Kyoto University · Engineering
Professor Kazuki Hayashi's research lab specializes in computational structural design and geometry processing, focusing on the integration of machine learning, graph-based methods, and differential geometry to solve complex engineering optimization problems. The lab develops innovative algorithms combining reinforcement learning and graph embedding to optimize truss and frame structures for minimal volume under mechanical constraints, while also advancing the generation of freeform surfaces with constant curvature properties. Their work spans structural topology optimization, deployable auxetic mechanisms, and geometric surface modeling using curvature flows and energy-based formulations.
Figures are computed from collected data and may differ slightly.
This paper addresses a combined method of reinforcement learning and graph embedding for binary topology optimization of trusses to minimize total structural volume under stress and displacement constraints. Although conventional deep learning methods owe their success to a convolutional neural network that is capable of capturing higher level latent information from pixels, the convolution is difficult to apply to discrete structures due to their irregular connectivity. Instead, a method based
A combined method of graph embedding (GE) and reinforcement learning (RL) is developed for discrete cross-section optimization of planar steel frames, in which the section size of each member is selected from a prescribed list of standard sections. The RL agent aims to minimize the total structural volume under various practical constraints. GE is a method for extracting features from data with irregular connectivity. While most of the existing GE methods aim at extracting node features, an impr
We consider a truss as a graph consisting of nodes and edges, and combine graph embedding (GE) and reinforcement learning (RL) to develop an agent for generating a stable assembly path for a truss with arbitrary configuration. GE is a method of embedding the features of a graph into a vector space. By using GE, the agent can obtain numerical information on neighboring members and nodes considering their connectivity. Since the stability of a structure is strongly affected by the relative positio
A method is presented for generating a discrete piecewise constant Gaussian curvature (CGC) surface. An energy functional is first formulated so that its stationary point is the linear Weingarten (LW) surface, which has a property such that the weighted sum of mean and Gaussian curvatures is constant. The CGC surface is obtained using the gradient derived from the first variation of a special type of the energy functional of the LW surface and updating the surface shape based on the Gaussian cur
Despite its unique deployment mechanisms known as a negative Poisson’s ratio, most existing studies on deployable auxetic structures have overlooked how to solve the dilemma between deployability and stability. In this study, we propose a method to improve both properties by introducing surface overlaying and joints with compliant mechanisms. We first derive open angles to achieve the target shape using conformal mapping. This derivation considers the combined effect of thickness and curvature,
Piecewise constant mean curvature (P-CMC) surfaces are generated using the mean curvature flow (MCF). As an extension of the known fact that a CMC surface is the stationary point of an energy functional, a P-CMC surface can be obtained as the stationary point of an energy functional of multiple patch surfaces and auxiliary surfaces between them. A new formulation is presented for the MCF as the negative gradient flow of the energy functional for multiple patch continuous surfaces, which are furt
To achieve object recognition, it is necessary to find the unique features of the objects to be recognized. Results in prior research suggest that methods that use multiple modalities information are effective to find the unique features. In this paper, the overview of the system that can extract the features of the objects to be recognized by integrating visual, tactile, and auditory information as multimodal sensor information with VRAE is shown. Furthermore, a discussion about changing the co
Local farmers in the Sahel have few choices for arresting soil fertility degradation due to subsistence livelihood for agriculture. However, there are some locally available materials which are not utilized for agricultural production. Through field survey on understanding local agricultural system, underutilized organic resources were identified and crops stumps and millet husk were tested for technology development. According to the obtained results through on-station experiment, crops stumps
Existing methods for form-finding prioritize discovering optimal shapes under design load conditions, often overlooking the designer’s shape preferences. To address this problem, this research relaxes the load condition and develops a user-friendly form-finding tool that encapsulates a new method for obtaining funicular surfaces that pass through user-prescribed points through load control. The method involves generating smooth load distributions via RBF interpolation of nodal loads, which are r
This study focuses on redevelopment promotion areas to shed light on how redevelopment is utilized across Japan and explores how functions are renewed in accordance with local characteristics. We classified 83 areas by type and found that redevelopment promotion has contributed to diverse development by setting aims in reference to the wide area. We point out the role redevelopment promotion has played and demonstrate the importance of “positioning in the higher plan,” ”the strengthening of regu
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