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Genesis Mission Data cards

As data-intensive research and artificial intelligence become central to DOE mission science, the need for machine-actionable dataset documentation has grown accordingly. However, many DOE-aligned communities, including the Office of Science, NNSA, and cross-laboratory collaborations, have developed independent metadata practices. This fragmentation creates friction for discovery, federation, and reuse across programs. To address these challenges, this talk introduces the Genesis Data Card: a shared metadata artifact developed in collaboration with a broad DOE community (Jefferson Lab and the National Lab of the Rockies, Oak Ridge, Sandia, Idaho, Berkeley, and Los Alamos). The Genesis Data Card aims to standardize dataset documentation across DOE-aligned initiatives while remaining extensible to discipline-specific needs. This talk will describe the data card template and the supporting code to validate completed data cards, using a companion LinkML schema. I'll walk through the design decisions behind the template, its alignment with existing standards, its treatment of sensitivity and governance metadata, and the phased roadmap toward lifecycle-integrated "xCards" that support autonomous discovery and reuse. The talk closes with current gaps, ongoing work, and how others can contribute datasets and feedback to the shared repository.

McSpadden, Helen [Thomas Jefferson National Accele

Genesis Data Card Schema, Template and Supporting Tools

Genesis Data Cards provide a standardized template and schema for documenting scientific datasets in support of discovery, access, interoperability, reusability, governed use, and AI usability. This release of the Genesis Data Card repository includes a versioned Markdown template, a LinkML schema with generated Pydantic and JSON artifacts, schema documentation, and example completed data cards. Validation tooling is provided to ensure that completed data cards conform to the schema prior to submission. Accompanying documentation for the structured metadata is provided as a Field Reference Guide. The schema and accompanying template provided in this repository address the call for actionable context that enables humans and AI systems to find, access, interpret, cite, and reuse data, and, when appropriate, integrate it into AI and machine learning workflows. The data card is intended to serve as a common metadata artifact intended to support standardized, cross-program dataset documentation across Department of Energy (DOE)-aligned efforts, including but not limited to Genesis Mission-related implementations, the Office of Science, National Nuclear Security Administration (NNSA), and Advanced Simulation and Computing (ASC) data governance and stewardship initiatives.

data card

Data Cards for Standardized Metadata Across DOE-Aligned Data Initiatives: Toward Transparent, Interoperable, and Governed Dataset Documentation

As data-intensive research, advanced computing, and artificial intelligence become increasingly central to scientific and operational workflows, the need for consistent, transparent, and machine-actionable documentation has grown correspondingly. Multiple DOE-aligned communities—including Office of Science, Genesis Mission, American Science Cloud (AmSC), National Nuclear Security Administration (NNSA) stewardship and governance, and related cross-laboratory collaborations—have independently developed metadata practices to support discovery, access, reuse, repository deposit, and compliance.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION

Simulation-driven design optimization of reaction injection molding (RIM) process for polydicyclopentadiene (pDCPD): Minimizing cycle time, defects, and warpage

Replacing metal components in trucks, trailers, and buses with lightweight polymer composites is challenging due to high temperatures and complex manufacturing. The Reaction Injection Molding (RIM) process using Dicyclopentadiene (DCPD) resin offers a solution by producing robust parts with excellent stiffness, impact strength, and resistance properties. Simulations are essential for optimizing this process, predicting defects, and improving quality. However, most commercial software is tailored for thermoplastics, requiring thermoset users to generate their own datasets. In this study, a material data card for DCPD was developed to perform RIM simulations. Design of Experiments (DOE) was used to identify key factors affecting filling, curing, and warpage, aiming to minimize cycle time and defects. The simulations explored varying injection gate parameters (size, location, number) and process conditions (mold/resin temperature, injection/curing pressure). Results showed that gate design significantly impacts filling behavior and defects. A single central gate provided balanced flow with fewer defects, while two corner gates led to more defects. Additionally, lower injection pressure increased filling time, while higher mold temperature accelerated curing but led to more warpage. In conclusion, this optimization framework aims to enhance DCPD part performance and promote sustainable manufacturing by reducing waste and energy consumption.

42 ENGINEERING

Enabling Next Generation Reaction Injection Molding (RIM) for Lightweight Structures

Replacing metal components in trucks, trailers, and buses with lightweight polymer composites is challenging due to high temperatures and complex manufacturing. The Reaction Injection Molding (RIM) process using Dicyclopentadiene (DCPD) resin offers a solution by producing robust parts with excellent stiffness, impact strength, and resistance properties. Simulations are essential for optimizing this process, predicting defects, and improving quality. However, most commercial software is tailored for thermoplastics, requiring thermoset users to generate their own datasets. In this project, a material data card for DCPD was developed to perform RIM simulations. Design of Experiments (DOE) was used to identify key factors affecting filling, curing, and warpage, aiming to minimize cycle time and defects. The simulations explored varying injection gate parameters (size, location, number) and process conditions (mold/resin temperature, injection/curing pressure). Results showed that gate design significantly impacts filling behavior and defects. A single central gate provided balanced flow with fewer defects, while two corner gates led to more defects. Additionally, lower injection pressure increased filling time, while higher mold temperature accelerated curing but led to more warpage. This optimization framework aims to enhance DCPD part performance and promote sustainable manufacturing by reducing waste and energy consumption. This research has been performed in collaborations with McClarin Composites. The research outcome has been submitted to the Journal of Manufacturing Processes.

36 MATERIALS SCIENCE

House Advantage or House of Cards? Stacking the Deck for Data Videos Leads to Null Results: Preprint

Videos are becoming a ubiquitous means of sharing information on social media platforms. In response, data videos - short clips combining visualization with dynamic storytelling, audio descriptions, and spatial referencing - have gained popularity for communicating data. These affordances suggest that data videos might communicate data patterns, trends, and concepts more effectively than static visualizations, enhancing comprehension. However, existing research has not systematically tested this claim. To address this gap, we conducted three controlled studies to measure comprehension differences between data videos and static visualizations. Despite leveraging visual cues and audio explanations, no data video led to significantly better comprehension than an analogous static visualization. Our results suggest data videos are not categorically better and that future research should examine the tradeoffs between their engagement benefits and costs.

97 MATHEMATICS AND COMPUTING

Evaluating Energy Savings Measures for Building Retrofits in an Interactive Workshop Environment

As part of the Better Buildings Summit 2025, a workshop was developed to simulate the decision process for implementing a set of energy savings measures on an existing building. As part of the workshop a "game" was created around energy savings strategies, and workshop participants selected renovation cards that provided data around the impacts of that renovation choice. Participants then were able to calculate overall savings and payback from the selected retrofit opportunities. This publication has been produced to package the resources used in the activity in an organized document so that the materials can be distributed and reused more broadly. It provides a comprehensive framework for replicating the workshop, including step-by-step instructions, retrofit "game cards" with data points, and facilitation guidance. By using these materials, readers can conduct their own version of this interactive workshop with stakeholders in their networks, such as building owners, energy managers, or policy makers. The goal is to empower users to simulate the decision-making processes for energy projects, foster collaboration, and drive meaningful discussions around cost-effective retrofit opportunities and goal-oriented outcomes.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI

Shape-shifting Elephants: Multi-modal Transport for Integrated Research Infrastructure

Data Acquisition (DAQ) workloads form an important class of scientific network traffic that by its nature (1) flows across different research infrastructure, including remote instruments and supercomputer clusters, (2) has ever-increasing throughput demands, and (3) has ever-increasing integration demands---for example, observations at one instrument could trigger a reconfiguration of another instrument. Today's DAQ transfers rely on UDP and (heavily tuned) TCP, but this is driven by convenience rather than suitability. The mismatch between Internet transport protocols and scientific workloads becomes more stark with the steady increase in link capacities, data generation, and integration across research infrastructure.This position paper argues the importance of developing specialized transport protocols for DAQ workloads. It proposes a new transport feature for this kind of elephant flow: multi-modality involves the network actively configuring the transport protocol to change how DAQ flows are processed across different underlying networks that connect scientific research infrastructure. Multi-modality is a layering violation that is proposed as a pragmatic technique for DAQ transport protocol design. It takes advantage of programmable network hardware that is increasingly being deployed in scientific research infrastructure. The paper presents an initial evaluation through a pilot study that includes a Tofino2 switch and Alveo FPGA cards, and using data from a particle detector.

97 MATHEMATICS AND COMPUTING

LLUDA (Low-cost Logging for Ubiquitous Decarbonization and Analysis) [SWR-24-131]

This repository features an Arduino-based GPS logger, called LLUDA, which uses the Adafruit Ultimate GPS FeatherWing with the Adafruit Feather M0 Adalogger, designed to capture and log GPS data in CSV format onto an SD card (embedded inside the Feather M0 Adalogger). The FeatherWing is powered through the vehicle's auxiliary power (from cigarette lighter) socket via a micro USB cable. The data it collects can be used to analyze vehicle operations and support vehicle modeling applications, helping to assess the potential for electrification.

Fakhimi, Setayesh [National Renewable Energy Labor

Transit Rider/Travel Behavior Inventory Survey - Minneapolis-St. Paul Metro - 1990

The 1990 transit on-board survey aimed to update the 1988 survey, which was conducted as part of the Preliminary Engineering Study for the Hennepin County Light Rail Transit System. The 1988 study received Regional Transit Board funding, and survey results could be applied to a mode split model for projecting ridership on the proposed Light Rail Transit System. However, this survey was designed with the 1990 Travel Behavior Inventory in mind. The intention had been to update the 1988 survey in 1990 to be compatible with the 1990 Travel Behavior Inventory data. The results of the 1990 survey were used primarily to create a table of observed transit trips between each of the 1,200 traffic analysis zones in the region. This trip table was used to calibrate a new mode split model, which estimated future year travel by mode. The 1990 update survey focused on new routes and routes that had changed significantly since 1988. To preserve compatibility with the 1988 survey, the same survey questionnaire card was used, together with the same survey procedures for data collection. The procedures randomly sampled bus patrons during the transit trip, asking key questions about the patron and the transit trip. The survey card was intended for patrons to fill out quickly so it could be completed during the transit trip. The questions focused on conditions that have proven over time to significantly influence ridership. In all, a total of 20,126 valid survey records were processed. Adding surrogate trips, the survey data file is composed of a total of 27,159 trip records . About 10% of the records were filled out by persons who had answered more than one questionnaire.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI

The ladder and readout cables of intermediate silicon strip detector for sPHENIX

A new silicon-strip-type detector was developed for precise charged-particle tracking in the central rapidity region of heavy ion collisions. A new detector and collaboration at the Relativistic Heavy Ion Collider at Brookhaven National Laboratory is sPHENIX, which is a major upgrade of the PHENIX detector. The intermediate tracker (INTT) is part of the advanced tracking system of the sPHENIX detector complex together with a CMOS monolithic-active-pixel-sensor based silicon-pixel vertex detector, a time-projection chamber, and a micromegas-based detector. The INTT detector is barrel shaped and comprises 56 silicon ladders. Two different types of strip sensors of 78 micron pitch and 320 micron thick are mounted on each half of a silicon ladder. Each strip sensor is segmented into 8 × 2 and 5 × 2 blocks with lengths of 16 and 20 mm. Strips are read out with a silicon strip-readout (FPHX) chip. In order to transmit massive data from the FPHX to the down stream readout electronics card (ROC), a series of long and high speed readout cables were developed. This document focuses on the silicon ladder, the readout cables, and the ROC of the INTT. The radiation hardness is studied for some parts of the INTT devices in the last part of this document, since the INTT employed some materials from the technology frontier of the industry whose radiation hardness is not necessarily well known.

43 PARTICLE ACCELERATORS

HEPTAPOD: Orchestrating High Energy Physics Workflows Towards Autonomous Agency

Many workflows in high-energy-physics (HEP) stand to benefit from recent advances in transformer-based large language models (LLMs). While early applications of LLMs focused on text generation and code completion, modern LLMs now support orchestrated agency: the coordinated execution of complex, multi-step tasks through tool use, structured context, and iterative reasoning. We introduce the HEP Toolkit for Agentic Planning, Orchestration, and Deployment (HEPTAPOD), an orchestration framework designed to bring this emerging paradigm to HEP pipelines. The framework enables LLMs to interface with domain-specific tools, construct and manage simulation workflows, and assist in common utility and data analysis tasks through schema-validated operations and run-card-driven configuration. To demonstrate these capabilities, we consider a representative Beyond the Standard Model (BSM) Monte Carlo validation pipeline that spans model generation, event simulation, and downstream analysis within a unified, reproducible workflow. HEPTAPOD provides a structured and auditable layer between human researchers, LLMs, and computational infrastructure, establishing a foundation for transparent, human-in-the-loop systems.

Menzo, Tony [Alabama U.; Fermilab] (ORCID:00000002

An FPGA-based hardware accelerator supporting sensitive sequence homology filtering with profile hidden Markov models

Abstract Background Sequence alignment lies at the heart of genome sequence annotation. While the BLAST suite of alignment tools has long held an important role in alignment-based sequence database search, greater sensitivity is achieved through the use of profile hidden Markov models (pHMMs). Here, we describe an FPGA hardware accelerator, called HAVAC, that targets a key bottleneck step (SSV) in the analysis pipeline of the popular pHMM alignment tool, HMMER. Results The HAVAC kernel calculates the SSV matrix at 1739 GCUPS on a $$\sim$$ ∼ $3000 Xilinx Alveo U50 FPGA accelerator card, $$\sim$$ ∼ 227× faster than the optimized SSV implementation in nhmmer . Accounting for PCI-e data transfer data processing, HAVAC is 65× faster than nhmmer’s SSV with one thread and 35× faster than nhmmer with four threads, and uses $$\sim$$ ∼ 31% the energy of a traditional high end Intel CPU. Conclusions HAVAC demonstrates the potential offered by FPGA hardware accelerators to produce dramatic speed gains in sequence annotation and related bioinformatics applications. Because these computations are performed on a co-processor, the host CPU remains free to simultaneously compute other aspects of the analysis pipeline.

59 BASIC BIOLOGICAL SCIENCES

MontePy: a Python library for reading, editing, and writing MCNP input files.

The Monte Carlo N-Particle (MCNP) radiation transport code is a highly capable and accurate code with a long legacy. MCNP uses the Monte Carlo simulation process to simulate the path of particles (e.g., neutrons, photons, charged particles, etc.), and their interaction with materials. It is widely used in nuclear engineering, high-energy physics, and other fields. Its origins in the mid-twentieth century predate many modern software conventions. MCNP users provide an input file to MCNP, which it then uses to create an internal representation of the simulation problem. These input files originally had to be stored as punchcard decks, and the user manual still uses the terminology of cards and decks, despite moving beyond punchcards. MCNP predates nearly all modern human readable markup or data serialization languages, such as the extensible Markup Language (XML), the Standard Generalized Markup Language (SGML), YAML (YAML Ain’t Markup Language), and Javascript Object Notation (JSON). Due to this, MCNP uses an entirely custom defined syntax language for its input, making off-the-shelf libraries for XML, YAML, and JSON impossible to use for scripting various operations on MCNP input files (Kulesza et al., 2022).

97 - MATHEMATICS AND COMPUTING

Captan+X Data Converter Integration

Fermi National Accelerator Laboratory's CAPTAN (Compact And Programmable daTa Acquisition Node) series provides a flexible hardware platform for data acquisition across a range of experiments and facilities. The latest iteration, CAPTAN+X, is built around a Kintex-7 FPGA supporting four FPGA Mezzanine Card (FMC) connections. As part of a broader laboratory effort to bring facility systems under a Model-Based Systems Engineering (MBSE) framework, CAPTAN+X is one of several systems slated to be incorporated into this modeling environment in the near term. A necessary step toward that goal is incorporating the platform's core functionality, which centers on integration with the LXD31K4 FMC, a data converter module combining dual AD9652 analog-to-digital converters and dual AD9142A digital-to-analog converters. Achieving compatibility required resolving pin-mapping conflicts between the LXD31K4's High Pin Count connector and the CAPTAN+X's available pin types, adapting a Board Support Project originally written for an UltraScale-class evaluation board to the Kintex-7 architecture, replacing incompatible primitives, restructuring clock distribution, and manually configuring chip initialization in place of an unsupported soft-processor-based approach. Functional verification of the ADC and DAC channels, followed by closed-loop testing combining both converters with real-time filtering, confirmed correct operation of the integrated system. These results establish a working hardware and firmware baseline for the CAPTAN+X platform, positioning it for future inclusion in the laboratory's growing MBSE modeling effort.

Espinoza, David [Illinois U., Urbana (main)]

CAPTAN+X Data Converter Integration

Fermi National Accelerator Laboratory's CAPTAN (Compact And Programmable daTa Acquisition Node) series provides a flexible hardware platform for data acquisition across a range of experiments and facilities. The latest iteration, CAPTAN+X, is built around a Kintex-7 FPGA supporting four FPGA Mezzanine Card (FMC) connections. As part of a broader laboratory effort to bring facility systems under a Model-Based Systems Engineering (MBSE) framework, CAPTAN+X is one of several systems slated to be incorporated into this modeling environment in the near term. A necessary step toward that goal is incorporating the platform's core functionality, which centers on integration with the LXD31K4 FMC, a data converter module combining dual AD9652 analog-to-digital converters and dual AD9142A digital-to-analog converters. Achieving compatibility required resolving pin-mapping conflicts between the LXD31K4's High Pin Count connector and the CAPTAN+X's available pin types, adapting a Board Support Project originally written for an UltraScale-class evaluation board to the Kintex-7 architecture, replacing incompatible primitives, restructuring clock distribution, and manually configuring chip initialization in place of an unsupported soft-processor-based approach. Functional verification of the ADC and DAC channels, followed by closed-loop testing combining both converters with real-time filtering, confirmed correct operation of the integrated system. These results establish a working hardware and firmware baseline for the CAPTAN+X platform, positioning it for future inclusion in the laboratory's growing MBSE modeling effort.

Espinoza, David [Illinois U., Urbana (main)]

Model Card for WaveDenoiser

This study used STEAD to train and evaluate this model because STEAD is among the best benchmark datasets available for local to regional data. STEAD is a global dataset with over 1 million 60 s long seismic waveforms that originated from approximately 450,000 earthquakes and background noise captured by more than 2,500 seismic stations. Each waveform in STEAD was attached with metadata such as earthquake locations, station locations, and signal arrival times when available

58 GEOSCIENCES

Travelling wave‐based fault detection and location in a real low‐voltage DC microgrid

Abstract This paper discusses a device‐level implementation of a travelling wave (TW) protection device (PD) designed for a real low‐voltage DC microgrid. The TWPD fault detection and location algorithm is executed on a commercial digital signal processor (DSP) board, involving signal sampling at 1 MHz via the DSP board's analog‐to‐digital converter (ADC). The analogue input card measures positive pole, negative pole and pole‐to‐pole voltages at the TWPD location. Upon a successful fault detection using a second‐order high‐pass filter, the voltage data is normalised and multi‐resolution analysis (MRA) is performed on a 128‐sample buffer around the TW arrival time. MRA employs the discrete wavelet transform (DWT) to capture high‐frequency voltage patterns, and then the Parseval's energy theorem quantifies these TW characteristics by computing the energy of reconstructed wavelet coefficients. These energy values per decomposed frequency band are the basis for training a random forest classifier that predicts fault location and type. The TWPD is fully implemented and connected to a real DC microgrid in Albuquerque, NM, USA, for validation, and results are shown for field tests verifying the performance under faults.

Paruthiyil, Sajay Krishnan [Department of Electric