Early Design Stage Research Articles

Harmonic Method for Simulating Unsteady Multispool Interactions

Abstract Modern civil jet engines arrange components on spools with different rotational speeds in order to improve compressor stall margin, overall engine performance, etc. The unsteady interactions among these components can be significant and should be considered at an early design stage if possible. Unsteady Reynolds-averaged Navier–Stokes (URANS) is a common approach to simulate these unsteady effects, but the disparity in time scales in a multispool simulation can lead to expensive URANS simulations. Harmonic methods are effective and efficient approaches to simulate unsteady interactions among turbomachinery components, but their applications to multispool simulations remain a challenge. The objective of this paper is to address this challenge. This paper extends the Favre-averaged non-linear harmonic method to simulate multispool turbomachinery components using a unified bladerow interface which transfers disturbances through bladerows with arbitrary blade counts at any rotational speed. The regularization of non-reflective boundary condition is described for certain circumferential wave number of the zero-frequency mode. The capability of the proposed approach is demonstrated by simulating the transfer of hot streaks through full 3D high- and intermediate-pressure turbines in a three-shaft engine. The temperature distributions from the harmonic method show good agreement with direct unsteady simulation in terms of the mean flow and the instantaneous flow. The radial migration of the hot streaks towards the hub are captured very well by the proposed harmonic method. The required wall-clock time of the harmonic method is roughly 240 times smaller than the whole annulus URANS simulation. This demonstrates that the proposed method can be an efficient design tool to trace hot streaks in multispool turbines at the early design stage.

Creating a common ground for the implementation of a community-based Marine Protected Area – a case study in Algarve, Portugal

Marine Protected Areas (MPAs) are a key tool for the worldwide strategy to halt the decline of biodiversity, yet they can also escalate conflicts between different human activities, conservation and other societal interests. Enabling conditions to secure MPAs effectiveness and the ability to deliver the desired socio-ecological outcomes often include the application of participatory approaches. One example of these approaches are collective visioning exercises where stakeholders can work together, projecting into the future their expectations and goals for MPAs. Our study presents a visioning exercise, using an adaptation of the Territory Game technique, as a starting point of a long and comprehensive participatory process to implement a community-based MPA in the southern part of Portugal. This particular MPA aims at protecting one of the largest rocky reefs of the Portuguese coast, an important biodiversity and human activities' hotspot, stressing the need to accommodate different interests into its design and planning. To the best of our knowledge, and in the context of an MPA, this is one of the few studies in the literature where the process of creating a stakeholders’ shared vision is described. Stakeholder mapping and raising interest activities were used to motivate their participation. A total of 7 visions were co-created by 50 stakeholders of 30 different institutions. From this set we were able to congregate a shared vision that became the flag of the subsequent participatory process. The visioning exercise made explicit that the MPA is a long-term investment, that includes immediate costs and benefits, some that will only arrive later. Considering the immediate costs, the desire to identify compensatory measures was also made explicit. Our results show that using visioning exercises in the early stages of an MPA design broadens the discussions and paves the way for less consensual tasks such as MPA zoning and regulation.

Estimation of engineering bedrock layer utilizing ground surface elevation in Gaussian process regression

An understanding of the ground structure has a significant impact on the performance of any structure built. Many cases of substantial inclination and settlement of buildings due to insufficient understanding have been reported. In the early stages of design, it is often difficult to estimate the depth to the bedrock layer over a wide area from a very limited number of borings. It is known that the elevation of the engineering bedrock layer and ground surface elevation are highly correlated. Ground surface elevation are useful as information on the elevation of the engineering bedrock layer because such data are available in the early stages. This paper proposes a methodology for estimating the spatial distribution of the engineering bedrock layer by utilizing the ground surface elevation in Gaussian process regression. We focus on the tendency of the engineering bedrock layer to be close in elevation to the ground surface when the slope angle is large. If the slope angle is below a certain value, the ground surface elevation is considered to have no significant information for engineering bedrock estimation and is excluded from observation. The estimation accuracy is evaluated by cross-validation, and the effectiveness of the proposed method is discussed.

Development of a new dynamic hysteresis model for magnetorheological dampers with annular-radial gaps considering fluid inertia and compressibility

Modeling the inherent non-linear dynamic hysteresis behavior of magnetorheological (MR) fluid dampers is a fundamental necessity for their practical implementation. Quasi-static models, have been developed under very low frequency and small amplitude excitation conditions, are only beneficial in the early stages of MR dampers design and are sufficient for manufacturing requirements. These models, however, have failed to predict the non-linear hysteresis behavior of MR dampers (i.e., force-displacement and force-velocity characteristics) under low to moderate ranges of frequency and displacement amplitudes. The main contribution of the present work is to formulate a novel physic-based dynamic model to predict the non-linear behavior of MR dampers featuring an annular-radial bypass valve under different applied currents, and low to moderate input excitations. The proposed model incorporates unsteady fluid behavior and the fluid compressibility effect on the hysteretic response without relying on experimental data to evaluate the model parameters. To derive the model, the velocity profile and the pressure drop have been derived by solving the fluid momentum equation via the Laplace transform technique and Cauchy residue theory. The continuity equation has been employed for considering the compressibility contribution to hysteretic response based on the variation of bulk moduli. The predicted results for the force-displacement and force-velocity behavior of the MR damper were subsequently compared with the experimental results. Results suggest the effectiveness of the proposed model for predicting the dynamic hysteresis characteristics of the annular-radial MR fluid dampers under the relatively sufficient variation of mechanical and magnetic loading conditions considered.

On the model complexity of the air handling unit to investigate the energy efficiency of indoor swimming pool facilities

Building performance simulation is a powerful tool applied both in research and for building design including heating, ventilation, and air-conditioning systems. Several research studies have used this tool to investigate the potential of energy savings measures for swimming facilities. However, in these facilities the technical complexity is a considerable challenge in modelling since many complex phenomena occur in the various sub-systems. The building industry traditionally plans and design these complex buildings by heuristic rules of thumb, and these empirical design rules may lead to significant differences between real and predicted performance. Therefore, it's important to develop simplified models with acceptable accuracy for simulation-based design of swimming facilities. The scientific literature introduces different simplifications for the air handling unit modelling, but the impact of these simplifications is hardly analyzed. Therefore, the paper investigates the model complexity of the air handling unit in a Norwegian swimming facility by comparing a novel simplified model and a detailed model which serves as a digital replica of a real unit. The simplified decoupled model is found to have an acceptable accuracy for early-stage design, bearing in mind the overall uncertainty at this design stage. However, when carrying out a detailed investigation of a swimming facility, the detailed model should be applied, since this complex heuristic rule-based model, is taking into account phenomena like thermal-coupling effects between the swimming pool and the air handling unit and the control errors of the real internal controller. In conclusion, the paper derives useful guidelines for building performance simulation design of air handling unit, which is the main energy-intensive component in indoor swimming pool facilities.

Fast NVH Prediction for E-Motor Noise and Validation

Fast NVH analysis from the start of the motor design is important to speed up product development by avoiding major NVH issues later. In this paper, different methods for electric motor noise and vibration predictions are proposed for different stages in the design process. The results are compared to previous experimental validation [1]. The first method combines electromagnetic finite element analysis to calculate the forces, with analytical models for the stator vibration and acoustic response [2]. This requires minimal structural design data, and can be carried out rapidly, allowing the exploration of many design possibilities in the early design stage, and is implemented in Ansys Motor-CAD. This is compared with the full structural finite element analysis (FEA) [1]. It is shown that the fast analytical NVH process provides a good prediction for the motor noise level early in the design process. The structural FEA approach provides additional information about the structural response at a later stage to refine the design. The use of frequency response functions (FRF) derived from the structural FEA are demonstrated, allowing the rapid calculation of noise results from the electromagnetic forces.

Towards an earthquake-resistant architectural design with the image classification method

ABSTRACT Architectural design is an interdisciplinary process which involves multiple stages that are interconnected. In this process, it is common for major decisions to be changed during the final stage, the analysis of the structural system. After making substantial corrections, the architect has to revisit the early stages, the preliminary project. This back-and-forth process can result in significant losses in time and cost. The proposed Irregularity Control Assistant (IC-Assistant) aims to provide architects with feedback on the conformity of structural system decisions to the irregularities defined in the Turkish Building Earthquake Code (TBEC-2018), using image processing methods at the early stages of the design process. The IC-Assistant was preliminarily created to evaluate the torsional irregularity of plan organization using deep learning methods. In this study, the results of the IC-Assistant were verified by structural analysis with the Prota-Structure program. The novelty of this study is the use of the image-classification method in earthquake-resistant architectural design. Up to this point, the method has been mainly used in facial recognition systems. This method minimizes time, human error, and cost losses and includes awareness of load bearing and earthquake resistance as inputs in the early stages of architectural design.

Holistic Approach for Assessing Buildings’ Environmental Impact and User Comfort from Early Design: A Method Combining Life Cycle Assessment, BIM, and Active House Protocol

Due to our increasing dependence on resources and energy, climate change is among the most tangible issues we are facing today. The construction industry has been identified as a key sector to intervene in, but mitigation strategies must focus on more than just operational energy. As current climate policies recommend, designers should consider the broader framework of environmental impacts characterizing the entire building lifecycle. Life Cycle Assessment (LCA) considers the mentioned aspects. Nevertheless, the complexity of LCA and the criticalities of related tools prevent the application of the approach during decisive early stages. Additionally, LCA allows the estimation of environmental issues, but fails to describe other dimensions of sustainability. The article proposes an evaluation method to support decision-making during the design of sustainable buildings. The method exploits the LCA tool and the assessment framework provided by a Green Sustainable Building Certification (Active House) integrated with BIM. The approach was applied and proven through a case study: a residential single-family building in northern Italy, comparing two technological options. The study confirmed the effectiveness of the multicriteria evaluation framework that, from the early design stage, can be used to measure the environmental impact of buildings alongside implications for the final users’ comfort.

Strategic and flexible LNG production under uncertain future demand and natural gas prices

The expectation in global demand for liquified natural gas (LNG) remains bullish in the coming years. Despite the unprecedented impact of the COVID-19 pandemic, and the oil price wars between OPEC and Russia in 2020, causing oversupply and falling prices, the LNG markets continue to demonstrate flexibility and resilience in delivering the needs of different sectors, whilst helping achieve the emissions targets. This is attributed to the high competitiveness amongst LNG producers and suppliers, providing greater confidence for medium-to-long term demand. However, the uncertainties in the current outlook for the return of demand and price growth in the post-COVID period pose difficulty for new liquefaction project investment decisions in the pre-Investment Decision Phase (pre-FID). Accordingly, the consideration of new production and selling strategies is needed in the early design stages of projects to cope with the shift in buyers' sentiments favouring increased reliance on spot and short-term uncontracted volumes, as well as incorporating additional flexibility into long-term contracts. In this study, the economic valuation of the flexible Air Product's AP-X liquefaction technology was investigated considering the modelling of price volatilities, using the mean-reverting jump-diffusion pricing model and Monte Carlo simulation, assuming different demand level scenarios in the high-income Asia Pacific markets based on historical trends. The results clearly demonstrate that embedding flexibility within an LNG production system allows producers and suppliers to diversify selling strategies, and take advantage of the lucrative market conditions when demand and prices increase, and hedge against market risks when demand and prices are low.

IMPRoVED: Integrated Method to Predict PostRouting setup Violations in Early Design Stages

The detail routing process is by far the most time consuming during the physical design flow. Routing starts with an estimation of timing slacks and aims to meet the timing specifications at signoff. In this paper, we propose an improved method to predict the net delays using RandomForestRegressor and thereby predict critical paths early on at the placement stage. Quick timing prediction is also essential in making time-sensitive edits to stepping of the chip based on post-Si feedback. The proposed algorithm is based on five novel features, namely, targeted feature selection, introduction of a one-hot encoding scheme, an outlier identification method, post-route buffer-bloat prediction, and post-route cell sizing prediction. Experimental results on academic benchmarks and industry circuits, both on advanced 10nm process node show that the proposed algorithm has led to significant improvements in accurately predicting timing slacks when compared with state of the art. The proposed algorithm predicts slack within 0.598% of signoff results, whereas the state of art results are erroneous by an average of 53.33% for the same metric. Overall time savings of 44.1% is seen when compared to running the traditional flow, and savings of 90% is seen for obtaining the timing results.

Caseworkers’ participation in procurement: Infrastructuring Child Welfare Services in Norway

Procurement is a widely adopted collaborative approach for acquiring new systems in the public sector. It exemplifies a situation in which the early stages of digital system design define the boundaries and constraints of a new system that must be specified in the tender document (i.e., a binding offer). Researchers and government officials have long recognized the benefit of end-user participation in system design. Given the central role of the pre-tender phases in procurement processes, however, there is a need to better understand what affects user participation in such early stages. In this paper, we research a procurement process in municipal Child Welfare Services in Norway. We focus on caseworkers' participation in procuring a future case management system. We build on the concept of participatory infrastructuring to characterize how the meaning of participation was shaped through three overarching participatory infrastructuring practices of decision-making within a rigid procurement process: (i) scaling up the project, (ii) negotiating participation in meetings with potential suppliers and in tender documents, and (iii) positioning caseworkers as subject experts. The analysis of these practices reveals that the definition of user needs in the tender documentation and the creation of knotworks define both the boundary conditions and the modalities of participation. We contribute to the conversation on participatory infrastructuring in Computer-Supported Cooperative Work by discussing how participatory infrastructuring provides a conceptual understanding of participation in the context of municipal systems procurement.

Effects of latitude and building orientation in indoor-illuminance levels towards energy efficiency

As a matter of concern in sustainable buildings, daylight is studied to improve the balance between visual comfort for the occupants and energy consumption. This study analyzed the effects of latitude and orientation on the sunlight illuminance level within a northwest/southeast-oriented hypothetical house, with a wide-glassed façade, by integrating the BIM and BEM methodologies. The house was located in five different locations showing different latitudes: Búzios, Brazil; Capri, Italy; Punta Cana, Dominican Republic; Dubai, United Arab Emirates; and Sydney, Australia. Five different studies were carried out for each one of them by using the Autodesk REVIT energy-analysis tool named Lighting; they included sun-path analysis, calculation of daylight factor and daylight autonomy, and evaluation of daylight illuminance levels. It was found that a high amount of sunlight enters the house on its rear side, where are located the most occupied rooms, predominantly in the summer season, in the afternoon hours; however, 67% of the total house is below the 2% of daylight factor threshold. Withal, the rear-side rooms are the ones that satisfy most of the time with illumination levels above 300 lux, with maximum levels varying according to the season. This research contributes to associating BIM and BEM methodologies as an option to improve the design of energy-efficient buildings, being possible to consider further improvements to enhance the illuminance in the rooms, both for the early design stages and for future retrofit plans.

Pre-Sizing Approach of a Fuel Cell-Battery Hybrid Power System with Interleaved Converters

This paper proposes a design methodology that is dedicated to improving the concept of a modular hybrid power chain that uses interleaved converters. The approach involves optimising the system under multi-physical constraints, where the number of cells in the interleaved converters is considered as a key modular parameter. The methodology uses analytical models to strike a balance between computation time and result accuracy. This compromise is indispensable to the construction of a smart design approach under multi-physical constraints, such as electric, efficiency, volume, and thermal constraints. The proposed approach has been applied to a hybrid fuel cell and battery power system for automotive applications; the goal is to obtain a global optimal architecture chain by optimising the number of interleaved converter cells and by determining appropriate power electronics components and the optimal sizing of sources. This constitutes the primary step for providing an effective pre-design support tool for considering architecture modularity, facilitating the use of new technologies in the early design stage. The results showed that the interleaving concept allows for better flexibility in respecting the design constraints to improve the design of hybrid power systems. The analysis also highlights the current limitations and performance of the optimisation method and suggests new areas for future work.

Facade Style Mixing Using Artificial Intelligence for Urban Infill

Artificial intelligence and machine learning, in particular, have made rapid advances in image processing. However, their incorporation into architectural design is still in its early stages compared to other disciplines. Therefore, this paper addresses the development of an integrated bottom–up digital design approach and describes a research framework for incorporating the deep convolutional generative adversarial network (GAN) for early stage design exploration and the generation of intricate and complex alternative facade designs for urban interiors. In this paper, a novel facade design is proposed using the architectural style, size, scale, and openings of two adjacent buildings as references to create a new building design in the same neighborhood for urban infill. This newly created building contains the outline, style and shape of the two main buildings. A 2D building design is generated as an image, where (1) neighboring buildings are imported as a reference using the cell phone and (2) iFACADE decodes their spatial neighborhood. It is illustrated that iFACADE will be useful for designers in the early design phase to create new facades in relation to existing buildings in a short time, saving time and energy. Moreover, building owners can use iFACADE to show their preferred architectural facade to their architects by mixing two building styles and creating a new building. Therefore, it is presented that iFACADE can become a communication platform in the early design phases between architects and builders. The initial results define a heuristic function for generating abstract facade elements and sufficiently illustrate the desired functionality of the prototype we developed.

Welcome, How Can I Help You? Design Considerations for a Virtual Reality Environment to Support the Orientation of Online Initial Teacher Education Students

Alongside the rapid and broad uptake of online learning in higher education, fully online students report feeling isolated and disconnected from their institutions. Although formal course content may be expertly designed to engage online learners, much of the information provided to support higher education students’ orientation to the institution and to study is presented online in a written static form. Such presentations may not be accessible and engaging and may contribute to feelings of disconnection. Technologies such as virtual reality (VR) are being used in higher education to engage, motivate and connect students in their learning. This paper reports on the early design stages for a VR that aims to support initial teacher education students to connect and engage with key orienting information. The design of the VR was achieved by following a user-centred, iterative engineering design process and design principles of spatiality, interaction and narrative. The VR environment emulates the School of Education’s physical, on-campus reception area to provide an immersive experience where students have a choice in the types and format of key study information they receive. This experience was designed to be utilised in online orientation but also throughout students’ first year of study. Future research directions include collecting student responses to the VR to inform how students can be involved in enhancing the VR so that it supports their learning and sense of connection. Furthermore, future research can aim for the expansion of the VR inclusive of additional information, rooms and buildings and increased capabilities such as gamification and mobile access. This will enable the creation of a valuable teaching resource for online programs.

An integrated framework for sustainable process design by hybrid and intensified equipment

With the increasing concern of the competitive market and carbon emissions, a sustainable, efficient process design becomes more and more important. The task of sustainable process design is to find efficient configurations and operating parameters to produce products or utilize materials. Currently, the scientific community's major focus is on separation synthesis, which aims to identify the best downstream separation configurations through different methods such as optimization, heuristic, and hybrid methods. Besides, innovative separation techniques with lower capital/operating costs and carbon emissions were proposed and identified to further improve the downstream process performance. However, most of the separations synthesis methods were based on conventional unit operations and usually applied for generating sustainable processes with a given reaction pathway without considering the possibilities of different raw materials. Generally, to produce a given target product, multiple reaction pathways are available, and each reaction pathway leads to different downstream processes. Also, applying intensification in the early stages of process design, e.g., separation synthesis, can generate sustainable process flowsheets with higher energy efficiency and lower environmental impact. This work aims to develop an integrated process synthesis framework, which includes reaction synthesis for the reaction pathways selection and separation synthesis involving intensified/hybrid units. So, for the new process design, given the product one needs to produce, this framework could identify the optimal reaction pathway with its best separation route. The developed framework was used to solve three case studies, including the new process design of dimethyl carbonate (DMC) production and retrofitting design of cumene and styrene production. For all the case studies, the framework was able to generate multiple innovative solutions that are sustainable and energy-efficient.

High-Precision Fitting of Simulation Parameters for Circuit Aging Effect

To take the influence of the aging effect on circuit performance into account at the early design stage, it is necessary to establish an accurate aging simulation model. However, there is a great discrepancy in the reversely deduced MOSFET transistor degradation from the aging model. To deal with that problem, a method is proposed in this paper that establishes the conversion relationship between the simulation parameters and the degradation of MOSFET transistor parameters. The degradation values were converted into model parameters that characterize the aging effect in SPICE, and the results show that aging simulation accuracy was improved to within 0.1%, which would bring great convenience to circuit reliability simulation and analysis. Lastly, we analyze the aging effect on the ring oscillator circuit via the model.

Inherent safety of clean fuels for maritime transport

The urgent need to reduce the emission of harmful pollutants in maritime transport promoted the development of several alternative propulsion systems based on clean fuels or carbon-neutral energy vectors. However, the alternative solutions under development pose new concerns from the safety perspective. Thus, an innovative methodology to rank the inherent safety performance of alternative systems at early design stages was developed. A case study representative of long-distance maritime transportation was analysed. The inherent safety performances of Liquefied Natural Gas (LNG), Liquid Hydrogen (LH2), and Liquid Ammonia (LNH3) were compared to that of Marine Gas Oil (MGO), assumed as a benchmark representing state-of-the-art technologies. Uncertainty and robustness of the safety ranking obtained were tested via a Monte Carlo analysis. The results show that technologies based on LNG have similar safety performances with respect to the benchmark option. Conversely, LH2 safety performance is currently limited by the lack of mature technologies for its safe storage whilst the safety of LNH3-based applications is affected by the toxicity of ammonia.

Investigating the applicability of human reliability analysis methods during early design stages of non-light-water nuclear power plants

Human interventions are an integral part of any system, whether through design, operation, maintenance, or upgrading. Moreover, although the reliance on human intervention in safety-related actions in advanced reactors (e.g., Generation IV) is expected to be reduced or completely replaced by automated actions, nuclear power plants (NPP) require human actions throughout their lifecycle from design, construction, operation, and decommissioning. Hence, the impacts of all operator actions are required to be captured and incorporated in the probabilistic risk assessment (PRA) of the modeled plant. Furthermore, a risk-informed and performance-based design and licensing approach expects that a PRA model, including human reliability analysis (HRA), is developed starting from the early design stages and used to inform all design iterations. However, due to the lack of details during the early design stages, HRA is often postponed until the design is mature enough. Conducting HRA in the final design stages, though adequate in capturing pre-, at-, and post-initiators, comes short of informing the design itself in the iterative design lifecycle. Moreover, due to most HRA methodologies being developed utilizing mostly the operating experience of existing light water reactors, limited guidance is available to the applicability of different HRA methodologies during the early stages of the design. Limited guidance is available, as well, on how to utilize the results of HRA in informing the design of later iterations. Hence, this study presents an investigation of the applicability of different HRA methodologies during the early stages of the design. The structure of a representative set of nine HRA methodologies is assessed against the available operating and emergency procedures within different design stages. Furthermore, these different HRA methodologies are assessed based on the availability of guidance on how to use their results to risk-inform the design in an iterative design process. Finally, the applicability of Open Preliminary Human Importance (OpenPHI) methodology, introduced specifically to implement HRA during early design stages, is assessed during the early stages of the design and compared against other methodologies.

Combining Bayesian active learning and conditional Gaussian process simulation for propagating mixed uncertainties through expensive computer simulators

Resulted from the limited information on both parameters and excitation at the early design stage of aerospace structures, evaluating the reliability with high accuracy has been recognized as a challenging task. Imprecise probability models have been widely developed and accepted due to their flexibility in separating the aleatory and epistemic uncertainties, and then the potential of estimating the reliability with high confidence. However, the propagation of these models through expensive-to-evaluate simulators remains to be a challenge due to the hierarchical model structure. To fill this gap, a new Bayesian active learning method is devised for efficiently learning the functional behavior of the failure probability and response variance over the epistemic input parameters. This information is especially useful for evaluating the safety of structures and for managing the uncertainties during the design process. The proposed method is based on training/updating a Gaussian Process Regression (GPR) model in the augmented space of aleatory and epistemic parameters, with the training data actively produced using two well-designed acquisition functions. The induced posterior features of the quantities of interest are inferred numerically based on efficient simulation of the GPR model. Benefiting from the decoupling scheme and the Bayesian adaptive design strategy, the proposed method is extremely efficient and provides accuracy guarantee for the numerical results. The effectiveness and superiority of the proposed method are demonstrated with numerical and engineering benchmarks, including the dynamic reliability analysis of a satellite structure.