bluuebunny/crossref_metadata_2025 huggingface dataset:
Monitoring Method for Laser Via Hole Processing of Printed Circuit Boards Based on Two-Color Method With a High-Speed Video Camera
Authors: Nakagawa Wataru , Yamaguchi Ryuta , Hirogaki Toshiki , Aoyama Eiichi
Published: November 2020

A build-up process is used to manufacture printed wiring boards (PWBs) for high-density circuits. Presently, CO2 laser beams are used to drill blind via holes (BVHs) that connect copper foils. The Cu-direct drilling process has received considerable attention but is problematic because it produces a copper overhang due to the complex processing phenomena. This report focuses on monitoring scattered matter by Cu-direct laser drilling with a high-speed camera and clarifying the factors related to processing quality while verifying the results by CFD (Computational Fluid Dinamics) analysis. Previous research has shown that processing progress can be made from temperature information using the two-color image method that can measure temperature without contact. However, the two-color image method generates noise in the temperature range (500–3000 °C) which is treated in this research. Filtering was possible by using the RGB data of each pixel on the image. By focusing on laser fluence, it became possible to estimate the laser irradiation time that can guarantee the quality in the drilled hole (BVH) in single pulse continuous irradiation.
The Stakeholder Agreement Metric (SAM): Quantifying Preference Agreement Between Product Stakeholders
Authors: Chou Suzanne , Arezoomand Mojtaba , Coulentianos Marianna J. , Nambunmee Kowit , Neitzel Richard , Adhvaryu Achyuta , Austin-Breneman Jesse
Published: November 2020

Go/no-go decisions require engineering design teams to evaluate whether a concept is worth further investment of resources. These decisions can be difficult when product success depends on multiple stakeholders in addition to the end-user. This study proposes the Stakeholder Agreement Metric (SAM) framework to estimate the level of agreement between stakeholder preferences via the distance between optimal designs calculated from a preference model derived from conjoint analysis. The framework was compared to the analytical hierarchy process (AHP) in an empirical case study describing the design and piloting of a hand tool for informal electronic waste workers in Thailand. Data from a follow-up assessment indicate the SAM estimate aligned with future metrics of stakeholder satisfaction. The study further demonstrated AHP may have practical limitations due to survey requirements. This study suggests that the SAM framework is a promising tool to further explore as a way to support designers making go/no-go decisions which involve multiple stakeholders.
Electromechanical Diode: Acoustic Non-Reciprocity in Weakly Nonlinear Metamaterial With Electromechanical Resonators
Authors: Bukhari Mohammad A. , Barry Oumar R.
Published: November 2020

Recent attention has been given to acoustic non-reciprocity in metamaterials with nonlinearity. However, the study of asymmetric cells has been limited to mechanical diodes only. There is no work reported on electromechanical rectifiers or diodes. This problem is investigated here by analytically and numerically studying a combination of nonlinear and linear chains coupled with electromechanical resonators. The system is simulated numerically using MATLAB built in integrator and the results are validated by results found in the literature. Numerical examples are carried out to obtain band structure, operation range of electromechanical diode, harvested power, and significant frequency shift, which is demonstrated using spectro-spatial analyses. The observed frequency shift is used to construct an electromechanical diode to guide the wave to propagate in one direction only. This only allows signal sensing for waves propagating in one direction and rejects any other signals. Furthermore, this electromechanical diode is evaluated by calculating the transmission ratio and the asymmetric ratio for a transient input signal.
Stochastic Stackelberg Games for Agent-Driven Robust Design
Authors: Rismiller Sean C. , Cagan Jonathan , McComb Christopher
Published: November 2020

Products must often endure unpredictable and challenging conditions while fulfilling their intended functions. Game-theoretic methods make it possible for designers to design solutions that are robust against complicated conditions, however, these methods are often specific to the problems they investigate. This work introduces the Game-Augmented Robust Simulated Annealing Teams (GARSAT) framework, a game-theoretic agent-based architecture that generates solutions robust to variation, and models problems with elementary information, making it easily extendable. The platform was used to generate designs under consideration of a multidimensional attack. Designs were produced under various adversarial settings and compared to designs generated without considering adversaries to validate the model. The process successfully created robust designs able to withstand multiple combined conditions, and the effects of the adversarial settings on the designs were explored.
An Efficient Multi-Objective Robust Optimization Method by Sequentially Searching From Nominal Pareto Solutions
Authors: Xia Tingting , Li Mian
Published: November 2020

Multi-objective optimization problems (MOOPs) with uncertainties are common in engineering design problems. To find the robust Pareto fronts, multi-objective robust optimization methods with inner-outer optimization structures generally have high computational complexity, which is always an important issue to address. Based on the general experience, robust Pareto solutions usually lie somewhere near the nominal Pareto points. Starting from the obtained nominal Pareto points, the search process for robust solutions could be more efficient. In this paper, we propose a method that sequentially approaching to the robust Pareto front (SARPF) from the nominal Pareto points. MOOPs are solved by the SARPF in two optimization stages. The deterministic optimization problem and the robustness metric optimization problem are solved in the first stage, and nominal Pareto solutions and the robust-most solutions can be found respectively. In the second stage, a new single-objective robust optimization problem is formulated to find the robust Pareto solutions starting from the nominal Pareto points in the region between the nominal Pareto front and the robust-most points. The proposed SARPF method can save a significant amount of computation time since the optimization process can be performed in parallel at each stage. Vertex estimation is also applied to approximate the worst-case uncertain parameter values which can save computational efforts further. The global solvers, NSGA-II for the multi-objective case and genetic algorithm (GA) for the single-objective case, are used in corresponding optimization processes. Two examples with comparison to a previous method are presented for the applicability and efficiency demonstration.
Two-Phase Thermal Metamaterial
Authors: Xu Zifu , Li Longqiu , Li Jiaxin
Published: November 2020

The capability of thermal metamaterials is required from single function to multifunction under different external heat conditions. The methods to develop thermal materials by simple structural transformations have been explored. While, the components of traditional thermal metamaterial are mainly set as solid materials, which is difficult to change the composition of materials, such as recombing and fixing the spatial position of material, because of material rigidity. Therefore, the potential of thermal materials is limited. Liquid has fluidity in spatial structure, for which the efficient combination of solid-liquid materials provides an avenue for dynamically modeling thermal field.

Herein, we propose the concept of two-phase thermal metamaterial, which is switchable by microscale elements. On one side, we develop a switchable thermal meta-unit manipulated by micro-element under the gradient field and explore the process of heat transfer by focusing on radiation and conduction under translucent media condition. Otherwise, we propose a method to achieve a non-reciprocal heat transfer system by the design of two-phase media. The propose of two-phase thermal metamaterials set a general background for a variety of applications for complex conditions.
Design of a Quadratic, Antagonistic, Cable-Driven, Variable Stiffness Actuator
Authors: Moore Ryan , Schimmels Joseph M.
Published: November 2020

Antagonistically actuated Variable Stiffness Actuators (VSAs) take inspiration from biological muscle structures to control both the stiffness and positioning of a joint. The design presented utilizes a cable running through a set of three pulleys, to displace a linear spring, yielding quadratic spring behavior. A quasi-static model of the mechanism is used to assess and optimize the force-displacement behavior. The mechanism prototype yielded a good match to the desired elastic behavior.
Mission Mobility Reliability Analysis of Off-Road Ground Vehicles
Authors: Liu Yixuan , Jiang Chen , Hu Zhen , Mourelatos Zissimos P. , Fu Yan , Gorsich David , Jayakumar Paramsothy , Majcher Monica
Published: November 2020

The NATO Reference Mobility Model (NRMM) has been developed to predict the mobility of off-road ground vehicles based on modeling and simulation (M&S). Due to various uncertainty sources in the M&S, uncertainty is inherent in the vehicle mobility. Aims to account for the uncertainty in the mobility prediction in mission planning, this paper develops a simulation-based mission mobility reliability analysis framework for off-road ground vehicles. A concept of mission mobility reliability (MMR) is first proposed to quantify the reliability of a mission path which passes through different types of soils. A single-loop Kriging surrogate modeling method is then employed to overcome the challenge in the mission mobility reliability assessment caused by the computationally expensive mobility simulation. Built upon the surrogate model-based mission mobility reliability analysis, a dynamic updating scheme is proposed to update the MMR estimation based on the on-line mobility data, during the course of a specific mission and for a particular vehicle. The online dynamic updating of MMR allows for effective and dynamic decision making during the mission phase. A case study is used to demonstrate the effectiveness of the proposed MMR analysis and updating framework.
Lineup Design Method for Intermediate Product Family by Monotonicity-Guided Optimization of Nested Mini-Max Problem
Authors: Fujita Kikuo , Ono Naoki , Mitsuhashi Yui , Nomaguchi Yutaka
Published: November 2020

As a product has become complicated, and its requirements have been diversified, the simultaneous and integrative design of a series of products has become so important. However, the contents of design activities have become complex across product variety and supply chain. This paper views such a situation through a chain of parts, intermediate products, and final products, and focuses on the lineup design problem of an intermediate product. The lineup design means here to secure the worst-case performance of intermediate products across a range of specifications. The problem is formulated as a mathematical problem to maximize the worst-case efficiency, i.e., the minimum efficiency of products across the range by arranging commonalization strategy, segmentation of the range, and original design variables. This paper proposes a two-phase approach, designing a framework, and optimizing contents under the framework. The latter phase is formulated as a nested mini-max optimization problem. An effective and efficient optimization scheme is configured with employing monotonicity analysis. Finally, an application to universal motors is demonstrated for ascertaining the validity and promises of the proposed design method.
Lyapunov Perron Transformation for Linear Quasi-Periodic Systems
Authors: Subramanian Susheelkumar C. , Redkar Sangram , Waswa Peter
Published: November 2020

It is known that a Lyapunov Perron (L-P) transformation converts a quasi-periodic system into a reduced system with a time-invariant coefficient. Though a closed form expression for L-P transformation matrix is missing in the literature, the application of combination of multiple theories would aid in such transformation. In this work, the authors have worked on extending the Floquet theory to find L-P transformation. As an example, a commutative system with linear quasi-periodic coefficients is transformed into a system with time-invariant coefficient analytically. Furthermore, for non-commutative systems, similar results are obtained in this work, with the help of an intuitive state augmentation and Normal Forms technique. The results of the reduced system are compared with the numerical integration technique for validation.
Symbolic Computation of Inverse Kinematics for General 6R Manipulators Based on Raghavan and Roth’s Solution
Authors: Arikawa Keisuke
Published: November 2020

We discuss the symbolic computation of inverse kinematics for serial 6R manipulators with arbitrary geometries (general 6R manipulators) based on Raghavan and Roth’s solution. The elements of the matrices required in the solution were symbolically calculated. In the symbolic computation, an algorithm for simplifying polynomials upon considering the symbolic constraints (constraints of the trigonometric functions and those of the rotation matrix), a method for symbolic elimination of the joint variables, and an efficient computation of the rational polynomials are presented. The elements of the matrix whose determinant produces a 16th-order single variable polynomial (characteristic polynomial) were symbolically calculated by using structural parameters (parameters that define the geometry of the manipulator) and hand configuration parameters (parameters that define the hand configuration). The symbolic determinant of the matrix consists of huge number of terms even when each element is replaced by a single symbol. Instead of expressing the coefficients in a characteristic polynomial by structural parameters and hand configuration parameters, we substituted appropriate rational numbers that strictly satisfy the constraints of the symbols for the elements of the matrix and calculated the determinant (numerical error free calculation). By numerically calculating the real roots of the rational characteristic polynomial and the joint angles for each root, we verified the formulation for the symbolic computation.
Human Inductive Biases in Design Decision Making
Authors: Shergadwala Murtuza N. , Panchal Jitesh H.
Published: November 2020

Designers make information acquisition decisions, such as where to search and when to stop the search. Such decisions are typically made sequentially, such that at every search step designers gain information by learning about the design space. However, when designers begin acquiring information, their decisions are primarily based on their prior knowledge. Prior knowledge influences the initial set of assumptions that designers use to learn about the design space. These assumptions are collectively termed as inductive biases. Identifying such biases can help us better understand how designers use their prior knowledge to solve problems in the light of uncertainty. Thus, in this study, we identify inductive biases in humans in sequential information acquisition tasks. To do so, we analyze experimental data from a set of behavioral experiments conducted in the past [1–5]. All of these experiments were designed to study various factors that influence sequential information acquisition behaviors. Across these studies, we identify similar decision making behaviors in the participants in their very first decision to “choose x”. We find that their choices of “x” are not uniformly distributed in the design space. Since such experiments are abstractions of real design scenarios, it implies that further contextualization of such experiments would only increase the influence of these biases. Thus, we highlight the need to study the influence of such biases to better understand designer behaviors. We conclude that in the context of Bayesian modeling of designers’ behaviors, utilizing the identified inductive biases would enable us to better model designer’s priors for design search contexts as compared to using non-informative priors.
Experimental Forced Response Analysis of Two-Degree-of-Freedom Piecewise-Linear Systems With a Gap
Authors: Saito Akira , Umemoto Junta , Noguchi Kohei , Tien Meng-Hsuan , D’Souza Kiran
Published: November 2020

In this paper, an experimental forced response analysis for a two degree of freedom piecewise-linear oscillator is discussed. First, a mathematical model of the piecewise linear oscillator is presented. Second, the experimental setup developed for the forced response study is presented. The experimental setup is capable of investigating a two degree of freedom piecewise linear oscillator model. The piecewise linearity is achieved by attaching mechanical stops between two masses that move along common shafts. Forced response tests have been conducted, and the results are presented. Discussion of characteristics of the oscillators are provided based on frequency response, spectrogram, time histories, phase portraits, and Poincaré sections. Period doubling bifurcation has been observed when the excitation frequency changes from a frequency with multiple contacts between the masses to a frequency with single contact between the masses occurs.
Architecture Selection for Hybrid Electric Mobility As a Service Vehicle
Authors: Schaich Noah , Free Christian , Nekoo Nishan , Leamy Michael J.
Published: November 2020

This paper documents the vehicle modeling and fuel economy simulation efforts for the Georgia Tech EcoCAR Mobility Challenge team during Year 1 of the current Advanced Vehicle Technology Competition (AVTC). The goal of the first year of the competition was to propose two possible hybrid electric vehicle (HEV) architectures based on a 2019 Chevrolet Blazer platform that could be built and refined throughout Years 2–4 of the competition. A Simulink vehicle model was used to compare a variety of HEV architectures with several different combinations of engines, batteries, and electric machines. An adaptive Equivalent Consumption Minimization Strategy was used to split torque between the internal combustion engine and two electric machines so that architectures with two electric machines could be modeled. The model was validating by comparing results from simulating a conventional Chevrolet Blazer with the 2.5L naturally aspirated engine to fuel economy results obtained by the Environmental Protection Agency (EPA). In addition to developing a hybrid vehicle, the competition is focused on exploring Mobility as a Service (MaaS), which introduces some special considerations when choosing a hybrid vehicle architecture. The results of the Simulink model as well as requirements set by the MaaS market led the Georgia Tech EcoCAR team to pursue a dual electric machine P0P4 parallel through the road hybrid vehicle.
Dynamic Performance Comparison Between In-Wheel and On-Board Motor Battery Electric Vehicles
Authors: de Carvalho Pinheiro Henrique , Castro dos Santos Pedro Gabriel , Sisca Lorenzo , Scavuzzo Santo , Ferraris Alessandro , Airale Andrea Giancarlo , Carello Massimiliana
Published: November 2020

This paper intends to present a novel full-vehicle numerical approach for in-wheel and on-board motor Battery Electric Vehicle (BEV) powertrain architectures, which overcomes the electrical and mechanical deficits widely present in the current literature. Namely, neglecting of the interaction between mechanical and electrical phenomena and its impact on the vehicle dynamic performance.

A co-simulation approach is employed: whereas the mechanical systems and their interactions are simulated with Adams Car, the electrical phenomena are solved by MATLAB/Simulink. The investigation is conducted over a full throttle maneuver by monitoring a set of performance indicators.
Design and Development of a Constant Force Non-Linear Spring (CF-NLS) for Energy Storage
Authors: Qaiser Zeeshan , Kang Liping , Johnson Shane
Published: November 2020

Development of constant force non-linear softening (CF-NLS) springs has recently gained attention in the literature due to their energy storage potential in many applications including robotics, biomechanics, machining, etc. These springs are typically designed by using computationally exhaustive topology optimization techniques which have shown to produce stress concentrations significantly reducing the operational life of the spring. Furthermore, current design methodologies including spline based optimizations are not exploiting the design space efficiently. There is a need of a computationally efficient design methodology capable of producing mechanisms without stress concentrations while more fully exploiting the design space. A new graph based design methodology is proposed by using a modified-depth first search (M-DFS) algorithm with 2D finite element analysis. A detailed parametric study is also conducted to design a mechanism by maximizing of the stored strain energy on a general stiffest-softening behavior. The proposed CF-NLS is validated experimentally and compared with mechanisms in the literature. It is observed that the proposed CF-NLS is providing more displacement capacity without stress concentrations and with less expensive materials due to improved exploitation of the design space. This proposed CF-NLS is beneficial for dynamic activities like walking, running and jumping robots or biomechanics where high energy storage capacity is required.
Geometrico-Static Analysis of a New Collaborative Parallel Robot for Safe Physical Interaction
Authors: Jeanneau Guillaume , Bégoc Vincent , Briot Sébastien
Published: November 2020

This paper introduces a geometrico-static analysis of an intrinsically safe parallel manipulator called R-Min. This robot was designed to reduce the risk of injury during a collision with a human operator, thanks to an underactuated architecture which enables large internal displacements in case of a collision. Indeed, the R-Min architecture is based on a modification of the well-known planar five-bar mechanism, where additional passive joints are introduced on the distal links in order to create a planar seven-bar mechanism with two degrees of underactuation. These two additional degrees of freedom are passively driven through the use of a supplementary passive leg, in which a tension spring is mounted between the base and the end-effector.

In this paper, the conditions satisfying the equilibrium and the stability of the mechanism are introduced, based on a geometrico-static analysis. The direct and inverse problems are then solved using a numerical approach. Solutions to both problems are presented and classified. One subset of solutions to the inverse problem is isolated and projected in the Cartesian space in order to obtain the payload-invariant workspace of the R-Min robot.
A Power Analysis to Determine Appropriate Sample Size for the Study of Student Design-Team Effectiveness
Authors: Takai Shun , Smith Thomas J. , Esterman Marcos
Published: November 2020

Forming collaborative teams is a critical first step in team-project-based design courses as team composition directly affects not only teamwork processes and outcomes but also teamwork skills and experience. While various approaches have been used to form teams, the best methodology has not been found due to a lack of understanding of how team compositions impact team performance and teamwork learning. We need to establish a team effectiveness model for student design teams that describes relationships between team characteristics and team performance or teamwork learning. One of many challenges in such an effort is to estimate an appropriate sample size to achieve statistically significant results before starting data collection. In this paper, we demonstrate a power analysis for determining an appropriate sample size, i.e., the number of student teams, before we study the effectiveness of student design-teams. We first present a hypothesized team effectiveness model for student design teams that shows possible relationships among team factors. We then illustrate a statistical analysis procedure for studying the team effectiveness model using structural equation modeling (SEM) or path analysis. We finally demonstrate a power analysis of SEM for determining the appropriate sample size for studying the team effectiveness model.
A Method to Specify Part of a System to Change in Improvement Design
Authors: Oizumi Kazuya , Aoyama Kazuhiro
Published: November 2020

Improvement design, which is characterized by minimum necessary changes to a past product, is employed to reuse verified and experienced parts to create a new product faster, reliable, and economically sound. However, as products become so complex that changes to some parts propagates concomitant changes to other parts, which makes it difficult to enjoy the advantages of improvement design. Therefore, design changes have to be contemplated at the early phase of design. This paper proposes an improvement design planning method based on House of quality. Parts of a product to be changed and directions on which they are changed are explored in terms of opportunity to improve product and risk of worsening other parts. By exploring the possible design in the trade-off between the opportunity and the risk, design change plan that comprises proper parts of a product to be changed can be decided. A case study on a solar boat design demonstrates the applicability and validity of the proposed method.
Applications of Polynomial Chaos-Based Cokriging to Simulation-Based Analysis and Design Under Uncertainty
Authors: Nagawkar Jethro , Leifsson Leifur
Published: November 2020

This paper demonstrates the use of the polynomial chaos-based Cokriging (PC-Cokriging) on various simulation-based problems, namely an analytical borehole function, an ultrasonic testing (UT) case and a robust design optimization of an airfoil case. This metamodel is compared to Kriging, polynomial chaos expansion (PCE), polynomial chaos-based Kriging (PC-Kriging) and Cokriging. The PC-Cokriging model is a multi-variate variant of PC-Kriging and its construction is similar to Cokriging. For the borehole function, the PC-Cokriging requires only three high-fidelity samples to accurately capture the global accuracy of the function. For the UT case, it requires 20 points. Sensitivity analysis is performed for the UT case showing that the F-number has negligible effect on the output response. For the robust design case, a 75 and 31 drag count reduction is reported on the mean and standard deviation of the drag coefficient, respectively, when compared to the baseline shape.
Development of a Modal Selection Method for Full Strain Field Estimation
Authors: Fu Gen , Untaroiu Alexandrina
Published: November 2020

Full field response of a structure is critical for evaluating the performance of large slender structures. Since only several discrete measurements can be acquired during operation, the data expansion method is important for the estimation of the full field responses of the large complex structure. In previous studies, modal transformation methods were mainly applied in model reduction/expansion and global shape sensing. Compared to other expansion methods, the modal method is straightforward to implement and computational efficient, which makes it the most suitable approach for real-time expansion. However, only the first several modes were included in the modal transformation method in previous studies. Since the errors due to truncated mode components can occur under high frequency band excitations, it is necessary to include all of the modes that contribute significantly to the responses of the structure. Therefore, in this study, a modal selection method based on operational modal analysis (OMA) is proposed for selecting proper modes. The modal characteristics of the system were derived with the strain data at several discrete locations. The contribution of each mode was quantified. By sorting the modes based on their contribution, the most significant modes can be used in the expansion process. Two operational modal analysis methods, stochastic system identification (SSI) and frequency domain decomposition (FDD), were considered and compared. The proposed approach was implemented with a computational model. Considerable improvement has been observed when high bandwidth excitations were added. The proposed modal selection method can successfully rank the participated modes. It can improve the accuracy of the modal transformation approach as shown in the impact loading case. It can be used for data expansion even when high frequency band is excited. Finally, we believe the novel methods presented in this study could be used in the development of more reliable health monitoring systems for turbomachinery.
A Method for Solving Multi-Objective Optimization Problems Containing an Infinite Number of Parameterized Objectives
Authors: Rudnick-Cohen Eliot
Published: November 2020

Multi-objective decision making problems can sometimes involve an infinite number of objectives. In this paper, an approach is presented for solving multi-objective optimization problems containing an infinite number of parameterized objectives, termed “infinite objective optimization”. A formulation is given for infinite objective optimization problems and an approach for checking whether a Pareto frontier is a solution to this formulation is detailed. Using this approach, a new sampling based approach is developed for solving infinite objective optimization problems. The new approach is tested on several different example problems and is shown to be faster and perform better than a brute force approach.
Extending the Use of Bio-Inspiration for Water Distribution Networks to Urban Settings
Authors: Dave Tirth , Layton Astrid
Published: November 2020

Prior work investigated the use of biological food webs as a source of quantitative guidance to balance the efficiency and redundancy in industrial water distribution networks. Urban water distribution networks, however, present unique challenges that prevent a direct replication of the bio-inspired methods used for industrial network settings. Many of the benefits bio-inspiration can impart on human networks, including resilience-related improvements, makes use of reuse- and recycling-related pathways — maximizing the use of all available value in the network. This work looks at the application of bio-inspiration to urban water network settings, modeling these networks to include local wastewater treatment options and testing actor aggregation options to best fit the ecosystem analogy. The results suggest that biological ecosystems do in fact have characteristics that can be beneficial to urban water distribution, but a change of system boundaries is required to recognize their potential.
Towards a Zero Trust Hybrid Security and Safety Risk Analysis Method
Authors: Papakonstantinou Nikolaos , Van Bossuyt Douglas L. , Linnosmaa Joonas , Hale Britta , O’Halloran Bryan
Published: November 2020

Designing and improving the resilience of complex sociotechnical/cyber-physical systems is not a simple task. Interdependencies between engineering domains can lead to emerging behavior which is difficult to predict and handle. Early identification of safety and security weaknesses of a safety-critical system leads to reduced redesign costs in later design phases. The scientific contribution of this paper is a method for early combined safety and security assessment based on interdisciplinary dependency models of the system. The focus is on the factors contributing to the estimation of the probabilities of successful attacks to system components. The Zero Trust paradigm is applied, in which all humans part of, or external to, the system pose a security risk. The estimation of security-related probabilities enables a combined safety and security overall risk calculation for the probability of losing specific key components or safety functions. The calculation of the security-related probabilities is a dynamic and difficult process that heavily depends on the domain and current global security environment. The methodology of this paper is demonstrated with a fictional case study of a spent fuel pool cooling system. The results of the case study showed that the overall risk of losing one key system component doubled when combining security and safety compared to only assessing safety events.
Extrapolation With Gaussian Random Processes and Evolutionary Programming
Authors: Planas Robert , Oune Nicholas , Bostanabad Ramin
Published: November 2020

Emulation plays an indispensable role in engineering design. However, the majority of emulation methods are formulated for interpolation purposes and their performance significantly deteriorates in extrapolation. In this paper, we develop a method for extrapolation by integrating Gaussian processes (GPs) and evolutionary programming (EP). Our underlying assumption is that there is a set of free-form parametric bases that can model the data source reasonably well. Consequently, if we can find these bases via some training data over a region, we can do predictions outside of that region. To systematically and efficiently find these bases, we start by learning a GP without any parametric mean function. Then, a rich dataset is generated by this GP and subsequently used in EP to find some parametric bases. Afterwards, we retrain the GP while using the bases found by EP. This retraining essentially allows to validate and/or correct the discovered bases via maximum likelihood estimation. By iterating between GP and EP we robustly and efficiently find the underlying bases that can be used for extrapolation. We validate our approach with a host of analytical problems in the absence or presence of noise. We also study an engineering example on finding the constitutive law of a composite microstructure.
Introducing Likelihood of Occurrence and Expected Cost to Human Error and Functional Failure Reasoning Framework
Authors: Irshad Lukman , Hulse Daniel , Demirel H. Onan , Tumer Irem Y. , Jensen David C.
Published: November 2020

Risk-based design uses severity and occurrence quantification to determine overall system risk and prioritize the most important hazards. To fully understand and effectively mitigate potential risks, the effects of component failures and human errors (acting alone and in tandem) need to be considered early. Then one can determine whether to allocate resources to proactively mitigate human errors in the design process. In previous work, the Human Error and Functional Failure Reasoning (HEFFR) framework was developed to model effects of human errors and component failures in a system, taking critical event scenarios as inputs and producing functional failures, human errors, and their propagation paths as outputs. With automated scenario generation, this framework can model millions of scenarios that cause system critical functions to fail. However, the outputs of this framework do not include any quantifiable measures to assess the risk of the hazards or prioritize fault scenarios. This work addresses these shortcomings by using a scenario probability and cost model to quantify the expected cost of failures in the HEFFR framework. A coolant tank case study is used to demonstrate this approach. The results show that the quantifiable measures enable HEFFR to identify worst-case scenarios, prioritize scenarios with the highest impact, and improve human-product interactions. However, the underlying likelihood and cost models are subject to uncertainties which may affect the assessments.
Substructure Interface Reduction Techniques to Capture Nonlinearities in Bolted Structures
Authors: Singh Aabhas , Allen Matthew S. , Kuether Robert J.
Published: November 2020

Structural dynamic finite element models typically use multipoint constraints (MPC) to condense the degrees of freedom (DOF) near bolted joints down to a single node, which can then be joined to neighboring structures with linear springs or nonlinear elements. Scalability becomes an issue when multiple joints are present in a system, because each requires its own model to capture the nonlinear behavior. While this increases the computational cost, the larger problem is that the parameters of the joint models are not known, and so one must solve a nonlinear model updating problem with potentially hundreds of unknown variables to fit the model to measurements. Furthermore, traditional MPC approaches are limited in how the flexibility of the interface is treated (i.e. with rigid bar elements the interface has no flexibility). To resolve this shortcoming, this work presents an alternative approach where the contact interface is reduced to a set of modal DOF which retain the flexibility of the interface and are capable of modeling multiple joints simultaneously. Specifically, system-level characteristic constraint (S-CC) reduction is used to reduce the motion at the contact interface to a small number of shapes. To capture the hysteresis and energy dissipation that is present during microslip of joints, a hysteretic element is applied to a small number of the S-CC Shapes. This method is compared against a traditional MPC method (using rigid bar elements) on a two-dimensional finite element model of a cantilever beam with a single joint near the free end. For all methods, a four-parameter Iwan element is applied to the interface DOF to capture how the amplitude dependent modal frequency and damping change with vibration amplitude.
A Comparison of Vector and Network-Based Measures for Assessing Design Similarity
Authors: Nandy Ananya , Dong Andy , Goucher-Lambert Kosa
Published: November 2020

In order to retrieve analogous designs for design-by-analogy, computational systems require the calculation of similarity between the target design and a repository of source designs. Representing designs as functional abstractions can support designers in practicing design-by-analogy by minimizing fixation on surface-level similarities. In addition, when a design is represented by a functional model using a function-flow format, many measures are available to determine functional similarity. In most current function-based design-by-analogy systems, the functions are represented as vectors and measures like cosine similarity are used to retrieve analogous designs. However, it is hypothesized that changing the similarity measure can significantly change the examples that are retrieved. In this paper, several similarity measures are empirically tested across a set of functional models of energy harvesting products. In addition, the paper explores representing the functional models as networks to find functionally similar designs using graph similarity measures. Surprisingly, the types of designs that are considered similar by vector-based and one of the graph similarity measures are found to vary significantly. Even among a set of functional models that share known similar technology, the different measures find inconsistent degrees of similarity — some measures find the set of models to be very similar and some find them to be very dissimilar. The findings have implications on the choice of similarity metric and its effect on finding analogous designs that, in this case, have similar pairs of functions and flows in their functional models. Since literature has shown that the types of designs presented can impact their effectiveness in aiding the design process, this work intends to spur further consideration of the impact of using different similarity measures when assessing design similarity computationally.
Development of Spatial Abilities in Engineering Education: An Empirical Study of the Influence of Visualisation Media
Authors: Zorn Stefan , Gericke Kilian
Published: November 2020

Spatial ability is one of the critical components of human intelligence. It has been proven that it is particularly crucial for success, especially in engineering, where interpreting views of an object presented by drawings, visualizing parts, or manipulating geometry in CAD are fundamental skills. Research has confirmed that spatial skills can be improved through instruction and teaching, for example, sketching and technical drawing, which are also included in the basic engineering classes. This study tested the hypothesis that the development of spatial skills during the fundamental design engineering class can be positively influenced due to the use of different visualization media for sketching and technical drawing tasks, whereas the used visualization media offer varying possibilities of interaction. Seventy students were pre- and post-tested with the Mental Rotation Test. All participants received the same training during the class but were given individual tasks with varying media. The analysis revealed a significant increase in mental rotation performance for all participants throughout the semester with a big effect size. Moreover, the mean performance improvement differed considerably depending on the visualization media and its offered interaction possibilities.
Surrogate Model Assisted Lithium-Ion Battery Co-Design for Fast Charging and Cycle Life Performances
Authors: Cui Tonghui , Zheng Zhuoyuan , Wang Pingfeng
Published: November 2020

As one of the significant enablers of portable devices and electric vehicles, lithium-ion batteries are drawing much attention for their high energy density and low self-discharging rate. A major hindrance to their further development has been the “range anxiety”, that fast-charging of Li-ion battery is not attainable without sacrificing battery life. In the past, much effort has been carried out to resolve such a problem by either improve the battery design or optimize the charging/discharging protocols, while limited work has been done to address the problem simultaneously, or through a control co-design framework, for a system-level optimum. The control co-design framework is ideal for lithium-ion batteries due to the strong coupling effects between battery design and control optimization. The integration of such coupling effects can lead to improved performances as compared with traditional sequential optimization approaches. However, the challenge of implementing such a co-design framework has been updating the dynamics efficiently for design variations. In this study, we optimize the charging time and cycle life of a lithium-ion battery as a control co-design problem. Specifically, the anode volume fraction and particle size, and the corresponding charging current profile are optimized for a minimum charging time with health-management considerations. The battery is modeled as a coupled electro-thermal-aging dynamical system. The design-dependent dynamics is parameterized thru a Gaussian Processes model, that has been trained with high-fidelity multiphysics simulation samples. A nested co-design approach was implemented using direct transcription, which achieves a better performance than the sequential design approach.
Mission-Level Optimization: Complex Systems Design for Highly Stochastic Life Cycle Use Case Scenarios
Authors: Chell Brian , Hoffenson Steven , Kruse Benjamin , Blackburn Mark R.
Published: November 2020

Mission engineering is a growing field with many practical opportunities and challenges. The goal of mission engineering is to increase system effectiveness, reduce life cycle costs, and aid in communicating system capabilities to key stakeholders. Optimizing system designs for their mission context is important to achieving these goals. However, system optimization is generally done using multiple key performance indicators (KPIs), which are not always directly representative of, nor easily translatable to, mission success. This paper introduces, motivates, and proposes a new approach for performing mission-level optimization (MLO), where the objective is to design systems that maximize the probability of mission success over the system life cycle. This builds on previous literature related to mission engineering, modeling, and analysis, as well as optimization under uncertainty. MLO problems are unique in their high levels of design, operational, and environmental uncertainty, as well as the single binary objective representing mission success or failure. By optimizing for mission success, designers can account for large numbers of KPIs and external factors when determining the best possible system design.
An Initial Analysis of Undergraduate Student Mental Models of Product Design
Authors: Driscoll Jessica R. , Hoffenson Steven , Pitterson Nicole
Published: November 2020

Design is a concept that means different things to different people. Even in the engineering design research community, there is little agreement on a consistent definition of design. This study looks into how engineering students understand product design, using a concept mapping exercise to elicit the key concepts and relationships present in their mental models. An analysis of concept maps from 130 third-year undergraduate engineering students shows how these students think about design, the common themes and relationships that are seen across the population, and variations across different groups of students. By understanding how students in the midst of ABET-accredited programs conceptualize design, conclusions can be drawn regarding the effectiveness of existing curricula in instilling a complete understanding of holistic product design. This can lead to recommendations regarding future engineering design learning objectives, teaching materials, and activities.
Design and Manufacturing of 3D Printed Foods With User Validation
Authors: Chirico Scheele Stefania , Binks Martin , Egan Paul F.
Published: November 2020

Additive manufacturing is becoming widely practical for diverse engineering applications, with emerging approaches showing great promise in the food industry. From the realization of complex food designs to the automated preparation of personalized meals, 3D printing promises many innovations in the food manufacturing sector. However, its use is limited due to the need to better understand manufacturing capabilities for different food materials and user preferences for 3D food prints. Our study aims to explore the 3D food printability of design features, such as overhangs and holes, and assess how well they print through quantitative and qualitative measurements. Designs with varied angles and diameters based on the standard design limitations for additive manufacturing were printed and measured using marzipan and chocolate. It was found that marzipan material has a minimum feature size for overhang design at 55° and for hole design at 4mm, while chocolate material has a minimum overhang angle size of 35° and does not reliably print holes. Users were presented a series of designs to determine user preference (N = 30) towards the importance of fidelity and accuracy between the expected design and the 3D printed sample, and how much they liked each sample. Results suggest that users prefer designs with high fidelity to their original shape and perceive the current accuracy/precision of 3D printers sufficient for accurately printing three-dimensional geometries. These results demonstrate the current manufacturing capabilities for 3D food printing and success in achieving high fidelity designs for user satisfaction. Both of these considerations are essential steps in providing automated and personalized manufacturing for specific user needs and preferences.