Design Solutions Research Articles

Carbon-optimised refurbishment measures for a simulated house in Edinburgh

ABSTRACT This research is conducted in the context of current efforts for net zero delivery in Scotland. Such a target is widely acknowledged as challenging by the industry necessitating some aspects of building design to change for higher performance. This study looks at ‘what is optimal’ in terms of carbon, both in operation and embodied in materials for dwellings by using the Pareto Optimal solution in a simulated case study in Edinburgh. At first, the potential of available glazing systems to find an optimum in operational and embodied carbon is investigated. The study then calculated the embodied carbon and operational carbon for added insulation and compared them against each other to find the most energy and environmentally-efficient option. An analysis to investigate the LCA of the 52 HVAC systems for the second phase of the building's life span is then conducted and finally a parametric analysis of using shading devices to observe if they can offer operational savings for the case study concludes the paper. This study demonstrates some recommended design solutions by globally used standards e.g. Passivhaus and common practices may not lead to carbon emissions minimisation in the refurbishment process.

Pressure Guidewire Indicated for Coronary Fractional Flow Reserve Assessment: Structural Design, Deficiencies and Potential Solutions.

Coronary heart disease (CHD) is one of the leading causes of mortality worldwide. It is primarily caused by myocardial ischemia and hypoxia resulting from atherosclerotic plaques in the coronary arteries, leading to symptoms such as angina. The severity of CHD determines the treatment approach, which may include medication or interventional therapy. Therefore, accurately assessing the severity of myocardial ischemia is crucial for effective CHD management. In recent years, fractional flow reserve (FFR), derived from the relationship between flow and pressure, has gained widespread recognition for providing valuable information to guide coronary revascularization. Pressure guidewires equipped with pressure sensors at their tips are the most commonly used tools for clinical FFR assessment. These wires measure vessel pressure to determine the severity of coronary lesions. However, during their use, issues such as signal drift, tip breakage, core wire fractures, and coating detachment may occur. This article reviews the historical development of pressure guidewires, examines the general structure of two commonly used pressure guidewires available in the market, highlights typical issues encountered during clinical use, and proposes corresponding solutions.

How can patent-based prospective life cycle assessment be used for eco-design?

Over the years, eco-design methods increasingly refer to the product conceptualization phase, guaranteeing increasingly sustainable results. To move in this phase in the most strategic way, it is necessary to seek solutions related to design interventions and reliably select the most sustainable options. This study proposes a new method to actively use the prospective LCA in eco-design, for the identification and evaluation of solutions to solve an environmental problem, defined at the detail level of design features. Both the solutions and the data needed to evaluate their environmental impacts prospectively are extracted from patents through a systematic procedure, ensuring compliance with the quality and reliability requirements prescribed by the ISO 14040 and ISO 14044 standards. The more general result highlighted by the case study is the comparison between prospective LCA and eco-design, from which it emerges how the former can actively support design rather than merely evaluating existing solutions. In patents, solutions at the level of detail of design features and technical parameters can actually be found and evaluated at this level trough prospective LCA. Eco-design conducted according to these solutions makes it possible to address environmental problems related to excessive consumption of resources associated with one or more phases of the life cycle of a product component. Beyond new theoretical speculations on the relationship between prospective LCA and eco-design, this study has helped to show that a patent search, also conducted according to the criteria of the ISO standards, allows this intersection to close the circle on the eco-design. In this way, it is possible to be surer of finding and selecting the design solutions that can actually solve the environmental problems of a product.

Advanced Architectures of Microfluidic Microcapacitor Arrays for 3D-Printable Biomimetic Electrostatic Artificial Muscles

Artificial muscles underlie exciting, novel technologies that have many wide-reaching applications: exoskeleton actuation, walker robots, prosthetics and stealthy underwater propulsion. Actuating these muscles via electrostatic forces promises excellent energy efficiency and output force density and a high strength-to-weight ratio. Building these muscles through 3D-printed and conductive microfluidics promises fast mass production at a low cost. A microfluidic double-helix weave as a potential solution for the architectural design of these actuators has previously been reported. However, more recent experimental work showed that a weave architecture was not manufacturable at the necessary scale, given the limitations of current 3D-printing technology. Herein, several alternative architectures are presented. They are more advanced and more compatible with current manufacturing requirements, and offer additional benefits. The presented experimental results confirm their improvements in manufacturability. These advanced architectures represent a significant step towards the experimental proof of principle and the practical implementation of electrostatic microfluidic 3D-printed artificial muscles.

ОБЗОР КОНСТРУКТИВНЫХ ОСОБЕННОСТЕЙ ВАГОНОВ ЦИСТЕРН

The study objective is to find a promising development direction in tank engineering. To achieve this goal, it is necessary to analyze existing engineering solutions, as well as to consider trends and limitations in the development of the domestic tank stock, and it is especially important to consider the design solutions used abroad. The paper includes the result of collecting and subsequent analysis of data on the design features and engineering solutions used abroad. When working with the obtained data, the most rational design option was determined, requiring a more detailed study of specific unites using computer modeling methods.

Design Methodology Development for High-Energy-Efficiency Buildings in Algerian Sahara Climatic Context

In Algeria, the rapid increase in population and urbanization, evolving comfort needs, subsidized electricity prices, and climate change has significantly contributed to higher energy consumption for heating and cooling as well as greenhouse gas emissions, particularly in southern regions characterized by hot and arid climates. Most recent constructions in Algeria are highly energy-intensive, unlike traditional Saharan architecture, which is far more environmentally friendly. This paper presents eco-friendly and cost-effective design methods and solutions inspired by Saharan architecture to guide architects and project owners during the design phase of buildings in hot climate regions. A numerical simulation was performed using EnergyPlus 9.2 to compare the energy consumption of a semi-collective residential building in Béni Abbès with four design alternatives inspired by vernacular architecture, “O”, “L”, “U”, and rectangular configurations. The findings showed that the O-shape configuration achieved the highest cooling energy savings (38.55% on the ground floor, 27.68% on the first floor), followed by the L-shape (31% and 32%), U-shape (28% and 29%), and rectangular shape (26% and 25%), highlighting the effectiveness of form optimization in enhancing energy efficiency. The results obtained demonstrate the energy efficiency of the four variants compared with the initial cases, with a reduction in cooling needs while using the same materials. This reduction could reach up to 39% during the hot season. The pay-back period for the investment was estimated at approximately six years for the city of Béni Abbès and around five years for the city of Adrar. By incorporating full insulation into all four variants, a maximum reduction in air conditioning consumption of approximately 53% was observed for the “O” variant in Béni Abbès compared with the initial case without insulation. In Adrar, this reduction reached around 48% for the same variant. Passive design elements, such as shape optimization, compact urban fabric, patio integration, and window shading, offer moderate energy savings with a shorter payback period, whereas complete insulation achieves higher energy savings but requires a longer time to offset the investment costs.

Mobile Application Prototype for Foot Self-care Support for Persons With Diabetes: A Human-Centered Design Approach.

The human-centered design approach has gained prominence in the development of mobile health solutions. However, its application to support foot self-care for persons with diabetes has not been extensively explored. This study aims to develop a mobile application prototype using a human-centered design approach to support foot self-care for persons with type 2 diabetes. The project used mixed methods, including a scoping review, patient interviews, a Delphi panel, and an acceptability and usability study of an educational booklet. This three-phase approach encompassed defining the context of use, specifying user requirements, and developing design solutions. This article specifically details the third phase of the project: the development of the low-fidelity prototype. Functionalities such as daily reminders for foot care, notifications for medical appointments, communication features with healthcare professionals and peers, and repositories of videos and educational content were integrated into the design. These features were tailored to address user needs, emphasizing knowledge enhancement in self-care practices. The human-centered design approach enabled the creation of a comprehensive prototype with essential functionalities and robust educational content, filling gaps in the digital health market and empowering persons to better manage their foot health.

Design 360

Design 360 is an augmented reality (AR) application that revolutionizes interior design by enabling users to visualize and interact with 3D furniture models in real-world spaces. The application allows users to place, adjust, and customize furniture elements such as chairs, sofas, and tables in an immersive AR environment. By leveraging Unity and AR frameworks, Design 360 enhances user experience through real-time scaling, positioning, and selection features. The project aims to bridge the gap between traditional interior design planning and digital visualization, offering an intuitive and interactive solution for homeowners, designers, and furniture retailers. Future enhancements include improved object rendering, AI-driven design recommendations, and enhanced user interactivity to refine the virtual design experience.

The Community-based Responses to the Opioid Crisis: Lessons Learned from Vancouver, Canada

Overdose deaths and non-fatal overdoses have increased in recent years across North America, due to the increased potency of fentanyl and its analogues, and the addition of other substances, such as benzodiazepines. Facing with the challenges of the opioid crisis, many North American cities have responded differently. These responses mainly focus on one field, such as medical care, law enforcement, judicature, and social security. Among those cities in North America, the community-based crisis response model in Vancouver is worthy of reference by other cities. According to the ethnographic fieldwork conducted in Vancouver Downtown Eastside in 2019, this paper argues that Vancouver has gradually formed a community-based response model since the establishment of Insite, which is the first supervised injection site in North America. The specific performance is as follows: Crosstown Clinic providing hydromorphone for drug addicts, OPS rescuing the overdose people, and Safe Supply strategy. In addition, according to relevant literature review, we found that responding to the challenges of the COVID-19, Vancouver also made some rewarding attempts to deal with the opioid crisis, such as compassion clubs and capsule fentanyl, all of which are the actions to drive the Safe Supply. And the decriminalization of possession certain amount hard drugs from January 31, 2023 in B.C.is another exemption approved by Canadian Government. In brief, Vancouver's community-based crisis response model promotes Vancouver to collaborate in the fields of activist, medical care, law enforcement, judicature, and social security to jointly participate in the governance of the opioid crisis. This paper argues that the lessons learned from Vancouver are the living representation of community empowerment which is confident, resilient, independent and energetic, which has the capacity to identify problems and design solutions at the local level, and which is inclusive and voluntary.

Deep learning for sensible cooling and heating loads associated with solar panels of residential buildings in arid climate

PurposeThis study aims to develop accurate prediction models for heating and cooling demands in buildings equipped with solar panels. By integrating renewable energy technologies, the goal is to design nearly energy-neutral buildings that significantly reduce energy consumption and enhance overall efficiency.Design/methodology/approachThe research utilizes deep learning models to address variables in building design, an area that previous studies have not fully explored. A dataset from arid climate regions was used to train and test two deep learning models to predict building energy consumption and solar energy output. The evaluation focused on how well the models predicted heating and cooling needs, as well as the amount of energy solar panels would need to generate in order to meet these demands. This approach represents an advancement over previous methodologies by integrating deep learning techniques with energy prediction in the context of arid climates, where energy efficiency is a critical concern.FindingsThe deep learning models developed in this study were highly accurate in predicting both heating and cooling requirements and the energy output from solar panels. This suggests that these models can effectively support the design of energy-efficient buildings, ensuring that the solar panels provide enough energy to cover the building’s needs.Originality/valueThis study introduces a novel method for predicting solar panel performance by integrating building characteristics with energy consumption, moving beyond traditional reliance on environmental factors. It optimizes energy management systems for arid climates, enhancing accuracy and applicability. The use of deep learning models with optimization techniques ensures precise and flexible predictions, providing a holistic solution for energy-efficient building design. The findings provide useful insights for architects and builders looking to create nearly zero-energy buildings, advancing the field of green building technologies.

Improve the efficiency of product low-carbon design: Combining design parameters mapping and differential analysis of carbon emissions

For low-carbon design of products, in addition to reducing carbon emissions, different design indicators must be met, which makes the design complicated. At the same time, there are usually multiple candidate design solutions, and the testing, validation, and optimization of these solutions combined with multiple indicators is time-consuming and labor-intensive. Therefore, it is significant to improve design efficiency and simplify the design process while ensuring the reliability of low-carbon design results. This paper proposes a low-carbon design method based on design parameters mapping and differential analysis of carbon emissions to realize the multi-objective optimization of low-carbon design, reduce the design workload, and improve design efficiency. Firstly, a comprehensive surrogate model mapping design parameters to design indicators is created by comparing and integrating multiple regression methods. Secondly, to quantify and compare the carbon emissions of solutions, a differentiated carbon emission quantitative model is established, retaining the differentiated processes of solutions. In addition, NSGA-II has been improved for a broader exploration of the design space. Finally, a small folding bicycle frame is taken as an example to validate the design method. The result shows that the proposed method can effectively realize the low-carbon design of products and improve the design efficiency.

Co-creating an Ecology of Design Briefs for people with respiratory disease

ABSTRACT In this study, we introduce a new approach to addressing the complexities of health systems challenges, which we name the Ecology of Design Briefs. This approach offers a structured framework for delivering key leverage points within these challenges and creating a conceptual space for feasible design opportunities. Acknowledging the limited reach of individual design solutions in tackling the complexities of health systems challenges, our approach draws on the ecology concept of Transition Design. The utilisation of the Ecology of Design Briefs results in a collection of interconnected specification documents for design projects that guide the creative process, working together synergistically to tackle the complexities. This approach was applied to enhance hospital care experiences for individuals with acute exacerbations of chronic obstructive pulmonary disease (COPD). Hospitalisations for this group frequently lead to multidimensional negative experiences, and addressing these issues is closely linked to resolving underlying health systems problems. Our findings suggest that the developed briefs provide comprehensive, mutually reinforcing, and detailed insights necessary for understanding these challenges. This study contributes to health systems problem-solving by conceptualising the Ecology of Design Briefs as an approach and documenting its application in a hospital care setting.

Carbon Footprint of Power Transformers Evaluated Through Life Cycle Analysis

The growing global demand for electricity is one of the crucial factors contributing to the increase in greenhouse gas (GHG) emissions. Power transformers, although essential components in electricity transmission and distribution systems, significantly impact the environment. This paper employs a Life Cycle Assessment (LCA) to evaluate the carbon footprint of two oil-immersed transformers with a capacity of 31.5 MVA and 25 MVA, manufactured in Poland in 2023, with an assumed lifetime of 40 years. The analysis follows a cradle-to-use approach and considers various scenarios, including differences in the average operating load levels, electricity generation from different sources, and a time frame spanning 2024–2063. After 2–3 years of transformer operation, even at low loads, the CO2 equivalent (CO2-eq) emissions associated with energy losses exceed those generated during the transformer production. These results underscore the critical importance of utilizing advanced construction materials and design solutions. Moreover, this analysis highlights the need to implement systemic actions aimed at restructuring electricity generation, especially in regions that heavily dependent on fossil fuels.

Empowering Communities Through Gamified Urban Design Solutions

The rapid urbanization of recent decades has intensified climate change challenges, demanding sophisticated solutions to build resilient and sustainable cities. A key aspect of sustainable urban planning is decentralizing and democratizing its processes, which requires citizen involvement from the early design stages. While current solutions such as digital tools, participatory workshops, gamification, and social media can enhance participation, they often exclude non-experts or those lacking digital skills. To address these limitations, this manuscript proposes a VR/AR gamified solution using open-source software and open GIS data. Specifically, it investigates the euPOLIS game as an innovative participatory tool offering an alternative to traditional approaches. This game decentralizes urban planning by shifting technical tasks to experts while citizens engage interactively, focusing solely on proposing solutions. To explore the potential of the proposed methodology, the euPOLIS game was demonstrated as a workshop activity in TNOC 2024 Festival, where 30 individuals from different academic background (i.e., citizens, architects, planners, etc.) voluntarily engaged and provided their impressions and feedback. The findings suggest that gamified solutions such as serious/simulation AR/VR games can effectively promote co-design, co-participation, and co-creation in urban planning in an inclusive and engaging manner.

Determination of Optimum Passive Design Parameters for Industrial Buildings in Different Climate Zones Using an Energy Performance Optimization Model Based on an Artificial Neural Network (ANN) and Particle Swarm Optimization (PSO)

With a focus on reducing building energy consumption, approaches that simultaneously optimize multiple passive design parameters in industrial buildings have received limited attention. Most existing studies tend to examine building geometry or individual design parameters under limited scenarios, underscoring the potential benefits of adopting a comprehensive, multiparameter approach that integrates climate-responsive and sustainable design strategies. This study bridges that gap by systematically optimizing key passive design parameters—building geometry, orientation, window-to-wall ratio (WWR), and glazing type—to minimize energy loads and enhance sustainability across five distinct climate zones. Fifteen different building geometries with equal floor areas and volumes were analyzed, considering fifteen glazing types and multiple orientations varying by 30° increments. DesignBuilder simulations yielded 16,900 results, and due to the inherent challenges in directly optimizing building geometry within simulation environments, the data were restructured to reveal underlying relationships. An Energy Performance Optimization Model, based on a Particle Swarm Optimization (PSO) algorithm integrated with an Artificial Neural Network (ANN), was developed to identify optimal design solutions tailored to specific climatic conditions. The optimization results successfully determined the optimal combinations of building geometry, orientation, WWR, and glazing type to reduce heating and cooling loads, thereby promoting energy efficiency and reducing carbon emissions in industrial buildings. This study offers a practical design solution set and provides architects with actionable recommendations during the early design phase, establishing a machine learning-based framework for achieving sustainable, energy-efficient, and climate-responsive industrial building designs.

Эргодизайн жилого модуля Российской орбитальной станции

This paper analyzes the habitable modules of the Russian Orbital Station (ROS); identifies astronauts’ main physiological, mental and emotional problems in conditions of long-term flight based on the studied scientific works. The authors propose principles of an integrated approach to solving ergonomic problems in the conditions of space modules. The paper stresses that space exploration is a promising problem for all humanity, while it is necessary to take into account the time intervals of human stay in space, which will increase. Flights beyond near-Earth space will significantly exceed the duration of current astronaut missions. Timely study of the problem of long-term human stay in space will require cooperation between scientists from space corporations and specialists in ergonomic design of “man-machine-environment” systems. The developed and proposed principles of ergonomic and design solutions for the residential module of the Russian Orbital Station in conditions of long-term exposure to microgravity can become one of the stages of fruitful cooperation between scientists from space corporations and young researchers in the field of ergodesign.

Novel Approach on Mathematical Modeling and Numerical Evaluation of the Seismic Protection of Structural Dynamic Systems

ABSTRACTNumerical studies for seismic isolated by lead core rubber bearing (LCRB) structural dynamic system are performed in Matlab and Simulink tools. For the numerical solution of the equation of motion fourth‐order Runge–Kutta method based Matlab solution (RKMBMS) technology and Simulink model‐based design solution (SMBDS) technology are developed and presented. For hysteretic restoring force, Bouc‐Wen's nonlinear model was used. Bouc‐Wen's nonlinear model dimensionless parameters were defined based on laboratory experiments. For the properties of LCRB such as stiffness, damping, damping ratio, yield strength, normalized yield strength, and yield displacement were used on base‐related standards. The stiffness, damping, and mass matrixes superstructure were built based on finite element method. For application, SMBDS technology state‐space model of the system was used. For the earthquake effects RKMBMS and SMBDS technologies are compared in terms of implementation (mathematic modeling, code preparation, and analyze duration) time. Long‐duration and long‐period earthquakes are observed to have particular influence on structural behavior. We observed that SMBDS technology for nonlinear dynamic analyses is attractive on implementation time and on minimizing and controlling errors, and it can be adopted especially for projects where time is a governing factor.

Hybrid method for energy flow in mid-high frequency acoustics: Applications in robust shape optimization for complex cavities

We present an efficient method for computing acoustic energy within complex-shaped geometries and cavities with obstacles in the mid-high frequency range. This method is based on the Simplified Energy Method (MES), known for its accuracy in such frequency ranges but traditionally limited to simple cavity shapes. The proposed hybrid method integrates the techniques of ray and triangle intersection with the MES formulation to address these limitations. By calculating the intersection points of the rays, we identify the obstructing elements before computing the energy transfer between the boundary elements. A primary intersection state matrix, containing direct view information between elements, is integrated into a modified MES equation to eliminate unnecessary computations and ensure precise calculations of energy transfer for obstructed elements. This hybrid approach is applied to both direct and reverberant fields to determine the total energy density. Numerical simulations conducted within a complex domain enclosure demonstrate the precision of the proposed algorithms when compared to traditional MES calculations. In addition, we propose applying this method to robust shape optimization, effectively balancing competing criteria to achieve optimized acoustic performance. This refined and computationally feasible tool significantly advances computational acoustics, providing accurate and efficient design solutions for complex environments.

An Efficient Optimization Method for Large-Solution Space Electromagnetic Automatic Design

In the field of electromagnetic design, it is sometimes necessary to search for the optimal design solution (i.e., the optimal solution) within a large solution space to complete the optimization. However, traditional optimization methods are not only slow in searching for the solution space but are also prone to becoming trapped in local optima, leading to optimization failure. This paper proposes a dual-population genetic algorithm to quickly find the optimal solution for electromagnetic optimization problems in large solution spaces. The method involves two populations: the first population uses the powerful dynamic decision-making ability of reinforcement learning to adjust the crossover probability, making the optimization process more stable and enhancing the global optimization capability of the algorithm. The second population accelerates the convergence speed of the algorithm by employing a “leader dominance” mechanism, allowing the population to quickly approach the optimal solution. The two populations are integrated through an immigration operator, improving optimization efficiency. The effectiveness of the proposed method is demonstrated through the optimization design of an electromagnetic metasurface material. Furthermore, the method designed in this paper is not limited to the electromagnetic field and has practical value in other engineering optimization areas, such as vehicle routing optimization, energy system optimization, and fluid dynamics optimization, etc.

Fictionation: development and evaluation of an idea generation tool grounded on design fiction

Abstract Idea generation requires the generation of many, various and novel ideas, and has the greatest impact on the quality of the final design solution within the design process. The literature offers numerous design methods and tools available for the use of designers in idea generation, though criticisms include the shortcomings of methods in supporting illogical thinking, as well as the lack of studies that test the effects of these methods on idea generation. This paper presents Fictionation, a card-based idea generation tool that seeks to increase novelty and variety by fostering an environment of creative invention based on design fiction and illogical thinking. The effects of the tool on the novelty and explored variety scores of the design outputs are investigated with an experimental study among undergraduate industrial design students. The results indicate that the Fictionation tool increases the novelty and variety of the ideas, and also has effects on improving academic performance and creating a more homogeneous student group.