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Devon Beck

Publications and source records attributed to Devon Beck.

4 recordsLinked to original sources

Functionally Grading the Slicing Process by Compiling Design Intent into Slicer Projects

Functional gradients control part behavior by varying structure, material, or process conditions across an object. Yet functionally graded fabrication is usually framed as grading geometry or material distribution rather than the slicing and fabrication process itself. In material-extrusion printing, many functional effects arise from slicer-controlled mechanisms, including local toolpath planning, surface treatment, material assignment, color mixing, and printer state. Mainstream FFF slicers expose these mechanisms as settings, but users must manually reconstruct heterogeneous intent as assigned mesh regions. We present slicer project compilation, an automated workflow that lowers heterogeneous implicit designs into slicer-native .3MF projects containing sub-meshes, settings, recipes, and process-state assignments. The compiler partitions spatial attributes into finite regions, extracts aligned sub-meshes, and serializes them into the target slicer's project dialect while preserving native toolpath planning, preview, support generation, and printer profiles. We demonstrate the approach across three parameter classes: settings meshes, virtual extrusion, and color or material halftoning. We also introduce calibrated translation models for temperature-responsive foaming TPU and PLA, allowing high-level density and Shore-hardness fields to drive fabrication-ready process fields. Printed examples include graded toolpath settings, foaming-filament properties, combined texture and process-state control, and color or material-mixture halftoning, replacing more than 2,500 repetitive manual slicer interactions. Our open-source implementation connects heterogeneous design representations to existing slicer ecosystems and provides a reusable foundation for automated, scalable functionally graded FFF fabrication.

cs.GR

Design-Intent Compilation for Heterogeneous Fabrication

Computational fabrication workflows increasingly require designers to specify spatially varying behavior, appearance, material composition, and process state. Yet most workflows force these intentions into printer-specific representations, such as material fractions, voxel labels, mesh partitions, or slicer settings. This coupling makes heterogeneous designs difficult to reuse because each backend requires a different realization of the same property. We present a compiler architecture for heterogeneous fabrication that treats design as a staged, typed lowering problem. A source design consists of implicit geometry and named, typed spatial attribute fields over a shared object domain. These attributes may encode measured data, visual appearance, target mechanical behavior, material recipes, process parameters, or other user-specified attributes. Translation models derive compiler-required realization attributes from source or intent attributes, and backend compilers emit machine-facing outputs such as voxel material stacks, process G-code, or configured slicer project files. This separates source modeling, attribute translation, and backend compilation, allowing a design to remain expressed in fabrication-agnostic terms while each toolchain determines how intent becomes executable instructions. We validate the method through fabricated objects and measurements across sampled volumetric data, CT-derived visual and mechanical models, Shore-hardness fields, and full-color fields, implemented via material jetting and material extrusion. These results show that one source design can be lowered into distinct material, process, and slicer representations without rewriting it in printer-specific terms. We provide the representation, translation framework, compiler interface, and workflows as an open-source Python package to accelerate research in heterogeneous computational fabrication.

cs.GR

Implicit Modeling for 3D-printed Multi-material Computational Object Design via Python

This paper introduces open-source contributions designed to accelerate research in volumetric multi-material additive manufacturing and metamaterial design. We present a flexible Python-based API facilitating parametric expression of multi-material gradients, integration with external libraries, multi-material lattice structure design, and interoperability with finite element modeling. Novel implicit multi-material modeling techniques enable detailed spatial grading at multiple scales within lattice structures. Additionally, our framework integrates with finite element analysis, offering predictive simulations via adaptive mesh sizing and direct import of simulation results to guide material distributions. Practical case studies illustrate the utility of these contributions, including functionally graded lattices, algorithmically generated structures, and simulation-informed designs, exemplified by a multi-material bicycle seat optimized for mechanical performance and rider comfort. Finally, we introduce a mesh export strategy compatible with standard slicing software, significantly broadening the accessibility and adoption of functionality graded computational design methodologies for multi-material fabrication.

cs.GR

Implicit Toolpath Generation for Functionally Graded Additive Manufacturing via Gradient-Informed Slicing

This paper presents a novel gradient-informed slicing method for functionally graded additive manufacturing (FGM) that overcomes the limitations of conventional toolpath planning approaches, which struggle to produce truly continuous gradients. By integrating multi-material gradients into the toolpath generation process, our method enables the fabrication of FGMs with complex gradients that vary seamlessly in any direction. We leverage OpenVCAD's implicit representation of geometry and material fields to directly extract iso-contours, enabling accurate, controlled gradient toolpaths. Two novel strategies are introduced to integrate these gradients into the toolpath planning process. The first strategy maintains traditional perimeter, skin, and infill structures subdivided by mixture ratios, with automated 'zippering' to mitigate stress concentrations. The second strategy fills iso-contoured regions densely, printing directly against gradients to eliminate purging and reduce waste. Both strategies accommodate gradually changing printing parameters, such as mixed filament ratios, toolhead switching, and variable nozzle temperatures for foaming materials. This capability allows for controlled variation of composition, density, and other properties within a single build, expanding the design space for functionally graded parts. Experimental results demonstrate the fabrication of high-quality FGMs with complex, multi-axis gradients, highlighting the versatility of our method. We showcase the successful implementation of both strategies on a range of geometries and material combinations, demonstrating the potential of our approach to produce intricate and functional FGMs. This work provides a robust, open-source, and automated framework for designing and fabricating advanced FGMs, accelerating research in multi-material additive manufacturing.

cs.CG