bluuebunny/crossref_metadata_2025_split huggingface dataset:
AWD Vehicle Dynamics and Energy Efficiency Improvement by Means of Interaxle Driveline and Steering Active Fusion
Authors: Vantsevich Vladimir V. 
Published: February 2014

This paper presents a novel approach to improve both energy efficiency and lateral dynamics of an all-wheel drive (AWD) vehicle by means of active functional/operational fusion of a driveline system, which distributes power between the front and rear driving axles, and a steering system that steers the front driving wheels.
The paper starts by presenting the kinematic discrepancy factor, which is a normalized difference of the front and rear theoretical velocities that influences the wheel power distribution, as a mathematical function of the tire rolling radii in the driven mode, the gear ratios of the driveline system, and the steering angle of the front wheels. Using this function, the gear ratios from the transfer case to the front and rear wheels are determined to optimize vehicle energy efficiency by minimizing the kinematic discrepancy at the vehicle’s straight line motion and on a curve.
It is also analytically shown that the wheel power distribution leads to the variation of the circumferential force of the front wheels that significantly influences the magnitude and direction of the front wheel lateral force. Thus, the paper introduced the wheel power distribution between the driving axles as an instrument for controlling oversteer-understeer transition of a vehicle, i.e., controlling vehicle lateral dynamics.
Finally, the steering angle of the front wheels is considered and analyzed as an input of an active steering system to control the vehicle oversteer-understeer process in combination with the effect of the steering angle on the kinematic discrepancy factor. Longitudinal velocity control is added to constrain the lateral acceleration. Thus, the functional fusion of the active steering and driveline systems for enhancing both AWD vehicle energy efficiency and dynamics is introduced for the first time.
Tolerance Analysis of Parallel Assemblies Using Tolerance-Maps® and a Functional Map Derived From Induced Deformations
Authors: Jaishankar Lupin Niranjan , Davidson Joseph K. , Shah Jami J. 
Published: February 2014

This paper concerns about modeling tolerance accumulation in parallel assemblies using a spatial math model, the T-Map. In this paper, a specific case in 3D is discussed where an Accumulation Tolerance-Map is modeled when two parts arranged in parallel support a target part between the datum and the functional target feature. By understanding how much of variation from the supporting parts contribute to variations of the target feature, a designer can better utilize the tolerance budget when assigning values to individual tolerances.
When the parts are flexible, deformations are induced when parts in parallel are clamped together during assembly. The amount of deformations on the target part depends on the geometric manufacturing variations on the support parts in parallel assemblies. When parts are clamped stresses are induced in more than one direction depending on the type and amount of geometric variation on the supports. The next part of this paper relates the limit on the largest von Mises stress in the target part to the functional limits in tolerance allocation that must be set at the beginning of a tolerance analysis of parts in such an assembly by the designer. The last part of the paper shows the construction of a Functional Tolerance Map from the tolerance limits obtained from the relationship between von Mises stresses and tolerances on individual parts.
Study on Driver Distraction Indexes Using Biological Signals Applying Assessment of Information Display
Authors: Ohkura Michiko , Takahashi Nobumichi , Seki Hironori , Saito Yukou , Hasegawa Koyo 
Published: February 2014

Driver distraction, which is one form of inattention, is a leading factor of vehicle crashes and near-crashes. Distraction occurs when a driver’s recognition of information needed to safely accomplish his driving task is delayed because some event, activity, object, or person within or outside the vehicle induces or shifts his attention away from the driving task.
To measure the distraction, driving performance indexes are commonly used. However, we employed biological signals to directly and quantitatively measure the distraction.
Our experiment results identified such useful biological indexes as EEG’s total power spectrum, beta wave ratio, ECG’s heart rate, and its LF/HF.
In this article, we introduce our trial in which we applied the index candidates to assess the information display positions.
Optimizing Part Sourcing Strategies for Low-Volume, Long Life Cycle Products Using Second Sourcing and Part Hoarding
Authors: Prabhakar Varun J. , Allison Hannah , Sandborn Peter , Eriksson Bo 
Published: February 2014

Long life cycle products, commonly found in aviation, medical and critical infrastructure applications, are often fielded and supported for long periods of time (20 years or more). The manufacture and support of long life cycle products rely on the availability of suitable parts, which over long periods of time, leaves the parts susceptible to supply chain disruptions such as suppliers exiting the market, allocation issues, counterfeit part risks, and part obsolescence.
Proactive mitigation strategies exist that can reduce the impact of supply chain disruptions. One solution to mitigating the supply chain risk is the strategic formulation of part sourcing strategies (optimally selecting one or more suppliers from which to purchase parts over the life of the part’s use within a product or organization). Strategic sourcing offers a way of avoiding the risk of part unavailability (and its associated penalties), but at the expense of qualification and support costs for multiple suppliers. An alternative disruption mitigation strategy is hoarding. Hoarding involves stocking enough parts in inventory to satisfy the forecasted part demand (for both manufacturing and maintenance requirements) of a fixed future time period. This excess inventory provides a buffer that reduces the effect of supply chain disruptions on the part total cost of ownership (TCO), but increases the total holding cost.
This paper presents a method of performing tradeoff analyses and identifying the optimal combination of second sourcing and hoarding for a specific part and product scenario. A case study was performed to examine the effects of hoarding on both single and second sourced parts. The case study results show that hoarding can contribute to a decrease in the cumulative TCO and a decrease in its variance.
Multi-Stage Optimization of Wind Farms With Limiting Factors
Authors: DuPont Bryony L. , Cagan Jonathan 
Published: February 2014

Larger onshore wind farms are often installed in phases, with discrete smaller sub-farms being installed and becoming operational in succession until the farm as a whole is completed. An extended pattern search (EPS) algorithm that selects both local turbine position and geometry is presented that enables the installation of a complete farm in discrete stages, exploring optimality of both incremental sub-farm solutions and the completed project as a whole. The objective evaluation is the maximization of profit over the life of the farm, and the EPS uses modeling of cost based on an extensive cost analysis by the National Renewable Energy Laboratory (NREL). The EPS uses established wake modeling to calculate the power development of the farm, and allows for the consideration of multiple or overlapping wakes.
A limiting factor is used to determine the size of wind farm stages: optimization stages based on the number of turbines currently available for development (representative of limitations in initial capital, which is commonly encountered in wind farm stage development). Two wind test cases are considered: a unidirectional test case with constant wind speed and a single wind direction, and a multidirectional test case, with three wind speeds and a defined probability of occurrence for each. The test case shown in the current work is employed on a 4000 km by 4000 km solution space. In addition, two different methods are performed: the first uses the optimal layout of a complete farm and then systematically “removes” turbines to create smaller sub-farms; the second uses a weighted multi-objective optimization over sequential, adjacent land that concurrently optimizes each sub-farm and the complete farm. The exploration of these resulting layouts indicates the value of full-farm optimization (in addition to optimization of the individual stages) and gives insight into how to approach optimality in sub-farm stages. The behavior exhibited in these tests cases suggests a heuristic that can be employed by wind farm developers to ensure that multi-stage wind farms perform at their peak throughout their completion.
Study on Method to Generate Wood Grain Pattern Representing Required Impression
Authors: Akiyama Ryo , Mori Takuya , Aoyama Hideki , Oya Tetsuo 
Published: February 2014

Various approaches for generating wood grain patterns using computer graphics have been proposed so far. However, with such conventional methods, it is difficult to reproduce real wood grain patterns, as well as design wood grain patterns with impressions that reflect customer needs.
This paper proposes a new approach for generating wood grain patterns. For instance, it can generate virtual trees by simulating tree growth taking into consideration environmental conditions, model fine tree tissues and reflection properties at the wood surface, etc. By applying these modeled factors, more diverse and accurate wood grain patterns can be generated. The authors also propose a method of controlling the grain patterns generated based on Kansei to realize grain patterns that meet customer needs. By building the basic system of the proposed method, various grain patterns could be generated, and grain pattern impressions controlled.
Emotionally Acceptable Decision Making in Engineering
Authors: Fukuda Shuichi 
Published: February 2014

Although there are many approaches to decision making, most of them are tools for a Closed World, they do not necessary provide a tool for decision making for such problems which many disciplines are related to and much heuristics or experience are called for.
Today, our world is expanding very quickly and the boundaries are disappearing very rapidly. In such an Open World, we need a wide variety of knowledge and experience to make a decision
And these pieces are not necessary obtained from the first. As we step forward, we find out what additional information is needed and we change our tracks to pursue better solutions.
And constraints also change with progress. In a Closed World, hard constraints remain hard all the way, but in an Open World, hard constraints may change to soft ones later.
Thus, how we can manage constraints and how we can postpone our decisions until we have necessary pieces of information are very important in decision making in an Open World.
This paper demonstrates that an AI approach provides a very versatile and useful tool for decision making in an open world by taking the case of producing welding procedure specification as an illustrative example.
Impact of Model-Based Design in Engineering Design Education
Authors: Andersson Kjell 
Published: February 2014

Project-based education in combination with problem-based learning has been very successful, and has contributed to the popularity of engineering design among students at technical universities. And when the project work addresses real industrial problems, offers insight into post-graduation working environments and gets direct feedback from professionals in industry, students can see the immediate relevance of their education — an invaluable boost to their learning experience.
Students taking MF2004, a capstone course at KTH Department of Machine Design, learn the whole process from idea generation to manufacturing and testing a final prototype built in close collaboration with an industrial partner or a research group at the department. The benefits of using real prototypes cannot be stressed enough — students find out for themselves why a product must be designed in a certain way (e.g. to make it possible to assemble). The course uses project-based learning as a teaching strategy and introduces a model-based design methodology which enables the students to evaluate and “experience” many different behaviors of the product using digital models in a virtual environment. In this way, students can see that many undesirable concepts and flaws can be avoided even before a prototype is manufactured.
This paper focuses on the introduction of the model-based design methodology and evaluation of its impact on learning in a capstone course in the Engineering Design MSc programme at KTH Department of Machine Design. A questionnaire was used to evaluate the effects on the students’ learning, as well as to assess how feasible they consider this methodology to be. On the basis of this, in combination with the weekly meetings with the project teams, we can report a positive attitude among the students and improved learning outcomes.
Development of a Common Platform for Testing Metamodel Based Design Optimization Methods
Authors: Younis Adel A. , Cheng George H. , Wang G. Gary , Dong Zuomin 
Published: February 2014

Metamodel based design optimization (MBDO) algorithms have attracted considerable interests in recent years due to their special capability in dealing with complex optimization problems with computationally expensive objective and constraint functions and local optima. Conventional unimodal-based optimization algorithms and stochastic global optimization algorithms either miss the global optimum frequently or require unacceptable computation time. In this work, a generic testbed/platform for evaluating various MBDO algorithms has been introduced. The purpose of the platform is to facilitate quantitative comparison of different MBDO algorithms using standard test problems, test procedures, and test outputs, as well as to improve the efficiency of new algorithm testing and improvement. The platform consists of a comprehensive test function database that contains about 100 benchmark functions and engineering problems. The testbed accepts any optimization algorithm to be tested, and only requires minor modifications to meet the test-bed requirements.
The testbed is useful in comparing the performance of competing algorithms through execution of same problems. It allows researchers and practitioners to test and choose the most suitable optimization tool for their specific needs. It also helps to increase confidence and reliability of the newly developed MBDO tools. Many new MBDO algorithms, including Mode Pursuing Sampling (MPS), Pareto Set Pursuing (PSP), and Space Exploration and Unimodal Region Elimination (SEUMRE), were tested in this work to demonstrate its functionality and benefits.
Using Planar Kinematics to Construct the Full 4-D Tolerance-Map for a Line-Profile
Authors: Savaliya S. B. , Davidson J. K. , Shah Jami J. 
Published: February 2014

Tolerances on line-profiles are used to control cross-sectional shapes of parts, even mildly twisted ones such as those on turbine or compressor blades. Such tolerances limit geometric manufacturing variations to a specified two-dimensional tolerance-zone, i.e. an area, the boundaries to which are curves parallel to the true profile. The single profile tolerance may be used to control position, orientation, and form of the profile.
For purposes of automating the assignment of tolerances during design, a math model, called the Tolerance-Map (T-Map), has been produced for most of the tolerance classes that are used by designers. Each T-Map is a hypothetical point-space that represents the geometric variations of a feature in its tolerance-zone. Of the six tolerance classes defined in the ASME/ANSI/ISO Standards, only one attempt has been made at modeling line-profiles [1], and the method used is a kinematic description, based largely on intuition, of the allowable displacements of the middle-sized profile within its tolerance-zone. The result presented is a 4-D double pyramid having a 3-D shape for the common base. Allowable small changes in size represent the fourth dimension in the altitude-direction of the pyramids. However, that work is limited to square, rectangular, and right-triangular profile shapes for which the 3-D transverse sections (called hypersections) of the 4-D T-Map are all geometrically similar to the base because the boundaries are doubly traced. For more generally shaped profiles, [2] the hypersections are not geometrically similar to the base.
The objective of this paper is to expand the kinematic description of a profile in its tolerance-zone to include the changing constraints that take place as size is incremented or decremented within the allowable tolerance-range. It provides validation of a different method that is described in a companion paper [3].
Validating the Coupling of Multibody Dynamic Simulations With Sea Keeping Simulations
Authors: Hannot Stephan D. A. , Los Jan G. , van Spaendonk Bram A. W. , Kruijswijk Alex B. , de Krijger Albert C. L. 
Published: February 2014

Dredging is the activity of excavating soil or other sediments from the bottom of a water body such as a lake or sea. The purpose of dredging varies: e.g. maintaining the depth of waterways or obtaining material for beach nourishment. Most ‘dredgers’ are composed of a floating structure (ship or pontoon) on which the dredging equipment that is used to excavate at the seabed is installed.
Dredging at open sea, offshore dredging, becomes a more common operating condition. This means that dredgers will have to be designed with surface wave induced motions and forces in mind. Therefore simulating the motions of dredgers due to surface waves coupled with the motion of the dredging equipment is an important design analysis step. This requires a tool that can simulate a coupled sea keeping and multibody dynamic problem. In this work the theory, development and validation of such a simulation tool are discussed.
Gear Noise Diagnosis System for Automobile Transmission Using Artificial Intelligence (Effect of Number of Intermediate Layers on Judgement Performance)
Authors: Nakamura Morimasa , Nishiyama Masahiko , Moriwaki Ichiro 
Published: February 2014

The present paper describes a digitizing method for the measured gear noise and a construction of a neural network system for gear noise diagnosis.
Gear noise emitted from automobile transmissions should be evaluated by gear noise experts. Although quietness performance estimates from measured noise levels of the transmissions on some production lines, the estimation must be very difficult. There is not a certain relationship between the measured noise levels and the evaluations by the gear noise experts. Therefore, the estimation should be severe. As a result, such an automatic gear noise diagnosis system must yield transmissions with over-quality.
The present study deals with a new gear noise diagnosis system to which an artificial intelligence, that is, a neural network system is applied. The previous evaluations by the new gear noise diagnosis system were good when the statistical property of the teacher signals from which the neural network system learned was similar to that of population. This fact means that many teacher signals are necessary on the practical use.
Proposed digitizing method of gear noise levels provided good evaluations of neural network system even when the statistical properties of the teacher signals were not similar to that of the population. In addition, a new method, “Moment method” for determining the construction of the neural network system was introduced instead of “Back Propagation Method”. The Moment Method contributed to the improvement of the system judgments.
The neural network system constructed using the Moment Method brought good performance. And the number of intermediate layers in the neural network system could be small enough to obtain good performance. It was found that the Moment method provided good learning because of connecting weights update function. When the Moment method was used for determining the connection weights between neurons in the neural network system, the developed gear noise diagnosis system achieved high and stable correct answer ratio. And the number of intermediate layers in the neural network system was only one enough for obtaining good performance of the system. Four intermediate layers, which was the maximum in this paper, did not provide much good performance.
Experimental Assessment of the Clique Problem in FlexRay
Authors: Horauer Martin , Schuster Harald , Balog Peter 
Published: February 2014

The FlexRay bus protocol recently adopted by the automotive industry provides both a time- and event-triggered communication paradigm, combined with communication via two independent channels, as well as optional bus-guardians in order to meet the bandwidth and reliability requirements by present and future emerging automotive applications.
Despite the benefits and improvements, when compared to traditional bus systems (e.g., CAN), rare faults may still occur. In this regard, this paper presents an experimental investigation of the clique problem, where a FlexRay network gets partitioned into multiple functional domains. In such a scenario the nodes within a domain may still be able to communicate with each other, however, not across domain boundaries. As a result affected applications that rely on information from nodes of either domain may be impaired in their intended functionality as long as such a clique exists. Such an impairment affecting critical applications like the braking system may result in hazardous situations.
Numerical Computation of Nonlinear Normal Modes of Nonconservative Systems
Authors: Renson L. , Kerschen G. 
Published: February 2014

Since linear modal analysis fails in the presence of non-linear dynamical phenomena, the concept of nonlinear normal modes (NNMs) was introduced with the aim of providing a rigorous generalization of linear normal modes to nonlinear systems. Initially defined as periodic solutions, numerical techniques such as the continuation of periodic solutions were used to compute NNMs. Because these methods are limited to conservative systems, the present study targets the computation of NNMs for non-conservative systems. Their definition as invariant manifolds in phase space is considered.
Specifically, the partial differential equations governing the manifold geometry are considered as transport equations and an adequate finite element technique is proposed to solve them. The method is first demonstrated on a conservative nonlinear beam and the results are compared to standard continuation techniques. Then, linear damping is introduced in the system and the applicability of the method is demonstrated.