Multidisciplinary Design Research Articles

Time identification of design knowledge push based on cognitive load measurement

The reuse of multidisciplinary design knowledge is pivotal in product development because of the increasingly fierce market competition. It can assist designers, particularly those who lack sufficient experience, in making correct decisions and achieving rapid design. Traditionally, designers primarily acquire design knowledge through information retrieval, which is typically time-consuming and inefficient. A solution that is widely considered to overcome the deficiencies of traditional knowledge retrieval approaches and actively provide designers with necessary knowledge is knowledge push. However, achieving the timely push of required knowledge to designers during the design process remains a challenging task. Accordingly, this paper presents a time identification method based on cognitive load measurement to identify the suitable time for design knowledge push. First, behavioral indicators related to the changes in cognitive load are identified by investigating the influence of the load on three types of behaviors: mouse dynamics, keystroke dynamics, and emotional states. Second, the possibility and efficacy of inferring the cognitive load by simultaneously and unobtrusively tracking the three aforementioned behaviors are considered through behavioral observations. Finally, predicting the knowledge push time based on the cognitive load using classification algorithms is investigated. The experimental results indicate that the accuracy of the proposed method in inferring the cognitive load is 55%, and that of push time is 83%.

Managing the Wellbeing of Elite Rugby Union Players from an Occupational Safety and Health Perspective.

The intense, physical contact nature of rugby union often encourages the normalization of risk-taking behaviour resulting in a relatively high acceptance of risk. This study aims to explore safety culture in rugby union from an OSH perspective, with the purpose of assisting coaches and management in their decision-making processes to improve players’ health, welfare, and long-term well-being. In terms of data collection, this study involved semi-structured interviews with senior support staff (n = 15) in elite rugby union. Interview transcripts underwent inductive analysis prior to an abductive analysis that was guided by an established occupational-safety-and-health (OSH) framework. Rugby union players’ safety can be considered from two dimensions: management’s commitment to safety (i.e., safety prioritization, safety empowerment, and safety justice), players’ involvement in safety (i.e., safety prioritization, and trust in other players’ safety competence, and players’ safety concern for the opposition players). Within the themes identified, players’ attitude towards their opponents’ safety which has been rarely considered as a factor for injury prevention is also discussed in this study. If sport support staff (i.e., managers/coaches/medical) can become more involved in players’ performance-orientated training using OSH management processes to aid in their decision-making, their exists the capacity to benefit players’ safe return to play after injury rehabilitation. Meanwhile, directing the development of appropriate behavioural educational interventions to raise safety-awareness amongst players can improve their long-term health and well-being and provide them with the necessary safety and health information to support their own decision-making processes. As a multidisciplinary design, this study contributes new multidisciplinary insights that have the potential to advance managerial practices utilizing an OSH perspective, including decision-making supporting risk alleviation for safety and long-term health and wellbeing initiatives in competitive team sports.

Updating multi-fidelity structural dynamic models for flexible wings with feed-forward neural network

In multidisciplinary design optimization of aerospace structures (e.g., a flexible wing), it may be convenient and practical to break such a complex problem into multi-fidelity, multi-stage design problems. Structural model updating is needed in multi-fidelity, multi-stage optimizations to ensure the consistency of models with different fidelity. However, due to the inequality in structural parameters, there exists a fundamental difficulty in the model updating from a lower fidelity model to a higher fidelity model. In this paper, a feed-forward neural network is applied to determine the structural dynamic characteristics of a higher fidelity model based upon a lower fidelity model. The feasibility of this approach is demonstrated by updating beam-like wings to a thin shell-based model and a one-cell wing box model, respectively. The quality and accuracy of model updating using the proposed method are also discussed regarding the neural network structure and sample size.

Multidisciplinary Design Optimization of a Re-Entry Spacecraft via Radau Pseudospectral Method

The design and optimization of re-entry spacecraft or its subsystems is a multidisciplinary or multiobjective optimization problem by nature. Multidisciplinary design optimization (MDO) focuses on using numerical optimization in designing systems with several subsystems or disciplines that have interactions and independent actions. In the present paper, the system-level optimizer, trajectory, geometry and shape, aerodynamics, and aerothermodynamics differential equations, are converted to algebraic equations using the Radau pseudospectral method (RPM) since a spacecraft is a nonlinear, extensive, and sparse system. The solution to the problem with the help of MDO is reached by iterating all the disciplines together; one can simultaneously enhance the design, decrease the time and cost of the entire design cycle, and minimize the structural mass of a re-entry spacecraft. Considering various methods presented in earlier research works, a combined and innovative all-at-once (AAO), RPM-based MDO method, including the key subsystems in the design process of a re-entry capsule-shape spacecraft with a low lift-to-drag ratio (L/D), is presented. Considering the applicable state and control variables, various constraints, and parameters applied to several geometric shapes of a blunt capsule and using Apollo’s aerodynamic and aerothermodynamic coefficients, the optimized dimensions for a re-entry spacecraft are presented. The introduced optimization scheme led to a 17% mass reduction compared to the original mass of the Apollo vehicle. Fast computing and simplified models are used together in this method to analyze a wide range of vehicle shapes and entry types during conceptual design.

A model-based multidisciplinary conceptual design for blended-wing-body underwater gliders

ABSTRACT Blended-wing-body underwater gliders (BWBUGs) can achieve superior performance for their shapes. Their overall performance is affected by shapes and shows correlations with other disciplines. In this paper, a universal classification and parameterisation model was proposed, including the shape, layout, structure, and energy consumption. To overcome the coupling between the multidisciplinary design in conceptual design, a model-based multidisciplinary system design was conducted for BWBUGs. This system adopted a parameterisation model to design the shape, layout, structure and employed multiple simulation modules to evaluate the system performance, which can facilitate the convenient definition of overall performance and design constraints, obtain various feasible system schemes rapidly, and boost the series development and agile design of BWBUG.

Optimisation-driven design to explore and exploit the process–structure–property–performance linkages in digital manufacturing

An intelligent manufacturing paradigm requires material systems, manufacturing systems, and design engineering to be better connected. Surrogate models are used to couple product-design choices with manufacturing process variables and material systems, hence, to connect and capture knowledge and embed intelligence in the system. Later, optimisation-driven design provides the ability to enhance the human cognitive abilities in decision-making in complex systems. This research proposes a multidisciplinary design optimisation problem to explore and exploit the interactions between different engineering disciplines using a socket prosthetic device as a case study. The originality of this research is in the conceptualisation of a computer-aided expert system capable of exploring process–structure–property–performance linkages in digital manufacturing. Thus, trade-off exploration and optimisation are enabled of competing objectives, including prosthetic socket mass, manufacturing time, and performance-tailored socket stiffness for patient comfort. The material system is modelled by experimental characterisation—the manufacturing time by computer simulations, and the product-design subsystem is simulated using a finite element analysis (FEA) surrogate model. We used polynomial surface response-based surrogate models and a Bayesian Network for design space exploration at the embodiment design stage. Next, at detail design, a gradient descent algorithm-based optimisation exploits the results using desirability functions to isolate Pareto non-dominated solutions. This work demonstrates how advanced engineering design synthesis methods can enhance designers’ cognitive ability to explore and exploit multiple disciplines concurrently and improve overall system performance, thus paving the way for the next generation of computer systems with highly intertwined material, digital design and manufacturing workflows.Graphical abstract

Integrated Optimal Design for Hybrid Electric Powertrain of Future Aircrafts

This paper presents the integrated optimal design of the powertrain of a hybrid regional aircraft using multidisciplinary design optimization (MDO). The sizing of the main components of the propulsion chain is performed over the flight mission under various scenarios regarding energy management strategies and technological assessments. For that purpose, a complete set of multidisciplinary surrogate models are integrated into the MDO process, taking account not only of the main electrical, thermal and mechanical aspects but also of environmental constraints such as partial discharges in electric motors regarding flight conditions. Several MDO formulations are investigated comparing local (i.e., motor mass minimization) and global optimizations (i.e., powertrain mass then fuel burn minimization at aircraft level). Results emphasize main systemic couplings showing that despite future technological progress, the series hybrid architecture is heavier than a conventional thermal aircraft. Nevertheless, thanks to the whole aircraft optimization, potential gains related to kerosene consumption can be reached, reducing the environmental footprint. The “energy gains” focused on in this paper may be added with aerodynamic gains potentially involved in more electric powertrain. This work has been carried out in the frame of the HASTECS project under the Clean Sky II program which aims at reducing CO2 emissions and environmental impacts of the aviation sector.

An Evaluation of a Web-Based Decision Aid for Treatment Planning of Small Kidney Tumors: Pilot Randomized Controlled Trial.

BackgroundSurgery is the most common treatment for localized small kidney masses (SKMs) up to 4 cm, despite a lack of evidence for improved overall survival. Nonsurgical management options are gaining recognition, as evidence supports the indolence of most SKMs. Decision aids (DAs) have been shown to improve patient comprehension of the trade-offs of treatment options and overall decision quality, and may improve consideration of all major options according to individual health priorities and preferences.ObjectiveThis pilot randomized controlled trial (RCT) primarily aims to evaluate the impact of a new web-based DA on treatment decisions for patients with SKM; that is, selection of surgical versus nonsurgical treatment options. Secondary objectives include an assessment of decision-making outcomes: decisional conflict, decision satisfaction, and an understanding of individual preferences for treatment that incorporate the trade-offs associated with surgical versus nonsurgical interventions.MethodsThree phases comprise the construction and evaluation of a new web-based DA on SKM treatment. In phase 1, this DA was developed in print format through a multidisciplinary design committee incorporating patient focus groups. Phase 2 was an observational study on patient knowledge and decision-making measures after randomization to receive the printed DA or institutional educational materials, which identified further educational needs applied to a web-based DA. Phase 3 will preliminarily evaluate the web-based DA: in a pilot RCT, 50 adults diagnosed with SKMs will receive the web-based DA or an existing web-based institutional website at urology clinics at a large academic medical center. The web-based DA applies risk communication and information about diagnosis and treatment options, elicits preferences regarding treatment options, and provides a set of options to consider with their doctor based on a decision-analytic model of benefits/harm analysis that accounts for comorbidity, age group, and tumor features. Questionnaires and treatment decision data will be gathered before and after viewing the educational material.ResultsThis phase will consist of a pilot RCT from August 2022 to January 2023 to establish feasibility and preliminarily evaluate decision outcomes. Previous study phases from 2018 to 2020 supported the feasibility of providing the printed DA in urology clinics before clinical consultation and demonstrated increased patient knowledge about the diagnosis and treatment options and greater likelihood of favoring nonsurgical treatment just before consultation. This study was funded by the National Cancer Institute. Recruitment will begin in August 2022.ConclusionsA web-based DA has been designed to address educational needs for patients making treatment decisions for SKM, accounting for comorbidities and treatment-related benefits and risks. Outcomes from the pilot trial will evaluate the potential of a web-based DA in personalizing treatment decisions and in helping patients weigh attributes of surgical versus nonsurgical treatment options for their SKMs.Trial RegistrationClinicalTrials.gov NCT05387863; https://clinicaltrials.gov/ct2/show/NCT05387863International Registered Report Identifier (IRRID)PRR1-10.2196/41451

Multidisciplinary optimization of a Francis turbine runner

A fully automated multi-disciplinary design optimization procedure for a Francis turbine runner has been developed in a previous task of the Horizon2020-HydroFlex project. The design optimization was limited to blade design, with the goal of improving the hydraulic efficiency and torque, and reducing the harmonic structural stresses. This is to ensure that the turbine is less prone to fatigue, but still performs well hydraulically. Results from the numerical optimization are presented in this paper. From the design optimization, two runner designs are highlighted. One that performs significantly better than a reference design, and one that performs significantly worse. It is observed that small, but significant improvements can be obtained in both torque and efficiency, while at the same time reducing the structural stresses drastically. This shows that there might be previously unknown areas in the design space that can be explored, especially on the structural side.

Back to His Roots: aLL Design – the Legacy of an All‐inclusive Architect

Alsop's last incarnation of architectural practice, aLL Design was co-founded with Marcos Rosello in 2011. Rosello recounts Alsop's tirelessly hospitable open-door policy in the studio, which promoted an atmosphere of benevolent multidisciplinary design exploration. The guiding principles the practice carries forward by way of legacy were set out during this period.

Effects of Aft-Body Extension Design on the Fundamental Characteristics of HWB Civil Aircraft

The extension of aft-body fuselage has become an important trend in the design of Hybrid Wing Body (HWB) civil aircraft due to its improved effect on flight control authority of aircraft. However, it is still unclear how efficient the extension of aft-body will be in improving flight control authority and how it affects other aspects of the flight performance of HWB. To address these problems, this paper evaluated and compared the flight performances of four HWB configurations with different aft-body lengths. A physics-based Multidiscipline Design Optimization (MDO) platform was firstly constructed, and four optimal design works were developed based on this platform, with different static margin constraints. The configurations to be studied came from the results of the four optimization design works, which presented different aft-body lengths under the influence of correspondence between static stability margins and aft-body layout. By investigating these four HWB configurations with the weight, basic takeoff and landing performance, and flight control authority, we can determine the influence of the aft-body extension design on the performances of the HWB civil aircraft and provide advice for the layout design of the HWB aircraft.

System Analysis and Design Space Exploration of Regional Aircraft with Electrified Powertrains

This paper explores the design spaces of a thin-haul and a regional aircraft with parallel hybrid-electric propulsion architectures for a 2030 entry into service date. Notional technology reference aircraft models were developed for a 19- and a 50-passenger aircraft based on publicly available data on Beechcraft 1900D and ATR 42-600, respectively. A set of airframe and propulsion system technologies projected to reach maturity by 2030 was infused into the aircraft models. Parametric, physics-based models were created for the charge-depleting hybrid architecture. Different modes of operation were identified and parameterized with a range of design variables to investigate the feasibility and trade space for peak power shaving, climb power boosting, electric taxi, battery usage schedules, and in-flight battery recharge strategies. Thousands of electrified aircraft concepts with varying electrification, operation, and technology scenarios were sized under the same system-level requirements as their conventional counterpart. The resulting multidisciplinary design space exploration environment was used to identify the optimum vision system designs and modes of operation for the minimum block fuel-burn objective. It has been found that both vehicle classes with the charge-depleting parallel hybrid electric architecture provided fuel-burn benefits over their 2030 advanced technology counterparts under certain operational modes.

Development of a bespoke 3D-printed spinal brace for lumbar support

Low back pain (LBP) is a significant contributor to disabilities in the UK. Many factors cause LBP, including poor posture, obesity, and spinal fractures, all resulting in spiralling healthcare costs. If spinal fractures are not properly braced, they can lead to weakened vertebrae in the spine and larger risks that can reoccur. There are many problems with flexible, semi-rigid and rigid braces currently available on the market. We present the user-centred design approach undertaken by a multidisciplinary design team consisting of product designers, design engineers, technical specialists, and healthcare professionals to develop a bespoke 3D-printed spinal brace using a digital design workflow.

A lumped-parameter coupled electro-piezo-aeroelastic model for flapping wings

Induced-strain actuated flapping wings and fins, achieved by surface-mounted piezoelectric actuators, do not need conventional motors and mechanisms, potentially reducing system weight, energy consumption, and mechanical complexity compared to conventional systems. A piezocomposite flapping wing or an underwater oscillating fin with induced-strain actuation can interact with the ambient fluid to yield flow vectoring, control, and lift or thrust generation. In this article, an electro-piezo-aeroelastic coupled lumped-parameter model is developed to predict the dynamic behavior of strain actuated flapping wings, and obtain insight into coupling mechanisms such as bend-twist coupling, fluid-structure interaction, and electro-piezo coupling. The piezoelectric wing is modeled as a laminated orthotropic plate. Using the Rayleigh-Ritz method, the distributed wing motion can be represented by lumped wing heave, chordwise curvature, and pitch displacements by assuming prescribed deformation shapes. The assumed shapes are compatible with the fluid effects interpreted as translational and torsional added mass and damping to the structure. The aeroelastic model is then coupled to the circuit model via electro-piezo coupling. The mechanical model is validated using the finite element method. It is found that four wing tip parameters, including first and second order heave motion, pitch, and chordwise curvature are sufficient to represent the wing motion. The lumped parameter wing model is then used to investigate the system optimal parameters for maximizing desired aero- and/or hydro-dynamic responses. System properties such as structural parameters, excitation frequency ratio, etc., are under investigation. The lumped parameter model is computationally efficient, and suitable for trade studies and multi-disciplinary design optimization. Also, the lumped parameter model serves as a foundation for flapping flight analysis, e.g., analyzing lift force, leading-edge vortex stabilization, and tip vortex shedding.

Design and Optimization Technologies of Permanent Magnet Machines and Drive Systems Based on Digital Twin Model

One of the keys to the success of the fourth industrial revolution (Industry 4.0) is to empower machinery with cyber–physical systems connectivity. The digital twin (DT) offers a promising solution to tackle the challenges for realizing digital and smart manufacturing which has been successfully projected in many scenes. Electrical machines and drive systems, as the core power providers in many appliances and industrial equipment, are supposed to be reinforced on the verge of Industry 4.0 in the fields of design optimization, fault prognostic and coordinated control. Therefore, this paper aims to investigate the DT modelling method and the applications in electrical drive systems. Firstly, taking the high-speed permanent-magnet machine drive system as an example, multi-disciplinary design fundamentals and technologies, aiming at building initial mechanism and simulation models, are reviewed. The state-of-the-art of DT technologies is figured out to serve for high-precision and multi-scale dynamic modelling, by which a framework for DT models of electrical drive systems is presented. More importantly, fault diagnosis and optimization strategies of electrical drive systems in the decision and application layer are also discussed for the DT models, followed by the conclusions presenting open questions and possible directions.

A reduced-order multi-body model with electromechanical-aeroelastic coupling for mechanism-free ornithopters

Piezoelectric material-actuated so-called solid-state (i.e., mechanism-free) ornithopters do not need conventional motors and mechanisms, potentially saving weight and energy consumption, reducing mechanical complexity, and improving wing flexibility. In solid-state ornithopters, wing flapping can be achieved by surface-mounted piezoelectric actuators. The design of a solid-state ornithopter is a complex multi-disciplinary task, and optimization of wing topology, actuator placement, and excitation parameters requires a computationally efficient model to predict its dynamic response and performance metrics. In this paper, effectively, a novel flight simulation model is presented based on a reduced-order lumped parameter multi-body model coupled with a vortex lattice program. The proposed lumped parameter model can be represented by an equivalent multi-body mechanical model or a circuit model. The coupling considered in the lumped parameter model includes: (1) the body-wing momentum interaction, (2) bend–twist​ coupling of the piezocomposite wings, (3) fluid–structure interactions between the flapping wings, oscillating body, and the ambient fluid, and (4) electromechanical coupling between a resistive–inductive–capacitive driving circuit and the piezocomposite wings. The wing motion is described using the Rayleigh–Ritz method, in which the representative wing modes are identified as spanwise plunge, chordwise curvature, and twist. The body-wing interaction is modeled using Hamilton’s principle. The fluid-induced effects on the wings have three contributions: added mass and damping, quasi-steady aerodynamic forces obtained using the vortex lattice program, and unsteady aerodynamic forces calculated using the Theodorsen formulation, which is integrated into the wing heave and pitch degrees of freedom in the lumped parameter model. The proposed reduced-order model proposed is computationally efficient, suitable for trade studies and multi-disciplinary design optimization, and can be easily converted to state representation for controller development purposes. The capabilities of this model are demonstrated through tethered and gliding flight simulations. System properties such as circuit parameters, structural parameters, excitation frequency ratio, etc., are investigated. Phugoid and short period modes are observed in gliding flight simulations. The contribution of active flapping is found by the comparison of flight simulations with and without active flapping. A net thrust contributed by unsteady lift is demonstrated even though the thrust-lift ratio is low. The proposed model serves as an extensible framework for modeling and design optimization of ornithopters.

A Dimension Reduction-Based Multidisciplinary Design Optimization Method for High Pressure Turbine Blades

Abstract The complex aero-thermal coupling between fluid and solid regions within high-pressure turbines makes it important to perform multidisciplinary design optimization of high-pressure turbine blades. However, most published works failed to consider the correlations between blade profiles and cooling structures that could best compromise the aerodynamic and thermal performance of high-pressure turbine blades, and the related optimization problems were so far limited to single- or bi-objective ones. The critical drawbacks of these available studies are mainly due to the reduced accuracies of the adopted methods when dealing with large numbers of design variables and objectives. To tackle these difficulties, a dimension reduction-based multidisciplinary design optimization method is proposed and validated through an aero-thermal design optimization of the NASA-C3X vane with a total of 39 design variables and five performance objectives. The main novelties of this proposed method lie in a hybrid dimension reduction of design space by means of the proper orthogonal decomposition and global sensitivity analysis methods, as well as the integration of the ensemble surrogate model and the reference vector evolutionary algorithm for optimal solutions. The results show that the prediction accuracy of the ensemble surrogate model for each performance objective is enhanced, even though the dimensionalities of design space are reduced. Complicated compromises exist among the five performance objectives under consideration. For NASA-C3X vane, the optimal design helps reduce irreversible flow losses especially wake losses while reducing the volumes with high-temperature and high-temperature gradient near the trailing edge is mainly responsible for the reduced irreversible losses due to heat transfer. The outcomes of this work are particularly relevant for the advanced design optimization methods for high pressure turbines.

All-At-Once formulation integrating pseudo-spectral optimal control for launch vehicle design and uncertainty quantification

Launch vehicle design is a multidisciplinary process involving different disciplines such as aerodynamics, structure, propulsion and trajectory. This latter is a key discipline in the design process as it is used to assess the overall performance of the vehicle by solving of an optimal control problem involving a system of nonlinear ordinary differential equations. Usual Multidisciplinary Design Optimization methods for launch vehicle design consider the trajectory design discipline as an auxiliary embedded optimization problem to find the optimal trajectory control. In this paper, a multidisciplinary approach is proposed relying on an All-At-Once formulation by using Gauss–Lobatto collocation technique to solve the optimal control problem. The problem is solved using a gradient-based optimizer. Furthermore, based on this framework, an uncertainty quantification technique using post-optimality analysis is derived to perform sensitivity analysis. This allows to analyze the influence of modeling uncertainty on the optimal launch vehicle performance in the early design phases. The efficiency of the proposed approach is illustrated on the optimization and uncertainty quantification of a representative Two-Stage-To-Orbit launch vehicle design problem.

Using a multidisciplinary, multi-method and collaborative research design to investigate the health communication power of the early childhood sector

This paper details the research design of a multidisciplinary, multi-method, collaborative research project investigating health communication from the experiences of the early childhood education (ECE) sector during the COVID-19 pandemic. With the rapidly evolving pandemic, the ECE sector was instantly tasked with expanding their required health practices to prevent the spread of infection. It was evident that the sector needed a system to communicate health advice in a timely, consistent and effective manner. Founded on a partnership model based on ‘knowledge brokering’ theory, this project demonstrates the value of a multidisciplinary research team collaborating with stakeholder organisations to investigate how COVID-19 health information traversed through complexities of organisational layers and diverse communities of families and staff. Detailing our data collection and analysis protocols, we conclude by outlining how our innovative research design is generating actionable and impactful recommendations for both the ECE and health sectors.

Toward artificially intelligent cloud-based building information modelling for collaborative multidisciplinary design

The technological tools people use for designing buildings have progressed from drawings to descriptive geometry, and from computer-aided drafting and design (CAD) to building information modelling (BIM). Yet despite their use of state-of-the-art BIM technology, the multidisciplinary teams that design modern buildings still face numerous challenges. Building models lack sufficient semantic content to properly express design intent, concurrent design is difficult due to the need for operators to maintain model consistency and integrity manually, managing design variations is cumbersome due to the packaging of information in files, and collaboration requires making-do with imperfect interoperability between application software. In response, we propose a ‘Cloud BIM’ (CBIM) approach to building modelling that seeks to automate maintenance of consistency across federated discipline-specific models by enriching models with semantic information that encapsulates design intent. The approach requires a new ontology to represent knowledge about the relationships between building model objects within and across disciplines. Discipline-specific building models are stored together with their data schema in knowledge graphs, and linked using objects and relationships from the CBIM ontology. The links are established using artificially intelligent semantic enrichment methods that recognize patterns of location, geometry, topology and more. Software methods that operate along CBIM relationship chains can detect inconsistencies that arise across disciplines and act to inform users, propose meaningful corrections, and apply them if approved. Future CBIM systems may provide designers with the functionality for collaborative multidisciplinary design by maintaining model consistency and managing versioning at the object level.