Early Conceptual Phase Research Articles

The Designers’ Perspective on Autonomous Mining Systems and Sociotechnology

Digitalization and automation technology offer new possibilities to increase productivity and obtain higher levels of autonomy in mining operations. Introducing autonomous systems into mining is not only a technical problem in terms of effectiveness and efficiency, nor a problem of safety in human-automation interactions. The systems also need to be designed and developed so that they foster healthy and attractive working environments. The design and development phase of new mining technology has not been extensively studied previously. To fill this knowledge gap, we investigated technology developers’ basic assumptions about humans and their interactions with the technology they develop. We conducted five semi-structured workshops within an EU funded project concerned with developing digitalization and automation solutions for the mining industry. The data suggests that many critical functions will still be under human control in future mining systems. The results also indicate increased complexity in the interaction between autonomous systems and humans as the technology becomes more advanced. As a result, we suggest that a human perspective, based on sociotechnical principles, should not only be considered in implementing the technology at mines but also in the early conceptual phases of developing and designing the technology. This will ensure healthy and attractive work environments in the future mining industry.

Supporting activities in public infrastructure projects that benefit most from ECI: Focus on the design sub-phase

Complex infrastructure projects have an increasing need to engage contractors in the pre-construction phase. Recent studies show that the early involvement of the contractor has a positive impact on the quality of the design, safety, cost, and time.The purpose of this study is to examine the main supporting design activities in the design-subphase in the pre-construction phase and examine which of these can benefit most from ECI. Semi-structured interviews were conducted, along with 3 workshops, literature studies, and document studies. 16 design activities were identified, and it was concluded that the top three activities that could benefit most from ECI are Constructability Reviews, Operability Reviews, and Design Reviews.Results showed an overall agreement that it would be beneficial to involve contractor competence during the late design-sub phase, more precisely during the transition from late schematic to detailed design process. Results from interviews are in contrast with the literature findings, which indicate that the early conceptual phase is most beneficial as the contractor impact is highest.

Exploring Pre-Construction Activities in Infrastructure Projects That Can Benefit from Contractor Involvement

The pre-construction phase of public infrastructure projects is characterized by significant uncertainty as crucial decisions are made with limited information. This early stage of project development is influenced by a multitude of factors and input from various stakeholders. While early contractor involvement (ECI) offers potential benefits for both clients and projects, the timing and selection of tasks for involving the contractor are critical to achieving these benefits. This study seeks to identify key pre-construction activities in public infrastructure projects and pinpoint the activities that stand to gain the most from ECI. The research methodology involved conducting semi-structured interviews, organizing seven workshops, and conducting the literature and document studies. Through these efforts, the study identified a total of 20 pre-construction activities, among which 5 activities emerged as the most favorable candidates for ECI, while 5 others were deemed less suitable. The findings underscore a consensus that involving contractor expertise during the Brief Development sub-phase holds significant promise. Notably, activities associated with planning, environmental considerations, and technical aspects related to the scope clarification, were found to be highly amenable to ECI. Activities addressing uncertainty management received particular attention, with clients valuing contractors’ practical experience in risk assessment and mitigation. Additionally, contractors’ insights into planning, activity dependencies, and their contributions to health, safety, and environmental plans were highly regarded. However, activities, categorized under the more technical sub-phases of Concept Development and Detailed Engineering yielded mixed results, while those falling within the predominantly social and political domain and involving political processes and societal impact, were viewed as less suitable for early contractor involvement. These findings emphasize the need to adopt a systematic and consistent approach to pre-construction activities, highlighting that ECI should not be applied as a one-size-fits-all solution. The interview results somewhat contrast with the literature findings, which indicate that the early conceptual phase is most beneficial as the contractor impact is highest. To some extent, the client, contractor, and consultant still see their benefit and strategy before the good of the project.

An optimized equation based on the gene expression programming method for estimating tunnel construction costs considering a variety of variables and indexes

Accurate cost estimation in tunneling is key to the project’s success. Such information is critical for the early conceptual and design phases when key choices must be made. Numerous variables influence the cost of tunnel construction, and limited information is available at the early stages of design when the possible use of tunnels is being studied. Therefore, there is a limited number of models at engineers’ disposal to develop a proper cost estimate for tunneling projects. This study aimed to offer a model for estimating the construction cost of drilling and blasting tunnels in the preliminary stage of a project. For this purpose, an optimized gene expression programming (GEP) method was used based on the study of 900 data points obtained from ten drilling and blasting tunnels, which were randomly split into the training (800 data points) and testing (100 data points) datasets. With the experience of previously constructed tunnels, eleven parameters were considered the most effective for the tunnel’s construction cost. The best fit on predictions generated an equation for the optimized GEP model. Finally, by comparing the equation’s outputs with the actual costs and its behavior with practice, its potential ability to estimate the construction cost of drilling and blasting tunnels was approved. Moreover, the Graphical User Interface (GUI) of the GEP model was created as a practical tool for estimating the construction cost of tunnels. This model can reduce tunnel uncertainties and give ML development in tunnel planning.

Predicting tunnel water inflow using a machine learning-based solution to improve tunnel construction safety

Water inflow is a typical and complicated geological hazard that may have a significant effect on both the building timeline and the safety of a tunnel under construction. Therefore, accurate water inflow estimation in tunneling is a key factor for the project's success. Such information is critical for the early conceptual and design phases, when key choices must be made. For this purpose, an optimized model based on the gene expression programming (GEP) method was proposed to estimate the water inflow in tunnels. An equation was generated for the optimized GEP model through the best fit of the predictions. Finally, by comparing the equation’s outputs with the actual ones and comparing its behavior with practice, its potential ability for estimating the water inflow of tunnels was approved. This model can reduce the uncertainties about tunnels and give machine learning development in tunnel planning.

Image regression-based digital qualification for simulation-driven design processes, case study on curtain airbag

Today digital qualification tools are part of many design processes that make them dependent on long and expensive simulations, leading to limited ability in exploring design alternatives. Conventional surrogate modelling techniques depend on the parametric models and come short in addressing radical design changes. Existing data-driven models lack the ability in dealing with the geometrical complexities. Thus, to address the resulting long development lead time problem in the product development processes and to enable parameter-independent surrogate modelling, this paper proposes a method to use images as input for design evaluation. Using a case study on the curtain airbag design process, a database consisting of 60,000 configurations has been created and labelled using a method based on dynamic relaxation instead of finite element methods. The database is made available online for research benchmark purposes. A convolutional neural network with multiple layers is employed to map the input images to the simulation output. It was concluded that the showcased data-driven method could reduce digital testing and qualification time significantly and contribute to real-time analysis in product development. Designers can utilise images of geometrical information to build real-time prediction models with acceptable accuracy in the early conceptual phases for design space exploration purposes.

Holistic eco-design tool within automotive field

In the last decades, sustainability has become a critical issue for the vehicle industry. Today automotive manufacturers are subjected to several government regulations aimed at making the industry more environmentally sustainable. In this context, many research and industrial activities are focused on the eco-design field by developing innovative materials, novel manufacturing technologies, and new methodology; the main objective is to combine the best design performance with increased environmental responsibility. In this paper, a holistic design and sustainability analysis method based on a multi-criteria approach is presented to support the designer in the early conceptual phase finding the best trade-off in terms of performance and sustainability. The new methodology generates a single-score index (SSI) based on product design/sustainability metrics; data normalization, weighting, and aggregation processes are also included in the evaluation method. This method is integrated into an eco-design framework developed through HyperWorks and MATLAB software tools. A case study, based on a reference geometry, a load case, and a list of materials and processes chosen by the designer, is described to show the potential of the proposed methodology. Finally, a critical review and concluding remarks are described following the SSI results; suggestions for further improvements are made.

A mixed-integer linear programming formulation for the modular layout of three-dimensional connected systems

Given the considerable complexity of process plants, there has been a great deal of research focused on aiding the design of plant layout through mathematical optimisation, i.e. optimising the positioning of the equipment in the plant for space and cost efficiency. Recently, the use of modular approaches within the construction industry, whereby work is performed off-site before being assembled on-site, has become a popular and powerful way of reducing build schedules and costs. Modular approaches have many other real applications where items must be packed to minimise the connections between them (e.g. piping, wiring, modular office and factory layouts) and consider the modular layout of the system.In this paper, we provide a formulation of the problem that, in addition to the standard layout problem, considers a modular block layout to allow modular construction and transportation of the plant. The problem is represented as a directed network, with the aim to pack the items into predefined containers and minimise the rectilinear distance between the connected items. We propose mixed-integer linear programming (MILP) models for the 2-dimensional and 3-dimensional problems and solve them using the state-of-the-art mathematical programming solver, Gurobi. Because of the combinatorial nature of the problem, solutions involving a large number of items may not converge and a suboptimal solution must be considered. However, our results suggest that even in the case of optimising a large number of items, the suboptimal solutions found after a reasonable number of iterations where deemed, by a domain expert, to be a good enough starting point to continue the design process, especially in the early concept phase.

FM and clinical employees' involvement in the design of eight Norwegian hospital projects

Purpose This paper aims to gain insight in how the involvement of facilities management (FM) and clinical employees are practiced in new Norwegian hospital projects and to study the benefits and lessons learned from the involvement. Design/methodology/approach This study is conducted by cross-sectional case studies of eight hospital projects by using a literature review, interviews and document studies of FM and clinical employees and project leaders (PLs) among Sykehusbygg. Findings The service design approach with a structured interaction between the PL’s of Sykehusbygg, and the different disciplines of clinical employees and FM specialist was rewarding and efficient. The facilitator role of Sykehusbygg is essential to manage such a broad and complex involvement process using a wide range of various techniques at the different stages of the projects (dialogue meetings, review meetings, workshops, post-it notes, 2-D drawings, mock-up and 3-D models, as well as virtual reality (VR) and Building Information Modeling technology). The clinical employees’ framework is stronger and much more structured than the involvement of FM competences through the different stages of the projects. The property management competences were involved at the early concept phase and design phase, whereas the Operation and Maintenance (O&M) competences were getting involved through the construction and commissioning phase. The value of FM involvement in all stages of the project is seen beneficial, particularly when the FM specialist become a part of the design team and located physically at the same place. The main reported benefits of early FM involvement are cost-effective technical solutions and installations, less design flaws and improved functionality, as well as a stronger ownership and mutual respect between the clinical and FM disciplines. However, not all hospital organizations see the benefits of the FM involvement of all stages, as they are driven by reducing capital cost. In one of the new projects, other ways of involving the FM competences were tested. Additionally, particularly for the O&M competences, a dialogue meeting with a clear focus of sharing experiences with different technical solution was found rewarding in terms of cost benefits. Research limitations/implications This study does not consider the social impact of the choices made in the design phase. The findings also indicated a certain development of the FM involvement. This is not studied in two of the newest projects where they are still in the design phase and the FM role was not interviewed. Practical implications The PL role is important as a facilitator role of the involvement process. Social implications A dialogue meeting with a group of O&M people was found rewarding and valuable for knowledge sharing. This methodology can be further developed and tested, as this group of stakeholders is not always available for giving input in the project. Originality/value The value of this study is the description of the interaction between the PLs and the hospital organization in the eight projects and lessons learned by the involvement of FM competences and clinical employees.

A Component-Sizing Methodology for a Hybrid Electric Vehicle Using an Optimization Algorithm

Many leading companies in the automotive industry have been putting tremendous effort into developing new powertrains and technologies to make their products more energy efficient. Evaluating the fuel economy benefit of a new technology in specific powertrain systems is straightforward; and, in an early concept phase, obtaining a projection of energy efficiency benefits from new technologies is extremely useful. However, when carmakers consider new technology or powertrain configurations, they must deal with a trade-off problem involving factors such as energy efficiency and performance, because of the complexities of sizing a vehicle’s powertrain components, which directly affect its energy efficiency and dynamic performance. As powertrains of modern vehicles become more complicated, even more effort is required to design the size of each component. This study presents a component-sizing process based on the forward-looking vehicle simulator “Autonomie” and the optimization algorithm “POUNDERS”; the supervisory control strategy based on Pontryagin’s Minimum Principle (PMP) assures sufficient computational system efficiency. We tested the process by applying it to a single power-split hybrid electric vehicle to determine optimal values of gear ratios and each component size, where we defined the optimization problem as minimizing energy consumption when the vehicle’s dynamic performance is given as a performance constraint. The suggested sizing process will be helpful in determining optimal component sizes for vehicle powertrain to maximize fuel efficiency while dynamic performance is satisfied. Indeed, this process does not require the engineer’s intuition or rules based on heuristics required in the rule-based process.

Towards a Highly Sensitive Piezoelectric Nano-Mass Detection-A Model-Based Concept Study.

The detection of exceedingly small masses still presents a large challenge, and even though very high sensitivities have been archived, the fabrication of those setups is still difficult. In this paper, a novel approach for a co-resonant mass detector is theoretically presented, where simple fabrication is addressed in this early concept phase. To simplify the setup, longitudinal and bending vibrations were combined for the first time. The direct integration of an aluminum nitride (AlN) piezoelectric element for simultaneous excitation and sensing further simplified the setup. The feasibility of this concept is shown by a model-based approach, and the underlying parameter dependencies are presented with an equivalent model. To include the geometrical and material aspects, a finite element model that supports the concept as a very promising approach for future nano-mass detectors is established.

Performance benchmark of state-of-the-art high-power lithium-ion cells and implications for their usability in low-voltage applications

For vehicle electrical systems, high-power optimized lithium-ion batteries offer superior cycle stability, compactness and weight compared to conventional lead–acid batteries. To identify lithium-ion cell candidates during early concept and development phases, both performance characteristics and a comparison of commercialized lithium-ion cells covering different cell chemistries are needed. Since the market share of high-power lithium ion cells is limited, scientific studies and extensive characterizations are rare. This study closes the gap by benchmarking state-of-the-art high-power cells considering the requirements of 12V/48V applications. The sensible begin-of-life parameters OCV, internal resistance, and capacity were investigated by stepwise OCV measurement, pulse power characterization and capacity measurement regarding the dimensions: SOC (0% to 100%), temperature (−25°C to +55°C) and current rate (up to 30C). All cells exhibit temperature dependent OCV curves, with ambient temperatures above zero hardly affecting the OCV hysteresis. A SOC dependency of the internal resistance of the tested lithium titanate oxide cell reduces the power capability, available cell capacity and energy efficiency. This cell, in contrast to the graphite-based cells, enables a neglection of a Butler–Volmer dependency and offers high charge acceptance at negative temperatures. The internal resistance of the lithium iron phosphate cell is less affected by SOC which allows for constant power output. Above 25°C and up to 15C, energy efficiencies of the graphite-based cells exceed 95%. We conclude that the lithium iron phosphate cell is best suited for 12V applications due to its voltage band and discharge characteristics. None of the cells stand out for use in 48V applications. Our findings from benchmarking among different cell chemistries are beneficial to other research areas such as battery simulation, battery management systems, or cell/system design.

Rapid flood risk screening model for compound flood events in Beira, Mozambique

Abstract. Coastal cities combine intensive socioeconomic activities and investments with high exposure to flood hazards. Developing effective strategies to manage flood risk in coastal cities is often a costly and complicated process. In designing strategies, engineers rely on computationally demanding flood simulation models, but they can only compare a limited number of strategies due to computational constraints. This limits the efficacy of standard flood simulation models in the crucial conceptual phase of flood risk management. This paper presents the Flood Risk Reduction Evaluation and Screening (FLORES) model, which provides useful risk information in this early conceptual phase. FLORES rapidly performs numerous simulations and compares the impact of many storms, strategies, and future scenarios. This article presents FLORES and demonstrates its merits in a case study for Beira, Mozambique. Our results demonstrate that expansion of the drainage capacity and strengthening of its coastal protection in the southwest are crucial components of any effective flood risk management strategy for Beira.

RDE Evaluation in the Early Concept Phase

RDE Evaluation in the Early Concept Phase

Development of an Overall Vehicle Sizing and Packaging Tool for Autonomous Electric Buses in the Early Concept Phase

Development of an Overall Vehicle Sizing and Packaging Tool for Autonomous Electric Buses in the Early Concept Phase

On the inverse identification of Lankford coefficients using geometrical changes under quasi-biaxial loading

Finite element simulation has become an important tool of process and production design in various fields, especially in the automotive industry. The calculation of forming processes in the early concept phase of new cars allows virtual adaptions, which can reduce costs of later phases in the product development significantly. Therefore, the precise characterization and modelling of the material behavior is necessary to ensure a robust and reliable numerical process design. The mechanical properties of numerous materials are highly influenced by the rolling or extrusion direction in the production process. This necessitates the characterization of materials in different loading directions. However, depending on the dimensional aspects of the semi-finished product, the manufacturing of specimens can be challenging or even impossible. Thus, in this investigation, an innovative, indirect approach for the identification of the Lankford coefficient in transversal direction is presented. Based on numerical and experimental data of layer compression tests the Lankford coefficient is determined by inverse modelling of the resulting specimen contour. Due to the characteristics of the layer compression test, it can even be used for semi-finished products with small transversal dimensions like extruded profiles. The presented methodology is on the one hand verified by conventional uniaxial tensile tests for aluminum as well as steel blank material. On the other hand it is used to determine Lankford coefficients for an aluminum extrusion hollow profile and the inversely identified material model is validated by comparison of strain distributions of experimental and numerical square tube bending tests.

Impact of uncertainties on the safety performances of the LBE-XADS concept nuclear reactor

Abstract The demonstration of large operative safety margins is the fundamental requirement for the transition of new generation nuclear reactors from the early concept phase to the initial industrial design one. In order to do so, it is necessary to perform a thorough characterization of the uncertainties affecting the models used for describing the physical behavior of the reactors and to quantify their impact on the safety performances of the plant, typically in terms of the probability of occurrence of deviations from the nominal, or design, operative conditions, often referred to as failure probabilities (reliability analysis). Conceptually, this problem can be solved by framing the problem within a stochastic setting and propagating the uncertainties, represented by suitable probability distributions, by resorting to sampling-based, Monte Carlo (MC) schemes. However, the high reliability of these plants and the complexity of the computer codes used to model their behavior are such that standard MC approaches would require prohibitive computational times. Further computational issues then arise due to the fact that the stochastic models adopted, i.e., the probability distributions, are, in turn, affected by uncertainties, typically related to the inference process adopted to estimate their relevant parameters, so that the estimates of the failure probabilities also become uncertain, with potentially significant impacts on any safety-based decision making process. In this context, the objective of this work is that of providing an innovative computational tool for efficiently performing Sobol-based global reliability sensitivity analysis that allows to satisfactorily quantify the impact of these additional uncertainties on the safety performances of innovative nuclear reactors concepts. The method exploits an original adaptive surrogate modeling with MC variance based techniques, in order to reduce the computational efforts while maintaining sufficient degrees of accuracy. The resulting algorithm is demonstrated with reference to a real innovative nuclear reactor concept, i.e., the Lead Bismuth Eutectic eXperimental Accelerator Driven System (LBE-XADS) reactor. The results of the analysis show the potentiality of the method, offering important insights on the robustness of the concept reactor safety design and suggesting possible paths of improvement, at acceptable computational times.

Approach to the Weight Estimation in the Conceptual Design of Hybrid-Electric-Powered Unconventional Regional Aircraft

The present work deals with the development of an innovative approach to the weight estimation in the conceptual design of a Hybrid-Electric-Powered (HEP) Blended Wing Body (BWB) commercial aircraft. In the last few decades, the improvement of the environmental impact of civil aviation has been the major concern of the aeronautical engineering community, in order to guarantee the sustainable development of the system in presence of a constantly growing market demand. The sustained effort in the improvement of the overall efficiency of conventional aircraft has produced a new generation of vehicles with an extremely low level of emissions and noise, capable of covering the community requirements in the short term. Unfortunately, the remarkable improvements achieved represent the asymptotic limit reachable through the incremental enhancement of existing concepts. Any further improvement to conform to the strict future environmental target will be possible only through the introduction of breakthrough concepts. The aeronautical engineering community is thus concentrating the research on unconventional airframes, innovative low-noise technologies, and alternative propulsion systems. The BWB is one of the most promising layouts in terms of noise emissions and chemical pollution. The further reduction of fuel consumption that can be achieved with gas/electric hybridisation of the power-plant is herein addressed in the context of multidisciplinary analyses. In particular, the payload and range limits are assessed in relation to the technological development of the electric components of the propulsion system. The present work explores the potentialities of an energy-based approach for the initial sizing of a HEP unconventional aircraft in the early conceptual phase of the design. A detailed parametric analysis has been carried out to emphasise how payload, range, and degree of hybridisation are strictly connected in terms of feasible mission requirements and related to the reasonable expectations of development of electric components suitable for aeronautical applications.

Shape grammars as design tools: an implementation of a multipurpose chair grammar

AbstractThis paper presents a multipurpose chair grammar and its implementation in the design toolChairDNA. This tool is oriented for the exploration of design alternatives in the early concept phase of the chair design process. This work addresses two shortcomings within the research area of shape grammars (SGs), namely, the lack of implementation of SGs applied to design domains, and the lack of practical applications in real-life design scenarios. To address these problems, a methodology is proposed for the implementation of a SG (more specifically, a set grammar) into a tool, comprising the translation of the grammar into user-interface elements oriented for design practitioners. By using the proposed tool, the user can add/delete chair components and edit shape parameters, while visualizing the effects on a three-dimensional digital model presented in a variety of CAD applications. Compared with other SG implementations, ChairDNA uses an approach that keeps under control the combinatorial explosion of rule applications, which simplifies the use of the tool by designers that do not have experience in SGs. The generative potential of the tool is demonstrated by generating chairs of different types, and its usability and utility in aiding the designer are evaluated by design students and design practitioners.

Inscriptions in Educational Design Team Meetings

Drawing and sketching are known to have been immensely beneficial to the design process in many domains, especially those in which the focus is on a tangible product, such as a car or a building. In contrast to these design fields, educational designers deal with abstract ideas and concepts—with learning processes that are not easily visualized—either in the imagination or in design drawings. This may be one of the reasons why educational designers are lagging behind other domains in utilizing drawing practices during the early conceptual phases of design. This article presents an exploratory investigation of how three small design teams created and used drawings (inscriptions, in this study) in support of their face-to-face design activities. It presents a new perspective on studying the process of educational design and has implications for the design and development of educational design tools and environments, as well as for training educational designers.