Design Requirements Research Articles

Comparative Study on the Reduction of Tritium Breeding Ratio Caused by Inventory Changes of a Solid-State Tritium Breeding Blanket in a Fusion Demonstration Reactor Using MCNP and FISPACT-II

The self-sufficient supply of tritium in the deuterium-tritium nuclear fusion demonstration reactor (DEMO) is a fundamental design requirement. But, it is hindered by depletion of tritium breeding materials resulting in reduction of tritium breeding ratio (TBR) less than the initial design value especially in the solid-state tritium breeding blanket (TBB) of the DEMO. Unlike the liquid tritium breeding blanket of DEMO, compensation measures of the depleted breeding material in the solid-state TBB will be its substitution depending on the reduction rate of TBR. To estimate the replacement period of the solid-state TBB, it is required to estimate the reduction rate of TBR according to the operation conditions of the DEMO and the physical configuration of a solid-state TBB. In this study, the representative simulation codes, MCNP and FISPACT-II, are used for assessment of the reduction rate of TBR with the benchmarking model which is modified from the one poloidal segment of the TBB in the Korean-DEMO. After 3 full power-year operations with the neutron irradiation with the benchmarking model, the TBR simulated by MCNP is reduced to 96.84% of the initially calculated TBR, but the TBR calculated by FISPACT-II is reduced to 90.57% of the initially calculated TBR.

Performance Measurement System Design for Integrated Thinking: Evidence from Japanese Electric Utility Providers

Asian companies are increasingly practicing integrated reporting to create long-term economic, environmental, and social value for investors and other stakeholders. To accomplish such value creation, far-reaching changes in strategies, management control systems, and governance are required, which is achieved through a management approach called integrated thinking. However, findings from previous studies indicate barriers in designing performance measurement systems, leading to misalignment between strategies and managers' decision-making. Therefore, this research study aims to expand existing knowledge on integrated reporting by (1) developing a conceptual framework for the characteristics of performance measurement systems to support integrated thinking and (2) analyzing the current status of performance measurement systems used by Japanese electric utility providers. To support integrated thinking, performance measurement systems should contain multidimensional and connected key performance indicators with quantitative target values and action plans that are integrated into the management reward system. By utilizing primary data, the most recent integrated reports of all 11 Japanese electric utility providers were analyzed trough a manual content analysis and percentage analysis. On average, the requirements of performance measurement system design are fulfilled to a degree of 56 %, while the lowest degree being 39 % and the highest degree being 75 %. In most cases, companies use multidimensional key performance indicators with incomplete target values and vaguely defined action plans. Key performance indicators are insufficiently connected and integrated with rewards systems, indicating the outside-in approach of integrated reporting. Larger companies that explicitly refer to the <IR> Framework tend to use more sophisticated performance measurement systems. The findings suggest several areas for improvement, such as connectivity between KPIs as well as further integrating non-financial KPIs with the rewards system.

Automated layout generation from sites to flats using GAN and transfer learning

Generating architectural layouts from sites to flats, encompassing site layouts (SLs), building layouts (BLs), and flat layouts (FLs), presents a complex process. Notably, the BL generation is challenging due to the small scale of data, making it difficult to train effective neural networks. This paper introduces an approach for generating layouts throughout the complete process. Initially, it proposes an enhanced generative adversarial network (GAN) combined with the transformer for Stable Diffusion (TranSD-GAN), considering design boundaries and requirements. Subsequently, for generating BLs with small-scale datasets, the paper proposes a stacking transfer learning method. Following this, image operations are conducted to support the flow of building information. Ultimately, BIM models are created at each stage. Through comparative experiments involving neural networks and generation cases, it is demonstrated that the proposed method significantly improves the generative capabilities of small-scale datasets and effectively aids designers throughout the layout design from sites to flats.

Data ‐Driven Long‐Term Energy Efficiency Prediction of Dielectric Elastomer Artificial Muscles

AbstractThe widespread adoption of dielectric elastomer actuators (DEAs) as compliant artificial muscle is on the horizon after a wide range of prototype demonstrations. The next step is to accelerate the material optimization for specific design requirements. This work proposes a data‐driven framework to predict long‐term DEA energy consumption and efficiency using measurements of initial electrical properties. DEA datasets are generated from 242 pre‐stretched single‐layer actuators and 53 multi‐layer bending actuators actuated for 30–180min. Devices are made with different elastomer and electrode materials, and tested with a novel instrument that can measure multiple aspects of DEA actuation. First, experiments are conducted to develop an empirical understanding of the electro‐mechanical energy conversion mechanism and the impact of material choices during DEA actuation. Second, data‐driven models are applied to the datasets to predict energy consumption and efficiency. Third, the potential generalization of this approach is investigated by using transfer learning strategies to predict energy efficiency at 100 min with as little as 1 min of input data. Moreover, it is found that linear regression can extend the prediction up to 180 min. Additionally, transfer learning is applied to predict energy‐related properties of multi‐layer DEAs using a small dataset. The proposed data‐driven framework can evolve into an intelligent system for accelerating new material discovery by predicting performance and providing device optimization strategies.

Design, motions, capabilities, and applications of quadruped robots: a comprehensive review

Robots are becoming integral to society and industries due to their enormous advantages. Among the various categories of mobile robots, including wheeled robot, tracked robot, and legged robots, the latter stands out as a better choice for most field applications due to their adaptability across various terrains. The purpose of this review is to study the locomotion capabilities of quadruped robots and judge their suitability for climbing applications as most unexplored applications of automation and robotics are required to climb. This review explores the locomotion capabilities of quadruped robots. It covers different aspects of quadruped robots like types of legs, leg design, gait patterns, and their mathematical formulations, and types of motions like omnidirectional motion and body sway motion. It also emphasizes its fault-tolerant gait, adaptability, and reliability. The paper also focuses on slope and stair climbing, outlining design requirements and applications. The study includes an examination of the applicability of various gaits under different conditions and the methods for increasing stability without compromising speed. Overall, the review serves as a valuable resource for future research in this field.

Design and Conformation of Separators for High-performance Aqueous Zinc-Ion Batteries.

Aqueous zinc-ion batteries (AZIBs) are considered promising candidates for large-scale energy storage due to their high safety, low cost, and environmental friendliness. As a core component, separator plays a unique yet oftentimes overlooked role in providing electrochemical stability in AZIBs. This concept focuses on the exquisite structure-property relationship of separators, highlighting three forms of these components and their structural design requirements, i.e., traditional membranes, solid-stateelectrolytes, and electrode coatings. The mechanism by which separators influence the zinc anode and the cathode is discussed. The article also identifies the challenges and potential future directions for functional separators in the development of high-performance AZIBs.

Extending the wisdom of Tai Lue weaving to create the values of handcraft and traditional wisdom for community furniture at Wat Yuan, Thailand

This work aims to study consumer demand for newly designed Tai Lue fabric patterns for decorating bar stools; to investigate consumer demand for the materials, colour, and design requirements of bar stools; and to produce prototype bar stools decorated by Tai Lue weaves based on customer preferences. Data were collected from interviews and a literature review was conducted to design a bar stool that incorporates Tai Lue weaving. A questionnaire was distributed to better understand the desires of customers, such as newly designed patterns, materials, colours, and design requirements of bar stools. Then a prototype bar stool was produced and customer preferences and satisfaction were identified and analysed. It was found that the most popular Tai Lue woven pattern is the Dok Sor pattern mixed with the Saeng pattern. This is suitable for producing cushions and backrests because it is tightly woven, flexible and adds to the furniture's appealing feeling. Furthermore, a prototype was produced using a D-style chair made with wood of a natural colour, which is simple and can be produced in the community. This prototype bar stool is suitable for use in coffee shops. Customer satisfaction was measured in terms of its Tai Lue weaving appreciation, acceptance, ease of use, comfort, satisfaction, and durability. The customer demand scored the highest at 4,000 baht (110 USD). Finally, this study can encourage the use of traditional Tai Lue weaving patterns, thereby creating additional value and income for the Tai Lue community at Wat Yuan, in Chiang Khan district, Phayao province, Thailand.

Powering Agricultural Pumps by Solar Photovoltaic System – Case Study from Palestine

This study investigates how Palestine's dependency on imported electricity might be reduced by utilizing renewable energy (RE). There is tremendous potential for utilizing solar energy (SE) in the area given the profusion of sunshine hours. This study's main objective is to use SE to drive agricultural pumps that draw groundwater out of the ground and deliver it to various irrigation systems. For a number of compelling reasons, SE must be used in agricultural initiatives in Palestine. As a result, the adoption of solar photovoltaic (PV) systems to power pumps and wells located within the Tulkarm District is being examined and compared in this study. wo pumps feeding the same well and rated at 250 and 150 horsepower each have been specifically chosen for this use. Following that, this study gives thorough design requirements, together with the technical and budgetary characteristics of the necessary solar PV system. The planned system consists of 517 PV panels that are carefully placed over a 1300 m2 area to successfully provide 50% of the energy needs of the pumps. The device additionally has a good payback period of 2.5 years

Kansei engineering for the intelligent connected vehicle functions: An online and offline data mining approach

The big data era enables automakers to mine users’ affective (Kansei) requirements for the car design. However, existing literature mostly applies text mining with users’ online comments, possibly leading to biased results since users without online comments were not considered. To fill in this gap, this paper proposes to jointly analyse users’ online commenting and offline usage big data, and develops a novel framework to efficiently fuse these two datasets for the Kansei engineering of the intelligent connected vehicle (ICV) functions. A behaviour-enhanced large language model is proposed to process users’ online comments; then, users’ Kansei requirements are further jointly analysed with their offline in-cabin behaviour data, by the proposed NLP-MDCEV (natural language process — multiple discrete-continuous extreme value) model, to understand user’s complex discrete and continuous choice decisions in the smart cockpit. In addition, the proposed framework aims to solve the problem of design tasks prioritization, where not all the Kansei requirements can be met if design resources are limited. The proposed framework is applied in the studied new energy vehicle company, with more than nine-months’ online comments and six-months’ offline usage data, where results suggest its merits of economic, efficient, and effective.

A stepwise scheme for the optimization implementation of lazy wave dynamic cables

The dynamic cables are usually designed to present a complex layout to improve service life and safety in commercial scale floating applications. It is urgent to establish consistent design philosophy and analysis methodologies to provide cost-efficient design requirement. A stepwise scheme for the optimization implementation of lazy wave dynamic cables is proposed and performed with a mass-damping equivalence model. A complicated multi-objective optimal procedure is implemented progressively under hydrostatic state, regular wave state and stochastic sea state. It is validated through a lazy wave dynamic cable (LWDC) from a cylindrical FPSO system under extreme conditions. Stepwise upgraded calibrations based on the coupling of multi-objective optimization modular NSGA-II and lumped mass FEM are applied to assess every sub-objective in defined steps. It is shown that the result is far beyond expectation than initial design after the application of the progressive solution system.

An improved cubature Kalman filter state prediction method based on the design of active denial tracking system.

In this paper, an improved CKF (Cubature Kalman Filter) target tracking method is adopted to solve the tracking and pointing problem in the field of the Active Denial System. The math model of the system is built and the precision requirement is analyzed. The improved CKF method is input as the feedforward compensation for system control to improve the system tracking performance. In the process of the iterative CKF algorithm, nonlinear means are used. The method makes full use of measurement information and estimates the target velocity acceleration model parameters through the neural network, which is used as the input of the CKF to modify the process parameters of CKF and improve the state estimation accuracy. At the same time, the limited lower bound method is used to ensure that the gain reaches the lower bound bottom line of the precision demand, so that it does not tend to zero with time, so as to avoid affecting its rapid response ability during maneuvering and so that the prediction error is also controlled within the range of the precision demand. The simulation and experimental results show the superiority of the method and make the system fully meet the design requirements.

Mechanism of active flow control using a novel spike aerodome-channel concept in the hypersonic flow: A numerical study

Among the design requirements of hypersonic vehicles, reducing aerodynamic heating and drag force simultaneously is the main challenge. This paper proposes a novel spike aerodome-channel combination concept to realize the flow field reconstruction around the hypersonic blunt body. The novel configuration is investigated in the axisymmetric flow at a Mach number of 6 at zero angle of attack. The two-dimensional Reynold-averaged Navier–Stokes equations are numerically solved, and the shear-stress transport k–ω model is the turbulence model implemented in this study. Parameters such as spike length and lateral jet location are investigated to explore the drag and heat reduction performance and the flow control features. The obtained results show that the application of the novel spike aerodome-channel concept alters the flow field by eliminating or replacing the strong bow shock wave, and the design of hypersonic vehicles can benefit from the application of the proposed concept. The blunt body coupled with a frustum of cone-tipped spike-channel configuration provides a remarkable drag reduction effect of 20.71% with respect to the case without channel. Considering the effect of lateral jet location, the drag reduction performance of the case with LR = 0.75 is superior to that of the root jet case at the same spike length, and a considerable drag reduction of 28.93% is obtained with L/D = 2.4. In addition, longer spike length is beneficial for improving drag reduction performance, while excellent efficiency of heat protection is obtained in a certain spike length range. For the case of L/D = 1.6 with root jet, the peak Stanton number is significantly decreased by 33.51%.

秸秆粪便斜式混配输送机螺旋-螺带组合机构设计与试验

In order to solve the problem of poor mixing effect of inclined spiral conveyor, this paper designed an inclined spiral and ribbon blade combination conveying device. The mechanics and kinematics analysis of the movement process of the material unit in each mechanism was carried out, on which key devices and components were designed based. Effects of the speed of main shaft (X1), the full coefficient (X2) and the angle of inclination (X3) on the mixing uniformity (Y1) and the residual rate of material (Y2) were explored. Three-dimensional quadratic regression orthogonal rotation central combination experiment method combined with response surface method was used to conduct experiments and explore the interaction effects of influence factors on indicators. A regression model of influence factors and evaluation indicators was established through the analysis of variance. The significant factors affecting Y1 were ordered of X3, X2, X1, and the significant factors affecting Y2 were ordered of X2, X1, and X3. In the interaction of factors, X1X2 had a significant impact on Y1 and Y2; X1X3 had an extremely significant impact on Y1; X2X3 had an extremely significant effect on Y1 and a significant impact on Y2. The optimal structure and working parameters combination were determined to be 50 rpm for the speed of main shaft, 60% for the full coefficient, and 19° for the angle of inclination, while the verification experiments demonstrated that the mixing uniformity and residual rate of material corresponding to the verification test were 90.37% and 5.31%, respectively. The inclined device with combined spiral and ribbon blade developed in this study meets the design requirements for the misprocess of the fertilizer utilization of agricultural organic wastes.

On the Combinatorial Acceptability Entropy Consensus Metric for Multi-Criteria Group Decisions

AbstractIn group decisions, achieving consensus is important, because it increases commitment to the result. For cooperative groups, Combinatorial Multicriteria Acceptability Analysis (CMAA) is a group decision framework that can achieve consensus efficiently. It is based on a novel Combinatorial Acceptability Entropy (CAE) consensus metric. As an output measure, the CAE metric is unique in its ability to identify the evaluations that have the greatest impact on consensus and to prevent premature consensus. This paper is intended to complement the original CMAA publication by providing additional insights into the CAE consensus metric. The design requirements for the CAE algorithm are presented, and it is shown how these requirements follow from the properties of cooperative decisions. The CAE-based consensus-building algorithm is contrasted both qualitatively and quantitatively with a representative example of the conventional input distance and input averaging approach to multi-criteria consensus-building. A simulation experiment illustrates the ability of the CAE-based algorithm to converge quickly to the correct decision as defined for cooperative decisions. The metric is able to meet a new, more stringent definition of hard consensus. The CAE approach highlights the need to distinguish between competitive and cooperative group decisions. Attention in the literature has been paid almost exclusively to the former type; the CAE approach demonstrates the greater efficiency and effectiveness that can be achieved with an approach that is designed specifically for the latter.

Monitoring Wearable Devices for Elderly People with Dementia: A Review

The growth in the prevalence of dementias is associated with a phenomenon that challenges the 21st century, population aging. Dementias require physical and mental effort on the part of caregivers, making it difficult to promote controlled and active care. This review aims to explore the usability and integration of wearable devices designed to measure the daily activities of elderly people with dementia. A survey was carried out in the following databases: LILACS, Science Direct and PubMed, between 2018 and 2024 and the methodologies as well as the selection criteria are briefly described. A total of 27 articles were included in the review that met the inclusion criteria and answered the research question. As the main conclusions, the various monitoring measurements and interaction aspects are critically important, demonstrating their significant contributions to controlled, adequate and active monitoring, despite the incomplete compliance with the key aspects which could guarantee solutions economically accessible to institutions or other organizations through the application of the design requirements. Future research should not only focus on the development wearable devices that follow the essential requirements but also on further studying the needs and adversities that elderly people with dementia face as a pillar for the development of a feasible device.

Toward a Methodology for the Verification and Validation of AI-Based Systems

<div>Verification and validation (V&V) is the cornerstone of safety in the automotive industry. The V&V process ensures that every component in a vehicle functions according to its specifications. Automated driving functionality poses considerable challenges to the V&V process, especially when data-driven AI components are present in the system. The aim of this work is to outline a methodology for V&V of AI-based systems. The backbone of this methodology is bridging the semantic gap between the symbolic level at which the operational design domain and requirements are typically specified, and the sub-symbolic, statistical level at which data-driven AI components function. This is accomplished by combining a probabilistic model of the operational design domain and an FMEA of AI with a fitness-for-purpose model of the system itself. The fitness-for-purpose model allows for reasoning about the behavior of the system in its environment, which we argue is essential to determine whether the system meets its requirements. While this work only provides an outline of such a methodology, we point out future research directions toward a full methodology for the V&V of AI-based systems.</div>

Semantic Kansei Engineering Approach for Game Controllers and Design Improvement

The entertainment industry undergoes constant changes, and video games, along with the ways people enjoy them, evolve dynamically. In this context, there arises a need to innovate in areas such as user–game interaction and the design of conventional controllers to keep up with these transformations. This study has found that the design requirements of the external geometry of video game controllers significantly impact users’ purchasing decisions, who often rely on their sensations and emotions. The primary aim of this research has been to demonstrate that it is possible to develop a specific methodology to establish design guidelines that evaluate geometry and ergonomic aspects, considering users’ emotional needs. To achieve this goal, the Kansei methodology has been employed, an engineering discipline that focuses on product design based on emotional interaction and user sensations when using them. Through advanced statistical techniques such as principal component analysis and linear regression, the set of observations has been reduced and a robust predictive model has been developed. Following this methodological approach, surveys and field studies have been conducted, thus differentiating the project from a conventional engineering approach in various stages. Special attention has been paid to the tactile part of the controller, especially its casing. After thorough analysis, the redesigned casing, incorporating improvements derived from statistical analyses, has been compared to existing market models. The results obtained show a significant improvement compared to existing market models, particularly highlighting enhancements in functional characteristics and ergonomic design, enabling comfortable use for individuals with different hand sizes and preventing the grip surface from being slippery. In summary, this work supports the effectiveness of the Kansei methodology as an approach to adapting product design to users’ perceptions and emotional needs.

Research on the Application of Manchu Folk Art in Modern Home Accessories

Manchu folk art as an important part of China’s traditional culture, has a high artistic value and cultural research value. The cultural and artistic production of Manchu folk art originated from a specific living environment and cultural background, which has a unique charm to its artistic style. Modern home accessories are commonly used in people’s daily lives, and their reasonable application can improve the atmosphere of the indoor space environment and make it more beautiful. The organic integration of modern home accessories with Manchu folk art not only can improve the humanistic atmosphere of indoor space, but also strengthen the indoor artistic atmosphere. This is conducive to the inheritance of Manchu folk art, to realize the innovative development of the art. To realize the integration between the two, one needs to consider the characteristics of modern home accessories and Manchu folk art, combined with the actual situation, according to the design requirements of modern home accessories, extract the appropriate elements from Manchu folk art, using the appropriate form, and integrate it into the home accessories, to improve its application effect.

Evaluating the Desirability of Outcome Ranking (DOOR) and Response Adjusted for Duration of Antibiotic Risk (RADAR) for Clinical Trials of Antibiotics in Pediatric Pneumonia.

Objective outcomes for pediatric community-acquired pneumonia (CAP) are lacking. The desirability of outcome ranking (DOOR) and response adjusted for duration of antibiotic risk (RADAR) outcome encompass clinical benefit and adverse effects, while also accounting for antibiotic exposure. We evaluated DOOR/RADAR through simulations and compared sample size considerations to non-inferiority designs in a hypothetical trial comparing antibiotics to no antibiotics (i.e., placebo) for children with mild CAP. We also evaluated a trial comparing different durations of antibiotics. Three scenarios were considered - one with no difference in DOOR between the two groups, one in which placebo is more efficacious, and another in which amoxicillin is more efficacious than placebo. Power to detect a difference between arms was greater using DOOR/RADAR compared to DOOR. Assuming a sample size of 200, DOOR had 2.5%, 50%, and 65% power to detect a statistical difference between arms for Scenarios 1-3, respectively, significantly less than DOOR/RADAR. Importantly, DOOR/RADAR incorrectly identified placebo as superior in Scenario 3 where amoxicillin was truly efficacious. Sample size requirements for non-inferiority designs were larger to achieve similar levels of power as DOOR and DOOR/RADAR. DOOR/RADAR has the potential to lead to an incorrect conclusion declaring placebo superior when amoxicillin is efficacious.

小麦制粉粒度检测装置供料部件设计与研究

To address the issues of poor timeliness and delayed feedback in traditional wheat milling processes for manual particle size detection, a wheat milling online particle size detection device has been designed. This paper focuses on the design optimization of the key feeding component in the device, which affects the accuracy of particle size detection. The feeding component adopts shaftless screw blades. Through theoretical analysis, the main parameter ranges affecting the throughput capacity of the shaftless screw conveyor are determined. A Box-Behnken experiment is designed to obtain the optimal parameter combination for each factor: outer diameter of screw blades 23.8 mm, inner diameter of screw blades 6.4 mm, pitch 11.2 mm, and blade rotation speed 288.9 r/min. Simulation and test stand experiments are conducted using the above parameter combination. The simulation results show that the average throughput capacity of the feeding component is 2.85 kg/h, while the average throughput capacity of the test stand experiment is 2.84 kg/h, with a coefficient of variation of uniformity of 1.33%. These results indicate that the above parameter combination meets the design requirements for the feeding component in the device.