bluuebunny/crossref_metadata_2025 huggingface dataset:
Police Encounters for Behavioral Health‐Related Reasons in Rural and Remote Communities: A Canadian Study☆
Authors: David Jean‐Denis
Published: November 2022

Evidence suggests police officers are increasingly called upon to respond to incidents related to mental health issues, emotional problems, and substance abuse. Many have raised concerns regarding their involvement in such incidents. Yet, little is known about these encounters in rural and remote communities despite evidence suggesting that the context of non‐urban areas should matter. Accordingly, this article proposes to examine variations in self‐reported encounters with the police for behavioral health‐related reasons across urban, rural, and remote communities. Using data from the 2014 General Social Survey, a representative sample of the Canadian population, we assess these self‐reported encounters from two different angles: encounters for one's own behavioral health crisis and encounters for a family member's behavioral health needs. While findings on the former are inconclusive, those examining police contacts for a family member suggest that living in rural or remote communities is significantly associated with a greater probability of experiencing such situations relative to living in urban areas. Furthermore, this probability increases with the relative geographical isolation of communities. These results are discussed in light of the rising concerns regarding our reliance on the police for such incidents and the need to account for the situation of rural and remote communities.
Discovery of the novel HLA‐B*57:164 allele, a variant of HLA‐B*57:01:01:01, in a Taiwanese individual
Authors: Yang Kuo‐Liang , Lin Py‐Yu
Published: November 2022

One nucleotide substitution in codon 317 of HLA‐B*57:01:01:01 results in the novel allele, HLA‐B*57:164.
Arabidopsis cyclin‐dependent kinase C2 interacts with HDA15 and is involved in far‐red light‐mediated hypocotyl cell elongation
Authors: Chen Chia‐Yang , Chang Chung‐Han , Wu Chien‐Han , Tu Yi‐Tsung , Wu Keqiang
Published: November 2022

Histone deacetylases (HDAs) regulate many aspects of plant development and responses to environmental changes. Previous studies have demonstrated that the Arabidopsis histone deacetylase HDA15 is a positive regulator in far‐red (FR) light‐mediated inhibition of hypocotyl elongation. Furthermore, HDA15 can be phosphorylated and its enzymatic activity is negatively regulated by phosphorylation. However, the kinases that can phosphorylate HDA15 are still unknown. Cyclin‐dependent kinases (CDKs) are a large family of serine/threonine protein kinases and have been identified as major regulators of the cell cycle and transcription. In this study, we show that the cyclin‐dependent kinase CDKC2 interacts with HDA15 both in vitro and in vivo. In vitro kinase assays show that CDKC2 phosphorylates HDA15. Genetic evidence suggests that HDA15 acts downstream of CDKC2 in hypocotyl elongation under FR light. Furthermore, HDA15 and CDKC2 function synergistically in the regulation of FR‐mediated cell elongation. The expression of cell wall organization‐ and auxin signaling‐related genes under FR light is increased in hda15 and cdkc2/hda15 mutants. Taken together, our study indicates that CDKC2 can phosphorylate HDA15 and plays an important role in FR light‐regulated hypocotyl elongation.
Destabilising geographies in Colombia: Trajectories and perspectives
Authors: Ulloa Astrid
Published: November 2022

Colombia has recently witnessed the emergence of new geographies, which opens new scenarios of analysis and political contexts leading to a better understanding of the multiplicity of humans–non‐humans and their territories, territorialities and their rights. These geographies enter dialogue with other disciplinary trajectories and Indigenous and Afro‐descendant perspectives. These new perspectives also interact with critical, feminist and decolonial geographies. These encounters have led to the arrival of new approaches, which I call destabilising geographies. The proposals positioned from these new perspectives look to decolonise the founding binary categories of geography. They are perspectives and proposals that destabilise institutionalised visions of geography because they emerge with and from social processes and movements that require political spaces and the recognition of territorial and environmental rights. These geographies propose an opening to other ontologies and epistemologies that contribute to the complexity of the categories of territory, body‐territory, human–non‐human territories, the political and the collective. They also reveal the racial territorial processes of extractive dynamics and armed conflict. In this text, I develop the following emergences: dissident feminist geographies, geographies of racialised extractivism, Black geographies and Indigenous relational spatialities. These reflections are based on my experience of over 16 years of teaching in the geography programme at Universidad Nacional de Colombia.
Mechanics of Interfacial Delamination in Deep-Sea Soft Robots Under Hydrostatic Pressure
Authors: Shao Xianmin , Cai Yijie , Yin Shunyu , Li Tiefeng , Jia Zheng
Published: November 2022

In recent years, with the increasing demand for ocean exploration, deep-sea soft robots featuring better environmental adaptability, lighter weight, and less energy consumption relative to traditional robots have emerged. Considering that deep-sea soft robots usually contain components composed of dissimilar materials in the form of layered structures, interfacial delamination is likely to occur under extreme hydrostatic pressure, which may significantly impact robot operation. Moreover, traditional numerical methods to analyze interfacial delamination with J-integral have limitations in analyzing interfacial delamination in abyssal environments due to the hydrostatic pressure exerted on delaminated interfaces. To address this largely unexplored issue, this paper proposes a numerical method suitable for calculating the energy release rate for interfacial delamination in a film-substrate structure under hydrostatic pressure and systematically studies the factors influencing the energy release rate in deep-sea soft robots with dimensional analysis. It can be found that a larger elastic mismatch between the film and the substrate will lead to a larger driving force for interfacial delamination. The failsafe maps are also obtained based on the proposed calculation method, through which it can be observed very intuitively whether the structure with various material parameters has a tendency of interfacial delamination at different water depths.
Generative Transformers for Design Concept Generation
Authors: Zhu Qihao , Luo Jianxi
Published: November 2022

Generating novel and useful concepts is essential during the early design stage to explore a large variety of design opportunities, which usually requires advanced design thinking ability and a wide range of knowledge from designers. Growing works on computer-aided tools have explored the retrieval of knowledge and heuristics from design data. However, they only provide stimuli to inspire designers from limited aspects. This study explores the recent advance of the natural language generation (NLG) technique in the artificial intelligence (AI) field to automate the early-stage design concept generation. Specifically, a novel approach utilizing the generative pre-trained transformer (GPT) is proposed to leverage the knowledge and reasoning from textual data and transform them into new concepts in understandable language. Three concept generation tasks are defined to leverage different knowledge and reasoning: domain knowledge synthesis, problem-driven synthesis, and analogy-driven synthesis. The experiments with both human and data-driven evaluation show good performance in generating novel and useful concepts.
A Novel Heat-Assisted Three-Roll Incremental Rolling System for Flexible Rolling
Authors: Jiang Zilin , Zeng Qiang , Anderoglu Osman , Maloy Stuart , Ehmann Kornel F. , Cao Jian
Published: November 2022

The increasing demand for customized products and rapid prototyping triggers the development of dieless forming process where the need of part-specific dies is eliminated compared to conventional forming processes. This paper presents a heat-assisted three-roll incremental rolling system capable of producing rods and tubes of various diameters without the need for die/tool replacement. The system incorporates two possible heating mechanisms, namely, an induction heater and a high-current power supply for electrically assisted forming. Due to its high flexibility and hot forming ability, this rolling system is ideal for low volume production or scientific research. The newly fabricated rolling machine was initially evaluated using low carbon steel rods. The experiments have shown that the machine can produce metallic rods down to 6 mm in diameter without apparent spiral marks on the outer surface of the rolled product using multiple passes. The finite element method (FEM) was used to analyze the reaction moment, depth of the spiral marks, and the effect of axial feeding speed on the spiral marks. The simulation model predicted the results of the experiments with less than a 10% error. The work established a flexible rolling platform for possible future research, which can include the study of interface behavior in the thermo-mechanical rolling processes, and the study of material behavior in this multi-axial multi-physics environment.
Influence of Purge Flow Injection on the Performance of an Axial Turbine With Three-Dimensional Airfoils and Non-Axisymmetric Endwall Contouring
Authors: Schäflein Lukas , Janssen Johannes , Brandies Henri , Jeschke Peter , Behre Stephan
Published: November 2022

In this paper, we present the evaluation of the aerodynamic robustness to rim seal purge flow of an optimized 1.5-stage axial turbine configuration with a bowed stator profile and endwall contouring. Performance maps obtained by experiments and numerical simulations show that the efficiency benefit gained by this optimized configuration is partially reduced, but not eliminated, by the injection of purge flow through the cavity downstream of the first stator. Measurements with five-hole probes and hot-wire probes, as well as unsteady RANS simulations, give detailed insights into the physical effects of the purge flow inside the rotor passage. There, when no purge flow is injected, the optimized configuration diminishes the formation of loss-inducing secondary flow structures near the hub and the casing. When purge flow is injected, however, new strong secondary flow structures are induced near the hub. These vortices generate additional losses and thereby partially negate the efficiency benefits gained by the optimization. From the data, we found that this influence of the purge flow is limited to the lower half of the channel height. The data also show that the optimized configuration is able to reduce the vorticity near the casing regardless of the purge flow injection, which in turn leads to an efficiency increase in this area. Together, these effects lead to a reduction of the previously gained efficiency benefit by the optimized configuration when it is subjected to purge flow injection. However, compared to a baseline configuration with cylindrical endwalls also subject to purge flow injection, the overall efficiency is still increased by 0.38%.
Automated Design of Packaging Cushions for Withstanding Drop Tests
Authors: So David , Hildebrand Lisa , Campbell Matthew I.
Published: November 2022

A method is described to automate the design of foam packaging cushions to ensure that the packaged product does not fail when subjected to dropping. This methodology includes CAD instructions to automatically create packaging shapes and an iterative search for optimal cushion thickness using Finite-Element Analysis (FEA) simulations. The FEA is correlated to real drop-test data and the foam material is modeled in its interaction with the product. While the entire process takes over 2 hours, the result can save engineers significant time to find packaging solutions and can produce solutions that are smaller than conventionally over-designed packaging solutions. The paper presents the detailed steps of the methodology and shows results for two example products.
Proposal of Defining Exploration and Exploitation in Engineering Design and Evaluating the Degree of Exploration by Natural Language Processing
Authors: Okamoto Masahiro , Murakami Tamotsu
Published: November 2022

Recently, in the field of business administration, the idea that ambidexterity of exploration and exploitation is necessary for organizations to continue to generate value in a sustainable manner has been attracting attention. Although the balance between exploration and exploitation is also considered to be important in engineering research and development and design, research from such a perspective has not been conducted. We have been analyzing the ambidexterity of exploration and exploitation from the perspective of design, and developing a method to evaluate the degree of ambidexterity objectively and quantitatively. In this paper, the definitions of exploration and exploitation in design, a quantitative evaluation method for the degree of exploration based on the definitions, and the results of the verification of this method are presented. The evaluation method is developed on the basis of the definition that focuses on whether the design object has changed qualitatively or quantitatively as a result of the organization’s activity. In this method, words related to the functions of the target product are extracted from the design documents, and their similarity to those in past documents is evaluated. As a result of applying the proposed method to the descriptions of past products, for which the relationship between exploration and exploitation has been clarified, it is shown that the proposed method can be appropriate as an evaluation method for exploration.
Experimental Validation of Origami’s Reservoir Computing Power and an Mechano-Intelligent Task of Payload Identification
Authors: Wang Jun , Li Suyi
Published: November 2022

Animals’ excellent capability to achieve complex locomotion and manipulation behaviors benefits from their unique body morphology, distributed sensory system, and direct connection with the environment, creating intelligence embodied directly in their bodies. This presents a significantly more flexible control strategy than most engineered robots that rely solely on a centralized control unit. A computing frame called physical reservoir computing is put forward to mimic the animal’s embodied intelligence, enabling many mechanical structures and materials to accomplish complex computation tasks. In this paper, we experimentally verify the computing capability of Miura-ori sheets using emulation tasks and find strategies to improve the computing performance by optimizing their physical and computational designs. Comprehensive parametric studies show that designing an unevenly distributed nodal mass and fine-tuning the origami folding designs are the most effective approach for improving computing performance. We also demonstrate the potential of using the origami reservoir to achieve an intelligent task: predicting the payload magnitude. In other words, the nonlinear dynamics of origami can be utilized to ‘feel’ the weight of objects on top of it. The results of this paper can pave the way to enable more advanced mechano-intelligence in origami-based structures and robots.
Design and Nonlinear Analysis of an Overconstraint Based Constant Amplification Ratio Compliant Mechanism
Authors: Zhu Jiaxiang , Hao Guangbo , Liu Tinghao , Li Haiyang
Published: November 2022

Compliant mechanism based amplifiers have been extensively studied with particular attentions to achieving a high amplification ratio. However, a constant amplification ratio is less investigated, which is much desired for a simple and quick prediction of outputs. In this research, we aim to address this need. Thereby, we present an overconstraint based constant amplification ratio compliant mechanism (OCARCM) that alleviates the change of the amplification ratio. Comparative analysis is provided between the proposed OCARCM and the widely-used bridge-type compliant amplifier in terms of the ability to remain constant amplification ratio with and without payload. The free-body diagram (FBD) combined with the beam constraint model (BCM) method is employed to obtain the closed-form solutions that accurately and insightfully elaborate the nonlinearities in the force-displacement characteristics of the OCARCM. The closed-form results are verified by the nonlinear finite element results (FEA) with a maximum error of 1%. Both models reveal that the amplification ratio of the proposed OCARCM decreases by 1%, while the amplification ratio of the bridge-type amplifier decreases by approximately 14% under the same conditions. An experiment based on the 3D-printed prototype is conducted, which provides some insights into the characteristics of the design and the potential for future improvement.
Biodynamic Response of Seated Human Body to Random and 1 Hz Lateral-Roll Dual-Axis Vibration
Authors: Lin Zefeng , Zhang Junhong , Li Meng , Ni Guangjian , Lin Jiewei
Published: November 2022

People are exposed to whole-body vibration involving multiple directions during daily life especially travelling in vehicles. This study carries out experimental research on human response to dual-axis lateral and roll vibration. Random and sinusoidal vibration defined at 1 Hz are employed as the stimuli. Corresponding apparent inertia and root mean square of human response are measured to investigate the effect of phase difference as well as the vibration intensity. As a result, the symmetrical effect of the phase difference on the human response is detected. The intensity of roll and lateral vibration shows opposite effects. Partial coherence analysis is conducted, and the dominance of lateral vibration is confirmed. Hence, to improve the ride comfort, the lateral vibration needs a higher priority to be controlled compared to the roll one. The compensation effect of the roll vibration provides an effective way to reduce human response around the resonance frequency as long as the magnitude of it is carefully controlled.
On the Effectiveness and Optimal Performance of Gravity Compensation Design of an Inverted Slider-Crank Mechanism Using Realistic Springs
Authors: Zeng Xiangxian , Kuo Chin-Hsing
Published: November 2022

Designing of spring-balanced linkage mechanisms for gravity compensation is commonly done through an ideal assumption that the springs should have a zero free-length (ZFL). After the design results were generated, the ZFL springs could then be physically implemented on the designed linkages by versatile mechanical arrangement, which, however, will inevitably complicate the mechanism structure. This paper investigates the design performance of gravity compensation (i.e., static balancing) of a spring-balanced inverted slider-crank mechanism that uses realistic practical springs rather than ZFL springs. The design aims to seek optimal dimension parameters of the slider-crank such that either its peak driving torque or the overall energy consumption can be minimized under the balancing effect. The effectiveness and the balancing performance of the resulting designs are evaluated through statistics of a database of 8,000 case studies of the slider-crank with different load conditions. As a result, the peak driving torque of the balanced inverted slider-crank can be reduced by 60%–85% while the overall energy consumption can be decreased by 60%–89% in most cases. It demonstrates that, instead of using unrealistic ZFL springs to pursue the status of perfect balancing, using realistic springs in balancing a simple four-bar may still guarantee an acceptable compromise in balancing performance while avoiding complicating the mechanism structure for ZFL-spring implementation.
A New Framework for Efficient Sequential Sampling-Based RBDO Using Space Mapping
Authors: Park Jeong Woo , Lee Ikjin
Published: November 2022

In the engineering application of sampling-based reliability-based design optimization (RBDO), the Monte Carlo simulation (MCS) using a surrogate model of the performance function is mainly used for the probability of failure calculation and sensitivity analysis. However, if an inaccurate surrogate model is used, the calculation result using MCS will also be inaccurate, so it is essential to improve the accuracy of the surrogate model using sequential sampling. Hence, various sampling-based RBDO methods and sequential sampling methods have been proposed and used in various fields, and space mapping may also be a new framework for sequential sampling. In this paper, RBDO based on a sampling method with the Gaussian process regression (GPR) and space mapping is proposed. Space mapping is generally used to request high-fidelity samples to update the low-fidelity model in multi-fidelity model conditions. However, in the proposed method, it is used for sequential sampling to improve the accuracy of the existing surrogate model. The major advantage of the proposed space mapping-based RBDO is that the existing surrogate model and the finally updated surrogate model can be formulated with simple matrix and vector calculations. In particular, when there is only a surrogate model that has been built due to the loss of existing sample information since the space mapping updates the model, the accuracy of the surrogate model can be improved by sequential sampling. In addition, the proposed method can provide a convergence condition that can be used universally in several problems with the location of the sequential sampling point. The proposed method can be compared with sequential sampling-based RBDO using GPR, and the calculation accuracy and efficiency are demonstrated through 2-D highly nonlinear example and engineering problem.
The Impact of Gender on Individual Perceptions and Team Psychological Safety in Engineering Design Teams
Authors: Cole Courtney , Jablokow Kathryn , Mohammed Susan , Miller Scarlett
Published: November 2022

Improving team interactions in engineering to model gender inclusivity has been at the forefront of many initiatives in both academia and industry. However, there has been limited evidence on the impact of gender-diverse teams on psychological safety. This is important because psychological safety has been shown to be a key facet for the development of innovative ideas, and has also been shown to be a cornerstone of effective teamwork. But how does the gender diversity of a team impact the development of psychological safety? The current study was developed to explore just this through an empirical study with 38 engineering design student teams over the course of an 8-week design project. These teams were designed to be half heterogeneous (either half-male and half-female, or majority male) or other half homogeneous (all male). We captured psychological safety at five time points between the homogenous and heterogenous teams and also explored individual dichotomous (peer-review) ratings of psychological safety at the end of the project. Results indicated that there was no difference in psychological safety between gender homogenous and heterogenous teams. However, females perceived themselves as more psychologically safe with other female team members compared to their ratings of male team members. Females also perceived themselves to be less psychologically safe with male team members compared to male ratings of female team members, indicating a discrepancy in perceptions between genders. These results point to the need to further explore the role of minoritized groups in psychological safety research and to explore how this effect presents itself (or is covered up) at the team level.
Vibration Energy Harvester With Piecewise Linear Nonlinear Oscillator and Controllable Gap Size
Authors: Veney Jacob , D’Souza Kiran
Published: November 2022

Recently, vibration energy harvesting has been seen as a viable energy source to provide for our energy dependent society. Researchers have studied systems ranging from civil structures like bridges to biomechanical systems including human motion as potential sources of vibration energy. In this work, a bench-top system of a piecewise-linear (PWL) nonlinear vibration harvester is studied. A similar idealized model of the harvester was previously looked at numerically, and in this work the method is adjusted to handle physical systems to construct a realistic harvester design. With the physically realizable harvester design, the resonant frequency of the system is able to be tuned by changing the gap size between the oscillator and mechanical stopper, ensuring optimal performance over a broad frequency range. Current nonlinear harvester designs show decreased performance at certain excitation conditions, but this design overcomes these issues while also still maintaining the performance of a linear harvester at resonance. In this investigation, the system is tested at various excitation conditions and gap sizes. The computational response of the resonance behavior of the PWL system is validated against the experiments. Additionally, the electromechanical response is also validated with the experiments by comparing the output power generated from the experiments with the computational prediction.
Trade-Off Characterization Between Social and Environmental Impacts Using Agent-Based Models and Life-Cycle Assessment
Authors: Liechty Joseph C. , Mabey Christopher S. , Mattson Christopher A. , Salmon John L. , Weaver Jason M.
Published: November 2022

Meeting the UN’s sustainable development goals requires designers and engineers to solve multi-objective optimization problems involving trade-offs between social, environmental, and economic impacts. This paper presents an approach for designers and engineers to quantify the social and environmental impacts of a product at a population-level and then perform a trade-off analysis between those impacts. In the approach, designers and engineers define the attributes of the product as well as the materials and processes used in the product’s life cycle. Agent-Based Modeling (ABM) tools that have been developed to model the social impacts of products are combined with Life-Cycle Assessment (LCA) tools that have been developed to evaluate the pressures that different processes create on the environment. Designers and engineers then evaluate the trade-offs between impacts using Pareto frontiers to find non-dominated solutions that minimize environmental impacts while maximizing positive and/or minimizing negative social impacts. Product adoption models generated by ABM allow designers and engineers to approximate population-level environmental impacts and avoid Simpson’s paradox, where a reversal in choices is preferred when looking at the population-level impacts versus the product-level impacts. This analysis of impacts has the potential to help designers and engineers create more impactful products that contribute towards the UN sustainable development goals.
The Effects of Representation Modality on Subsystem Clustering
Authors: Murphy Alexander R. , Patel Apurva , Sen Chiradeep , Summers Joshua D.
Published: November 2022

The representation of an engineering system can come in different modalities. These modalities may impact how designers’ reason about a given system, which could have implications for how solutions are derived to a given problem. In this paper, function structures, function graphs, and component graphs are compared to understand how each representation modality impacts subsystem clustering behavior. This was achieved through a human-subjects experiment that presented three common products (a hair dryer, a food mixer, and a toilet) represented in one of the three described modalities and a troubleshooting scenario. Results suggest that the effects of the representation modality are consistent between participants at two different universities; however, these effects are not consistent between products. Similarly, the effects of representation modality on the occurrence of element pairs also vary between products, suggesting that the specifics of the system that is represented have a non-negligible effect on the clustering patterns. This analysis can be expanded in future work to include clusters of larger size to take a deeper look at subsystem reasoning. These preliminary results show that representation modality can affect systems thinking. This work takes a step towards understanding how function modeling impacts design cognition at the subsystem level, and how functional decomposition compares to other modalities of system representation.
Progress Towards Data-Driven High-Rate Structural State Estimation on Edge Computing Devices
Authors: Satme Joud , Coble Daniel , Priddy Braden , Downey Austin R. J. , Bakos Jason D. , Comert Gurcan
Published: November 2022

Structures operating in high-rate dynamic environments, such as hypersonic vehicles, orbital space infrastructure, and blast mitigation systems, require microsecond (μs) decision-making. Advances in real-time sensing, edge-computing, and high-bandwidth computer memory are enabling emerging technologies such as High-rate structural health monitoring (HR-SHM) to become more feasible. Due to the time restrictions such systems operate under, a target of 1 millisecond (ms) from event detection to decision-making is set at the goal to enable HR-SHM. With minimizing latency in mind, a data-driven method that relies on time-series measurements processed in real-time to infer the state of the structure is investigated in this preliminary work. A methodology for deploying LSTM-based state estimators for structures using subsampled time-series vibration data is presented. The proposed estimator is deployed to an embedded real-time device and the achieved accuracy along with system timing are discussed. The proposed approach has shown potential for high-rate state estimation as it provides sufficient accuracy for the considered structure while a time-step of 2.5 ms is achieved. The Contributions of this work are twofold: 1) a framework for deploying LSTM models in real-time for high-rate state estimation, 2) an experimental validation of LSTMs running on a real-time computing system.
A Decision-Centric Perspective on Evolving Cyber-Physical-Social Systems: Effectiveness, Group Value, and Opportunities
Authors: van Beek Anton
Published: November 2022

In this paper, we view evolving cyber-physical-social systems (CPSSs) from a group decision-making perspective, introduce the group value concept as a potential approach to improve their effectiveness, and conclude by identifying a set of research directions for further scientific inquiry. An evolving CPSS is a system in which the digital and physical spaces adapt to changing interests in the social space. In this paper, we introduce the group value concept as an approach to balancing the interests of individuals in the social space and deciding how a CPSS should evolve. The advantages afforded by the group value concept are twofold: (i) it enables CPSSs to evolve along with the interests of the social space, and (ii) it provides transparency in the decision-making process that will improve public support. The group value is a stochastic function that is constructed by modeling the distributions of individual value functions and shares a similarity with utility-theory and normative models for group decision-making. Through analysis of the introduced framework, we show: (i) how the group value concept can be used to bring about evolving CPSSs, (ii) introduce the difference between utility theory and normative models for group decision-making, (iii) define the conditions under which the introduced evolving CPSSs framework is valid, and (iv) delineate a set of four research areas for further scientific inquiry. The motivation for delineating a set of additional research challenges comes from the observation that group decisions violate the conditions of logical decision-making that can only be satisfied for an individual’s decisions. Consequently, establishing an agent that controls the evolution of a CPSS needs to consider the consequences of violating these conditions on the effectiveness of the decision. Through continued research in the identified decision-centric research areas, evolving CPPSs can be established to address many societal challenges and will be more effective as they enjoy broader public support.
Hysteresis Suppression in Coupled Resonators Under Simultaneous Primary and Superharmonic Excitations
Authors: Lyu Ming , Zhao Jian , Kacem Najib , Song Jiahao , Sun Rongjian , Liu Pengbo
Published: November 2022

A general model of two resonators subjected to electrostatic coupling and simultaneous primary and superharmonic excitations is developped. A reduced-order model including quadratic and cubic nonlinear terms is generated and the multi-scale method is used to solve the dynamic characteristics and analyze the contribution of the different frequency components. In addition, an overall nonlinear coefficient is defined, which can be adjusted to make the system exhibit different dynamic characteristics including softening, hardening, and linear behaviors. Finally, the conditions for restoring the linear behavior at the highest possible amplitude and suppressing its hysteresis are given.
Aircraft Maintenance Schedule Design Optimization During a Pandemic
Authors: Jordan Elizabeth , Azarm Shapour
Published: November 2022

The aim of this paper is to formulate and solve the aircraft maintenance scheduling design optimization problem while considering the effects of a pandemic, such as the COVID-19 pandemic. Aircraft maintenance is dependent on how much the aircraft is in service, among other factors. It is no surprise that the pandemic has significantly impacted airline operations, due to travel restrictions and people’s hesitancy to travel. Thus, it is important for airliners to consider the progression of the pandemic when designing their flight and maintenance schedules. The approach proposed in this paper addresses this issue by integrating several models. The first one is a time series forecasting model to predict future COVID-19 cases — in this paper we use a Long Short-Term Memory (LSTM) network. The second model is a simple neural network for predicting flight frequencies based on historical flight data and the results of the first model. The predicted flight frequencies are used to generate a flight schedule, which serves as input to the third model — the maintenance schedule design optimization model, which is formulated as a mixed binary-integer non-linear optimization problem. The final output from the integrated model is the optimized maintenance schedule and associated costs. To demonstrate the proposed approach, we present an illustrative example with 3 aircraft and perform a sensitivity analysis to gain further insight into the results.
Investigating How Engineers and Designers Communicate Design Rationale
Authors: Mirabito Yakira , Goucher-Lambert Kosa
Published: November 2022

Design rationale is the explicit documentation of the reasons behind decisions made in designing a product or system. Typically, design rationale is captured using a combination of written reports and oral presentations. Research shows that the structure and information used to communicate rationale significantly influence human behavior. To better understand the influence that communication of design rationale has on the design process, a detailed understanding of the information and techniques used to communicate design rationale needs to be studied. This research aims to identify how engineers and designers communicate this information in written form and the implications that their communication patterns have in engineering design. Eight hundred and forty-six pages of technical engineering design reports from 28 teams representing 116 individuals were analyzed using a mixed-methods approach and then compared across project types. The data were coded into categories using a schema we developed. The findings highlight the range of clarity that designers use in their rationales to support their design actions. Instead of clear, logical reasoning trends, designers often use techniques to fill gaps in design rationale through making assumptions, inserting oneself, or redirecting focus. The results suggest a need for improving design communication in engineering education and practice, perhaps through existing design reasoning frameworks or design rationale capturing tools. By capturing design rationale clearly between human designers, human-AI systems can leverage these findings to increase human confidence in and acceptance of a design agent’s recommendations.
Assessing the Manufacturability of Students’ Early-Stage Designs Based on Previous Experience With Traditional Manufacturing and Additive Manufacturing
Authors: Pearl Seth , Meisel Nicholas
Published: November 2022

As additive manufacturing (AM) becomes more mainstream in industry, the newer design for additive manufacturing (DfAM) considerations must be distinguished from the older design for traditional manufacturing (DfTM) considerations. Designers who wish to maximize additive manufacturing’s potential must reconsider the traditional manufacturing axioms they may be more familiar with. While research has previously investigated the potential influences that can affect the designs produced in concept generation, little research has been done explicitly targeting the manufacturability of early-stage concepts and how previous experience in manufacturing affects this. The research in this paper addresses this gap in knowledge, specifically targeting differences in concept generation due to designer experience with additive manufacturing and traditional manufacturing. In this study, participants were given priming content on DfTM and DfAM considerations and then asked to complete a design challenge centered on concept generation. The participants’ final designs were evaluated for manufacturability as suited for traditional and additive manufacturing. Results show that students with low manufacturing experience levels create designs that are more naturally suited for traditional manufacturing. Additionally, as designers’ manufacturing experience levels increase, there is an increase in the number of designs suited for additive manufacturing. This correlates with a higher self-reported use of DfAM axioms in the evaluation of these designs. These results suggests that students with high manufacturing experience levels make a subconscious decision for which manufacturing process to design for.
Scalar Field Prediction on Topologically-Varying Graphs Using Spectral Shape Encoding
Authors: Ferguson Kevin , Hardin James , Gillman Andrew , Kara Levent Burak
Published: November 2022

Scalar fields, such as stress or temperature fields, are often calculated in shape optimization and design problems in engineering. For complex problems where shapes have varying topology and cannot be parametrized, data-driven scalar field prediction can be faster than traditional finite-element methods. However, current data-driven techniques to predict scalar fields are limited to a fixed grid domain, instead of arbitrary graph/mesh structures. In this work, we propose a method to predict scalar fields on meshes of arbitrary refinement and topology. It uses features that capture shape geometry on a local and global scale as input to a multilayer perceptron to predict solutions to partial differential equations on graph data structures. The proposed set of global features is a vector that concisely represents the entire mesh as a spectral shape encoding. The model is trained on finite-element von Mises stress fields, and once trained it can estimate stress values at each node on any input mesh. Two shape datasets are investigated, and the model demonstrates decent performance on both, with a median R-squared value of 0.75. We also demonstrate the model’s performance on a temperature field in a conduction problem, where its predictions have a median R-squared value of 0.98. By predicting from a simple, yet rich, set of mesh features, our method provides a potential flexible alternative to finite-element simulation in engineering design contexts. Code and datasets are available at: https://github.com/kevinferg/spectral-shape-encoding.
Generative Design of Cyber-Physical-Human System Families: Concepts and Research Issues
Authors: Rosen David W. , Choi Young Mi
Published: November 2022

Cyber-physical-social systems (CPSS) are typically considered as an evolution of cyber-physical systems to include human interactions; further, that interactions among humans through CPSS can lead to emergence of social or community structures and behaviors. Cyber-physical-human systems (CPHS) can be considered as subsets of CPSS that are smart products that offer services to its customer, supported by back-end systems (e.g., information, finance) and other infrastructure. In this paper, initial concepts and research issues are presented regarding the design of CPHS families and generations of these families. Significant research gaps are identified that should drive future research directions. Potential impacts of filling those gaps provide motivation for the development of a design methodology for CPHS. The approach proposed here is a novel combination of generative and configuration design methods with product family design methodology. With this approach, a wide variety of CPHS, including customized CPHS, can be developed quickly by sharing technologies and modules across CPHS family members. Further, the foundation is provided for the evolution of CPHS families; for example, deciding when to add a new family member, when to design a new CPHS family platform, or when the current CPHS family can no longer be supported and a new family developed. The domain of assistive technology is used in this paper to provide an example field of practice that could benefit from a systematic design methodology and opportunities to leverage technology solutions.
Real Driving Route Simulation for Intelligent Traffic Modelling
Authors: Yu Liangyao , Wang Ruoqi , Cheng Yiming
Published: November 2022

With the development of intelligent vehicle driving, the vehicles must be trained through deep learning method. Therefore, the vehicles will be driven on real roads and subjected to traffic and environmental conditions, such as traffic lights, traffic jams, rounds, stops, curves, road condition and gradient. The on-road driving tests make it difficult to predefine beforehand the route, since the conditions are changeable and unpredictable. On the other hand, it is quite time-consuming and expensive. However, the generation of methods and algorithms able to read the main important parameters from the route (speed and gradient profile) would give a twofold benefit: generation and optimization or appropriate routes considering the testing objective, and if a powertrain model available, simulation of vehicle performance and emissions. In such a context, this thesis aims to generate real driving speed profiles based on either Google Maps guidance or GPX experiment data, considering speed limit, curvature and traffic condition. Real driving cycle generation from the on-line platform Google Maps and GPX data shows advantage over traditional experimental data characterization in aspects of cost, universality and convenience. Based on this approach, it is possible to analyze the influence of driver characteristics, curvature and traffic condition on driving behavior, emissions and fuel consumption, supporting in the phase of intelligent vehicle strategy development. The generated profile is compared to real driving recorded GPX data and is verified to be generally realistic.
Scanning electron microscope imaging by selective e-beaming using photoelectron beams from semiconductor photocathodes
Authors: Nishitani Tomohiro , Arakawa Yuta , Noda Shotaro , Koizumi Atsushi , Sato Daiki , Shikano Haruka , Iijima Hokuto , Honda Yoshio , Amano Hiroshi
Published: November 2022

Pulsed electron beams from a photocathode using an InGaN semiconductor have brought selectively scanning technology to scanning electron microscopes, where the electron beam irradiation intensity and area can be arbitrarily selected within the field of view in SEM images. The p-type InGaN semiconductor crystals grown in the metalorganic chemical vapor deposition equipment were used as the photocathode material for the electron beam source after the surface was activated to a negative electron affinity state in the electron gun under ultrahigh vacuum. The InGaN semiconductor photocathode produced a pulsed electron beam with a rise and fall time of 3 ns, consistent with the time structure of the irradiated pulsed laser used for the optical excitation of electrons. The InGaN photocathode-based electron gun achieved a total beam operation time of 1300 h at 15 μA beam current with a downtime rate of 4% and a current stability of 0.033% after 23 cycles of surface activation and continuous beam operation. The InGaN photocathode-based electron gun has been installed in the conventional scanning electron microscope by replacing the original field emission gun. SEM imaging was performed by selective electron beaming, in which the scanning signal of the SEM system was synchronized with the laser for photocathode excitation to irradiate arbitrary regions in the SEM image at arbitrary intensity. The accuracy of the selection of regions in the SEM image by the selective electron beam was pixel by pixel at the TV scan speed (80 ns/pix, 25 frame/s) of the SEM.
Time response measurement of pulsed electron beam from InGaN photocathode
Authors: Sato Daiki , Shikano Haruka , Koizumi Atsushi , Nishitani Tomohiro
Published: November 2022

The photocurrent from a semiconductor photocathode with a negative-electron affinity surface can be arbitrarily controlled by the excitation laser power. Applying this characteristic to a scanning electron microscope allows the probe current to be arbitrarily controlled at any location on the sample. A photocathode with a fast time response is required to control the probe current at high speed. This study used an InGaN photocathode for pulsed electron beam generation and investigated its time response. A pulsed electron beam with 3.8 ns pulse width and 8.1 × 103 A cm−2 current density was observed, and the rise and fall times of the photocurrent were found to be 1.7 and 2.0 ns, respectively. The results show that despite the bottleneck of the time response of the laser power, the InGaN photocathode generates an electron beam that can control the probe current on a pixel-by-pixel for a 270 MHz scan speed.
Sport Fan Motivation: A Comparison of Local, Nonlocal, and Distant National Basketball Association Fans in the United States and China
Authors: Guo Sitong
Published: November 2022

The aim of the current study was to examine the sport motivations of three types of National Basketball Association fans based on their geographic proximity to the team: local fans (i.e., U.S.-based fans of a local team), nonlocal fans (i.e., U.S.-based fans of a nonlocal team), and distant fans (i.e., China-based fans). The author used the psychological continuum model to measure level of psychological involvement with the team in order to determine whether fans were casual, moderate, or loyal. Using one-way analyses of variance and factorial analyses of variance, the author found that Chinese distant fans reported the highest motivation for seven of the nine types of motivation measured. Results also show that geographic locality predicted significant motivational differences among casual and moderate fans but not among loyal fans. The findings have both theoretical and applied implications and call for stronger focus on the influence of locality in the sport industry.