Integrating the Use of Commercial Simulators into Lecture Courses

Since commercial simulators are commonly used in the practice of engineering, we need to ensure they are included in engineering education. Computer laboratory sections were added to a “lecture” course to teach the use of a simulator and to give the students practice in solving realistic problems. By thinking about the computer lab as a problem‐based learning environment, minimal lecture time was necessary to train the students on the simulator. Examples of instructions, problem statements and results from a student survey are presented.     

基于“转移”概念的VR交互策略研究

目的当下,VR内容的质量成为限制VR发展瓶颈,对影响内容质量的交互设计问题进行研究分析,探讨如何解决VR内容交互中的疲劳问题,帮助用户更好地进行交互,提升内容质量。方法以总结VR交互的特征为出发点,通过案例研究的方式探索特征与疲劳问题的关系,基于"转移"的概念对解决疲劳问题的方法进行归纳,提炼出解决疲劳问题的设计策略。结合案例研究,通过演绎推理对设计策略进行价值验证。结论在VR交互中,以身体整体进行交互的特征激化了因用户生理限制存在的问题,过度追求自然的交互方式导致疲劳问题的出现,影响着用户在VR中的体验质量。基于"转移"概念提出的交互设计策略能够有效缓解疲劳。灵活应用以身体或心理进行转移行为的交互设计策略,可以将疲劳控制在可接受的程度,借此消除疲劳,进而降低消极情感的产生概率,提高用户在VR体验过程中的体验质量。     

Applying James Stice's Strategy to Teach Design to Sophomore Mechanical Engineering Undergraduates

The James Stice strategies for teaching problem‐solving and improving student learning have been adopted in the development of a sophomore‐level “Materials, Manufacturing & Design” course. The curriculum, the assessment method, and the results of student evaluation over a three‐year period are described. Correlation between assessments by two faculty members (in the form of design project written‐report and oral‐presentation grades) and students self‐assessment (in the form of a retrospective survey employing a Likert‐type scale and student written comments) show that the Stice strategies are successful in teaching engineering design to sophomores.     

A Cognitive Study of Problem Solving in Statics

Background Even as expectations for engineers continue to evolve to meet global challenges, analytical problem solving remains a central skill. Thus, improving students' analytical problem solving skills remains an important goal in engineering education. This study involves observation of students as they execute the initial steps of an engineering problem solving process in statics. Purpose (Hypothesis ) (1) What knowledge elements do statics students have the greatest difficulty applying during problem solving? (2) Are there differences in the knowledge elements that are accurately applied by strong and weak statics students? (3) Are there differences in the cognitive and metacognitive strategies used by strong and weak statics students during analysis? Design /Method These questions were addressed using think‐aloud sessions during which students solved typical textbook problems. We selected the work of twelve students for detailed analysis, six weak and six strong problem solvers, using an extreme groups split based on scores on the think‐aloud problems and a course exam score. The think‐aloud data from the two sets of students were analyzed to identify common technical errors and also major differences in the problem solving processes. Conclusions We found that the weak, and most of the strong problem solvers relied heavily on memory to decide what reactions were present at a given connection, and few of the students could reason physically about what reactions should be present. Furthermore, the cognitive analysis of the students' problems solving processes revealed substantial differences in the use of self‐explanation by weak and strong students.     

An approach to multi‐start clustering for global optimization with non‐linear constraints

This paper describes a multi‐start with clustering strategy for use on constrained optimization problems. It is based on the characteristics of non‐linear constrained global optimization problems and extends a strategy previously tested on unconstrained problems. Earlier studies of multi‐start with clustering found in the literature have focused on unconstrained problems with little attention to non‐linear constrained problems. In this study, variations of multi‐start with clustering are considered including a simulated annealing or random search procedure for sampling the design domain and a quadratic programming (QP) sub‐problem used in cluster formation. The strategies are evaluated by solving 18 non‐linear mathematical problems and six engineering design problems. Numerical results show that the solution of a one‐step QP sub‐problem helps predict possible regions of attraction of local minima and can enhance robustness and effectiveness in identifying local minima without sacrificing efficiency. In comparison to other multi‐start techniques found in the literature, the strategies of this study can be attractive in terms of the number of local searches performed, the number of minima found, whether the global minimum is located, and the number of the function evaluations required. Copyright © 2002 John Wiley & Sons, Ltd.     

Inexact Schwarz‐algebraic multigrid preconditioners for crack problems modeled by extended finite element methods

Traditional algebraic multigrid (AMG) preconditioners are not well suited for crack problems modeled by extended finite element methods (XFEM). This is mainly because of the unique XFEM formulations, which embed discontinuous fields in the linear system by addition of special degrees of freedom. These degrees of freedom are not properly handled by the AMG coarsening process and lead to slow convergence. In this paper, we proposed a simple domain decomposition approach that retains the AMG advantages on well‐behaved domains by avoiding the coarsening of enriched degrees of freedom. The idea was to employ a multiplicative Schwarz preconditioner where the physical domain was partitioned into “healthy” (or unfractured) and “cracked” subdomains. First, the “healthy” subdomain containing only standard degrees of freedom, was solved approximately by one AMG V‐cycle, followed by concurrent direct solves of “cracked” subdomains. This strategy alleviated the need to redesign special AMG coarsening strategies that can handle XFEM discretizations. Numerical examples on various crack problems clearly illustrated the superior performance of this approach over a brute force AMG preconditioner applied to the linear system. Copyright © 2011 John Wiley & Sons, Ltd.     

Teaching engineering design: Can reading a textbook make a difference?

Teaching design is an integral part of most engineering curricula. Often, students are introduced to the engineering design process through a chapter in a textbook. Does this passive approach to teaching an active process aid the students' learning? An experiment was conducted to assess what students learn about the design process when they read a text. Here, 10 students enrolled in a freshman course were asked to read aloud from a freshmen engineering textbook. Half of the subjects read the text prior to solving three open-ended engineering design problems and the other half solved the same problems before they read the text. Both the subjects' process in solving the problems, as well as the quality of their solutions (the product), are assessed. Results show that subjects that read the text before they solved the three problems spent significantly more time solving the problems and were more sophisticated in their problem solving strategies. These subjects also scored better when judged on the quality of their approach to the problem (including the number of design criteria considered, communications, assumptions, and technical accuracy). However, these subjects did not score better on a quality measure of the final solution.     

Use of genetic algorithms to solve production and operations management problems: A review

Operations managers and scholars in their search for fast and good solutions to real-world problems have applied genetic algorithms to many problems. While genetic algorithms are promising tools for problem solving, future research will benefit from a review of the problems that have been solved and the designs of the genetic algorithms used to solve them. This paper provides a review of the use of genetic algorithms to solve operations problems. Reviewed papers are classified according to the problems they solve. The basic design of each genetic algorithm is described, the shortcomings of the current research are discussed and directions for future research are suggested.     

关键策略的物元模型

关键策略是为解决关键问题而制定的，在决定过程中具有“牵一发而动全身”的作用。因此，如何生成关键策略是科学决策的核心问题之一，它的形式化研究对于提高决策的可操作性具有重要价值。本文利用可拓方法，建立了关键问题和关键策略的形式化概念，分析了关键策略的性质，提出了关键策略的生成步骤。     

Basic Engineering Software for Teaching (“BEST”) Dynamics

Engineering dynamics is the study of motion, but textbooks and chalkboards, the traditional classroom teaching tools, cannot show that motion. Mechanical models are helpful, but relatively inflexible; they are qualitative, not quantitative. Since July 1992, personnel from the University of Missouri-Rolla have been developing and classroom testing “BEST”* (Basic Engineering Software for Teaching) Dynamics with the goal of improving the teaching and learning of engineering dynamics. About forty-five different problem simulations, representing a selection of typical kinematics and kinetics problems for both particles and rigid bodies, have been completed. These problems enable the user to vary inputs to view a wide variety of configurations and behavior. Students using “BEST” Dynamics have reported improved ability to visualize motion, and somewhat improved problem solving ability. Recent work has focused on adding, to some of the problems, “Solutions” which give detailed support in writing and solving equations. This paper will introduce the reader to “BEST” Dynamics and its classroom use. It will also provide some philosophical commentary on the applicability of instructional software to the problem-solving-oriented engineering classroom.     

Efficient and accurate waveguide mode computation using BI‐RME and Lanczos methods

In this paper, a special purpose algorithm for solving large eigenvalue problems based on the Lanczos method is successfully applied to an engineering problem: the electromagnetic analysis and design of passive waveguide devices. For dealing with such complex problems, the boundary integral‐resonant mode expansion (BI‐RME) technique has been recently proposed. This technique solves integral equations (IEs) through the well‐known method of moments (MoM), thus leading to structured eigenvalue problems. These problems frequently become very large when solving complex arbitrary geometries with high accuracy. In such cases, the eigenvalue problem cannot be efficiently solved with standard methods by means of personal computers, essentially due to CPU time and memory allocation requirements. In this paper, we propose an alternative technique, based on the Lanczos method, for the fast and accurate solution of large BI‐RME generalized eigenvalue problems. The novel theoretical aspects of this approach, as well as the impacton the original BI‐RME formulation, are described. Comparative benchmarks are also successfully presented for the full‐wave analysis and design of real passive microwave devices. Copyright © 2005 John Wiley Sons, Ltd.     

Analysing optimum push/pull junction point location using multiple criteria decision‐making for multistage stochastic production system

This research focuses on solving the multistage process push/pull junction point location problem. An aim is to implement a hybrid push/pull production system that can satisfy both high service‐levels and low inventory levels. Simultaneously, we consider sophisticated variability, such as multi‐products, random setup, indiscriminate break‐downs, yield loss, batch processes, and other contingencies. The problem can be solved by a multiple criteria decision‐making (MCDM) method. A technique for order‐preference by similarity‐to‐ideal solution (TOPSIS) is used to select a suitable option. The optimisation involves evaluation of stochastic performance measures within alternative scenarios among candidate junction‐point locations using a discrete event simulation model. A practical thin film transistor‐liquid crystal display (TFT‐LCD) process case‐study is utilised to illustrate the proposed method. After implementing a hybrid push/pull production strategy, simulation results indicate that the inventory level was reduced by over 18% while the service level remained about the same. For another scenario, a 3.4% decrease in service‐level can be paid off by a 46% decrease in inventory level and 34% improvement in lead time.     

The Horizon of the Emulsion Particulate Strategy: Engineering Hollow Particles for Biomedical Applications

With their hierarchical structures and the substantial surface areas, hollow particles have gained immense research interest in biomedical applications. For scalable fabrications, emulsion‐based approaches have emerged as facile and versatile strategies. Here, the recent achievements in this field are unfolded via an “emulsion particulate strategy,” which addresses the inherent relationship between the process control and the bioactive structures. As such, the interior architectures are manipulated by harnessing the intermediate state during the emulsion revolution (intrinsic strategy), whereas the external structures are dictated by tailoring the building blocks and solidification procedures of the Pickering emulsion (extrinsic strategy). Through integration of the intrinsic and extrinsic emulsion particulate strategy, multifunctional hollow particles demonstrate marked momentum for label‐free multiplex detections, stimuli‐responsive therapies, and stem cell therapies.     

Functional Enzyme Mimics for Oxidative Halogenation Reactions that Combat Biofilm Formation

Transition‐metal oxide nanoparticles and molecular coordination compounds are highlighted as functional mimics of halogenating enzymes. These enzymes are involved in halometabolite biosynthesis. Their activity is based upon the formation of hypohalous acids from halides and hydrogen peroxide or oxygen, which form bioactive secondary metabolites of microbial origin with strong antibacterial and antifungal activities in follow‐up reactions. Therefore, enzyme mimics and halogenating enzymes may be valuable tools to combat biofilm formation. Here, halogenating enzyme models are briefly described, enzyme mimics are classified according to their catalytic functions, and current knowledge about the settlement chemistry and adhesion of fouling organisms is summarized. Enzyme mimics with the highest potential are showcased. They may find application in antifouling coatings, indoor and outdoor paints, polymer membranes for water desalination, or in aquacultures, but also on surfaces for food packaging, door handles, hand rails, push buttons, keyboards, and other elements made of plastic where biofilms are present. The use of natural compounds, formed in situ with nontoxic and abundant metal oxide enzyme mimics, represents a novel and efficient “green” strategy to emulate and utilize a natural defense system for preventing bacterial colonization and biofilm growth.     

Developing Problem Solving Skills: The McMaster Problem Solving Program

This paper describes a 25-year project in which we defined problem solving, identified effective methods for developing students' skill in problem solving, implemented a series of four required courses to develop the skill, and evaluated the effectiveness of the program. Four research projects are summarized in which we identified which teaching methods failed to develop problem solving skill and which methods were successful in developing the skills. We found that students need both comprehension of Chemical Engineering and what we call general problem solving skill to solve problems successfully. We identified 37 general problem solving skills. We use 120 hours of workshops spread over four required courses to develop the skills. Each skill is built (using content-independent activities), bridged (to apply the skill in the content-specific domain of Chemical Engineering) and extended (to use the skill in other contexts and contents and in everyday life). The tests and examinations of process skills, TEPS, that assess the degree to which the students can apply the skills are described. We illustrate how self-assessment was used.     

Engaging and Supporting Problem Solving in Engineering Ethics

Learning to solve ethical problems is essential to the education of all engineers. Engineering ethics problems are complex and ill structured with multiple perspectives and interpretations to address in their solution. In two experiments, we examined alternative strategies for engaging ethical problem solving. In Experiment 1, students studied two versions of an online learning environment consisting of everyday ethics problems. Students using question hypertext links to navigate applied more perspectives and canons and wrote stronger overall solutions to ethics problems than those using embedded hypertext links. In Experiment 2, students engaged in a more generative task, evaluating alternative arguments for solutions to the cases or generating and supporting their own solutions. Both groups better supported their solutions and generated more counterclaims than control students. These studies focused on solving realistic case‐based ethics problems as an effective method for addressing ABET's ethics criteria.     

Job shop scheduling with a non-regular objective: A comparison of neighbourhood structures based on a sequencing/timing decomposition

Commercial software packages for production management are characterized by a gap between MRP logic, based on a backward scheduling approach, and finite capacity scheduling, usually based on forward scheduling. In order to partially bridge that gap, we need scheduling algorithms able to meet due dates while keeping WIP and inventory costs low. This leads us to consider job shop scheduling problems characterized by non-regular objective functions; such problems are even more difficult than classical job shop scheduling, and suitable heuristics are needed. One possibility is to consider local search strategies based on the decomposition of the overall problem into sequencing and timing sub-problems. For given job sequences, the optimal timing problem can be solved as a node potential problem on a graph. Since solving the timing problem is a relatively time-consuming task, we need to define a suitable neighbourhood structure to explore the space of job sequences; this can be done by generalizing well-known results for the minimum makespan problem. A related issue is if solving timing problems exactly is really necessary, or if an approximate solution is sufficient; hence, we also consider solving the timing problem approximately by a fast heuristic. We compare different neighbourhood structures, by embedding them within a pure local improvement strategy. Computational experiments show that the overall approach performs better than release/dispatch rules, although the performance improvement depends on the problem characteristics, and that the fast heuristic is quite competitive with the optimal timing approach. On the one hand, these results pave the way to the development of better local search algorithms (based e.g. on tabu search); on the other hand, it is worth noting that the heuristic timing approach, unlike the optimal one, can be extended to cope with the complicating features typical of practical scheduling problems.     

Velocity‐based formulations for standard and quasi‐incompressible hypoelastic‐plastic solids

We present three velocity‐based updated Lagrangian formulations for standard and quasi‐incompressible hypoelastic‐plastic solids. Three low‐order finite elements are derived and tested for non‐linear solid mechanics problems. The so‐called V‐element is based on a standard velocity approach, while a mixed velocity–pressure formulation is used for the VP and the VPS elements. The two‐field problem is solved via a two‐step Gauss–Seidel partitioned iterative scheme. First, the momentum equations are solved in terms of velocity increments, as for the V‐element. Then, the constitutive relation for the pressure is solved using the updated velocities obtained at the previous step. For the VPS‐element, the formulation is stabilized using the finite calculus method in order to solve problems involving quasi‐incompressible materials. All the solid elements are validated by solving two‐dimensional and three‐dimensional benchmark problems in statics as in dynamics. Copyright © 2016 John Wiley & Sons, Ltd.     

Development of a Work Sampling Methodology for Behavioral Observations: Application to Teamwork

Engineering programs must assess students' abilities to master “criteria 3 a‐k.” Skills such as teamwork, problem solving, design, and ethical understanding entail learning various processes; hence, assessing these outcomes is better accomplished by focusing on the process rather than the result. Methods for observing students' performance, such as 100 percent behavioral observation, are ideal but expensive. We extend work sampling, an economic industry‐based alternative, to observe cognitive and behavioral processes. Specifically, we describe a work sampling methodology to assess students engaged in teamwork. We then determine attributes of teamwork, establish target time proportions using 100 percent observation, and statistically compare the targets to proportions obtained from work sampling intervals to determine the effective interval. The robustness of work sampling is tested in four learning environments. Results indicate that sampling provides a statistically valid alternative for assessing teamwork. However, when observing design and ethical understanding processes, additional research is needed to make work sampling viable.     

Microfluidic‐Based Approaches in Targeted Cell/Particle Separation Based on Physical Properties: Fundamentals and Applications

Cell separation is a key step in many biomedical research areas including biotechnology, cancer research, regenerative medicine, and drug discovery. While conventional cell sorting approaches have led to high‐efficiency sorting by exploiting the cell's specific properties, microfluidics has shown great promise in cell separation by exploiting different physical principles and using different properties of the cells. In particular, label‐free cell separation techniques are highly recommended to minimize cell damage and avoid costly and labor‐intensive steps of labeling molecular signatures of cells. In general, microfluidic‐based cell sorting approaches can separate cells using “intrinsic” (e.g., fluid dynamic forces) versus “extrinsic” external forces (e.g., magnetic, electric field, etc.) and by using different properties of cells including size, density, deformability, shape, as well as electrical, magnetic, and compressibility/acoustic properties to select target cells from a heterogeneous cell population. In this work, principles and applications of the most commonly used label‐free microfluidic‐based cell separation methods are described. In particular, applications of microfluidic methods for the separation of circulating tumor cells, blood cells, immune cells, stem cells, and other biological cells are summarized. Computational approaches complementing such microfluidic methods are also explained. Finally, challenges and perspectives to further develop microfluidic‐based cell separation methods are discussed.