data centers to handle the continuous increase in cloud users’ demands. Consequently, these cloud data centers consume, and have the potential to waste, substantial amounts of energy. This energy consumption increases the operational cost and the CO2 emissions. The goal of this paper is to develop an optimized energy and SLA-aware virtual machine (VM placement strategy that dynamically assigns VMs to Physical Machines (PMs in cloud data centers. This placement strategy co-optimizes energy consumption and service level agreement (SLA violations. The proposed solution adopts utility functions to formulate the VM placement problem. A genetic algorithm searches the possible VMs-to-PMs assignments with a view to finding an assignment that maximizes utility. Simulation results using CloudSim show that the proposed utility-based approach reduced the average energy consumption by approximately 6 % and the overall SLA violations by more than 38 %, using fewer VM migrations and PM shutdowns, compared to a well-known heuristics-based approach.

Control concepts for vehicle drive line to reduce fuel consumption

Energy Technology Data Exchange (ETDEWEB)

Ossyra, J.C.

2005-07-01

In this work advanced drive line control concepts for off-road vehicles have been developed and investigated to reduce the power losses and finally the fuel consumption of the entire drive system by use of on-line optimization procedure. Two separate closed loop speed controls have been developed for the use on a microcontroller onboard the vehicle: one to control the hydrostatic transmission and the other to control the engine speed. Considering the loss characteristics of the displacement machines in the hydrostatic transmission and the steady state characteristics of the combustion engine by use of pure mathematical approximations of measured curves, a direct optimization strategy is used, which works on-line on a microcontroller. A laboratory hardware-in-the loop test rig has been used to investigate the proposed control concepts. For different typical and desired work cycles of an off-road machine on level ground and uphill a slope the effectiveness of the proposed control concepts have been proven. (orig.)

How important is vehicle safety for older consumers in the vehicle purchase process?

Science.gov (United States)

Koppel, Sjaan; Clark, Belinda; Hoareau, Effie; Charlton, Judith L; Newstead, Stuart V

2013-01-01

This study aimed to investigate the importance of vehicle safety to older consumers in the vehicle purchase process. Older (n = 102), middle-aged (n = 791), and younger (n = 109) participants throughout the eastern Australian states of Victoria, New South Wales, and Queensland who had recently purchased a new or used vehicle completed an online questionnaire about their vehicle purchase process. When asked to list the 3 most important considerations in the vehicle purchase process (in an open-ended format), older consumers were mostly likely to list price as their most important consideration (43%). Similarly, when presented with a list of vehicle factors (such as price, design, Australasian New Car Assessment Program [ANCAP] rating), older consumers were most likely to identify price as the most important vehicle factor (36%). When presented with a list of vehicle features (such as automatic transmission, braking, air bags), older consumers in the current study were most likely to identify an antilock braking system (41%) as the most important vehicle feature, and 50 percent of older consumers identified a safety-related vehicle feature as the highest priority vehicle feature (50%). When asked to list up to 3 factors that make a vehicle safe, older consumers in the current study were most likely to list braking systems (35%), air bags (22%), and the driver's behavior or skill (11%). When asked about the influence of safety in the new vehicle purchase process, one third of older consumers reported that all new vehicles are safe (33%) and almost half of the older consumers rated their vehicle as safer than average (49%). A logistic regression model was developed to predict the profile of older consumers more likely to assign a higher priority to safety features in the vehicle purchasing process. The model predicted that the importance of safety-related features was influenced by several variables, including older consumers' beliefs that they could protect themselves

A Support Vector Machine Approach to Dutch Part-of-Speech Tagging

NARCIS (Netherlands)

Poel, Mannes; Stegeman, L.; op den Akker, Hendrikus J.A.; Berthold, M.R.; Shawe-Taylor, J.; Lavrac, N.

Part-of-Speech tagging, the assignment of Parts-of-Speech to the words in a given context of use, is a basic technique in many systems that handle natural languages. This paper describes a method for supervised training of a Part-of-Speech tagger using a committee of Support Vector Machines on a

FEM analysis of an single stator dual PM rotors axial synchronous machine

Science.gov (United States)

Tutelea, L. N.; Deaconu, S. I.; Popa, G. N.

2017-01-01

The actual e - continuously variable transmission (e-CVT) solution for the parallel Hybrid Electric Vehicle (HEV) requires two electric machines, two inverters, and a planetary gear. A distinct electric generator and a propulsion electric motor, both with full power converters, are typical for a series HEV. In an effort to simplify the planetary-geared e-CVT for the parallel HEV or the series HEV we hereby propose to replace the basically two electric machines and their two power converters by a single, axial-air-gap, electric machine central stator, fed from a single PWM converter with dual frequency voltage output and two independent PM rotors. The proposed topologies, the magneto-motive force analysis and quasi 3D-FEM analysis are the core of the paper.

PWM Inverter control and the application thereof within electric vehicles

Science.gov (United States)

Geppert, Steven

1982-01-01

An inverter (34) which provides power to an A.C. machine (28) is controlled by a circuit (36) employing PWM control strategy whereby A.C. power is supplied to the machine at a preselectable frequency and preselectable voltage. This is accomplished by the technique of waveform notching in which the shapes of the notches are varied to determine the average energy content of the overall waveform. Through this arrangement, the operational efficiency of the A.C. machine is optimized. The control circuit includes a micro-computer and memory element which receive various parametric inputs and calculate optimized machine control data signals therefrom. The control data is asynchronously loaded into the inverter through an intermediate buffer (38). In its preferred embodiment, the present invention is incorporated within an electric vehicle (10) employing a 144 VDC battery pack (32) and a three-phase induction motor (18).

Task Assignment and Path Planning for Multiple Autonomous Underwater Vehicles Using 3D Dubins Curves †

Directory of Open Access Journals (Sweden)

Wenyu Cai

2017-07-01

Full Text Available This paper investigates the task assignment and path planning problem for multiple AUVs in three dimensional (3D underwater wireless sensor networks where nonholonomic motion constraints of underwater AUVs in 3D space are considered. The multi-target task assignment and path planning problem is modeled by the Multiple Traveling Sales Person (MTSP problem and the Genetic Algorithm (GA is used to solve the MTSP problem with Euclidean distance as the cost function and the Tour Hop Balance (THB or Tour Length Balance (TLB constraints as the stop criterion. The resulting tour sequences are mapped to 2D Dubins curves in the X − Y plane, and then interpolated linearly to obtain the Z coordinates. We demonstrate that the linear interpolation fails to achieve G 1 continuity in the 3D Dubins path for multiple targets. Therefore, the interpolated 3D Dubins curves are checked against the AUV dynamics constraint and the ones satisfying the constraint are accepted to finalize the 3D Dubins curve selection. Simulation results demonstrate that the integration of the 3D Dubins curve with the MTSP model is successful and effective for solving the 3D target assignment and path planning problem.

Single product lot-sizing on unrelated parallel machines with non-decreasing processing times

Science.gov (United States)

Eremeev, A.; Kovalyov, M.; Kuznetsov, P.

2018-01-01

We consider a problem in which at least a given quantity of a single product has to be partitioned into lots, and lots have to be assigned to unrelated parallel machines for processing. In one version of the problem, the maximum machine completion time should be minimized, in another version of the problem, the sum of machine completion times is to be minimized. Machine-dependent lower and upper bounds on the lot size are given. The product is either assumed to be continuously divisible or discrete. The processing time of each machine is defined by an increasing function of the lot volume, given as an oracle. Setup times and costs are assumed to be negligibly small, and therefore, they are not considered. We derive optimal polynomial time algorithms for several special cases of the problem. An NP-hard case is shown to admit a fully polynomial time approximation scheme. An application of the problem in energy efficient processors scheduling is considered.

SOLON: An autonomous vehicle mission planner

Science.gov (United States)

Dudziak, M. J.

1987-01-01

The State-Operator Logic Machine (SOLON) Planner provides an architecture for effective real-time planning and replanning for an autonomous vehicle. The highlights of the system, which distinguish it from other AI-based planners that have been designed previously, are its hybrid application of state-driven control architecture and the use of both schematic representations and logic programming for the management of its knowledge base. SOLON is designed to provide multiple levels of planning for a single autonomous vehicle which is supplied with a skeletal, partially-specified mission plan at the outset of the vehicle's operations. This mission plan consists of a set of objectives, each of which will be decomposable by the planner into tasks. These tasks are themselves comparatively complex sets of actions which are executable by a conventional real-time control system which does not perform planning but which is capable of making adjustments or modifications to the provided tasks according to constraints and tolerances provided by the Planner. The current implementation of the SOLON is in the form of a real-time simulation of the Planner module of an Intelligent Vehicle Controller (IVC) on-board an autonomous underwater vehicle (AUV). The simulation is embedded within a larger simulator environment known as ICDS (Intelligent Controller Development System) operating on a Symbolics 3645/75 computer.

Throughput centered prioritization of machines in transfer lines

Energy Technology Data Exchange (ETDEWEB)

Pascual, R., E-mail: rpascual@ing.puc.cl [Physical Asset Management Lab, Centro de Mineria, Pontificia Universidad Catolica de Chile, Av. Vicuna Mackenna 4860, Santiago (Chile); Godoy, D. [Physical Asset Management Lab, Centro de Mineria, Pontificia Universidad Catolica de Chile, Av. Vicuna Mackenna 4860, Santiago (Chile); Louit, D.M. [Komatsu Chile S.A., Av. Americo Vespucio 0631, Quilicura, Santiago (Chile)

2011-10-15

In an environment of scarce resources and complex production systems, prioritizing is key to confront the challenge of managing physical assets. In the literature, there exist a number of techniques to prioritize maintenance decisions that consider safety, technical and business perspectives. However, the effect of risk mitigating elements-such as intermediate buffers in production lines-on prioritization has not yet been investigated in depth. In this line, the work proposes a user-friendly graphical technique called the system efficiency influence diagram (SEID). Asset managers may use SEID to identify machines that have a greater impact on the system throughput, and thus set prioritized maintenance policies and/or redesign of buffers capacities. The tool provides insight to the analyst as it decomposes the influence of a given machine on the system throughput as a product of two elements: (1) system influence efficiency factor and (2) machine unavailability factor. We illustrate its applicability using three case studies: a four-machine transfer line, a vehicle assembly line, and an open-pit mining conveyor system. The results confirm that the machines with greater unavailability factors are not necessarily the most important for the efficiency of the production line, as it is the case when no intermediate buffers exist. As a decision aid tool, SEID emphasizes the need to move from a maintenance vision focused on machine availability, to a systems engineering perspective. - Highlights: > We propose a graphical technique to prioritize machines in production lines. > The tool is called 'system efficiency influence diagram' (SEID). > It helps setting prioritized maintenance policies and/or redesign of buffers. > The SEID technique focuses on system efficiency and throughput. > We illustrate its applicability using three case studies.

Contribution à la conception et à la commande des machines synchrones à double excitation. Application au véhicule hybride.

OpenAIRE

AMARA , Yacine

2001-01-01

This Thesis concerns the design of hybrid excited synchronous machines used for hybrid and/or electric vehicles traction.; Les travaux présentés dans ce mémoire concernent la conception et la commande des machines synchrones à double excitation. Ce concept apparaît viable et améliore les performances des machines synchrones et plus globalement les systèmes d’entraînement où elles s’intègrent.

Off-highway vehicle technology roadmap.; TOPICAL

International Nuclear Information System (INIS)

NONE

2002-01-01

The off-highway sector is under increasing pressure to reduce operating costs (including fuel costs) and to reduce emissions. Recognizing this, the Society of Automotive Engineers and the U.S. Department of Energy (DOE) convened a workshop in April 2001 (ANL 2001) to (1) determine the interest of the off-highway sector (consisting of agriculture, construction, surface mining, inland marine) in crafting a shared vision of off-highway, heavy machines of the future and (2) identify critical research and development (R and D) needs for minimizing off-highway vehicle emissions while cost-effectively maintaining or enhancing system performance. The workshop also enabled government and industry participants to exchange information. During the workshop, it became clear that the challenges facing the heavy, surface-based off-highway sector can be addressed in three major machine categories: (1) engine/aftertreatment and fuels/lubes, (2) machine systems, and (3) thermal management. Working groups convened to address these topical areas. The status of off-highway technologies was determined, critical technical barriers to achieving future emission standards were identified, and strategies and technologies for reducing fuel consumption were discussed. Priority areas for R and D were identified. Given the apparent success of the discussions at the workshop, several participants from industry agreed to help in the formation of a joint industry/government ''roadmap'' team. The U.S. Department of Energy's Office of Heavy Vehicle Technologies has an extensive role in researching ways to make heavy-duty trucks and trains more efficient, with respect to both fuel usage and air emissions. The workshop participants felt that a joint industry/government research program that addresses the unique needs of the off-highway sector would complement the current research program for highway vehicles. With industry expertise, in-kind contributions, and federal government funding (coupled with

Implications of advanced vehicle technologies for older drivers.

Science.gov (United States)

Molnar, Lisa J; Eby, David W

2017-09-01

Advances are being made in vehicle technologies that may help older adults compensate for some of the declines in abilities associated with aging. These advances hold promise for increasing vehicle safety, reducing injuries, and making the driving task more comfortable. However, important research gaps remain with regard to how various advanced technologies impact the safety of older drivers, as well as older drivers' perceptions about these technologies. This special issue contains seven original contributions that address these issues. Specific topics include the: congruence of design guidelines with the needs and abilities of older drivers, transfer of control between automated and manual driving, use of in-vehicle monitoring technology, motivations for technology use and assigned meanings, technology valuation, and effects on driving behavior. Copyright © 2017 Elsevier Ltd. All rights reserved.

Parametric modeling of components for selection and specification of hybrid vehicle drivetrains

NARCIS (Netherlands)

Hofman, T.; Steinbuch, M.; Druten, van R.M.; Serrarens, A.F.A.

2007-01-01

Drivetrain hybridization implies adding a secondary power source (electric machine/battery) to a primary power source (engine/filled fuel tank) in order to improve: fuel economy, emissions, drivability (performance), comfort and safety. Designing a hybrid vehicle drivetrain fulfilling the required

Layout design and energetic analysis of a complex diesel parallel hybrid electric vehicle

International Nuclear Information System (INIS)

Finesso, Roberto; Spessa, Ezio; Venditti, Mattia

2014-01-01

Highlights: • Layout design, energetic and cost analysis of complex parallel hybrid vehicles. • Development of global and real-time optimizers for control strategy identification. • Rule-based control strategies to minimize fuel consumption and NO x . • Energy share across each working mode for battery and thermal engine. - Abstract: The present paper is focused on the design, optimization and analysis of a complex parallel hybrid electric vehicle, equipped with two electric machines on both the front and rear axles, and on the evaluation of its potential to reduce fuel consumption and NO x emissions over several driving missions. The vehicle has been compared with two conventional parallel hybrid vehicles, equipped with a single electric machine on the front axle or on the rear axle, as well as with a conventional vehicle. All the vehicles have been equipped with compression ignition engines. The optimal layout of each vehicle was identified on the basis of the minimization of the overall powertrain costs during the whole vehicle life. These costs include the initial investment due to the production of the components as well as the operating costs related to fuel consumption and to battery depletion. Identification of the optimal powertrain control strategy, in terms of the management of the power flows of the engine and electric machines, and of gear selection, is necessary in order to be able to fully exploit the potential of the hybrid architecture. To this end, two global optimizers, one of a deterministic nature and another of a stochastic type, and two real-time optimizers have been developed, applied and compared. A new mathematical technique has been developed and applied to the vehicle simulation model in order to decrease the computational time of the optimizers. First, the vehicle model equations were written in order to allow a coarse time grid to be used, then, the control variables (i.e., power flow and gear number) were discretized, and the

On Coding the States of Sequential Machines with the Use of Partition Pairs

DEFF Research Database (Denmark)

Zahle, Torben U.

1966-01-01

This article introduces a new technique of making state assignment for sequential machines. The technique is in line with the approach used by Hartmanis [l], Stearns and Hartmanis [3], and Curtis [4]. It parallels the work of Dolotta and McCluskey [7], although it was developed independently...

Protein secondary structure assignment revisited: a detailed analysis of different assignment methods

Directory of Open Access Journals (Sweden)

de Brevern Alexandre G

2005-09-01

Full Text Available Abstract Background A number of methods are now available to perform automatic assignment of periodic secondary structures from atomic coordinates, based on different characteristics of the secondary structures. In general these methods exhibit a broad consensus as to the location of most helix and strand core segments in protein structures. However the termini of the segments are often ill-defined and it is difficult to decide unambiguously which residues at the edge of the segments have to be included. In addition, there is a "twilight zone" where secondary structure segments depart significantly from the idealized models of Pauling and Corey. For these segments, one has to decide whether the observed structural variations are merely distorsions or whether they constitute a break in the secondary structure. Methods To address these problems, we have developed a method for secondary structure assignment, called KAKSI. Assignments made by KAKSI are compared with assignments given by DSSP, STRIDE, XTLSSTR, PSEA and SECSTR, as well as secondary structures found in PDB files, on 4 datasets (X-ray structures with different resolution range, NMR structures. Results A detailed comparison of KAKSI assignments with those of STRIDE and PSEA reveals that KAKSI assigns slightly longer helices and strands than STRIDE in case of one-to-one correspondence between the segments. However, KAKSI tends also to favor the assignment of several short helices when STRIDE and PSEA assign longer, kinked, helices. Helices assigned by KAKSI have geometrical characteristics close to those described in the PDB. They are more linear than helices assigned by other methods. The same tendency to split long segments is observed for strands, although less systematically. We present a number of cases of secondary structure assignments that illustrate this behavior. Conclusion Our method provides valuable assignments which favor the regularity of secondary structure segments.

Present and future of laser welding machine; Laser yosetsuki no genjo to tenbo

Energy Technology Data Exchange (ETDEWEB)

Taniu, Y. [Ishikawajima-Harima Heavy Industries Co. Ltd., Tokyo (Japan)

1998-04-01

This paper describes recent trends of laser welding machine. For CO2 laser welding machine, seam weld of large diameter weld pipes using a 25 kW-class machine, and plate weld of steel plate using a 45 kW-class machine are reported. For YAG laser welding machine, high-output 5.5 kW-class machines are commercialized. Machines with slab structure of plate-like YAG chrystal have been developed which show high-oscillation efficiency and can be applied to cutting. Machines have been developed in which YAG laser output with slab structure is transmitted through GI fiber. High-speed welding of aluminum alloys can be realized by improving the converging performance. Efficiency of YAG laser can be enhanced through the time-divided utilization by switching the beam transmission path using fiber change-over switch. In the automobile industry, CO2 laser is mainly used, and a system combining CO laser with articulate robot is realized. TIG and MIG welding is often used for welding of aluminum for railway vehicles. It is required to reduce the welding strain. In the iron and steel industry, the productivity has been improved by the laser welding. YAG laser is put into practice for nuclear reactors. 5 refs., 8 figs., 1 tab.

Analysis of machining and machine tools

CERN Document Server

Liang, Steven Y

2016-01-01

This book delivers the fundamental science and mechanics of machining and machine tools by presenting systematic and quantitative knowledge in the form of process mechanics and physics. It gives readers a solid command of machining science and engineering, and familiarizes them with the geometry and functionality requirements of creating parts and components in today’s markets. The authors address traditional machining topics, such as: single and multiple point cutting processes grinding components accuracy and metrology shear stress in cutting cutting temperature and analysis chatter They also address non-traditional machining, such as: electrical discharge machining electrochemical machining laser and electron beam machining A chapter on biomedical machining is also included. This book is appropriate for advanced undergraduate and graduate mechani cal engineering students, manufacturing engineers, and researchers. Each chapter contains examples, exercises and their solutions, and homework problems that re...

Does providing nutrition information at vending machines reduce calories per item sold?

Science.gov (United States)

Dingman, Deirdre A; Schulz, Mark R; Wyrick, David L; Bibeau, Daniel L; Gupta, Sat N

2015-02-01

In 2010, the United States (US) enacted a restaurant menu labeling law. The law also applied to vending machine companies selling food. Research suggested that providing nutrition information on menus in restaurants might reduce the number of calories purchased. We tested the effect of providing nutrition information and 'healthy' designations to consumers where vending machines were located in college residence halls. We conducted our study at one university in Southeast US (October-November 2012). We randomly assigned 18 vending machines locations (residence halls) to an intervention or control group. For the intervention we posted nutrition information, interpretive signage, and sent a promotional email to residents of the hall. For the control group we did nothing. We tracked sales over 4 weeks before and 4 weeks after we introduced the intervention. Our intervention did not change what the residents bought. We recommend additional research about providing nutrition information where vending machines are located, including testing formats used to present information.

Fault Risk Assessment of Underwater Vehicle Steering System Based on Virtual Prototyping and Monte Carlo Simulation

Directory of Open Access Journals (Sweden)

He Deyu

2016-09-01

Full Text Available Assessing the risks of steering system faults in underwater vehicles is a human-machine-environment (HME systematic safety field that studies faults in the steering system itself, the driver’s human reliability (HR and various environmental conditions. This paper proposed a fault risk assessment method for an underwater vehicle steering system based on virtual prototyping and Monte Carlo simulation. A virtual steering system prototype was established and validated to rectify a lack of historic fault data. Fault injection and simulation were conducted to acquire fault simulation data. A Monte Carlo simulation was adopted that integrated randomness due to the human operator and environment. Randomness and uncertainty of the human, machine and environment were integrated in the method to obtain a probabilistic risk indicator. To verify the proposed method, a case of stuck rudder fault (SRF risk assessment was studied. This method may provide a novel solution for fault risk assessment of a vehicle or other general HME system.

Path Planning Software and Graphics Interface for an Autonomous Vehicle, Accounting for Terrain Features

National Research Council Canada - National Science Library

Hurezeanu, Vlad

2000-01-01

A Navigation Test Vehicle (NTV) is being developed at the Center for Intelligent Machines and Robots at the University of Florida under the sponsorship of the Air Force Research Laboratory at Tyndall Air Force Base...

Distinguishing Asthma Phenotypes Using Machine Learning Approaches.

Science.gov (United States)

Howard, Rebecca; Rattray, Magnus; Prosperi, Mattia; Custovic, Adnan

2015-07-01

Asthma is not a single disease, but an umbrella term for a number of distinct diseases, each of which are caused by a distinct underlying pathophysiological mechanism. These discrete disease entities are often labelled as 'asthma endotypes'. The discovery of different asthma subtypes has moved from subjective approaches in which putative phenotypes are assigned by experts to data-driven ones which incorporate machine learning. This review focuses on the methodological developments of one such machine learning technique-latent class analysis-and how it has contributed to distinguishing asthma and wheezing subtypes in childhood. It also gives a clinical perspective, presenting the findings of studies from the past 5 years that used this approach. The identification of true asthma endotypes may be a crucial step towards understanding their distinct pathophysiological mechanisms, which could ultimately lead to more precise prevention strategies, identification of novel therapeutic targets and the development of effective personalized therapies.

Stochastic User Equilibrium Assignment in Schedule-Based Transit Networks with Capacity Constraints

Directory of Open Access Journals (Sweden)

Wangtu Xu

2012-01-01

Full Text Available This paper proposes a stochastic user equilibrium (SUE assignment model for a schedule-based transit network with capacity constraint. We consider a situation in which passengers do not have the full knowledge about the condition of the network and select paths that minimize a generalized cost function encompassing five components: (1 ride time, which is composed of in-vehicle and waiting times, (2 overload delay, (3 fare, (4 transfer constraints, and (5 departure time difference. We split passenger demands among connections which are the space-time paths between OD pairs of the network. All transit vehicles have a fixed capacity and operate according to some preset timetables. When the capacity constraint of the transit line segment is reached, we show that the Lagrange multipliers of the mathematical programming problem are equivalent to the equilibrium passenger overload delay in the congested transit network. The proposed model can simultaneously predict how passengers choose their transit vehicles to minimize their travel costs and estimate the associated costs in a schedule-based congested transit network. A numerical example is used to illustrate the performance of the proposed model.

Throughput centered prioritization of machines in transfer lines

International Nuclear Information System (INIS)

Pascual, R.; Godoy, D.; Louit, D.M.

2011-01-01

In an environment of scarce resources and complex production systems, prioritizing is key to confront the challenge of managing physical assets. In the literature, there exist a number of techniques to prioritize maintenance decisions that consider safety, technical and business perspectives. However, the effect of risk mitigating elements-such as intermediate buffers in production lines-on prioritization has not yet been investigated in depth. In this line, the work proposes a user-friendly graphical technique called the system efficiency influence diagram (SEID). Asset managers may use SEID to identify machines that have a greater impact on the system throughput, and thus set prioritized maintenance policies and/or redesign of buffers capacities. The tool provides insight to the analyst as it decomposes the influence of a given machine on the system throughput as a product of two elements: (1) system influence efficiency factor and (2) machine unavailability factor. We illustrate its applicability using three case studies: a four-machine transfer line, a vehicle assembly line, and an open-pit mining conveyor system. The results confirm that the machines with greater unavailability factors are not necessarily the most important for the efficiency of the production line, as it is the case when no intermediate buffers exist. As a decision aid tool, SEID emphasizes the need to move from a maintenance vision focused on machine availability, to a systems engineering perspective. - Highlights: → We propose a graphical technique to prioritize machines in production lines. → The tool is called 'system efficiency influence diagram' (SEID). → It helps setting prioritized maintenance policies and/or redesign of buffers. → The SEID technique focuses on system efficiency and throughput. → We illustrate its applicability using three case studies.

Cooperative Control for Multiple Autonomous Vehicles Using Descriptor Functions

Directory of Open Access Journals (Sweden)

Marta Niccolini

2014-01-01

Full Text Available The paper presents a novel methodology for the control management of a swarm of autonomous vehicles. The vehicles, or agents, may have different skills, and be employed for different missions. The methodology is based on the definition of descriptor functions that model the capabilities of the single agent and each task or mission. The swarm motion is controlled by minimizing a suitable norm of the error between agents’ descriptor functions and other descriptor functions which models the entire mission. The validity of the proposed technique is tested via numerical simulation, using different task assignment scenarios.

Cognitive Connected Vehicle Information System Design Requirement for Safety: Role of Bayesian Artificial Intelligence

OpenAIRE

Ata Khan

2013-01-01

Intelligent transportation systems (ITS) are gaining acceptance around the world and the connected vehicle component of ITS is recognized as a high priority research and development area in many technologically advanced countries. Connected vehicles are expected to have the capability of safe, efficient and eco-driving operations whether these are under human control or in the adaptive machine control mode of operations. The race is on to design the capability to operate in connected traffic ...

Hybrid-secondary uncluttered permanent magnet machine and method

Science.gov (United States)

Hsu, John S.

2005-12-20

An electric machine (40) has a stator (43), a permanent magnet rotor (38) with permanent magnets (39) and a magnetic coupling uncluttered rotor (46) for inducing a slip energy current in secondary coils (47). A dc flux can be produced in the uncluttered rotor when the secondary coils are fed with dc currents. The magnetic coupling uncluttered rotor (46) has magnetic brushes (A, B, C, D) which couple flux in through the rotor (46) to the secondary coils (47c, 47d) without inducing a current in the rotor (46) and without coupling a stator rotational energy component to the secondary coils (47c, 47d). The machine can be operated as a motor or a generator in multi-phase or single-phase embodiments and is applicable to the hybrid electric vehicle. A method of providing a slip energy controller is also disclosed.

Technical engineering services in support of the Nike-Tomahawk sounding rocket vehicle system

Science.gov (United States)

1972-01-01

Task assignments in support of the Nike-Tomahawk vehicles, which were completed from May, 1970 through November 1972 are reported. The services reported include: analytical, design and drafting, fabrication and modification, and field engineering.

Kafka's Writing Machine: Metamorphosis in the Penal Colony

Directory of Open Access Journals (Sweden)

Arnold Weinstein

1982-09-01

Full Text Available Kafka's "In the Penal Colony" is a problematic story, largely because of the conflicting interpretations it has received: does its famous machine dispense grace or torture? Is Kafka giving us a parable of Old vs. New Law? How does the "liberal" explorer or the "liberal" reader assess the Officer's impassioned pleading for the Machine and the kind of justice it serves? A strange kind of coherence emerges, however, when one focusses on the central unifying motif of the story: understanding. The tale itself is little more than the Officer's desperate effort to make the explorer-reader understand; the machine itself makes its victim understand the nature of justice. Language is, of course, a primary vehicle for understanding, and Kafka's story dramatizes two radically opposed languages: verbal and physical. All efforts to bridge the distance between people, between matter and spirit, seem to fail, at least insofar as spoken language is concerned; the machine's mission is to create physical language, an unmediated script which is the reality of which it speaks. By writing the crime onto and into the flesh of the criminal, the machine offers a sublime and frightening figure of "visceral knowledge," of the open self as the opened self. By entering into the machine himself, the Officer undergoes the classic Kafka metamorphosis: he becomes the prisoner, and he thereby suffers knowledge. The entire parable may be seen as an illustration of the writer's yearning for a language so potent that the reader would experience, "in the flesh," the writer's words. Kafka's own narrative techniques aim at precisely such a metamorphosis in the reader.

Opportunity costs calculation in agent-based vehicle routing and scheduling

NARCIS (Netherlands)

Mes, Martijn R.K.; van der Heijden, Matthijs C.; Schuur, Peter

2006-01-01

In this paper we consider a real-time, dynamic pickup and delivery problem with timewindows where orders should be assigned to one of a set of competing transportation companies. Our approach decomposes the problem into a multi-agent structure where vehicle agents are responsible for the routing and

Predicting transmission of structure-borne sound power from machines by including terminal cross-coupling

DEFF Research Database (Denmark)

Ohlrich, Mogens

2011-01-01

of translational terminals in a global plane. This paired or bi-coupled power transmission represents the simplest case of cross-coupling. The procedure and quality of the predicted transmission using this improved technique is demonstrated experimentally for an electrical motor unit with an integrated radial fan......Structure-borne sound generated by audible vibration of machines in vehicles, equipment and house-hold appliances is often a major cause of noise. Such vibration of complex machines is mostly determined and quantified by measurements. It has been found that characterization of the vibratory source...

ANN Surface Roughness Optimization of AZ61 Magnesium Alloy Finish Turning: Minimum Machining Times at Prime Machining Costs

Directory of Open Access Journals (Sweden)

Adel Taha Abbas

2018-05-01

Full Text Available Magnesium alloys are widely used in aerospace vehicles and modern cars, due to their rapid machinability at high cutting speeds. A novel Edgeworth–Pareto optimization of an artificial neural network (ANN is presented in this paper for surface roughness (Ra prediction of one component in computer numerical control (CNC turning over minimal machining time (Tm and at prime machining costs (C. An ANN is built in the Matlab programming environment, based on a 4-12-3 multi-layer perceptron (MLP, to predict Ra, Tm, and C, in relation to cutting speed, vc, depth of cut, ap, and feed per revolution, fr. For the first time, a profile of an AZ61 alloy workpiece after finish turning is constructed using an ANN for the range of experimental values vc, ap, and fr. The global minimum length of a three-dimensional estimation vector was defined with the following coordinates: Ra = 0.087 μm, Tm = 0.358 min/cm3, C = $8.2973. Likewise, the corresponding finish-turning parameters were also estimated: cutting speed vc = 250 m/min, cutting depth ap = 1.0 mm, and feed per revolution fr = 0.08 mm/rev. The ANN model achieved a reliable prediction accuracy of ±1.35% for surface roughness.

Assessing a Novel Method to Reduce Anesthesia Machine Contamination: A Prospective, Observational Trial.

Science.gov (United States)

Biddle, Chuck J; George-Gay, Beverly; Prasanna, Praveen; Hill, Emily M; Davis, Thomas C; Verhulst, Brad

2018-01-01

Anesthesia machines are known reservoirs of bacterial species, potentially contributing to healthcare associated infections (HAIs). An inexpensive, disposable, nonpermeable, transparent anesthesia machine wrap (AMW) may reduce microbial contamination of the anesthesia machine. This study quantified the density and diversity of bacterial species found on anesthesia machines after terminal cleaning and between cases during actual anesthesia care to assess the impact of the AMW. We hypothesized reduced bioburden with the use of the AMW. In a prospective, experimental research design, the AMW was used in 11 surgical cases (intervention group) and not used in 11 control surgical cases. Cases were consecutively assigned to general surgical operating rooms. Seven frequently touched and difficult to disinfect "hot spots" were cultured on each machine preceding and following each case. The density and diversity of cultured colony forming units (CFUs) between the covered and uncovered machines were compared using Wilcoxon signed-rank test and Student's t -tests. There was a statistically significant reduction in CFU density and diversity when the AMW was employed. The protective effect of the AMW during regular anesthetic care provides a reliable and low-cost method to minimize the transmission of pathogens across patients and potentially reduces HAIs.

Grouping puts figure-ground assignment in context by constraining propagation of edge assignment.

Science.gov (United States)

Brooks, Joseph L; Brook, Joseph L; Driver, Jon

2010-05-01

Figure-ground organization involves the assignment of edges to a figural shape on one or the other side of each dividing edge. Established visual cues for edge assignment primarily concern relatively local rather than contextual factors. In the present article, we show that an assignment for a locally unbiased edge can be affected by an assignment of a remote contextual edge that has its own locally biased assignment. We find that such propagation of edge assignment from the biased remote context occurs only when the biased and unbiased edges are grouped. This new principle, whereby grouping constrains the propagation of figural edge assignment, emerges from both subjective reports and an objective short-term edge-matching task. It generalizes from moving displays involving grouping by common fate and collinearity, to static displays with grouping by similarity of edge-contrast polarity, or apparent occlusion. Our results identify a new contextual influence on edge assignment. They also identify a new mechanistic relation between grouping and figure-ground processes, whereby grouping between remote elements can constrain the propagation of edge assignment between those elements. Supplemental materials for this article may be downloaded from http://app.psychonomic-journals.org/content/supplemental.

FLEET ASSIGNMENT MODELLING

Directory of Open Access Journals (Sweden)

2016-01-01

Full Text Available The article is devoted to the airline scheduling process and methods of its modeling. This article describes the main stages of airline scheduling process (scheduling, fleet assignment, revenue management, operations, their features and interactions. The main part of scheduling process is fleet assignment. The optimal solution of the fleet assignment problem enables airlines to increase their incomes up to 3 % due to quality improving of connections and execution of the planned number of flights operated by less number of aircraft than usual or planned earlier. Fleet assignment of scheduling process is examined and Conventional Leg-Based Fleet Assignment Model is analyzed. Finally strong and weak aspects of the model (SWOT are released and applied. The article gives a critical analysis of FAM model, with the purpose of identi- fying possible options and constraints of its use (for example, in cases of short-term and long-term planning, changing the schedule or replacing the aircraft, as well as possible ways to improve the model.

Analysis and optimization of machining parameters of laser cutting for polypropylene composite

Science.gov (United States)

Deepa, A.; Padmanabhan, K.; Kuppan, P.

2017-11-01

Present works explains about machining of self-reinforced Polypropylene composite fabricated using hot compaction method. The objective of the experiment is to find optimum machining parameters for Polypropylene (PP). Laser power and Machining speed were the parameters considered in response to tensile test and Flexure test. Taguchi method is used for experimentation. Grey Relational Analysis (GRA) is used for multiple process parameter optimization. ANOVA (Analysis of Variance) is used to find impact for process parameter. Polypropylene has got the great application in various fields like, it is used in the form of foam in model aircraft and other radio-controlled vehicles, thin sheets (∼2-20μm) used as a dielectric, PP is also used in piping system, it is also been used in hernia and pelvic organ repair or protect new herrnis in the same location.

Cyclic Parameter Refinement of 4S-10 Hybrid Flux-Switching Motor for Lightweight Electric Vehicle

Science.gov (United States)

Rani, J. Abd; Sulaiman, E.; Kumar, R.

2017-08-01

A great deal of attention has been given to the reduction of lighting the vehicle because the lighter the vehicle the energy consumption is comparatively low. Hence, the lightweight electric vehicle was introduced for lower carbon footprint and the sizing of the vehicle itself. One of the components to reduce the weight of the vehicle is the propulsion system which comprised of electric motor functioning as the source of torque to drive the propulsion system of the machine. This paper presents the refinement methodology for the optimized design of the 4S-10P E-Core hybrid excitation flux switching motor. The purpose of the refinement methodology is to improve the torque production of the optimized motor. The result of the successful improvement of the torque production is justifiable for a lightweight electric vehicle to drive the propulsion system.

Vehicle Classification Using an Imbalanced Dataset Based on a Single Magnetic Sensor

Directory of Open Access Journals (Sweden)

Chang Xu

2018-05-01

Full Text Available This paper aims to improve the accuracy of automatic vehicle classifiers for imbalanced datasets. Classification is made through utilizing a single anisotropic magnetoresistive sensor, with the models of vehicles involved being classified into hatchbacks, sedans, buses, and multi-purpose vehicles (MPVs. Using time domain and frequency domain features in combination with three common classification algorithms in pattern recognition, we develop a novel feature extraction method for vehicle classification. These three common classification algorithms are the k-nearest neighbor, the support vector machine, and the back-propagation neural network. Nevertheless, a problem remains with the original vehicle magnetic dataset collected being imbalanced, and may lead to inaccurate classification results. With this in mind, we propose an approach called SMOTE, which can further boost the performance of classifiers. Experimental results show that the k-nearest neighbor (KNN classifier with the SMOTE algorithm can reach a classification accuracy of 95.46%, thus minimizing the effect of the imbalance.

Vehicle Classification Using an Imbalanced Dataset Based on a Single Magnetic Sensor.

Science.gov (United States)

Xu, Chang; Wang, Yingguan; Bao, Xinghe; Li, Fengrong

2018-05-24

This paper aims to improve the accuracy of automatic vehicle classifiers for imbalanced datasets. Classification is made through utilizing a single anisotropic magnetoresistive sensor, with the models of vehicles involved being classified into hatchbacks, sedans, buses, and multi-purpose vehicles (MPVs). Using time domain and frequency domain features in combination with three common classification algorithms in pattern recognition, we develop a novel feature extraction method for vehicle classification. These three common classification algorithms are the k-nearest neighbor, the support vector machine, and the back-propagation neural network. Nevertheless, a problem remains with the original vehicle magnetic dataset collected being imbalanced, and may lead to inaccurate classification results. With this in mind, we propose an approach called SMOTE, which can further boost the performance of classifiers. Experimental results show that the k-nearest neighbor (KNN) classifier with the SMOTE algorithm can reach a classification accuracy of 95.46%, thus minimizing the effect of the imbalance.

A modeling method for hybrid energy behaviors in flexible machining systems

International Nuclear Information System (INIS)

Li, Yufeng; He, Yan; Wang, Yan; Wang, Yulin; Yan, Ping; Lin, Shenlong

2015-01-01

Increasingly environmental and economic pressures have led to great concerns regarding the energy consumption of machining systems. Understanding energy behaviors of flexible machining systems is a prerequisite for improving energy efficiency of these systems. This paper proposes a modeling method to predict energy behaviors in flexible machining systems. The hybrid energy behaviors not only depend on the technical specification related of machine tools and workpieces, but are significantly affected by individual production scenarios. In the method, hybrid energy behaviors are decomposed into Structure-related energy behaviors, State-related energy behaviors, Process-related energy behaviors and Assignment-related energy behaviors. The modeling method for the hybrid energy behaviors is proposed based on Colored Timed Object-oriented Petri Net (CTOPN). The former two types of energy behaviors are modeled by constructing the structure of CTOPN, whist the latter two types of behaviors are simulated by applying colored tokens and associated attributes. Machining on two workpieces in the experimental workshop were undertaken to verify the proposed modeling method. The results showed that the method can provide multi-perspective transparency on energy consumption related to machine tools, workpieces as well as production management, and is particularly suitable for flexible manufacturing system when frequent changes in machining systems are often encountered. - Highlights: • Energy behaviors in flexible machining systems are modeled in this paper. • Hybrid characteristics of energy behaviors are examined from multiple viewpoints. • Flexible modeling method CTOPN is used to predict the hybrid energy behaviors. • This work offers a multi-perspective transparency on energy consumption

Vision based speed breaker detection for autonomous vehicle

Science.gov (United States)

C. S., Arvind; Mishra, Ritesh; Vishal, Kumar; Gundimeda, Venugopal

2018-04-01

In this paper, we are presenting a robust and real-time, vision-based approach to detect speed breaker in urban environments for autonomous vehicle. Our method is designed to detect the speed breaker using visual inputs obtained from a camera mounted on top of a vehicle. The method performs inverse perspective mapping to generate top view of the road and segment out region of interest based on difference of Gaussian and median filter images. Furthermore, the algorithm performs RANSAC line fitting to identify the possible speed breaker candidate region. This initial guessed region via RANSAC, is validated using support vector machine. Our algorithm can detect different categories of speed breakers on cement, asphalt and interlock roads at various conditions and have achieved a recall of 0.98.

Context-aware prioritization of information: an architecture for real-time in-vehicle information management

NARCIS (Netherlands)

Stoter, Arjan; Cornelisse, Erik; Dalmolen, Simon

2011-01-01

Human Machine Interfaces (HMIs) are the communication devices between in-vehicle applications and the driver. Frequently, independent HMIs are used for different applications which may cause information overload situations at the driver. Hence, a common HMI design that determines the application

Machine rates for selected forest harvesting machines

Science.gov (United States)

R.W. Brinker; J. Kinard; Robert Rummer; B. Lanford

2002-01-01

Very little new literature has been published on the subject of machine rates and machine cost analysis since 1989 when the Alabama Agricultural Experiment Station Circular 296, Machine Rates for Selected Forest Harvesting Machines, was originally published. Many machines discussed in the original publication have undergone substantial changes in various aspects, not...

Design and market considerations for axial flux superconducting electric machine design

Science.gov (United States)

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.

Development and Application of ANN Model for Worker Assignment into Virtual Cells of Large Sized Configurations

International Nuclear Information System (INIS)

Murali, R. V.; Fathi, Khalid; Puri, A. B.

2010-01-01

This paper presents an extended version of study already undertaken on development of an artificial neural networks (ANNs) model for assigning workforce into virtual cells under virtual cellular manufacturing systems (VCMS) environments. Previously, the same authors have introduced this concept and applied it to virtual cells of two-cell configuration and the results demonstrated that ANNs could be a worth applying tool for carrying out workforce assignments. In this attempt, three-cell configurations problems are considered for worker assignment task. Virtual cells are formed under dual resource constraint (DRC) context in which the number of available workers is less than the total number of machines available. Since worker assignment tasks are quite non-linear and highly dynamic in nature under varying inputs and conditions and, in parallel, ANNs have the ability to model complex relationships between inputs and outputs and find similar patterns effectively, an attempt was earlier made to employ ANNs into the above task. In this paper, the multilayered perceptron with feed forward (MLP-FF) neural network model has been reused for worker assignment tasks of three-cell configurations under DRC context and its performance at different time periods has been analyzed. The previously proposed worker assignment model has been reconfigured and cell formation solutions available for three-cell configuration in the literature are used in combination to generate datasets for training ANNs framework. Finally, results of the study have been presented and discussed.

Improved transistor-controlled and commutated brushless DC motors for electric vehicle propulsion

Science.gov (United States)

Demerdash, N. A.; Miller, R. H.; Nehl, T. W.; Nyamusa, T. A.

1983-01-01

The development, design, construction, and testing processes of two electronically (transistor) controlled and commutated permanent magnet brushless dc machine systems, for propulsion of electric vehicles are detailed. One machine system was designed and constructed using samarium cobalt for permanent magnets, which supply the rotor (field) excitation. Meanwhile, the other machine system was designed and constructed with strontium ferrite permanent magnets as the source of rotor (field) excitation. These machine systems were designed for continuous rated power output of 15 hp (11.2 kw), and a peak one minute rated power output of 35 hp (26.1 kw). Both power ratings are for a rated voltage of 115 volts dc, assuming a voltage drop in the source (battery) of about 5 volts. That is, an internal source voltage of 120 volts dc. Machine-power conditioner system computer-aided simulations were used extensively in the design process. These simulations relied heavily on the magnetic field analysis in these machines using the method of finite elements, as well as methods of modeling of the machine power conditioner system dynamic interaction. These simulation processes are detailed. Testing revealed that typical machine system efficiencies at 15 hp (11.2 kw) were about 88% and 84% for the samarium cobalt and strontium ferrite based machine systems, respectively. Both systems met the peak one minute rating of 35 hp.

Distributed tactical reasoning framework for intelligent vehicles

Science.gov (United States)

Sukthankar, Rahul; Pomerleau, Dean A.; Thorpe, Chuck E.

1998-01-01

In independent vehicle concepts for the Automated Highway System (AHS), the ability to make competent tactical-level decisions in real-time is crucial. Traditional approaches to tactical reasoning typically involve the implementation of large monolithic systems, such as decision trees or finite state machines. However, as the complexity of the environment grows, the unforeseen interactions between components can make modifications to such systems very challenging. For example, changing an overtaking behavior may require several, non-local changes to car-following, lane changing and gap acceptance rules. This paper presents a distributed solution to the problem. PolySAPIENT consists of a collection of autonomous modules, each specializing in a particular aspect of the driving task - classified by traffic entities rather than tactical behavior. Thus, the influence of the vehicle ahead on the available actions is managed by one reasoning object, while the implications of an approaching exit are managed by another. The independent recommendations form these reasoning objects are expressed in the form of votes and vetos over a 'tactical action space', and are resolved by a voting arbiter. This local independence enables PolySAPIENT reasoning objects to be developed independently, using a heterogenous implementation. PolySAPIENT vehicles are implemented in the SHIVA tactical highway simulator, whose vehicles are based on the Carnegie Mellon Navlab robots.

Evolutionary approaches for scheduling a flexible manufacturing system with automated guided vehicles and robots

Directory of Open Access Journals (Sweden)

Ramaraj Natarajan

2012-08-01

Full Text Available This paper addresses the scheduling of machines, an Automated Guided Vehicle (AGV and two robots in a Flexible Manufacturing System (FMS formed in three loop layouts, with objectives to minimize the makespan, mean flow time and mean tardiness. The scheduling optimization is carried out using Sheep Flock Heredity Algorithm (SFHA and Artificial Immune System (AIS algorithm. AGV is used for carrying jobs between the Load/Unload station and the machines. The robots are used for loading and unloading the jobs in the machines, and also used for transferring jobs between the machines. The algorithms are applied for test problems taken from the literature and the results obtained using the two algorithms are compared. The results indicate that SFHA performs better than AIS for this problem.

FY17 ISCR Scholar End-of-Assignment Report - Robbie Sadre

Energy Technology Data Exchange (ETDEWEB)

Sadre, R. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

2017-10-20

Throughout this internship assignment, I did various tasks that contributed towards the starting of the SASEDS (Safe Active Scanning for Energy Delivery Systems) and CES-21 (California Energy Systems for the 21st Century) projects in the SKYFALL laboratory. The goal of the SKYFALL laboratory is to perform modeling and simulation verification of transmission power system devices, while integrating with high-performance computing. The first thing I needed to do was acquire official Online LabVIEW training from National Instruments. Through these online tutorial modules, I learned the basics of LabVIEW, gaining experience in connecting to NI devices through the DAQmx API as well as LabVIEW basic programming techniques (structures, loops, state machines, front panel GUI design etc).

Design of a multi-vehicles delivery tours satisfying duration constraints

Energy Technology Data Exchange (ETDEWEB)

Langevin, A; Soumis, F

1987-01-01

The following organization was studied for the letter and parcel pick-up and delivery problem in an urban environment. The day is divided in periods of time in which each vehicle starts from a sorting centre, travels to a very precise area of the region, picks up and delivers letters and parcels, and returns to the depot to have the collected material sorted out for delivery during the following period. The intent of this approach is to have each zone serviced by one vehicle only, in order to facilitate the work of the dispatcher and routing of each vehicle. A method has been developed of partitioning an urban region into zones to be assigned, each one to a specific vehicle, so as to minimize the total number of vehicles used or the total distance travelled by all vehicles. The first part of the method determines the zones and the average number of points to visit. Then, a first refinement of the method takes into account the daily variability of the demand in each zone, whereas a second refinement examines the advantage of allowing some overlapping of zones for the purpose of having an overloaded vehicle relieved by one from an adjacent zone. 17 refs., 11 figs., 2 tabs.

Vehicle detection based on the use of shadow region and edge

Science.gov (United States)

Jeong, Sangheon; Kang, Seongkoo; Kim, Joongkyu

2013-07-01

Automotive and advanced driver assistance systems have attracted a great deal of attention lately. In these systems, effective and reliable vehicle detection is important because such systems can reduce the number of accidents and save human' lives. This paper describes an approach to detecting a forward vehicle using a camera mounted on the moving vehicle. In this paper, we describe two methods to detect a vehicle on the road. First, by using the vehicle's shadow, we can obtain the general location of the vehicular candidate. Second, we can identify the strong vertical edges at the left and right position of a vehicle. By combining the shadows and the edge, we can detect the vehicle's location. But other regions may also be detected, such as car windows, reflections, and illumination by the sun. In order to remove these other factors, defined as noises, we need to use a filter. After using the filter, we can calculate the exact location of the vehicle. Additionally, by using connected component labeling, we can obtain coordinates and establish the vehicle's location. Connected component labeling find all connected components in an image and assigns a unique label to all points in the same component. These methods are very useful for vehicle detection and the development of the driving assistance systems, and they can protect drivers' safety from having an accident.

Integration of Disaster Detection and Warning System for a Smart Vehicle

Directory of Open Access Journals (Sweden)

Chun-Chieh Wang

2014-02-01

Full Text Available For firefighters and rescuers, the disaster relief works are difficulty performed in the tunnels because of their constricted space. To reduce the losses of accident, the safety of tunnels and factories should be ordinarily kept under surveillance. Hence, a multisensor based smart tracked vehicle is designed for the application of autonomous detection and surveillance in this paper. Besides, multisensors, communication modules, wireless cameras, an electronic compass, and a GPS module are installed in the vehicle. The key feature is the integration of disaster detection and warning systems so that the vehicle can move autonomously. Furthermore, a LabVIEW graphical programming software is applied to design a human machine interface (HMI and integrate all systems such that the vehicle can be guided by High Speed Downlink Packet Access (HSHPA based remote control. Moreover, basic stamp microcontrollers are utilized as its control kernel such that the remote monitoring and control system (RMCS can be constructed successfully.

Multi-path transportation futures study : vehicle characterization and scenario analyses.

Energy Technology Data Exchange (ETDEWEB)

Plotkin, S. E.; Singh, M. K.; Energy Systems; TA Engineering; ORNL

2009-12-03

Projecting the future role of advanced drivetrains and fuels in the light vehicle market is inherently difficult, given the uncertainty (and likely volatility) of future oil prices, inadequate understanding of likely consumer response to new technologies, the relative infancy of several important new technologies with inevitable future changes in their performance and costs, and the importance - and uncertainty - of future government marketplace interventions (e.g., new regulatory standards or vehicle purchase incentives). This Multi-Path Transportation Futures (MP) Study has attempted to improve our understanding of this future role by examining several scenarios of vehicle costs, fuel prices, government subsidies, and other key factors. These are projections, not forecasts, in that they try to answer a series of 'what if' questions without assigning probabilities to most of the basic assumptions.

Assessing a Novel Method to Reduce Anesthesia Machine Contamination: A Prospective, Observational Trial

Directory of Open Access Journals (Sweden)

Chuck J. Biddle

2018-01-01

Full Text Available Background. Anesthesia machines are known reservoirs of bacterial species, potentially contributing to healthcare associated infections (HAIs. An inexpensive, disposable, nonpermeable, transparent anesthesia machine wrap (AMW may reduce microbial contamination of the anesthesia machine. This study quantified the density and diversity of bacterial species found on anesthesia machines after terminal cleaning and between cases during actual anesthesia care to assess the impact of the AMW. We hypothesized reduced bioburden with the use of the AMW. Methods. In a prospective, experimental research design, the AMW was used in 11 surgical cases (intervention group and not used in 11 control surgical cases. Cases were consecutively assigned to general surgical operating rooms. Seven frequently touched and difficult to disinfect “hot spots” were cultured on each machine preceding and following each case. The density and diversity of cultured colony forming units (CFUs between the covered and uncovered machines were compared using Wilcoxon signed-rank test and Student’s t-tests. Results. There was a statistically significant reduction in CFU density and diversity when the AMW was employed. Conclusion. The protective effect of the AMW during regular anesthetic care provides a reliable and low-cost method to minimize the transmission of pathogens across patients and potentially reduces HAIs.

Implementation Approach for Plug-in Electric Vehicles at Joint Base Lewis McChord. Task 4

Energy Technology Data Exchange (ETDEWEB)

Schey, Stephen [Idaho National Lab. (INL), Idaho Falls, ID (United States); Francfort, Jim [Idaho National Lab. (INL), Idaho Falls, ID (United States)

2014-12-01

This study focused on Joint Base Lewis McChord (JBLM), which is located in Washington State. Task 1 consisted of a survey of the non-tactical fleet of vehicles at JBLM to begin the review of vehicle mission assignments and the types of vehicles in service. In Task 2, daily operational characteristics of select vehicles were identified and vehicle movements were recorded in data loggers in order to characterize the vehicles’ missions. In Task 3, the results of the data analysis and observations were provided. Individual observations of the selected vehicles provided the basis for recommendations related to PEV adoption (i.e., whether a battery electric vehicle or plug-in hybrid electric vehicle [collectively referred to as PEVs] can fulfill the mission requirements0, as well as the basis for recommendations related to placement of PEV charging infrastructure. This report focuses on an implementation plan for the near-term adoption of PEVs into the JBLM fleet.

ANN Surface Roughness Optimization of AZ61 Magnesium Alloy Finish Turning: Minimum Machining Times at Prime Machining Costs.

Science.gov (United States)

Abbas, Adel Taha; Pimenov, Danil Yurievich; Erdakov, Ivan Nikolaevich; Taha, Mohamed Adel; Soliman, Mahmoud Sayed; El Rayes, Magdy Mostafa

2018-05-16

Magnesium alloys are widely used in aerospace vehicles and modern cars, due to their rapid machinability at high cutting speeds. A novel Edgeworth⁻Pareto optimization of an artificial neural network (ANN) is presented in this paper for surface roughness ( Ra ) prediction of one component in computer numerical control (CNC) turning over minimal machining time ( T m ) and at prime machining costs ( C ). An ANN is built in the Matlab programming environment, based on a 4-12-3 multi-layer perceptron (MLP), to predict Ra , T m , and C , in relation to cutting speed, v c , depth of cut, a p , and feed per revolution, f r . For the first time, a profile of an AZ61 alloy workpiece after finish turning is constructed using an ANN for the range of experimental values v c , a p , and f r . The global minimum length of a three-dimensional estimation vector was defined with the following coordinates: Ra = 0.087 μm, T m = 0.358 min/cm³, C = $8.2973. Likewise, the corresponding finish-turning parameters were also estimated: cutting speed v c = 250 m/min, cutting depth a p = 1.0 mm, and feed per revolution f r = 0.08 mm/rev. The ANN model achieved a reliable prediction accuracy of ±1.35% for surface roughness.

[A new machinability test machine and the machinability of composite resins for core built-up].

Science.gov (United States)

Iwasaki, N

2001-06-01

A new machinability test machine especially for dental materials was contrived. The purpose of this study was to evaluate the effects of grinding conditions on machinability of core built-up resins using this machine, and to confirm the relationship between machinability and other properties of composite resins. The experimental machinability test machine consisted of a dental air-turbine handpiece, a control weight unit, a driving unit of the stage fixing the test specimen, and so on. The machinability was evaluated as the change in volume after grinding using a diamond point. Five kinds of core built-up resins and human teeth were used in this study. The machinabilities of these composite resins increased with an increasing load during grinding, and decreased with repeated grinding. There was no obvious correlation between the machinability and Vickers' hardness; however, a negative correlation was observed between machinability and scratch width.

Marine Vehicle Sensor Network Architecture and Protocol Designs for Ocean Observation

Directory of Open Access Journals (Sweden)

Yeqiang Shu

2012-01-01

Full Text Available The micro-scale and meso-scale ocean dynamic processes which are nonlinear and have large variability, have a significant impact on the fisheries, natural resources, and marine climatology. A rapid, refined and sophisticated observation system is therefore needed in marine scientific research. The maneuverability and controllability of mobile sensor platforms make them a preferred choice to establish ocean observing networks, compared to the static sensor observing platform. In this study, marine vehicles are utilized as the nodes of mobile sensor networks for coverage sampling of a regional ocean area and ocean feature tracking. A synoptic analysis about marine vehicle dynamic control, multi vehicles mission assignment and path planning methods, and ocean feature tracking and observing techniques is given. Combined with the observation plan in the South China Sea, we provide an overview of the mobile sensor networks established with marine vehicles, and the corresponding simulation results.

Active and passive vehicle safety at Volkswagen accident research

Energy Technology Data Exchange (ETDEWEB)

Jungmichel, M.; Stanzel, M.; Zobel, R. [Volkswagen AG, Wolfsburg (Germany)

2001-07-01

Accident Analysis is an efficient means of improving vehicle passive safety and is used frequently and intensively. However, reliable data on accident causation is much more difficult to obtain. In most cases, one or more of the persons involved in an accident will face litigation and therefore are reluctant to provide the information that is essential to researchers. In addition, antilock brakes in almost every current vehicle have caused certain characteristic evidence, i.e. skid marks, to appear much less frequently than before. However, this evidence provides valuable information for assessing the reaction of the driver and his attempt to avoid the accident. In order to implement strategies of accident avoidance, accident causation must first be fully understood. Therefore, one of the assignments of the Volkswagen Accident Research Unit is to interpret global statistics, as well as to study single cases in order to come up with strategies for collision avoidance or mitigation. Currently, our primary concern is focused on active vehicle safety by researching vehicle behavior in the pre-crash phase. (orig.)

Dynamic cellular manufacturing system considering machine failure and workload balance

Science.gov (United States)

Rabbani, Masoud; Farrokhi-Asl, Hamed; Ravanbakhsh, Mohammad

2018-02-01

Machines are a key element in the production system and their failure causes irreparable effects in terms of cost and time. In this paper, a new multi-objective mathematical model for dynamic cellular manufacturing system (DCMS) is provided with consideration of machine reliability and alternative process routes. In this dynamic model, we attempt to resolve the problem of integrated family (part/machine cell) formation as well as the operators' assignment to the cells. The first objective minimizes the costs associated with the DCMS. The second objective optimizes the labor utilization and, finally, a minimum value of the variance of workload between different cells is obtained by the third objective function. Due to the NP-hard nature of the cellular manufacturing problem, the problem is initially validated by the GAMS software in small-sized problems, and then the model is solved by two well-known meta-heuristic methods including non-dominated sorting genetic algorithm and multi-objective particle swarm optimization in large-scaled problems. Finally, the results of the two algorithms are compared with respect to five different comparison metrics.

Taking Over Control From Highly Automated Vehicles in Complex Traffic Situations: The Role of Traffic Density.

Science.gov (United States)

Gold, Christian; Körber, Moritz; Lechner, David; Bengler, Klaus

2016-06-01

The aim of this study was to quantify the impact of traffic density and verbal tasks on takeover performance in highly automated driving. In highly automated vehicles, the driver has to occasionally take over vehicle control when approaching system limits. To ensure safety, the ability of the driver to regain control of the driving task under various driving situations and different driver states needs to be quantified. Seventy-two participants experienced takeover situations requiring an evasive maneuver on a three-lane highway with varying traffic density (zero, 10, and 20 vehicles per kilometer). In a between-subjects design, half of the participants were engaged in a verbal 20-Questions Task, representing speaking on the phone while driving in a highly automated vehicle. The presence of traffic in takeover situations led to longer takeover times and worse takeover quality in the form of shorter time to collision and more collisions. The 20-Questions Task did not influence takeover time but seemed to have minor effects on the takeover quality. For the design and evaluation of human-machine interaction in takeover situations of highly automated vehicles, the traffic state seems to play a major role, compared to the driver state, manipulated by the 20-Questions Task. The present results can be used by developers of highly automated systems to appropriately design human-machine interfaces and to assess the driver's time budget for regaining control. © 2016, Human Factors and Ergonomics Society.

Autonomous control of a locomotion vehicle

International Nuclear Information System (INIS)

Ichikawa, Yoshiaki; Senoh, Makoto; Miyata, Kenji

1984-01-01

A path planner and an execution system are proposed for autonomous vehicle control. The planner creates a near shortest path avoiding obstacles that are represented by combinations of circles and line segments on a two dimensional map. For realizing real time execution, path search procedures employ a heuristic pruning strategies in selecting a node to expand and in generating successor nodes. Nodes are selected for expansion in order, according to a cost assigned to each node. The cost is mainly evaluated by approximating a path length from the initial node to the goal node. In order to expand a node and to generate successor nodes, a specific search procedure is activated that finds positions avoiding obstacles in the direction of the goal, and creates successor nodes corresponding to the positions. The execution system, utilizing an ultrasonic range finder equipped to the vehicle performs a plan repair against unknown obstacles when echoes from the obstacles are observed. The plan repair is conducted by a map edition and replanning in such a way that new circles representing the echoes are added to the map. Obstacle avoidance tests with a vehicle controlled by microprocessors demonstrate the utility of heuristics just outlined. (author)

UOP LDR 300 All Assignments New

OpenAIRE

ADMIN

2018-01-01

UOP LDR 300 All Assignments New Check this A+ tutorial guideline at http://www.ldr300assignment.com/ldr-300-uop/ldr-300-all-assignments-latest For more classes visit http://www.ldr300assignment.com LDR 300 Week 1 Assignment Leadership Assessment (2 Papers) LDR 300 Week 2 Assignment Leadership Theories Matrix (2 Set) LDR 300 Week 2 Assignment Formulating Leadership Part I (2 Papers) LDR 300 Week 3 Assignment Interaction and Influence Amo...

Creation of operation algorithms for combined operation of anti-lock braking system (ABS) and electric machine included in the combined power plant

Science.gov (United States)

Bakhmutov, S. V.; Ivanov, V. G.; Karpukhin, K. E.; Umnitsyn, A. A.

2018-02-01

The paper considers the Anti-lock Braking System (ABS) operation algorithm, which enables the implementation of hybrid braking, i.e. the braking process combining friction brake mechanisms and e-machine (electric machine), which operates in the energy recovery mode. The provided materials focus only on the rectilinear motion of the vehicle. That the ABS task consists in the maintenance of the target wheel slip ratio, which depends on the tyre-road adhesion coefficient. The tyre-road adhesion coefficient was defined based on the vehicle deceleration. In the course of calculated studies, the following operation algorithm of hybrid braking was determined. At adhesion coefficient ≤0.1, driving axle braking occurs only due to the e-machine operating in the energy recovery mode. In other cases, depending on adhesion coefficient, the e-machine provides the brake torque, which changes from 35 to 100% of the maximum available brake torque. Virtual tests showed that values of the wheel slip ratio are close to the required ones. Thus, this algorithm makes it possible to implement hybrid braking by means of the two sources creating the brake torque.

Fair Package Assignment

Science.gov (United States)

Lahaie, Sébastien; Parkes, David C.

We consider the problem of fair allocation in the package assignment model, where a set of indivisible items, held by single seller, must be efficiently allocated to agents with quasi-linear utilities. A fair assignment is one that is efficient and envy-free. We consider a model where bidders have superadditive valuations, meaning that items are pure complements. Our central result is that core outcomes are fair and even coalition-fair over this domain, while fair distributions may not even exist for general valuations. Of relevance to auction design, we also establish that the core is equivalent to the set of anonymous-price competitive equilibria, and that superadditive valuations are a maximal domain that guarantees the existence of anonymous-price competitive equilibrium. Our results are analogs of core equivalence results for linear prices in the standard assignment model, and for nonlinear, non-anonymous prices in the package assignment model with general valuations.

A Constraint-Based Model for Fast Post-Disaster Emergency Vehicle Routing

Directory of Open Access Journals (Sweden)

Roberto Amadini

2013-12-01

Full Text Available Disasters like terrorist attacks, earthquakes, hurricanes, and volcano eruptions are usually unpredictable events that affect a high number of people. We propose an approach that could be used as a decision support tool for a post-disaster response that allows the assignment of victims to hospitals and organizes their transportation via emergency vehicles. By exploiting the synergy between Mixed Integer Programming and Constraint Programming techniques, we are able to compute the routing of the vehicles so as to rescue much more victims than both heuristic based and complete approaches in a very reasonable time.

Contribution to the design and the control of synchronous double excitation machines: hybrid vehicle application; Contribution a la conception et a la commande des machines synchrones a double excitation: application au vehicule hybride

Energy Technology Data Exchange (ETDEWEB)

Amara, Y

2001-12-01

Double excitation machines are synchronous machines where two excitation circuits coexist: one with permanent magnets and the other with windings. This study shows that double excitation allows to combine the advantages of synchronous machines with winded inductor with those of permanent magnet machines. This concept allows a better dimensioning of the converter-machine set and a better energy management. In order to allow the operation of permanent magnet machines over a wide range of speeds, it is necessary to have a magnetic reaction of the induced circuit of the same order than the excitation flux. On the other hand, the power factor is weaker and the power supply converter is over-dimensioned. The double excitation allows the permanent magnet machines to work over a large speed range with a better power factor, even when the magnetic reaction of the induced circuit is relatively weak with respect to the excitation flux. (J.S.)

Multi-sources model and control algorithm of an energy management system for light electric vehicles

International Nuclear Information System (INIS)

Hannan, M.A.; Azidin, F.A.; Mohamed, A.

2012-01-01

Highlights: ► An energy management system (EMS) is developed for a scooter under normal and heavy power load conditions. ► The battery, FC, SC, EMS, DC machine and vehicle dynamics are modeled and designed for the system. ► State-based logic control algorithms provide an efficient and feasible multi-source EMS for light electric vehicles. ► Vehicle’s speed and power are closely matched with the ECE-47 driving cycle under normal and heavy load conditions. ► Sources of energy changeover occurred at 50% of the battery state of charge level in heavy load conditions. - Abstract: This paper presents the multi-sources energy models and ruled based feedback control algorithm of an energy management system (EMS) for light electric vehicle (LEV), i.e., scooters. The multiple sources of energy, such as a battery, fuel cell (FC) and super-capacitor (SC), EMS and power controller, DC machine and vehicle dynamics are designed and modeled using MATLAB/SIMULINK. The developed control strategies continuously support the EMS of the multiple sources of energy for a scooter under normal and heavy power load conditions. The performance of the proposed system is analyzed and compared with that of the ECE-47 test drive cycle in terms of vehicle speed and load power. The results show that the designed vehicle’s speed and load power closely match those of the ECE-47 test driving cycle under normal and heavy load conditions. This study’s results suggest that the proposed control algorithm provides an efficient and feasible EMS for LEV.

The Machine within the Machine

CERN Multimedia

Katarina Anthony

2014-01-01

Although Virtual Machines are widespread across CERN, you probably won't have heard of them unless you work for an experiment. Virtual machines - known as VMs - allow you to create a separate machine within your own, allowing you to run Linux on your Mac, or Windows on your Linux - whatever combination you need.   Using a CERN Virtual Machine, a Linux analysis software runs on a Macbook. When it comes to LHC data, one of the primary issues collaborations face is the diversity of computing environments among collaborators spread across the world. What if an institute cannot run the analysis software because they use different operating systems? "That's where the CernVM project comes in," says Gerardo Ganis, PH-SFT staff member and leader of the CernVM project. "We were able to respond to experimentalists' concerns by providing a virtual machine package that could be used to run experiment software. This way, no matter what hardware they have ...

Consensus seeking, formation keeping, and trajectory tracking in multiple vehicle cooperative control

Science.gov (United States)

Ren, Wei

Cooperative control problems for multiple vehicle systems can be categorized as either formation control problems with applications to mobile robots, unmanned air vehicles, autonomous underwater vehicles, satellites, aircraft, spacecraft, and automated highway systems, or non-formation control problems such as task assignment, cooperative transport, cooperative role assignment, air traffic control, cooperative timing, and cooperative search. The cooperative control of multiple vehicle systems poses significant theoretical and practical challenges. For cooperative control strategies to be successful, numerous issues must be addressed. We consider three important and correlated issues: consensus seeking, formation keeping, and trajectory tracking. For consensus seeking, we investigate algorithms and protocols so that a team of vehicles can reach consensus on the values of the coordination data in the presence of imperfect sensors, communication dropout, sparse communication topologies, and noisy and unreliable communication links. The main contribution of this dissertation in this area is that we show necessary and/or sufficient conditions for consensus seeking with limited, unidirectional, and unreliable information exchange under fixed and switching interaction topologies (through either communication or sensing). For formation keeping, we apply a so-called "virtual structure" approach to spacecraft formation flying and multi-vehicle formation maneuvers. As a result, single vehicle path planning and trajectory generation techniques can be employed for the virtual structure while trajectory tracking strategies can be employed for each vehicle. The main contribution of this dissertation in this area is that we propose a decentralized architecture for multiple spacecraft formation flying in deep space with formation feedback introduced. This architecture ensures the necessary precision in the presence of actuator saturation, internal and external disturbances, and

Development of iFab (Instant Foundry Adaptive Through Bits) Manufacturing Process and Machine Library

Science.gov (United States)

2012-08-01

input shaft , pump, gearbox, rack & pinion… Wheel assy wheel, tire, drive hub, lug, spindle , bearing… Braking brake disc/drum, caliper, friction...processes and associated machines is provided. Progress with respect to Task 3 (to design and develop the Manufacturing Capability Modeling Environment...of Military Ground Vehicle Design , Materials, and Processes ............... 4 4.2 Task 2 Manufacturing Knowledge Characterization

The H-Metaphor as a Guideline for Vehicle Automation and Interaction

Science.gov (United States)

Flemisch, Frank O.; Adams, Catherine A.; Conway, Sheila R.; Goodrich, Ken H.; Palmer, Michael T.; Schutte, Paul C.

2003-01-01

Good design is not free of form. It does not necessarily happen through a mere sampling of technologies packaged together, through pure analysis, or just by following procedures. Good design begins with inspiration and a vision, a mental image of the end product, which can sometimes be described with a design metaphor. A successful example from the 20th century is the desktop metaphor, which took a real desktop as an orientation for the manipulation of electronic documents on a computer. Initially defined by Xerox, then refined by Apple and others, it could be found on almost every computer by the turn of the 20th century. This paper sketches a specific metaphor for the emerging field of highly automated vehicles, their interactions with human users and with other vehicles. In the introduction, general questions on vehicle automation are raised and related to the physical control of conventional vehicles and to the automation of some late 20th century vehicles. After some words on design metaphors, the H-Metaphor is introduced. More details of the metaphor's source are described and their application to human-machine interaction, automation and management of intelligent vehicles sketched. Finally, risks and opportunities to apply the metaphor to technical applications are discussed.

Influence of Electric Discharges on Bearings of Electric Machines

Directory of Open Access Journals (Sweden)

Karel Chmelik

2006-01-01

Full Text Available I the last time many articles were found out discussed about shaft voltage, bearing currents and their influence on lifetime and reliability of electric machines bearings. This is associated with extension of use of static converters for control drives for DC motors feeding in the past and for induction motors feeding from frequency converters in the last time. It is known from our own experiences that not all failures assigned to bearing currents were their real reason and we also know how hardly the mentioned currents can be measured on real machines and how work-intensive and expensive is to detect real reason of the failure on damaged bearing. We will not concern with basics of classical bearing currents in this paper, because they were known and studied in the beginning of the last century but our own investigations will be presented.

Design and Performance Improvement of AC Machines Sharing a Common Stator

Science.gov (United States)

Guo, Lusu

With the increasing demand on electric motors in various industrial applications, especially electric powered vehicles (electric cars, more electric aircrafts and future electric ships and submarines), both synchronous reluctance machines (SynRMs) and interior permanent magnet (IPM) machines are recognized as good candidates for high performance variable speed applications. Developing a single stator design which can be used for both SynRM and IPM motors is a good way to reduce manufacturing and maintenance cost. SynRM can be used as a low cost solution for many electric driving applications and IPM machines can be used in power density crucial circumstances or work as generators to meet the increasing demand for electrical power on board. In this research, SynRM and IPM machines are designed sharing a common stator structure. The prototype motors are designed with the aid of finite element analysis (FEA). Machine performances with different stator slot and rotor pole numbers are compared by FEA. An 18-slot, 4-pole structure is selected based on the comparison for this prototype design. Sometimes, torque pulsation is the major drawback of permanent magnet synchronous machines. There are several sources of torque pulsations, such as back-EMF distortion, inductance variation and cogging torque due to presence of permanent magnets. To reduce torque pulsations in permanent magnet machines, all the efforts can be classified into two categories: one is from the design stage, the structure of permanent magnet machines can be optimized with the aid of finite element analysis. The other category of reducing torque pulsation is after the permanent magnet machine has been manufactured or the machine structure cannot be changed because of other reasons. The currents fed into the permanent magnet machine can be controlled to follow a certain profile which will make the machine generate a smoother torque waveform. Torque pulsation reduction methods in both categories will be

Detuning Minimization of Induction Motor Drive System for Alternative Energy Vehicles

Directory of Open Access Journals (Sweden)

Habibur Rehman

2015-08-01

Full Text Available This paper evaluates different types of AC machines and various control techniques for their suitability for the drive system of Alternative Energy Vehicles (AEV. An Indirect Field Oriented (IFO drive system for the AEV application is chosen and its major problem of detuning is addressed by designing an offline and an online rotor resistance adaptation technique. The offline scheme sets the slip gain at various operating conditions based on the fact that if the rotor resistance is set correctly and field orientation is achieved, then there should be a linear relationship between the torque current and the output torque. The online technique is designed using Model Reference Adaptive System (MRAS for the rotor resistance adaptation. For an ideal field oriented machine, the rotor flux along the q-axis should be zero. This condition acts as a reference model for the proposed MRAS scheme. The current model flux observer in the synchronous frame of reference is selected as an adjustable model and its rotor resistance is tuned so that the flux along the q-axis becomes zero. The effectiveness of the offline tuning scheme is evident through performance validation of the drive system, which is implemented in a real Ford vehicle. The experimental results obtained while driving the test vehicle are included in the paper while the proposed online scheme is validated on a 3.75 kW prototype induction motor.

Advances in Integrated Vehicle Thermal Management and Numerical Simulation

Directory of Open Access Journals (Sweden)

Yan Wang

2017-10-01

Full Text Available With the increasing demands for vehicle dynamic performance, economy, safety and comfort, and with ever stricter laws concerning energy conservation and emissions, vehicle power systems are becoming much more complex. To pursue high efficiency and light weight in automobile design, the power system and its vehicle integrated thermal management (VITM system have attracted widespread attention as the major components of modern vehicle technology. Regarding the internal combustion engine vehicle (ICEV, its integrated thermal management (ITM mainly contains internal combustion engine (ICE cooling, turbo-charged cooling, exhaust gas recirculation (EGR cooling, lubrication cooling and air conditioning (AC or heat pump (HP. As for electric vehicles (EVs, the ITM mainly includes battery cooling/preheating, electric machines (EM cooling and AC or HP. With the rational effective and comprehensive control over the mentioned dynamic devices and thermal components, the modern VITM can realize collaborative optimization of multiple thermodynamic processes from the aspect of system integration. Furthermore, the computer-aided calculation and numerical simulation have been the significant design methods, especially for complex VITM. The 1D programming can correlate multi-thermal components and the 3D simulating can develop structuralized and modularized design. Additionally, co-simulations can virtualize simulation of various thermo-hydraulic behaviors under the vehicle transient operational conditions. This article reviews relevant researching work and current advances in the ever broadening field of modern vehicle thermal management (VTM. Based on the systematic summaries of the design methods and applications of ITM, future tasks and proposals are presented. This article aims to promote innovation of ITM, strengthen the precise control and the performance predictable ability, furthermore, to enhance the level of research and development (R&D.

Integration of passive driver-assistance systems with on-board vehicle systems

Science.gov (United States)

Savchenko, V. V.; Poddubko, S. N.

2018-02-01

Implementation in OIAS such functions as driver’s state monitoring and high-precision calculation of the current navigation coordinates of the vehicle, modularity of the OIAS construction and the possible increase in the functionality through integration with other onboard systems has a promising development future. The development of intelligent transport systems and their components allows setting and solving fundamentally new tasks for the safety of human-to-machine transport systems, and the automatic analysis of heterogeneous information flows provides a synergistic effect. The analysis of cross-modal information exchange in human-machine transport systems, from uniform methodological points of view, will allow us, with an accuracy acceptable for solving applied problems, to form in real time an integrated assessment of the state of the basic components of the human-to-machine system and the dynamics in changing situation-centered environment, including the external environment, in their interrelations.

Evaluation of connected vehicle impact on mobility and mode choice

Directory of Open Access Journals (Sweden)

Simon Minelli

2015-10-01

Full Text Available Connected vehicle is emerging as a solution to exacerbating congestion problems in urban areas. It is important to understand the impacts of connected vehicle on network and travel behavior of road users. The main objective of this paper is to evaluate the impact of connected vehicle on the mode choice and mobility of transportation networks. An iterative methodology was used in this paper where demands for various modes were modified based on the changes in travel time between each origin-destination (OD pair caused by introduction of connected vehicle. Then a traffic assignment was performed in a micro-simulation model, which was able to accurately simulate vehicle-to-vehicle communication. It is assumed that vehicles are equipped with a dynamic route guidance technology to choose their own route using real-time traffic information obtained through communication. The travel times obtained from the micro-simulation model were compared with a base scenario with no connected vehicle. The methodology was tested for a portion of Downtown Toronto, Ontario, Canada. In order to quantify changes in mode share with changes in travel time associated with each OD pair, mode choice models were developed for auto, transit, cycling and pedestrians using data mainly from the Transportation Tomorrow Survey. The impact of connected vehicle on mode choice was evaluated for different market penetrations of connected vehicle. The results of this study show that average travel times for the whole auto mode will generally increase, with the largest increase from connected vehicles. This causes an overall move away from the auto mode for high market penetrations if a dynamic route guidance algorithm is implemented.

A Crowd-Based Intelligence Approach for Measurable Security, Privacy, and Dependability in Internet of Automated Vehicles with Vehicular Fog

Directory of Open Access Journals (Sweden)

Ashish Rauniyar

2018-01-01

Full Text Available With the advent of Internet of things (IoT and cloud computing technologies, we are in the era of automation, device-to-device (D2D and machine-to-machine (M2M communications. Automated vehicles have recently gained a huge attention worldwide, and it has created a new wave of revolution in automobile industries. However, in order to fully establish automated vehicles and their connectivity to the surroundings, security, privacy, and dependability always remain a crucial issue. One cannot deny the fact that such automatic vehicles are highly vulnerable to different kinds of security attacks. Also, today’s such systems are built from generic components. Prior analysis of different attack trends and vulnerabilities enables us to deploy security solutions effectively. Moreover, scientific research has shown that a “group” can perform better than individuals in making decisions and predictions. Therefore, this paper deals with the measurable security, privacy, and dependability of automated vehicles through the crowd-based intelligence approach that is inspired from swarm intelligence. We have studied three use case scenarios of automated vehicles and systems with vehicular fog and have analyzed the security, privacy, and dependability metrics of such systems. Our systematic approaches to measuring efficient system configuration, security, privacy, and dependability of automated vehicles are essential for getting the overall picture of the system such as design patterns, best practices for configuration of system, metrics, and measurements.

Sensor Architecture and Task Classification for Agricultural Vehicles and Environments

Directory of Open Access Journals (Sweden)

Francisco Rovira-Más

2010-12-01

Full Text Available The long time wish of endowing agricultural vehicles with an increasing degree of autonomy is becoming a reality thanks to two crucial facts: the broad diffusion of global positioning satellite systems and the inexorable progress of computers and electronics. Agricultural vehicles are currently the only self-propelled ground machines commonly integrating commercial automatic navigation systems. Farm equipment manufacturers and satellite-based navigation system providers, in a joint effort, have pushed this technology to unprecedented heights; yet there are many unresolved issues and an unlimited potential still to uncover. The complexity inherent to intelligent vehicles is rooted in the selection and coordination of the optimum sensors, the computer reasoning techniques to process the acquired data, and the resulting control strategies for automatic actuators. The advantageous design of the network of onboard sensors is necessary for the future deployment of advanced agricultural vehicles. This article analyzes a variety of typical environments and situations encountered in agricultural fields, and proposes a sensor architecture especially adapted to cope with them. The strategy proposed groups sensors into four specific subsystems: global localization, feedback control and vehicle pose, non-visual monitoring, and local perception. The designed architecture responds to vital vehicle tasks classified within three layers devoted to safety, operative information, and automatic actuation. The success of this architecture, implemented and tested in various agricultural vehicles over the last decade, rests on its capacity to integrate redundancy and incorporate new technologies in a practical way.

Plagiarism-Proofing Assignments

Science.gov (United States)

Johnson, Doug

2004-01-01

Mr. Johnson has discovered that the higher the level of student engagement and creativity, the lower the probability of plagiarism. For teachers who would like to see such desirable results, he describes the characteristics of assignments that are most likely to produce them. Two scenarios of types of assignments that avoid plagiarism are…

Effect of Machining Velocity in Nanoscale Machining Operations

International Nuclear Information System (INIS)

Islam, Sumaiya; Khondoker, Noman; Ibrahim, Raafat

2015-01-01

The aim of this study is to investigate the generated forces and deformations of single crystal Cu with (100), (110) and (111) crystallographic orientations at nanoscale machining operation. A nanoindenter equipped with nanoscratching attachment was used for machining operations and in-situ observation of a nano scale groove. As a machining parameter, the machining velocity was varied to measure the normal and cutting forces. At a fixed machining velocity, different levels of normal and cutting forces were generated due to different crystallographic orientations of the specimens. Moreover, after machining operation percentage of elastic recovery was measured and it was found that both the elastic and plastic deformations were responsible for producing a nano scale groove within the range of machining velocities from 250-1000 nm/s. (paper)

[Risk factors for road traffic injury in agricultural vehicle drivers].

Science.gov (United States)

Cui, M J; Chen, Y; Li, Y; Hu, J; Zhang, X J

2017-08-20

Objective: To examine the risk factors for road traffic injury in agricultural vehicle drivers. Methods: A total of 103 drivers (who had suffered agricultural vehicle road traffic injury within the past year based on the road traffic injury registrar from the Traffic Management Bureau) who were involved in the annual agricultural vehicle inspection from December 2014 to January 2015 were randomly sampled from the Yixing Agricultural Vehicle Station as the case group for this study. Based on a 1∶2 assignment ratio and matched for sex, age, and education, a total of 206 drivers who had not suffered any agricultural vehicle road traffic injury within the past year were selected as the control group. The general information, vehicle information, driving information, driving behavior, and accident details of the agricultural vehicle drivers were analyzed. Results: The incidence rate of road traffic injury was 7.24% given the 103 agricultural vehicle drivers who had suffered agricultural vehicle road traffic injury in the past year. Univariate logistic regression analysis showed that drinking, debt, pressure, history of car accident, history of drunk driving, smoking and phone use during driving, fatigue driving, and driving with illness were the risk factors for road traffic injury in agricultural vehicle drivers ( OR =2.332, 2.429, 19.778, 5.589, 8.517, 2.125, 3.203, 10.249 and 5.639, respectively) . Multivariate logistic regression analysis also demonstrated that pressure, history of car accident, history of drunk driving, fatigue driving, and driving with illness were the risk factors for road traffic injury in agricultural vehicle drivers ( OR =12.139, 11.184, 6.729, 5.939, and 6.544, respectively) . Conclusion: Pressure, history of car accident, history of drunk driving, fatigue driving, and driving with illness are the major risk factors for road traffic injury in agricultural vehicle drivers.

Simulation of hybrid vehicle propulsion with an advanced battery model

Energy Technology Data Exchange (ETDEWEB)

Nallabolu, S.; Kostetzer, L.; Rudnyi, E. [CADFEM GmbH, Grafing (Germany); Geppert, M.; Quinger, D. [LION Smart GmbH, Frieding (Germany)

2011-07-01

In the recent years there has been observed an increasing concern about global warming and greenhouse gas emissions. In addition to the environmental issues the predicted scarcity of oil supplies and the dramatic increase in oil price puts new demands on vehicle design. As a result energy efficiency and reduced emission have become one of main selling point for automobiles. Hybrid electric vehicles (HEV) have therefore become an interesting technology for the governments and automotive industries. HEV are more complicated compared to conventional vehicles due to the fact that these vehicles contain more electrical components such as electric machines, power electronics, electronic continuously variable transmissions (CVT), and embedded powertrain controllers. Advanced energy storage devices and energy converters, such as Li-ion batteries, ultracapacitors, and fuel cells are also considered. A detailed vehicle model used for an energy flow analysis and vehicle performance simulation is necessary. Computer simulation is indispensible to facilitate the examination of the vast hybrid electric vehicle design space with the aim to predict the vehicle performance over driving profiles, estimate fuel consumption and the pollution emissions. There are various types of mathematical models and simulators available to perform system simulation of vehicle propulsion. One of the standard methods to model the complete vehicle powertrain is ''backward quasistatic modeling''. In this method vehicle subsystems are defined based on experiential models in the form of look-up tables and efficiency maps. The interaction between adjacent subsystems of the vehicle is defined through the amount of power flow. Modeling the vehicle subsystems like motor, engine, gearbox and battery is under this technique is based on block diagrams. The vehicle model is applied in two case studies to evaluate the vehicle performance and fuel consumption. In the first case study the affect

HUMAN DECISIONS AND MACHINE PREDICTIONS.

Science.gov (United States)

Kleinberg, Jon; Lakkaraju, Himabindu; Leskovec, Jure; Ludwig, Jens; Mullainathan, Sendhil

2018-02-01

Can machine learning improve human decision making? Bail decisions provide a good test case. Millions of times each year, judges make jail-or-release decisions that hinge on a prediction of what a defendant would do if released. The concreteness of the prediction task combined with the volume of data available makes this a promising machine-learning application. Yet comparing the algorithm to judges proves complicated. First, the available data are generated by prior judge decisions. We only observe crime outcomes for released defendants, not for those judges detained. This makes it hard to evaluate counterfactual decision rules based on algorithmic predictions. Second, judges may have a broader set of preferences than the variable the algorithm predicts; for instance, judges may care specifically about violent crimes or about racial inequities. We deal with these problems using different econometric strategies, such as quasi-random assignment of cases to judges. Even accounting for these concerns, our results suggest potentially large welfare gains: one policy simulation shows crime reductions up to 24.7% with no change in jailing rates, or jailing rate reductions up to 41.9% with no increase in crime rates. Moreover, all categories of crime, including violent crimes, show reductions; and these gains can be achieved while simultaneously reducing racial disparities. These results suggest that while machine learning can be valuable, realizing this value requires integrating these tools into an economic framework: being clear about the link between predictions and decisions; specifying the scope of payoff functions; and constructing unbiased decision counterfactuals. JEL Codes: C10 (Econometric and statistical methods and methodology), C55 (Large datasets: Modeling and analysis), K40 (Legal procedure, the legal system, and illegal behavior).

Active flywheel control for hybrid vehicle; Compensation active des pulsations de couple dans un vehicule hybride

Energy Technology Data Exchange (ETDEWEB)

Tnani, S.; Coirault, P.; Champenois, G. [Ecole Superieure d' Ingenieurs, Lab. d' Automatique et d' Informatique Industrielle, 86 - Poitiers (France)

2005-01-01

In the paper, the authors propose a novel control strategy of torque ripple on hybrid vehicle. The combustion engine ripple's are reduced by using an active filter and an AC machine which is mounted on the crank-shaft to generate on inverse torque sequence. The control strategy is based on a multi-objectives state feedback synthesis. A complete modelling of the hybrid propulsion of the vehicle is achieved. Simulation results highlight the interest of the control scheme. (authors)

Virtual screening by a new Clustering-based Weighted Similarity Extreme Learning Machine approach.

Science.gov (United States)

Pasupa, Kitsuchart; Kudisthalert, Wasu

2018-01-01

Machine learning techniques are becoming popular in virtual screening tasks. One of the powerful machine learning algorithms is Extreme Learning Machine (ELM) which has been applied to many applications and has recently been applied to virtual screening. We propose the Weighted Similarity ELM (WS-ELM) which is based on a single layer feed-forward neural network in a conjunction of 16 different similarity coefficients as activation function in the hidden layer. It is known that the performance of conventional ELM is not robust due to random weight selection in the hidden layer. Thus, we propose a Clustering-based WS-ELM (CWS-ELM) that deterministically assigns weights by utilising clustering algorithms i.e. k-means clustering and support vector clustering. The experiments were conducted on one of the most challenging datasets-Maximum Unbiased Validation Dataset-which contains 17 activity classes carefully selected from PubChem. The proposed algorithms were then compared with other machine learning techniques such as support vector machine, random forest, and similarity searching. The results show that CWS-ELM in conjunction with support vector clustering yields the best performance when utilised together with Sokal/Sneath(1) coefficient. Furthermore, ECFP_6 fingerprint presents the best results in our framework compared to the other types of fingerprints, namely ECFP_4, FCFP_4, and FCFP_6.

Hybrid systems, optimal control and hybrid vehicles theory, methods and applications

CERN Document Server

Böhme, Thomas J

2017-01-01

This book assembles new methods showing the automotive engineer for the first time how hybrid vehicle configurations can be modeled as systems with discrete and continuous controls. These hybrid systems describe naturally and compactly the networks of embedded systems which use elements such as integrators, hysteresis, state-machines and logical rules to describe the evolution of continuous and discrete dynamics and arise inevitably when modeling hybrid electric vehicles. They can throw light on systems which may otherwise be too complex or recondite. Hybrid Systems, Optimal Control and Hybrid Vehicles shows the reader how to formulate and solve control problems which satisfy multiple objectives which may be arbitrary and complex with contradictory influences on fuel consumption, emissions and drivability. The text introduces industrial engineers, postgraduates and researchers to the theory of hybrid optimal control problems. A series of novel algorithmic developments provides tools for solving engineering pr...

Prediction of Machine Tool Condition Using Support Vector Machine

International Nuclear Information System (INIS)

Wang Peigong; Meng Qingfeng; Zhao Jian; Li Junjie; Wang Xiufeng

2011-01-01

Condition monitoring and predicting of CNC machine tools are investigated in this paper. Considering the CNC machine tools are often small numbers of samples, a condition predicting method for CNC machine tools based on support vector machines (SVMs) is proposed, then one-step and multi-step condition prediction models are constructed. The support vector machines prediction models are used to predict the trends of working condition of a certain type of CNC worm wheel and gear grinding machine by applying sequence data of vibration signal, which is collected during machine processing. And the relationship between different eigenvalue in CNC vibration signal and machining quality is discussed. The test result shows that the trend of vibration signal Peak-to-peak value in surface normal direction is most relevant to the trend of surface roughness value. In trends prediction of working condition, support vector machine has higher prediction accuracy both in the short term ('One-step') and long term (multi-step) prediction compared to autoregressive (AR) model and the RBF neural network. Experimental results show that it is feasible to apply support vector machine to CNC machine tool condition prediction.

Evaluation of half wave induction motor drive for use in passenger vehicles

Science.gov (United States)

Hoft, R. G.; Kawamura, A.; Goodarzi, A.; Yang, G. Q.; Erickson, C. L.

1985-01-01

Research performed at the University of Missouri-Columbia to devise and design a lower cost inverter induction motor drive for electrical propulsion of passenger vehicles is described. A two phase inverter motor system is recommended. The new design is predicted to provide comparable vehicle performance, improved reliability and a cost advantage for a high production vehicle, decreased total rating of the power semiconductor switches, and a somewhat simpler control hardware compared to the conventional three phase bridge inverter motor drive system. The major disadvantages of the two phase inverter motor drive are that it is larger and more expensive than a three phase machine, the design of snubbers for the power leakage inductances produce higher transient voltages, and the torque pulsations are relatively large because of the necessity to limit the inverter switching frequency to achieve high efficiency.

Environmentally Friendly Machining

CERN Document Server

Dixit, U S; Davim, J Paulo

2012-01-01

Environment-Friendly Machining provides an in-depth overview of environmentally-friendly machining processes, covering numerous different types of machining in order to identify which practice is the most environmentally sustainable. The book discusses three systems at length: machining with minimal cutting fluid, air-cooled machining and dry machining. Also covered is a way to conserve energy during machining processes, along with useful data and detailed descriptions for developing and utilizing the most efficient modern machining tools. Researchers and engineers looking for sustainable machining solutions will find Environment-Friendly Machining to be a useful volume.

Asynchronous vehicle pose correction using visual detection of ground features

International Nuclear Information System (INIS)

Harnarinesingh, Randy E S; Syan, Chanan S

2014-01-01

The inherent noise associated with odometry manifests itself as errors in localization for autonomous vehicles. Visual odometry has been previously used in order to supplement classical vehicle odometry. However, visual odometry is limited in its ability to reduce errors in localization for large travel distances that entail the cumulative summing of individual frame-to-frame image errors. In this paper, a novel machine vision approach for tiled surfaces is proposed to address this problem. Tile edges in a laboratory environment are used to define a travel trajectory for the Quansar Qbot (autonomous vehicle) built on the iRobot iRoomba platform with a forward facing camera. Tile intersections are used to enable asynchronous error recovery for vehicle position and orientation. The proposed approach employs real-time image classification and is feasible for error mitigation for large travel distances. The average position error for an 8m travel distance using classical odometry was measured to be 0.28m. However, implementation of the proposed approach resulted in an error of 0.028m. The proposed approach therefore significantly reduces pose estimation error and could be used to supplement existing modalities such as GPS and Laser-based range sensors

Machine Learning and Inverse Problem in Geodynamics

Science.gov (United States)

Shahnas, M. H.; Yuen, D. A.; Pysklywec, R.

2017-12-01

During the past few decades numerical modeling and traditional HPC have been widely deployed in many diverse fields for problem solutions. However, in recent years the rapid emergence of machine learning (ML), a subfield of the artificial intelligence (AI), in many fields of sciences, engineering, and finance seems to mark a turning point in the replacement of traditional modeling procedures with artificial intelligence-based techniques. The study of the circulation in the interior of Earth relies on the study of high pressure mineral physics, geochemistry, and petrology where the number of the mantle parameters is large and the thermoelastic parameters are highly pressure- and temperature-dependent. More complexity arises from the fact that many of these parameters that are incorporated in the numerical models as input parameters are not yet well established. In such complex systems the application of machine learning algorithms can play a valuable role. Our focus in this study is the application of supervised machine learning (SML) algorithms in predicting mantle properties with the emphasis on SML techniques in solving the inverse problem. As a sample problem we focus on the spin transition in ferropericlase and perovskite that may cause slab and plume stagnation at mid-mantle depths. The degree of the stagnation depends on the degree of negative density anomaly at the spin transition zone. The training and testing samples for the machine learning models are produced by the numerical convection models with known magnitudes of density anomaly (as the class labels of the samples). The volume fractions of the stagnated slabs and plumes which can be considered as measures for the degree of stagnation are assigned as sample features. The machine learning models can determine the magnitude of the spin transition-induced density anomalies that can cause flow stagnation at mid-mantle depths. Employing support vector machine (SVM) algorithms we show that SML techniques

Weight optimization of an aerobrake structural concept for a lunar transfer vehicle

Science.gov (United States)

Bush, Lance B.; Unal, Resit; Rowell, Lawrence F.; Rehder, John J.

1992-01-01

An aerobrake structural concept for a lunar transfer vehicle was weight optimized through the use of the Taguchi design method, finite element analyses, and element sizing routines. Six design parameters were chosen to represent the aerobrake structural configuration. The design parameters included honeycomb core thickness, diameter-depth ratio, shape, material, number of concentric ring frames, and number of radial frames. Each parameter was assigned three levels. The aerobrake structural configuration with the minimum weight was 44 percent less than the average weight of all the remaining satisfactory experimental configurations. In addition, the results of this study have served to bolster the advocacy of the Taguchi method for aerospace vehicle design. Both reduced analysis time and an optimized design demonstrated the applicability of the Taguchi method to aerospace vehicle design.

Stirling engine electric hybrid vehicle propulsion system conceptual design study. Final report

Energy Technology Data Exchange (ETDEWEB)

Dochat, G; Artiles, A; Killough, J; Ray, A; Chen, H S

1978-08-01

Results of a six-month study to characterize a series Stirling engine electric hybrid vehicle propulsion system are presented. The Stirling engine was selected as the heat conversion element to exploit the high efficiency (> .36), low pollution, multi-fuel and quiet operation of this machine. A free-piston Stirling engine driving a linear alternator in a hermatically sealed enclosure was chosen to gain the reliability, long life, and maintenance free characteristics of a sealed unit. The study performs trade off evaluations, selection of engine, battery, motor and inverter size, optimization of components, and develops a conceptual design and characterization of the total propulsion system. The conclusion of the study is that a Stirling engine electric hybrid propulsion system can be used successfully to augment the battery storage of a passenger vehicle and will result in significant savings of petroleum energy over present passenger vehicles. The performance and range augmentation of the hybrid design results in significant improvements over an all electric vehicle. The hybrid will be capable of performing 99% of the passenger vehicle annual trip distribution requirements with extremely low fuel usage. (TFD)

New Vehicle Detection Method with Aspect Ratio Estimation for Hypothesized Windows

Directory of Open Access Journals (Sweden)

Jisu Kim

2015-12-01

Full Text Available All kinds of vehicles have different ratios of width to height, which are called the aspect ratios. Most previous works, however, use a fixed aspect ratio for vehicle detection (VD. The use of a fixed vehicle aspect ratio for VD degrades the performance. Thus, the estimation of a vehicle aspect ratio is an important part of robust VD. Taking this idea into account, a new on-road vehicle detection system is proposed in this paper. The proposed method estimates the aspect ratio of the hypothesized windows to improve the VD performance. Our proposed method uses an Aggregate Channel Feature (ACF and a support vector machine (SVM to verify the hypothesized windows with the estimated aspect ratio. The contribution of this paper is threefold. First, the estimation of vehicle aspect ratio is inserted between the HG (hypothesis generation and the HV (hypothesis verification. Second, a simple HG method named a signed horizontal edge map is proposed to speed up VD. Third, a new measure is proposed to represent the overlapping ratio between the ground truth and the detection results. This new measure is used to show that the proposed method is better than previous works in terms of robust VD. Finally, the Pittsburgh dataset is used to verify the performance of the proposed method.

Hybrid machining processes perspectives on machining and finishing

CERN Document Server

Gupta, Kapil; Laubscher, R F

2016-01-01

This book describes various hybrid machining and finishing processes. It gives a critical review of the past work based on them as well as the current trends and research directions. For each hybrid machining process presented, the authors list the method of material removal, machining system, process variables and applications. This book provides a deep understanding of the need, application and mechanism of hybrid machining processes.

Method for providing slip energy control in permanent magnet electrical machines

Science.gov (United States)

Hsu, John S.

2006-11-14

An electric machine (40) has a stator (43), a permanent magnet rotor (38) with permanent magnets (39) and a magnetic coupling uncluttered rotor (46) for inducing a slip energy current in secondary coils (47). A dc flux can be produced in the uncluttered rotor when the secondary coils are fed with dc currents. The magnetic coupling uncluttered rotor (46) has magnetic brushes (A, B, C, D) which couple flux in through the rotor (46) to the secondary coils (47c, 47d) without inducing a current in the rotor (46) and without coupling a stator rotational energy component to the secondary coils (47c, 47d). The machine can be operated as a motor or a generator in multi-phase or single-phase embodiments and is applicable to the hybrid electric vehicle. A method of providing a slip energy controller is also disclosed.

Dynamic Sequence Assignment.

Science.gov (United States)

1983-12-01

D-136 548 DYNAMIIC SEQUENCE ASSIGNMENT(U) ADVANCED INFORMATION AND 1/2 DECISION SYSTEMS MOUNTAIN YIELW CA C A 0 REILLY ET AL. UNCLSSIIED DEC 83 AI/DS...I ADVANCED INFORMATION & DECISION SYSTEMS Mountain View. CA 94040 84 u ,53 V,..’. Unclassified _____ SCURITY CLASSIFICATION OF THIS PAGE REPORT...reviews some important heuristic algorithms developed for fas- ter solution of the sequence assignment problem. 3.1. DINAMIC MOGRAMUNIG FORMULATION FOR

Comparisons of likelihood and machine learning methods of individual classification

Science.gov (United States)

Guinand, B.; Topchy, A.; Page, K.S.; Burnham-Curtis, M. K.; Punch, W.F.; Scribner, K.T.

2002-01-01

Classification methods used in machine learning (e.g., artificial neural networks, decision trees, and k-nearest neighbor clustering) are rarely used with population genetic data. We compare different nonparametric machine learning techniques with parametric likelihood estimations commonly employed in population genetics for purposes of assigning individuals to their population of origin (“assignment tests”). Classifier accuracy was compared across simulated data sets representing different levels of population differentiation (low and high FST), number of loci surveyed (5 and 10), and allelic diversity (average of three or eight alleles per locus). Empirical data for the lake trout (Salvelinus namaycush) exhibiting levels of population differentiation comparable to those used in simulations were examined to further evaluate and compare classification methods. Classification error rates associated with artificial neural networks and likelihood estimators were lower for simulated data sets compared to k-nearest neighbor and decision tree classifiers over the entire range of parameters considered. Artificial neural networks only marginally outperformed the likelihood method for simulated data (0–2.8% lower error rates). The relative performance of each machine learning classifier improved relative likelihood estimators for empirical data sets, suggesting an ability to “learn” and utilize properties of empirical genotypic arrays intrinsic to each population. Likelihood-based estimation methods provide a more accessible option for reliable assignment of individuals to the population of origin due to the intricacies in development and evaluation of artificial neural networks. In recent years, characterization of highly polymorphic molecular markers such as mini- and microsatellites and development of novel methods of analysis have enabled researchers to extend investigations of ecological and evolutionary processes below the population level to the level of

Intelligent behaviors through vehicle-to-vehicle and vehicle-to-infrastructure communication

Science.gov (United States)

Garcia, Richard D.; Sturgeon, Purser; Brown, Mike

2012-06-01

The last decade has seen a significant increase in intelligent safety devices on private automobiles. These devices have both increased and augmented the situational awareness of the driver and in some cases provided automated vehicle responses. To date almost all intelligent safety devices have relied on data directly perceived by the vehicle. This constraint has a direct impact on the types of solutions available to the vehicle. In an effort to improve the safety options available to a vehicle, numerous research laboratories and government agencies are investing time and resources into connecting vehicles to each other and to infrastructure-based devices. This work details several efforts in both the commercial vehicle and the private auto industries to increase vehicle safety and driver situational awareness through vehicle-to-vehicle and vehicle-to-infrastructure communication. It will specifically discuss intelligent behaviors being designed to automatically disable non-compliant vehicles, warn tractor trailer vehicles of unsafe lane maneuvers such as lane changes, passing, and merging, and alert drivers to non-line-of-sight emergencies.

Object-based detection of vehicles using combined optical and elevation data

Science.gov (United States)

Schilling, Hendrik; Bulatov, Dimitri; Middelmann, Wolfgang

2018-02-01

The detection of vehicles is an important and challenging topic that is relevant for many applications. In this work, we present a workflow that utilizes optical and elevation data to detect vehicles in remotely sensed urban data. This workflow consists of three consecutive stages: candidate identification, classification, and single vehicle extraction. Unlike in most previous approaches, fusion of both data sources is strongly pursued at all stages. While the first stage utilizes the fact that most man-made objects are rectangular in shape, the second and third stages employ machine learning techniques combined with specific features. The stages are designed to handle multiple sensor input, which results in a significant improvement. A detailed evaluation shows the benefits of our workflow, which includes hand-tailored features; even in comparison with classification approaches based on Convolutional Neural Networks, which are state of the art in computer vision, we could obtain a comparable or superior performance (F1 score of 0.96-0.94).

CONNJUR R: an annotation strategy for fostering reproducibility in bio-NMR—protein spectral assignment

Energy Technology Data Exchange (ETDEWEB)

Fenwick, Matthew; Hoch, Jeffrey C. [UConn Health, Department of Molecular Biology and Biophysics (United States); Ulrich, Eldon [University of Wisconsin-Madison, Department of Biochemistry (United States); Gryk, Michael R., E-mail: gryk@uchc.edu [UConn Health, Department of Molecular Biology and Biophysics (United States)

2015-10-15

Reproducibility is a cornerstone of the scientific method, essential for validation of results by independent laboratories and the sine qua non of scientific progress. A key step toward reproducibility of biomolecular NMR studies was the establishment of public data repositories (PDB and BMRB). Nevertheless, bio-NMR studies routinely fall short of the requirement for reproducibility that all the data needed to reproduce the results are published. A key limitation is that considerable metadata goes unpublished, notably manual interventions that are typically applied during the assignment of multidimensional NMR spectra. A general solution to this problem has been elusive, in part because of the wide range of approaches and software packages employed in the analysis of protein NMR spectra. Here we describe an approach for capturing missing metadata during the assignment of protein NMR spectra that can be generalized to arbitrary workflows, different software packages, other biomolecules, or other stages of data analysis in bio-NMR. We also present extensions to the NMR-STAR data dictionary that enable machine archival and retrieval of the “missing” metadata.

CONNJUR R: an annotation strategy for fostering reproducibility in bio-NMR—protein spectral assignment

International Nuclear Information System (INIS)

Fenwick, Matthew; Hoch, Jeffrey C.; Ulrich, Eldon; Gryk, Michael R.

2015-01-01

Reproducibility is a cornerstone of the scientific method, essential for validation of results by independent laboratories and the sine qua non of scientific progress. A key step toward reproducibility of biomolecular NMR studies was the establishment of public data repositories (PDB and BMRB). Nevertheless, bio-NMR studies routinely fall short of the requirement for reproducibility that all the data needed to reproduce the results are published. A key limitation is that considerable metadata goes unpublished, notably manual interventions that are typically applied during the assignment of multidimensional NMR spectra. A general solution to this problem has been elusive, in part because of the wide range of approaches and software packages employed in the analysis of protein NMR spectra. Here we describe an approach for capturing missing metadata during the assignment of protein NMR spectra that can be generalized to arbitrary workflows, different software packages, other biomolecules, or other stages of data analysis in bio-NMR. We also present extensions to the NMR-STAR data dictionary that enable machine archival and retrieval of the “missing” metadata

Covering path generation for autonomous turf-care vehicle

DEFF Research Database (Denmark)

Mai, Christian; Jouffroy, Jerome; Top, Søren

2017-01-01

A covering path generation algorithm is developed to generate a lengthwise pattern based on a polygon describing the outer boundary and obstacles (polygon holes) of a geographical area. The algorithm is applied to an autonomous lawn-care robot for application to large grass turfs, for example golf......-courses, which require structured and precise cutting patterns. The geographical polygon is recorded by manually driving the vehicle around the contour, resulting in a polygon given as geographical (latitude, longitude) coordinates of the vertices, which together with machine parameters are used to generate...

Transportation and Production Lot-size for Sugarcane under Uncertainty of Machine Capacity

Directory of Open Access Journals (Sweden)

Sudtachat Kanchala

2018-01-01

Full Text Available The integrated transportation and production lot size problems is important effect to total cost of operation system for sugar factories. In this research, we formulate a mathematic model that combines these two problems as two stage stochastic programming model. In the first stage, we determine the lot size of transportation problem and allocate a fixed number of vehicles to transport sugarcane to the mill factory. Moreover, we consider an uncertainty of machine (mill capacities. After machine (mill capacities realized, in the second stage we determine the production lot size and make decision to hold units of sugarcane in front of mills based on discrete random variables of machine (mill capacities. We investigate the model using a small size problem. The results show that the optimal solutions try to choose closest fields and lower holding cost per unit (at fields to transport sugarcane to mill factory. We show the results of comparison of our model and the worst case model (full capacity. The results show that our model provides better efficiency than the results of the worst case model.

Dynamic Vehicle Scheduling for Working Service Network with Dual Demands

Directory of Open Access Journals (Sweden)

Bing Li

2017-01-01

Full Text Available This study aims to develop some models to aid in making decisions on the combined fleet size and vehicle assignment in working service network where the demands include two types (minimum demands and maximum demands, and vehicles themselves can act like a facility to provide services when they are stationary at one location. This type of problem is named as the dynamic working vehicle scheduling with dual demands (DWVS-DD and formulated as a mixed integer programming (MIP. Instead of a large integer program, the problem is decomposed into small local problems that are guided by preset control parameters. The approach for preset control parameters is given. By introducing them into the MIP formulation, the model is reformulated as a piecewise form. Further, a piecewise method by updating preset control parameters is proposed for solving the reformulated model. Numerical experiments show that the proposed method produces better solution within reasonable computing time.

Magnetic Decoupling Design and Experimental Validation of a Radial-Radial Flux Compound-Structure Permanent-Magnet Synchronous Machine for HEVs

Directory of Open Access Journals (Sweden)

Zhiyi Song

2012-10-01

Full Text Available The radial-radial flux compound-structure permanent-magnet synchronous machine (CS-PMSM, integrated by two concentrically arranged permanent-magnet electric machines, is an electromagnetic power-splitting device for hybrid electric vehicles (HEVs. As the two electric machines share a rotor as structural and magnetic common part, their magnetic paths are coupled, leading to possible mutual magnetic-field interference and complex control. In this paper, a design method to ensure magnetic decoupling with minimum yoke thickness of the common rotor is investigated. A prototype machine is designed based on the proposed method, and the feasibility of magnetic decoupling and independent control is validated by experimental tests of mutual influence. The CS-PMSM is tested by a designed driving cycle, and functions to act as starter motor, generator and to help the internal combustion engine (ICE operate at optimum efficiency are validated.

Power electronics and electric machinery challenges and opportunities in electric and hybrid vehicles

Energy Technology Data Exchange (ETDEWEB)

Adams, D.J.; Hsu, J.S.; Young, R.W. [Oak Ridge National Lab., TN (United States); Peng, F.Z. [Univ. of Tennessee, Knoxville, TN (United States)

1997-06-01

The development of power electronics and electric machinery presents significant challenges to the advancement of electric and hybrid vehicles. Electronic components and systems development for vehicle applications have progressed from the replacement of mechanical systems to the availability of features that can only be realized through interacting electronic controls and devices. Near-term applications of power electronics in vehicles will enable integrated powertrain controls, integrated chassis system controls, and navigation and communications systems. Future applications of optimized electric machinery will enable highly efficient and lightweight systems. This paper will explore the areas where research and development is required to ensure the continued development of power electronics and electric machines to meet the rigorous demands of automotive applications. Additionally, recent advances in automotive related power electronics and electric machinery at Oak Ridge National Laboratory will be explained. 3 refs., 5 figs.

Scheduling with Learning Effects and/or Time-Dependent Processing Times to Minimize the Weighted Number of Tardy Jobs on a Single Machine

Directory of Open Access Journals (Sweden)

Jianbo Qian

2013-01-01

Full Text Available We consider single machine scheduling problems with learning/deterioration effects and time-dependent processing times, with due date assignment consideration, and our objective is to minimize the weighted number of tardy jobs. By reducing all versions of the problem to an assignment problem, we solve them in O(n4 time. For some important special cases, the time complexity can be improved to be O(n2 using dynamic programming techniques.

Our Policies, Their Text: German Language Students' Strategies with and Beliefs about Web-Based Machine Translation

Science.gov (United States)

White, Kelsey D.; Heidrich, Emily

2013-01-01

Most educators are aware that some students utilize web-based machine translators for foreign language assignments, however, little research has been done to determine how and why students utilize these programs, or what the implications are for language learning and teaching. In this mixed-methods study we utilized surveys, a translation task,…

Determining the Effectiveness of Incorporating Geographic Information Into Vehicle Performance Algorithms

Energy Technology Data Exchange (ETDEWEB)

Sera White

2012-04-01

This thesis presents a research study using one year of driving data obtained from plug-in hybrid electric vehicles (PHEV) located in Sacramento and San Francisco, California to determine the effectiveness of incorporating geographic information into vehicle performance algorithms. Sacramento and San Francisco were chosen because of the availability of high resolution (1/9 arc second) digital elevation data. First, I present a method for obtaining instantaneous road slope, given a latitude and longitude, and introduce its use into common driving intensity algorithms. I show that for trips characterized by >40m of net elevation change (from key on to key off), the use of instantaneous road slope significantly changes the results of driving intensity calculations. For trips exhibiting elevation loss, algorithms ignoring road slope overestimated driving intensity by as much as 211 Wh/mile, while for trips exhibiting elevation gain these algorithms underestimated driving intensity by as much as 333 Wh/mile. Second, I describe and test an algorithm that incorporates vehicle route type into computations of city and highway fuel economy. Route type was determined by intersecting trip GPS points with ESRI StreetMap road types and assigning each trip as either city or highway route type according to whichever road type comprised the largest distance traveled. The fuel economy results produced by the geographic classification were compared to the fuel economy results produced by algorithms that assign route type based on average speed or driving style. Most results were within 1 mile per gallon ({approx}3%) of one another; the largest difference was 1.4 miles per gallon for charge depleting highway trips. The methods for acquiring and using geographic data introduced in this thesis will enable other vehicle technology researchers to incorporate geographic data into their research problems.

Machine Visual Guidance For An Autonomous Undersea Submersible

Science.gov (United States)

Nguyen, Hoa G.; Kaomea, Peter K.; Heckman, Paul J.

1988-12-01

Optical imaging is the preferred sensory modality for underwater robotic activities requiring high resolution at close range, such as station keeping, docking, control of manipulator, and object retrieval. Machine vision will play a vital part in the design of next generation autonomous underwater submersibles. This paper describes an effort to demonstrate that real-time vision-based guidance and control of autonomous underwater submersibles is possible with compact, low-power, and vehicle-imbeddable hardware. The Naval Ocean Systems Center's EAVE-WEST (Experimental Autonomous Vehicle-West) submersible is being used as the testbed. The vision hardware consists of a PC-bus video frame grabber and an IBM-PC/AT compatible single-board computer, both residing in the artificial intelligence/vision electronics bottle of the submersible. The specific application chosen involves the tracking of underwater buoy cables. Image recognition is performed in two steps. Feature points are identified in the underwater video images using a technique which detects one-dimensional local brightness minima and maxima. Hough transformation is then used to detect the straight line among these feature points. A hierarchical coarse-to-fine processing method is employed which terminates when enough feature points have been identified to allow a reliable fit. The location of the cable identified is then reported to the vehicle controller computer for automatic steering control. The process currently operates successfully with a throughput of approximately 2 frames per second.

Vehicle Detection with Occlusion Handling, Tracking, and OC-SVM Classification: A High Performance Vision-Based System

Science.gov (United States)

Velazquez-Pupo, Roxana; Sierra-Romero, Alberto; Torres-Roman, Deni; Shkvarko, Yuriy V.; Romero-Delgado, Misael

2018-01-01

This paper presents a high performance vision-based system with a single static camera for traffic surveillance, for moving vehicle detection with occlusion handling, tracking, counting, and One Class Support Vector Machine (OC-SVM) classification. In this approach, moving objects are first segmented from the background using the adaptive Gaussian Mixture Model (GMM). After that, several geometric features are extracted, such as vehicle area, height, width, centroid, and bounding box. As occlusion is present, an algorithm was implemented to reduce it. The tracking is performed with adaptive Kalman filter. Finally, the selected geometric features: estimated area, height, and width are used by different classifiers in order to sort vehicles into three classes: small, midsize, and large. Extensive experimental results in eight real traffic videos with more than 4000 ground truth vehicles have shown that the improved system can run in real time under an occlusion index of 0.312 and classify vehicles with a global detection rate or recall, precision, and F-measure of up to 98.190%, and an F-measure of up to 99.051% for midsize vehicles. PMID:29382078

Optimization of a permanent magnet synchronous machine with respect to variable loads; Optimierung einer permanenterregten Synchronmaschine unter Beruecksichtigung von Lastspielen

Energy Technology Data Exchange (ETDEWEB)

Kreim, Alexander; Schaefer, Uwe [TU Berlin (Germany). Sek. EM4 Elektrische Antriebstechnik

2010-10-15

This article introduces a nonlinear optimization algorithm for mixed integer problems. The proposed algorithm is a trust region algorithm for an exact penalty function. The quadratic subproblem is used for the integration of discrete variables. This is done by a branch-and-bound approach. The application of the algorithm is shown by minimizing the losses of a permanent magnet synchronous machine. The machine is designed for use in hybrid and electric vehicles. It is shown how load cycles can be included into the optimization process. (orig.)

Process planning optimization on turning machine tool using a hybrid genetic algorithm with local search approach

Directory of Open Access Journals (Sweden)

Yuliang Su

2015-04-01

Full Text Available A turning machine tool is a kind of new type of machine tool that is equipped with more than one spindle and turret. The distinctive simultaneous and parallel processing abilities of turning machine tool increase the complexity of process planning. The operations would not only be sequenced and satisfy precedence constraints, but also should be scheduled with multiple objectives such as minimizing machining cost, maximizing utilization of turning machine tool, and so on. To solve this problem, a hybrid genetic algorithm was proposed to generate optimal process plans based on a mixed 0-1 integer programming model. An operation precedence graph is used to represent precedence constraints and help generate a feasible initial population of hybrid genetic algorithm. Encoding strategy based on data structure was developed to represent process plans digitally in order to form the solution space. In addition, a local search approach for optimizing the assignments of available turrets would be added to incorporate scheduling with process planning. A real-world case is used to prove that the proposed approach could avoid infeasible solutions and effectively generate a global optimal process plan.

Electric personnel carrier introduced : RES Equipment Sales spearheads development of electric underground vehicle

International Nuclear Information System (INIS)

Tollinsky, N.

2010-01-01

RES Equipment Sales of Dryden, Ontario is leading the development of a battery-powered personnel utility vehicle for underground mining applications. Among the advantages of the battery-powered personnel carrier are quietness of the carrier and zero emissions, which eliminates particulates from diesel engines and reduces the need for ventilation. This article discussed the design and building of the vehicle. It was designed to accommodate up to 3 battery packs, depending on the frequency of use. Swapping batteries takes between 2 or 3 minutes. Spent batteries must be plugged in for 6 hours and rest for another 6 to 8 hours before being ready for service. The vehicle accommodates 2 or 3 people and travels at speeds of 6 to 8 miles per hour. This article also provided background information on RES Equipment Sales. The company remanufactures underground mining equipment, including load-haul-dump machines, jumbos, haul trucks and utility vehicles. In addition, the company sells and services new equipment, including Oldenburg Cannon jumbos, scalers and utility vehicles, as well as Canun International pneumatic rock drills and NPK rock breakers. 1 ref., 1 fig.

Machine terms dictionary

Energy Technology Data Exchange (ETDEWEB)

NONE

1979-04-15

This book gives descriptions of machine terms which includes machine design, drawing, the method of machine, machine tools, machine materials, automobile, measuring and controlling, electricity, basic of electron, information technology, quality assurance, Auto CAD and FA terms and important formula of mechanical engineering.

Machine learning, computer vision, and probabilistic models in jet physics

CERN Multimedia

CERN. Geneva; NACHMAN, Ben

2015-01-01

In this talk we present recent developments in the application of machine learning, computer vision, and probabilistic models to the analysis and interpretation of LHC events. First, we will introduce the concept of jet-images and computer vision techniques for jet tagging. Jet images enabled the connection between jet substructure and tagging with the fields of computer vision and image processing for the first time, improving the performance to identify highly boosted W bosons with respect to state-of-the-art methods, and providing a new way to visualize the discriminant features of different classes of jets, adding a new capability to understand the physics within jets and to design more powerful jet tagging methods. Second, we will present Fuzzy jets: a new paradigm for jet clustering using machine learning methods. Fuzzy jets view jet clustering as an unsupervised learning task and incorporate a probabilistic assignment of particles to jets to learn new features of the jet structure. In particular, we wi...

МЕТHОDS OF SYSТЕМ CALCULATION-ANALYTICAL AND STAND DIAGNOSTICATING OF PASSENGER VEHICLES

Directory of Open Access Journals (Sweden)

М. Govoruschenko

2009-01-01

Full Text Available The new power model for fuel expense diagnosticating is developed on the principle that allows to estimate the general state of vehicles in a simple and accessible way as well as particular units for measuring and analysis of private and general coefficiency of machines.

Some relations between quantum Turing machines and Turing machines

OpenAIRE

Sicard, Andrés; Vélez, Mario

1999-01-01

For quantum Turing machines we present three elements: Its components, its time evolution operator and its local transition function. The components are related with the components of deterministic Turing machines, the time evolution operator is related with the evolution of reversible Turing machines and the local transition function is related with the transition function of probabilistic and reversible Turing machines.

Vehicle detection from very-high-resolution (VHR) aerial imagery using attribute belief propagation (ABP)

Science.gov (United States)

Wang, Yanli; Li, Ying; Zhang, Li; Huang, Yuchun

2016-10-01

With the popularity of very-high-resolution (VHR) aerial imagery, the shape, color, and context attribute of vehicles are better characterized. Due to the various road surroundings and imaging conditions, vehicle attributes could be adversely affected so that vehicle is mistakenly detected or missed. This paper is motivated to robustly extract the rich attribute feature for detecting the vehicles of VHR imagery under different scenarios. Based on the hierarchical component tree of vehicle context, attribute belief propagation (ABP) is proposed to detect salient vehicles from the statistical perspective. With the Max-tree data structure, the multi-level component tree around the road network is efficiently created. The spatial relationship between vehicle and its belonging context is established with the belief definition of vehicle attribute. To effectively correct single-level belief error, the inter-level belief linkages enforce consistency of belief assignment between corresponding components at different levels. ABP starts from an initial set of vehicle belief calculated by vehicle attribute, and then iterates through each component by applying inter-level belief passing until convergence. The optimal value of vehicle belief of each component is obtained via minimizing its belief function iteratively. The proposed algorithm is tested on a diverse set of VHR imagery acquired in the city and inter-city areas of the West and South China. Experimental results show that the proposed algorithm can detect vehicle efficiently and suppress the erroneous effectively. The proposed ABP framework is promising to robustly classify the vehicles from VHR Aerial imagery.

Prediction of Driver's Intention of Lane Change by Augmenting Sensor Information Using Machine Learning Techniques.

Science.gov (United States)

Kim, Il-Hwan; Bong, Jae-Hwan; Park, Jooyoung; Park, Shinsuk

2017-06-10

Driver assistance systems have become a major safety feature of modern passenger vehicles. The advanced driver assistance system (ADAS) is one of the active safety systems to improve the vehicle control performance and, thus, the safety of the driver and the passengers. To use the ADAS for lane change control, rapid and correct detection of the driver's intention is essential. This study proposes a novel preprocessing algorithm for the ADAS to improve the accuracy in classifying the driver's intention for lane change by augmenting basic measurements from conventional on-board sensors. The information on the vehicle states and the road surface condition is augmented by using an artificial neural network (ANN) models, and the augmented information is fed to a support vector machine (SVM) to detect the driver's intention with high accuracy. The feasibility of the developed algorithm was tested through driving simulator experiments. The results show that the classification accuracy for the driver's intention can be improved by providing an SVM model with sufficient driving information augmented by using ANN models of vehicle dynamics.

Predicting the market potential of plug-in electric vehicles using multiday GPS data

International Nuclear Information System (INIS)

Khan, Mobashwir; Kockelman, Kara M.

2012-01-01

GPS data for a year's worth of travel by 255 Seattle households illuminate how plug-in electric vehicles can match household needs. The results suggest that a battery-electric vehicle (BEV) with 100 mi of range should meet the needs of 50% of one-vehicle households and 80% of multiple-vehicle households, when charging once a day and relying on another vehicle or mode just 4 days a year. Moreover, the average one-vehicle Seattle household uses each vehicle 23 mi per day and should be able to electrify close to 80% of its miles, while meeting all its travel needs, using a plug-in hybrid electric vehicle (PHEV) with 40-mile all-electric range. Households owning two or more vehicles can electrify 50 to 70% of their total household miles using a PHEV40, depending on how they assign the vehicle across drivers each day. Cost comparisons between the average single-vehicle household owning a Chevrolet Cruze versus a Volt PHEV suggest that, when gas prices are $3.50 per gallon and electricity rates are at 11.2 ct/kWh, the Volt will save the household $535 per year in operating costs. Similarly, the Toyota Prius PHEV will provide an annual savings of $538 per year over the Corolla. - Highlights: ► Daily travel distances over a year were obtained for 255 Seattle households. ► 100-mi-range BEVs can meet 99% of daily needs for 50% of one-vehicle households. ► 100-mi-range BEVs can meet 99% of needs for 80% of multi-vehicle households. ► One-vehicle households will electrify close to 80% of their miles using a PHEV40 while meeting all trip-distance needs. ► Two-vehicle households can electrify 50 to 70% of household miles using a PHEV40 while meeting all trip-distance needs.

Support vector machine in machine condition monitoring and fault diagnosis

Science.gov (United States)

Widodo, Achmad; Yang, Bo-Suk

2007-08-01

Recently, the issue of machine condition monitoring and fault diagnosis as a part of maintenance system became global due to the potential advantages to be gained from reduced maintenance costs, improved productivity and increased machine availability. This paper presents a survey of machine condition monitoring and fault diagnosis using support vector machine (SVM). It attempts to summarize and review the recent research and developments of SVM in machine condition monitoring and diagnosis. Numerous methods have been developed based on intelligent systems such as artificial neural network, fuzzy expert system, condition-based reasoning, random forest, etc. However, the use of SVM for machine condition monitoring and fault diagnosis is still rare. SVM has excellent performance in generalization so it can produce high accuracy in classification for machine condition monitoring and diagnosis. Until 2006, the use of SVM in machine condition monitoring and fault diagnosis is tending to develop towards expertise orientation and problem-oriented domain. Finally, the ability to continually change and obtain a novel idea for machine condition monitoring and fault diagnosis using SVM will be future works.

Defect detection and classification of machined surfaces under multiple illuminant directions

Science.gov (United States)

Liao, Yi; Weng, Xin; Swonger, C. W.; Ni, Jun

2010-08-01

Continuous improvement of product quality is crucial to the successful and competitive automotive manufacturing industry in the 21st century. The presence of surface porosity located on flat machined surfaces such as cylinder heads/blocks and transmission cases may allow leaks of coolant, oil, or combustion gas between critical mating surfaces, thus causing damage to the engine or transmission. Therefore 100% inline inspection plays an important role for improving product quality. Although the techniques of image processing and machine vision have been applied to machined surface inspection and well improved in the past 20 years, in today's automotive industry, surface porosity inspection is still done by skilled humans, which is costly, tedious, time consuming and not capable of reliably detecting small defects. In our study, an automated defect detection and classification system for flat machined surfaces has been designed and constructed. In this paper, the importance of the illuminant direction in a machine vision system was first emphasized and then the surface defect inspection system under multiple directional illuminations was designed and constructed. After that, image processing algorithms were developed to realize 5 types of 2D or 3D surface defects (pore, 2D blemish, residue dirt, scratch, and gouge) detection and classification. The steps of image processing include: (1) image acquisition and contrast enhancement (2) defect segmentation and feature extraction (3) defect classification. An artificial machined surface and an actual automotive part: cylinder head surface were tested and, as a result, microscopic surface defects can be accurately detected and assigned to a surface defect class. The cycle time of this system can be sufficiently fast that implementation of 100% inline inspection is feasible. The field of view of this system is 150mm×225mm and the surfaces larger than the field of view can be stitched together in software.

Vision-based control in driving assistance of agricultural vehicles

Energy Technology Data Exchange (ETDEWEB)

Khadraoui, D.; Martinet, P.; Bonton, P.; Gallice, J. [Univ. Blaise Pascal, Aubiere (France). Lab. des Sciences et Materiaux pour l`Electronique et d`Automatique; Debain, C. [Inst. de Recherche pour l`Ingenierie de l`Agriculture et de l`Environment, Montoldre (France). Div. Techniques du Machinisme Agricole; Rouveure, R. [Inst. de Recherche pour l`Ingenierie de l`Agriculture et de l`Environment, Antony (France). Div. Electronique et Intelligence Artificielle

1998-10-01

This article presents a real-time control system for an agricultural mobile machine (vehicle) based on an on-board vision system using a single camera. This system has been designed to help humans in repetitive and difficult tasks in the agricultural domain. The aim of the robotics application concerns the control of the vehicle with regard to the reap limit detected in image space. The perception aspect in relation to the application has been described in previous work, and here the authors deal with the control aspect. They integrate image features issues from the modeling of the scene in the control loop to perform an image-based servoing technique. The vehicle behavior described here concerns bicycle and neural models, and three control laws are then synthesized. The first and the second are modeling approaches and use an interaction between the scene and the image space. They are based on the regulation of a task function. The third is a black-box modeling technique, and is based on a neural network. Finally, experimental results obtained with these different control laws in different conditions are presented and discussed.

Design of Sail-Assisted Unmanned Surface Vehicle Intelligent Control System

OpenAIRE

Ma, Yong; Zhao, Yujiao; Diao, Jiantao; Gan, Langxiong; Bi, Huaxiong; Zhao, Jingming

2016-01-01

To achieve the wind sail-assisted function of the unmanned surface vehicle (USV), this work focuses on the design problems of the sail-assisted USV intelligent control systems (SUICS) and illustrates the implementation process of the SUICS. The SUICS consists of the communication system, the sensor system, the PC platform, and the lower machine platform. To make full use of the wind energy, in the SUICS, we propose the sail angle of attack automatic adjustment (Sail_4A) algorithm and present ...

Using HL7 in hospital staff assignments.

Science.gov (United States)

Unluturk, Mehmet S

2014-02-01

Hospital staff assignments are the instructions that allocate the hospital staff members to the hospital beds. Currently, hospital administrators make the assignments without accessing the information regarding the occupancy of the hospital beds and the acuity of the patient. As a result, administrators cannot distinguish between occupied and unoccupied beds, and may therefore assign staff to unoccupied beds. This gives rise to uneven and inefficient staff assignments. In this paper, the hospital admission-discharge-transfer (ADT) system is employed both as a data source and an assignment device to create staff assignments. When the patient data is newly added or modified, the ADT system updates the assignment software client with the relevant data. Based on the relevant data, the assignment software client is able to construct staff assignments in a more efficient way. © 2013 Elsevier Ltd. All rights reserved.

AN AUTONOMOUS GPS-DENIED UNMANNED VEHICLE PLATFORM BASED ON BINOCULAR VISION FOR PLANETARY EXPLORATION

Directory of Open Access Journals (Sweden)

M. Qin

2018-04-01

Full Text Available Vision-based navigation has become an attractive solution for autonomous navigation for planetary exploration. This paper presents our work of designing and building an autonomous vision-based GPS-denied unmanned vehicle and developing an ARFM (Adaptive Robust Feature Matching based VO (Visual Odometry software for its autonomous navigation. The hardware system is mainly composed of binocular stereo camera, a pan-and tilt, a master machine, a tracked chassis. And the ARFM-based VO software system contains four modules: camera calibration, ARFM-based 3D reconstruction, position and attitude calculation, BA (Bundle Adjustment modules. Two VO experiments were carried out using both outdoor images from open dataset and indoor images captured by our vehicle, the results demonstrate that our vision-based unmanned vehicle is able to achieve autonomous localization and has the potential for future planetary exploration.

An Autonomous Gps-Denied Unmanned Vehicle Platform Based on Binocular Vision for Planetary Exploration

Science.gov (United States)

Qin, M.; Wan, X.; Shao, Y. Y.; Li, S. Y.

2018-04-01

Vision-based navigation has become an attractive solution for autonomous navigation for planetary exploration. This paper presents our work of designing and building an autonomous vision-based GPS-denied unmanned vehicle and developing an ARFM (Adaptive Robust Feature Matching) based VO (Visual Odometry) software for its autonomous navigation. The hardware system is mainly composed of binocular stereo camera, a pan-and tilt, a master machine, a tracked chassis. And the ARFM-based VO software system contains four modules: camera calibration, ARFM-based 3D reconstruction, position and attitude calculation, BA (Bundle Adjustment) modules. Two VO experiments were carried out using both outdoor images from open dataset and indoor images captured by our vehicle, the results demonstrate that our vision-based unmanned vehicle is able to achieve autonomous localization and has the potential for future planetary exploration.

e-Learning Application for Machine Maintenance Process using Iterative Method in XYZ Company

Science.gov (United States)

Nurunisa, Suaidah; Kurniawati, Amelia; Pramuditya Soesanto, Rayinda; Yunan Kurnia Septo Hediyanto, Umar

2016-02-01

XYZ Company is a company based on manufacturing part for airplane, one of the machine that is categorized as key facility in the company is Millac 5H6P. As a key facility, the machines should be assured to work well and in peak condition, therefore, maintenance process is needed periodically. From the data gathering, it is known that there are lack of competency from the maintenance staff to maintain different type of machine which is not assigned by the supervisor, this indicate that knowledge which possessed by maintenance staff are uneven. The purpose of this research is to create knowledge-based e-learning application as a realization from externalization process in knowledge transfer process to maintain the machine. The application feature are adjusted for maintenance purpose using e-learning framework for maintenance process, the content of the application support multimedia for learning purpose. QFD is used in this research to understand the needs from user. The application is built using moodle with iterative method for software development cycle and UML Diagram. The result from this research is e-learning application as sharing knowledge media for maintenance staff in the company. From the test, it is known that the application make maintenance staff easy to understand the competencies.

A New Evolutionary Algorithm Based on Bacterial Evolution and Its Application for Scheduling A Flexible Manufacturing System

Directory of Open Access Journals (Sweden)

Chandramouli Anandaraman

2012-01-01

Full Text Available A new evolutionary computation algorithm, Superbug algorithm, which simulates evolution of bacteria in a culture, is proposed. The algorithm is developed for solving large scale optimization problems such as scheduling, transportation and assignment problems. In this work, the algorithm optimizes machine schedules in a Flexible Manufacturing System (FMS by minimizing makespan. The FMS comprises of four machines and two identical Automated Guided Vehicles (AGVs. AGVs are used for carrying jobs between the Load/Unload (L/U station and the machines. Experimental results indicate the efficiency of the proposed algorithm in its optimization performance in scheduling is noticeably superior to other evolutionary algorithms when compared to the best results reported in the literature for FMS Scheduling.

Tool management in manufacturing systems equipped with CNC machines

Directory of Open Access Journals (Sweden)

Giovanni Tani

1997-12-01

Full Text Available This work has been carried out for the purpose of realizing an automated system for the integrated management of tools within a company. By integrating planning, inspection and tool-room functions, automated tool management can ensure optimum utilization of tools on the selected machines, guaranteeing their effective availability. The first stage of the work consisted of defining and developing a Tool Management System whose central nucleus is a unified Data Base for all of the tools, forming part of the company's Technological Files (files on machines, materials, equipment, methods, etc., interfaceable with all of the company departments that require information on tools. The system assigns code numbers to the individual components of the tools and file them on the basis of their morphological and functional characteristics. The system is also designed to effect assemblies of tools, from which are obtained the "Tool Cards" required for compiling working cycles (CAPP, for CAM programming and for the Tool-room where the tools are physically prepared. Methods for interfacing with suitable systems for the aforesaid functions have also been devised

Simulations of Quantum Turing Machines by Quantum Multi-Stack Machines

OpenAIRE

Qiu, Daowen

2005-01-01

As was well known, in classical computation, Turing machines, circuits, multi-stack machines, and multi-counter machines are equivalent, that is, they can simulate each other in polynomial time. In quantum computation, Yao [11] first proved that for any quantum Turing machines $M$, there exists quantum Boolean circuit $(n,t)$-simulating $M$, where $n$ denotes the length of input strings, and $t$ is the number of move steps before machine stopping. However, the simulations of quantum Turing ma...

Monitoring system for gamma radiation of porch type for vehicles; Sistema de monitoreo de radiacion gamma tipo portal para vehiculos

Energy Technology Data Exchange (ETDEWEB)

Vazquez C, R.M.; Molina, G.; Gutierrez O, E.; Ramirez J, F.J.; Garcia H, J.M.; Aguilar B, M.A.; Vilchis P, A.E.; Cruz E, P.; Torres B, M.A. [ININ, 52045 Ocoyoacac, Estado de Mexico (Mexico)

2005-07-01

A monitoring system of gamma radiation for vehicles of the porch type developed in the ININ is presented. This system carries out the radiological monitoring of the vehicles in continuous form, detecting the bottom radiological environment and the presence of nuclear material transported in vehicles. The vehicles are monitored while they pass to low speed through the porch. The detectors are plastic scintillators of great volume that allow high sensibility detection. The arrangement of detecting is interconnected in net, and the data are concentrated on a personal computer whose interface man-machine can be accessed from any personal computer connected to Internet. The system monitoring in real time with options of sampling times from 50 ms configurable up to 500 ms. (Author)

Cognitive Connected Vehicle Information System Design Requirement for Safety: Role of Bayesian Artificial Intelligence

Directory of Open Access Journals (Sweden)

Ata Khan

2013-04-01

Full Text Available Intelligent transportation systems (ITS are gaining acceptance around the world and the connected vehicle component of ITS is recognized as a high priority research and development area in many technologically advanced countries. Connected vehicles are expected to have the capability of safe, efficient and eco-driving operations whether these are under human control or in the adaptive machine control mode of operations. The race is on to design the capability to operate in connected traffic environment. The operational requirements can be met with cognitive vehicle design features made possible by advances in artificial intelligence-supported methodology, improved understanding of human factors, and advances in communication technology. This paper describes cognitive features and their information system requirements. The architecture of an information system is presented that supports the features of the cognitive connected vehicle. For better focus, information processing capabilities are specified and the role of Bayesian artificial intelligence is defined for data fusion. Example applications illustrate the role of information systems in integrating intelligent technology, Bayesian artificial intelligence, and abstracted human factors. Concluding remarks highlight the role of the information system and Bayesian artificial intelligence in the design of a new generation of cognitive connected vehicle.

ELECTROMAGNETIC BIOSPHERE POLLUTION BY MOTOR TRANSPORT (VEHICLES, ELECTRIC VEHICLES, HYBRID VEHICLES

Directory of Open Access Journals (Sweden)

S. Selivanov

2009-01-01

Full Text Available The physics of the electromagnetic field is considered. The analysis of electromagnetic radiation on the human-being, the origin of which is the vehicle the electric vehicle, the hybrid vehicle is being considered. The monitoring of electromagnetic radiation of vehicles is carried out.

The 21st annual intelligent ground vehicle competition: robotists for the future

Science.gov (United States)

Theisen, Bernard L.

2013-12-01

The Intelligent Ground Vehicle Competition (IGVC) is one of four, unmanned systems, student competitions that were founded by the Association for Unmanned Vehicle Systems International (AUVSI). The IGVC is a multidisciplinary exercise in product realization that challenges college engineering student teams to integrate advanced control theory, machine vision, vehicular electronics and mobile platform fundamentals to design and build an unmanned system. Teams from around the world focus on developing a suite of dual-use technologies to equip ground vehicles of the future with intelligent driving capabilities. Over the past 21 years, the competition has challenged undergraduate, graduate and Ph.D. students with real world applications in intelligent transportation systems, the military and manufacturing automation. To date, teams from over 80 universities and colleges have participated. This paper describes some of the applications of the technologies required by this competition and discusses the educational benefits. The primary goal of the IGVC is to advance engineering education in intelligent vehicles and related technologies. The employment and professional networking opportunities created for students and industrial sponsors through a series of technical events over the fourday competition are highlighted. Finally, an assessment of the competition based on participation is presented.

Machine tool structures

CERN Document Server

Koenigsberger, F

1970-01-01

Machine Tool Structures, Volume 1 deals with fundamental theories and calculation methods for machine tool structures. Experimental investigations into stiffness are discussed, along with the application of the results to the design of machine tool structures. Topics covered range from static and dynamic stiffness to chatter in metal cutting, stability in machine tools, and deformations of machine tool structures. This volume is divided into three sections and opens with a discussion on stiffness specifications and the effect of stiffness on the behavior of the machine under forced vibration c

Electricity of machine tool

International Nuclear Information System (INIS)

Gijeon media editorial department

1977-10-01

This book is divided into three parts. The first part deals with electricity machine, which can taints from generator to motor, motor a power source of machine tool, electricity machine for machine tool such as switch in main circuit, automatic machine, a knife switch and pushing button, snap switch, protection device, timer, solenoid, and rectifier. The second part handles wiring diagram. This concludes basic electricity circuit of machine tool, electricity wiring diagram in your machine like milling machine, planer and grinding machine. The third part introduces fault diagnosis of machine, which gives the practical solution according to fault diagnosis and the diagnostic method with voltage and resistance measurement by tester.

Implementation Approach for Electric Vehicles at Marine Corps Base Camp Lejeune. Task 4

Energy Technology Data Exchange (ETDEWEB)

Schey, Stephen [Idaho National Lab. (INL), Idaho Falls, ID (United States); Francfort, Jim [Idaho National Lab. (INL), Idaho Falls, ID (United States)

2015-11-01

Battelle Energy Alliance, LLC, managing and operating contractor for the U.S. Department of Energy’s Idaho National Laboratory, is the lead laboratory for U.S. Department of Energy Advanced Vehicle Testing. Battelle Energy Alliance, LLC contracted with Intertek Testing Services, North America (Intertek) to conduct several U.S. Department of Defense base studies to identify potential U.S. Department of Defense transportation systems that are strong candidates for introduction or expansion of plug-in electric vehicles (PEVs). This study is focused on the Marine Corps Base Camp Lejeune (MCBCL) located in North Carolina. Task 1 consisted of a survey of the non-tactical fleet of vehicles at MCBCL to begin the review of vehicle mission assignments and types of vehicles in service. In Task 2, daily operational characteristics of vehicles were identified to select vehicles for further monitoring and attachment of data loggers. Task 3 recorded vehicle movements in order to characterize the vehicles’ missions. The results of the data analysis and observations were provided. Individual observations of the selected vehicles provided the basis for recommendations related to PEV adoption, i.e., whether a battery electric vehicle (BEV) or plug-in hybrid electric vehicle (PHEV) (collectively PEVs) can fulfill the mission requirements. It also provided the basis for recommendations related to placement of PEV charging infrastructure. This report focuses on an implementation plan for the near-term adoption of PEVs into the MCBCL fleet. Intertek acknowledges the support of Idaho National Laboratory, Marine Corps headquarters, and Marine Corps Base Camp Lejeune fleet management and personnel for participation in this study. Intertek is pleased to provide this report and is encouraged by enthusiasm and support from MCBCL personnel.

A heuristic for the inventory management of smart vending machine systems

Directory of Open Access Journals (Sweden)

Yang-Byung Park

2012-12-01

Full Text Available Purpose: The purpose of this paper is to propose a heuristic for the inventory management of smart vending machine systems with product substitution under the replenishment point, order-up-to level policy and to evaluate its performance.Design/methodology/approach: The heuristic is developed on the basis of the decoupled approach. An integer linear mathematical model is built to determine the number of product storage compartments and replenishment threshold for each smart vending machine in the system and the Clarke and Wright’s savings algorithm is applied to route vehicles for inventory replenishments of smart vending machines that share the same delivery days. Computational experiments are conducted on several small-size test problems to compare the proposed heuristic with the integrated optimization mathematical model with respect to system profit. Furthermore, a sensitivity analysis is carried out on a medium-size test problem to evaluate the effect of the customer service level on system profit using a computer simulation.Findings: The results show that the proposed heuristic yielded pretty good solutions with 5.7% error rate on average compared to the optimal solutions. The proposed heuristic took about 3 CPU minutes on average in the test problems being consisted of 10 five-product smart vending machines. It was confirmed that the system profit is significantly affected by the customer service level.Originality/value: The inventory management of smart vending machine systems is newly treated. Product substitutions are explicitly considered in the model. The proposed heuristic is effective as well as efficient. It can be easily modified for application to various retail vending settings under a vendor-managed inventory scheme with POS system.

Electrical-Loss Analysis of Power-Split Hybrid Electric Vehicles

Directory of Open Access Journals (Sweden)

Andrea Bonfiglio

2017-12-01

Full Text Available The growing development of hybrid electric vehicles (HEVs has seen the spread of architectures with transmission based on planetary gear train, realized thanks to two electric machines. This architecture, by continuously regulating the transmission ratio, allows the internal combustion engine (ICE to work in optimal conditions. On the one hand, the average ICE efficiency is increased thanks to better loading situations, while, on the other hand, electrical losses are introduced due to the power circulation between the two electrical machines mentioned above. The aim of this study is then to accurately evaluate electrical losses and the average ICE efficiency in various operating conditions and over different road missions. The models used in this study are presented for both the Continuously Variable Transmission (CVT architecture and the Discontinuously Variable Transmission (DVT architecture. In addition, efficiency maps of the main components are shown. Finally, the simulation results are presented to point out strengths and weaknesses of the CVT architecture.

Machine medical ethics

CERN Document Server

Pontier, Matthijs

2015-01-01

The essays in this book, written by researchers from both humanities and sciences, describe various theoretical and experimental approaches to adding medical ethics to a machine in medical settings. Medical machines are in close proximity with human beings, and getting closer: with patients who are in vulnerable states of health, who have disabilities of various kinds, with the very young or very old, and with medical professionals. In such contexts, machines are undertaking important medical tasks that require emotional sensitivity, knowledge of medical codes, human dignity, and privacy. As machine technology advances, ethical concerns become more urgent: should medical machines be programmed to follow a code of medical ethics? What theory or theories should constrain medical machine conduct? What design features are required? Should machines share responsibility with humans for the ethical consequences of medical actions? How ought clinical relationships involving machines to be modeled? Is a capacity for e...

Prediction of Driver’s Intention of Lane Change by Augmenting Sensor Information Using Machine Learning Techniques

Science.gov (United States)

Kim, Il-Hwan; Bong, Jae-Hwan; Park, Jooyoung; Park, Shinsuk

2017-01-01

Driver assistance systems have become a major safety feature of modern passenger vehicles. The advanced driver assistance system (ADAS) is one of the active safety systems to improve the vehicle control performance and, thus, the safety of the driver and the passengers. To use the ADAS for lane change control, rapid and correct detection of the driver’s intention is essential. This study proposes a novel preprocessing algorithm for the ADAS to improve the accuracy in classifying the driver’s intention for lane change by augmenting basic measurements from conventional on-board sensors. The information on the vehicle states and the road surface condition is augmented by using an artificial neural network (ANN) models, and the augmented information is fed to a support vector machine (SVM) to detect the driver’s intention with high accuracy. The feasibility of the developed algorithm was tested through driving simulator experiments. The results show that the classification accuracy for the driver’s intention can be improved by providing an SVM model with sufficient driving information augmented by using ANN models of vehicle dynamics. PMID:28604582

Prediction of Driver’s Intention of Lane Change by Augmenting Sensor Information Using Machine Learning Techniques

Directory of Open Access Journals (Sweden)

Il-Hwan Kim

2017-06-01

Full Text Available Driver assistance systems have become a major safety feature of modern passenger vehicles. The advanced driver assistance system (ADAS is one of the active safety systems to improve the vehicle control performance and, thus, the safety of the driver and the passengers. To use the ADAS for lane change control, rapid and correct detection of the driver’s intention is essential. This study proposes a novel preprocessing algorithm for the ADAS to improve the accuracy in classifying the driver’s intention for lane change by augmenting basic measurements from conventional on-board sensors. The information on the vehicle states and the road surface condition is augmented by using an artificial neural network (ANN models, and the augmented information is fed to a support vector machine (SVM to detect the driver’s intention with high accuracy. The feasibility of the developed algorithm was tested through driving simulator experiments. The results show that the classification accuracy for the driver’s intention can be improved by providing an SVM model with sufficient driving information augmented by using ANN models of vehicle dynamics.

Comparison of four machine learning algorithms for their applicability in satellite-based optical rainfall retrievals

Science.gov (United States)

Meyer, Hanna; Kühnlein, Meike; Appelhans, Tim; Nauss, Thomas

2016-03-01

Machine learning (ML) algorithms have successfully been demonstrated to be valuable tools in satellite-based rainfall retrievals which show the practicability of using ML algorithms when faced with high dimensional and complex data. Moreover, recent developments in parallel computing with ML present new possibilities for training and prediction speed and therefore make their usage in real-time systems feasible. This study compares four ML algorithms - random forests (RF), neural networks (NNET), averaged neural networks (AVNNET) and support vector machines (SVM) - for rainfall area detection and rainfall rate assignment using MSG SEVIRI data over Germany. Satellite-based proxies for cloud top height, cloud top temperature, cloud phase and cloud water path serve as predictor variables. The results indicate an overestimation of rainfall area delineation regardless of the ML algorithm (averaged bias = 1.8) but a high probability of detection ranging from 81% (SVM) to 85% (NNET). On a 24-hour basis, the performance of the rainfall rate assignment yielded R2 values between 0.39 (SVM) and 0.44 (AVNNET). Though the differences in the algorithms' performance were rather small, NNET and AVNNET were identified as the most suitable algorithms. On average, they demonstrated the best performance in rainfall area delineation as well as in rainfall rate assignment. NNET's computational speed is an additional advantage in work with large datasets such as in remote sensing based rainfall retrievals. However, since no single algorithm performed considerably better than the others we conclude that further research in providing suitable predictors for rainfall is of greater necessity than an optimization through the choice of the ML algorithm.

Humanizing machines: Anthropomorphization of slot machines increases gambling.

Science.gov (United States)

Riva, Paolo; Sacchi, Simona; Brambilla, Marco

2015-12-01

Do people gamble more on slot machines if they think that they are playing against humanlike minds rather than mathematical algorithms? Research has shown that people have a strong cognitive tendency to imbue humanlike mental states to nonhuman entities (i.e., anthropomorphism). The present research tested whether anthropomorphizing slot machines would increase gambling. Four studies manipulated slot machine anthropomorphization and found that exposing people to an anthropomorphized description of a slot machine increased gambling behavior and reduced gambling outcomes. Such findings emerged using tasks that focused on gambling behavior (Studies 1 to 3) as well as in experimental paradigms that included gambling outcomes (Studies 2 to 4). We found that gambling outcomes decrease because participants primed with the anthropomorphic slot machine gambled more (Study 4). Furthermore, we found that high-arousal positive emotions (e.g., feeling excited) played a role in the effect of anthropomorphism on gambling behavior (Studies 3 and 4). Our research indicates that the psychological process of gambling-machine anthropomorphism can be advantageous for the gaming industry; however, this may come at great expense for gamblers' (and their families') economic resources and psychological well-being. (c) 2015 APA, all rights reserved).

A note on ranking assignments using reoptimization

DEFF Research Database (Denmark)

Pedersen, Christian Roed; Nielsen, L.R.; Andersen, K.A.

2005-01-01

We consider the problem of ranking assignments according to cost in the classical linear assignment problem. An algorithm partitioning the set of possible assignments, as suggested by Murty, is presented where, for each partition, the optimal assignment is calculated using a new reoptimization...

Use of unmanned aerial vehicles for efficient beach litter monitoring

KAUST Repository

Martin, Cecilia

2018-05-05

A global beach litter assessment is challenged by use of low-efficiency methodologies and incomparable protocols that impede data integration and acquisition at a national scale. The implementation of an objective, reproducible and efficient approach is therefore required. Here we show the application of a remote sensing based methodology using a test beach located on the Saudi Arabian Red Sea coastline. Litter was recorded via image acquisition from an Unmanned Aerial Vehicle, while an automatic processing of the high volume of imagery was developed through machine learning, employed for debris detection and classification in three categories. Application of the method resulted in an almost 40 times faster beach coverage when compared to a standard visual-census approach. While the machine learning tool faced some challenges in correctly detecting objects of interest, first classification results are promising and motivate efforts to further develop the technique and implement it at much larger scales.

Use of unmanned aerial vehicles for efficient beach litter monitoring

KAUST Repository

Martin, Cecilia; Parkes, Stephen; Zhang, Qiannan; Zhang, Xiangliang; McCabe, Matthew; Duarte, Carlos M.

2018-01-01

A global beach litter assessment is challenged by use of low-efficiency methodologies and incomparable protocols that impede data integration and acquisition at a national scale. The implementation of an objective, reproducible and efficient approach is therefore required. Here we show the application of a remote sensing based methodology using a test beach located on the Saudi Arabian Red Sea coastline. Litter was recorded via image acquisition from an Unmanned Aerial Vehicle, while an automatic processing of the high volume of imagery was developed through machine learning, employed for debris detection and classification in three categories. Application of the method resulted in an almost 40 times faster beach coverage when compared to a standard visual-census approach. While the machine learning tool faced some challenges in correctly detecting objects of interest, first classification results are promising and motivate efforts to further develop the technique and implement it at much larger scales.

Code-expanded radio access protocol for machine-to-machine communications

DEFF Research Database (Denmark)

Thomsen, Henning; Kiilerich Pratas, Nuno; Stefanovic, Cedomir

2013-01-01

The random access methods used for support of machine-to-machine, also referred to as Machine-Type Communications, in current cellular standards are derivatives of traditional framed slotted ALOHA and therefore do not support high user loads efficiently. We propose an approach that is motivated b...... subframes and orthogonal preambles, the amount of available contention resources is drastically increased, enabling the massive support of Machine-Type Communication users that is beyond the reach of current systems.......The random access methods used for support of machine-to-machine, also referred to as Machine-Type Communications, in current cellular standards are derivatives of traditional framed slotted ALOHA and therefore do not support high user loads efficiently. We propose an approach that is motivated...... by the random access method employed in LTE, which significantly increases the amount of contention resources without increasing the system resources, such as contention subframes and preambles. This is accomplished by a logical, rather than physical, extension of the access method in which the available system...

Condition Assessment and End-of-Life Prediction System for Electric Machines and Their Loads

Science.gov (United States)

Parlos, Alexander G.; Toliyat, Hamid A.

2005-01-01

An end-of-life prediction system developed for electric machines and their loads could be used in integrated vehicle health monitoring at NASA and in other government agencies. This system will provide on-line, real-time condition assessment and end-of-life prediction of electric machines (e.g., motors, generators) and/or their loads of mechanically coupled machinery (e.g., pumps, fans, compressors, turbines, conveyor belts, magnetic levitation trains, and others). In long-duration space flight, the ability to predict the lifetime of machinery could spell the difference between mission success or failure. Therefore, the system described here may be of inestimable value to the U.S. space program. The system will provide continuous monitoring for on-line condition assessment and end-of-life prediction as opposed to the current off-line diagnoses.

Real life working shift assignment problem

Science.gov (United States)

Sze, San-Nah; Kwek, Yeek-Ling; Tiong, Wei-King; Chiew, Kang-Leng

2017-07-01

This study concerns about the working shift assignment in an outlet of Supermarket X in Eastern Mall, Kuching. The working shift assignment needs to be solved at least once in every month. Current approval process of working shifts is too troublesome and time-consuming. Furthermore, the management staff cannot have an overview of manpower and working shift schedule. Thus, the aim of this study is to develop working shift assignment simulation and propose a working shift assignment solution. The main objective for this study is to fulfill manpower demand at minimum operation cost. Besides, the day off and meal break policy should be fulfilled accordingly. Demand based heuristic is proposed to assign working shift and the quality of the solution is evaluated by using the real data.

Research on an Axial Magnetic-Field-Modulated Brushless Double Rotor Machine

Directory of Open Access Journals (Sweden)

Bin Yu

2013-09-01

Full Text Available Double rotor machine, an electronic continuously variable transmission, has great potential in application of hybrid electric vehicles (HEVs, wind power and marine propulsion. In this paper, an axial magnetic-field-modulated brushless double rotor machine (MFM-BDRM, which can realize the speed decoupling between the shaft of the modulating ring rotor and that of the permanent magnet rotor is proposed. Without brushes and slip rings, the axial MFM-BDRM offers significant advantages such as excellent reliability and high efficiency. Since the number of pole pairs of the stator is not equal to that of the permanent magnet rotor, which differs from the traditional permanent magnet synchronous machine, the operating principle of the MFM-BDRM is deduced. The relations of corresponding speed and toque transmission are analytically discussed. The cogging toque characteristics, especially the order of the cogging torque are mathematically formulated. Matching principle of the number of pole pairs of the stator, that of the permanent magnet rotor and the number of ferromagnetic pole pieces is inferred since it affects MFM-BDRM’s performance greatly, especially in the respect of the cogging torque and electromagnetic torque ripple. The above analyses are assessed with the three-dimensional (3D finite-element method (FEM.

24 CFR 221.770 - Assignment option.

Science.gov (United States)

2010-04-01

... 24 Housing and Urban Development 2 2010-04-01 2010-04-01 false Assignment option. 221.770 Section... § 221.770 Assignment option. A mortgagee holding a conditional or firm commitment issued on or before... mortgagee's approved underwriter on or before November 30, 1983) has the option to assign, transfer and...

Exploiting the ALICE HLT for PROOF by scheduling of Virtual Machines

International Nuclear Information System (INIS)

Meoni, Marco; Boettger, Stefan; Zelnicek, Pierre; Kebschull, Udo; Lindenstruth, Volker

2011-01-01

The HLT (High-Level Trigger) group of the ALICE experiment at the LHC has prepared a virtual Parallel ROOT Facility (PROOF) enabled cluster (HAF - HLT Analysis Facility) for fast physics analysis, detector calibration and reconstruction of data samples. The HLT-Cluster currently consists of 2860 CPU cores and 175TB of storage. Its purpose is the online filtering of the relevant part of data produced by the particle detector. However, data taking is not running continuously and exploiting unused cluster resources for other applications is highly desirable and improves the usage-cost ratio of the HLT cluster. As such, unused computing resources are dedicated to a PROOF-enabled virtual cluster available to the entire collaboration. This setup is especially aimed at the prototyping phase of analyses that need a high number of development iterations and a short response time, e.g. tuning of analysis cuts, calibration and alignment. HAF machines are enabled and disabled upon user request to start or complete analysis tasks. This is achieved by a virtual machine scheduling framework which dynamically assigns and migrates virtual machines running PROOF workers to unused physical resources. Using this approach we extend the HLT usage scheme to running both online and offline computing, thereby optimizing the resource usage.

Human-Automation Interaction Design for Adaptive Cruise Control Systems of Ground Vehicles

Directory of Open Access Journals (Sweden)

Hwisoo Eom

2015-06-01

Full Text Available A majority of recently developed advanced vehicles have been equipped with various automated driver assistance systems, such as adaptive cruise control (ACC and lane keeping assistance systems. ACC systems have several operational modes, and drivers can be unaware of the mode in which they are operating. Because mode confusion is a significant human error factor that contributes to traffic accidents, it is necessary to develop user interfaces for ACC systems that can reduce mode confusion. To meet this requirement, this paper presents a new human-automation interaction design methodology in which the compatibility of the machine and interface models is determined using the proposed criteria, and if the models are incompatible, one or both of the models is/are modified to make them compatible. To investigate the effectiveness of our methodology, we designed two new interfaces by separately modifying the machine model and the interface model and then performed driver-in-the-loop experiments. The results showed that modifying the machine model provides a more compact, acceptable, effective, and safe interface than modifying the interface model.

Human-Automation Interaction Design for Adaptive Cruise Control Systems of Ground Vehicles.

Science.gov (United States)

Eom, Hwisoo; Lee, Sang Hun

2015-06-12

A majority of recently developed advanced vehicles have been equipped with various automated driver assistance systems, such as adaptive cruise control (ACC) and lane keeping assistance systems. ACC systems have several operational modes, and drivers can be unaware of the mode in which they are operating. Because mode confusion is a significant human error factor that contributes to traffic accidents, it is necessary to develop user interfaces for ACC systems that can reduce mode confusion. To meet this requirement, this paper presents a new human-automation interaction design methodology in which the compatibility of the machine and interface models is determined using the proposed criteria, and if the models are incompatible, one or both of the models is/are modified to make them compatible. To investigate the effectiveness of our methodology, we designed two new interfaces by separately modifying the machine model and the interface model and then performed driver-in-the-loop experiments. The results showed that modifying the machine model provides a more compact, acceptable, effective, and safe interface than modifying the interface model.

Job Assignments under Moral Hazard

DEFF Research Database (Denmark)

Koch, Alexander; Nafziger, Julia

Inefficient job assignments are usually explained with incomplete information about employees' abilities or contractual imperfections. We show that inefficient assignments arise even without uncertainty about the employee's ability and with complete contracts. Building on this result we provide...

EZ-ASSIGN, a program for exhaustive NMR chemical shift assignments of large proteins from complete or incomplete triple-resonance data

Energy Technology Data Exchange (ETDEWEB)

Zuiderweg, Erik R. P., E-mail: zuiderwe@umich.edu; Bagai, Ireena [The University of Michigan Medical School, Department of Biological Chemistry (United States); Rossi, Paolo [Rutgers University, Center for Integrative Proteomics Research (United States); Bertelsen, Eric B. [Arbor Communications, Inc. (United States)

2013-10-15

For several of the proteins in the BioMagResBank larger than 200 residues, 60 % or fewer of the backbone resonances were assigned. But how reliable are those assignments? In contrast to complete assignments, where it is possible to check whether every triple-resonance Generalized Spin System (GSS) is assigned once and only once, with incomplete data one should compare all possible assignments and pick the best one. But that is not feasible: For example, for 200 residues and an incomplete set of 100 GSS, there are 1.6 Multiplication-Sign 10{sup 260} possible assignments. In 'EZ-ASSIGN', the protein sequence is divided in smaller unique fragments. Combined with intelligent search approaches, an exhaustive comparison of all possible assignments is now feasible using a laptop computer. The program was tested with experimental data of a 388-residue domain of the Hsp70 chaperone protein DnaK and for a 351-residue domain of a type III secretion ATPase. EZ-ASSIGN reproduced the hand assignments. It did slightly better than the computer program PINE (Bahrami et al. in PLoS Comput Biol 5(3):e1000307, 2009) and significantly outperformed SAGA (Crippen et al. in J Biomol NMR 46:281-298, 2010), AUTOASSIGN (Zimmerman et al. in J Mol Biol 269:592-610, 1997), and IBIS (Hyberts and Wagner in J Biomol NMR 26:335-344, 2003). Next, EZ-ASSIGN was used to investigate how well NMR data of decreasing completeness can be assigned. We found that the program could confidently assign fragments in very incomplete data. Here, EZ-ASSIGN dramatically outperformed all the other assignment programs tested.

24 CFR 221.255 - Assignment option.

Science.gov (United States)

2010-04-01

... 24 Housing and Urban Development 2 2010-04-01 2010-04-01 false Assignment option. 221.255 Section... Assignment option. (a) A mortgagee holding a mortgage insured pursuant to a conditional or firm commitment issued on or before November 30, 1983 has the option to assign, transfer and deliver to the Commissioner...

Autonomous vehicles:challenges, opportunities, and future implications for transportation policies

Institute of Scientific and Technical Information of China (English)

Saeed Asadi Bagloee; Madjid Tavana; Mohsen Asadi; Tracey Oliver

2016-01-01

This study investigates the challenges and opportunities pertaining to transportation policies that may arise as a result of emerging autonomous vehicle (AV) technologies. AV technologies can decrease the trans-portation cost and increase accessibility to low-income households and persons with mobility issues. This emerg-ing technology also has far-reaching applications and implications beyond all current expectations. This paper provides a comprehensive review of the relevant literature and explores a broad spectrum of issues from safety to machine ethics. An indispensable part of a prospective AV development is communication over cars and infrastructure (connected vehicles). A major knowledge gap exists in AV technology with respect to routing behaviors. Connected-vehicle technology provides a great opportunity to imple-ment an efficient and intelligent routing system. To this end, we propose a conceptual navigation model based on a fleet of AVs that are centrally dispatched over a network seeking system optimization. This study contributes to the literature on two fronts: (i) it attempts to shed light on future opportunities as well as possible hurdles associated with AV technology;and (ii) it conceptualizes a navigation model for the AV which leads to highly efficient traffic circulations.

Indirect Tire Monitoring System - Machine Learning Approach

Science.gov (United States)

Svensson, O.; Thelin, S.; Byttner, S.; Fan, Y.

2017-10-01

The heavy vehicle industry has today no requirement to provide a tire pressure monitoring system by law. This has created issues surrounding unknown tire pressure and thread depth during active service. There is also no standardization for these kind of systems which means that different manufacturers and third party solutions work after their own principles and it can be hard to know what works for a given vehicle type. The objective is to create an indirect tire monitoring system that can generalize a method that detect both incorrect tire pressure and thread depth for different type of vehicles within a fleet without the need for additional physical sensors or vehicle specific parameters. The existing sensors that are connected communicate through CAN and are interpreted by the Drivec Bridge hardware that exist in the fleet. By using supervised machine learning a classifier was created for each axle where the main focus was the front axle which had the most issues. The classifier will classify the vehicles tires condition and will be implemented in Drivecs cloud service where it will receive its data. The resulting classifier is a random forest implemented in Python. The result from the front axle with a data set consisting of 9767 samples of buses with correct tire condition and 1909 samples of buses with incorrect tire condition it has an accuracy of 90.54% (0.96%). The data sets are created from 34 unique measurements from buses between January and May 2017. This classifier has been exported and is used inside a Node.js module created for Drivecs cloud service which is the result of the whole implementation. The developed solution is called Indirect Tire Monitoring System (ITMS) and is seen as a process. This process will predict bad classes in the cloud which will lead to warnings. The warnings are defined as incidents. They contain only the information needed and the bandwidth of the incidents are also controlled so incidents are created within an

Free-piston engine-and-hydraulic pump for railway vehicles

Directory of Open Access Journals (Sweden)

A. F. Golovchuk

2013-04-01

Full Text Available Purpose. The development of the free-piston diesel engine-and-hydraulic pump for the continuously variable hydrostatical transmission of mobile power vehicles. Methodology. For a long time engine builders have been interesting in the problem of developing free piston engines, which have much bigger coefficient of efficiency (40…80%. Such engines don’t have the conversion of reciprocating motion for inner combustion engine piston into rotating motion of crankshaft, from which the engine torque is transferred to the power machine transmission. Free-piston engines of inner combustion don’t have the crank mechanism (CM that significantly reduces mechanical losses for friction. Such engines can be used as compressors. Free-piston engine compressor (FPEC – is a free-piston machine in which energy received from engine’s cylinder is being transferred direct to compressor’s pistons connected with operational pistons of engine without crank mechanism. Part of the pressed air is being consumed for engine cylinder drain and the other part is going to the consumer. Findings. The use of free-piston engines-and-hydraulic pumps as power-transmission plants of power vehicles (diesel locomotives, combine harvester, tractors, cars and other mobile and stationary power installations with the continuously variable transmissions allows cost effectiveness improvement and metal consumption reduction of these vehicles, since the cost effectiveness of FPE is higher by 25-30%, and the metal consumption is lower by 40-50%. Originality. One of the important advantages of the free-piston engines is their simplicity and engine balance. As a result of the crank mechanism absence their construction is much simplified and the vibrations, peculiar to the ordinary engines are eliminated. In such installation the engine pistons are directly connected through the rod to compressor pistons and therefore there are no losses in the bearing bushes. Practical value. The free

Simple machines

CERN Document Server

Graybill, George

2007-01-01

Just how simple are simple machines? With our ready-to-use resource, they are simple to teach and easy to learn! Chocked full of information and activities, we begin with a look at force, motion and work, and examples of simple machines in daily life are given. With this background, we move on to different kinds of simple machines including: Levers, Inclined Planes, Wedges, Screws, Pulleys, and Wheels and Axles. An exploration of some compound machines follows, such as the can opener. Our resource is a real time-saver as all the reading passages, student activities are provided. Presented in s

Machine performance assessment and enhancement for a hexapod machine

Energy Technology Data Exchange (ETDEWEB)

Mou, J.I. [Arizona State Univ., Tempe, AZ (United States); King, C. [Sandia National Labs., Livermore, CA (United States). Integrated Manufacturing Systems Center

1998-03-19

The focus of this study is to develop a sensor fused process modeling and control methodology to model, assess, and then enhance the performance of a hexapod machine for precision product realization. Deterministic modeling technique was used to derive models for machine performance assessment and enhancement. Sensor fusion methodology was adopted to identify the parameters of the derived models. Empirical models and computational algorithms were also derived and implemented to model, assess, and then enhance the machine performance. The developed sensor fusion algorithms can be implemented on a PC-based open architecture controller to receive information from various sensors, assess the status of the process, determine the proper action, and deliver the command to actuators for task execution. This will enhance a hexapod machine`s capability to produce workpieces within the imposed dimensional tolerances.

Accelerated Lane-Changing Trajectory Planning of Automated Vehicles with Vehicle-to-Vehicle Collaboration

Directory of Open Access Journals (Sweden)

Haijian Bai

2017-01-01

Full Text Available Considering the complexity of lane changing using automated vehicles and the frequency of turning lanes in city settings, this paper aims to generate an accelerated lane-changing trajectory using vehicle-to-vehicle collaboration (V2VC. Based on the characteristics of accelerated lane changing, we used a polynomial method and cooperative strategies for trajectory planning to establish a lane-changing model under different degrees of collaboration with the following vehicle in the target lane by considering vehicle kinematics and comfort requirements. Furthermore, considering the shortcomings of the traditional elliptical vehicle and round vehicle models, we established a rectangular vehicle model with collision boundary conditions by analysing the relationships between the possible collision points and the outline of the vehicle. Then, we established a simulation model for the accelerated lane-changing process in different environments under different degrees of collaboration. The results show that, by using V2VC, we can achieve safe accelerated lane-changing trajectories and simultaneously satisfy the requirements of vehicle kinematics and comfort control.

Estimation of tire characteristics by concerning test data of vehicles; Jidosha no senkai shiken data ni yoru dire tokusei no suisan

Energy Technology Data Exchange (ETDEWEB)

Nakamura, M; Sekine, T; Nagae, H [Nihon University, Tokyo (Japan)

1997-10-01

To study and/or develop the vehicle motion of a braking in turns theoretically, the cornering characteristics of the tire under the action of braking forces must be required. On the other hand, such data are very few to be published and also there be few tire testing machine to be able to use. The authors tried to derive such data from the vehicle behaviors in steady turns and braking in turns. Because each wheel loads are unknown factors, the two wheeled vehicle model are employed in analysis. The methodology of analysis and the reasonable results are presented in this paper. 5 refs., 10 figs., 2 tabs.

An algorithm for ranking assignments using reoptimization

DEFF Research Database (Denmark)

Pedersen, Christian Roed; Nielsen, Lars Relund; Andersen, Kim Allan

2008-01-01

We consider the problem of ranking assignments according to cost in the classical linear assignment problem. An algorithm partitioning the set of possible assignments, as suggested by Murty, is presented where, for each partition, the optimal assignment is calculated using a new reoptimization...... technique. Computational results for the new algorithm are presented...

48 CFR 42.602 - Assignment and location.

Science.gov (United States)

2010-10-01

... 48 Federal Acquisition Regulations System 1 2010-10-01 2010-10-01 false Assignment and location... Assignment and location. (a) A CACO may be assigned only when (1) the contractor has at least two locations..., or a full-time CACO may be assigned. In determining the location of the CACO, the responsible agency...

Superconducting rotating machines

International Nuclear Information System (INIS)

Smith, J.L. Jr.; Kirtley, J.L. Jr.; Thullen, P.

1975-01-01

The opportunities and limitations of the applications of superconductors in rotating electric machines are given. The relevant properties of superconductors and the fundamental requirements for rotating electric machines are discussed. The current state-of-the-art of superconducting machines is reviewed. Key problems, future developments and the long range potential of superconducting machines are assessed

Advanced single permanent magnet axipolar ironless stator ac motor for electric passenger vehicles

Science.gov (United States)

Beauchamp, E. D.; Hadfield, J. R.; Wuertz, K. L.

1983-01-01

A program was conducted to design and develop an advanced-concept motor specifically created for propulsion of electric vehicles with increased range, reduced energy consumption, and reduced life-cycle costs in comparison with conventional systems. The motor developed is a brushless, dc, rare-earth cobalt, permanent magnet, axial air gap inductor machine that uses an ironless stator. Air cooling is inherent provided by the centrifugal-fan action of the rotor poles. An extensive design phase was conducted, which included analysis of the system performance versus the SAE J227a(D) driving cycle. A proof-of-principle model was developed and tested, and a functional model was developed and tested. Full generator-level testing was conducted on the functional model, recording electromagnetic, thermal, aerodynamic, and acoustic noise data. The machine demonstrated 20.3 kW output at 1466 rad/s and 160 dc. The novel ironless stator demonstated the capability to continuously operate at peak current. The projected system performance based on the use of a transistor inverter is 23.6 kW output power at 1466 rad/s and 83.3 percent efficiency. Design areas of concern regarding electric vehicle applications include the inherently high windage loss and rotor inertia.

Sustainable machining

CERN Document Server

2017-01-01

This book provides an overview on current sustainable machining. Its chapters cover the concept in economic, social and environmental dimensions. It provides the reader with proper ways to handle several pollutants produced during the machining process. The book is useful on both undergraduate and postgraduate levels and it is of interest to all those working with manufacturing and machining technology.

Vehicle classification in WAMI imagery using deep network

Science.gov (United States)

Yi, Meng; Yang, Fan; Blasch, Erik; Sheaff, Carolyn; Liu, Kui; Chen, Genshe; Ling, Haibin

2016-05-01

Humans have always had a keen interest in understanding activities and the surrounding environment for mobility, communication, and survival. Thanks to recent progress in photography and breakthroughs in aviation, we are now able to capture tens of megapixels of ground imagery, namely Wide Area Motion Imagery (WAMI), at multiple frames per second from unmanned aerial vehicles (UAVs). WAMI serves as a great source for many applications, including security, urban planning and route planning. These applications require fast and accurate image understanding which is time consuming for humans, due to the large data volume and city-scale area coverage. Therefore, automatic processing and understanding of WAMI imagery has been gaining attention in both industry and the research community. This paper focuses on an essential step in WAMI imagery analysis, namely vehicle classification. That is, deciding whether a certain image patch contains a vehicle or not. We collect a set of positive and negative sample image patches, for training and testing the detector. Positive samples are 64 × 64 image patches centered on annotated vehicles. We generate two sets of negative images. The first set is generated from positive images with some location shift. The second set of negative patches is generated from randomly sampled patches. We also discard those patches if a vehicle accidentally locates at the center. Both positive and negative samples are randomly divided into 9000 training images and 3000 testing images. We propose to train a deep convolution network for classifying these patches. The classifier is based on a pre-trained AlexNet Model in the Caffe library, with an adapted loss function for vehicle classification. The performance of our classifier is compared to several traditional image classifier methods using Support Vector Machine (SVM) and Histogram of Oriented Gradient (HOG) features. While the SVM+HOG method achieves an accuracy of 91.2%, the accuracy of our deep

Research on a novel axial-flux magnetic-field-modulated brushless double-rotor machine with low axial force and high efficiency

Directory of Open Access Journals (Sweden)

Chengde Tong

2017-05-01

Full Text Available The axial-flux magnetic-field-modulated brushless double-rotor machine (MFM-BDRM is a possible alternative as a power-split device for hybrid electric vehicles (HEVs. However, the existence of large axial force may lead to assembly problems and rich inner air-gap harmonics could result in high PM loss and low efficiency. This paper proposes a novel axial-flux MFM-BDRM with improved PM rotor structure. 2-D analytical method to predict the magnetic-field distribution of the proposed MFM-BDRM is developed and the design procedure of the proposed machine is illustrated. The impact of key geometrical parameters on axial force and torque is investigated. To evaluate the advantage of the proposed machine, a comparison is made with a conventional one with respect to electromagnetic performances. Results show that the proposed machine is effective in reducing PM eddy loss and axial force by 60% and 35%, respectively.

The 20th annual intelligent ground vehicle competition: building a generation of robotists

Science.gov (United States)

Theisen, Bernard L.; Kosinski, Andrew

2013-01-01

The Intelligent Ground Vehicle Competition (IGVC) is one of four, unmanned systems, student competitions that were founded by the Association for Unmanned Vehicle Systems International (AUVSI). The IGVC is a multidisciplinary exercise in product realization that challenges college engineering student teams to integrate advanced control theory, machine vision, vehicular electronics and mobile platform fundamentals to design and build an unmanned system. Teams from around the world focus on developing a suite of dual-use technologies to equip ground vehicles of the future with intelligent driving capabilities. Over the past 20 years, the competition has challenged undergraduate, graduate and Ph.D. students with real world applications in intelligent transportation systems, the military and manufacturing automation. To date, teams from over 80 universities and colleges have participated. This paper describes some of the applications of the technologies required by this competition and discusses the educational benefits. The primary goal of the IGVC is to advance engineering education in intelligent vehicles and related technologies. The employment and professional networking opportunities created for students and industrial sponsors through a series of technical events over the four-day competition are highlighted. Finally, an assessment of the competition based on participation is presented.

EZ-ASSIGN, a program for exhaustive NMR chemical shift assignments of large proteins from complete or incomplete triple-resonance data

International Nuclear Information System (INIS)

Zuiderweg, Erik R. P.; Bagai, Ireena; Rossi, Paolo; Bertelsen, Eric B.

2013-01-01

For several of the proteins in the BioMagResBank larger than 200 residues, 60 % or fewer of the backbone resonances were assigned. But how reliable are those assignments? In contrast to complete assignments, where it is possible to check whether every triple-resonance Generalized Spin System (GSS) is assigned once and only once, with incomplete data one should compare all possible assignments and pick the best one. But that is not feasible: For example, for 200 residues and an incomplete set of 100 GSS, there are 1.6 × 10 260 possible assignments. In “EZ-ASSIGN”, the protein sequence is divided in smaller unique fragments. Combined with intelligent search approaches, an exhaustive comparison of all possible assignments is now feasible using a laptop computer. The program was tested with experimental data of a 388-residue domain of the Hsp70 chaperone protein DnaK and for a 351-residue domain of a type III secretion ATPase. EZ-ASSIGN reproduced the hand assignments. It did slightly better than the computer program PINE (Bahrami et al. in PLoS Comput Biol 5(3):e1000307, 2009) and significantly outperformed SAGA (Crippen et al. in J Biomol NMR 46:281–298, 2010), AUTOASSIGN (Zimmerman et al. in J Mol Biol 269:592–610, 1997), and IBIS (Hyberts and Wagner in J Biomol NMR 26:335–344, 2003). Next, EZ-ASSIGN was used to investigate how well NMR data of decreasing completeness can be assigned. We found that the program could confidently assign fragments in very incomplete data. Here, EZ-ASSIGN dramatically outperformed all the other assignment programs tested

Asynchronized synchronous machines

CERN Document Server

Botvinnik, M M

1964-01-01

Asynchronized Synchronous Machines focuses on the theoretical research on asynchronized synchronous (AS) machines, which are "hybrids” of synchronous and induction machines that can operate with slip. Topics covered in this book include the initial equations; vector diagram of an AS machine; regulation in cases of deviation from the law of full compensation; parameters of the excitation system; and schematic diagram of an excitation regulator. The possible applications of AS machines and its calculations in certain cases are also discussed. This publication is beneficial for students and indiv

Multi-vehicle detection with identity awareness using cascade Adaboost and Adaptive Kalman filter for driver assistant system.

Science.gov (United States)

Wang, Baofeng; Qi, Zhiquan; Chen, Sizhong; Liu, Zhaodu; Ma, Guocheng

2017-01-01

Vision-based vehicle detection is an important issue for advanced driver assistance systems. In this paper, we presented an improved multi-vehicle detection and tracking method using cascade Adaboost and Adaptive Kalman filter(AKF) with target identity awareness. A cascade Adaboost classifier using Haar-like features was built for vehicle detection, followed by a more comprehensive verification process which could refine the vehicle hypothesis in terms of both location and dimension. In vehicle tracking, each vehicle was tracked with independent identity by an Adaptive Kalman filter in collaboration with a data association approach. The AKF adaptively adjusted the measurement and process noise covariance through on-line stochastic modelling to compensate the dynamics changes. The data association correctly assigned different detections with tracks using global nearest neighbour(GNN) algorithm while considering the local validation. During tracking, a temporal context based track management was proposed to decide whether to initiate, maintain or terminate the tracks of different objects, thus suppressing the sparse false alarms and compensating the temporary detection failures. Finally, the proposed method was tested on various challenging real roads, and the experimental results showed that the vehicle detection performance was greatly improved with higher accuracy and robustness.

Utilization Assessment of Target Electrification Vehicles at Marine Corps Base Camp Lejeune. Task 3

Energy Technology Data Exchange (ETDEWEB)

Schey, Stephen [Idaho National Lab. (INL), Idaho Falls, ID (United States); Francfort, Jim [Idaho National Lab. (INL), Idaho Falls, ID (United States)

2015-11-01

Battelle Energy Alliance, LLC, managing and operating contractor for the U.S. Department of Energy’s Idaho National Laboratory, is the lead laboratory for U.S. Department of Energy Advanced Vehicle Testing. Battelle Energy Alliance, LLC contracted with Intertek Testing Services, North America (Intertek) to conduct several U.S. Department of Defense base studies to identify potential U.S. Department of Defense transportation systems that are strong candidates for introduction or expansion of plug-in electric vehicles (PEVs). Task 1 consisted of a survey of the non-tactical fleet of vehicles at MCBCL to begin the review of vehicle mission assignments and types of vehicles in service. Task 2 involved identifying daily operational characteristics of select vehicles and initiating data logging of vehicle movements in order to characterize the vehicle’s mission. Individual observations of these selected vehicles provide the basis for recommendations related to PEV adoption and whether a battery electric vehicle or plug-in hybrid electric vehicle (collectively referred to as PEVs) can fulfill the mission requirements and provide observations related to placement of PEV charging infrastructure. This report provides the results of the data analysis and observations related to replacement of current vehicles with PEVs. This fulfills part of the Task 3 requirements. Task 3 also includes an assessment of the charging infrastructure required to support this replacement, which is the subject of a separate report. Intertek acknowledges the support of Idaho National Laboratory, Marine Corps headquarters, and Marine Corps Base Camp Lejeune Fleet management and personnel for participation in this study. Intertek is pleased to provide this report and is encouraged by enthusiasm and support from MCBCL personnel.

Machine Shop Lathes.

Science.gov (United States)

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…

A study on ultra-precision machining technique for Al6061-T6 to fabricate space infrared optics

Science.gov (United States)

Ryu, Geun-man; Lee, Gil-jae; Hyun, Sang-won; Sung, Ha-yeong; Chung, Euisik; Kim, Geon-hee

2014-08-01

In this paper, analysis of variance on designed experiments with full factorial design was applied to determine the optimized machining parameters for ultra-precision fabrication of the secondary aspheric mirror, which is one of the key elements of the space cryogenic infrared optics. A single point diamond turning machine (SPDTM, Nanotech 4μpL Moore) was adopted to fabricate the material, AL6061-T6, and the three machining parameters of cutting speed, feed rate and depth of cut were selected. With several randomly assigned experimental conditions, surface roughness of each condition was measured by a non-contact optical profiler (NT2000; Vecco). As a result of analysis using Minitab, the optimum cutting condition was determined as following; cutting speed: 122 m/min, feed rate: 3 mm/min and depth of cut: 1 μm. Finally, a 120 mm diameter aspheric secondary mirror was attached to a particularly designed jig by using mixture of paraffin and wax and successfully fabricated under the optimum machining parameters. The profile of machined surface was measured by a high-accuracy 3-D profilometer(UA3P; Panasonic) and we obtained the geometrical errors of 30.6 nm(RMS) and 262.4 nm(PV), which satisfy the requirements of the space cryogenic infrared optics.

Battery electric vehicles - implications for the driver interface.

Science.gov (United States)

Neumann, Isabel; Krems, Josef F

2016-03-01

The current study examines the human-machine interface of a battery electric vehicle (BEV) from a user-perspective, focussing on the evaluation of BEV-specific displays, the relevance of provided information and challenges for drivers due to the concept of electricity in a road vehicle. A sample of 40 users drove a BEV for 6 months. Data were gathered at three points of data collection. Participants perceived the BEV-specific displays as only moderately reliable and helpful for estimating the displayed parameters. This was even less the case after driving the BEV for 3 months. A taxonomy of user requirements was compiled revealing the need for improved and additional information, especially regarding energy consumption and efficiency. Drivers had difficulty understanding electrical units and the energy consumption of the BEV. On the background of general principles for display design, results provide implications how to display relevant information and how to facilitate drivers' understanding of energy consumption in BEVs. Practitioner Summary: Battery electric vehicle (BEV) displays need to incorporate new information. A taxonomy of user requirements was compiled revealing the need for improved and additional information in the BEV interface. Furthermore, drivers had trouble understanding electrical units and energy consumption; therefore, appropriate assistance is required. Design principles which are specifically important in the BEV context are discussed.

Robust vehicle detection in aerial images based on salient region selection and superpixel classification

Science.gov (United States)

Sahli, Samir; Duval, Pierre-Luc; Sheng, Yunlong; Lavigne, Daniel A.

2011-05-01

For detecting vehicles in large scale aerial images we first used a non-parametric method proposed recently by Rosin to define the regions of interest, where the vehicles appear with dense edges. The saliency map is a sum of distance transforms (DT) of a set of edges maps, which are obtained by a threshold decomposition of the gradient image with a set of thresholds. A binary mask for highlighting the regions of interest is then obtained by a moment-preserving thresholding of the normalized saliency map. Secondly, the regions of interest were over-segmented by the SLIC superpixels proposed recently by Achanta et al. to cluster pixels into the color constancy sub-regions. In the aerial images of 11.2 cm/pixel resolution, the vehicles in general do not exceed 20 x 40 pixels. We introduced a size constraint to guarantee no superpixels exceed the size of a vehicle. The superpixels were then classified to vehicle or non-vehicle by the Support Vector Machine (SVM), in which the Scale Invariant Feature Transform (SIFT) features and the Linear Binary Pattern (LBP) texture features were used. Both features were extracted at two scales with two size patches. The small patches capture local structures and the larger patches include the neighborhood information. Preliminary results show a significant gain in the detection. The vehicles were detected with a dense concentration of the vehicle-class superpixels. Even dark color cars were successfully detected. A validation process will follow to reduce the presence of isolated false alarms in the background.

Assessment of Charging Infrastructure for Plug-in Electric Vehicles at Marine Corps Base Camp Lejeune. Task 3

Energy Technology Data Exchange (ETDEWEB)

Schey, Stephen [Idaho National Lab. (INL), Idaho Falls, ID (United States); Francfort, Jim [Idaho National Lab. (INL), Idaho Falls, ID (United States)

2015-11-01

Battelle Energy Alliance, LLC, managing and operating contractor for the U.S. Department of Energy’s Idaho National Laboratory, is the lead laboratory for the U.S. Department of Energy’s advanced vehicle testing. Battelle Energy Alliance, LLC contracted with Intertek Testing Services, North America (Intertek) to conduct several U.S. Department of Defense-based studies to identify potential U.S. Department of Defense transportation systems that are strong candidates for introduction or expansion of plug-in electric vehicles (PEVs). Task 1 consisted of a survey of the non-tactical fleet of vehicles at Marine Corps Base Camp Lejeune to begin the review of vehicle mission assignments and types of vehicles in service. Task 2 selected vehicles for further monitoring and involved identifying daily operational characteristics of these select vehicles. Data logging of vehicle movements was initiated in order to characterize the vehicle’s mission. The Task 3 vehicle utilization report provided results of the data analysis and observations related to the replacement of current vehicles with PEVs. Finally, this report provides an assessment of charging infrastructure required to support the suggested PEV replacements. Intertek acknowledges the support of Idaho National Laboratory, Marine Corps headquarters, and Marine Corps Base Camp Lejeune Fleet management and personnel for participation in this study. Intertek is pleased to provide this report and is encouraged by enthusiasm and support from Marine Corps Base Camp Lejeune personnel.

Scene recognition and colorization for vehicle infrared images

Science.gov (United States)

Hou, Junjie; Sun, Shaoyuan; Shen, Zhenyi; Huang, Zhen; Zhao, Haitao

2016-10-01

In order to make better use of infrared technology for driving assistance system, a scene recognition and colorization method is proposed in this paper. Various objects in a queried infrared image are detected and labelled with proper categories by a combination of SIFT-Flow and MRF model. The queried image is then colorized by assigning corresponding colors according to the categories of the objects appeared. The results show that the strategy here emphasizes important information of the IR images for human vision and could be used to broaden the application of IR images for vehicle driving.

Exogenous spatial attention influences figure-ground assignment.

Science.gov (United States)

Vecera, Shaun P; Flevaris, Anastasia V; Filapek, Joseph C

2004-01-01

In a hierarchical stage account of vision, figure-ground assignment is thought to be completed before the operation of focal spatial attention. Results of previous studies have supported this account by showing that unpredictive, exogenous spatial precues do not influence figure-ground assignment, although voluntary attention can influence figure-ground assignment. However, in these studies, attention was not summoned directly to a region in a figure-ground display. In three experiments, we addressed the relationship between figure-ground assignment and visuospatial attention. In Experiment 1, we replicated the finding that exogenous precues do not influence figure-ground assignment when they direct attention outside of a figure-ground stimulus. In Experiment 2, we demonstrated that exogenous attention can influence figure-ground assignment if it is directed to one of the regions in a figure-ground stimulus. In Experiment 3, we demonstrated that exogenous attention can influence figure-ground assignment in displays that contain a Gestalt figure-ground cue; this result suggests that figure-ground processes are not entirely completed prior to the operation of focal spatial attention. Exogenous spatial attention acts as a cue for figure-ground assignment and can affect the outcome of figure-ground processes.

Effects of vehicle power on passenger vehicle speeds.

Science.gov (United States)

McCartt, Anne T; Hu, Wen

2017-07-04

During the past 2 decades, there have been large increases in mean horsepower and the mean horsepower-to-vehicle weight ratio for all types of new passenger vehicles in the United States. This study examined the relationship between travel speeds and vehicle power, defined as horsepower per 100 pounds of vehicle weight. Speed cameras measured travel speeds and photographed license plates and drivers of passenger vehicles traveling on roadways in Northern Virginia during daytime off-peak hours in spring 2013. The driver licensing agencies in the District of Columbia, Maryland, and Virginia provided vehicle information numbers (VINs) by matching license plate numbers with vehicle registration records and provided the age, gender, and ZIP code of the registered owner(s). VINs were decoded to obtain the curb weight and horsepower of vehicles. The study focused on 26,659 observed vehicles for which information on horsepower was available and the observed age and gender of drivers matched vehicle registration records. Log-linear regression estimated the effects of vehicle power on mean travel speeds, and logistic regression estimated the effects of vehicle power on the likelihood of a vehicle traveling over the speed limit and more than 10 mph over the limit. After controlling for driver characteristics, speed limit, vehicle type, and traffic volume, a 1-unit increase in vehicle power was associated with a 0.7% increase in mean speed, a 2.7% increase in the likelihood of a vehicle exceeding the speed limit by any amount, and an 11.6% increase in the likelihood of a vehicle exceeding the limit by 10 mph. All of these increases were highly significant. Speeding persists as a major factor in crashes in the United States. There are indications that travel speeds have increased in recent years. The current findings suggest the trend toward substantially more powerful vehicles may be contributing to higher speeds. Given the strong association between travel speed and crash

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

Science.gov (United States)

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.

Comparison of machine learning algorithms for detecting coral reef

Directory of Open Access Journals (Sweden)

Eduardo Tusa

2014-09-01

Full Text Available (Received: 2014/07/31 - Accepted: 2014/09/23This work focuses on developing a fast coral reef detector, which is used for an autonomous underwater vehicle, AUV. A fast detection secures the AUV stabilization respect to an area of reef as fast as possible, and prevents devastating collisions. We use the algorithm of Purser et al. (2009 because of its precision. This detector has two parts: feature extraction that uses Gabor Wavelet filters, and feature classification that uses machine learning based on Neural Networks. Due to the extensive time of the Neural Networks, we exchange for a classification algorithm based on Decision Trees. We use a database of 621 images of coral reef in Belize (110 images for training and 511 images for testing. We implement the bank of Gabor Wavelets filters using C++ and the OpenCV library. We compare the accuracy and running time of 9 machine learning algorithms, whose result was the selection of the Decision Trees algorithm. Our coral detector performs 70ms of running time in comparison to 22s executed by the algorithm of Purser et al. (2009.

Zooniverse: Combining Human and Machine Classifiers for the Big Survey Era

Science.gov (United States)

Fortson, Lucy; Wright, Darryl; Beck, Melanie; Lintott, Chris; Scarlata, Claudia; Dickinson, Hugh; Trouille, Laura; Willi, Marco; Laraia, Michael; Boyer, Amy; Veldhuis, Marten; Zooniverse

2018-01-01

Many analyses of astronomical data sets, ranging from morphological classification of galaxies to identification of supernova candidates, have relied on humans to classify data into distinct categories. Crowdsourced galaxy classifications via the Galaxy Zoo project provided a solution that scaled visual classification for extant surveys by harnessing the combined power of thousands of volunteers. However, the much larger data sets anticipated from upcoming surveys will require a different approach. Automated classifiers using supervised machine learning have improved considerably over the past decade but their increasing sophistication comes at the expense of needing ever more training data. Crowdsourced classification by human volunteers is a critical technique for obtaining these training data. But several improvements can be made on this zeroth order solution. Efficiency gains can be achieved by implementing a “cascade filtering” approach whereby the task structure is reduced to a set of binary questions that are more suited to simpler machines while demanding lower cognitive loads for humans.Intelligent subject retirement based on quantitative metrics of volunteer skill and subject label reliability also leads to dramatic improvements in efficiency. We note that human and machine classifiers may retire subjects differently leading to trade-offs in performance space. Drawing on work with several Zooniverse projects including Galaxy Zoo and Supernova Hunter, we will present recent findings from experiments that combine cohorts of human and machine classifiers. We show that the most efficient system results when appropriate subsets of the data are intelligently assigned to each group according to their particular capabilities.With sufficient online training, simple machines can quickly classify “easy” subjects, leaving more difficult (and discovery-oriented) tasks for volunteers. We also find humans achieve higher classification purity while samples

Machining of Machine Elements Made of Polymer Composite Materials

Science.gov (United States)

Baurova, N. I.; Makarov, K. A.

2017-12-01

The machining of the machine elements that are made of polymer composite materials (PCMs) or are repaired using them is considered. Turning, milling, and drilling are shown to be most widely used among all methods of cutting PCMs. Cutting conditions for the machining of PCMs are presented. The factors that most strongly affect the roughness parameters and the accuracy of cutting PCMs are considered.

Electric vehicle equipment for grid-integrated vehicles

Science.gov (United States)

Kempton, Willett

2013-08-13

Methods, systems, and apparatus for interfacing an electric vehicle with an electric power grid are disclosed. An exemplary apparatus may include a station communication port for interfacing with electric vehicle station equipment (EVSE), a vehicle communication port for interfacing with a vehicle management system (VMS), and a processor coupled to the station communication port and the vehicle communication port to establish communication with the EVSE via the station communication port, receive EVSE attributes from the EVSE, and issue commands to the VMS to manage power flow between the electric vehicle and the EVSE based on the EVSE attributes. An electric vehicle may interface with the grid by establishing communication with the EVSE, receiving the EVSE attributes, and managing power flow between the EVE and the grid based on the EVSE attributes.

Improving Machining Accuracy of CNC Machines with Innovative Design Methods

Science.gov (United States)

Yemelyanov, N. V.; Yemelyanova, I. V.; Zubenko, V. L.

2018-03-01

The article considers achieving the machining accuracy of CNC machines by applying innovative methods in modelling and design of machining systems, drives and machine processes. The topological method of analysis involves visualizing the system as matrices of block graphs with a varying degree of detail between the upper and lower hierarchy levels. This approach combines the advantages of graph theory and the efficiency of decomposition methods, it also has visual clarity, which is inherent in both topological models and structural matrices, as well as the resiliency of linear algebra as part of the matrix-based research. The focus of the study is on the design of automated machine workstations, systems, machines and units, which can be broken into interrelated parts and presented as algebraic, topological and set-theoretical models. Every model can be transformed into a model of another type, and, as a result, can be interpreted as a system of linear and non-linear equations which solutions determine the system parameters. This paper analyses the dynamic parameters of the 1716PF4 machine at the stages of design and exploitation. Having researched the impact of the system dynamics on the component quality, the authors have developed a range of practical recommendations which have enabled one to reduce considerably the amplitude of relative motion, exclude some resonance zones within the spindle speed range of 0...6000 min-1 and improve machining accuracy.

Machinability of nickel based alloys using electrical discharge machining process

Science.gov (United States)

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.

The achievements of the Z-machine; Les exploits de la Z-machine

Energy Technology Data Exchange (ETDEWEB)

Larousserie, D

2008-03-15

The ZR-machine that represents the latest generation of Z-pinch machines has recently begun preliminary testing before its full commissioning in Albuquerque (Usa). During its test the machine has well operated with electrical currents whose intensities of 26 million Ampere are already 2 times as high as the intensity of the operating current of the previous Z-machine. In 2006 the Z-machine reached temperatures of 2 billions Kelvin while 100 million Kelvin would be sufficient to ignite thermonuclear fusion. In fact the concept of Z-pinch machines was imagined in the fifties but the technological breakthrough that has allowed this recent success and the reborn of Z-machine, was the replacement of gas by an array of metal wires through which the electrical current flows and vaporizes it creating an imploding plasma. It is not well understood why Z-pinch machines generate far more radiation than theoretically expected. (A.C.)

Quantum machine learning.

Science.gov (United States)

Biamonte, Jacob; Wittek, Peter; Pancotti, Nicola; Rebentrost, Patrick; Wiebe, Nathan; Lloyd, Seth

2017-09-13

Fuelled by increasing computer power and algorithmic advances, machine learning techniques have become powerful tools for finding patterns in data. Quantum systems produce atypical patterns that classical systems are thought not to produce efficiently, so it is reasonable to postulate that quantum computers may outperform classical computers on machine learning tasks. The field of quantum machine learning explores how to devise and implement quantum software that could enable machine learning that is faster than that of classical computers. Recent work has produced quantum algorithms that could act as the building blocks of machine learning programs, but the hardware and software challenges are still considerable.

Classification of underwater targets from autonomous underwater vehicle sampled bistatic acoustic scattered fields.

Science.gov (United States)

Fischell, Erin M; Schmidt, Henrik

2015-12-01

One of the long term goals of autonomous underwater vehicle (AUV) minehunting is to have multiple inexpensive AUVs in a harbor autonomously classify hazards. Existing acoustic methods for target classification using AUV-based sensing, such as sidescan and synthetic aperture sonar, require an expensive payload on each outfitted vehicle and post-processing and/or image interpretation. A vehicle payload and machine learning classification methodology using bistatic angle dependence of target scattering amplitudes between a fixed acoustic source and target has been developed for onboard, fully autonomous classification with lower cost-per-vehicle. To achieve the high-quality, densely sampled three-dimensional (3D) bistatic scattering data required by this research, vehicle sampling behaviors and an acoustic payload for precision timed data acquisition with a 16 element nose array were demonstrated. 3D bistatic scattered field data were collected by an AUV around spherical and cylindrical targets insonified by a 7-9 kHz fixed source. The collected data were compared to simulated scattering models. Classification and confidence estimation were shown for the sphere versus cylinder case on the resulting real and simulated bistatic amplitude data. The final models were used for classification of simulated targets in real time in the LAMSS MOOS-IvP simulation package [M. Benjamin, H. Schmidt, P. Newman, and J. Leonard, J. Field Rob. 27, 834-875 (2010)].

Machine protection systems

CERN Document Server

Macpherson, A L

2010-01-01

A summary of the Machine Protection System of the LHC is given, with particular attention given to the outstanding issues to be addressed, rather than the successes of the machine protection system from the 2009 run. In particular, the issues of Safe Machine Parameter system, collimation and beam cleaning, the beam dump system and abort gap cleaning, injection and dump protection, and the overall machine protection program for the upcoming run are summarised.

WebAssign: Assessing Your Students' Understanding Continuously

Science.gov (United States)

Risley, John S.

1999-11-01

Motivating students to learn is a constant challenge for faculty. Technology can play a significant role. One such solution is WebAssign — a web-based homework system that offers new teaching and learning opportunities for educators and their students. WebAssign delivers, collects, grades, and records customized homework assignments over the Internet. Students get immediate feedback with credit and instructors can implement "Just-in-Time" teaching. In this talk, I will describe how assignments can be generated with different numerical values for each question, giving each student a unique problem to solve. This feature encourages independent thinking with the benefit of collaborative learning. Example assignments taken from textbook questions and intellectually engaging Java applet simulations will be shown. Studies and first-hand experience on the educational impact of using WebAssign will also be discussed.

Preliminary Test of Upgraded Conventional Milling Machine into PC Based CNC Milling Machine

International Nuclear Information System (INIS)

Abdul Hafid

2008-01-01

CNC (Computerized Numerical Control) milling machine yields a challenge to make an innovation in the field of machining. With an action job is machining quality equivalent to CNC milling machine, the conventional milling machine ability was improved to be based on PC CNC milling machine. Mechanically and instrumentally change. As a control replacing was conducted by servo drive and proximity were used. Computer programme was constructed to give instruction into milling machine. The program structure of consists GUI model and ladder diagram. Program was put on programming systems called RTX software. The result of up-grade is computer programming and CNC instruction job. The result was beginning step and it will be continued in next time. With upgrading ability milling machine becomes user can be done safe and optimal from accident risk. By improving performance of milling machine, the user will be more working optimal and safely against accident risk. (author)

GUIDELINES FOR RATIONALIZATION OF MANAGEMENT OF PERFORMANCE OF LOGISTICS SYSTEM OF TRANSPORT MACHINE MANUFACTURING ENTERPRISES

OpenAIRE

Yulia A. Anankina

2013-01-01

The main problems that occurs in a process of movement of material flows in the enterprises of transport machine manufacturing enterprises are stated in the article. Particular attention is paid to the rational use of vehicles on the existing capacity of the material flow of the enterprise. Process of transport service of material flow is concerned step by step. The place of transport in the logistics enterprise system is determined by authors. We give guidelines for rationalization of manage...

Existing machine propulsion is transformed by state-of-the-art gearbox apparatus saves at least 50% energy

Science.gov (United States)

Abramov, V.

2013-12-01

This innovation on www.repowermachine.com is finalist at Clean-tech and Energy of 2012 Minnesota's TEKNE AWARDS. Vehicles are pushed by force of friction between their wheels and land, propellers and water or air according to Third Newton's law of physics of moving. Force of friction is dependent to vehicle weight as highest torque of wheel or propeller for vehicle moving from stop. Friction force DOES NOT dependent to motor power. Why existing SUV of 2,000 lb uses 550 hp motor when first vehicle has 0.75 hp motor (Carl Benz';s patent #37435, January 29, 1886 in Germany)? Gas or magnet field reaches needed torque of wheels too slowly because requires huge motor power for acceleration SUV from 0 to 100 mph for 5 second. The acceleration system by gas or magnet field uses additional energy for increasing motor shaft idle speed and reduces its highest torque of physical volume because necessary to increase motor power that equal/exceed motor power according to vehicle weight. Therefore, any transmission torque DOES NOT NEED and it is use as second brake. Ship, locomotives, helicopters, CNC machine tools, etc motor(s) directly turn wheels, propellers, spindles or ignore to use gear -transmission designs. How do you follow to Creator's physics law of LEVER for saving energy? Existing machine propulsion is transformed by one comprising least numbers of gears and maybe shafts from above state-of-the-art 1,000 gearbox apparatus designs. It is installed or replaced transmission in existing propulsion that is transformed to non-accelerated propulsion. It cuts about 80% mechanical energy that acceleration system wastes in motor heat form, cuts time of movement by reaching each speed for 1-2 seconds. It produces all needed speeds and uses only idle speed of cheapest motor with reduced power and cost that have replaced existing motor too. There is opportunity to eliminate vehicle/machine roads traffics in cities that creates additional unknown GHG emissions Revolutionary

Hybrid platform. Economical hybrid drive for commercial vehicles; Hybrid Plattform. Wirtschaftlicher Hybridantrieb fuer Nutzfahrzeuge

Energy Technology Data Exchange (ETDEWEB)

Wallner, S.; Lamke, M.; Mohr, M.; Sedlacek, M.; Speck, F.D. [ZF Friedrichshafen AG, Friedrichshafen (Germany)

2011-07-01

Up to now, hybrid systems have been adapted to their specific requirements in the various applications for trucks, buses as well as mobile and building machines. From a technical point of view, this does indeed result in optimized hybrid drives for each single vehicle application, but due to small volumes, such single developments are critical from a business point of view. ZF Friedrichshafen AG is providing a solution to the technical and economical requirements of the cost-sensitive CV segment in the form of a modular CV parallel hybrid platform composed of a hybrid module system, an inverter, a battery system, and a hybrid software integrated into the overall vehicle. Thanks to the intelligent combination of assemblies and the use of as many identical parts as possible, platforms are realized which cover power ranges between 60 and 120 kW, voltage ranges between 350 and 650 V, and battery capacities between 2 and 4 kWh. The dimensions of the platform elements are such that integration into the diverse commercial vehicle applications is made easy. The hybrid software required for the vehicle-specific functions is also configurable for the mentioned CV applications. (orig.)

Homogenization of Vehicle Fleet Frontal Crash Pulses from 2000–2010

Science.gov (United States)

Locey, Caitlin M.; Garcia-Espana, J. Felipe; Toh, Akira; Belwadi, Aditya; Arbogast, Kristy B.; Maltese, Matthew R.

2012-01-01

Full-scale vehicle crash tests are performed globally to assess vehicle structure and restraint system performance. The crash pulse, captured by accelerometers mounted within the occupant compartment, measures the motion of the vehicle during the impact event. From an occupant’s perspective, the crash pulse is the inertial event to which the vehicle’s restraint systems must respond in order to mitigate the forces and accelerations that act on a passenger, and thus reduce injury risk. The objective of this study was to quantify the characteristics of crash pulses for different vehicle types in the contemporary North American fleet, and delineate current trends in crash pulse evolution. NHTSA and Transport Canada crash test databases were queried for full-frontal rigid barrier crash tests of passenger vehicles model year 2000–2010 with impact angle equaling zero degrees. Acceleration-time histories were analyzed for all accelerometers attached to the vehicle structure within the occupant compartment. Custom software calculated the following crash pulse characteristics (CPCs): peak deceleration, time of peak deceleration, onset rate, pulse duration, and change in velocity. Vehicle body types were classified by adapting the Highway Loss Data Institute (HLDI) methodology, and vehicles were assigned a generation start year in place of model year in order to more accurately represent structural change over time. 1094 vehicle crash tests with 2795 individual occupant compartment-mounted accelerometers were analyzed. We found greater peak decelerations and and shorter pulse durations across multiple vehicle types in newer model years as compared to older. For midsize passenger cars, large passenger cars, and large SUVs in 56 km/h rigid barrier tests, maximum deceleration increased by 0.40, 0.96, and 1.57 g/year respectively, and pulse duration decreased by 0.74, 1.87, and 2.51 ms/year. We also found that the crash pulse characteristics are becoming more homogeneous in

Study of on-machine error identification and compensation methods for micro machine tools

International Nuclear Information System (INIS)

Wang, Shih-Ming; Yu, Han-Jen; Lee, Chun-Yi; Chiu, Hung-Sheng

2016-01-01

Micro machining plays an important role in the manufacturing of miniature products which are made of various materials with complex 3D shapes and tight machining tolerance. To further improve the accuracy of a micro machining process without increasing the manufacturing cost of a micro machine tool, an effective machining error measurement method and a software-based compensation method are essential. To avoid introducing additional errors caused by the re-installment of the workpiece, the measurement and compensation method should be on-machine conducted. In addition, because the contour of a miniature workpiece machined with a micro machining process is very tiny, the measurement method should be non-contact. By integrating the image re-constructive method, camera pixel correction, coordinate transformation, the error identification algorithm, and trajectory auto-correction method, a vision-based error measurement and compensation method that can on-machine inspect the micro machining errors and automatically generate an error-corrected numerical control (NC) program for error compensation was developed in this study. With the use of the Canny edge detection algorithm and camera pixel calibration, the edges of the contour of a machined workpiece were identified and used to re-construct the actual contour of the work piece. The actual contour was then mapped to the theoretical contour to identify the actual cutting points and compute the machining errors. With the use of a moving matching window and calculation of the similarity between the actual and theoretical contour, the errors between the actual cutting points and theoretical cutting points were calculated and used to correct the NC program. With the use of the error-corrected NC program, the accuracy of a micro machining process can be effectively improved. To prove the feasibility and effectiveness of the proposed methods, micro-milling experiments on a micro machine tool were conducted, and the results

Online forecasting of electrical load for distributed management of plug-in electric vehicles

OpenAIRE

Basu , Kaustav; Ovalle , Andres; Guo , Baoling; Hably , Ahmad; Bacha , Seddik; Hajar , Khaled

2016-01-01

International audience; The paper aims at making online forecast of electrical load at the MV-LV transformer level. Optimal management of the Plug-in Electric Vehicles (PEV) charging requires the forecast of the electrical load for future hours. The forecasting module needs to be online (i.e update and make forecast for the future hours, every hour). The inputs to the predictor are historical electrical and weather data. Various data driven machine learning algorithms are compared to derive t...

National Machine Guarding Program: Part 1. Machine safeguarding practices in small metal fabrication businesses.

Science.gov (United States)

Parker, David L; Yamin, Samuel C; Brosseau, Lisa M; Xi, Min; Gordon, Robert; Most, Ivan G; Stanley, Rodney

2015-11-01

Metal fabrication workers experience high rates of traumatic occupational injuries. Machine operators in particular face high risks, often stemming from the absence or improper use of machine safeguarding or the failure to implement lockout procedures. The National Machine Guarding Program (NMGP) was a translational research initiative implemented in conjunction with two workers' compensation insures. Insurance safety consultants trained in machine guarding used standardized checklists to conduct a baseline inspection of machine-related hazards in 221 business. Safeguards at the point of operation were missing or inadequate on 33% of machines. Safeguards for other mechanical hazards were missing on 28% of machines. Older machines were both widely used and less likely than newer machines to be properly guarded. Lockout/tagout procedures were posted at only 9% of machine workstations. The NMGP demonstrates a need for improvement in many aspects of machine safety and lockout in small metal fabrication businesses. © 2015 The Authors. American Journal of Industrial Medicine published by Wiley Periodicals, Inc.

Non-conventional electrical machines

CERN Document Server

Rezzoug, Abderrezak

2013-01-01

The developments of electrical machines are due to the convergence of material progress, improved calculation tools, and new feeding sources. Among the many recent machines, the authors have chosen, in this first book, to relate the progress in slow speed machines, high speed machines, and superconducting machines. The first part of the book is dedicated to materials and an overview of magnetism, mechanic, and heat transfer.

Advanced Machine learning Algorithm Application for Rotating Machine Health Monitoring

Energy Technology Data Exchange (ETDEWEB)

Kanemoto, Shigeru; Watanabe, Masaya [The University of Aizu, Aizuwakamatsu (Japan); Yusa, Noritaka [Tohoku University, Sendai (Japan)

2014-08-15

The present paper tries to evaluate the applicability of conventional sound analysis techniques and modern machine learning algorithms to rotating machine health monitoring. These techniques include support vector machine, deep leaning neural network, etc. The inner ring defect and misalignment anomaly sound data measured by a rotating machine mockup test facility are used to verify the above various kinds of algorithms. Although we cannot find remarkable difference of anomaly discrimination performance, some methods give us the very interesting eigen patterns corresponding to normal and abnormal states. These results will be useful for future more sensitive and robust anomaly monitoring technology.

Advanced Machine learning Algorithm Application for Rotating Machine Health Monitoring

International Nuclear Information System (INIS)

Kanemoto, Shigeru; Watanabe, Masaya; Yusa, Noritaka

2014-01-01

The present paper tries to evaluate the applicability of conventional sound analysis techniques and modern machine learning algorithms to rotating machine health monitoring. These techniques include support vector machine, deep leaning neural network, etc. The inner ring defect and misalignment anomaly sound data measured by a rotating machine mockup test facility are used to verify the above various kinds of algorithms. Although we cannot find remarkable difference of anomaly discrimination performance, some methods give us the very interesting eigen patterns corresponding to normal and abnormal states. These results will be useful for future more sensitive and robust anomaly monitoring technology

Simulating the impacts of on-street vehicle parking on traffic operations on urban streets using cellular automation

Science.gov (United States)

Chen, Jingxu; Li, Zhibin; Jiang, Hang; Zhu, Senlai; Wang, Wei

2017-02-01

In recent years, many bicycle lanes on urban streets are replaced with vehicle parking places. Spaces for bicycle riding are reduced, resulting in changes in bicycle and vehicle operational features. The objective of this study is to estimate the impacts of on-street parking on heterogeneous traffic operation on urban streets. A cellular automaton (CA) model is developed and calibrated to simulate bicycle lane-changing on streets with on-street parking. Two types of street segments with different bicycle lane width are considered. From the simulation, two types of conflicts between bicycles and vehicles are identified which are frictional conflicts and blocking conflicts. Factors affecting the frequency of conflicts are also identified. Based on the results, vehicle delay is estimated for various traffic situations considering the range of occupancy levels for on-street parking. Later, a numerical network example is analyzed to estimate the network impact of on-street parking on traffic assignment and operation. Findings of the study are helpful to policies and design regarding on-street vehicle parking to improve the efficiency of traffic operations.

Solving the rectangular assignment problem and applications

NARCIS (Netherlands)

Bijsterbosch, J.; Volgenant, A.

2010-01-01

The rectangular assignment problem is a generalization of the linear assignment problem (LAP): one wants to assign a number of persons to a smaller number of jobs, minimizing the total corresponding costs. Applications are, e.g., in the fields of object recognition and scheduling. Further, we show

7 CFR 900.106 - Assignment of mediator.

Science.gov (United States)

2010-01-01

... 7 Agriculture 8 2010-01-01 2010-01-01 false Assignment of mediator. 900.106 Section 900.106 Agriculture Regulations of the Department of Agriculture (Continued) AGRICULTURAL MARKETING SERVICE (Marketing... Assignment of mediator. The Director of the Division shall assign a mediator, from the group designated by...

Representative Vector Machines: A Unified Framework for Classical Classifiers.

Science.gov (United States)

Gui, Jie; Liu, Tongliang; Tao, Dacheng; Sun, Zhenan; Tan, Tieniu

2016-08-01

Classifier design is a fundamental problem in pattern recognition. A variety of pattern classification methods such as the nearest neighbor (NN) classifier, support vector machine (SVM), and sparse representation-based classification (SRC) have been proposed in the literature. These typical and widely used classifiers were originally developed from different theory or application motivations and they are conventionally treated as independent and specific solutions for pattern classification. This paper proposes a novel pattern classification framework, namely, representative vector machines (or RVMs for short). The basic idea of RVMs is to assign the class label of a test example according to its nearest representative vector. The contributions of RVMs are twofold. On one hand, the proposed RVMs establish a unified framework of classical classifiers because NN, SVM, and SRC can be interpreted as the special cases of RVMs with different definitions of representative vectors. Thus, the underlying relationship among a number of classical classifiers is revealed for better understanding of pattern classification. On the other hand, novel and advanced classifiers are inspired in the framework of RVMs. For example, a robust pattern classification method called discriminant vector machine (DVM) is motivated from RVMs. Given a test example, DVM first finds its k -NNs and then performs classification based on the robust M-estimator and manifold regularization. Extensive experimental evaluations on a variety of visual recognition tasks such as face recognition (Yale and face recognition grand challenge databases), object categorization (Caltech-101 dataset), and action recognition (Action Similarity LAbeliNg) demonstrate the advantages of DVM over other classifiers.

A field study of human factors and vehicle performance associated with PHEV adaptation

International Nuclear Information System (INIS)

Farhar, B.C.; Maksimovic, D.; Tomac, W.A.; Coburn, T.C.

2016-01-01

Smart-grid and electric-vehicle technologies are rapidly diffusing, yet important policy implications remain to be fully analyzed. This multi-year field study sought to fill part of this gap by exploring human adaptation to plug-in hybrid electric vehicle (PHEV) performance and vehicle charging in smart-grid environments. Homes were equipped with smart meters in a smart-grid experiment conducted by the local utility. Study households were organized by either standard or time-of-use electricity pricing, and randomly assigned to “managed” or “unmanaged” charging scenarios. Using a mixed-methods approach, study data were collected through vehicle data loggers, smart-plugs interviews, and questionnaires. The paper describes vehicle operations and performance; the ways in which households managed PHEV charging; and the manner in which they responded to smart-grid, smart-plug, and dashboard feedback. Findings indicate that households actively managed PHEV charging; however, they preferred flexible charging scenarios. Charging-management decisions were influenced by electricity-pricing. Online feedback on household- and vehicle-electricity consumption was generally ignored, but drivers responded to dashboard feedback as they drove. These results provide empirical bases for government and corporate policymakers to improve policy decisions relative to PHEV impacts on electricity loads, design of smart-grid feedback, and design of charging infrastructures. - Highlights: •Utility pricing is the most important factor in vehicle-charging management. •Web-based energy feedback systems are ineffective in changing energy behavior. •Time-of-use pricing motivates off-peak vehicle charging. •PHEV charging infrastructure should be Placed in commercial/Multifamily buildings. •Charging systems need to be as unobtrusive as possible, requiring little of people.

An automated miniature robotic vehicle inspection system

Energy Technology Data Exchange (ETDEWEB)

Dobie, Gordon; Summan, Rahul; MacLeod, Charles; Pierce, Gareth; Galbraith, Walter [Centre for Ultrasonic Engineering, University of Strathclyde, 204 George Street, Glasgow, G1 1XW (United Kingdom)

2014-02-18

A novel, autonomous reconfigurable robotic inspection system for quantitative NDE mapping is presented. The system consists of a fleet of wireless (802.11g) miniature robotic vehicles, each approximately 175 × 125 × 85 mm with magnetic wheels that enable them to inspect industrial structures such as storage tanks, chimneys and large diameter pipe work. The robots carry one of a number of payloads including a two channel MFL sensor, a 5 MHz dry coupled UT thickness wheel probe and a machine vision camera that images the surface. The system creates an NDE map of the structure overlaying results onto a 3D model in real time. The authors provide an overview of the robot design, data fusion algorithms (positioning and NDE) and visualization software.

An automated miniature robotic vehicle inspection system

International Nuclear Information System (INIS)

Dobie, Gordon; Summan, Rahul; MacLeod, Charles; Pierce, Gareth; Galbraith, Walter

2014-01-01

A novel, autonomous reconfigurable robotic inspection system for quantitative NDE mapping is presented. The system consists of a fleet of wireless (802.11g) miniature robotic vehicles, each approximately 175 × 125 × 85 mm with magnetic wheels that enable them to inspect industrial structures such as storage tanks, chimneys and large diameter pipe work. The robots carry one of a number of payloads including a two channel MFL sensor, a 5 MHz dry coupled UT thickness wheel probe and a machine vision camera that images the surface. The system creates an NDE map of the structure overlaying results onto a 3D model in real time. The authors provide an overview of the robot design, data fusion algorithms (positioning and NDE) and visualization software

Multi-vehicle detection with identity awareness using cascade Adaboost and Adaptive Kalman filter for driver assistant system.

Directory of Open Access Journals (Sweden)

Baofeng Wang

Full Text Available Vision-based vehicle detection is an important issue for advanced driver assistance systems. In this paper, we presented an improved multi-vehicle detection and tracking method using cascade Adaboost and Adaptive Kalman filter(AKF with target identity awareness. A cascade Adaboost classifier using Haar-like features was built for vehicle detection, followed by a more comprehensive verification process which could refine the vehicle hypothesis in terms of both location and dimension. In vehicle tracking, each vehicle was tracked with independent identity by an Adaptive Kalman filter in collaboration with a data association approach. The AKF adaptively adjusted the measurement and process noise covariance through on-line stochastic modelling to compensate the dynamics changes. The data association correctly assigned different detections with tracks using global nearest neighbour(GNN algorithm while considering the local validation. During tracking, a temporal context based track management was proposed to decide whether to initiate, maintain or terminate the tracks of different objects, thus suppressing the sparse false alarms and compensating the temporary detection failures. Finally, the proposed method was tested on various challenging real roads, and the experimental results showed that the vehicle detection performance was greatly improved with higher accuracy and robustness.

Electrical machines & drives

CERN Document Server

Hammond, P

1985-01-01

Containing approximately 200 problems (100 worked), the text covers a wide range of topics concerning electrical machines, placing particular emphasis upon electrical-machine drive applications. The theory is concisely reviewed and focuses on features common to all machine types. The problems are arranged in order of increasing levels of complexity and discussions of the solutions are included where appropriate to illustrate the engineering implications. This second edition includes an important new chapter on mathematical and computer simulation of machine systems and revised discussions o

Construction of electron beam machine 350 keV/10 mA for multipurpose application of thin sample at P3TM-BATAN

International Nuclear Information System (INIS)

Darsono

2004-01-01

Research and development starting in 1984 of electron beam technology in Indonesia is first briefly presented. BATAN assigned to the Yogyakarta Nuclear Center the project of constructing an electron beam machine of 350 keV/10 mA for multipurpose applications especially for thin samples for duration of five years. The main objective of the project was the young scientists training and demonstration purposes in operation and maintenance of the machine. The engineers have learned through experience of the low energy ion accelerator (150 kV) many techniques to construct the system component such as E-gun, high voltage, vacuum, beam optics, scanning horn and window, beam stopper, and conveyer as well as the embedded control system. Because of the window cooling system, the uses of the machine are limited for irradiating a thin sample of plastics, hydrogel, powder, or liquid. Future plans for modification of the machine are stated. (S. Ohno)

My Favorite Assignment.

Science.gov (United States)

ABCA Bulletin, 1983

1983-01-01

Describes three assignments for enticing business communication students to undertake library research: an analysis of a Fortune 500 company, a career choice report, and a report on an organization that offers potential employment. (AEA)

DNA-based machines.

Science.gov (United States)

Wang, Fuan; Willner, Bilha; Willner, Itamar

2014-01-01

The base sequence in nucleic acids encodes substantial structural and functional information into the biopolymer. This encoded information provides the basis for the tailoring and assembly of DNA machines. A DNA machine is defined as a molecular device that exhibits the following fundamental features. (1) It performs a fuel-driven mechanical process that mimics macroscopic machines. (2) The mechanical process requires an energy input, "fuel." (3) The mechanical operation is accompanied by an energy consumption process that leads to "waste products." (4) The cyclic operation of the DNA devices, involves the use of "fuel" and "anti-fuel" ingredients. A variety of DNA-based machines are described, including the construction of "tweezers," "walkers," "robots," "cranes," "transporters," "springs," "gears," and interlocked cyclic DNA structures acting as reconfigurable catenanes, rotaxanes, and rotors. Different "fuels", such as nucleic acid strands, pH (H⁺/OH⁻), metal ions, and light, are used to trigger the mechanical functions of the DNA devices. The operation of the devices in solution and on surfaces is described, and a variety of optical, electrical, and photoelectrochemical methods to follow the operations of the DNA machines are presented. We further address the possible applications of DNA machines and the future perspectives of molecular DNA devices. These include the application of DNA machines as functional structures for the construction of logic gates and computing, for the programmed organization of metallic nanoparticle structures and the control of plasmonic properties, and for controlling chemical transformations by DNA machines. We further discuss the future applications of DNA machines for intracellular sensing, controlling intracellular metabolic pathways, and the use of the functional nanostructures for drug delivery and medical applications.

A comprehensive overview of hybrid electric vehicle: Powertrain configurations, powertrain control techniques and electronic control units

Energy Technology Data Exchange (ETDEWEB)

Cagatay Bayindir, Kamil; Goezuekuecuek, Mehmet Ali; Teke, Ahmet [Cukurova University, Department of Electrical and Electronics Engineering, Balcali, Saricam, Adana (Turkey)

2011-02-15

The studies for hybrid electrical vehicle (HEV) have attracted considerable attention because of the necessity of developing alternative methods to generate energy for vehicles due to limited fuel based energy, global warming and exhaust emission limits in the last century. HEV incorporates internal composition engine, electric machines and power electronic equipments. In this study, overview of HEVs with a focus on hybrid configurations, energy management strategies and electronic control units are presented. Advantages and disadvantages of each configuration are clearly emphasized. The existing powertrain control techniques for HEVs are classified and comprehensively described. Electronic control units used in HEV configuration are also elaborated. The latest trends and technological challenges in the near future for HEVs are discussed. (author)

Machine translation

Energy Technology Data Exchange (ETDEWEB)

Nagao, M

1982-04-01

Each language has its own structure. In translating one language into another one, language attributes and grammatical interpretation must be defined in an unambiguous form. In order to parse a sentence, it is necessary to recognize its structure. A so-called context-free grammar can help in this respect for machine translation and machine-aided translation. Problems to be solved in studying machine translation are taken up in the paper, which discusses subjects for semantics and for syntactic analysis and translation software. 14 references.

A novel photochemical machining process for magnesium aerospace and biomedical microengineering applications

International Nuclear Information System (INIS)

Allen, D M; Simpkins, M; Almond, H

2010-01-01

Research was carried out to evaluate the feasibility of fabricating perforated (filigree) magnesium microcomponents with metal wire widths of the order of the metal thickness using a photochemical machining (PCM) process. Experimentally, it has been demonstrated for the first time that metal wire widths of 0.15 mm can be achieved within a 2D, 0.25 mm thick magnesium foil to fabricate microcomponents for use as micro air vehicle (MAV) wings or stents through a bespoke PCM process. This etching process differs significantly from the industrial etching process used currently to manufacture magnesium letterpress printing plates and embossing dies

Research on application of LADAR in ground vehicle recognition

Science.gov (United States)

Lan, Jinhui; Shen, Zhuoxun

2009-11-01

For the requirement of many practical applications in the field of military, the research of 3D target recognition is active. The representation that captures the salient attributes of a 3D target independent of the viewing angle will be especially useful to the automatic 3D target recognition system. This paper presents a new approach of image generation based on Laser Detection and Ranging (LADAR) data. Range image of target is obtained by transformation of point cloud. In order to extract features of different ground vehicle targets and to recognize targets, zernike moment properties of typical ground vehicle targets are researched in this paper. A technique of support vector machine is applied to the classification and recognition of target. The new method of image generation and feature representation has been applied to the outdoor experiments. Through outdoor experiments, it can be proven that the method of image generation is stability, the moments are effective to be used as features for recognition, and the LADAR can be applied to the field of 3D target recognition.

Identical parallel machine scheduling with nonlinear deterioration and multiple rate modifying activities

Directory of Open Access Journals (Sweden)

Ömer Öztürkoğlu

2017-07-01

Full Text Available This study focuses on identical parallel machine scheduling of jobs with deteriorating processing times and rate-modifying activities. We consider non linearly increasing processing times of jobs based on their position assignment. Rate modifying activities are also considered to recover the increase in processing times of jobs due to deterioration. We also propose heuristics algorithms that rely on ant colony optimization and simulated annealing algorithms to solve the problem with multiple RMAs in a reasonable amount of time. Finally, we show that ant colony optimization algorithm generates close optimal solutions and superior results than simulated annealing algorithm.

A Comprehensive Study of Key Electric Vehicle (EV Components, Technologies, Challenges, Impacts, and Future Direction of Development

Directory of Open Access Journals (Sweden)

Fuad Un-Noor

2017-08-01

Full Text Available Electric vehicles (EV, including Battery Electric Vehicle (BEV, Hybrid Electric Vehicle (HEV, Plug-in Hybrid Electric Vehicle (PHEV, Fuel Cell Electric Vehicle (FCEV, are becoming more commonplace in the transportation sector in recent times. As the present trend suggests, this mode of transport is likely to replace internal combustion engine (ICE vehicles in the near future. Each of the main EV components has a number of technologies that are currently in use or can become prominent in the future. EVs can cause significant impacts on the environment, power system, and other related sectors. The present power system could face huge instabilities with enough EV penetration, but with proper management and coordination, EVs can be turned into a major contributor to the successful implementation of the smart grid concept. There are possibilities of immense environmental benefits as well, as the EVs can extensively reduce the greenhouse gas emissions produced by the transportation sector. However, there are some major obstacles for EVs to overcome before totally replacing ICE vehicles. This paper is focused on reviewing all the useful data available on EV configurations, battery energy sources, electrical machines, charging techniques, optimization techniques, impacts, trends, and possible directions of future developments. Its objective is to provide an overall picture of the current EV technology and ways of future development to assist in future researches in this sector.

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

Science.gov (United States)

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.

Electric vehicle station equipment for grid-integrated vehicles

Science.gov (United States)

Kempton, Willett; Kiamilev, Fouad; McGee, Rodney; Waite, Nick

2017-09-05

Methods, systems, and apparatus transferring power between the grid and an electric vehicle are disclosed. The apparatus may include at least one vehicle communication port for interfacing with electric vehicle equipment (EVE) and a processor coupled to the at least one vehicle communication port to establish communication with the EVE, receive EVE attributes from the EVE, and transmit electric vehicle station equipment (EVSE) attributes to the EVE. Power may be transferred between the grid and the electric vehicle by maintaining EVSE attributes, establishing communication with the EVE, and transmitting the EVSE maintained attributes to the EVE.

Efficient adaptive constrained control with time-varying predefined performance for a hypersonic flight vehicle

Directory of Open Access Journals (Sweden)

Caisheng Wei

2017-03-01

Full Text Available A novel low-complexity adaptive control method, capable of guaranteeing the transient and steady-state tracking performance in the presence of unknown nonlinearities and actuator saturation, is investigated for the longitudinal dynamics of a generic hypersonic flight vehicle. In order to attenuate the negative effects of classical predefined performance function for unknown initial tracking errors, a modified predefined performance function with time-varying design parameters is presented. Under the newly developed predefined performance function, two novel adaptive controllers with low-complexity computation are proposed for velocity and altitude subsystems of the hypersonic flight vehicle, respectively. Wherein, different from neural network-based approximation, a least square support vector machine with only two design parameters is utilized to approximate the unknown hypersonic dynamics. And the relevant ideal weights are obtained by solving a linear system without resorting to specialized optimization algorithms. Based on the approximation by least square support vector machine, only two adaptive scalars are required to be updated online in the parameter projection method. Besides, a new finite-time-convergent differentiator, with a quite simple structure, is proposed to estimate the unknown generated state variables in the newly established normal output-feedback formulation of altitude subsystem. Moreover, it is also employed to obtain accurate estimations for the derivatives of virtual controllers in a recursive design. This avoids the inherent drawback of backstepping — “explosion of terms” and makes the proposed control method achievable for the hypersonic flight vehicle. Further, the compensation design is employed when the saturations of the actuator occur. Finally, the numerical simulations validate the efficiency of the proposed finite-time-convergent differentiator and control method.

Induction machine handbook

CERN Document Server

Boldea, Ion

2002-01-01

Often called the workhorse of industry, the advent of power electronics and advances in digital control are transforming the induction motor into the racehorse of industrial motion control. Now, the classic texts on induction machines are nearly three decades old, while more recent books on electric motors lack the necessary depth and detail on induction machines.The Induction Machine Handbook fills industry's long-standing need for a comprehensive treatise embracing the many intricate facets of induction machine analysis and design. Moving gradually from simple to complex and from standard to

Chaotic Boltzmann machines

Science.gov (United States)

Suzuki, Hideyuki; Imura, Jun-ichi; Horio, Yoshihiko; Aihara, Kazuyuki

2013-01-01

The chaotic Boltzmann machine proposed in this paper is a chaotic pseudo-billiard system that works as a Boltzmann machine. Chaotic Boltzmann machines are shown numerically to have computing abilities comparable to conventional (stochastic) Boltzmann machines. Since no randomness is required, efficient hardware implementation is expected. Moreover, the ferromagnetic phase transition of the Ising model is shown to be characterised by the largest Lyapunov exponent of the proposed system. In general, a method to relate probabilistic models to nonlinear dynamics by derandomising Gibbs sampling is presented. PMID:23558425

Rotating electrical machines

CERN Document Server

Le Doeuff, René

2013-01-01

In this book a general matrix-based approach to modeling electrical machines is promulgated. The model uses instantaneous quantities for key variables and enables the user to easily take into account associations between rotating machines and static converters (such as in variable speed drives).   General equations of electromechanical energy conversion are established early in the treatment of the topic and then applied to synchronous, induction and DC machines. The primary characteristics of these machines are established for steady state behavior as well as for variable speed scenarios. I

New fuzzy support vector machine for the class imbalance problem in medical datasets classification.

Science.gov (United States)

Gu, Xiaoqing; Ni, Tongguang; Wang, Hongyuan

2014-01-01

In medical datasets classification, support vector machine (SVM) is considered to be one of the most successful methods. However, most of the real-world medical datasets usually contain some outliers/noise and data often have class imbalance problems. In this paper, a fuzzy support machine (FSVM) for the class imbalance problem (called FSVM-CIP) is presented, which can be seen as a modified class of FSVM by extending manifold regularization and assigning two misclassification costs for two classes. The proposed FSVM-CIP can be used to handle the class imbalance problem in the presence of outliers/noise, and enhance the locality maximum margin. Five real-world medical datasets, breast, heart, hepatitis, BUPA liver, and pima diabetes, from the UCI medical database are employed to illustrate the method presented in this paper. Experimental results on these datasets show the outperformed or comparable effectiveness of FSVM-CIP.

New Fuzzy Support Vector Machine for the Class Imbalance Problem in Medical Datasets Classification

Directory of Open Access Journals (Sweden)

Xiaoqing Gu

2014-01-01

Full Text Available In medical datasets classification, support vector machine (SVM is considered to be one of the most successful methods. However, most of the real-world medical datasets usually contain some outliers/noise and data often have class imbalance problems. In this paper, a fuzzy support machine (FSVM for the class imbalance problem (called FSVM-CIP is presented, which can be seen as a modified class of FSVM by extending manifold regularization and assigning two misclassification costs for two classes. The proposed FSVM-CIP can be used to handle the class imbalance problem in the presence of outliers/noise, and enhance the locality maximum margin. Five real-world medical datasets, breast, heart, hepatitis, BUPA liver, and pima diabetes, from the UCI medical database are employed to illustrate the method presented in this paper. Experimental results on these datasets show the outperformed or comparable effectiveness of FSVM-CIP.

Software and Human-Machine Interface Development for Environmental Controls Subsystem Support

Science.gov (United States)

Dobson, Matthew

2018-01-01

The Space Launch System (SLS) is the next premier launch vehicle for NASA. It is the next stage of manned space exploration from American soil, and will be the platform in which we push further beyond Earth orbit. In preparation of the SLS maiden voyage on Exploration Mission 1 (EM-1), the existing ground support architecture at Kennedy Space Center required significant overhaul and updating. A comprehensive upgrade of controls systems was necessary, including programmable logic controller software, as well as Launch Control Center (LCC) firing room and local launch pad displays for technician use. Environmental control acts as an integral component in these systems, being the foremost system for conditioning the pad and extremely sensitive launch vehicle until T-0. The Environmental Controls Subsystem (ECS) required testing and modification to meet the requirements of the designed system, as well as the human factors requirements of NASA software for Validation and Verification (V&V). This term saw significant strides in the progress and functionality of the human-machine interfaces used at the launch pad, and improved integration with the controller code.

Your Sewing Machine.

Science.gov (United States)

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…

Machine Learning

CERN Multimedia

CERN. Geneva

2017-01-01

Machine learning, which builds on ideas in computer science, statistics, and optimization, focuses on developing algorithms to identify patterns and regularities in data, and using these learned patterns to make predictions on new observations. Boosted by its industrial and commercial applications, the field of machine learning is quickly evolving and expanding. Recent advances have seen great success in the realms of computer vision, natural language processing, and broadly in data science. Many of these techniques have already been applied in particle physics, for instance for particle identification, detector monitoring, and the optimization of computer resources. Modern machine learning approaches, such as deep learning, are only just beginning to be applied to the analysis of High Energy Physics data to approach more and more complex problems. These classes will review the framework behind machine learning and discuss recent developments in the field.

Investigation of the Machining Stability of a Milling Machine with Hybrid Guideway Systems

Directory of Open Access Journals (Sweden)

Jui-Pin Hung

2016-03-01

Full Text Available This study was aimed to investigate the machining stability of a horizontal milling machine with hybrid guideway systems by finite element method. To this purpose, we first created finite element model of the milling machine with the introduction of the contact stiffness defined at the sliding and rolling interfaces, respectively. Also, the motorized built-in spindle model was created and implemented in the whole machine model. Results of finite element simulations reveal that linear guides with different preloads greatly affect the dynamic responses and machining stability of the horizontal milling machine. The critical cutting depth predicted at the vibration mode associated with the machine tool structure is about 10 mm and 25 mm in the X and Y direction, respectively, while the cutting depth predicted at the vibration mode associated with the spindle structure is about 6.0 mm. Also, the machining stability can be increased when the preload of linear roller guides of the feeding mechanism is changed from lower to higher amount.

Introduction to AC machine design

CERN Document Server

Lipo, Thomas A

2018-01-01

AC electrical machine design is a key skill set for developing competitive electric motors and generators for applications in industry, aerospace, and defense. This book presents a thorough treatment of AC machine design, starting from basic electromagnetic principles and continuing through the various design aspects of an induction machine. Introduction to AC Machine Design includes one chapter each on the design of permanent magnet machines, synchronous machines, and thermal design. It also offers a basic treatment of the use of finite elements to compute the magnetic field within a machine without interfering with the initial comprehension of the core subject matter. Based on the author's notes, as well as after years of classroom instruction, Introduction to AC Machine Design: * Brings to light more advanced principles of machine design--not just the basic principles of AC and DC machine behavior * Introduces electrical machine design to neophytes while also being a resource for experienced designers * ...

Precision machining commercialization

International Nuclear Information System (INIS)

1978-01-01

To accelerate precision machining development so as to realize more of the potential savings within the next few years of known Department of Defense (DOD) part procurement, the Air Force Materials Laboratory (AFML) is sponsoring the Precision Machining Commercialization Project (PMC). PMC is part of the Tri-Service Precision Machine Tool Program of the DOD Manufacturing Technology Five-Year Plan. The technical resources supporting PMC are provided under sponsorship of the Department of Energy (DOE). The goal of PMC is to minimize precision machining development time and cost risk for interested vendors. PMC will do this by making available the high precision machining technology as developed in two DOE contractor facilities, the Lawrence Livermore Laboratory of the University of California and the Union Carbide Corporation, Nuclear Division, Y-12 Plant, at Oak Ridge, Tennessee

Are there intelligent Turing machines?

OpenAIRE

Bátfai, Norbert

2015-01-01

This paper introduces a new computing model based on the cooperation among Turing machines called orchestrated machines. Like universal Turing machines, orchestrated machines are also designed to simulate Turing machines but they can also modify the original operation of the included Turing machines to create a new layer of some kind of collective behavior. Using this new model we can define some interested notions related to cooperation ability of Turing machines such as the intelligence quo...