Design Stage Research Articles

Effect of Reinforcement Corrosion on Structural Behavior in Reinforced Concrete Structures According to Initiation and Propagation Periods

Reinforced concrete (RC) structures lose performance over time. One of the most significant environmental factors causing performance degradation is reinforcement corrosion. Corrosion reduces the diameter of the reinforcement and degrades the mechanical properties of both the concrete and the steel. In order to determine the degradation of the structural performance caused by corrosion, it is essential to identify the time periods in which corrosion initiates and propagates, and to thoroughly analyze the parameters that govern these processes. In this study, the corrosion initiation and propagation times were calculated separately for an RC frame exposed to chloride ions. Factors contributing to the further reduction of these processes were identified. Analyses and comparisons were made to determine the structural performance of the calculated RC frame over its service life. The results showed that corrosion reduces the structural performance, especially in regions with high seismic potential, where preventive measures against corrosion are essential. The most important parameter influencing the corrosion mechanism is the corrosion rate, while another important factor is the formation of cracks on the element surface. In cases where cracks are present, the corrosion initiation time is shortened, which means that materials should be selected at the design stage that are suitable for the environment, and the years of maintenance required should be calculated by the design engineers. In addition, the surfaces of RC elements should be monitored, and crack tracking should be carried out.

Neuroethical considerations and attitudes about neurostimulation as a fatigue countermeasure among emergency responders

IntroductionFirst responders play a pivotal role in ensuring the wellbeing of individuals during critical situations. The demanding nature of their work exposes them to prolonged shifts and unpredictable situations, leading to elevated fatigue levels. Modern countermeasures to fatigue do not provide the best results. This study evaluates the acceptance and ethical considerations of a novel fatigue countermeasure using transcranial Direct Current Stimulation (tDCS) for fire and emergency medical services (EMS) personnel.MethodsTo better understand first responders' perceptions and ethical concerns about this novel fatigue countermeasure in their work, we conducted semi-structured interviews with first responders (N = 20). Interviews were transcribed into text and analyzed using qualitative content analysis.ResultsOver half of responders (59%) were interested, but over a third had a cautionary stand. Half of the participants seemed to have positive views regarding acceptability; a few were more cautionary or hesitant. A main area of consideration was user control (75%), with the majority wanting to retain some control over when or whether to accept the stimulation. Just above half of the participants (64%) mentioned privacy concerns. Another relevant consideration, raised by 50% of participants, was safety and the potential impact of stimulation (e.g., side effects, long-term effects). Overall, participants thought they needed to understand the system better and agreed that more education and training would be required to make people more willing to use it.DiscussionOur exploration into combating fatigue among first responders through tDCS has revealed promising initial reactions from the responder community. Findings from this study lay the groundwork for a promising solution, while still in a nascent design stage, to improve the effectiveness and resilience of first responders in fatiguing shifts and critical situations.

Model of material movement on the working surface of a vibrating machine

This article presents studies related to the calculation of the peculiarities of the movement of bulk material on the working surface of a vibrating machine – for example, on a sowing surface – in terms of the intensity of the potential force field acting on the material being processed. This approach makes it possible to adjust its design to the selected technological process at the design stage of the vibrating machine, which further makes it possible to minimize energy consumption for vibration processing of bulk raw materials without reducing the quality of its preparation.

A Multi-layer Parallelogram Flexure Architecture for Higher Out-of-Plane Load Bearing Stiffness

Abstract Parallelogram Flexure Mechanism (PFM) is a common flexure module which is widely used as a building block in the design and manufacturing of flexure-based XY motion stages that provide in-plane Degrees of Freedom (DoFs). In such motion stages, low in-plane stiffness along the DoF helps increase the DoF range of motion and reduce the actuation effort. At the same time, high out-of-plane stiffness is paramount to suppress out-of-plane parasitic motions, support heavy payloads and mitigate the negative impacts of out-of-plane resonant modes. Achieving both of these design objectives simultaneously is extremely challenging in PFMs and flexure mechanisms comprising PFMs due to the inherent tradeoff between the in-plane and out-of-plane stiffness. This paper resolves this tradeoff by proposing a novel multi-layer PFM architecture, referred to as the sandwich PFM, that achieves a significant improvement in the out-of-plane translational and rotational stiffness compared to conventional single-layer PFMs without impacting the in-plane DoF stiffness. Analytical models will be derived for the in-plane and out-of-plane stiffness of the sandwich PFM that closely match with the Finite Element Analysis (FEA) results. Several design insights into the performance of the sandwich PFM are discussed using the analytical stiffness models and a general procedure is proposed to design a sandwich PFM.

Control of building safety through snow load monitoring

Climatic loading in the form of snow load is a significant factor for building structures. This is relevant during the design stage, the execution stage, and especially throughout the operational period. Building owners are legally required to ensure that their roofs are cleared of snow, often raising the question of whether such action is necessary in a particular situation. To address this, various devices have been developed to facilitate the systematic monitoring and measurement of snow load on roofs. These devices measure snow weight either indirectly or directly. The methods for monitoring snow weight and evaluating the effect of snow load on structural safety have been extensively discussed in the literature, considering aspects of structural integrity, operation under harsh conditions, and the economic implications of building management. In this paper, the authors propose an innovative approach to monitoring snow load using snow scales, supplemented by roof deflection measurements with tilt sensors (inclinometers). Such systems not only ensure the safety of the building and its occupants by providing reliable and verified results but also achieve this in a cost-effective manner.

Innovating sustainable fashion design: an exploration of the sustainability of a hybrid method through the C2CAD framework

ABSTRACT Sustainability in the fashion industry is evolving, with a trend towards integrating digital technology with traditional crafts, as more eyes are on artisanal values than manufacturing benefits. Meanwhile, a hybrid design and making method merges human skills with digital tools for sustainable creation, as investigated in the design innovations of the opera costume in this study. The study applies the C2CAD framework to guide design, develop an optimised design model, and validate the sustainable impact of each design step. The design model focuses on small-scale customised pieces by the designer and highlights the stages of hybrid design and making, resulting in a sustainable design process that displays a non-linear recursive route. The research reveals the interaction between the making techniques and necessitates a balance between aesthetics and sustainability. The findings provide a valuable insight into the application of the sustainable fashion design model and making method in the design process.

Study on the influence of guardrails on the mechanical properties of pre-stressed hollow plate beam bridges structure

In order to improve the design level of pre-stressed hollow slab bridge beams, the airport 1# bridge was taken as the research object to study on the influence of guardrails on the mechanical properties of pre-stressed hollow plate beam bridges. On the basis of conducting overall structural verification, a solid model was established to analyze the influence of bridge deck guardrails on the mechanical behavior of cast-in-place joints in hollow slab bridges. Research shows that the maximum deflection and the maximum bending moment internal force decreases by 40 % and 14.5 %, respectively when taking into account the stiffness of the guardrail. However, the maximum shear force of the hollow slab edge joint and middle joint increases by 75 % and 14.5 %, respectively. The maximum shear force increases by 35.62 % when the height of the guardrail increases from 0.5 m to 2 m. The results indicate that the influence of bridge deck guardrails on the shear performance of slab hinge joints should be considered during the preliminary design stage of such bridges. The research results can provide reference for such structures.

A user-centered approach in complex engineering design environments

In complex engineering design environments, the demand for high quality products and high functionality are critical, the end-user requirements have to be integrated into the design process since the earliest design stages. In such contexts, strict design requirements related to quality, safety, and usability must be taken into account concurrently. To this aim, in this work, an integrated user-centered decision-based design method is proposed in the medical design environment context. This work is aimed at proposing a design method to be applied to complex design environments. The proposed case study is the design of an intercom device, aimed at improving patient-doctor communication in the case of bedridden patients on with helmet for Continuous Positive Airway Pressure (CPAP) therapy during SARS- CoV2 pandemic emergency. Patients undergoing helmet-assisted ventilation are often immersed in a highly noisy environment, unable to fully communicate their needs to the doctors. A three-steps decision based integrated product design and process simulation are used in the early design stages, to gain optimal product designs in a user-centered design viewpoint, for novel industrial products. The first step, modular design, is aimed at defining relations between the components of the assembly in a user centered approach. Design alternatives are generated in a Design for Manufacturing and Assembly DFMA viewpoint. In the second step, the group decision making step, in a multiple criteria context, the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is applied together with the fuzzy set theory, to overcome uncertainties in the verbal judgments of the decision makers. The third step is related to the simulation of the assembly and manufacturing process, with the aim of defining a final optimal design. The proposed group multicriteria decision making based design method proved to be efficient in complex user centered engineering design contexts.

Integrating axiomatic design and design structure matrix into model‐based systems engineering: A case study for emergency response space mission design

AbstractWith the increasing complexity of space missions due to technological advancements, model‐based systems engineering (MBSE) has become a new paradigm for systems engineering (SE), providing a more formal and accurate system engineering process while reducing costs. However, MBSE does not offer a comprehensive approach for effective system function design. This study introduces a conceptual design approach that integrates axiomatic design (AD) and design structure matrix (DSM) into the MBSE paradigm and applies it to functional and logical design. The research focuses on utilizing the design knowledge encapsulated by system models to facilitate the development of new systems. System models have the potential to bridge different design domains in AD, reveal implicit associations, and offer functional and structural analysis capabilities. To validate our approach, we conducted a case study on an Emergency Response Remote Sensing mission system. This case study demonstrates that our proposed methodology lends formality to traditional AD by deriving AD matrices and DSMs from a system model, thereby enhancing the system's structure while curtailing elemental alterations during iterative design processes. The novelty of this research lies in realizing the integration of traditional design theory with the model paradigm of SE, leading to an effective design solution during the functional and logical design stages.

ОГЛЯД ДОСЛІДЖЕНЬ ТА ОБҐРУНТУВАННЯ НОВИХ МАТЕМАТИЧНИХ МЕТОДІВ МОДЕЛЮВАННЯ АЕРОПРУЖНОСТІ КРИЛА З ЛЮФТОМ КЕРУЮЧИХ ПОВЕРХОНЬ

The phenomenon of instability in flight due to the interaction of aerodynamic, elastic and inertial forces. could prove disastrous. Therefore, due importance is given to the aeroelastic analysis of the aircraft at the design stage. Free play, sometimes called play, occurs as a result of wear on parts such as lugs or moving mounts, often due to the aging of the aircraft. Excessive free play is detrimental to the flight safety of the aircraft. This can lead to catastrophic aeroelastic instabilities such as limit cycle oscillation (LCO), a phenomenon associated with sustained vibration of a fixed amplitude. LCO can accelerate the accumulation of structural fatigue damage and compromise controllability during flight. Aircraft control systems play a critical role in ensuring stability, maneuverability and flight safety. Over the past few decades, nonlinear aeroelasticity has received increasing attention. Advanced computational capabilities have stimulated renewed interest among researchers in re-examining the control surface free play problem with the goal of refining analytical models for greater accuracy. Both modern theoretical and experimental analyzes of free play have opened up new possibilities for the study of aeroelasticity. Despite the apparent understanding of the fundamental problem and the availability of numerous modeling approaches, freewheeling research continues to generate varied predictions regarding aeroelastic dynamic behavior and associated properties. Free play, defined as the sag or movement of mechanical connections between control inputs and aircraft control surfaces, is a ubiquitous aspect of control system design. While a little play may be tolerable, excessive play can lead to non-linearities and uncertainties, potentially compromising flight performance and safety. The aim of the article is to review existing methods of numerical research, analyze new mathematical methods for modeling aeroelastic vibrations and formulate the problem of developing safety criteria for transport category aircraft in terms of preventing elastic instability in the presence of free play in the control mechanism.

Optimizing Vehicle Body Cross-Sections Using a Parametric Mathematical Model

This paper proposes a fast optimization method of body section at the conceptual design stage, based on the demand for body performance in body concept design. The study first establishes a geometrically simplified model of the truss body structure and uses the transfer matrix method to establish a fully parameterized model of the geometrically simplified body under bending conditions. Then, the stochastic gradient genetic algorithm is used to optimize the solution and determine the geometric parameters of each section. In the example of this paper, after the optimization of the established meshless model, the mass of the whole vehicle is reduced by 30%, and the stiffness of the whole vehicle is greater than that of the benchmark vehicle (5128 N/mm, 4386 N/mm), and at the same time, compared with the conceptual design method of the body of CAE technology, the modeling time is greatly reduced, and the computational efficiency of the analytical method is greatly improved compared with the finite element method.

Experimental determination of lateral sway of a pneumatic spring when passing through a railroad switch in conditions of provision of high-speed trains` safety

Experimental determination of lateral sway of a pneumatic spring when passing through a railroad switch in conditions of provision of high-speed trains` safety

Investigating the impact of data monitoring committee recommendations on the probability of trial success

ABSTRACT Determining the probability of success of a clinical trial using a prior distribution on the treatment effect can significantly enhance decision-making by the sponsor. In a group sequential design, the probability of success calculated at the design stage can be updated to incorporate the information disclosed by the Data Monitoring Committee (DMC), usually consisting in a simple statement that advises to continue or to stop the trial, either for efficacy or futility, following pre-specified rules defined in the protocol. We define the “probability of success post interim” as the probability of success conditioned on the assumption that the DMC recommends continuing the trial after an interim analysis. A good assessment of this probability helps mitigate the tendency of the study team to express excessive optimism or unwarranted pessimism regarding the trial’s ultimate outcome after the DMC recommendation. We explore the relationship between this “probability of success post interim” and the initial probability of success, and we provide an in-depth investigation of how interim boundaries impact these probabilities. This analysis offers valuable insights that can guide the selection of boundaries for both efficacy and futility interim analyses, leading to more informed clinical trial designs.

Digital Twin in the Design and Dynamic Assessment of Energy Performance of Multi-Family Buildings

The article explores the potential of Digital Twin (DT) technology in the design and dynamic assessment of the energy performance of multi-family buildings. Traditional approaches to building energy assessment provide static data that do not account for changing operational conditions and lack continuous energy consumption-monitoring capabilities. The use of Digital Twin enables monitoring and analyzing of the building’s energy parameters at every stage of its life cycle. The article presents the application of DT technology for assessing energy performance at the conceptual stage and in the early phases of design. These parameters must meet legal requirements. Validation conducted on four multi-family buildings demonstrated high accuracy, with the average difference between predicted and actual energy performance (EP) values below 3.5%. Thanks to the DT model, it is possible to determine energy parameters already at the conceptual stage, which helps avoid costly changes in later project phases. Early determination of these parameters also allows for accurate estimation of design and investment costs. Tests of the proposed solution were conducted on several multi-family buildings, comparing preliminary data with final results. The research results show that DT technology allows for precise planning of energy performance at the conceptual and preliminary design stages. This reduces operational costs, increases energy efficiency, and better adapts buildings to changing technological and legal conditions.

A methodology for improved predictions of surface ground movements around shafts

Shafts are typically employed in urban environments to provide access or ventilation to underground structures such as stations, railways or highways. The choice of design is determined, among other things, by the need to control settlements at the surface, often estimated during early design stages using empirical expressions. These have been shown to have limited accuracy, failing to account appropriately for the effect of shaft diameter on the ground movements associated with shaft excavation. This paper reviews empirical expressions available in the literature in the context of a large database of settlements induced by shaft excavation in London. A comprehensive set of detailed numerical analyses is performed to enable the development of a new set of expressions capable of predicting accurately the computed vertical and horizontal ground movements at the surface. The new expressions are shown to provide better predictions of the observed field data than predictive expressions available in the literature, establishing a new benchmark against which future proposals can be assessed.

ANALISIS EFEKTIFITAS VISUALISASI PERMODELAN DESAIN ARSITEKTUR BERBASIS KECERDASAN BUATAN (AI)

This research focuses on the iteration of architectural modeling using artificial intelligence (AI) as a solution to generate visualization concepts in the architectural iteration process. It examines the development of AI in architecture and highlights AI's position in current architectural practice. AI has revolutionized the way architectural designs are developed, presented, and interpreted. With its ability to process complex data, AI accelerates the design process, enables the exploration of innovative solutions, and enhances understanding of projects before construction begins. AI is used in various applications, from automating visualizations to generating floor plans, opening new potentials in designing and visualizing architectural projects. However, the use of AI in architecture is still in its early stages, and challenges remain in applying AI to conceptual design stages. This research will analyze the effectiveness of AI in architectural modeling and design visualization, evaluating its impact on efficiency, creativity, and design output quality, and exploring limitations and future recommendations for AI use in architectural practice. Based on platform evaluations, MidJourney and DALL·E show superiority in visual quality and design accuracy, each with the highest scores. MidJourney and DALL·E are the top choices for creative and technical architectural visualization, while Leonardo AI and Bing AI show limitations in creativity and flexibility.

Role of Statistics in Artificial Intelligence Technology

Artificial intelligence (AI) research and applications have sparked a broad scientific, economic, social, and political debate. Statistical approaches and techniques are fundamental to AI because they allow robots to learn from data and make intelligent decisions. It's possible even to view statistics as a fundamental component of AI. Statistics is an ideal partner for other disciplines in teaching, research, and practice because of its specialized knowledge of data evaluation, which begins with the correct phrasing of the research question and continues through a study design stage to analysis and interpretation of the results. This work aims to demonstrate how statistical methodology is relevant to the development of AI. In terms of methodological development, planning, research design, evaluation of data quality and collection, distinction of causation and relationships, and evaluation of result uncertainty, we talk about the contributions of statistics to the field of artificial intelligence. This study thoroughly analyzes the crucial role statistics play in AI, demonstrating the numerous applications of statistical ideas like probability, regression, classification, and clustering. The essay highlights the value of statistical analysis in handling uncertainty, making predictions, and training AI models all of which improve the efficiency and precision of AI systems.

Exploring How Older Adults Experience semAPP, a 360° Media-Based Tool for Memory Assessment: Qualitative Study.

Technology is already a part of our daily lives, and its influence is growing rapidly. This evolution has not spared the health care field. Nowadays, a crucial challenge is considering aspects such as design, development, and implementation, highlighting their functionality, ease of use, compatibility, performance, and safety when a new technological tool is developed. As noted in many works, the abandonment rate is usually higher when a user has a terrible experience with these instruments. It would be appropriate to incorporate the final users-whether they are patients, health care professionals, or both-in the stages of instrument design to understand their needs and preferences. Since most apps that fail did not include end users and health care professionals in the development phase, their involvement at all stages of app development may increase their commitment and improve integration, self-management, and health outcomes. This study aims (1) to develop semAPP (spatial and episodic memory assessment application), a 360° media-based tool, to assess memory in aging by simulating a real-life situation and (2) to test the usability of the app and the connected experience in an end-user population. A total of 34 older adults participated in the study: 16 (47%) healthy individuals and 18 (53%) patients with mild cognitive impairment. They used semAPP and completed qualitative and quantitative measures. The app includes 2 parts: object recognition and spatial memory tasks. During the first task, users have to navigate in an apartment freely and visit rooms, and then they must recognize the right map of the house. In the second task, users are immersed in a living room, and they have to encode and then recall some target objects, simulating a relocation. We deployed this app on an 11.2-inch iPad, and we tested its usability and the experience of users interacting with the app. We conducted descriptive analyses for both the entire sample and each subgroup; we also conducted parametric and correlation analyses to compare groups and to examine the relationship between task execution and the virtual experience, as well as the acceptance of technology. Both groups judged the app as an easy-to-use tool, and they were willing to use it. Moreover, the results match the idea that usability might be influenced by different factors depending on instrument and personal features, such as presentation, functionality, system performance, interactive behavior, attitudes, skills, and personality. The findings support the possibility of using semAPP in older patients, as well as the importance of designing and evaluating new technological tools, considering not only the general population but also the specific target ones.

An Evolutionary Modular Product Development Under Circular Economy Approach

The incorporation of new technologies and materials, as well as the rapid evolution of products, makes it necessary to guide the product design and development process from bio-inspired perspectives that promote a circular economy. Among the proposals based on a bio-inspired solution is the framework called the Genomic Model of Eco-innovation and Eco-design, which integrates the Cradle-to-Cradle paradigm, material and substance flow analysis, along with all aspects present in the life cycle analysis of products. In this work, innovation is carried out through the integration of genetic algorithms as a methodological tool for optimizing the modular product design in the definition of the genotype within the aforementioned framework. Through a systematic approach, it analyzes how the modular reconfiguration of products, based on circular design principles and genetic optimization, can contribute to a significant reduction in resource use and waste generation. The proposed methodology is applied to a practical case based on the redesign of a small household appliance, demonstrating its potential to facilitate the implementation of circular economy strategies in the early stages of the product design and development process for studying product modularity, with the aims of improving its design and reducing its impact.

ESR Essentials: how to get to valuable radiology AI: the role of early health technology assessment-practice recommendations by the European Society of Medical Imaging Informatics.

AI tools in radiology are revolutionising the diagnosis, evaluation, and management of patients. However, there is a major gap between the large number of developed AI tools and those translated into daily clinical practice, which can be primarily attributed to limited usefulness and trust in current AI tools. Instead of technically driven development, little effort has been put into value-based development to ensure AI tools will have a clinically relevant impact on patient care. An iterative comprehensive value evaluation process covering the complete AI tool lifecycle should be part of radiology AI development. For value assessment of health technologies, health technology assessment (HTA) is an extensively used and comprehensive method. While most aspects of value covered by HTA apply to radiology AI, additional aspects, including transparency, explainability, and robustness, are unique to radiology AI and crucial in its value assessment. Additionally, value assessment should already be included early in the design stage to determine the potential impact and subsequent requirements of the AI tool. Such early assessment should be systematic, transparent, and practical to ensure all stakeholders and value aspects are considered. Hence, early value-based development by incorporating early HTA will lead to more valuable AI tools and thus facilitate translation to clinical practice. CLINICAL RELEVANCE STATEMENT: This paper advocates for the use of early value-based assessments. These assessments promote a comprehensive evaluation on how an AI tool in development can provide value in clinical practice and thus help improve the quality of these tools and the clinical process they support. KEY POINTS: Value in radiology AI should be perceived as a comprehensive term including health technology assessment domains and AI-specific domains. Incorporation of an early health technology assessment for radiology AI during development will lead to more valuable radiology AI tools. Comprehensive and transparent value assessment of radiology AI tools is essential for their widespread adoption.