bluuebunny/crossref_metadata_2025 huggingface dataset:
Robot Base Placement and Kinematic Evaluation of 6R Serial Manipulators to Achieve Collision-Free Welding of Large Intersecting Cylindrical Pipes
Authors: Dharmawan Audelia Gumarus , Sedore Blake William Clark , Soh Gim Song , Foong Shaohui , Otto Kevin
Published: January 2016

This paper presents a systematic approach for identifying feasible robot base placement regions within a workcell, and evaluating performance of industrial robots for the design of mobile industrial robotic system to perform collision-free automated welding of large intersecting cylindrical pipe structures. First, a mathematical model based on the geometry of intersecting cylindrical pipes is used to generate the welding task and torch orientation. Next, collision detection is performed using line geometry and possible robot base positions are identified and rated according to the manipulability measure. This yields a graph of feasible robot base placement regions that perform collision-free welding rated in terms of its dexterity. Finally, a task metric based on kinematic measures to evaluate the robot’s performance is proposed and discussed. An implementation of this approach for evaluating two different 6R industrial robots for welding jack-up rig structures was used as examples. This technique will also be applicable for designing mobile robotic system for tasks other than welding which may require trajectory-following end-effector motion uninterrupted by objects within the workspace such as painting, taping, blasting, cutting, etc.
Abstraction of Semantic Mid-Surface Based on Rib-Feature Recognition
Authors: Zhu Huawei , Liu Yusheng
Published: January 2016

Mid-surface abstraction is an effective simplification method for thin-wall models. The complexity of finite element analysis (FEA) for a mid-surface model can be reduced greatly after abstraction. Although the model decomposition method is adopted for mid-surface extraction, it is hard to obtain the correct mid-surface model for complex models since the existing heuristic rule based methods lack of design intention. In addition, the mid-surface model is not easy to reuse. In this study, a semantic based mid-surface model representation and generation method is proposed. Firstly, a hierarchical semantic mid-surface model based on rib-feature decomposition is proposed. Secondly, based on the reorganization of rib-features and decomposition of the thin-wall model, the rib-features’ semantic information are obtained by the abstraction of the structure and connection in the thin-wall model. Then the hierarchical structure is generated by connection semantics. According to the various structure semantics, different abstraction methods will be employed to get the mid-surface patch for each sub region. Finally, the hierarchical semantic mid-surface model is constructed by the generation of the connection relationship between mid-surface patches based on the connection semantics between the rib-features. This semantic model ensures the high efficiency and accuracy of mid-surface regeneration when local modifications occur to a thin-wall model. A typical example is given to demonstrate the process.
Magneto-Rheological (MR) Valve for Use in Hydro-Pneumatic Suspensions
Authors: Grobler Jacob F. , Els Schalk
Published: January 2016

The suspension design requirements for vehicles that need both good on-road and off-road capabilities as well as vehicles where the payload changes significantly during operation is quite challenging. To overcome the ride comfort vs. handling compromise that most vehicles suffer from some suspension systems offer adjustability and control to overcome this conflict. The uptake of controllable dampers on commercial vehicles, allthough cost effective and technically feasible, have been low mainly because dampers on their own cannot significantly reduce the compromises involved with fully laden vs. empty or on-road vs. off-road use. The University of Pretoria developed a Four State Semi-Active Suspension System (4S4) that allows for the control and adjustability of the stiffness and the damping of the suspension. The 4S4 makes use of solenoid valves of which the response time unfortunately increases with an increase in flow, especially when implemented on larger vehicles, reducing the effectiveness of the control.

This paper presents an alternative to the solenoid valves currently used in the 4S4 in the form of a magneto-Rheological (MR) valve that acts as a normal continuously variable MR damper, but also has the ability to virtually block the flow of fluid, thus switching between the two different spring characteristics. Experimental results show that it is indeed possible to replace the solenoid valves with a MR valve.
Development of Manufacturing Method for Truss Core Panel Based on Origami-Forming
Authors: Nguyen Hoan Thai Tat , Thai Phuong Thao , Yu Bo , Hagiwara Ichiro
Published: January 2016

Although honeycomb panel is widely used in various stages, its adhesive for gluing honeycomb core and plate may burn by fire, leading to the requirement of another lightweight and high stiffness panel. Recently, an Origami structure called Truss Core Panel (TCP) is known as a lightweight structure that has equivalent bending stiffness as honeycomb panel, and safer in fire. However, some difficulties are found in forming TCP in general. In this study, a new forming process of TCP based on origami-forming is developed. In particular, the TCP is partitioned into several parts that are flat unfoldable into 2D crease patterns. After that, blanks of material are cut as the shapes of those crease pattern, and be formed by a robot system to get the desired 3D shape. Firstly, partition method by dividing TCP into pyramid cores and sheet plate is presented, suggesting an ability to manufacture a wider range of structure than before. Tools arrangement of robot device and a countermeasure for springback are considered. Next, by applying Origami unfolding technique, an improvement of partition method is proposed: dividing TCP into cores rows, and then searching for a Origami crease pattern in order to fold that cores row. The cutting method of every core is modified for reducing the number of facets, making the problem simpler. Finally, an Origami crease pattern based on this new cutting method is presented, producing cores row with any number of cores.
Sampling Methods for Uncertainty in Life Cycle Cost Analysis in Product Design
Authors: Cunha Lorena , Wang Qing
Published: January 2016

Life cycle cost (LCC) analysis was initiated from the necessity to calculate the cost of products from ‘cradle to grave’. LCC is not a new tool, but its use is still limited and requires further studies, especially concerning all the uncertainty involved. This project seeks to study and understand the difference between the two most common sampling methods utilized to measure this uncertainty: Latin Hypercube sampling (LHS) and Random sampling (also known as Monte Carlo sampling). The LLC model was developed in SEER-H Galorath Software and the samples from two different types of variable and in two sizes (100 and 1000) were collected using Microsoft Excel and the Risk Solver Add-in. The data was analyzed with a range of statistical tools using the R package software: t-Test, boxplot, scatterplot and the cumulative distribution function. The results point to the fact that LHS seems to be more accurate using small samples, but when comparing big samples the outcome is quite similar in both sampling methods.
Measurement of Assembly System Complexity Based on the Task Differences Induced From Product Variety
Authors: Oh Kwansuk , Kim Daeyoung , Hong Yoo S.
Published: January 2016

As mass customization becomes a major challenge for manufacturing companies, assembly systems should have the capabilities to accommodate a high variety of products. Since the assembly system operations become much more complex with the increased variety, the firms are in need of a measure which is general and practical enough to correctly estimate the complexity of an assembly system. This paper proposes a new model which measures the complexity based on the modeling of production architecture. Production architecture describes how a product is processed in an assembly system. Then, the complexity is measured by checking which tasks are processed at each station since the differences among tasks are regarded as the main cause of complexity. The model has been applied to a case, a simplified version of real data from an electronics manufacturer. Applying this approach, the complexity induced from task differences can be measured from each station to an entire assembly system, and one can reduce the overall complexity by controlling the tasks which are allocated to stations. Consequently, the firms can get fundamental insights into the operation of complex assembly systems with the help of production architecture from which the complexity measure is derived.
Variable-Fidelity Optimization With In-Situ Surrogate Model Refinement
Authors: Mehmani Ali , Chowdhury Souma , Messac Achille
Published: January 2016

Owing to the typical low fidelity of surrogate models, it is often challenging to accomplish reliable optimum solutions in Surrogate-Based Optimization (SBO) for complex nonlinear problems. This paper addresses this challenge by developing a new model-independent approach to refine the surrogate model during optimization, with the objective to maintain a desired level of fidelity and robustness “where” and “when” needed. The proposed approach, called Adaptive Model Refinement (AMR), is designed to work particularly with population-based optimization algorithms. In AMR, reconstruction of the model is performed by sequentially adding a batch of new samples at any given iteration (of SBO) when a refinement metric is met. This metric is formulated by comparing (1) the uncertainty associated with the outputs of the current model, and (2) the distribution of the latest fitness function improvement over the population of candidate designs. Whenever the model-refinement metric is met, the history of the fitness function improvement is used to determine the desired fidelity for the upcoming iterations of SBO. Predictive Estimation of Model Fidelity (an advanced surrogate model error metric) is applied to determine the model uncertainty and the batch size for the samples to be added. The location of the new samples in the input space is determined based on a hypercube enclosing promising candidate designs, and a distance-based criterion that minimizes the correlation between the current sample points and the new points. The powerful mixed-discrete PSO algorithm is used in conjunction with different surrogate models (e.g., Kriging, RBF, SVR) to apply the new AMR method. The performance of the proposed AMR-based SBO is investigated through three different benchmark functions.
Three-Dimensional Tooth Segmentation by Integrating Multiple Ray-Sum Images From CBCT Data
Authors: Barone Sandro , Paoli Alessandro , Razionale Armando V.
Published: January 2016

The reconstruction of tooth anatomies is of utmost importance when dental implant surgeries and/or orthodontic corrections must be planned. In the last few years, cone beam CT (CBCT) has gained popularity in dentistry for 3D imaging of jawbones and teeth. However, within CBCT data sets, each tooth is defined by a region, which cannot be easily separated from surrounding tissues (i.e., bone tissue) by only considering pixel’s grey-intensity values. For this reason, some enhancement is usually necessary in order to properly segment tooth geometries.

In this paper, a semi-automatic approach to reconstruct individual 3D tooth anatomies by processing CBCT-scan data is presented. The methodology is based on the creation of a minimal number of 2D “local ray-sum” images by adding the absorption values of adjacent voxels along the most significant views for each tooth. The knowledge of the specific anatomical patient morphology drives the selection of these significant projection directions. The reconstructed “ray-sum” images greatly enhance the clearness of the root contours, which can then be interactively traced by dentists. A set of meaningful 2D tooth contours is consequently obtained and used to automatically extract a cubic spline curve for each transverse slice, thus approximating the overall 3D tooth profile.

The effectiveness of the methodology has been evaluated by comparing the results obtained for the reconstruction of anterior teeth with those obtained by using classical segmentation tools provided within commercial software.
Investigation of GPU Use in Conjunction With DCA-Based Articulated Multibody Systems Simulation
Authors: Laflin Jeremy J. , Anderson Kurt S. , Hans Michael
Published: January 2016

Since computational performance is critically important for simulations to be used as an effective tool to study and design dynamic systems, the computing performance gains offered by Graphics Processing Units (GPUs) cannot be ignored. Since the GPU is designed to execute a very large number of simultaneous tasks (nominally Single Instruction Multi-Data (SIMD)), recursive algorithms in general, such as the DCA, are not well suited to be executed on GPU-type architecture. This is because each level of recursion is dependent on the previous level. However, there are some ways that the GPU can be leveraged to increase computational performance when using the DCA to form and solve the equations of motion for articulated multibody systems with a very large number of degrees-of-freedom.

Computational performance of dynamic simulations is highly dependent on the nature of the underlying formulation and the number of generalized coordinates used to characterize the system. Therefore, algorithms that scale in a more desirable (lower order) fashion with the number of degrees-of-freedom are generally preferred when dealing with large (N > 10) systems. However, the utility of using simulations as a scientific tool is directly related to actual compute time. The DCA, and other top performing methods, have demonstrated the desirable property of the required compute time scaling linearly with (O(n)) with the number of degrees-of-freedom (n) and sublinearly (O(logn) performance when implemented in parallel. However for the DCA, total compute time could be further reduced by exploiting the large number of independent operations involved in the first few levels of recursion.

A simple chain-type pendulum example is used to explore the feasibility of using the GPU to execute the assembly and disassembly operations for the levels of recursion that contain enough bodies for this process to be computationally advantageous. A multi-core CPU is used to perform the operations in parallel using Open MP for the remaining levels. The number of levels of recursion that utilizes the GPU is varied from zero to all levels. The data corresponding to zero utilization of the GPU provides the reference compute-time in which the assembly and disassembly operations necessary at each level are performed in parallel using Open MP. The computational time required to simulate the system for one time-step where the GPU is utilized for various levels of recursion is compared to the reference compute time also varying the number of bodies in the system.

A decrease in the compute-time when using the GPU is demonstrated relative to the reference compute-time even for systems of moderate size n < 1000 for arrangements using the GPU. This is a lower number of bodies than was expected for this test case and confirms that the GPU can bring significant increases in computational efficiency for large systems, while preserving the attractive sub-linear scalability (w.r.t. compute time) of the DCA.
A Product Feature Inference Model for Mining Implicit Customer Preferences Within Large Scale Social Media Networks
Authors: Tuarob Suppawong , Tucker Conrad S.
Published: January 2016

The acquisition and mining of product feature data from online sources such as customer review websites and large scale social media networks is an emerging area of research. In many existing design methodologies that acquire product feature preferences form online sources, the underlying assumption is that product features expressed by customers are explicitly stated and readily observable to be mined using product feature extraction tools. In many scenarios however, product feature preferences expressed by customers are implicit in nature and do not directly map to engineering design targets. For example, a customer may implicitly state “wow I have to squint to read this on the screen”, when the explicit product feature may be a larger screen. The authors of this work propose an inference model that automatically assigns the most probable explicit product feature desired by a customer, given an implicit preference expressed. The algorithm iteratively refines its inference model by presenting a hypothesis and using ground truth data, determining its statistical validity. A case study involving smartphone product features expressed through Twitter networks is presented to demonstrate the effectiveness of the proposed methodology.
A Novel Methodology for the Creation of Customized Eruption Guidance Appliances
Authors: Tilli Jacopo , Paoli Alessandro , Razionale Armando V. , Barone Sandro
Published: January 2016

Within the orthodontic field, malocclusion problems are usually treated by using different types of appliances. In particular, Eruption Guidance Appliances (EGAs) are recommended for early orthodontic treatment or prevention of malocclusion problems. The traditional approach with EGAs is based on the use of standard prefabricated appliances. Experts in the orthodontic field believe that the customization of the EGAs would strongly enhance the results of malocclusion treatments.

This paper presents an innovative methodology for the design and manufacturing of fully customized EGAs. The methodology is based on an extensive integration between traditional orthodontic procedures with advanced computer aided design processes. The methodology moves from the digitalization of the plaster models obtained by optical scanning techniques. The patient morphology is then exploited, under dental practitioner supervision, for the design of the appliance geometry through CAD modeling tools. Medical guided assessment is required throughout the most of the data elaboration processes, in order to design the EGAs accordingly to the patient’s clinical conditions. Low-pressure injection molds for the physical manufacturing of the appliances are then 3D printed by using rapid prototyping techniques. The proposed methodology allows the production of patient customized appliances guaranteeing low cost manufacturing and high quality standards, similar to those typically obtained by in series productions. Moreover, the presented approach offers a high integration level with numerical and finite element methods, which can be used for evaluating the stress applied on the EGA, thus allowing the reinforcement of the appliance prior its manufacturing.
Text Analysis of Assembly Work Instructions
Authors: Renu Rahul Sharan , Mocko Gregory
Published: January 2016

The objective of this research is to investigate the requirements and performance of parts-of-speech tagging of assembly work instructions. Natural Language Processing of assembly work instructions is required to perform data mining with the objective of knowledge reuse. Assembly work instructions are key process engineering elements that allow for predictable assembly quality of products and predictable assembly lead times. Authoring of assembly work instructions is a subjective process. It has been observed that most assembly work instructions are not grammatically complete sentences. It is hypothesized that this can lead to false parts-of-speech tagging (by Natural Language Processing tools). To test this hypothesis, two parts-of-speech taggers are used to tag 500 assembly work instructions (obtained from the automotive industry). The first parts-of-speech tagger is obtained from Natural Language Processing Toolkit (nltk.org) and the second parts-of-speech tagger is obtained from Stanford Natural Language Processing Group (nlp.stanford.edu). For each of these taggers, two experiments are conducted. In the first experiment, the assembly work instructions are input to the each tagger in raw form. In the second experiment, the assembly work instructions are preprocessed to make them grammatically complete, and then input to the tagger. It is found that the Stanford Natural Language Processing tagger with the preprocessed assembly work instructions produced the least number of false parts-of-speech tags.
Multi-Corrugated Indented Foldcore Sandwich Panel for Energy Absorption
Authors: Li Yang , You Zhong
Published: January 2016

Sandwich panels, which consist of light core structure in middle and two outside skins, have been widely used for load bearing and energy absorption. Recently, origami foldcores, which can be used as light core structures in sandwich panels, are of interest of many for their open-channel design, continuous manufacturing process, and abundant number of design parameters in comparison with honeycomb and foams. However, one main drawback of origami foldcores is their relatively low energy absorbing capacity. In this paper, we propose a new origami foldcore design, which is based on a zigzag origami pattern known as Miura pattern. The new design has a multi-corrugated shape as its cross-section, and asymmetric dents in it. It achieves a more efficient failure mechanism with both shell buckling and inversing modes, and doubles the energy absorption of Miura pattern foldcore.
Advancing the Additive Manufacturing Workforce: Summary and Recommendations From a NSF Workshop
Authors: Williams Christopher B. , Simpson Timothy W. , Hripko Michael
Published: January 2016

Accompanying the increasing advances and interest in Additive Manufacturing (AM) technologies is an increasing demand for a workforce that is knowledgeable about the technologies and how to employ them to solve engineering problems. As a step towards addressing this knowledge gap, a workshop was held at the National Science Foundation (NSF) to discuss the educational needs of, and opportunities for, developing an AM workforce. With the goal of developing novel educational partnerships to better prepare and enhance the AM workforce, the workshop participants — 66 representatives from academia, industry, and government — sought to answer questions such as “What should we teach to the AM workforce and why?”, “To whom and how should we teach AM?”, and “How should we partner for AM education and training?” Key educational themes that emerged include: (1) AM processes and process/material relationships, (2) engineering fundamentals with an emphasis on materials science and manufacturing, (3) professional skills for problem solving and critical thinking, (4) design practices and tools that leverage the design freedom enabled by AM, and (5) cross-functional teaming and ideation techniques to nurture creativity. The paper summarizes the speaker presentations and outcomes from the workshop, along with several new educational partnerships identified by small working groups. Based on the presentations and partnerships, we recommend the following to advance the AM workforce. First, ensure that all AM curricula provide students with an understanding of (i) AM and traditional manufacturing processes to enable them to effectively select the appropriate process for product realization; (ii) the relationships between AM processes and material properties; and (iii) “Design for AM”, including computational tools for AM design as well as frameworks for process selection, costing, and solution generation that take advantage of AM capabilities. Second, establish a national network for AM education that, by leveraging existing “distributed” educational models and NSF’s ATE Programs, provides open source resources as well as packaged activities, courses, and curricula for all educational levels (K-Gray). Third, promote K-12 educational programs in STEAM (STEM plus the arts) and across all formal and informal learning environments in order to leverage the unique capabilities of AM in engaging students in hands-on, tactile, and visual learning activities. Fourth, provide support for collaborative and community-oriented maker spaces that promote awareness of AM among the public and provide AM training programs for incumbent workers and students seeking alternative pathways to gain AM knowledge and experience. Recommendations for scaling and coordinating these activities across local, regional, and national levels are also discussed to create synergies among the proposed activities and existing efforts.
Evaluation of a Model Based Learning Approach for Engineering Design
Authors: Andersson Kjell
Published: January 2016

Project-based education in combination with problem-based learning has been very successful, and has contributed to the popularity of engineering design education among students at technical universities. The close connection to industrial problems by the use of industry-connected projects has boosted this popularity still further and to get an insight of future working environments after graduation is very inspiring for the students.

The curriculum of the Machine Design capstone course at KTH Department of Machine Design covers the whole process from idea generation to manufacturing and testing a final prototype. A major part of the course consists of project work where students develop a product prototype in close cooperation with an industrial partner or with a research project at the department. This means that a major part of the course uses project-based learning as a teaching strategy. In addition, a model-based design methodology is introduced 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 evaluates the use and learning outcome of model-based design in a capstone course in the Engineering Design MSc program at KTH Department of Machine Design. The approach has been used during a period of three years and the effect on the students’ learning has been evaluated by a questionnaire after each course. I this paper we compare the results of these questionnaires and discuss implications and general conclusions about this learning approach.
Design of Multi-Degree-of-Freedom Planar Morphing Mechanisms With Single-Degree-of-Freedom Sub-Chains
Authors: Funke Lawrence , Schmiedeler James P.
Published: January 2016

This paper deals with the synthesis of multi-degree-of-freedom planar mechanisms by breaking the problem into the synthesis of multiple single-degree-of-freedom planar mechanisms. Specifically, this paper investigates synthesizing shape-changing mechanisms capable of matching multiple closed profiles with significant changes in shape. These mechanisms can be used for applications such as morphing wings or morphing dies for polymer extrusion. Well established synthesis techniques for single-degree-of-freedom planar mechanisms are used and reviewed for completeness. The paper then compares multiple forms of two optimization techniques used to find suitable mechanisms. The problems investigated herein are highly nonlinear and highly constrained; therefore, advanced optimization strategies are needed. This paper uses both gradient-based optimization and a genetic algorithm (GA) to find mechanisms capable of matching the design profiles. It also looks at additions to the GA that leverage the presence of the single-degree-of-freedom subchains. The gradient-based optimization and GA with additions were able to find mechanisms with better matching error than the blind GA. However, the improvement was modest and not always present, indicating that it is likely best to start with the blind GA and introduce gradient-based optimization, additions to the GA, and changes in the setting as needed to improve results.
Resource Allocation for Reduction of Epistemic Uncertainty in Simulation-Based Multidisciplinary Design
Authors: Jiang Zhen , Chen Shishi , Apley Daniel W. , Chen Wei
Published: January 2016

Epistemic model uncertainty is a significant source of uncertainty that affects a multidisciplinary system. In order to achieve a reliable design, it is critical to ensure that the disciplinary/subsystem simulation models are trustworthy, so that the aggregated uncertainty of system quantities of interest (QOIs) is acceptable. Uncertainty reduction can be achieved by gathering additional experiments and simulations data; however resource allocation for multidisciplinary design optimization (MDO) remains a challenging task due to the complex structure of a multidisciplinary system. In this paper, we develop a novel approach by integrating multidisciplinary uncertainty analysis (MUA) and multidisciplinary statistical sensitivity analysis (MSSA) to answer the questions about where (sampling locations), what (disciplinary responses), and which (simulations versus experiments) for allocating more resources. To manage the complexity in making the above decisions, a sequential procedure is proposed. First, the input space of a multidiscipline system is explored to identify the locations with unacceptable amounts of uncertainty with respect to the system QOIs. Next, these input locations are selected through a correlation check so that they are sparsely located in the input space, and their corresponding critical responses are identified based on MSSA. Finally, using a preposterior analysis, decisions are made about what type of resources (experimental or computational) should be allocated to the critical responses at the chosen input locations. The proposed method is applied to a benchmark electronic packaging problem to demonstrate how epistemic uncertainty is gradually reduced via gathering more data.
Road-Vehicles Control Logic Integrating Real Time Multibody Model Follower
Authors: Ramirez Ruiz Isabel , Sabbioni Edoardo , Braghin Francesco , Cheli Federico
Published: January 2016

The challenge to enhance the vehicle driving and handling with a state estimation and prediction system is presented by fusing a primary real time multibody vehicle model capable of providing a good indication of vehicle stability and control, and a secondary model able to estimate the vehicle state from vehicle real and virtual sensors to correct the indications of the primary model. A mathematical algorithm combines these two models in the drive control system improving the behavior of the active systems of the vehicle.

A Multibody vehicle model has been used to achieve a high fidelity simulation of vehicle dynamics. The selected software is LMS.Virtual.Lab Motion with Real-Time Solver which complements the AMESim Real-Time Solver to handle complex real-time 3D-1D mechatronic systems without any simplified conceptual models.

A Sensor Signal Processing Model has been developed to estimate the vehicle states and calculating tire-road contact forces and vehicle sideslip angle. The methodological approach uses the equations of motion of the chassis applying the fundamental principles of classical physics: Newtonian method and Euler angles.

The control logic is based on the continuous updating of the preview multibody vehicle model by the controller sensors information network, which makes the model forecast behavior closer to the real one and improve comfort and linearity of the vehicle response. The driver inputs (throttle, steer angle and torque, brake, gear) are the same for the MBS real time model and for the real vehicle. A first training logic updates the MBS model based on the real vehicle behavior calculated by the sensor network, where the logic has to update in the MBS model just the factors depending on the vehicle itself (for example car weight, tire temperature, shock absorber damping forces, tires characteristics) and to understand and keep into account different environment variation (wet / dry surface). If the real vehicle is equipped with active control systems to improve handling and stability, as active camber control, drive by wire, ESP, Body movement active controls, the real time multibody model will interact with the models 1D or 3D of these vehicle dynamics controls and will improve their performance with a very high accuracy prediction of their influence on vehicle dynamic response.

In conclusion with the help of the preview multibody vehicle model the drive control logic will increase the performance and drive ability of the vehicle with smart logic interacting with all the active systems.
Emotional Modularization
Authors: Fukuda Shuichi
Published: January 2016

This paper points out that in order to provide emotional satisfaction to the customer, hardware products should be modularized not only with functions or shapes, but with more meanings such as adaptability, etc. Thus, a network-structured modularization is called for more than a tree-structured one to cope with diverse customer expectations.

The emerging field of material digitalization, which can be compared to physical FEM, is expected to provide a versatile and flexible tool for this purpose and it will change our design from the current open loop system to the closed loop system so that it will provide us with the capability of managing deterioration and that of adaptability to the frequently and widely changing situations.
Analysis and Design of a Two Degree of Freedom Hoeckens-Pantograph Leg Mechanism
Authors: Fedorov Dmitri , Birglen Lionel
Published: January 2016

Hoeckens and Chebychev linkages have been widely discussed in the literature as design solutions to build single degree of freedom (DOF) leg mechanisms. Compared to fully actuated legs, often bio-inspired, they offer an unmatched simplicity. However, due to their limited motion capability, they can only be used when the traversed terrain is of limited difficulty. In order to alleviate this drawback, a novel design with a second DOF is proposed in this paper. The introduced mechanism is composed of a Hoeckens linkage augmented by a Pantograph for which the position of the pivot can be changed through an additional rotating link. Screw theory is used to determine the kinematic equations of the mechanism, its singular configurations, and its attainable workspace. Subsequently, an optimization of the geometric parameters is performed to maximize performance indices pertaining to the size of the mechanism’s workspace. Finally, possible use of compliant joints is discussed.
Design Sensitivity Method for Sampling-Based RBDO With Fixed COV
Authors: Cho Hyunkyoo , Choi K. K. , Lee Ikjin , Lamb David
Published: January 2016

Conventional reliability-based design optimization (RBDO) uses the means of input random variables as its design variables; and the standard deviations (STDEVs) of the random variables are fixed constants. However, the fixed STDEVs may not correctly represent certain RBDO problems well, especially when a specified tolerance of the input random variable is presented as a percentage of the mean value. For this kind of design problem, the coefficients of variations (COVs) of the input random variables should be fixed, which means STDEVs are not fixed. In this paper, a method to calculate the design sensitivity of probability of failure for RBDO with fixed COV is developed. For sampling-based RBDO, which uses Monte Carlo simulation for reliability analysis, the design sensitivity of the probability of failure is derived using a first-order score function. The score function contains the effect of the change in the STDEV in addition to the change in the mean. As copulas are used for the design sensitivity, correlated input random variables also can be used for RBDO with fixed COV. Moreover, the design sensitivity can be calculated efficiently during the evaluation of the probability of failure. Using a mathematical example, the accuracy and efficiency of the developed method are verified. The RBDO result for mathematical and physical problems indicates that the developed method provides accurate design sensitivity in the optimization process.
A Novel Application of Gamification for Collecting High-Level Design Information
Authors: Cheong Hyunmin , Li Wei , Iorio Francesco
Published: January 2016

This paper presents a novel application of gamification for collecting high-level design descriptions of objects. High-level design descriptions entail not only superficial characteristics of an object, but also function, behavior, and requirement information of the object. Such information is difficult to obtain with traditional data mining techniques. For acquisition of high-level design information, we investigated a multiplayer game, “Who is the Pretender?” in an offline context. Through a user study, we demonstrate that the game offers a more fun, enjoyable, and engaging experience for providing descriptions of objects than simply asking people to list them. We also show that the game elicits more high-level, problem-oriented requirement descriptions and less low-level, solution-oriented structure descriptions due to the unique game mechanics that encourage players to describe objects at an abstract level. Finally, we present how crowdsourcing can be used to generate game content that facilitates the gameplay. Our work contributes towards acquiring high-level design knowledge that is essential for developing knowledge-based CAD systems.
An Efficient Saddle Point Search Method Using Kriging Metamodels
Authors: He Lijuan , Wang Yan
Published: January 2016

Simulating phase transformation of materials at the atomistic scale requires the knowledge of saddle points on the potential energy surface (PES). In the existing first-principles saddle point search methods, the requirement of a large number of expensive evaluations of potential energy, e.g. using density functional theory (DFT), limits the application of such algorithms to large systems. Thus, it is meaningful to minimize the number of functional evaluations as DFT simulations during the search process. Furthermore, model-form uncertainty and numerical errors are inherent in DFT and search algorithms. Robustness of the search results should be considered. In this paper, a new search algorithm based on Kriging is presented to search local minima and saddle points on a PES efficiently and robustly. Different from existing searching methods, the algorithm keeps a memory of searching history by constructing surrogate models and uses the search results on the surrogate models to provide the guidance of future search on the PES. The surrogate model is also updated with more DFT simulation results. The algorithm is demonstrated by the examples of Rastrigin and Schwefel functions with a multitude of minima and saddle points.
Investigating the Impact of Interactive Immersive Virtual Reality Environments in Enhancing Task Performance in Online Engineering Design Activities
Authors: Bharathi Ajay Karthic B. Gopinath , Tucker Conrad S.
Published: January 2016

The objective of this paper is to test the hypothesis that immersive virtual reality environments such as those achievable through the head-mounted displays, enhance task performance in online engineering design activities. In this paper, task performance is measured by the time to complete a given engineering activity. Over the last decade, a wide range of virtual reality applications have been developed based on non-immersive and immersive virtual reality systems for educational purposes. However, a major limitation of non-immersive virtual reality systems is the lack of an immersive experience that not only provides content to students, but also enables them to interact and learn in a completely 360 degree immersive environment. The authors of this work have developed a replica of a physical engineering laboratory in an interactive virtual learning environment. This research measures the difference in task performance between i) students exposed to an immersive virtual reality system and ii) students exposed to a non-immersive virtual reality system, in the interactive virtual environment developed by the research team. This research seeks to explore whether statistically significant differences in performance exist between these groups. Knowledge gained from testing this hypothesis will inform educators about the value and impact of immersive virtual reality technologies in enhancing online education. A case study involving 54 students in a product functional analysis task is used to test the hypothesis.
Optimization of Additively Manufactured Multi-Material Lattice Structures Using Generalized Optimality Criteria
Authors: Stankovic Tino , Mueller Jochen , Egan Paul , Shea Kristina
Published: January 2016

Recent progress in additive manufacturing allows for printing customized products with multiple materials and complex geometries. Effectively designing such complex products for optimal performance within the confines of additive manufacturing constraints is challenging, due to the large number of variables in the search space and uncertainties about how the manufacturing processes affect fabricated materials and structures. In this study, characteristics of materials, i.e. Young’s modulus (E), ultimate tensile strength (UTS) and density (ρ), for a multi-material inkjet-based 3D-printer are measured experimentally in order to generate data curves for a computational optimization process in configuring multimaterial lattice structures. An optimality criteria method is developed for computationally searching for optimal solutions of a multi-material lattice with fixed topology and truss cross-section sizes using the empirically obtained material measurements. Results demonstrate the feasibility of the approach for optimizing multi-material, lightweight truss structures subject to displacement constraints.
Risk-Based Path Planning Optimization Methods for UAVs Over Inhabited Areas
Authors: Rudnick-Cohen Eliot , Herrmann Jeffrey W. , Azarm Shapour
Published: January 2016

Operating unmanned aerial vehicles (UAVs) over inhabited areas requires mitigating the risk to persons on the ground. Because the risk depends upon the flight path, UAV operators need approaches (techniques) that can find low-risk flight paths between the mission’s start and finish points. In some areas, the flight paths with the lowest risk are excessively long and indirect because the least-populated areas are too remote. Thus, UAV operators are concerned about the tradeoff between risk and flight time. Although there exist approaches for assessing the risks associated with UAV operations, existing risk-based path planning approaches have considered other risk measures (besides the risk to persons on the ground) or simplified the risk assessment calculation. This paper presents a risk assessment technique and bi-objective optimization methods to find low-risk and time (flight path) solutions and computational experiments to evaluate the relative performance of the methods (their computation time and solution quality). The methods were a network optimization approach that constructed a graph for the problem and used that to generate initial solutions that were then improved by a local approach and a greedy approach and a fourth method that did not use the network solutions. The approaches that improved the solutions generated by the network optimization step performed better than the optimization approach that did not use the network solutions.
The Can Crusher Project: A Multi-Semester Design Project to Enhance Retention of Engineering Skill Sets
Authors: Sullivan Gerald A. , Hardin Jon-Michael
Published: January 2016

This paper describes a three semester long project which promotes the development and retention of engineering skill-sets by involving students in the design and fabrication of a can-crushing device. The can-crusher project was inspired by spiral learning theory and provides opportunities for students to practice engineering skill sets, including CAD, programming, machining and working with practical electronics. The paper details the implementation of the project and shows how the project addresses skill-set deficits that can occur in conventional curricula. Finally, modifications to the content/organization of the can-crusher project are proposed based on the experiences of the first group of students to complete the three semester sequence.
The Dynamics of DNA Supercoiling: A Brownian Dynamics Study
Authors: Ikenna Ivenso , Lillian Todd D.
Published: January 2016

Induced torsional stresses lead to an increase in the magnitude of torque sustained by double stranded DNA. There exists a critical magnitude of torque at which the DNA buckles signaling the beginning of the formation of a plectonemically supercoiled domain in the DNA. Further torsional deformation leads to an increase in the size of the supercoiled domain while the torque sustained by the DNA remains constant. The formation of the supercoiled domain also leads to a reduction in the end-to-end extension of the DNA starting with an abrupt reduction at the onset of buckling. Experiments have shown that this reduction in extension follows a linear trend. We investigate, by means of Brownian dynamics simulations, the extensional and torsional response of dsDNA to induced torsional stresses.
Experimental Validation of the Kinematics of a 3PRS Compliant Mechanism for Micromilling
Authors: Ruiz Antonio , Campa Gomez Francisco , Roldan-Paraponiaris Constantino , Altuzarra Oscar
Published: January 2016

The present work deals with the development of a hybrid manipulator of 5 degrees of freedom for milling moulds for microlenses. The manipulator is based on a XY stage under a 3PRS compliant parallel mechanism. The mechanism takes advantage of the compliant joints to achieve higher repetitiveness, smoother motion and a higher bandwidth, due to the high precision demanded from the process, under 0.1 micrometers. This work is focused on the kinematics of the compliant stage of the hybrid manipulator. First, an analysis of the workspace required for the milling of a single mould has been performed, calculating the displacements required in X, Y, Z axis as well as two relative rotations between the tool and the workpiece from a programmed toolpath. Then, the 3PRS compliant parallel mechanism has been designed using FEM with the objective of being stiff enough to support the cutting forces from the micromilling, but flexible enough in the revolution and spherical compliant joints to provide the displacements needed. Finally, a prototype of the 3PRS compliant mechanism has been built, implementing a motion controller to perform translations in Z direction and two rotations. The resulting displacements in the end effector and the actuated joints have been measured and compared with the FEM calculations and with the rigid body kinematics of the 3PRS.
Design Integration Into Circuits and Mechatronics Courses
Authors: Nagel Jacquelyn K. S. , Holland S. Keith
Published: January 2016

Lab exercises have traditionally been a time when students follow a given procedure, collect data, and interpret the data. The highly structured experience often leads to students focusing on the procedure and not fully thinking through the concepts being covered. While labs are fully completed each week, the structured approach does not prepare students for the open-ended, non-procedural work entry-level engineers will encounter in industry. To encourage a deeper understanding of course concepts and how they translate to physical systems and better prepare students for the workforce, open-ended design projects were offered in place of structured labs in the circuits and mechatronics courses at James Madison University.

The design projects are undirected experiences that build on the directed experiences in lecture and lab. Students are challenged to work in teams to design, build, test, and in one case, calibrate, an electrical system. No instruction is provided for the project, rather, a set of design requirements, timetable, and supplemental materials (e.g., data sheets, vendor design briefs, past labs relevant to the design requirements) are given. Students must synthesize multiple weeks of course content into a single design project. This paper reports on our observations and student feedback for embedding design experiences in engineering science courses.