bluuebunny/crossref_metadata_2025 huggingface dataset:
Crimes of the powerful in Latin America and the Caribbean: Toward a research agenda
Authors: Atiles Jose
Published: November 2023

The scholarship on crimes of the powerful encompasses a critical examination of social harms, and crimes perpetrated by privately or publicly operated businesses and corporations, the state, international organizations, elites, as well as the state‐mediated administrative and political responses to these crimes. Going beyond state‐centric definitions of crime and deviance, this scholarship emphasizes studying power and the harmful and criminogenic operations of the neoliberal‐capitalism. However, this scholarship has overlooked the systemic examination of these crimes in the Global South, Latin America and the Caribbean, and their impact on racialized, gendered, and other marginalized communities. This article aims to contribute to this scholarship by providing an overview of the current developments in the scholarship on crimes of the powerful and proposing some future research areas for Latin America and the Caribbean. Thus, the article aims to demonstrate that the Latin American and Caribbean experiences with crimes of the powerful can expand our understanding of the social harms generated by powerful organizations and actors and magnify the analytical and methodological reach of this critical scholarship.
Identification of the novel HLA‐A*11:456 allele by next‐generation sequencing
Authors: Liu Zheng , Kang Yiqing , Wang Ziqing , Sun Yamin , Li Jianbin
Published: November 2023

HLA‐A*11:456 has one non‐synonymous nucleotide substitution compared to HLA‐A*11:02:01:01 at position 565 in exon 3.
Full‐length sequence of the novel HLA‐A*02:1103 allele by next generation sequencing in a Chinese individual
Authors: Li Zhen , Zou Hong‐Yan
Published: November 2023

HLA‐A*02:1103 differs from HLA‐A*02:01:01:01 by one nucleotide change at nucleotide 811 in exon 4 from G to A.
Outcome prediction in dogs admitted through the emergency room: Accuracy of staff prediction and comparison with an illness severity stratification system for hospitalized dogs
Authors: Le Gal Alice , Barfield Dominic Martin , Wignall Roseanne Helen , Cook Simon David
Published: November 2023

Objective

To determine whether emergency staff and students can predict patient outcome within 24 hours of admission, comparing the accuracy of clinician prognostication with outcome prediction by Acute Patient Physiologic and Laboratory Evaluation (APPLE)fast scoring and identifying whether experience or mood would be associated with accuracy.

Design

Prospective observational study between April 2020 and March 2021.

Setting

University teaching hospital.

Animals

One hundred and sixty‐one dogs admitted through an Emergency Service were assessed. Where data were available, an APPLEfast score was calculated per patient. An APPLEfast score of >25 was deemed a predictor for mortality.

Interventions

None.

Measurements and Main Results

Emergency staff and students were asked to complete surveys about dogs admitted to the emergency room. All clinicopathological data were available for review, and the animals were available for examination. Data collected included opinions on whether the patient would be discharged from hospital, a mood score, position, and experience in Emergency and Critical Care. One‐hundred and twenty‐five dogs (77.6%) were discharged; 36 dogs (22.4%) died or were euthanized. Two hundred and sixty‐six responses were obtained; 202 responses (75.9%) predicted the correct outcome. Students, interns, residents, faculty, and nurses predicted the correct outcome in 81.4%, 58.3%, 83.3%, 82.1%, and 65.5% of cases, respectively. Of 64 incorrect predictions, 43 (67.2%) predicted death in hospital. APPLEfast scores were obtained in 121 cases, predicting the correct outcome in 83 cases (68.6%). Of 38 cases in which APPLEfast was incorrect, 27 (71.1%) were dogs surviving to discharge. Mean APPLEfast score was 22.9 (± 6.2). There was no difference in outcome prediction accuracy between staff and APPLEfast scores (P = 0.13). Neither experience nor mood score was associated with outcome prediction ability (P = 0.55 and P = 0.74, respectively).

Conclusions

Outcome prediction accuracy by staff is not significantly different to APPLEfast scoring where a cutoff of >25 is used to predict mortality. When predictions were incorrect, they often predicted nonsurvival.
Sonographic features of the uncomplicated postoperative abdomen in dogs treated for pyometra by ovariohysterectomy
Authors: Nilsson Mia K. , Toresson Linda , Ljungvall Ingrid , Nyman Lee Helena T. , McEvoy Fintan J.
Published: November 2023

Pyometra is a prevalent disease in intact bitches and the standard treatment is ovariohysterectomy (OHE). Published descriptions of normal sonographic findings after OHE are currently lacking. The aims of this prospective observational study were to describe and compare postoperative abdominal sonographic features for three timepoints following OHE in a group of dogs with pyometra and an uneventful recovery. A total of 22 dogs had sequential focused abdominal ultrasound examinations on days 1, 4–6, and 10–15 postsurgery. Recorded sonographic features for each examination time point and characteristics of the cervical stump and the mesovarium, size, and echogenicity of medial iliac lymph nodes (MILNs), presence of free peritoneal fluid, and pneumoperitoneum. The cervical stump appeared as a heterogenous area with a hypoechoic center surrounded by hyperechogenic tissue in all dogs. The cervical stump transverse‐sectional area was larger on day 4–6 compared with day 1 and day 10–15 (P = .0009). Mesovarium ligature reactions were identified as heterogeneous and hyperechoic areas with central and/or edge shadowing in all dogs. The size and echogenicity of MILNs and the mesovarium reactions did not significantly differ among time points. Free peritoneal fluid was detected in 45%, 41%, and 9% and pneumoperitoneum in 95%, 82%, and 14% of dogs at sequential time points. Findings from this sample of dogs with an uneventful recovery following OHE due to pyometra can be used to assist veterinarians in interpreting postoperative abdominal ultrasonographic characteristics in future dogs treated surgically for pyometra.
Agri-Food Supply Chain Traceability Supported by a Formal Ontology: A Grain Elevator to Processor Use Case
Authors: Ameri Farhad , Wallace Evan , Yoder Reid , Riddick Frank
Published: November 2023

Traceability of food products to their sources is critical for quick responses to food emergencies. However, having the complete and consistent information needed to quickly investigate sources and identify affected material has proven difficult. Food trace-ability is challenging for a variety of reasons including diversity and heterogenicity of participants, complexity of the supply chain and its processes and lack of a common understanding of steps in a supply chain, and incompleteness of data, and unwillingness of actors to expose information of their internal operations. The objective of this work is to address the traceability challenge by developing a formal ontology that can provide a shared and common understanding of the traceability model across all stakeholders in a food supply chain. In previous research, an ontological approach was adopted to address the traceability problem in the context of a use case related to harvest to on-farm storage activities. This work extends the Supply Chain Traceability ontology by introducing additional critical tracking events including transform event, sampling event, observation event, custody change event, and ownership change event in the context of a scenario involving shipments of commodity grain from a primary grain elevator to a processor of grain such as a feed manufacturer. A knowledge graph is generated based on a simulated dataset and the ontology is validated through query, reasoning, and visualization conducted in the RDFox environment.
Orientation Optimization With Topological Derivative for Anisotropic Materials With Rotational Symmetry
Authors: Noda Masaki , Matsushima Kei , Yamada Takayuki
Published: November 2023

This paper proposes a method for optimizing the orientation of multi-directionally reinforced materials that exhibit rotational symmetry, such as woven CFRP sheets or laminated CFRP sheets. The orientation is represented in a “relaxed” Cartesian format, and symmetry modifications are employed to prevent overlapping design variables for identical material constants. The optimal orientation is estimated using topological derivatives for anisotropic materials, and the orientation distribution is subsequently optimized based on this estimate. The proposed method is validated using a range of numerical examples of elasticity problems.
Improving Nonuniform Utilization of Li-Ion Pouch Cells Using Tapered Electrodes Through Calendering
Authors: Cho Changik , Kelley Seth , Tylka Joseph G. , He Miao , Nandola Naresh N. , Rahn Christopher D.
Published: November 2023

Large format lithium-ion pouch cells can have fewer tabs, less packaging material and interconnects, and lower cost but nonuniform material utilization reduces the achievable power and energy densities. The impedance varies across the cell with active material farthest from the tabs having the highest impedance. As a result, these underutilized parts of the cell do not become fully charged or discharged, especially at high current rates, and the energy storage capability of the cell is not fully realized. The current collector thickness can be thickened to increase material utilization, but cost and energy density suffer. In this paper, we propose and simulate linearly tapered electrode coatings to decrease thickness (and increase impedance) in low impedance areas, improving the impedance uniformity and material utilization across the cell. The taper is introduced in the calendering process, by tilting the rollers to change thickness and porosity across the width of the cell. A multiple particle (MP) model is developed and validated in COMSOL to optimize the slope of the taper based on Brute-force algorithm. Higher impedance near the tab balances the higher impedance in the current collector away from the tab. The analysis results show that a 10% linearly tapered positive electrode can improve uniformity by 8 times with 3C charging and increase capacity by 13% with 5C charging.
Topology Optimization of Rarefied Gas Devices With Discrete Velocity Method
Authors: Guan Kaiwen , Matsushima Kei , Yamada Takayuki
Published: November 2023

This paper presents a topology optimization method for rarefied gas devices. Based on the discrete velocity method, which is a conventional iterative scheme to solve the Boltzmann equation, we propose an extension to include a pseudo design density that characterizes distribution of materials in the design domain. Using a discrete version of the optimization problem, we obtain a system of discrete adjoint equations, which can be solved by recording necessary information during the discrete velocity method calculation. Design sensitivity to maximize (or minimize) an objective function can be calculated from the solution of the adjoint equations. Validity of the optimization method is demonstrated through optimization of a bent pipe.
Shape-Based Force Estimation Method for Guidewire Navigation in Neurointervention Surgery
Authors: Xu Yang , Golden Jacob , Mangla Ronin , Wu Karen , Mangla Sundeep , Masur Sean , Shi Yong
Published: November 2023

A study is currently being conducted on a robotic system designed to assist surgeons during neuroendovascular interventions. To navigate the robotic-assisted system through the vascular artery network, a guidewire is employed. However, the existing commercial robotic system lacks a force feedback mechanism, which could potentially pose safety concerns due to the contact force or friction between the guidewire and the vascular artery. Since the entire procedure is captured by X-ray imaging, it is feasible to estimate the force exerted on the artery by analyzing the shape of the guidewire. This article proposes a force estimation method that relies on the changes in the guidewire’s shape during the contact process. By examining its curvature, the contact force and friction force of the guidewire can be calculated. The turning points on the curvature curve enable the determination of the contact positions for multi-point loading. The effectiveness of the proposed shape-based force estimation method is validated through Finite Element Method (FEM) simulations, which demonstrate a good approximation. The error between the actual and estimated forces at most contact points is approximately 10%. Furthermore, the proposed method is further substantiated through an experimental test, where it is observed that the accuracy of curvature calculation is directly linked to the contour fitting process. Improved results in curvature calculation are achieved by employing more points for each segment fitting.
The Economic and Environmental Sustainability of Additive Manufacturing for Tooling: A Case Study on Using Laser Powder Bed Fusion for Making Injection Molding Tool Inserts
Authors: Liao Jiankan , De Kleine Robert , Powell Jason , Cooper Daniel
Published: November 2023

Laser powder bed fusion (L-PBF) can make injection molding tools with conformal cooling channels that can reduce plastic part warpage and production cycle times. In this study, we define the design space in which L-PBF tools are economically and environmentally beneficial compared to traditional toolmaking methods. We develop mechanistic production cost, lead time, and cradle-to-grave life cycle assessment models of the cumulative energy demand (CED) and greenhouse gas (GHG) emissions associated with injection molding (IM) tool inserts made from tool steel using a Renishaw AM500Q L-PBF machine versus conventional 3-axis machining of equivalent beryllium copper (BeCu) inserts. These models are applied to a set of seven tool inserts used to make glass fiber reinforced plastic engine intake filter housings. The models are informed using insert build time and electrical power measurements on the L-PBF machine. Across all the inserts, using L-PBF was found to be slower, costlier, and more energy and emissions intensive than conventional mold making. However, benefits from reduced IM cycle times and plastic part rejection rates when using the L-PBF inserts can lead to whole life cycle improvements. We calculate how the breakeven plastic part production volumes (above which L-PBF inserts are faster, cheaper, and more environmentally benign over the life cycle) change for varying cycle time and part reject rate improvements. Assuming the L-PBF inserts result in 15% and 2.5% reductions in cycle time and part rejects respectively, then the breakeven production volumes are 60,000 parts for lead time, 4,000 parts for CED and GHG emissions, and greater than the likely mold lifespan (100,000 parts) for cost.
A Proposal of an Efficient and Accurate Methodology for Accounting the Static Transmission Error in Epicyclic Gearset
Authors: Bruzzone Fabio , Rosso Carlo
Published: November 2023

Epicyclic gearsets are commonly used in a variety of industrial applications and while these systems offer many advantages they can also suffer from dynamic problems such as vibration and noise due to their complex geometry and multiple contact points. One important factor in understanding and mitigating these dynamic problems is the calculation of Static Transmission Error (STE). By accurately calculating STE, engineers can gain insights into the behavior of the gear system and make informed decisions regarding design changes and operational parameters to improve performance and reduce dynamic issues. Therefore, the calculation of STE is an essential tool in the design and analysis of epicyclic gear systems. In this paper a simplified but accurate methodology is proposed for the rapid computation of this important parameter. The foundation stiffness of the internal ring gear is first analyzed using a parametric Finite Element (FE) model and an analytical expression is derived. In addition, the engagement stiffness is accurately computed and used as connection element between gears. A schematization of the system using a limited number of degrees of freedom for each component is then presented along with the procedure to compute the STE using the proposed approach. Results are then obtained for a simple test case and conclusions are drawn.
Design and Nonlinear Analysis of 2-Body Centrifugal Pendulum Vibration Absorber for Suppression of Multiple Harmonic Frequencies in Torsional Vibration of Rotor System
Authors: Zhou Xingyu , Inoue Tsuyoshi , Heya Akira
Published: November 2023

The centrifugal pendulum vibration absorber (CPVA) is widely used as an effective vibration suppression device. Most of the CPVAs that have been studied so far are composed of a single mass point or a rigid body (1-body CPVA). They are effective in reducing the vibration of a single-order component. This property makes them highly suitable for using in gasoline-powered vehicles. The development of electric vehicles (EVs) and hybrid electric vehicles (HEVs) has introduced complex torsional vibrations to the vehicle’s rotational shaft. As a result, it has become necessary to suppress vibrations of different order components simultaneously. Therefore, in this study, a rigid body model for a 2-body CPVA is proposed to suppress rotor system vibrations with multiple order components. A multi-body dynamics (MBD) analysis model is constructed to analyze a rotor system equipped with the 2-body CPVA. Furthermore, tuning equations for the 2-body CPVA to suppress multiple order components are derived, and the shape of the 2-body CPVA is investigated to further enhance its effectiveness. The designed 2-body CPVAs are installed on the rotor system, and numerical analysis is performed using the direct integration method and shooting method. Subsequently, it is confirmed that the 2-body CPVA is effective in reducing torsional vibrations with two-order components. Furthermore, it demonstrated the superiority of one 2-body CPVA in suppressing vibrations of multiple order components compared to two different 1-body CPVAs.
VariableTypography: Artificial Intelligence Augmented Reading Experience
Authors: Shi Shuhui , You Weitao , Han Kaixin , Song Jinyu , Sun Lingyun
Published: November 2023

Nowadays, digital information has overloaded and reading time has been fragmented due to the significant development of digital devices, such as phones, computers, etc. Optimizing the reading experience has become a challenge. Prior studies on Chinese digital reading have primarily focused on uniform and consistent typography settings. Nevertheless, this standard typography is not applicable to real-world scenarios. Usually, people leverage different typographical variables to emphasize part of a sentence to highlight key information. Inspired by this, we propose a novel screen reading method, dubbed VariableTypography (VT), that highlights key information in various typographic ways by utilizes artificial intelligence tool ChatGPT to identify key information in the text, aiming to enhance the reading experience. In the field of artificial intelligence, significant progress has been made in natural language processing, resulting in innovative tools like ChatGPT. With its low operating threshold and the ability to use natural language for prompt engineering, ChatGPT has attracted widespread attention. In this study, we incorporated ChatGPT into a real-world reading scenario and integrated it with VT to examine its potential for assisted reading. To evaluate the effectiveness of VT, objective and subjective experiments were conducted in naturalistic remote settings with 70 participants using their smartphones in daily Interlude Reading scenarios. The results show that our proposed VT effectively improved readers’ subjective information acquisition while significantly reducing cognitive load during reading, without affecting the original reading efficiency. Additionally, VT is evidenced with good subjective acceptance. We hope that our findings will shed light on the field of digital Chinese readability.
A Digital Twin Assisted Framework for Quality Assurance in Mould Manufacturing
Authors: Böttjer Till , Ramanujan Devarajan
Published: November 2023

This paper discusses a Digital Twin framework for quality assurance in mould manufacturing consisting of the physical and virtual manufacturing process connected by a data lake. To this end, we present the DT framework and demonstrate its applicability at the example of ensuring the quality of milling features on a mould tool part. For the demonstration we build two cascaded models, a tool wear state model and an insert part quality model. The tool wear state model assigns a label corresponding to the tool wear state using cutting force measurements. The part quality model then uses the tool state and engineering data to classify quality of individual milling features on the mould tool part. To develop the cascaded models, we conducted a case study which experimentally collected machine controller data and cutting forces using a Kistler dynamometer for machining a test part on a Makino V33i three-axis vertical milling machine. The test part contains mould tool specific features and is made of hardened tool steel (46-52 HRC). Three milling tools were repeatedly used to machine test parts and gather data at different tool wear states. For validating the part quality model, we further collected metrology data from a coordinate measurement machine. Results show that the developed cascaded models are able to monitor the tool wear stage and to classify quality deviations with a weighted F1 measure of 89.0%.
Electric Machine and Battery Sizing for Hybrid Electric Heavy Duty Vehicles
Authors: Hegde Shailesh , Bonfitto Angelo , Castellanos Molina Luis M.
Published: November 2023

Medium- to heavy duty vehicles make a major contribution to freight transportation and are expected to keep growing continuously. In order to reduce the CO2 emissions and avoid climate change, ambitious regulations have been introduced. To fulfill these requirements, aerodynamic drag and vehicle mass reduction, more efficient conventional internal combustion engines (ICE) and alternative powertrain architectures are being developed. Hybrid electric vehicles (HEVs) are one of the solutions with the highest potential for fuel economy improvement, provided that all the subsystems at play are correctly sized. In this work, a power based approach is used to define the electric machine (EM) and battery size by considering the power request in braking and technology constraints in the battery and power electronics. The hybrid layouts under study are P0, P1, and P2 parallel applied to a 35 Ton vehicle whose model is developed in a Matlab/Simulink environment using the velocity profile from the European Union Commission simulation tool (VECTO). The Equivalent Consumption Minimization Strategy is used as an energy management system to provide optimal torque references to ICE and EM. The regional delivery and long haul driving cycles, which are the official driving cycles for the certification of heavy duty vehicles in the EU, were used to evaluate the performance of hybrid solutions with respect to conventional pure ICE.
Robotic Exoskeleton Glove System Design and Simulation for Patients With Brachial Plexus Injuries
Authors: Xu Wenda , Guo Yunfei , Ben-Tzvi Pinhas
Published: November 2023

This paper presents a novel robotic exoskeleton glove system for patients who suffer from brachial plexus injuries. The robotic exoskeleton glove systems takes advantage of our previously designed rigid coupling hybrid mechanism (RCHM) concept that was used for the index finger mechanism design of the exoskeleton glove. The finger mechanism utilizes the single degree of freedom case of the RCHM that combines a rack-and-pinion mechanism and offset-slider-crank mechanism as the rigid coupling mechanism. The serial and special arrangement enables the design of each finger mechanism of the glove with reduced degrees of freedom while more closely imitating the human hand motion. The exoskeleton glove is designed to assist patients with hand disabilities in daily activities, and as such, it is optimized to be compact, lightweight, and portable, and includes modulated electronics for everyday use. The control system contains low-level motor control and high-level human-machine interface components, which enable safe and intuitive control of the exoskeleton glove, thereby enhancing the user’s ability to perform various daily activities. A high-level user interface voice activation is also integrated into the system. The paper also describes a simulation environment that was developed using MATLAB Simscape and was designed to test out and optimize different control algorithms.
Coupling Simulated Annealing and Homogenization to Design Thermally Conductive Hybrid Lattice Support Structures for LPBF
Authors: White Lisha , Liang Xuan , Zhang Guanglu , Cagan Jonathan , Zhang Yongjie Jessica
Published: November 2023

When designed effectively, support structures for Laser Powder Bed Fusion (LPBF) quickly dissipate heat and mitigate part distortion without driving up excessive costs. Lattices, composed of individual unit cells strategically arranged to achieve a desired function, are a promising solution as support structure. Prior research utilizing gradient-based optimizers to design lattice support structures for heat dissipation pose challenges regarding limited design exploration and non-differentiable design variables. Non-gradient-based optimizers are an alternative solution but are known to be too slow compared to gradient-based optimizers and have not yet been applied to optimize the heat dissipation of lattice support structures. Thus, this paper presents a computational framework that facilitates the design of lattice support structures with stochastic optimization to maximize heat dissipation. Simulated annealing (SA) is utilized to quickly optimize the distribution of three commonly employed unit cells while adhering to user-defined manufacturing constraints. By incorporating both stage-dependent actions and homogenization approximation with SA, a broader exploration of the design space is accomplished without compromising computation time. The framework is validated through the case study of a cantilever beam by generating optimal hybrid lattice support structures with about 16% better heat dissipation than the uniformly distributed benchmark design with manufacturing constraints satisfied.
Frequency Response Based Optimization of an Aircraft Hydraulic Pump Support Structure
Authors: Kersten Simon T. , Mechefske Chris K.
Published: November 2023

Free-size optimization is an effective method for determining the optimal thickness of the elements in a finite element model given a set of constraints and objectives. This work aims to show that size optimization can be used as a tool to reduce the structural vibrations transmitted from non-structural components on-board an aircraft into the cabin. A test structure of a hydraulic pump support frame is analyzed using a frequency response analysis. The output velocity is measured for three independent dynamic input loads across a 20–4000 Hz bandwidth. The maximum frequency response velocity for each input load was used to define the upper bounds of the velocity for the optimized model. The design space had a minimum thickness equal to the original thickness and a maximum thickness of 1.5 times the original thickness. The objective was to determine the optimal locations for new material to be added, so that the original design was not significantly changed. This was done to ensure the structural integrity of the frame and increase the ease of implementing the design while still reducing the transmission of structural vibrations. The optimized model showed an average reduction of 6% in the maximum frequency response velocity for the three loading directions, while increasing the mass by 9%.
Study on Driver’s Preview Distance Based on Driving Simulator Tests
Authors: Gobbi Massimiliano , Mastinu Giampiero , Milivinti Massimiliano , Previati Giorgio , Ríos Hidalgo Daniel
Published: November 2023

Several simplified driving models used nowadays assume that the drivers’ preview distance is mainly dependent on the vehicle speed. The scope of this paper is to analyze the behavior of a sample of drivers during a lane change test, evaluating specifically the evolution of their preview distance.

In order to undergo this study, the tests are performed in a DiM400 dynamic driving simulator installed at Politecnico di Milano. The preview distance is measured while performing a specially designed test, divided in straight and double lane change sections, at a constant speed of 80 km/h. Furthermore, a wearable eye tracker is used to acquire the data from the drivers’ eyes. Finally, a simple method to estimate the preview distance under the testing conditions of this project is undergone.

Opposite to what it is mainly stated in the literature, it can be observed a clear variation of the preview distance along each of the tests performed in the simulator. Drivers seem to increase it when driving straight, while they reduce it considerably to perform the double lane change maneuver. The algorithm developed in this paper provides an easy estimation of this quantity, although several limitations must be taken into account.
Exploration of Building Clustering Potential With Energy Storage in New York City
Authors: Kaminski Gregory , Odonkor Philip
Published: November 2023

The adoption of distributed energy resources has increased in recent years due to decreasing implementation costs and increasing regulatory incentives to reduce energy consumption. This trend has been driven by a surge in energy consciousness and the availability of energy-saving products and technologies. Many energy consumers are also electing to use battery systems to store energy locally, further reducing reliance on the electrical grid and maximizing the benefits of distributed energy systems. For owners of multiple buildings, or multiple owners willing to share the operational cost, building clusters may be formed to more effectively take advantage of these distributed resources and storage systems. However, determining what makes a “good” building cluster when implementing these systems in existing buildings is a challenge. Additional challenges are presented when geographical proximity of these buildings is considered. Using metrics derived from comparison of unique five-building clusters from a population of sixteen stock buildings with a given distributed energy resource (in this case, a solar photovoltaic panel array) and energy storage system, we apply performance ranking information to a population of actual building data from New York City. In doing so, the authors aim to build upon the concept of logical building clusters with consideration of physical building location to develop an understanding of which geographic areas present the greatest opportunity for clustering.
Proposed Design for Electromechanical Telescoping Actuator to Replace Hydraulics in Extreme High Force and Long Stroke Applications
Authors: Sleight Crawford Carmen , Smyk Mariia , Cheung Sophia , Coughran Doug , Costello Jeffrey , Liang ZhiYi , Winter Amos G.
Published: November 2023

The increasing demand for electrification in various industries has led to the need for new technology to evolve and support this shift. Manufacturers in the industrial and military market are exploring the electrification of its hydraulic actuation devices in order to improve efficiency, sustainability, and maintenance. However, replacing hydraulic actuators with electromechanical alternatives presents a significant challenge, particularly in high force, high stroke applications that require a stroke length of 2.4 m (8 ft) to 6.7 m (22 ft) and the delivery of 150 kN of force. In this paper, we present the design and scaled-prototype of an electromechanical telescoping actuator architecture that can meet these demanding requirements. The proposed design relies on screw and nut mechanisms that are engaged simultaneously in a telescoping manner and is able to achieve more than double extension of its collapsed length. Our group was able to successfully develop and evaluate the design and build a scaled-down prototype that could likely serve as a direct replacement for currently used long-stroke high-force hydraulics. The prototype was able to achieve extension from 17 cm (7 in) to 49 cm (19.2 in) with 10 s cycle time, and is able to lift at least 28 N (6.3 lbf). This work was done in partnership with Oshkosh Corporation.
Animated Point Clouds Real-Time Rendering for Extended Reality
Authors: Piazzolla Pietro , Rossoni Marco , Pozzi Matteo , Colombo Giorgio , Gribaudo Marco
Published: November 2023

Point cloud 3D models are becoming more and more popular thanks to the spreading of scanning systems employed in many fields, like autonomous vehicles and robotics. When used for rendering purposes, point clouds are usually displayed with their original color acquired at scan time, without considering the lighting condition of the scene where the model is placed. This leads to a lack of realism in many contexts, especially in the case of animated point clouds employed in eXtended Reality applications where it would be desirable to have the model reacting to incoming light and integrating with the surrounding environment. This paper proposes the application of Physically Based Rendering (PBR), a rendering technique widely used in Real-Time Computer Graphics applications, to animated point cloud models for reproducing specular reflections, and achieving a photo-realistic and physically accurate look under any lighting condition. Firstly, we consider the extension of commonly used animated point cloud formats, to include normal vectors, and PBR parameters (such as roughness and Metalness), as well as the encoding of the animated environment maps required by the technique. Then, an animated point cloud model is rendered with a shader implementing the proposed PBR method. Finally, the proposed PBR pipeline is compared to traditional renderings of the same point cloud obtained with commonly used shaders, under different lighting conditions in different environments. It will be shown how, using the proposed PBR method, the point cloud better integrates visually with its surroundings. Moreover, it will be shown that using this rendering technique it is possible to render different materials, by exploiting the features of PBR and the encoding of the surrounding environment.
High-Speed Schlieren Imaging of Shock Waves for the Study of Tympanic Membrane’s Response
Authors: Oliveira Luiz Jonathan , Alipanahi Anahita , Cheng Jeffrey Tao , Rosowski John J. , Furlong-Vazquez Cosme
Published: November 2023

The mechanics of tympanic membrane (TM) fractures resulting from exposure to high-pressure blasts are not yet fully understood. To investigate TM responses to such events, shock tubes can be utilized as loading devices. The effective use of these devices requires proper characterization. One appropriate method for visualizing the shock waves produced by a shock tube is high-speed Schlieren imaging, which can provide both qualitative and quantitative information. In this paper, we present a shock tube integrated with a high-speed Schlieren system and high-speed dynamic pressure transducers. The highspeed Schlieren system allowed us to observe the shock waves emitted from the shock tube and characterize the Mach number of each wave. The flow structures generated from the tube exit were identified and synchronization between Schlieren images and pressure data was achieved. The shock tube showed good repeatability and generated supersonic blasts capable of rupturing TM samples, with a shock Mach number of up to 1.4. The versatile and cost-effective nature of the shock tube opens new possibilities for understanding the real-time mechanics of TM fractures and investigating their dynamic response in the future, when even more sophisticated quantitative optical techniques will be used to investigate the TM’s behavior in these conditions.
Automating Style Analysis and Visualization With Explainable AI - Case Studies on Brand Recognition
Authors: Chen Yu-Hsuan , Kara Levant Burak , Cagan Jonathan
Published: November 2023

Incorporating style-related objectives into shape design has been centrally important to maximize product appeal. However, stylistic features such as aesthetics and semantic attributes are hard to codify even for experts. As such, algorithmic style capture and reuse have not fully benefited from automated data-driven methodologies due to the challenging nature of design describability. This paper proposes an AI-driven method to fully automate the discovery of brand-related features. Our approach introduces BIGNet, a two-tier Brand Identification Graph Neural Network (GNN) to classify and analyze scalar vector graphics (SVG). First, to tackle the scarcity of vectorized product images, this research proposes two data acquisition workflows: parametric modeling from small curve-based datasets, and vectorization from large pixel-based datasets. Secondly, this study constructs a novel hierarchical GNN architecture to learn from both SVG’s curve-level and chunk-level parameters. In the first case study, BIGNet not only classifies phone brands but also captures brand-related features across multiple scales, such as the location of the lens, the height-width ratio, and the screen-frame gap, as confirmed by AI evaluation. In the second study, this paper showcases the generalizability of BIGNet learning from a vectorized car image dataset and validates the consistency and robustness of its predictions given four scenarios. The results match the difference commonly observed in luxury vs. economy brands in the automobile market. Finally, this paper also visualizes the activation maps generated from a convolutional neural network and shows BIGNet’s advantage of being a more human-friendly, explainable, and explicit style-capturing agent.
Finite Element Simulation of Gleeble Testing Toward Thermomechanical Analysis of Alloy Materials
Authors: Xu Dong , Zhang Kevin J. , Frame Lesley D. , Kim Jeongho , Tang Jiong
Published: November 2023

This study investigates the mechanical behavior of alloy materials at high temperature (750°C) by correlating finite element simulation with the experimental testing using Gleeble system. Traditionally, such characterization is challenging due to the measurement challenges in experimentation. In this research the Gleeble 3500 physical simulator is used to collect experimental data under specific temperatures and strain rates, providing necessary data for parameter identification. In order to accurately analyze the underlying physical process, the temperature gradient of the specimen during Gleeble testing needs to be considered. As such, a comprehensive finite element based analysis is established to study the temperature/stress distribution during the testing process. An empirical constitutive model, the Johnson-Cook constitutive relation, is adopted to characterize the mechanical behavior of metal materials at high temperatures and high strain rates. Parameters from reference material are used to facilitate initial analysis, which are subsequently modified empirically to examine the parametric influence. To reduce the computational cost, simulation simplification is explored. Through analyzing the predicted results of stress and force, this study provides insights to the importance of developing high fidelity finite element simulation that can authentically duplicate the actual physical process. The analysis formulation will play key role in facilitating optimized identification of material parameters utilizing Gleeble testing data.
An Integrated Approach to Designing Robust Turbocompressors on Gas Bearings Through Surrogate Modeling and Constrained Multi-Objective Optimization
Authors: Massoudi Soheyl , Picard Cyril , Schiffmann Jürg
Published: November 2023

Designing turbocompressors is a complex and challenging task, as it involves balancing conflicting objectives such as efficiency, stability, and robustness against manufacturing deviations. This paper proposes an integrated design methodology for turbocompressors supported on gas bearings, which utilizes surrogate models and ensemble learning with artificial neural networks. The proposed approach addresses the limitations of nominal and separate optimizations by integrating all relevant design aspects into a single optimization problem. A multi-objective optimization is carried out, considering four objectives and over twenty constraints, including robustness against manufacturing deviations of the radial and axial bearings in terms of stability, load capacity, and efficiency, as well as robustness against performance metric gradients. The proposed methodology maximizes the compressor’s range in speeds and mass flow, while also maximizing the signal-to-noise ratio of the isentropic efficiency over the compressor map. Additionally, the approach maximizes system efficiency, taking into account component losses and isentropic efficiency of the compressor. To enable rapid and automated integrated design, the methodology reduces the compressor representation to a fully cylindrical representation. The study finds that the proposed methodology has the potential to significantly enhance the overall performance of turbocompressors in terms of efficiency, stability, and robustness. The methodology eliminates the need for sequential and iterative design steps, providing an optimal starting point for higher representation of the system with CFD and finite elements study. Furthermore, the proposed methodology has broad applications, including the optimization of other complex and interdependent systems in various fields. This study highlights the crucial role of a comprehensive and integrated approach to turbocompressor design and provides a valuable framework for future research in this area.
Predicting Vehicle Motion in Shallow Water with Data-Driven Hydrodynamics Model
Authors: Yamashita Hiroki , Martin Juan E. , Sugiyama Hiroyuki , Tison Nathan , Grunin Arkady , Jayakumar Paramsothy
Published: November 2023

In this study, a numerical procedure for predicting vehicle mobility in shallow water is proposed with the data-driven hydrodynamic force and moment model. To this end, the high-fidelity coupled CFD-MBD model is developed to characterize the hydrodynamic loads exerted on the vehicle in shallow water and used to generate the training dataset for the proposed data-driven model. The neural networks are called from the MBD mobility solver every time step to determine the hydrodynamic loads, given the current vehicle motion states and water conditions, allowing for predicting the transient responses of the vehicle interacting with shallow water. It is demonstrated by several numerical examples that the complex vehicle-water interaction behavior was accurately predicted by the proposed data-driven hydrodynamics model while achieving a substantial computational speedup.
Let’s Chat If You Are Unhappy – The Effect of Emotions on Interaction Experience and Trust Toward Empathetic Chatbots
Authors: Liao Ting , Yan Bei
Published: November 2023

Chatbots are now prevalent in obtaining information and executing tasks on behalf of human users. While the design community has paid more attention to streamlining user-chatbot interactions, the existing literature has not thoroughly examined social elements such as emotions and understood how emotions influence user interaction and trust in chatbots. This study proposes to test how participants perceive an empathetic chatbot versus a non-empathetic one under various emotional states (i.e., positive, neutral, negative) when the chatbot facilitates conversations for student advising via an online platform. The study shows the importance of presenting empathetic cues in the design of chatbots or other intelligent agents. The empathetic behavior of the chatbot improves participants’ trust and perception of the chatbot’s performance. The improvement is more salient to people with negative emotions than people who feel neutral or positive. This interaction effect is explained by people’s perceived effort of the chatbot during the interaction with people, even though the chatbot is a technological agent that acts based on algorithms. The results suggest that people attribute human qualities to chatbots in social interaction and highlight the emotional needs of people who experience negative emotions. Therefore, design efforts need to be designated according to people’s dynamic emotional states.
Selectively Stiffened Integrated Composite Hinge
Authors: Klocke Philip , Skinner Mitchel , George Andy , Magleby Spencer
Published: November 2023

Fiber-reinforced composites have potential advantages for manufacturing origami arrays. However, methods for manufacturing large origami arrays using composite materials are complex, time-consuming, and expensive. This research proposes two processes for synthesizing origami-based arrays, each made using fiber-reinforced composites and requiring only a single layup. The overarching principle used in these processes is to selectively modify the stiffness in the composite array, thus forming both the panels and hinge lines of an origami array. The feasibility of using these processes to produce deployable carbon fiber arrays is then demonstrated.
Design of Unhinged Compliant Mechanism to Enable Bistable Segments in Continuum Robots
Authors: Niazi Muhammad Umer Khan , Mehmood Usman , Choi Jaesoon , Moon Youngjin
Published: November 2023

Continuum robots have seen increased utilization in various fields such as aerospace, rescue operations, human interaction, and especially medicine. More specifically, in medicine, continuum robots have enabled minimally invasive surgeries and faster patient recovery time. However, the design of continuum robots needs to be improved, especially by enhancing or incorporating characteristics that improve functionality across various applications. This paper explores different mechanisms, including bistable, compliant, and lamina emergent mechanisms, to achieve these design goals. Specifically compliant bistable mechanisms which can store energy when deformed and utilize this energy to transition from one state to another have shown significant promise for the design of continuum robots. In this paper we explore the characteristics and functions associated with compliant bistable mechanisms and their potential integration in device designs, we review the design process for adapting compliant bistable mechanisms to continuum robots, highlighting the challenges and considerations involved. We also present two examples of applications to continuum robot designs that demonstrate the potential of compliant mechanisms for creating varied functionality for a number of applications. By understanding the capabilities and limitations of compliant mechanisms, we can advance the design of continuum robots, which presents a significant opportunity for innovation and progress in the field of medical device design.