Computational Design of Knit Templates

2022 ◽  
Vol 41 (2) ◽  
pp. 1-16
Author(s):  
Benjamin Jones ◽  
Yuxuan Mei ◽  
Haisen Zhao ◽  
Taylor Gotfrid ◽  
Jennifer Mankoff ◽  
...  

We present an interactive design system for knitting that allows users to create template patterns that can be fabricated using an industrial knitting machine. Our interactive design tool is novel in that it allows direct control of key knitting design axes we have identified in our formative study and does so consistently across the variations of an input parametric template geometry. This is achieved with two key technical advances. First, we present an interactive meshing tool that lets users build a coarse quadrilateral mesh that adheres to their knit design guidelines. This solution ensures consistency across the parameter space for further customization over shape variations and avoids helices, promoting knittability. Second, we lift and formalize low-level machine knitting constraints to the level of this coarse quad mesh. This enables us to not only guarantee hand- and machine-knittability, but also provides automatic design assistance through auto-completion and suggestions. We show the capabilities through a set of fabricated examples that illustrate the effectiveness of our approach in creating a wide variety of objects and interactively exploring the space of design variations.

PCI Journal ◽  
2020 ◽  
Vol 65 (6) ◽  
pp. 35-61
Author(s):  
Chungwook Sim ◽  
Maher Tadros ◽  
David Gee ◽  
Micheal Asaad

Ultra-high-performance concrete (UHPC) is a special concrete mixture with outstanding mechanical and durability characteristics. It is a mixture of portland cement, supplementary cementitious materials, sand, and high-strength, high-aspect-ratio microfibers. In this paper, the authors propose flexural design guidelines for precast, prestressed concrete members made with concrete mixtures developed by precasters to meet minimum specific characteristics qualifying it to be called PCI-UHPC. Minimum specified cylinder strength is 10 ksi (69 MPa) at prestress release and 18 ksi (124 MPa) at the time the member is placed in service, typically 28 days. Minimum flexural cracking and tensile strengths of 1.5 and 2 ksi (10 and 14 MPa), respectively, according to ASTM C1609 testing specifications are required. In addition, strain-hardening and ductility requirements are specified. Tensile properties are shown to be more important for structural optimization than cylinder strength. Both building and bridge products are considered because the paper is focused on capacity rather than demand. Both service limit state and strength limit state are covered. When the contribution of fibers to capacity should be included and when they may be ignored is shown. It is further shown that the traditional equivalent rectangular stress block in compression can still be used to produce satisfactory results in prestressed concrete members. A spreadsheet workbook is offered online as a design tool. It is valid for multilayers of concrete of different strengths, rows of reinforcing bars of different grades, and prestressing strands. It produces moment-curvature diagrams and flexural capacity at ultimate strain. A fully worked-out example of a 250 ft (76.2 m) span decked I-beam of optimized shape is given.


Author(s):  
Cari R. Bryant ◽  
Matt Bohm ◽  
Robert B. Stone ◽  
Daniel A. McAdams

This paper builds on previous concept generation techniques explored at the University of Missouri - Rolla and presents an interactive concept generation tool aimed specifically at the early concept generation phase of the design process. Research into automated concept generation design theories led to the creation of two distinct design tools: an automated morphological search that presents a designer with a static matrix of solutions that solve the desired input functionality and a computational concept generation algorithm that presents a designer with a static list of compatible component chains that solve the desired input functionality. The merger of both the automated morphological matrix and concept generation algorithm yields an interactive concept generator that allows the user to select specific solution components while receiving instantaneous feedback on component compatibility. The research presented evaluates the conceptual results from the hybrid morphological matrix approach and compares interactively constructed solutions to those returned by the non-interactive automated morphological matrix generator using a dog food sample packet counter as a case study.


Author(s):  
А.И. Гайкович ◽  
С.И. Лукин ◽  
О.Я. Тимофеев

Процесс создания проекта судна или корабля рассматривается как преобразование информации, содержащейся в техническом задании на проектирование, нормативных документах и знаниях проектанта, в информацию, объем которой позволяет реализовать проект. Проектирование может быть представлено как поиск решения в пространстве задач. Построение цепочки последовательно решаемых задач составляет методику проектирования. Проектные задачи могут быть разбиты на две группы. Первая группа ‒ это полностью формализуемые задачи, для решения которых есть известные алгоритмы. Например, построение теоретического чертежа по известным главным размерениям и коэффициентам формы. Ко второй группе задач можно отнести трудно формализуемые или неформализуемые задачи. Например, к задачам этого типа можно отнести разработку общего расположения корабля. Важнейшим инструментом проектирования современного корабля или судна является система ав­томатизированного проектирования (САПР). Решение САПР задач первой группы не представляет проблемы. Введение в состав САПР задач второй группы подразумевает разработку специального ма­тематического аппарата, базой для которого, которым является искусственный интеллект, использующий теорию нечетких множеств. Однако, настройка искусственных нейронных сетей, создание шкал для функций принадлежности элементов нечетких множеств и функций предпочтений лица принимающего решения, требует участие человека. Таким образом, указанные элементы искусственного интеллекта фиксируют качества проек­танта как специалиста и создают его виртуальный портрет. The process of design a project of a ship is considered as the transformation of information contained in the design specification, regulatory documents and the designer's knowledge into information, the volume of which allows the project to be implemented. Designing can be represented as a search for a solution in the space of problems. The construction of a chain of sequentially solved tasks constitutes the design methodology. Design problems can be divided into two groups. The first group is completely formalizable tasks, for the solution of which there are known algorithms. For example, the construction of ship's surface by known main dimensions and shape coefficients. Tasks of the second group may in­clude those which are difficult to formalize or non-formalizable. For example, tasks of this type can include develop­ment of general arrangement of a ship. The most important design tool of a modern ship or vessel is a computer-aided design system (CAD). The solu­tion of CAD problems of the first group is not a problem. Introduction of tasks of the second group into CAD implies development of a special mathematical apparatus, the basis for which is artificial intelligence, which uses the theory of fuzzy sets. However, the adjustment of artificial neural networks, the creation of scales for membership functions of fuzzy sets elements and functions of preferences of decision maker, requires human participation. Thus, the above elements of artificial intelligence fix the qualities of the designer as a specialist and create his virtual portrait.


Author(s):  
Kikuo Fujita ◽  
Shinsuke Akagi

Abstract A Framework of computational design method and model is proposed for layout and geometry design of complicated mechanical systems, which is named “configuration network and its viewing control”. In the method, a design object is represented with a set of declarative relationships among various elements of a system, that is, configurations, which is gradually extended from schematic structure to exact layout and geometry through design process. Since a whole of such configurations forms a too complicated network to compute all together, how to view subparts is controlled based on levels of granularity and width of scope range. Such a configuration network is made to grow and refined through embodying geometry and layout corresponding to a focused subpart with a numerical optimization procedure. The framework has also an ability to flexibly integrate with engineering analysis. Moreover, a design system is implemented with an object-oriented programming technique, and it is applied to a design problem of air conditioner units in order to show the validity and effectiveness of the framework.


2021 ◽  
Author(s):  
Yuki Shimizu ◽  
Shigeo Morimoto ◽  
Masayuki Sanada ◽  
Yukinori Inoue

The optimal design of interior permanent magnet synchronous motors requires a long time because finite element analysis (FEA) is performed repeatedly. To solve this problem, many researchers have used artificial intelligence to construct a prediction model that can replace FEA. However, because the training data are generated by FEA, it takes a very long time to obtain a sufficient amount of data, making it impossible to train a large-scale prediction model. Here, we propose a method for generating a large amount of data from a small number of FEA results using machine learning. An automatic design system with a deep generative model and a convolutional neural network is then constructed. With its sufficient data, the proposed system can handle three topologies and three motor parameters in a wide range of current vector regions. The proposed system was applied to multi-objective optimization design, with the optimization completed in 13-15 seconds.


2021 ◽  
Author(s):  
Yuki Shimizu ◽  
Shigeo Morimoto ◽  
Masayuki Sanada ◽  
Yukinori Inoue

The optimal design of interior permanent magnet synchronous motors requires a long time because finite element analysis (FEA) is performed repeatedly. To solve this problem, many researchers have used artificial intelligence to construct a prediction model that can replace FEA. However, because the training data are generated by FEA, it takes a very long time to obtain a sufficient amount of data, making it impossible to train a large-scale prediction model. Here, we propose a method for generating a large amount of data from a small number of FEA results using machine learning. An automatic design system with a deep generative model and a convolutional neural network is then constructed. With its sufficient data, the proposed system can handle three topologies and three motor parameters in a wide range of current vector regions. The proposed system was applied to multi-objective optimization design, with the optimization completed in 13-15 seconds.


2014 ◽  
Vol 510 ◽  
pp. 133-138 ◽  
Author(s):  
Young Tae Sohn ◽  
Myon Woong Park

In accordance with the increased awareness of resource depletion and environmental pollution, the importance of eco-friendly disposal and recycling of vehicles as a potentially valuable resource is emphasized; in particular, this is important as automobile production and demand continues steadily. In this paper, a systematic dismantling system is proposed to minimize the quantity of ASR by dismantling End-of-Life Vehicles (ELVs) rationally and efficiently. An adaptive layout design system is also provided to aid for the effective implementation of the proposed dismantling system to industrial applications. The proposed dismantling system is based on eco-friendly dismantling and improves not only the recyclability of ELVs, but also the efficiency of the dismantling operations. The adaptive layout design system is a software tool, which allows a layout of a dismantling plant according to the specific requirements of the customers, and estimates the overall figures and capacity of an intended plant by simulation of the dismantling process. This interactive design system can be useful for testing alternative layouts of a dismantling plant customized to meet particular recycling needs.


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