Early Design Research Articles

Early Marine Systems' Design – Cracking the wicked problem - The case of a novel biomass harvesting vessel

Several IMDC contributions have argued for a better approach to capture stakeholders' expectations in vessel newbuilding projects' execution. The appropriate processes of requirements elucidation are, however, often forgotten or insufficiently handled in traditional ship design and customer-designer settings. Such situations most often reveal a situation in which both "tamed" and "wicked" problems are addressed and must be dealt with properly and effectively at the earliest stage of the process. This paper shows how such problems can be addressed by using the existing multidisciplinary methodology. A practical approach consisting of a set of methods, tools, and work processes integrated into the Accelerated Business Development (ABD) approach is applied to a specific use case, a next-generation factory stern trawler development. A detailed step-by-step story of the early vessel design process – requirements elucidation in parallel with concept design solution development – is outlined following a narrative approach. The process being described covers how necessary support information, stakeholders' expectations identification, business[1]related analyses, specific design layout, onboard comfort, and fish process handling and storage are dealt with effectively and efficiently. This case study exemplifies specific solutions to better handle particularly wicked problem situations, but also tamed problems are addressed systemically. The paper concludes by showing how a final ship design solution can look like and consequently be prepared for and to be built. The handover process and documentation from requirements capture and concept design solution development to further basic design activities are highlighted. The case vessel at hand won the prestigious “ship-of-the-year” award in Norway in 2023. The paper critically discusses what are likely to be the most important factors leading to this outcome.

Simulation Study on Student Residential Energy Use Behaviors: A Case Study of University Dormitories in Sichuan, China

Studying the energy use behavior of occupants is crucial for accurately predicting building energy consumption. However, few studies have considered the impact of occupant behaviors on energy consumption in university dormitories. The objective of this study is to establish an agent-based model of energy consumption for university dormitories based on energy use behavior. The dormitories of a typical university in Sichuan, China, were subdivided into three clusters using a two-step cluster analysis. Subsequently, the energy use behaviors of occupants in each type of dormitory were characterized to establish a stochastic energy use behavior model. On the basis of the above, NETLOGO was used to construct an agent-based model for dormitories’ energy consumption to dynamically simulate energy use behavior. The accuracy of the model was verified by comparing the simulated values with the measured data. Finally, a building-energy-friendly retrofit scheme was proposed, and it was found that the optimized dormitory reduced energy consumption by 16.07%. Therefore, the results can provide information support for energy-saving decisions during the early design and retrofit phases of buildings. With the popularity of centralized supply, the research methodology may provide an extensive reference for energy management policies and sustainable strategies in the building sector.

Closing the gap between early and detailed ship design models

Conventionally, ship design and engineering are segregated activities, carried out with different software packages that thus each have their own place, qualities and tools. And consequently, a different data model. As a report on ongoing work to bridge that gap, this paper first explores existing neutral data models and standards employed or considered in maritime applications and concludes that none of these is directly applicable. It continues with describing the requirements and derived abstract data model of the SEUS project and its design and engineering applications. A graph database is identified as a potentially useful tool for SEUS data modelling, and a hands-on experiment confirms this presumption.

Prediction and Optimization Analysis of the Performance of an Office Building in an Extremely Hot and Cold Region

The White Paper on Peak Carbon and Carbon Neutral Action 2022 states that China is to achieve peak carbon by 2030 and carbon neutrality by 2060. Based on the “3060 dual-carbon” goal, how to improve the efficiency of energy performance is an important prerequisite for building a low-carbon, energy-saving, green, and beautiful China. The office performance building studied in this paper is located in the urban area of Turpan, where the climate is characterized by an extremely hot summer environment and a cold winter environment. At the same time, the building is oriented east–west, with the main façade facing west, and the main façade consists of a large area of single-layer glass curtain wall, which is affected by western sunlight. As a result, there are serious problems with the building’s energy consumption, which in turn leads to excessive carbon emissions and high life cycle costs for the building. To address the above problems, this paper analyzes and optimizes the following four dimensions. First, the article creates a Convolutional Neural Network (CNN) prediction model with Total Energy Use in Buildings (TEUI), Global Warming Potential (GWP), and Life Cycle Costs (LCC) as the performance objectives. After optimization, the R2 of the three are 0.9908, 0.9869, and 0.9969, respectively, thus solving the problem of low accuracy of traditional prediction models. Next, the NSGA-II algorithm is used to optimize the three performance objectives, which are reduced by 41.94%, 40.61%, and 31.29%, respectively. Then, in the program decision stage, this paper uses two empowered Topsis methods to optimize this building performance problem. Finally, the article analyzes the variables using two sensitivity analysis methods. Through the above research, this paper provides a framework of optimization ideas for office buildings in extremely hot and cold regions while focusing on the four major aspects of machine learning, multi-objective optimization, decision analysis, and sensitivity analysis systematically and completely. For the development of office buildings in the region, whether in the early program design or in the later stages, energy-saving measures to optimize the design have laid the foundation of important guidelines.

Heat Transfer Models and Measurements of Brushless DC Motors for Small UASs

Heat transfer affects a motor’s sizing, its performance, and, ultimately, the overall vehicle’s range and endurance. However, the thermal literature does not have early-stage models for outrunner brushless DC (BLDC) motors found in small unmanned aerial systems (UASs). To address this gap, we have developed a non-dimensional heat transfer model (Nusselt correlation). Parametric experiments of four different-sized BLDC motors under load in Reynolds-matched wind tunnel tests generated data for model correlation. The motors’ aspect ratios (diameter/length) ranged from 0.9 to 1.5. The freestream Reynolds number of the axial flow over the motors ranged from 20,000 to 40,000. The rotational Reynolds number ranged from 10,000 to 20,000. The results showed that aspect ratio had the largest influence on heat transfer, followed by rotational and freestream Reynolds numbers. A steady-state model used the correlation to predict the motor’s ambient temperature differential within 10 K of experimental data. A case study applied the correlation to predict a hypothetical motor’s continuous torque in different environments. The correlation enables conceptual designers to capture thermally-driven trade-offs in early design stages and reduce costly revisions in later stages.

François Rabelais and his dystonic giants.

Spasmodic torticollis was an early designation used for cervical dystonia. The origin of this name is attributed to French physician and writer François Rabelais in the mid-sixteenth century. This early description of torticollis in the book Pantagruel was an inspiration for the understanding of cervical dystonia. The art expressed in Rabelais' literature ‒ which was immortalized by the drawings of Gustave Doré ‒ influenced poetry, art, and photography, and led to the adoption of the term torticollis in the neurological sciences.

Research on the Energy Consumption Influence Mechanism and Prediction for the Early Design Stage of University Public Teaching Buildings in Beijing

The public teaching buildings of universities have a large flow of people, high lighting requirements, and large energy consumption, which present significant potential for energy saving. The greatest opportunity for integrating “green” architectural design strategies lies in the design phase, especially the early stage of architectural design. However, current designers often rely on experience or qualitative judgment for decision-making. Thus, there is a pressing need for rational and quantitative green architectural design theories and techniques to guide and support decision-making for the design parameters of teaching buildings. This study, based on field surveys of 40 teaching buildings, constructs building archetypes regarding energy consumption including 28 typical values. Based on the “Rectangle”, “L”, “U”, and “Courtyard” archetypes, through batch energy consumption simulation and multiple regression methods, the influence mechanisms of nine energy consumption influencing factors on four types of building energy consumptions were explored, and energy consumption prediction models were derived. The findings of this research can serve as factor evaluation and selection in the early stage of architectural design for public teaching buildings at universities, and the prediction model can assist in the early estimation of energy consumption. This aims to enrich and supplement green architectural design methods by supporting the design of green public teaching buildings and providing reference and application for relevant engineering practices.

Integrated simulation and control environment for the development and safe start-up of cable driven parallel robots

ABSTRACT This article presents a new environment designed to facilitate the conceptualization and automation of CDPRs (Cable Driven Parallel Robots). Utilizing a platform for robotic simulation, an industrial controller, and a data gateway to communicate both systems, it is possible to emulate CDPR motion in early design, development, and start-up phases. Thus, this simulation environment allows to test how the robot will behave in advance in order to obtain a safer and more reliable first operation with the real robot. An spatially under-constrained CDPR with four cables was used to validate the capabilities of the proposed integrated environment, comparing its performance against an industry-standard hardware prototype. Both the simulation model and the real prototype performed the same trajectory in order to assess a time delay and position errors between them. Evaluation results revealed that the simulation accurately replicated the performance of its industrial counterpart, with a peak divergence of 0.27% in the position of the robot under various speed scenarios. This occurs even when accounting for latency arising from data exchange connecting the industrial control unit to the simulation. The results have shown that the environment is suitable for trajectory control of new CDPR architectures under different dynamic conditions.

Integrating Pix2Pix and computational fluid dynamics for enhanced indoor airflow prediction: A case study with wing-walls

Computational Fluid Dynamics (CFD) is often used for analyzing natural ventilation but is limited in early design stages due to its high computational demands and the need for detailed inputs. To overcome such limitations of CFD simulation, this paper proposes a method using a conditional Generative Adversarial Network (cGAN) based image-to-image translation (Pix2Pix) to predict the indoor airflow condition. Compared to other traditional machine learning models that predict averaged values like indoor air velocity, Pix2Pix can predict contour plot of indoor airflow for the given building floor plan image, which provides more intuitive feedback to designers. The proposed method was tested to understand indoor air movement caused by wing-walls attached to the windows. The model was trained using 1153 pairs of floor plan images, incorporating variations in window widths, wing-wall depth, wing-wall angle, wind speed, and wind direction. It achieved a prediction accuracy of 94 % and produced results in less than a second. Moreover, the model showed relatively better performance with the changes in windows and wing-walls properties rather than wind properties. This high performance indicates that Pix2Pix can serve as an efficient proxy model of conventional CFD simulations, helping designers optimize ventilation in building designs at an early stage without the need for complex inputs.

Multi-objective optimisation of a thermocline thermal energy storage integrated in a concentrated solar power plant

Most of CSP plants built today are all equipped with storage devices. Most are sensitive heat storages, in particular 2-tank systems. The aim of this study is to optimise a thermocline storage, designed for the Andasol CSP plant in Spain, on the basis of exergy, environmental and economic criteria. The optimum tank geometry, particle size and heat transfer fluid/filler material pair must be determined. To achieve this, six different fillers operating with Dowtherm A synthetic oil are being investigated: machined ceramics, ceramics obtained from waste materials and natural rock. The NSGA-II multi-objective genetic algorithm is used to solve the problem. This optimisation selects recycled ceramics as best filler materials. The exergy efficiency is not affected by the filler, with more than 99.8%. The application of TOPSIS method combined with weighting derived from Shannon entropy, selects recycled ceramic obtained from electric furnaces as the best filler. This tank has a tapered shape (diameter of 27.4 m, height of 22.2 m) and a very small particle diameter (6 mm). Compared with an earlier design available in literature, the environmental impact is reduced by 19%. The LCOE reaches 10.8 c€/kWhe, a 48% reduction compared with the selling price of heat in Spain (in 2021).

Linking Model-Based Systems Engineering (MBSE) and Multidisciplinary Analysis and Optimization (MDAO) for Early Design of Helicopter Primary Parameters

The design of a helicopter involves multiple disciplines and a large number of technical parameters with conflicting objectives, leading to the challenges of multidisciplinary coupling in design and optimization. In the context of the application of Model-Based Systems Engineering (MBSE) in complex product design, how to bridge the gap between MBSE and Multidisciplinary Design Analysis and Optimization (MDAO) to accelerate the early design process of helicopters remains an urgent problem to be addressed. The paper proposed an optimization framework that links MBSE and MDAO models for the design optimization problem of helicopters. On the MBSE side, the design optimization problem of helicopters was defined through the descriptive SysML model. On the MDAO side, the specific domain analysis model and optimization analysis workflow were established. The integration of design data was achieved through stereotype plugins and design components, bridging the gap between MBSE and MDAO, and providing accurate engineering data for system design verification. The paper provided an optimization case of a helicopter, with the optimal mission performance of the helicopter as the objective function. Through MDAO analysis, the design optimization of fuel consumption, take-off weight, and rotor dynamics parameters was completed, achieving an integrated process of system design and optimization.

Quantifying Impacts of Uncertainties on Certification-Driven Design

Airworthiness certification is challenging for novel aircraft concepts. To avoid the significant cost associated with the redesign for certification compliance, incorporating certification requirements into early aircraft design is desired for unconventional aircraft. However, epistemic uncertainties arising from modeling assumptions, and aleatory uncertainties stemming from uncontrollable noise factors may have impacts on the certification analysis and certification-constrained design process. This paper presents an uncertainty quantification study based on a certification-constrained design and optimization study previously conducted for NASA’s Parallel Electric–Gas Architecture with Synergistic Utilization Scheme (PEGASUS) concept. The epistemic uncertainties are modeled through a set of multiplicative factors applied to intermediate disciplinary variables. The sensitivity analysis between design metrics and multiplicative factors reveals that uncertainties in stability and control derivatives can significantly affect certification constraint predictions, and uncertainties in drag approximations have considerable impacts on the vehicle sizing process. The aleatory uncertainties added to flight dynamics simulations include wind velocities and variations of weight and center of gravity. Four representative design candidates are evaluated for their robustness against aleatory uncertainties based on the Monte Carlo simulation performed on noise factors. The results show that aleatory uncertainties can affect the aircraft dynamic responses in flight test simulations, thus compromising certification compliance.

Bridging simulation granularity in system-of-systems: conjunct application of discrete element method and discrete event simulations in construction equipment design

AbstractThe paper addresses a critical challenge in System-of-Systems (SoS) simulations arising from the different granularity levels in SoS simulations, integrating non-coupled Discrete Element Method results into SoS-level Discrete Event Simulations using surrogate modeling. Illustrated with a wheel loader bucket use-case in mining, it enhances early design decision-making and lays the groundwork for improving SoS simulations in construction equipment design. This paves the way for broader research and application across diverse engineering design domains.

Utilization of the system architecture in the context of validation in the business-to-business (B2B) sector

AbstractThe European Green Deal aims to reduce global emissions by minimizing the use of resources. Early validation of products helps to reduce rework, costs and therefore resources. However, validation of complex mechatronic products is challenging due to interdependencies. Companies are applying systems engineering to meet this challenge. Current validation approaches are insufficient in the early design phases. This paper presents an approach to validation using the system architecture in the B2B sector. A machine tool and a custom built machine are presented as evaluation examples.

Scenario building guidelines for sustainable innovation

AbstractThe integration of sustainability into highly uncertain technology development is key to support manufacturing companies to reduce their environmental impacts. The use of future scenarios to support decision-making in early design for sustainability is promising, but there is a lack of systematic guidelines on how to build them. Through literature review and empirical research scenario-building guidelines were designed. The guidelines are step-by-step activities to be performed in workshops. Results suggest the guidelines were successful in building consistent, plausible, and useful scenarios.

The Karakuri IoT toolkit: a collaborative solution for ideating and prototyping IoT opportunities

AbstractThis paper presents a collaborative solution developed to enable people without prior Internet of Things (IoT) knowledge to ideate, conceptualise, role-play and prototype potential improvements to their work processes and environments. The solution, called the Karakuri IoT toolkit and method, was tested in two workshops with eight production leaders at a Swedish manufacturing company. Outcomes were analysed from the perspectives of materials interaction and instruments of inquiry. Results indicate the solution can help people conceive and prototype improvement ideas at early design stages.

Plantwide flexibility analysis of a biogas to methanol process: Assessing the implications of uncertainties on process duties and emissions

During the last decade, the issue of major concern for the process industry is the reconversion of conventional chemical processes into more sustainable ones, especially in the light of the emission goals set by the EU for 2050. For this purpose several technologies exploiting cogeneration, biomasses and energy integration have been recently conceived. However, these strategies usually imply a reduction in terms of degrees of freedom and a higher sensitivity of the process to eventual uncertainties. In this case, external perturbations could compromise the profitability and sustainability of the system and the design based on nominal operating conditions is not sufficient anymore to assess the actual performance of the plant. In this research work the challenge concerning negative emissions plants and their performances under perturbed conditions is discussed in detail in order to outline and provide a quantitative methodology to enable a more conscious decision since the early design stage.

A tradespace exploration approach for changeability assessment from a system-of-systems perspective: application from the construction machinery industry

AbstractThe rapid development of new technologies such as electrification, autonomy, and other contextual factors pose significant challenges to development teams in balancing competing aspects while developing value-robust solutions. One approach for achieving value robustness is designing for changeability. This paper presents a tradespace exploration from a Systems-of-Systems perspective to facilitate changeability assessment during early design stages. The approach is further demonstrated on a fleet of haulers operating in a mining site.

Multi-objective optimization for gymnasium layout in early design stage: Based on genetic algorithm and neural network

The layout of gymnasium directly affects environment performance. The current methods are insufficient to provide quantified decision support for gymnasium layouts in the early design stages (EDS). This study proposes a framework for optimizing the layout of gymnasiums using a multi-objective optimization (MOO) method based on genetic algorithms (GA) and neural networks. The study tested the framework using a community sports arena as an example, and the results indicate: the final optimized solutions achieved a maximum reduction of 11.1 % in cooling energy consumption (CE) and 3.3 % in solar radiation (SR) compared to the earlier generations, along with a 0.9 % improvement in thermal comfort percentage (TCP). This framework promotes the development of algorithm-driven methods for stadium layout design, while the prediction model based on RBF neural networks can simultaneously provide effective performance predictions for similar design outcomes.

Design and Evaluation of a New Nanoscale and Cost-Efficient Coplanar Digital Parity Generator Based on Quantum Dots

A parity generator as a combinational logic circuit in digital circuits can generate the parity bit in the transmitter. It is very applicable in digital networking and communications. Also, rather than diodes and transistors, quantum dots will be used in the next-generation circuits. Quantum-dot Cellular Automata (QCA) offers a new platform where binary data is represented by polarized cells that are defined by the electron configurations. Therefore, a coplanar 4-bit parity generator is suggested in this work. This new arrangement eliminates complicated crossovers and provides complete access to all input and output pins. An XOR gate is used to implement the suggested architecture. Simulation waveforms and performance data confirm the proposed circuits’ functioning and advantages. The suggested four-bit parity generator uses less overhead than its equivalents. We simulated and tested the suggested circuit with the assistance of the QCADesigner 2.0.3 simulator. The QCADesigner software findings demonstrate that the suggested design is simpler and less expensive than earlier designs. Compared to the present best design, the suggested four-bit parity generator reduces cell number and latency by 55.29% and 40%, respectively.