Visualization of MBSE Datasets in an Interactive 3D Game Engine.
Abstract not provided.
Wilson, Kelsey↗
SEARCH · Engineering Papers
Results for “Interactive visualization”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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F-Hash: Feature-Based Hash Design for Time-Varying Volume Visualization via Multi-Resolution Tesseract Encoding
Interactive time-varying volume visualization is challenging due to its complex spatiotemporal features and sheer size of the dataset. Recent works transform the original discrete time-varying volumetric data into continuous Implicit Neural Representations (INR) to address the issues of compression, rendering, and super-resolution in both spatial and temporal domains. However, training the INR takes a long time to converge, especially when handling large-scale time-varying volumetric datasets. In this work, we proposed F-Hash, a novel feature-based multi-resolution Tesseract encoding architecture to greatly enhance the convergence speed compared with existing input encoding methods for modeling time-varying volumetric data. The proposed design incorporates multi-level collision-free hash functions that map dynamic 4D multi-resolution embedding grids without bucket waste, achieving high encoding capacity with compact encoding parameters. Our encoding method is agnostic to time-varying feature detection methods, making it a unified encoding solution for feature tracking and evolution visualization. Experiments show the F-Hash achieves state-of-the-art convergence speed in training various time-varying volumetric datasets for diverse features. We also proposed an adaptive ray marching algorithm to optimize the sample streaming for faster rendering of the time-varying neural representation.
deep learning↗
Structural basis of TFIIIC-dependent RNA polymerase III transcription initiation
RNA polymerase III (Pol III) is responsible for transcribing 5S ribosomal RNA (5S rRNA), tRNAs, and other short non-coding RNAs. Its recruitment to the 5S rRNA promoter requires transcription factors TFIIIA, TFIIIC, and TFIIIB. Here, we use cryoelectron microscopy (cryo-EM) to visualize the S. cerevisiae complex of TFIIIA and TFIIIC bound to the promoter. Gene-specific factor TFIIIA interacts with DNA and acts as an adaptor for TFIIIC-promoter interactions. We also visualize DNA binding of TFIIIB subunits, Brf1 and TBP (TATA-box binding protein), which results in the full-length 5S rRNA gene wrapping around the complex. Our smFRET study reveals that the DNA within the complex undergoes both sharp bending and partial dissociation on a slow timescale, consistent with the model predicted from our cryo-EM results. Our findings provide new insights into the transcription initiation complex assembly on the 5S rRNA promoter and allow us to directly compare Pol III and Pol II transcription adaptations.
59 BASIC BIOLOGICAL SCIENCES↗
Bent DNA Bows as Sensing Amplifiers for Detecting DNA-Interacting Salts and Molecules
Due to the central role of DNA, its interactions with inorganic salts and small organic molecules are important. For example, such interactions play important roles in various fundamental cellular processes in living systems and are involved in many DNA-damage related diseases. Strategies to improve the sensitivity of existing techniques for studying DNA interactions with other molecules would be appreciated in situations where the interactions are too weak. Here we report our development and demonstration of bent DNA bows for amplifying, sensing, and detecting the interactions of 14 inorganic salts and small organic molecules with DNA. With the bent DNA bows, these interactions were easily visualized and quantified in gel electrophoresis, which were difficult to measure without bending. In addition, the strength of the interactions of DNA with the various salts/molecules were quantified using the modified Hill equation. This work highlights the amplification effects of the bending elastic energy stored in the DNA bows and the potential use of the DNA bows for quantitatively measuring DNA interactions with small molecules as simple economic methods; it may also pave the way for exploiting the bent DNA bows for other applications such as screening DNA-interacting molecules and drugs.
59 BASIC BIOLOGICAL SCIENCES↗
Uncertainty Visualization for Renewable Energy Potential
In this paper, we present the reV (Renewable Energy Potential) Dashboard, an interactive browser-based tool for uncertainty visualization and data exploration built using customized plotly dash components. With continuing development and utilization of computational models to study the power sector there is an increasing need for data-driven visualization tools which allow scientists, researchers, and engineers to interact with their data in real-time. Our principle motivation for developing this interactive uncertainty visualization was to provide domain scientists and modelers a platform which allows them to better understand and communicate scientific findings stemming from intricate information encoded in their data that is otherwise difficult to capture by conventional analysis. The development of customized dashboard components using the React programming paradigm, combined with fully pre-processed data, allows for users to select a variety of data options to update and manipulate the visualization in a straightforward computationally efficient manner.
dashboard↗
Three-Dimensional Grid Visualization for Planning Activities: A Dubai Case Study
National Laboratory of the Rockies (NLR), in collaboration with the Dubai Electricity and Water Authority (DEWA) and Infra-X, has undertaken the Energy Visualization Analysis Project. The aim of this project is to enhance analytical and 3D visualization capabilities for distribution network planning and renewable energy integration. As modern grid continues to evolve with large-scale solar PV deployment and emerging distributed energy resources (DERs), the ability to effectively analyze, visualize, and communicate complex grid behaviors has become increasingly critical. The project focuses on developing empirical use cases based on real distribution feeder data and engineering workflows, ensuring the outcomes are directly aligned with operational environment. Through time-series power flow simulations and nodal hosting capacity analysis, the study quantifies the impacts of high PV penetration on voltage and thermal limits within representative 11 kV feeders. These analyses identify specific nodes and conditions where DER integration challenges arise. Furthermore, a Battery Energy Storage System (BESS) optimization algorithm was applied to determine the optimal size and placement of storage systems that can mitigate network constraints and enhance hosting capacity. The comparative results between base-case and BESS-augmented scenarios clearly demonstrate improvements in network stability and load management efficiency. In parallel, the NLR team developed an immersive 3D visualization framework, enabling interactive exploration of grid simulations using commodity head-mounted display (HMD) systems. This framework transforms conventional 2D simulation data into spatially intuitive visual environments - allowing engineers to analyze feeder conditions, PV hosting potential, and BESS effects in real time. This report represents the first foundational phase in establishing a visualization-driven analytical ecosystem. It provides a methodological foundation for data integration, visualization architecture, and simulation-based decision support, paving the way for large-scale adoption of immersive visualization across DEWA's Smart Grid Initiative, R&D activities, and future network resilience studies.
24 POWER TRANSMISSION AND DISTRIBUTION↗
IrrigationViz: A Geospatial Visualization Application to Facilitate Irrigation Modernization
Irrigation water delivery infrastructure, such as canals and pipelines, are essential to agriculture in the Western U.S., yet many of these systems are reaching the end of their useful lives. Reinvestment can achieve a wide variety of benefits, from water conservation to energy savings or renewable energy generation. Modernization requires significant planning, design, and implementation funding which can be a challenge for many irrigation districts. Here, this paper introduces IrrigationViz, a web-based mapping application designed to help irrigation districts visualize and generate high-level cost and benefit estimates for infrastructure modernization projects. These estimates can help water managers identify projects that benefit from additional engineering resources and ultimately obtain funding. IrrigationViz includes map interactions, graphs, and visualization components to facilitate planning and communication to stakeholders and funders. IrrigationViz combines user-provided information about a water-delivery system with public datasets and basic engineering formulas to generate estimates of the benefits of reinvestment. Estimates include the amount of water seepage in earthen canals, potential hydropower generation associated with replacing a canal with a pressurized pipe, and pipe size recommendations. We found that hydropower generation estimates compared favorably with real world projects, but seepage loss estimates showed high variability relative to on-the-ground measurements
99 - GENERAL AND MISCELLANEOUS↗
Visualizing the Hidden Half: Plant-Microbe Interactions in the Rhizosphere
Plant roots and the associated rhizosphere constitute a dynamic environment that fosters numerous intra- and interkingdom interactions, including metabolite exchange between plants and soil mediated by root exudates and the rhizosphere microbiome. These interactions affect plant fitness and performance, soil health, and the belowground carbon budget.
59 BASIC BIOLOGICAL SCIENCES↗
Resonant interaction between phonons and PbTe/PbSe (001) misfit dislocation networks
Here this work aims at a quantitative and mechanistic understanding of the dynamic process of the phonon-dislocation interaction in PbTe/PbSe (001) heterostructures using the Concurrent Atomistic-Continuum (CAC) method as the simulation tool. The misfit dislocation network and the atomic-scale dislocation core structure obtained in the simulations are found to agree reasonably well with the experimental observations of the PbTe/PbSe (001) interface. Through visualizing the dynamic interaction between phonons and dislocations, as well as quantifying the dislocation vibration amplitude, the phonon energy transmission, and the thermal resistance of the misfit interfaces, this work has illustrated and quantified two mechanisms for phonon-dislocation interaction: (1) phonon scattering by the strain field of dislocations, and (2) phonon scattering by dislocations that vibrate via the local modes of a dislocation network; the latter, leads to resonant phonon-dislocation interaction, which is manifested as local maxima of out-of-phase vibration of the atoms on the two sides of the slip plane, leading to local minima of the energy transmission in the heterostructure that contains one interface. The local vibrational modes are found to be excited only by shear stress induced by transverse phonons. Among various resonant modes, the one with the lowest frequency has the strongest effect. This work has also demonstrated the collective motion of dislocations under ultrafast phonon pulses. In addition, the dynamic properties of the misfit dislocation network localized within one interface are found to be significantly altered by the presence of misfit dislocations at other interfaces, thus further confirming the cooperative dynamic nature of the motion of dislocations and phonons.
36 MATERIALS SCIENCE↗
A centralized resource for bacterial–fungal interactions research
Research on bacterial-fungal interactions (BFIs) has revealed that fungi and bacteria frequently interact with one another within diverse ecosystems and microbiomes. Assessing the current state of knowledge within the field of BFI research, particularly with respect to what interactions between bacteria and fungi have been previously described, is very challenging and time consuming. This is largely due to a lack of any centralized resource, with reports of BFIs being spread across publications in numerous journals using non-standardized text to describe the relationships. To address this issue, we have developed the BFI Research Portal, a publicly accessible database of previously reported interactions between bacterial and fungal taxa to serve as a centralized resource for the field. Users can query bacterial or fungal taxa to see what members from the other kingdom have been observed as interaction partners. Search results are accompanied by interactive and intuitive visual outputs, and the database is a dynamic resource that will be updated as new BFIs are reported.
59 BASIC BIOLOGICAL SCIENCES↗
CCQE-like $\nu_{e}$ Selection in SBND using Convolutional Visual Network
Neutrinos from the Booster Neutrino Beam (BNB) at Fermilab interact with argon in a Liquid Argon Time Projection Chamber (LArTPC) differently based on their flavour. By examining the particles produced in a charged-current interaction, both the interaction type and the neutrino flavour can be inferred. The Short Baseline Near Detector has the largest neutrino-argon cross section data to date, motivating in-depth studies of various cross-section channels and topologies. This project aims to select electron neutrino quasi-elastic-like (QE-like) interactions in SBND using Convolutional Visual Network (CVN) scores. The CVN is a neural network that processes visual information from an event and assigns scores corresponding to its likelihood of being each interaction type. An inclusive study of electron neutrino charged current interactions using CVN has already been conducted. This analysis aims to build on this study, further utilizing CVN scores to isolate electron neutrino QE-like interactions characterized by the presence of an electron and one or more protons ($N > 0$) in the final state. The project s goal is to contribute to the overall cross-section measurement efforts within the SBN program at Fermilab.
Breen, Genevieve [Mt. Holyoke Coll.]↗
Approach to using 3D laser-induced breakdown spectroscopy (LIBS) data to explore the interaction of FLiNaK and FLiBe molten salts with nuclear-grade graphite
Nuclear graphite has historically been a key component of many nuclear reactor designs and has emerged as key to numerous advanced nuclear reactor design concepts. Molten salt reactors (MSRs) are one broad group of advanced reactor designs currently being pursued by industry for commercialization. Several MSR designs under consideration use graphitic materials that directly interface with a molten salt, whether it is a fuel salt, coolant salt, or both. Therefore, the interaction of graphite materials with molten salts must be understood. To gain this required understanding, a range of data is needed including porosity, strength, and composition as a function of different salt exposure parameters. In this study, a laser-induced breakdown spectroscopy (LIBS) measurement and data analysis methodology was developed to obtain spatially resolved elemental composition information for graphite samples exposed to a molten fluoride salt. Traditional univariate emission line analysis of atomic, ionic, and molecular optical emission signals was coupled via correlation analysis with spectral decomposition of the data using principal component analysis. Elemental depth profiling and elemental mapping were also performed to visualize salt–graphite interactions. LIBS was demonstrated to be useful for measuring key analytes such as fluorine and hydrogen, which are troublesome for other analysis techniques. Evidence for complex behavior was found, thereby demonstrating the usefulness of the developed approach for future systematic studies.
22 GENERAL STUDIES OF NUCLEAR REACTORS↗
ParFlow Sand Tank: A tool for groundwater exploration
The ParFlow Sand Tank model is an open source application designed to allow users to interactively simulate and visualize groundwater movement through the subsurface. The app is designed for both research and education; teaching hydrogeology concepts and making it easy explore and run sophisticated groundwater simulations. Our goal is to support increased accessibility and usability of research grade hydrology tools for research and teaching. The Sand Tank application simulates groundwater and surface water fluxes as well as contaminant transport in real time using the integrated physical hydrology model ParFlow (Kollet & Maxwell, 2006; Maxwell & Miller, 2005; Osei-Kuffuor et al., 2014) and the particle tracking code EcoSlim (Maxwell et al., 2019). ParFlow is a numerical hydrology model that simulates spatially distributed groundwater and surface water flow. It is a well established research tool with more than 90 publications documenting its development use to advance our understanding of groundwater dynamics and groundwater surface water interactions from the hillslope to the continental scale e.g. (Condon et al., 2020; Condon & Maxwell, 2019; Maxwell & Condon, 2016). It is designed for efficient parallel computation and has been run on many platforms spanning from laptops to supercomputers. However, one of the challenges of ParFlow is that it requires significant training and hydrologic expertise to develop simulations. The Sand Tank application makes this model accessible to anyone for education and exploration. Our application uses ParFlow for its simulation backend and ParaView for the data loading and processing. The communication infrastructure relies on the ParaViewWeb framework. We use model templates deployed in Docker images to setup the Sand Tank framework. Users can build the application locally or interact with it through our web deployment. When interacting with a template users can interactively change model parameters like subsurface processes or pump/inject water into the subsurface and watch the system respond to their changes in real time as the simulation runs. Additionally, our template setup will allow more advanced users to build custom templates of increasing complexity for both research and educational purposes.
54 ENVIRONMENTAL SCIENCES↗
EnergyPlus Model Context Protocol Server (EnergyPlus-MCP) v0.1
EnergyPlus-MCP is the first open-source Model Context Protocol server specifically designed for EnergyPlus building energy simulation. This innovative software enables AI assistants and other applications to interact programmatically with EnergyPlus through a standardized, secure interface, eliminating traditional technical barriers in building energy modeling. The software provides specialized tools across five functional domains: server management, model configuration and loading, comprehensive building component inspection, systematic model modification, and simulation execution with results visualization. Key features include automated HVAC system discovery and topology mapping, advanced schedule analysis, intelligent model validation, and interactive visualization capabilities. EnergyPlus-MCP's layered architecture ensures robust separation between protocol communication and domain expertise, enabling scalable deployment across organizations, educational institutions, and research teams. Unlike direct LLM approaches that suffer from inconsistent results and security gaps, EnergyPlus-MCP provides validated, reliable interactions while maintaining scientific rigor. This democratizes sophisticated building energy analysis, making EnergyPlus accessible to broader audiences through conversational interfaces and streamlined workflows.
Li, Han [Lawrence Berkeley National Laboratory (LB↗
Applications of physics informed neural operators
Abstract We present a critical analysis of physics-informed neural operators (PINOs) to solve partial differential equations (PDEs) that are ubiquitous in the study and modeling of physics phenomena using carefully curated datasets. Further, we provide a benchmarking suite which can be used to evaluate PINOs in solving such problems. We first demonstrate that our methods reproduce the accuracy and performance of other neural operators published elsewhere in the literature to learn the 1D wave equation and the 1D Burgers equation. Thereafter, we apply our PINOs to learn new types of equations, including the 2D Burgers equation in the scalar, inviscid and vector types. Finally, we show that our approach is also applicable to learn the physics of the 2D linear and nonlinear shallow water equations, which involve three coupled PDEs. We release our artificial intelligence surrogates and scientific software to produce initial data and boundary conditions to study a broad range of physically motivated scenarios. We provide the source code , an interactive website to visualize the predictions of our PINOs, and a tutorial for their use at the Data and Learning Hub for Science .
97 MATHEMATICS AND COMPUTING↗
Enabling Command-and-Control in Advanced In Situ Workflows
Scientific discovery is progressing towards autonomous science with the combination of scientific instruments, high-performance computing, and artificial intelligence in complex workflows. This evolution introduces new requirements for managing scientific workflows, including feedback loops, near real-time constraints, and the ability to dynamically control workflow execution. In situ workflows that analyze and visualize data as it is generated are well-suited to satisfy stringent time constraints and their iterative nature offers greater opportunities for command-and-control. However, only a few of the many workflow management systems available have been specifically designed to manage in situ workflows and often lack support for automated feedback loops that allow analysis and visualization components to interact with the main scientific data producer. To address this need, we present in this paper how to add command-and-control capabilities to a workflow management system. We identify the functional design requirements of such a command-and-control system, detail its architecture, interface, and core mechanisms, and illustrate how advanced in situ workflows can leverage command-and-control in three use cases: graceful termination with checkpoint, dynamic and adaptive data reduction, and event-triggered analysis.
Mehta, Kshitij [ORNL] (ORCID:0000000297149981)↗
Three-Dimensional Single-Molecule Localization Microscopy in Whole-Cell and Tissue Specimens
Super-resolution microscopy techniques are versatile and powerful tools for visualizing organelle structures, interactions, and protein functions in biomedical research. However, whole-cell and tissue specimens challenge the achievable resolution and depth of nanoscopy methods. We focus on three-dimensional single-molecule localization microscopy and review some of the major roadblocks and developing solutions to resolving thick volumes of cells and tissues at the nanoscale in three dimensions. These challenges include background fluorescence, system- and sample-induced aberrations, and information carried by photons, as well as drift correction, volume reconstruction, and photobleaching mitigation. We also highlight examples of innovations that have demonstrated significant breakthroughs in addressing the abovementioned challenges together with their core concepts as well as their trade-offs.
59 BASIC BIOLOGICAL SCIENCES↗
Toward Human-Centric Transportation and Energy Metrics: Influence of Mode, Vehicle Occupancy, Trip Distance, and Fuel Economy
Traditional metrics measuring transportation and energy outcomes can be augmented to better represent impacts on people's lives and systems-level performance. In this context, this study introduces two novel metrics: road capacity (as number of people traveling and accessing services) and energy intensity (as energy use for people traveling and accessing services). Current national-level distributions of available data in the United States for factors contributing to the two new integrated metrics are used as context to evaluate potential outcomes. These factors include vehicle occupancy, mode share, fuel economy, and trip distance. Variations in input values provide insights on how these factors shape efficiencies in road capacity and energy intensity. Parametric sensitivity analysis indicates that the impact of each input depends upon the metric being evaluated. For the human-centered road capacity mobility metric, increasing vehicle occupancy has the largest effect – twice that of increasing mode share for bike, walk, and transit. For the energy intensity mobility metric, the effect of improving fuel economy is the largest. However, when the focus is on accessibility (instead of mobility), for both metrics the effect of lowering average trip distance is the largest. Additionally, a novel interactive tool to visualize the results for various parameter combinations makes the metrics practitioner ready. The findings suggest that the diffusion of new human-centric metrics that benchmark outcomes associated with road capacity and energy may be significant in motivating new sustainable transportation investments and efficient utilization of infrastructure, mobility assets, and services.
ADVANCED PROPULSION SYSTEMS↗