Hub Design Research Articles

Willingness to pay for shared mobility hubs: a stated choice joint-survey in four European cities

Abstract This paper aims to assess the relative importance of different shared mobility hub design elements. A standardised survey was developed and applied among users and residents in different areas, including a stated preference experiment, to examine trade-offs between integration dimensions and the willingness-to-pay for different attributes of hubs. The results underscore a disparity between the attributes most valued by respondents and their willingness-to-pay for them, which holds significance in the planning and functioning of mobility hubs. Although elements such as information and digital integration were indicated as being prerequisites for a successful shared mobility hub, respondents are not willing to pay for it, indicating that these would have to be arranged by the government and/or transport operators. Respondents are more willing to pay for shared mobility and public transport within walking distance from one another or for placemaking strategies (such as services or landscaping), which are more evident elements related to the physical integration (and design) of hubs.

What do parents want? Relevant content and formats for resources to address issues of racism, antiracism, and xenophobia with youth

Diverse U.S. parents seek to engage in conversations about racism and immigration injustices with their children. To inform the design of a free resource hub and curriculum, we interviewed 62 parents of 3–17 year olds across 6 demographic categories (Asian/Asian American, Black, Latinx, Multiracial, Native American, White). We explored the question: “What content (substance and format) would be useful for parents in addressing issues of race, racism, and immigration with their children?” Analyses yielded multiple cross-cutting themes addressing both the substance and format of resources parents viewed as important for addressing these topics. Four content themes include: (a) Desire for Credible, Nonpartizan Information; (b) Testimonials as Windows and Mirrors; (c) Age Appropriateness; and (d) Systems and Intersectionality. The two main format themes to emerge were: (a) Multiple Modalities and Sources and (b) Interactive and Ready-made. Implications for the development of ethnic-racial and antiracism socialization interventions and other resources are discussed.

Design and Prototyping of a Novel Triple Lumen Photo-Angioplasty Device: Lumi-Solve-T.

A triple lumen iteration of the novel photo-angioplasty drug eluting balloon catheter (DEBc) Lumi-Solve may be compromised by guidewire shadow (GWS)-mediated attenuation of balloon surface drug activation. The current study aimed to design and evaluate a novel triple lumen prototype, designated Lumi-Solve-T, to circumvent these issues. Effects of guidewire shadowing (GWS) on vascular smooth muscle cell (VSMC) proliferation was evaluated using the MTT assay. In-silico modelling of GWS in the novel triple lumen design was conducted. Computer-aided design (CAD) and finite element analysis (FEA) contributed to development of a novel triple lumen catheter. 3D printing of rudimentary and refined prototypes of the catheter together with assembly of a novel fibre-optic (FO) complex and ex-vivo evaluation of the triple lumen device, Lumi-Solve T, was also performed. GW insertion in a parallel triple lumen FO: GW port orientation demonstrated significantly reduced inhibition of VSMC proliferation after 7 days confirming the need for an alternative triple lumen design. In-silico analysis identified a multi-fibre FO sleeve design supported uniform, radial and uninterrupted UV365nm light transmission to the angioplasty balloon surface. FEA confirmed a multi-fibre FO ribbon design afforded a practical method of FO sleeve generation and facilitated a novel hub configuration able to afford a FO ribbon to sleeve transition. 3D printed prototypes demonstrated the utility of the novel design. A dedicated third port and lumen for the Lumi-Solve FO is required for optimal balloon surface photo-activation. A novel triple lumen design, Lumi-Solve-T, incorporating a ribbon to sleeve FO transition and novel hub design offers a realistic solution to current device limitations.

Optimizing energy hub systems: A comprehensive analysis of integration, efficiency, and sustainability

This study introduces a novel application of modified particle swarm optimization (PSO) for optimizing multi-energy hub systems (EHSs) to enhance efficiency and sustainability. The proposed method leverages PSO to optimize the scheduling of various energy resources, including gas turbines, biomass units, and renewable sources such as solar and wind power. Unlike traditional optimization approaches that rely on genetic algorithm (GA) and complex encoding schemes, the PSO algorithm simplifies the process using real-valued vectors and direct communication within the swarm, which significantly reduces implementation complexity. Key contributions of this work include the development of a tailored PSO algorithm that integrates seamlessly with the multi-objective optimization of EHSs. The algorithm simultaneously targets a reduction in operational costs and carbon emissions, offering a comprehensive solution for energy hub design. The proposed PSO approach has demonstrated a 10.35 % reduction in operating costs and an 85.03 % decrease in CO2 emissions compared to traditional baseline setups. In comparative analysis, the integration of renewable sources using the PSO algorithm resulted in a 77.91 % reduction in total CO2 emissions and an 85.61 % decrease in operating costs, showcasing its effectiveness in advancing both economic and environmental objectives. Furthermore, the study provides a detailed evaluation of various scenarios, revealing that the PSO-optimized EHS configuration achieves a significant reduction in reliance on non-renewable energy sources (RES). For instance, the incorporation of photovoltaics and wind turbines in the EHS setup led to a 46.39 % increase in energy sold to the grid and a 26.82 % decrease in electricity purchased from external sources. These quantitative results underscore the robustness and practical benefits of the proposed PSO method in designing and optimizing energy systems for improved sustainability and cost-effectiveness.

Exploring the Lived Experiences of Members of a Faculty Research Hub Design Team in a College of Education at an HSI

ABSTRACT Researchers used a transcendental phenomenological approach to explore the experiences of faculty members in a Faculty Research Hub design team at a Hispanic-Serving Institution. Through data analysis, several themes emerged: (1) Support and leadership, (2) Commitment to improvement, (3) Individual motivation, (4) Structure and collaborative nature of the team, (5) Small team size with diverse expertise, and (6) Faculty learning and development. These themes align with the input, process, or outcome stages of Binkhorst et al.’s (2015) integrative descriptive framework for Teacher Design Teams (TDTs). The study suggests that Hispanic-Serving Institutions aspiring to become R1 institutions should consider implementing and evaluating Faculty Design Teams (FDTs) to enhance faculty research productivity and doctoral student success.

Bionic Optimization Design and Fatigue Life Prediction of a Honeycomb-Structured Wheel Hub.

The wheel hub is an important component of the wheel, and a good hub design can significantly improve vehicle handling, stability, and braking performance, ensuring safe driving. This article optimized the hub structure through morphological aspects, where reducing the hub weight contributed to enhanced fuel efficiency and overall vehicle performance. By referencing honeycombed structures, a bionic hub design is numerically simulated using finite element analysis and response surface optimization. The results showed that under the optimization of the response surface analytical model, the maximum stress of the optimized bionic hub was 109.34 MPa, compared to 119.77 MPa for the standard hub, representing an 8.7% reduction in maximum stress. The standard hub weighs 34.02 kg, while the optimized hub weight was reduced to 29.89 kg, a decrease of 12.13%. A fatigue analysis on the optimized hub indicated that at a stress of 109.34 MPa, the minimum load cycles were 4.217 × 105 at the connection point with the half-shaft, meeting the fatigue life requirements for commercial vehicle hubs outlined in the national standard GB/T 5334-2021.

Hub production scheduling problem with mold availability constraints

This research delves into a scheduling challenge inherent in the wheel hub casting process, a critical stage in automotive wheel manufacturing. The process involves shaping molten metal into specific wheel hub designs using dedicated molds. Diverse customer demands necessitate a unique mold for each wheel hub design, posing a scheduling challenge due to the limited availability of these expensive and long-lasting molds. There are 2 machines available for casting. Each wheel hub design requires a specific mold. These molds are expensive, long-lasting, and need periodic maintenance. The objective function is to minimize the total time (makespan) to complete all casting jobs. Only one job requiring a specific mold can be processed at a time (due to mold limitations). Molds are unavailable during maintenance periods. The challenge lies in scheduling jobs considering both machine availability and mold constraints to minimize the overall production time. We formulate a mathematical model using mixed integer programming to precisely represent the problem and its constraints. Inspired by the Longest Processing Time (LPT) rule, we propose a heuristic named LRTPT to efficiently schedule jobs on the two machines. For large-scale problems, we employ a novel SIAIS algorithm to find near-optimal solutions effectively. We also present a dedicated branch and bound algorithm specifically tailored to solve smaller-sized instances of the problem. This algorithm leverages two lower bounds and several dominance properties to expedite the search for the optimal solution. To evaluate the effectiveness of our proposed approaches, we conduct a series of comprehensive experiments. The results demonstrate that the branch and bound algorithm significantly outperforms the widely used optimization solver CPLEX for smaller problems. Furthermore, the SIAIS algorithm proves to be more efficient than existing scheduling heuristics.

Planning framework for establishment of hydrogen hubs incorporating the path towards net-zero-driven policies

Hydrogen hubs are emerging as strategic solutions to meet governmental emission reduction targets. A critical aspect of hydrogen hub design involves diversifying end uses, encompassing mobility, backup/storage, heating and cooling provision, onsite electricity generation, and grid energy supply. This paper introduces a comprehensive hydrogen hub model catering to these varied applications. Additionally, a novel multi-stage planning framework is proposed to assist hub operators in making informed decisions regarding the integration of diverse renewable energy sources and infrastructure. This framework addresses varying demands efficiently and economically. Moreover, to align with governmental emission reduction policies leading to net-zero targets, a proactive strategy is suggested. Through zoning for commercial, residential, educational, and healthcare sectors, the Sydney hydrogen hub is envisioned under two scenarios: business-as-usual and towards-net-zero design. Notably, CO2 emissions are projected to decrease from 18.3 ktonnes in the former to 4.7 ktonnes in the latter scenario.

Optimal design of greenfield energy hubs in the context of carbon neutral energy supply

This paper proposes a sequential co-optimization (SCO) framework for the design of greenfield energy hubs, aiming to achieve net zero emissions. The SCO framework offers an evolutionary approach to long-term planning and operation, taking into account various evolving factors such as carbon emission policies, technological and economic advancements in energy supply components, changes in land-use, and developments at different stages of the design horizon. The framework ensures that the design of greenfield developments aligns with their evolving characteristics, determining the optimal dispatch flow for firming renewable energy through co-generation and demand flexibility options like smart loads, electric vehicles, and hydrogen-based systems. A sensitivity analysis is conducted to study the impact of emissions, evolving characteristics of greenfield developments, and techno-economic aspects of supply units on the energy hub design. Case studies demonstrate that the proposed design enables large-scale distributed energy systems to meet local energy demand and participate in the electricity market. The SCO framework provides a robust and flexible platform for the correlated optimization of planning and operation of greenfield energy hubs, for advancing towards net zero emissions.

The impact of the Impeller's hub design on the performance and blood damage in a microaxial mechanical circulatory support device – A numerical study

This study uses CFD methods to investigate the effects of the impeller's geometry on the hemodynamic characteristics, pump performance, and blood damage parameters, in a percutaneous microaxial Mechanical Circulatory Support (MCS) device. The numerical simulations employ the steady state Reynolds-Averaged Navier-Stokes approximation using the SST k−ω turbulent model. Three different impeller models are examined with different hub conversion angles (α = 0○, 3○ and 5○). The analysis includes 23 cases for different pressure heads (Δp = 60–80 mmHg) and angular velocities (ω = 30–52 kRPM). The obtained flow rate is compared between the cases to assess the effect of the impeller's design and working conditions on the pump performance. The comparative risk of shear-induced platelet activation is estimated using the statistical median of the stress-accumulation values calculated along streamlines. The risk of hemolysis is estimated using the average exposure time to shear stress above a threshold (τ > 425 Pa). The results reveal that the shape of the impeller's hub has a great impact on the flow patterns, performance, and risk of blood damage, as well as the angular velocity. The highest flow rate (Q = 3.7 L/min) and efficiency (η = 11.3 %) were achieved using a straight hub (α = 0○). Similarly, for the same condition of flow and pressure, the straight hub impeller has the lowest blood damage risk parameters. This study shed light on the effect of pump design on the performance and risk of blood damage, indicating the roles of the hub shape and angular velocity as dominant parameters.

REVERSE ENGINEERING AND PROTOTYPING OF TWO WHEELER SPROCKET HUB

This project successfully reverse engineered and prototyped a two-wheeler sprocket hub. A 3D scanner captured the geometry of the original sprocket hub, generating precise data for a digital model. Geomagic software was then utilized to process the scan data and create an STL file, suitable for 3D printing. The final stage involved 3D printing the sprocket hub prototype using a material chosen for its strength and durability. This project not only achieved a comprehensive understanding of the sprocket hub's design through 3D scanning, but also produced a functional prototype for comparison with the original component in terms of dimension, function, and performance. The knowledge gained through this project is valuable for sprocket hub maintenance, repair, and potential future modifications. Key Words: Two-wheeler sprocket hub, Reverse engineering, 3D scanning, Prototyping, 3D printing, STL file.

Design and FEA analysis of hub based dual rotor machine for optimal energy generation in four wheeled electric vehicle application

This research article focuses on the design and Finite Element Analysis (FEA) analysis of a hub-based Dual Rotor Machine (DRM). Conventional, electric machines can perform either motoring or generating operations at an instant of time for electric vehicle (EV) applications. However, the proposed DRM can perform both motoring and generating modes of operation simultaneously. For this dual operation, a power rating of 15 kW Brushless DC Machine is selected with outer rotor configuration to achieve high starting torque in motoring operation and a power rating of 6 kW Permanent Magnet Synchronous Machine is considered for generating operation with an inner rotor. Based on theoretical results, the design of DRM is developed and analysed using FEA software programs such as MagNet, Jmag and ThermNet. By using a two-dimensional (2-D) transient solver, the proposed DRM performance is simulated and validated with cogging torque, electromagnetic, thermal and stress analysis. The performance of the proposed DRM model is also tested with drive cycle data of WLTP-II (Worldwide Harmonised Light Vehicle Test Procedure) in ANSYS Motor-CAD software. The simulation results confirm the proposed DRM can consume only 252 Wh over 405 Wh energy consumed by a single rotor machine and ensuring its applicability for EV applications.

Equity in Resilience Hub Design and Transportation through Community Discussions

This research highlights transportation, placement, and features of resilience hubs preferred by underserved populations, using Edmonton, Alberta as a case study. Semi-structured focus groups were conducted with eight different underserved populations (n=52), and thematic analysis was performed to determine common themes and inform equity-centered engineering design. By talking directly with community members, we found that resilience hubs should be placed in locations that are easily accessible by walking or public transit, and additional infrastructure is needed to meet users’ needs. Most underserved participants prefer locations that are close to their neighborhood, indicating a proximity-based approach for future implementation.

Evaluation of parametric sedan wheel hub based on Kansei Engineering and regression analysis

<p><strong>Purpose:</strong> Parametric design has become one of the most important means of sedan design. The purpose of this paper is to construct a linear regression model to explore the matching relationship between Kansei words and the morphological elements of sedan wheels and to incorporate perceptual factors into the rational thinking of parametric wheel hub design. <strong>Design/methodology/approach:</strong> To forecast the matching relationship between wheel shape design features and semantics, this research offers a multiple linear regression model. First, using sample similarity matrix data analysis and offline research, 20 typical samples of car wheels were collected. Third, the wheel shape design elements are obtained by applying the semantic difference (SD) method to four groups of users’ evaluation data on the perceived words of the car wheels. Firstly, the wheel shape is divided into six basic features and seventeen subdivided features using morphological analysis. The collected car wheel samples are then researched and coded. Ultimately, a multiple linear regression model is built utilizing shape coding matching to the styles to direct the wheel parametric design process, yielding sedan wheel design schemes with various semantics of style. <strong>Findings:</strong> The results show that the regression models can provide good prediction performance (R<sup>2</sup> values are greater than 0.7). This study shows that the use of multiple regression models can accurately and cost-effectively predict the wheel hub morphological elements that meet the user’s perceptual needs through morphological elements and Kansei words. <strong>Originality/value:</strong> This paper is the first to use a multiple regression model to predict a parametric wheel shape that fits the user’s sensibility, which helps the user to present and feel the design scheme in a digital environment. The different wheel hub schemes generated by parametric design can be virtually displayed in the metaverse, helping users and designers to carry out more convenient scheme selections.</p>

A Methodology for Designing a Fish-Friendly Turbine Rotor Applied to High-Power Generation

Most large hydropower facilities employing conventional hydraulic turbines, e.g., Francis, Kaplan, or Bulb turbines, etc., cause significant harm to fish, resulting in high mortality rates, during turbine operation. This results from strong injury-inducing mechanisms at the rotor, including shear stresses, pressure variations, and pressure drop through the rotor. The study outlines a methodology for designing a fish-friendly turbine that is suitable for high-power generation applications. This methodology for a hydraulic channel design within the turbine rotor was derived based on classical fundamental applications of a rotor design, supplemented by subsequent assessments that incorporate fish-friendly design parameters that have been documented in the existing literature. A spiral curve characterized by a linear angle variation between the rotor's inlet and outlet was employed to project the blade geometry. Here, the Göttingen hydrofoil series was used, while a second-order polynomial function guided the hub design. Both of these parametrizations sought to enhance the turbine's hydraulic efficiency. Minimum Absolute Pressure, Strain Rate, and Pressure Variation Rate intervals were established as assessment criteria for fish survival for certain species, as has also been previously explored in the literature. The findings were outlined in terms of hydrodynamic performance and flow behavior within the rotor. An improvement in hydraulic efficiency was observed, transitioning from a Preliminary Turbine geometry design to an Optimized Turbine Geometry design. The turbine rotor was optimized using Computational Fluid Dynamics (CFD) simulations, generated from a Design of Experiments (DOE). Modifications to the hydrofoil type, the sweep angle, and the trailing edge angle of the blades were all made, coupled with integrations of assessments considering fish-friendly parameters.

Integration of Riboflavin-Modified Carbon Fiber Mesh Electrode Systems in a 3D-Printed Catheter Hub.

Catheter line infection is a common complication within clinical environments, and there is a pressing need for technological options to aid in reducing the possibility of sepsis. The early identification of contamination could be pivotal in reducing cases and improving outcomes. A sensing rationale based on a riboflavin-modified electrode system integrated within a modified 3D-printed catheter needle-free connector is proposed, which can monitor changes in pH brought about by bacterial contamination. Riboflavin, vitamin B2, is a biocompatible chemical that possesses a redox-active flavin core that is pH dependent. The oxidation peak potential of the adsorbed riboflavin responds linearly to changes in pH with a near-Nernstian behavior of 63 mV/pH unit and is capable of accurately monitoring the pH of an authentic IV infusate. The proof of principle is demonstrated with an electrode-printed hub design offering a valuable foundation from which to explore bacterial interactions within the catheter lumen with the potential of providing an early warning of contamination.

Numerical Investigations and Artificial Neural Network-Based Performance Prediction of a Centrifugal Fan Having Innovative Hub Geometry Designs

It is a well-known fact that air approaches the eye region of the rotating impeller of a centrifugal fan with shock-less entry conditions in an ideal scenario. The flow in this region is associated with induced swirl losses, leading to cumulative performance losses. Proper flow guidance in the vicinity of the eye region is essential to minimize possible flow losses. The flow guiding structure may be in the form of a projection or extrusion connected to the rotating impeller of the turbo machines and is generally named a hub. These attachments enhance the overall flow augmentation of the turbo machines in terms of static pressure improvement by reducing a significant amount of inlet turning losses. This article attempts to highlight the efficacy of hubs of various shapes and sizes on the pressure rise of the centrifugal fan using Computational Fluid Dynamics (CFD). Simulation results revealed that the optimized hub configuration yields about an 8.4% higher head coefficient and 8.6% higher relative theoretical efficiency than that obtained for the hub-less base configuration. This improvement in these paraments therefore also commemorates the global progress in energy efficiency as per the UN’s Sustainable Development Goals, SDG 7 in particular. Simultaneously, in the Artificial Neural Network (ANN), a Multi-Layer Perceptron (MLP) model is used to forecast the performance of a centrifugal fan with an optimized hub design. The results predicted by the ANN model are found to be in close agreement with the optimized hub shape’s numerical results.

Planning the Design and Operation of Urban Energy Systems with Limited Data Availability: A Holistic Open-Source Tool Chain

Urban energy systems are becoming more complex due to the integration of renewable energy sources and electrification of heat supply. Dynamic planning and operation strategies are necessary to optimally satisfy energy demands, especially in the 5th generation of heating and cooling networks, which efficiently address these challenges through decentralized water-water heat pumps. An end-to-end tool chain is presented which enables to analyze and evaluate such systems in early planning phases with limited data availability. It includes thermal building simulations, heating network simulations, optimization, and incorporation capabilities for model-based operation algorithms and AI-based forecasting algorithms. User acceptance of the energy system can also be considered in the design phase in future. This paper presents the interaction of the open-source tools: TEASER, which generates high-resolution time-series of heating and cooling demands of buildings; uesgraphs, which generates and simulates thermal networks from geodata; and EHDO, which optimizes energy hub designs. Future research pathways include integrating AI-based operation optimization and surveys to support user feedback integration. Work will also address substation models for the 5th generation heating networks and novel data infrastructures. The tool chain has already been successfully used in many scenarios, but open questions remain around integrating the methods into the operation phase and further developing the complex energy models the tool chain is built upon.

Static load-carrying behavior and material properties of additively manufactured gears (PBF-LB/M, 16MnCr5)

PurposeNumerous metals can be processed using the additive manufacturing process laser-based powder bed fusion of metals (PBF-LB/M, ISO/ASTM 52900). The main advantages of additive manufacturing technologies are the high degree of design freedom and the cost-effective implementation of lightweight structures. This could be profitable for gears with increased power density, combining reduced mass with considerable material strength. Current research on additively manufactured gears is focused on developing lightweight structures but is seldom accompanied by simulations and even less by mechanical testing. There has been very little research into the mechanical and material properties of additively manufactured gears. The purpose of this study is to investigate the behavior of lightweight structures in additively manufactured gears under static loads.Design/methodology/approachThis research identifies the static load-carrying capacity of helical gears with different lightweight structures produced by PBF-LB/M with the case hardening steel 16MnCr5. A static gear loading test rig with a maximum torque at the pinion of T1 = 1200 Nm is used. Further focus is set on analyzing material properties such as the relative density, microstructure, hardness depth profile and chemical composition.FindingsAll additively manufactured gear variants show no failure or plastic deformation at the maximum test load. The shaft hub connection, the lightweight hub designs and the gearing itself are stable and intact regarding their form and function. The identified material characteristics are comparable to conventionally manufactured gears (wrought and machined), but also some particularities were observed.Originality/valueThis research demonstrates the mechanical strength of lightweight structures in gears. Future research needs to consider the dynamic load-carrying capacity of additively manufactured gears.

Intermediate service facility planning in a stochastic and competitive market: Incorporating agent-infrastructure interactions over networks

This paper presents a network-based multi-agent optimization model for the strategic planning of service facilities in a stochastic and competitive market. We focus on the type of service facilities that are of intermediate nature, i.e., users may need to deviate from the shortest path to receive/provide services in between the users’ planned origins and destinations. This problem has many applications in emerging transportation mobility, including dynamic ride-sharing hub design and competitive facility location and allocation problems for alternative fuel vehicle refueling stations. The main contribution of this paper is establishing a new multi-agent optimization framework considering decentralized decision makings of facility investors and users over a transportation network and providing rigorous analyses of its mathematical properties, such as uniqueness and existence of system equilibrium. In addition, we develop an exact convex reformulation of the original multi-agent optimization problems to overcome computational challenges brought by non-convexity. Extensive analysis on case studies showed how the proposed model can capture the complex interaction between different stakeholders in an uncertain environment. Additionally, our model allowed quantifying the value of stochastic modeling and information availability by exploring stochastic metrics, including value of stochastic solution (VSS) and expected value of perfect information (EVPI), in a multi-agent framework.