Various Media in the Design Process and Methodology

In order to solve the problems of complicated design process, insufficient optimization of design parameters and low reuse of design knowledge during traditional mechanical product detailed design process, this paper proposes a rule-driven product configuration design method. Traditional mechanical product design process is divided into a number of design nodes and partially complex functions of traditional design process are defined in nodes. Design nodes are configured and connected after forming rule-driven nodes ,which sharply simplifies the configuration process of traditional design process and can realize the optimization of design parameters. The basic database that adapt to the design node is developed and the design knowledge is integrated into the basic database and node rules, which improves the configurability of the design process and better supports the parameter optimization of the design process and reuse of design knowledge. Finally, the system software is developed and the design process of Marine diesel turbocharger is taken as an example to verify the effectiveness of the method.

Background Cardiovascular diseases are the leading cause of death throughout the developed world, attributed to approximately 17.8 million deaths worldwide in 2017 with increasing prevalence due to the aging population. Cardiovascular diseases generally result in heart failure. While the best treatment option for heart failure patients is heart transplantation, there is a severe deficiency in the availability of donor hearts. Rotary Blood Pumps (RBPs) utilised as Ventricular Assist Devices (VADs) provide an alternative treatment option. These devices are small implantable pumps that support the failing heart by providing power to augment circulation. The development of RBPs generally begins with initial designs obtained using traditional pump design methods (such as that developed by Stepanoff). However, studies have shown that this approach produces RBP prototypes far from optimal in design. Traditional theory relies on design constants derived empirically for large industrial pumps and these do not scale down well when applied to the much smaller RBPs. The initial designs are therefore generally quite poor and require an iterative build-and-test approach to obtain suitable pump prototypes – a process that is expensive and time consuming. Therefore, by improving the methodology for obtaining initial designs to better reflect the final product, development time can be greatly reduced. A popular avenue for analysing the effect of design variations and to further develop early prototypes of RBPs is to employ Computational Fluid Dynamics (CFD) simulations. These numerical simulations provide detailed data regarding the flow fields within these devices. However, a range of simulation options is available, leading to a wide range of potential predictions. In an attempt to provide a benchmark case, the FDA presented a challenge in which a pump design and test conditions were defined, allowing for direct comparison amongst different simulation approaches from a number of labs/RBP developers. The purpose of this thesis was to produce a gross design tool to provide a good starting point in RBP prototyping and a CFD simulation approach for verification that can also be used as a design refinement tool. Methods Formulating a design method for pumps requires the generation of empirical data. A number of pump design variables was identified as having an impact on pump performance, and a large number of experimental tests would have been needed to test the influence of each. Instead, a Design of Experiments (DOE) was utilised to streamline the process. The DOE outputs a relatively small number of tests required to fit a statistical model. Each design specified by the DOE was examined experimentally using a custom-built automated pump test platform to generate a number of performance measures. The obtained results were used to formulate a Response Surface Method (RSM) statistical model that showed acceptable fit to the input data. Coupled with desirability functions, the RSM model allowed for design optimisation. This tool essentially replaces Stepanoff’s traditional design methodology. The RSM model provides a robust tool that allows the user flexibility in design optimisation goals. The FDA pump was investigated in this thesis and a wide variety of simulation approaches was examined to determine which was most accurate. A range of factors were considered which included: mesh density, interface position between the rotating and stationary zones, steady vs. transient simulations, discretisation schemes, time step size and choice of turbulence model. The most appropriate option from each investigative study was selected to determine a recommended simulation approach. Final simulations were performed using these recommendations and were compared to the FDA experimental results to confirm the suitability of the suggested settings. Determination of Centrifugal Blood Pump Characteristics using CFD and Experimental Analysis iii The statistical model developed was used to design two different impellers as validation test cases. The first impeller was designed to optimise the maximum efficiency, P – Q curve slope and efficiency consistency. The second impeller was designed to mimic the approach used in traditional design methods for RBPs in setting a target design point as the primary objective and the aforementioned factors (from the first impeller) as secondary objectives. These two case studies underwent statistical performance predictions, CFD simulations, PIV analysis and experimental hydraulic testing to validate the statistical and CFD models. Results From the initial CFD study, a hybrid SBES turbulence model with full transient simulation on a fine grid with small time steps proved to be the most suitable both in terms of pressure rise generated by the FDA pump and resulting velocity fields when compared to published experimental results. From these findings the CFD modelling strategy was established. CFD results for the two validation pumps showed pressure rises matching the experimental data (8% and 1% difference for each impeller) within an acceptable range (<10% from the mean). The simulated velocity fields also closely replicated the PIV data for the majority of the flow domain. The statistical performance predictions well reflected those measured experimentally with the majority of data points falling within its confidence intervals. The hydraulic results also supported the main goal of this thesis, whereby an impeller generated using the statistical model, operated far closer to the target design point than that of a blood pump designed following Stepanoff’s methodology. Overall, both the statistical model and CFD approach provided accurate predictions and the purpose of the thesis was achieved. Final Remarks The statistical and CFD models developed in this thesis yield an effective design tool and verification methodology and show improvement over the current traditional design methods and accuracy in simulated results. Ultimately, the utilisation of these tools will lead to a reduction in the development time for new RBPs and provide a good understanding of the flow dynamics within these pumps, leading to improved pump designs reaching patients sooner. These tools are readily generalizable and could be adopted as design tools now.

With the rapid development of artificial intelligence, handicraft design has developed from artificial design to artificial intelligence design. Traditional handicraft design has the problems of long time consumption and low output, so it is necessary to improve the process technology. Artificial intelligence technology can provide optimized design steps in handicraft design and improve design efficiency and process level. Handicrafts are regarded as important social products and exist in people’s daily life. In the current society, many people do handicrafts and there are major exhibitions. Furthermore, the display of handicrafts is also very grand and shocking. In the design of handicrafts, the traditional design method cannot completely keep up with the production speed and efficiency of handicrafts. Therefore, this paper adopts the fusion multi-intelligent decision algorithm of multi-node branch design in the design method of handicraft. The algorithm model combination is used to analyze and design the layout of the handicraft, which speeds up the design efficiency and production of the handicraft. In this paper, two intelligent algorithms will be used for fusion; they are genetic algorithm and GA-PSO fusion algorithm obtained by particle swarm optimization and they are embedded in handicraft design method for application through mathematical model construction and function construction. After comparing the performance parameter index data of three intelligent algorithms and GA-PSO fusion algorithm, it is obtained that GA-PSO fusion algorithm is 97% correct and has 82% readability, 72% robustness, and 61% structure, making it have better important indicators. Four algorithms optimize each design problem in all aspects of handicraft design at present. Design efficiency, image distribution rate, image optimization degree, and image clarity are compared by simulation experiments. Compared with three intelligent algorithms, traditional design methods, and manual design methods, GA-PSO fusion algorithm can effectively improve the design method and design effect of handicrafts with 92.1% design efficiency, 82.7% image distribution rate, 94.3% image optimization degree, and 84% layout void rate. Finally, the space complexity experiment of four algorithms shows that GA-PSO algorithm can achieve 9.73 dispersion with 11.42 space complexities, which makes the dimension reduction relatively stable, and the algorithm can maintain stability in the design and application of handicrafts.

Mass-collaborative product development refers to a paradigm where large groups of people compete and collaborate globally to develop new products and services. In contrast to the traditional top-down decomposition-based design processes, the primary mechanism in mass-collaborative product development is bottom-up evolution. Hence, the issues underlying mass-collaborative processes are fundamentally different from those in traditional design processes. For example, instead of determining the best sequence in which activities should be carried out, the emphasis is on developing the right conditions under which product evolution can be fostered. Existing research on product development is primarily focused on top-down design processes. The evolutionary nature of mass-collaborative product development has received very little attention. Specifically, computational models for these processes have not been developed. In this paper, a step toward understanding the fundamental processes underlying mass-collaborative product development using a computational model is presented. The model presented in this paper is based on an agent-based modeling approach, which allows the modeling of the behavior of different entities within a product development scenario and the study of the effect of their interactions. The model captures the information about (i) products as modules and their interdependencies, and (ii) the participants involved and their strategies. The benefits of the agent-based model in understanding mass-collaborative product development are shown using a simple product model. The following aspects of the product development processes are studied: (a) the rate of evolution of the individual modules and the entire product, (b) product evolution patterns and the effect of the number of participants, (c) the effect of prior work on product evolution, (d) the evolution and distribution of participants, and (e) the effect of participant incentives. The agent-based modeling approach is shown as a promising approach for understanding the evolutionary nature of mass-collaborative product development processes.

With development of nonlinear construction theory and digital technology, parameterization construction design has drawn extensive attention in construction industry as a new method of solving complex problems in construction. Parameterization design method has broken through the qualitative and transcendental design methods for design issues in the traditional design process. After getting rid of the form constraint of Euclidean geometry, generation of construction space and form is on the judgment basis of quantized data. Such bottom-up dynamic design process has broken through imprisonment of traditional form and construction design has returned to the original point of rational creation. In this paper, a certain foundation is laid for theoretical researches on development, influence and future of parameterization design from the aspects of parameterization design concept, tool, scheme generation, its influence on design thinking, etc.

The draft ASME Plant Systems Design standard (PSD-1) provides a new approach to design of nuclear and other plants with potential for significant hazards to the health and safety of the public, the worker, and the environment. The objectives of PSD-1 are to improve integration of health, safety, and environmental risk evaluations with design; reduce new plant design, construction, commissioning, and life cycle costs; reduce licensing and construction uncertainty; and improve operating plant availability. PSD-1 includes requirements and guidance, for design organizations to incorporate risk informed probabilistic design methodologies with traditional deterministic design methods using reliability and availability targets. It integrates systems engineering, qualitative and quantitative risk evaluations, and probabilistic design methods into traditional design processes. The risk evaluation processes integrate safety risk evaluations with production risk evaluations to increase performance over the plant life cycle. Risk evaluation processes also integrate current industry and regulatory concepts of defense-in-depth, safety significance, as well as risk-informed and performance-based design into a seamless design process. The PSD committee follows a systems engineering process and is writing the standard in a Model Based Systems Engineering tool. This paper provides an introduction and overview of the new standard that is targeted for publication in 2025.

The Department of the Navy 2021 Unmanned Campaign Framework has identified a need for increased capability in long-term autonomous maritime systems. In the context of this research, long-term autonomy is defined as the capabilities of self-governance, situational awareness, and operation independent of human interaction over a prolonged period. DARPA’s Anti-Submarine Warfare Continuous Trail Unmanned Vessel (ACTUV) program, now the U.S. Navy’s Sea Hunter program, among others, showcases the Navy’s commitment to develop and explore unmanned autonomous maritime systems. One of the challenges for development of these unmanned systems lies in the ship design process. Traditional ship design methods assume crewed operations when sizing the systems, generating layouts, and considering operational requirements. Existing unmanned maritime systems are often retrofitted to be unmanned rather than being uniquely designed for their purpose. Even in cases where autonomous systems are designed from scratch, these systems are fundamentally limited by technologies developed for traditional vessels. This can result in suboptimal solutions and missed opportunities. In particular, a lack of focus on reliability and endurance in both technology development and early in the design process results in significant impacts to unmanned systems. Reliability is often measured using mean time between failures. Given that maintenance is traditionally carried out frequently, reliability is not often a limiter for mission success, as the crew can handle non-critical failures. This assumption becomes invalid in the sphere of autonomous ship design, where theater maintenance is not feasible. For example, in a test voyage from SanDiego to PearlHarbor, Sea Hunter relied on crew on a support vessel to resolve several mechanical issues which arose in its journey. This suggests a possible technology gap in the reliability of subsystems key to autonomous maritime systems. Entwined with reliability is endurance. Endurance refers to how long the vessel can stay out at sea, a critical factor for many autonomous missions. Additional aspects of traditional ship design will need to be altered, including but not limited to the following: human support systems, human interfaces, and general structural design.The authors propose a set of modifications to the traditional ship design process to support the design of autonomous ships starting from concept design through full contract design. Design disciplines specifically tailored to unmanned system design will be incorporated into the design process. A technology impact forecasting (TIF) study will be conducted to determine key areas of research needed to support future unmanned systems. This approach results in system performance metrics needed to meet requirements and quantifies the deficits or surpluses by comparison to a baseline vehicle and mission. The baseline mission for this analysis will be a security anti-submarine warfare activity similar to the ACTUV program, with an initial endurance goal of 90days. The TIF analysis of this baseline mission will quantify gaps in performance metrics and will offer a guideline for where further research and investment are required to enable the vision of long-term autonomous maritime systems.

Facing the design and development of complex products, the traditional design innovation model can not solve the problem of the transformation of consumers' emotional information in the design process. The main reason is that users' emotional information is difficult to capture in the design process, and the traditional design process can not solve complex problems. In this case, it is necessary to establish a product perceptual intention model based on perceptual engineering and neural network. The model is not only a new method of product innovation design, but also a market-oriented process to reduce design risk. This research is an interdisciplinary application research. Taking the electric water heater product as an example, the model is constructed, mainly using the relevant theoretical knowledge of perceptual engineering and neural network. The model transforms emotional information into measurable data, and establishes the corresponding relationship between product shape structure and perceptual evaluation value through BP neural network. The model provides a reliable scientific theoretical basis for the perceptual design of products, can speed up the product development process, reduce the development cost, and make the development results more in line with consumers' expectations. The model is suitable for enterprise application and is an effective supplement to the traditional design method. Similarly, the model can also provide reference for the development and design of other products.

As we enter 21st century, the environmental problem is increasingly prominent. Chinese urban residence construction stands in the transition period of sustainable development. How to realize low energy consumption, long service life and high quality of residence becomes a subject to be solved in Chinese residence construction in new era. For China's traditional residential design and construction method formed as a linear process and single data feedback as well as great loss of information in design, the residential quality and properties have not only been unimproved, but have also led to relatively more time and costs spent. This paper introduces a design concept of whole life cycle and points out the traditional design concept and processes of the residence construction must be charged in order to realize its sustainable development. According to the design concept of the whole life cycle, this paper puts forward the residence design principle based on whole life cycle and institutes the residence design processes based on whole life cycle.

The use of flexible roof diaphragms is very common in the United States, both for residential buildings and large-scale commercial buildings. Due to its simplicity, the traditional diaphragm design method is commonly used in diaphragm design, in particular for the design of diaphragms with relatively small dimensions. The traditional diaphragm design method assumes the axial chord forces developed in framing members under in-plane loading are carried only by the perimeter elements. The traditional diaphragm design method has always been thought to be a conservative design method, especially when applied to large diaphragms. In recent years, the engineering community began to question the applicability of the traditional diaphragm design method. A new design approach known as the collective chord design method was proposed to analyze the chord forces for very large flexible roof diaphragms. This method utilizes strain compatibility of a simple beam to estimate the axial forces in chord members. This paper evaluates the applicability of the traditional and collective chord design methods by modeling the behavior of large panelized roof diaphragms numerically.

This chapter focuses on recent development of direct probability-based designmethods, including the expanded reliability-based design (expanded RBD) method, reliabilitybased robust geotechnical design (RGD) method, and the new safety standards for flood defenses in the Netherlands which is the first ever national standard that adopts direct (or full) probability-based design methods. One major criticism to the simplified semi-probabilistic RBD format is displacement of sound engineering judgment and lack of flexibility for practitioners. Because the simplified semi-probabilistic RBD format adopts the same trial-and-error approach as traditional allowable stress design (ASD) methods and it is developed to circumvent the need for practitioners to perform probabilistic analysis, these compromises seem unavoidable. An alternative solution to this dilemma is to maintain the engineering judgment and flexibility similar to ASD methods, but at the expense of performing probabilistic analysis using direct probability-based designmethods. It is shown that, with the aid of commonly available computers and widely used computer software such as Microsoft Excel, performing Monte Carlo Simulation (MCS)-based probabilistic analysis and design are becoming more and more straightforward and convenient. MCS is already available in some commercial geotechnical software programs. MCS can be comprehended easily as a repetitive computer execution of traditional ASD design calculation, and the reliability analysis background required for performing MCS is substantially reduced. A gravity retaining wall design example is used in this chapter to illustrate theMCS-based design method in Excel.

The product design theory and methods based on “the Scientific Outlook on Development” have been set up by our group in recent 10 years, The new progress concerning Research of product design theory and methods include: 1) QCTES was instead of IQCTES including six requirements of product design; 2) traditional design stages were replaced with four new stages including investigation, planning, implement and inspection; 3) green design was replaced with harmonious design; 4) traditional design method was replaced with deep-layer design method; 5) concept and connotation of product top-layer design were proposed; 6) more detailed contents of product synthesis design method were advanced. We got good effects to apply above product design methodology on many product designs recent years.

For product development, the enterprise and design department how to effectively operate design strategy and process to short cut the gaps from the user and marketing feedback. To achieve the objectives of enterprise and consumer is one important issues of product design. But in the product design form design objective, strategy and concept either influence the design result or change the product concept and the development of design process. This paper discussion the ”Wireless LAN Card” product design as a case study to analysis the customer requirement and the process develop of technological innovation from enterprise perspective. In design process face the impact of marketing competitors to change design objective and strategy for responding new marketing problem. And the marketing competitive oriented design process is completely different form traditional similar design process. The main succeed key factor is to change the weakness of marketing to advantageous. Therefore in case study the design process use the methods of brainstorming and patent design to solve the problem further construct the process planning from marketing competition oriented. Finally success reverses weakness and adds a new pattern patent design and use a new material to improve product quality.

Sensitivity analysis of energy performance and thermal comfort throughout building design process

<p>Optimal design is attracting increasing interest due to the huge energy and material consumption for tall steel structures. The optimization of certain structure is based on primitive design, which is commonly obtained by traditional design process. The design results obtained from the optimization of primitive design is called optimal design. Traditional optimal design method commonly starts with a primitive design which is greatly over constrained. The over constrained primitive design has great design redundancies, and further optimization process will successively reduce the design redundancies until the controlling constraints are properly constrained. There is another optimization process, however, which starts with a primitive design which is under constrained. The under constrained primitive design will be effectively upgraded in successive optimization process using minimum structural material increments until the controlling constraints are properly constrained. The first optimization process, which starts with over constrained primitive design is called forwardly constrained optimal design (FCOD) method. The second optimization process, which starts with under constrained primitive design is called reversely constrained optimal design (RCOD) method. In this paper, the RCOD method is applied to a 10-storys steel frame structure to investigate the superiority of the RCOD method when compared with the FCOD method.</p>