Design Alternatives Research Articles

Aided design decision-making framework for engineering projects considering cost and social benefits

PurposeCurrently, engineering project design lacks a design framework that fully combines subjective experience and objective data. This study develops an aided design decision-making framework to automatically output the optimal design alternative for engineering projects in a more efficient and objective mode, which synthesizes the design experience.Design/methodology/approachA database of design components is first constructed to facilitate the retrieval of data and the design alternative screening algorithm is proposed to automatically select all feasible design alternatives. Then back propagation (BP) neural network algorithm is introduced to predict the cost of all feasible design alternatives. Based on the gray relational degree-particle swarm optimization (GRD-PSO) algorithm, the optimal design alternative can be selected considering multiple objectives.FindingsThe case study shows that the BP neural network-cost prediction algorithm can well predict the cost of design alternatives, and the framework can be widely used at the design stage of most engineering projects. Design components with low sensitivity to design objectives have been obtained, allowing for the consideration of disregarding their impacts on design objectives in such situations requiring rapid decisions. Meanwhile, design components with high sensitivity to design objective weights have also been obtained, drawing special attention to the effects of changes in the importance of design objectives on the selection of these components. Simultaneously, the framework can be flexibly adjusted to different design objectives and identify key design components, providing decision reference for designers.Originality/valueThe framework proposed in this paper contributes to the knowledge of design decision-making by emphasizing the importance of combining objective data and subjective experience, whose significance is ignored in the existing literature.

Efficiency enhancement techniques in finite element analysis: navigating complexity for agile design exploration

Purpose This paper aims to comprehensively explore techniques for reducing solution time in finite element analysis (FEA), addressing the critical need for expediting computations to facilitate agile design exploration within project timelines. Design/methodology/approach Drawing from a wide array of literature sources, this paper synthesizes and analyzes various methodologies used to enhance the efficiency of FEA. Techniques are scrutinized in terms of their applicability, effectiveness and potential limitations. Findings The review signifies application of linear assumptions across multiple facets of analysis and delves into matrix order reduction strategies, geometry simplification, symmetry exploitation, submodeling and mesh attribute control. It reveals how these techniques can effectively reduce computational burdens while maintaining acceptable levels of accuracy. Research limitations/implications While this review provides a comprehensive overview of existing efficiency enhancement techniques in FEA, it acknowledges inherent limitations of any synthesis-based study. Future research should focus on refining these methodologies. Practical implications The insights provided in this paper offer practical guidance for structural engineers and researchers seeking to optimize FEA workflows. By implementing these techniques, practitioners can expedite solution times and enhance their ability to explore design alternatives efficiently ultimately leading to cost savings and more robust structures. Originality/value This review contributes to the existing literature by offering a comprehensive synthesis of efficiency enhancement techniques in FEA. By highlighting the originality and value of each discussed methodology, this paper provides a roadmap for future research and practical implementation in the field of structural engineering.

Role of pre-operative endovascular embolization of a giant sacrococcygeal teratoma in neonate: a case report

BackgroundGiant sacrococcygeal teratomas (SCTs) are at risk of perinatal morbidity and mortality due to their high vascularity. Pre-operative embolization of the feeding arteries, prior to complete surgical resection, may assist in minimizing the intraoperative blood loss by occluding these feeding arteries.Case presentationWe present a case of a highly vascular giant SCT in a neonate, which was successfully embolized through an endovascular approach prior to surgery. The femoral artery approach was chosen, with access established using a Micropuncture introducer as a sheath. Embolization was performed using a combination of microcoils, Gelfoam slurry, and polyvinyl alcohol particles. The patient developed femoral artery spasm post-procedure, which resolved with the application of a glyceryl trinitrate patch.ConclusionsPerforming pre-operative endovascular embolization on a giant sacrococcygeal teratoma presents particular challenges, primarily due to the difficulty in assessing small vessels and the potential complications associated with this procedure. Nevertheless, this technique proves exceptionally valuable in helping the surgeon minimize blood loss during surgery, thereby reducing the risks of morbidity and mortality. Comprehensive planning for the embolization procedure is essential, encompassing the identification of potential vascular access points and alternatives, along with careful selection of the appropriate catheter.

IMPACT OF SHADING DEVICES ON COOLING LOAD IN EDUCATIONAL BUILDINGS

ABSTRACT This paper examines the influence of shading devices in non-residential buildings on enhancing cooling loads, mitigating environmental impact, and reducing energy consumption in semi-arid climates. The focus is on educational buildings as part of Algeria's national strategy to enhance sustainability and decrease energy usage. To achieve this, a comparative analysis was conducted, encompassing both numerical and experimental assessments of the effects of four indoor shading techniques and three outdoor shading techniques. Subsequently, the impact of the optimal shading combination on four main orientations was evaluated using dynamic building simulation software. The outcomes demonstrate that the optimal combination of shading devices substantially affects cooling loads, leading to noteworthy energy savings and a reduction in CO2 emissions. Notably, these savings can reach up to 7% in cooling load reduction and up to 32% in energy and CO2 emission reductions. Furthermore, the study concludes that distinct design considerations should be tailored to climate attributes and building orientations to achieve maximal cooling load reductions. This research enriches the existing knowledge concerning the optimization of shading devices for educational buildings with a focus on cooling load reduction. The findings emphasize the necessity for architects, builders, and proprietors to incorporate passive design alternatives that align optimally with energy efficiency, cost-effectiveness, and overall building sustainability.

Slab design combining interlocking blocks with a structural sheet

The construction of structural slabs is one of the more complex, costly, time consuming, and hazardous processes in constructing buildings. This is mainly due to the on-site formwork placement, reinforcement arrangement, and concrete pouring — all required for commonplace slab designs. In theory, industrialization-ready slab designs pose a promising path towards overcoming these challenges. However, designs that can deliver on this promise are not yet fully developed. Here we present a new structural slab design fit for an industrialized construction framework. It is made of interlocking blocks that are adhesively bonded to a structural sheet. We first present the slab design, detail the rationale behind it, and illustrate its inherently quick and accurate construction technique. Then, using numerical simulations, we examine the structural action of the proposed design and how it compares with that of a typical reinforced concrete slab with the same material quantities. We find that the structural performance of the proposed design is competitive with that of a reinforced concrete slab in terms of stiffness, carrying capacity, and ductility. Our results show that the inherently superior constructability of the proposed design is achieved without critical sacrifice of performance, thus underscoring its promising potential as a viable structural design alternative.

A multi-criteria decision-making approach for pressurized water reactor based on hesitant fuzzy-improved cumulative prospect theory and 2-additive fuzzy measure

As one of the world's largest energy consumers, China has paid much attention to the development of non-fossil energy sources. The nuclear power is regarded as the top priority for development due to its remarkable ecological and economic advantages. Given the large investment, long lifecycle, and rigorous quality control, the conceptual design plays a critical role in the pressurized water reactor development. Multitudinous design alternatives are presented at this stage and it is essential to develop an advanced evaluation approach. Hence, this work proposes a multi-criteria decision-making approach for pressurized water reactor based on hesitant fuzzy-improved cumulative prospect theory and 2-additive fuzzy measure. Firstly, considering the inherent uncertainty and cognitive biases of nuclear power experts, cumulative prospect values are calculated for design alternatives by adopting dual prospect reference points and two-tuple entropy measure under a hesitant fuzzy environment. Secondly, a linear programming model based on bidirectional projection measures is constructed to eliminate the discordance between the independent criteria assumption and interdependent evaluation information. This model helps to identify optimal 2-additive fuzzy measures, which serve as the basis for determining the Shapley importance and interaction indices of evaluation criteria. Then, taking Shapley interaction indices modification into account, a quadratic programming model based on the global criterion method is built. Finally, 2-additive Choquet integral-based TOPSIS method is proposed to select the optimal design alternative. A case study on the essential service water system is implemented to demonstrate the reliability and superiority of the proposed approach.

Co-designing for the NHS: the development of sustainable theatre garments

AbstractNHS Scotland, one of the keystone healthcare providers in the UK, have recently set a wide variety of sustainability targets in an effort to mitigate waste and the intensive energy demands of healthcare. Medical garment production, management and design is an area in which design researchers can explore and offer solutions. This paper presents a series of co-design explorations to examine design alternatives to single-use theatre caps, the majority of which are currently disposed of routinely. Using a series of probes, major insights into how theatre cap design may be improved is presented.

Partisipatif Konsep Rancangan Musala Baiturrohmah Gang Haji Nawi Jatimakmur Pondok Gede Kota Bekasi

Musala Baiturrohmah, located in Gang Haji Nawi, Jatimakmur Village, Pondok Gede District, Bekasi City, was initially a privately owned prayer facility. Over time, it has expanded to accommodate various community activities, serving not only as a place of worship but also for educational and social functions. Recognizing the need to enhance its facilities, the owner decided to renovate the Musala to include additional functional spaces and improve the surrounding environment. To achieve this, the owner collaborated with the Architecture Study Program at the Faculty of Engineering, Karno University. This partnership involved permanent lecturers, students, and alumni in forming a Community Service Team. The team undertook stages of field exploration, surveying, studying, design transformation, and reporting. Two design alternatives were developed for the Musala building, offering options that cater to the needs of both the owner and the local community.

Optimization of landscape garden greening design based on multi objective genetic algorithm

This paper presents a novel approach to optimize landscape garden greening design using a multi-objective genetic algorithm (MOGA)[1]. Incorporating genetic algorithms into landscape architecture offers a promising avenue for efficiently navigating the complex and multidimensional design space inherent in green infrastructure projects. Through a comprehensive bibliometric analysis of existing literature, this study synthesizes key insights into the application of genetic algorithms in landscape design and identifies gaps for further exploration[2]. Leveraging the evolutionary process of genetic algorithms, our methodology focuses on simultaneously optimizing multiple objectives such as biodiversity conservation, aesthetic appeal, water efficiency, and ecosystem services provisioning[3]. By iteratively evolving and selecting landscape configurations based on fitness criteria derived from these objectives, the MOGA enables designers to explore a diverse range of design alternatives and identify Pareto-optimal solutions that balance competing priorities. The integration of genetic algorithms into landscape design facilitates an iterative and adaptive design process, allowing for the exploration of complex trade-offs and the generation of innovative design solutions. Through a case study application, we demonstrate the effectiveness of the MOGA approach in optimizing landscape garden greening designs, showcasing its potential to enhance sustainability, resilience, and functionality in urban green spaces. This research contributes to the growing body of knowledge on computational design methods in landscape architecture and provides valuable insights for practitioners and researchers seeking to leverage genetic algorithms for optimizing green infrastructure projects.

Client-centered detached modular housing: natural language processing-enabled design recommender system

Abstract Designing modular housing is a complex task that necessitates a thorough understanding of the diverse needs of clients in terms of both design aesthetics and floor plan layout. Furthermore, adhering to design for manufacture and assembly (DfMA) principles adds to the complexity, as these are essential modular home requirements. Traditional construction methods frequently fail to meet the specific needs of both clients and DfMA, potentially resulting in suboptimal design solutions. Incorporating client requirements during the design phase necessitates the use of an effective system and framework to reduce changes in subsequent project stages. Existing literature lacks a suitable approach, particularly in the context of modular housing. To address this gap, this paper introduces an artificial intelligence–building information modeling recommender system (RS) for detached modular housing design. The system processes client requirements entered as text utilizing the Word2vec algorithm with the GloVe dataset, refined through transfer learning using surveyed client data of housing needs. The system recommends three distinct modular building design alternatives sourced from a building information modeling models database using cosine and Euclidean similarity functions. A sensitivity analysis ensures that client needs are considered fairly, increasing the robustness of the RS. By incorporating natural language processing, this system transforms the construction industry by making initial designs more client-centric compared with traditional methods. Furthermore, it promotes improved collaboration among clients, design, and construction teams, reducing modifications to design in later stages of construction.

Poly(2-methyl-2-oxazoline) as a polyethylene glycol alternative for lipid nanoparticle formulation

Lipid nanoparticles (LNPs) have emerged as the platform of choice for mRNA delivery. Polyethylene glycol (PEG) is considered a key component of currently approved LNP-based delivery systems as it ensures particle stability and shapes various facets of LNP behavior in biological systems. Whilst PEG has numerous characteristics that are favorable for delivery systems, there is a growing body of evidence that suggests that it is immunogenic. Thus, next-generation mRNA therapeutics are likely to benefit from the identification of PEG alternatives. Towards this end, we have assessed the suitability of poly(2-methyl-2-oxazoline) (PMOZ) for LNP-based mRNA delivery. We compared the properties and bioactivities of PMOZ-containing LNPs to that of a standard composition that includes PEG. Decreasing the percentage of PMOZ in formulations improved transfection efficiency and enhanced the immunostimulatory potential. Reducing the PMOZ density was shown to enhanced antigen-specific T-cell responses in vivo. Interestingly, we found that this was not the case for antibody responses. A direct comparison between LNPs that contain the same amount of PEG or PMOZ strongly suggests that the former induces stronger CD8+ T-cell responses while the latter induces superior neutralizing titers. These findings augur well for the further development of PMOZ as a PEG replacement for LNP-based mRNA delivery approaches.

VFT and AHP Approach to Selecting the Best Option in Decision-Making at PLN: A Case Study in the Cawang-Gandul Project

PLN EIC is one of PLN’s business units and is responsible for the development of electrical infrastructure in the working area of DKI Jakarta, Banten Province, and its surroundings. One of the national strategic projects included in the PLN is the 500 kV Cawang Baru II/Cililitan-Gandul transmission line project, with a COD target of 2026. The delay in the completion of this project and the non-fulfillment of stakeholders’ expectations will certainly have a broad impact on the operation of the electricity system, the impact on PLN’s financial performance, the social impact, the environmental impact, as well as the direct impact on the performance and image of PLN EIC. This research aims to assist management in making decisions related to the best transmission line design for the Cawang-Gandul project so that project completion can be on time and in accordance with stakeholder expectations. In this research, several methodological approaches were used to gain a broader and more complete understanding. The Problem Tree Analysis approach, combined with brainstorming and structured interview techniques, was used to explore business issues. Two complementary approaches, namely Value-Focused Thinking (VFT) and the Stakeholder Analysis method, are used to formulate stakeholder expectations and will become guidelines for formulating alternative strategies. Using a structured interview technique, 4 alternative strategies were formulated in the form of the transmission line design, namely (1) Compact Lattice Tower, (2) Underground Cable, (3) Combine Design (Compact Lattice Tower + Underground Cable), and (4) Steel Pole Tower. The next methodological approach uses the Analytic Hierarchy Process (AHP) to determine the best transmission line design, which is then analyzed using AHP Super Decision software. The results of this research show that the Underground Cable design is the best design alternative that can be implemented in the Cawang-Gandul project with several advantages, namely minimal social conflict, easy implementation, and a relatively faster work process. The final stage of research is to make an implementation plan.

Strategic Priorities for the Development of Food Security of the State Taking into Account Hybrid Threats and Challenges

Relevance. Food security is one of the most urgent and complex problems of the modern world. In the context of globalization, climate change, economic fluctuations and other factors, ensuring the stability and reliability of food security is becoming a complex task that requires effective strategies.The purpose is to analyze and evaluate strategic priorities in the field of food security, taking into account complex hybrid threats and challenges. Objectives: identification of strategic alternatives; development of a mathematical model with fuzzy variables and rules for evaluating strategic alternatives; analysis of evaluation results to identify the most effective strategic directions.Methodology. The research methodology included the use of fuzzy logic methods to build a mathematical model for evaluating strategic alternatives.Results. As a result of the study, it was revealed that the strategic alternative S1 received the highest rating, emphasizing its key importance for the sustainability of the food system. Alternatives S7, S9, S4 and S3 also have high ratings, which makes them potentially effective for ensuring food security. Alternatives S10, S8, S2, S6 and S5 are less of a priority, but are important for reducing various risks associated with food security, such as lack of food and vulnerability of supplies.Conclusions. The results of the study allowed us to conclude that the use of the fuzzy logic tool provides an opportunity to conduct a deeper and more comprehensive analysis of complex factors affecting food security. This approach allows us to take into account the uncertainty and multidimensionality of data related to the food system and introduce more accurate modeling of this dynamic area. Such a method enriches the decision-making process in the field of food security, contributing to the development of more effective strategic decisions and management approaches that take into account a variety of factors and their interaction. This contributes to improving the quality of research and helps to form more rational and informed strategies that contribute to ensuring the stability and reliability of food security.

Retrospective and prospective evaluation of the FluoroType®-Mycobacteria VER 1.0 assay for the identification of mycobacteria from cultures in a French center.

Rapid, reliable identification of mycobacteria from positive cultures is essential for patient management, particularly for the differential diagnosis of Mycobacterium tuberculosis complex (MTBC) and nontuberculous mycobacteria (NTM) species. The aim of the present study was to evaluate a new "In-Vitro-Diagnostic"-certified PCR kit, FluoroType®-Mycobacteria VER1.0 (Hain Lifescience GmbH) for NTM and MTBC identification from cultures. Mycobacteria identification isolated from positive cultures during routine practice at the Lyon university hospital mycobacteria laboratory obtained by hsp65 amplification/sequencing were compared retrospectively and prospectively to those obtained by and the FluoroType®-Mycobacteria VER1.0kit. The overall agreement between hsp65 amplification/sequencing and the FluoroType®-Mycobacteria VER1.0kit was 88.4% (84/95); 91.2% (52/57) for the retrospective period and 84.2% (32/38) for the prospective period. There were 9 (9.5%) minor discrepancies (species in the FluoroType®-Mycobacteria VER1.0database and identified at genus level): 4 during the retrospective period, 5 during the prospective period; and 2 (2.1%) major discrepancies (species in the FluoroType®-Mycobacteria VER1.0database and identified incorrectly to species level): 1 during the retrospective period (M. kumamotonense identified as M. abscessus subsp massiliense by the kit) and 1 during the prospective period (M. chimaera identified as M. smegmatis by the kit). Including concordant results at genus level and minor discrepancies, 17.9% (17/95) of strains were identified as Mycobacterium sp. by the FluoroType®-Mycobacteria-VER1.0kit. The good performance of the FluoroType®-Mycobacteria-VER1.0kit with few major discrepancies could enable its use for first-line identification of positive mycobacteria cultures. However, an alternative identification method at least for reference laboratories is needed owing to the non-negligible proportion of NTM strains were identified at genus level.

Stated opinions and potential travel with DRT – a survey covering three different age groups

ABSTRACT Previous research shows that well-grounded knowledge of the intended travellers is essential for achieving successful DRT services. However, there is a lack of understanding of the potential travels in different age groups, and the acceptance of design alternatives that may affect these. Based on surveys conducted in Sweden, this paper investigates these factors in a hypothetical DRT service, in the age groups 6–17, 18–69 and over 70 years. A total of 1241 people answered the questionnaires. The results show that the age groups have similar acceptance regarding delays and departure time intervals. Older adults have lower acceptance of digital solutions, and children and older adults have stronger requirements for value-added services. About 85–90% of the respondents claim they would use the service, at least occasionally. The results also show how a DRT system should be configured to allow room for system efficiency gains, while still being accepted by most travellers.

Designing pareto-optimal selection systems for multiple minority subgroups and multiple criteria.

Currently used Pareto-optimal (PO) approaches for balancing diversity and validity goals in selection can deal only with one minority group and one criterion. These are key limitations because the workplace and society at large are getting increasingly diverse and because selection system designers often have interest in multiple criteria. Therefore, the article extends existing methods for designing PO selection systems to situations involving multiple criteria and multiple minority groups (i.e., multiobjective PO selection systems). We first present a hybrid multiobjective PO approach for computing selection systems that are PO with respect to (a) a set of quality objectives (i.e., criteria) and (b) a set of diversity objectives where each diversity objective relates to a different minority group. Next, we propose three two-dimensional subspace procedures that aid selection designers in choosing between the PO systems in case of a high number of quality and diversity objectives. We illustrate our novel multiobjective PO approaches via several example applications, thereby demonstrating that they are the first to reveal the complete gamut of eligible PO selection designs and to faithfully capture the Pareto trade-off front in case of more than two objectives. In addition, a small-scale cross-validation study confirms that the resulting PO selection designs retain an advantage over alternative designs when applied in new validation samples. Finally, the article provides a link to an executable code to perform the new multiobjective PO approaches. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Direct Stiffness–Strength Method: An Alternative Design Approach to AISI for Sheathed Cold-Formed Steel Z-Section Structural Members Subjected to Bending

Direct Stiffness–Strength Method: An Alternative Design Approach to AISI for Sheathed Cold-Formed Steel Z-Section Structural Members Subjected to Bending

Assessing Cleaning in Remanufacturing: A Case Study of Shot Blasting Efficiency to Alternator Design

Cleaning is a crucial step in the remanufacturing of end-of-life components. The main purpose of cleaning is to remove all contaminant items such as dirt, oils, dust in order to facilitate the process of core inspection before moving on to the subsequent step to complete the remanufacturing activity. However, there are issues/challenges related to the cleaning methods that affect the process efficiency. It has also been reported that the cleaning process is time consuming and has adverse impact to the environment. Cleaning is directly influenced by the various cleaning methods and the design features of each core/incoming parts. Therefore, the aim of this paper is to evaluate the effectiveness of shot blasting cleaning method from core design perspectives in the case of an alternator. The results will be assessed based cleanliness level after the cleaning process on the core surface, complex shape, geometry, and joining method. The outcome demonstrates that the complexity of the core design also affects the cleaning process efficiency. According to the study shot blasting cleaning method without any pretreatment process was insufficient to fully clean the core. Hence, it is suggested to consider several parameters to enhance the shot blasting method to clean the used alternator for remanufacturing process.

Design optimisation towards lower embodied carbon of prefabricated buildings: Balancing standardisation and customisation

The design principle of standardisation is widely acknowledged for its potential in reducing embodied carbon emissions (CE) in prefabrications through the facilitated reuse of prefabricated elements. Yet, its effectiveness in optimising CE in precast constructions remains underexplored. This article introduces a micro-level sustainable design optimisation approach for precast projects that factors the CE of both building materials and concrete formwork. Using a parametric approach, the method generates design alternatives derived from the original architecture design. Structure analysis is then employed to determine the design of structure elements and formwork pieces. With the objective of minimising CE from building materials and formwork, a genetic algorithm (GA) is used to explore solutions with the lowest CE. Comparative analysis shows this approach's effectiveness over standardisation-only designs, reducing concrete, reinforcement, precast formwork, and overall CE by 14.32%, 16.71%, 10.39%, and 10.51%, respectively. These findings underscore that increased standardisation does not necessarily lead to lower embodied CE. Integrating the benefits of element standardisation and customisation presents a promising carbon reduction strategy. The introduction of micro-level variables enhances the understanding of standardisation and offers novel carbon reduction strategies, such as increasing the adaptability of casting formwork and maximising the use of existing formwork pieces. Designers and manufactures can adopt these strategies for lower embodied CE of projects. This study also addresses the limitations of design tools used in early architecture design stages, providing designers with continuous decision-making assistance, thereby facilitating the implementation of sustainable strategies.

Active learning-based optimization of structures under stochastic excitations with first-passage probability constraints

In various efforts to manage the risk of structural failures caused by stochastic excitations such as wind and earthquake loads, the first-passage probability often needs to be calculated as a reliability constraint. Estimating the first-passage probability with low computational costs is essential, especially in structural optimization requiring iterative reliability calculations for design alternatives. This paper presents a new active learning-based framework for reliability-based design optimization (RBDO) of structures under stochastic excitations. A mixture-distribution-based formulation of the first-passage probability is utilized to handle the high-dimensional sequences of stochastic excitations during the optimization. The design parameter sensitivity of the first-passage probability is introduced to use a gradient-based optimizer in the RBDO iterations. These procedures employ heteroscedastic Gaussian process-based surrogates of the logarithmic responses. An active-learning scheme identifies the best training point to reduce the computational costs in the first-passage probability calculations and optimization. The numerical examples dealing with the optimal design of an eight-story building system and a tower structure subjected to stochastic wind loads demonstrate the accuracy and efficiency of the proposed method.