bluuebunny/crossref_metadata_2025_split huggingface dataset:
Hit, Miss, or Error? Predicting Errors in Design Decision Making for Radically Innovative Ideas Using Individual Attributes
Authors: Peng Aoran , Miller Scarlett R. 
Published: November 2022

Abstract
Researchers and practitioners alike agree that for companies to survive and thrive they must develop and support radical innovation. However, these ideas are complex and risky, and not all succeed. Because of this, decision makers are often left to make hard decisions in terms of which ideas move on and which are abandoned. The goal of this paper was to provide pilot evidence to identify the impact of individual attributes on the effectiveness of decision making for radical innovation. Specifically, we sought to identify how individual personality and preferences for creativity impacted the likelihood of students selecting radical ideas using principles from signal detection theory (SDT). To do this, we used data from a previous studies’ of 2252 idea evaluations by student designers and classified these decisions based on SDT to see if we could predict the likelihood of occurrence based on individual attributes: hit (correct identification), miss (Type 1 Error), false alarm (Type II Error), and correct rejection. The results showed that lower levels of risk tolerance resulted in an increased likelihood that a hit occurred. On the other hand, higher levels of neuroticism and motivation resulted in an increased likelihood of a Type I error, or the likelihood that an individual would neglect a good idea that had a high chance of future success. Finally, increased risk tolerance and decreased motivation resulted in an increased likelihood that Type II error occurred, or that an individual would expend resources on an idea with limited likelihood of success. The results of this study can serve as empirical evidence on decision making in radical tasks and provide a basis for future investigations. In addition, these results provide a methodology for studying decision making in innovative design.
Stapler Design With Stacked Tensegrity Mechanisms for Surgical Procedures
Authors: Khanzode Dhruva , Jha Ranjan , Chablat Damien , Duchalais Emilie 
Published: November 2022

Abstract
In this paper, a planar mechanism formed by stacking tensegrity mechanisms has been designed. This mechanism is formed by three segments but the approach can be applied to a larger number of segments. This mechanism is studied to serve as a stapler for laparoscopic rectal cancer surgery where conventional tools cannot be easily accessed. To do this, two identical mechanisms will be used and operated similarly: one to carry the clips and the cutting knife and the second in parallel to allow the closing of the clips by bringing the two mechanisms together. The parameterization of the segments allows a variation of all lengths. Thus, the size of the segments can decrease proportionally from the base to the top, resulting in a tapered shape from the base to the tip like an elephant trunk. The mechanism has linear springs and cables for its actuation. The singularities, as well as the stability of the parallel mechanism, were analyzed using the minimum energy principle. Optimization was also performed to obtain the largest angular deflection for a segment based on a ratio between the size of the base and the moving platform of the robotic system. The result of this work is a family of mechanisms that can generate the same workspace for different stability properties. After optimization, the radius of curvature of the mechanism will be studied to allow insertion into the patient’s belly.
Design Recommendations for Reducing the Environmental Impact of Battery Packs
Authors: Quijano-Ortiz Felipe , Seepersad Carolyn 
Published: November 2022

Abstract
Electrification of the transportation sector is expanding rapidly, and lithium-ion batteries are an essential technology making electromobility possible. Automobile manufacturers currently optimize their battery strategy for fast charge, long range, and safety for the duration of the vehicle’s life. Batteries must eventually be replaced as they degrade and lose performance. While end of life batteries are not useful in electric vehicles, they can be repurposed to work in alternative energy storage products with lower performance. Once they can no longer store energy, they can be recycled to recover valuable metals and reintroduce them into newer products. The environmental impact of batteries differs across the industry since there is a lack of battery design standards. The goal of this work is to study the design choices that facilitate reusability and recyclability of electric vehicle batteries and compile them into a list of design recommendations. The recommendations are derived from published literature, in which design tradeoffs between performance, economics and recycling and reuse are investigated. The purpose of this paper is to synthesize these recommendations and best practices from throughout the published literature and organize them into summary tables that serve as quick-reference design guidelines for the engineer.
Gait Prediction for Prosthesis Design Evaluation
Authors: Morrison Tyler , Su Hai-Jun 
Published: November 2022

Abstract
In this paper, we introduce the key elements of a computational tool and a comprehensive methodology for enabling simulation-informed design of robotic ankle prostheses. Our approach is based on trajectory optimization methods for predicting human walking gait applied to a model of a bilateral lower leg amputee with robotic ankle prostheses. The goal of this simulation tool and design methodology is to provide a means to evaluate the performance of a prosthetic design and its effect on adapting human walking gait before involving human subject studies. The gait prediction problem is formulated as a multi-objective trajectory optimization of a multibody dynamic system within the existing framework of the open-source biomechanics package, OpenSim. Our approach models the effects of a planar human model with legs and torso, Hill-type muscle actuators, a closed-loop linkage for the robotic prosthetic device, and a DC motor dynamics model. To demonstrate the gait prediction process in use for design evaluation, we include a pair of example design evaluation simulations. In the first example, the gait prediction method shows that the initially proposed prosthesis design fails to improve the human effort estimated by cubic muscle excitations. In the second example, after the selection of a different actuator, the gait prediction method shows that the modified design has the potential to relieve some of the effort of walking required from the amputee. These examples combine to demonstrate how our methodology may be useful for design.
Digital Twin Modeling Method for Container Terminal in Port
Authors: Wang Yan , Yang Wenqiang , Zheng Yu , Zhang Lei , Zhang Ziqing 
Published: November 2022

Abstract
With the acceleration of the construction of smart ports, the business process in ports is becoming more and more intelligent. Most container terminals in port are generally more automated than other terminals, so it is easier to promote the informatization construction of automated terminals. Through digital twin technology, a container terminal in port can be simulated into a complete system with different combinations of layout, equipment and technology, which can realize real-time monitoring, optimize business processes and bring huge economic benefits. In short, digital twin technology has become an important factor in promoting the development of container terminal. In this paper, digital twin technology is applied to the business of container terminal. Meanwhile, the business processes of container terminal are sorted out according to production factors, production information and production tasks. Then a digital twin model modeling method for container terminal from the three dimensions of element, behavior and rule is proposed to realize the virtual simulation of container terminal. The modeling process of element model, behavior model and rule model in port is elaborated in detail. Taking the container terminal in Qingdao Port as a case study, a digital twin system architecture of container terminal is studied. Part of the DT modeling process of container terminal in Qingdao Port is provided. The feasibility and effectiveness of the modeling method are verified. At last, some applications of digital twin container terminal are advised.
Design Optimization of Pelvic Prosthesis for Type-1 Resection
Authors: S. Rajaraman , Rakshit Sourav 
Published: November 2022

Abstract
Reconstruction of the pelvic region post the resection of pelvic bone sarcoma is vital for the rehabilitation and restoration of activities of daily living in patients. The prosthesis design should restore maximum functional outcomes for tumors that do not significantly decrease life expectancy. Currently, reconstruction methods use either bone grafts or prostheses. For tumors at regions such as the iliac wing and for young patients, there is minimal chance of bone grafts to remodel into the exact anatomy of the iliac wing. On the other hand, a customized pelvic prosthesis ensures restoration of the anatomical configuration and mechanical strength. A commercially available pelvic prosthesis is solid and is much stiffer than the bone leading to stress shielding effect and higher strains on the intact pelvic bone. This work proposes the design of a lightweight Ti6Al4V pelvic prosthesis for type-I resection due to a sarcoma at the iliac wing, which matches the exact anatomy of the resected pelvic bone. First, a compliance minimization problem subject to walking gait cycle loads with mass constraint equal to the mass of the resected iliac bone is solved using topology optimization. Then the density field from topology optimization is mapped into shell and lattice infills. Prosthesis designs with different lattice structures are subjected to a compression test simulation, and the heterogeneity of lattices on the structural performance of the prosthesis is studied. Thus, a lightweight prosthesis, similar in geometry, stiffness and mass to the natural iliac bone, is achieved with a decrease in stress shielding effect.
A Design Framework for Evolving Cyber-Physical-Social System (CPSS) Based on Force Field
Authors: Zhou Ziqing , Sun Yanwei , Ouyang Chun , Gan Zhongxue , Ming Zhenjun 
Published: November 2022

Abstract
A Cyber-Physical-Social System (CPSS), as an extension of cyber-physical system (CPS), has received considerable attention in recent years both in academia and industry. Compared to CPS, CPSS has great advantages on efficiency, adaption and robustness due to the existence of self-organizing social system. One of the difficulties in the design of CPSS is anchored in the lack of a control mechanism to achieve self-organizing capability while the system is evolving. To address this problem, we propose a design framework for evolving CPSS based on the force field, which is composed of inner force and task force field. In addition to the framework, we present several performance evaluation indicators to quantify the self-organizing capability of the system, including consumption, emergence, and scalability. We test the performance of the framework using a disaster-relief example, which involves the computational control algorithm (cyber system), robot (physical system), and self-organizing swarm (social system). The result shows that based on our framework, the system can automatically evolve from disorder to order, adapt to the changeable environment and successfully finish the task in a very efficient manner.
Data Driven Integrated Design Space Exploration Using iSOM
Authors: Sushil Rashmi Rama , Baby Mathew , Sharma Gehendra , Balu Nellippallil Anand , Ramu Palaniappan 
Published: November 2022

Abstract
Design preferences or targets are typically available at system level. A designer is usually interested in understanding patches of design space at component levels, across different stages and process that corresponds to such system targets or preferences. This demands a thorough design space exploration permitting both forward and inverse designs. Such exploration becomes cumbersome with large variables and complex systems with conflicting goals. Current work proposes using interpretable self organising map (iSOM) as a visual enabler of decision support system for exploring designs to understand the trade off in system targets/goals. The novelty lies in being able to use a visual form to compare greater than three conflicting goals simultaneously while accounting for design variables. The proposed approach is demonstrated using two test problems: i) hot rolling and cooling process chain design for the production of steel rods and ii) head and neck-injury risk evaluations for vehicular crashworthiness. Using the first problem, we demonstrate the capability of iSOM for the solution space exploration of a many-objective steel manufacturing process chain problem to realize the design of a steel product, in the context of a compromise Decision Support Problem formulation. In the second problem, we demonstrate the capability of iSOM for early-stage design space exploration to identify critical injury-risk regions of interest for different car crash scenarios. These two case studies illustrate the capability to carry out a forward and inverse design, by the proposed approach.
A Constraint-Handling Technique for Parametric Optimization and Control Co-Design
Authors: Tsai Ying-Kuan , Malak Richard J. 
Published: November 2022

Abstract
This paper proposes a novel technique for handling constraints in population-based algorithms (e.g., genetic algorithms) for parametric optimization and control co-design (CCD). Constraint boundaries are approximated during optimization using a machine-learning classification approach called a support vector machine (SVM). Population members classified as infeasible are shifted to the predicted boundary of the feasible set, promoting exploration in the most important regions of the search space. A numerical test problem and a case study of an elastic inverted pendulum on a cart are used for benchmarking. The inverted pendulum problem, which features inherently unstable dynamics and control system limitations (i.e., saturation), highlights the relevance of constraint handling in CCD problems. The case study includes constraints to ensure stability and account for controller saturation. Performance and computational cost are compared to the existing parametric optimization technique, Predicted Parameterized Pareto Genetic Algorithm (P3GA). Results show that the P3GA with the newly proposed constraint-handling technique outperforms the original P3GA both qualitatively and quantitatively.
Can We Get an Intervention, Please? The Utility of Teaming Interventions on Engineering Design Student Psychological Safety
Authors: Scarpinella Samantha , Cole Courtney , Ritter Sarah , Mohammed Susan , Jablokow Kathryn , Miller Scarlett 
Published: November 2022

Abstract
Research on psychological safety has been growing in recent years due to its role in promoting creativity and innovation, among other items. This is because teams with high levels of psychological safety feel safe to express ideas and opinions. While we are becoming more aware of the importance of psychological safety in teaming, there is limited evidence in how to facilitate or build it within teams, particularly in an educational context. This paper was developed to respond to this research void by identifying the impact of teaming interventions aimed at improving psychological safety in engineering design student teams. Specifically, we studied two cohorts of students in a cornerstone design class (N = 414 students), one who received a series of video interventions and introduced role playing (intervention) and one who did not (control). These role assignments — referred to as the Lenses of Psychologically Safety — were created to promote key leadership attributes that have been shown to be crucial in facilitating psychologically safe teams. To compare the utility of the intervention, Psychological Safety was gathered at 5 key time points of a multi-week design project. The results identified three key findings. First, the interventions were successful in increasing psychological safety in engineering teams. In addition, the results indicated the utility of the Lenses of Psychological Safety throughout the design process. Finally, the results identified that groups who used these lenses had higher perceptions of Psychological Safety in their teams. Overall, these results indicated that psychological safety can be improved in engineering education through the intervention methods described within.
Novel MEMS Capacitive Sensor Excited at Electrical Resonance for Detecting Helium Based on Changes in Air Electrical Properties
Authors: Mohaidat Sulaiman , Alsaleem Fadi 
Published: November 2022

Abstract
Dry cask storage (DCS) is increasingly used for extended long-term storage of spent nuclear fuel. The canister is vacuum dried and then pressurized with helium to ensure an inert atmosphere and efficient heat transfer. Thus, helium leakage detection plays an important part in ensuring the safety of nuclear waste storage facilities. However, as it is a noble light gas with no order or color, using conventional gas sensing techniques for detecting Helium is a challenge. To overcome this challenge, in this paper we present the working principle of a simple electrostatic MEMS structure to detect Helium in ambient air. The working principle of this novel sensor is based on the decrease in the air die-electric constant due to the presence of Helium. While this change is small, we show that activating the MEMS RLC circuit can significantly amplify the sensor response and hence increase its sensitivity. The sensor response is simulated at different Helium concentration levels using a finite element model. The simulations showed that an electrostatic MEMS sensor operating close to the electrical resonance frequency of an RLC circuit showed different deflection and as such a different capacitance at different levels of helium. A decrease up to 20% of the MEMS deflection was observed at 20% Helium concentration compared to near 0% concentration.
Compact Time Domain NMR Design for the Determination of Hydrogen Content in Gas Turbine Fuels
Authors: Martin Jacob , Downey Austin , Won Sang Hee 
Published: November 2022

Abstract
Low-resolution nuclear magnetic resonance is a tool that has been employed for many years as an effective method for analyzing complex materials in a non-destructive fashion. This work has been aimed at the development of a prototype compact NMR system with the potential to be utilized for simple and rapid in situ measurements of key properties of jet fuels. The compact system consists of a neodymium magnet configuration with a field strength of 0.645 T, custom printed circuit boards, and radio frequency electronics. It is driven by a National Instruments PXI chassis fitted with modules that control the excitation and detection of hydrogen proton resonance in various samples. The current system is suitable for transverse relaxation (T2) studies using the Carr-Purcell-Meiboom-Gill pulse sequence, as it can produce relaxation curves containing thousands of spin echoes. Determination of hydrogen content (mass %), which is strongly correlated to combustion properties of fuels, is the primary area of interest for this study. Utilizing an array of 16 reference samples, a direct correlation between initial signal amplitude and hydrogen density (kmol/m3) was established. This relationship, along with mass density measurements, was used to determine hydrogen content in six different jet fuels. The maximum error between measured and accepted values for the fuels was 0.7%.
Effect of Optimal Geometries and Performance Parameters on Airfoil Latent Space Dimension
Authors: Van Slooten Alec , Fuge Mark 
Published: November 2022

Abstract
Although learning low-dimensional airfoil manifolds can facilitate aerodynamic optimizations, the properties of these latent spaces are not well understood. This paper investigates airfoil manifolds to provide greater insight into the effects of optimized geometry and data set features on latent spaces. Specifically, we investigate if optimized geometries occupy lower dimensional manifolds than non-optimized geometries. We also examine the effect of including target optimization conditions as data set features for a range of latent space sizes. We explore these areas using the UIUC airfoil database and a subset of these airfoils optimized with CBGAN and CEBGAN models. Lower dimensional airfoil manifolds are learned using both autoencoders and principal component analysis (PCA) models. The performance of these models are also compared to each other in ranges of training sample sizes and latent dimension size using mean squared error (MSE) between the original testing samples and the reprojected data constructed from the models as a metric. The results of this study suggest that optimized geometry does not always lie in a lower dimensional latent space as the two data sets were observed to have similar intrinsic dimensionalities. This study further demonstrates that including input parameters used in airfoil coordinate generation as data set features does not necessarily decrease the latent space dimensionality.
Synthetic Fault Mode Generation for Resilience Analysis and Failure Mechanism Discovery
Authors: Hulse Daniel , Irshad Lukman 
Published: November 2022

Abstract
Traditional risk-based design processes seek to mitigate operational hazards by manually identifying possible faults and corresponding mitigation strategies — a tedious process which critically relies on the designer’s limited knowledge. Resilience-based design, on the other hand, seeks to embody generic hazard-mitigating properties in the system to mitigate unknown hazards, often by modelling the system’s response to potential randomly-generated hazardous events. This work creates a framework to adapt these scenario generation approaches to the traditional risk-based design process to synthetically generate fault modes, by representing them as a unique combination of internal component health-states which can then be injected and simulated in a model of the system failure dynamics. The design process may then reduce the risk of unknown internal hazards by iteratively mitigating the effects of these modes. The performance of this approach is evaluated in a model of an autonomous rover, where cluster analysis shows that elaborating the faulty state-space in the drive system using this approach uncovers a wider range of possible hazardous trajectories and failure consequences within each trajectory. However, this increase in hazard information gained from exhaustive mode sampling comes at a high computational expense, highlighting the need for advanced, efficient methods to search and sample the faulty state-space.