Jul 2026· Journal of Visualized Experiments· Vol 233· 0 citations
Medicine
TL;DR
This protocol demonstrates the deployment and use of a locally containerized workflow system that supports the findable, accessible, interoperable, reusable (FAIR) data principles and supports Scalability to high-performance computing (HPC) or cloud resources via Galaxy's Pulsar system.
Abstract
In many virtual experiments, multiple software packages are used with varied simulation types, pre- and post-processing tools, and tools to visualize the experiments' results-often a combination of all. The typical method of integrating these is a manual one, with bespoke solutions created for each application area, which scales poorly and impedes sharing and reproducibility. This protocol demonstrates the deployment and use of a locally containerized workflow system. Following it, users will launch a local Galaxy instance using Docker, create and run an OpenMC neutronics simulation workflow, pass the outputs through a chain of format-conversion tools, and load the results into both ParaView and NVIDIA Omniverse for visualization. The containerized deployment promotes reproducibility and portability on any machine meeting the hardware requirements described in Section 1. Once the system is running, workflows can be re-run against new inputs without manual reconfiguration, additional simulation codes can be wrapped as new tools with modest effort, and tools can be used in multiple workflows and application areas. The approach supports the findable, accessible, interoperable, reusable (FAIR) data principles: run histories capture full provenance metadata, workflows are exportable as portable files and can be shared directly between Galaxy instances, and tools are packaged in version-controlled containers that can be published in a public repository. Scalability to high-performance computing (HPC) or cloud resources via Galaxy's Pulsar system is a natural extension of the architecture described here. The method is demonstrated through a fusion neutronics case study. OpenMC is used to simulate neutron transport in a Direct Accelerated Geometry Monte Carlo (DAGMC) computer-aided design (CAD) geometry, producing a tritium breeding ratio (TBR) result and a neutron-track dataset. The simulation workflows are then connected to the NVIDIA Omniverse as the metaverse platform for invocation and visualization.
Our team has been simulating 3-D flows in stars using the PPM gas dynamics codes for many years. In the early years, we built highly specialized systems and software to post-process data well after a simulation was completed. Recently, we have moved our visualization and data analysis software to generic, highly cost-effective systems and have moved the human interface to Web browsers. The Web server must still offer fast access to the simulation data, perhaps even while the simulation is running, but the user and a laptop can be located anywhere with wifi. The benefit is fully interactive access to the data with an ability to visualize or plot nearly any desired quantity in any desired fashion at a moment's notice. We have exploited this new capability by integrating it with a browser-driven ability to launch new simulation runs to enable scientific discovery through simulation in homework assignments for a course in stellar structure and evolution at the University of Minnesota.
T. Wetherbee, T. Ruwart, P. Woodward et al.· Practice and Experience in A...· 0 citations
Open standards for representing and exchanging interactive 3D scenes and data is a critical capability needed to publish visualization and graphics to the web. X3D, the successor to VRML, is a leading provider of such capabilities, enabling integration with web services, supporting cross-platform execution, and facilitating inter-application data exchange. Building on the capabilities of X3D and other open data standards, the addition of cross-platform, shareable execution modules implemented via generalized programming languages provides additional powerful web deployment capabilities. To this end, we have developed execution models based on the emerging open standards WebAssembly (WASM) and WebGPU. WASM transforms complex code, in our case C++, into portable, secure, and performant modules supported by web browsers; while WebGPU enables cross-platform graphics and processing capabilities. In this paper we describe how we use WASM and WebGPU to build cross-platform web applications using the C++ VTK toolkit as the underlying graphics and visualization engine.
Sankhesh Jhaveri, S. Jourdain, Jaswant Panchumarti et al.· IEEE Computer Graphics and A...· 0 citations
Parametric computer-aided design (CAD) modeling is difficult to evaluate with a single metric. Existing CAD benchmarks often emphasize synthetic or CAD-native settings, limited input modalities, or executability and IoUs alone. We introduce RealCADBench, a benchmark for intent-to-program CAD modeling from real industrial design intents. It contains 12,632 tasks from 19 factory-automation categories and spans text descriptions, 2D engineering drawings, real product pictures, and rendered images for both Part and Assembly modeling. We report results on a 1,770-task evaluation slice: 1,745 Part tasks across four input regimes and RCB-Assm25, a 25-task assembly study used in every reported assembly comparison. Each method generates FreeCAD API Python, which a shared runtime executes to export the 3D model. We evaluate the exported model using executability, Solid IoU, Surface IoU, and a rubric-based visual-semantic identity Judge. Among the nine standalone frontier large models evaluated, no model leads all four metrics. Across six frontier-scale large models, executability ranges from 0.565 to 0.812, Solid IoU from 0.2841 to 0.5379, and Surface IoU from 0.112 to 0.217 across the four Part regimes. The highest regime-balanced composite comes from a different model than the leaders on the four component metrics. On RCB-Assm25, Codex with GPT-5.5 improves executability and both IoU metrics over standalone GPT-5.5, but lowers the Judge score by 6.98 percentage points, leaving GPT-5.5 as the Judge leader. We also observe recurring failure modes, most notably missing fine structures, loss of part identity, and incorrect assembly placement. These results show that execution alone is insufficient to characterize realistic CAD modeling and that frontier models and agents differ substantially across executability, IoUs, and visual-semantic identity.
JoyIndustrial VisCAD Team Linxin Cai, Qiu-He Hong, Zhi-Chao Huang et al.· 0 citations
AlgoPlasma is an open-source library in which core numerical algorithms for plasma modeling are implemented as modular, well-documented, and independently testable components. Rather than offering a complete simulation code, it allows researchers to select, adapt, and assemble the required components into application-specific workflows. The current release is centered on particle-based simulation, while AlgoPlasma is designed to encompass a broader range of approaches to plasma modeling. It provides components for particle initialization and advancement, particle--grid coupling, field solution, collision modeling, parallel data exchange, input/output, and selected fluid updates. Documentation links mathematical formulations to source implementations, interfaces, and usage, while verification and validation cases evaluate numerical accuracy and physical behavior. AlgoPlasma thus establishes a shared algorithmic foundation for plasma modeling, transforming repeatedly reimplemented numerical methods into open, reusable, tested, and explainable components for research, verification, education, and collaborative development.
Yinjian Zhao, Zhongping Zhao, Zhe Liu et al.· 0 citations
As 3D software proliferates, software artifacts now extend beyond code and 2D user interfaces to include 3D assets. Among these assets, collision meshes are critical as they define the geometry used by physics engines for collision detection and physical interaction. Although existing tools can automatically generate collision meshes from visual meshes, they often fail to capture the intended interaction behavior. As a result, developers need to manually edit many heterogeneous collision meshes, a process that is time-consuming and challenging to scale. To address this problem, we present a neuro-symbolic program synthesis approach for batch-editing collision meshes. We formulate the task as a programming-by-example problem: given a family of collision meshes with the same editing intent and a small number of user demonstrations, our approach synthesizes a reusable program that captures the editing intent and applies it to non-demonstration meshes. We implement this in a tool named MeshForge, and evaluate it across 24 tasks on 600 collision meshes. MeshForge successfully synthesizes 23/24 tasks, requiring 2.2 demonstrations and 3.5 seconds of synthesis time on average.
Data validation in ETL workflows is most often performed after transformation, even though many data quality issues originate earlier in the pipeline. In practice, this means that errors are detected late, when tracing their source and applying corrections already requires additional effort. In this work, we explore whether virtual reality (VR) could be used as an alternative interface for addressing this problem earlier, at the stage of raw data inspection. We present VR-ETL, a proof-of-concept system that allows users to inspect and correct tabular data before transformation by interacting with it inside an immersive 3D environment. The system imports CSV datasets and applies a set of rule-based validation checks targeting common data quality problems, such as missing values, format inconsistencies, and basic referential integrity violations. Detected issues are visualized directly within the 3D representation of the data, using color-coded cells and simple spatial summaries that reflect error distribution across columns and records. A functional prototype was implemented using Unity and OpenXR and tested on structured datasets containing up to 10,000 records. During controlled technical testing, the system supported automated validation, real-time visual feedback, and immediate re-validation after user corrections, while maintaining performance suitable for immersive use on consumer-grade hardware. All intentionally seeded rule-based errors were detected. Although usability and workflow efficiency were not evaluated in this study, the prototype demonstrates that pre-transformation data validation in VR is technically feasible and provides a concrete starting point for future empirical investigations.
Unknown authors· Computer Science and Informa...· 0 citations
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