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At least 577 records · Page 32

Enhancing Operational Safety via Agentic Dialogue Hazard Identification Analysis

Operational safety in high-stakes domains such as industrial process control, autonomous, and safety-critical systems demand reliable hazard identification. While large language models (LLMs) have shown promise in automating safety analysis tasks, single-turn, monolithic inference is brittle: it lacks the self-correction, deliberation, and contextual refinement that safety engineers apply iteratively. In this paper, we introduce HAZDIAL, a framework that investigates whether structured agentic dialogue (multi-agent, multi-turn interactions) improves the quality of NLP-based hazard identification over single-pass baselines. We systematically compare two dialogue modalities: adversarial debate and constructive discussion, and propose an genetic algorithm-based agentic interaction optimization. We evaluate all configurations against a curated golden dataset using standard classification metrics (accuracy, precision, recall, F1) and a novel dialogue metrics. This work advances the intersection of dialogue systems, multi-agent reasoning, and AI safety, providing empirical evidence for dialogue-driven hazard analysis.

Das, Sanjay [ORNL] (ORCID:0009000542591915)↗

Development of a scintillator based fast-ion loss detector for the Wendelstein 7-X stellarator

A new scintillator based fast-ion loss detector (FILD) system has been designed for the Wendelstein 7-X (W7-X) stellarator. The mechanical design of the system is presented here along with engineering analyses of the system. This includes an assessment of the structural loads which also considers electromagnetic forces calculated for possible disruption scenarios as well as a mode frequency analysis of the system. Furthermore, an analysis of the thermal characteristics of the actively cooled probe head under prescribed steady state and transient heat loads is presented. Finally, the optical relay system is described and its properties used to forward model synthetic camera signals using the FILDSIM code and based on theoretical fast-ion losses incident on the probe head calculated using the ASCOT5 code.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Applications of the Dulmage–Mendelsohn decomposition for debugging nonlinear optimization problems

Nonlinear modeling and optimization is a valuable tool for aiding decisions by engineering practitioners, but programming an optimization problem based on a complex electrical, mechanical, or chemical process is a time-consuming and error-prone activity. Therefore, there is a need for model analysis and debugging tools that can detect and diagnose modeling errors. One such tool is the Dulmage–Mendelsohn decomposition, which identifies structurally under- and over-determined subsets in systems of equations and variables by partitioning the bipartite graph of the system. This work provides the necessary background to understand the Dulmage–Mendelsohn decomposition and its application to the analysis of nonlinear optimization problems, demonstrates its use in diagnosing a variety of modeling errors, and introduces software implementations for analyzing nonlinear optimization problems in the Pyomo and JuMP algebraic modeling languages.

42 ENGINEERING↗

Cycloidal Shaping of Polyhedra in Two-Rotor Systems

A method of solution is proposed for the model of the cycloid shaping of polyhedra. The method is based on reducing the equations to algebraic form by polynomial approximation of transcendental functions.

42 ENGINEERING↗

SetGo: Metadata Readiness for Scientific AI Datasets

Scientific datasets intended for AI use require both computational readiness for model training and metadata readiness for discovery, sharing, and reuse. The Readiness Engine for Data Integration (REDI) addresses computational readiness, but no corresponding tool evaluates whether a dataset’s metadata are sufficiently complete, governed, and standards-compliant for publication and agent-based consumption. Existing FAIR assessors operate only on published repository records, and no single system covers FAIR compliance, licensing, provenance, governance, reproducibility, and catalog readiness together. We present SetGo, an open-source Python toolkit that assesses and repairs metadata readiness across these six dimensions before a dataset is published or archived. Applied to four scientific corpora, SetGo surfaces deficiencies that general-purpose tools do not detect: ERA5 climate metadata scores 4% on ACDD 1.3 compliance; materials datasets fail OPTIMADE species-definition requirements; and PDB-derived proteomics data carries licensing terms incompatible with standard SPDX identifiers. Guided enrichment raises overall FAIR scores from 52–57% to 81–91%, and a single setgo publish command pushes to Hugging Face Hub, CKAN, or OpenMetadata with ML Commons Croissant 1.0 metadata sidecars. To support interactive and automated workflows, SetGo integrates with coding agents powered by large language models (LLMs) through a /setgo skill that enables natural-language execution of the full assess–enrich–publish loop, with user involvement limited to supplying missing metadata values.

Wilkinson, Sean [ORNL] (ORCID:0000000214437479)↗

Modeling Heat Transfer and Pressurization of Polymeric Methylene Diisocyanate (PMDI) Polyurethane Foam in a Sealed Container

Polymer foam encapsulants provide mechanical, electrical, and thermal isolation in engineered systems. It can be advantageous to surround objects of interest, such as electronics, with foams in a hermetically sealed container to protect the electronics from hostile environments, such as a crash that produces a fire. However, in fire environments, gas pressure from thermal decomposition of foams can cause mechanical failure of the sealed system. In this work, a detailed study of thermally decomposing polymeric methylene diisocyanate (PMDI)-polyether-polyol based polyurethane foam in a sealed container is presented. Both experimental and computational work is discussed. Three models of increasing physics fidelity are presented: No Flow, Porous Media, and Porous Media with VLE. Each model us described in detail, compared to experiment, and uncertainty quantification is performed. While the Porous Media with VLE model matches has the best agreement with experiment, it also requires the most computational resources.

36 MATERIALS SCIENCE↗

Edible oil structures at low and intermediate concentrations. II. Ultra-small angle X-ray scattering of in situ tristearin solids in triolein

Ultra-small angle X-ray scattering has been used for the first time to elucidate, in situ, the aggregation structure of a model edible oil system. The three-dimensional nano- to micro-structure of tristearin solid particles in triolein solvent was investigated using 5, 10, 15, and 20% solids. Three different sample preparation procedures were investigated: two slow cooling rates of 0.5°/min, case 1 (22 days of storage at room temperature) and case 2 (no storage), and one fast cooling of 30°/min, case 3 (no storage). The length scale investigated, by using the Bonse-Hart camera at beamline ID-15D at the Advanced Photon Source, Argonne National Laboratory, covered the range from 300 Å to 10 μm. The unified fit and the Guinier-Porod models in the Irena software were used to fit the data. The former was used to fit 3 structural levels. Level 1 structures showed that the primary scatterers were essentially 2-dimensional objects for the three cases. The scatterers possessed lateral dimensions between 1000 and 4300 Å. This is consistent with the sizes of crystalline nanoplatelets present which were observed using cryo-TEM. Level 2 structures were aggregates possessing radii of gyration, R{sub g2} between 1800 Å and 12000 Å and fractal dimensions of either D{sub 2}=1 for case 3 or 1.8≤D{sub 2}≤2.1 for case 1 and case 2. D{sub 2} = 1 is consistent with unaggregated 1-dimensional objects. 1.8 ≤ D{sub 2} ≤ 2.1 is consistent with these 1-dimensional objects (below) forming structures characteristic of diffusion or reaction limited cluster-cluster aggregation. Level 3 structures showed that the spatial distribution of the level 2 structures was uniform, on the average, for case 1, with fractal dimension D{sub 3}≈3 while for case 2 and case 3 the fractal dimension was D{sub 3}≈2.2, which suggested that the large-scale distribution had not come to equilibrium. The Guinier-Porod model showed that the structures giving rise to the aggregates with a fractal dimension given by D{sub 2} in the unified fit level 2 model were cylinders described by the parameter s≈1 in the Guinier-Porod model. The size of the base of these cylinders was in agreement with the cryo-TEM observations as well as with the results of the level 1 unified fit model. By estimating the size of the nanoplatelets and understanding the structures formed via their aggregation, it will be possible to engineer novel lipids systems that embody desired functional characteristics.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Mathematical Programming Models for Shale Oil & Gas Development: A Review and Perspective

Here, in this paper, we provide a comprehensive review of mathematical programming models for shale oil & gas development, and we offer a perspective on outstanding research opportunities. We distinguish contributions in five major topic areas, namely: (1) development planning, (2) water management, (3) production optimization, (4) supplies, gathering & processing, and (5) life cycle analysis & sustainability. We highlight how various types of mathematical programming models (i.e., linear programs, nonlinear programs, mixed-integer linear programs, mixed-integer nonlinear programs) have been proposed primarily by the Process Systems Engineering community to address the respective decision-making problems, and we highlight instances of successful deployment in industry. Finally, based on a critical assessment of the existing body of work, we identify opportunities for future research across the major topic areas.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Self-assembled oxide films with tailored nanoscale ionic and electronic channels for controlled resistive switching

Resistive switches are non-volatile memory cells based on nano-ionic redox processes that offer energy efficient device architectures and open pathways to neuromorphics and cognitive computing. However, channel formation typically requires an irreversible, not well controlled electroforming process, giving difficulty to independently control ionic and electronic properties. The device performance is also limited by the incomplete understanding of the underlying mechanisms. Here, we report a novel memristive model material system based on self-assembled Sm-doped CeO 2 and SrTiO 3 films that allow the separate tailoring of nanoscale ionic and electronic channels at high density (~10 12 inch –2 ). Here, we systematically show that these devices allow precise engineering of the resistance states, thus enabling large on–off ratios and high reproducibility. The tunable structure presents an ideal platform to explore ionic and electronic mechanisms and we expect a wide potential impact also on other nascent technologies, ranging from ionic gating to micro-solid oxide fuel cells and neuromorphics.

36 MATERIALS SCIENCE↗

A mobile test facility based on a magnetic cumulative generator to study the stability of the power plants under impact of lightning currents

The report presents the results of the development and field testing of a mobile test facility based on a helical magnetic cumulative generator (MCGTF). The system is designed for full-scale modeling of lightning currents to study the safety of power plants of any type, including nuclear power plants. Advanced technologies of high-energy physics for solving both engineering and applied problems underlie this pilot project. The energy from the magnetic cumulative generator (MCG) is transferred to a high-impedance load with high efficiency of more than 50% using pulse transformer coupling. Modeling of the dynamics of the MEG that operates in a circuit with lumped parameters allows one to apply the law of inductance output during operation of the MCG, thus providing the required front of the current pulse in the load without using any switches. The results of field testing of the MCGTF are presented for both the ground loop and the model load. The ground loop generates a load resistance of 2–4 Ω. In the tests, the ohmic resistance of the model load is 10 Ω. It is shown that the current pulse parameters recorded in the resistive-inductive load are close to the calculated values.

42 ENGINEERING↗

Object-Oriented Database for Managing Building Modeling Components and Metadata: Preprint

Building simulation enables users to explore and evaluate multiple building designs. When tools for optimization, parametrics, and uncertainty analysis are combined with analysis engines, the sheer number of discrete simulation datasets makes it difficult to keep track of the inputs. The integrity of the input data is critical to designers, engineers, and researchers for code compliance,validation, and building commissioning long after the simulations are finished. This paper discusses an application that stores inputs needed for building energy modeling in a searchable, indexable, flexible, and scalable database to help address the problem of managing simulation input data.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Model Predictive Fault-Tolerant Tracking Control for PDF Control Systems With Packet Losses

In this article, a fault-tolerant tracking control strategy is investigated for nonlinear probability density function (PDF) control systems with the actuator fault, uncertainties, unknown disturbance, and random packet losses. The control input signal dropout and measurement signal dropouts are described as the independent Bernoulli distribution. An adaptive fault diagnosis (FD) observer based on the Lyapunov function is given to simultaneously estimate the fault, disturbance, and state with packet losses. Furthermore, different from the traditional robust fault-tolerant control (FTC), a new active fault-tolerant tracking controller is designed based on the model predictive control framework, which has better adaptive fault-tolerant performance. Finally, the validity of the proposed FTC method has been proved by a simulation study of a papermaking process.

42 ENGINEERING↗

Power Decoupling Method for Voltage Source Inverters Using Grid Voltage Modulated Direct Power Control in Unbalanced System

The grid voltage modulated direct power control (GVM-DPC) is a novel power regulation method for grid-connected voltage source inverters (VSI). However, interactions between real and reactive powers still exist in GVM-DPC under unbalanced grid voltage condition, which may deteriorate its transient performance. Here, this article proposes a power decoupling method for GVM-DPC-based VSI in unbalanced systems based on the dynamic feedforward power compensation strategy, which can reduce the coupling magnitudes of real and reactive powers in the transient stages. First, the power coupling mechanism of positive and negative sequence real and reactive powers of VSI under the unbalanced voltage condition is analyzed. Then, the power coupling magnitudes (PCM) are derived according to relationships among the positive sequence components of real power, reactive power and point of common coupling (PCC) voltages. Next, the PCM are compensated into the GVM-DPC for the better decoupling performance. Furthermore, a stability analysis of the proposed control system is studied based on the impedance model, and a comparison with the traditional power decoupling method based on virtual impedance is conducted to show the superiority of the proposed method. Finally, simulations, hardware-in-loop test and experiment are conducted to validate the effectiveness of the proposed method.

42 ENGINEERING↗

Multiscale modeling for fluid transport in nanosystems.

Atomistic-scale behavior drives performance in many micro- and nano-fluidic systems, such as mircrofludic mixers and electrical energy storage devices. Bringing this information into the traditionally continuum models used for engineering analysis has proved challenging. This work describes one such approach to address this issue by developing atomistic-to-continuum multi scale and multi physics methods to enable molecular dynamics (MD) representations of atoms to incorporated into continuum simulations. Coupling is achieved by imposing constraints based on fluxes of conserved quantities between the two regions described by one of these models. The impact of electric fields and surface charges are also critical, hence, methodologies to extend finite-element (FE) MD electric field solvers have been derived to account for these effects. Finally, the continuum description can have inconsistencies with the coarse-grained MD dynamics, so FE equations based on MD statistics were derived to facilitate the multi scale coupling. Examples are shown relevant to nanofluidic systems, such as pore flow, Couette flow, and electric double layer.

Lee, Jonathan W.↗

Sensitivity and Uncertainty Workflow of Full System SIERRA Models Supporting High Consequence Applications

Credibility of end-to-end CompSim (Computational Simulation) models and their agile execution requires an expressive framework to describe, communicate and execute complex computational tool chains representing the model. All stakeholders from system engineering and customers through model developers and V&V partners need views and functionalities of the workflow representing the model in a manner that is natural to their discipline. In the milestone and in this report we define workflow as a network of computation simulation activities executed autonomously on a distributed set of computational platforms. The FY19 ASC L2 Milestone (6802) for the Integrated Workflow (IWF) project was designed to integrate and improve existing capabilities or develop new functionalities to provide a wide range of stakeholders a coherent and intuitive platform capable of defining and executing CompSim modeling from analysis workflow definition to complex ensemble calculations. The main goal of the milestone was to advance the integrated workflow capabilities to support the weapon system analysts with a production deployment in FY20. Ensemble calculations supporting program decisions include sensitivity analysis, optimization and uncertainty quantification. The goal of the L2 milestone aligned with the ultimate goal of the IWF project is to foster cultural and technical shift toward and integrated CompSim capability based on automated workflows. Specific deliverables were defined in five broad categories: 1) Infrastructure, including development of distributed-computing workflow capability, 2) integration of Dakota (Sandia's sensitivity, optimization and UQ engine) with SAW (Sandia Analysis Workbench), 3) ARG (Automatic Report Generator introspecting analysis artifacts and generating human-readable extensible and archivable reports), 4) Libraries and Repositories aiding capability reuse, and 5) Exemplars to support training, capturing best practices and stress testing of the platform. A set of exemplars was defined to represent typical weapon system qualification CompSim projects. Analyzing the required capabilities and using the findings to plan implementation of required capabilities ensured optimal allocation of development resources focused on production deployment after the L2 is completed. It was recognized early that the end-to-end modeling applications pose a considerable number of diverse risks, and a formal risk tracking process was implemented. The project leveraged products, capabilities and development tasks of IWF partners. SAW, Dakota, Cubit, Sierra, Slycat, and NGA (NexGen Analytics, a small business) contributed to the integrated platform developed during this milestone effort. New products delivered include: a) NGW (Next Generation Workflow) for robust workflow definition and execution, b) Dakota wizards, editor and results visualization, and c) the automatic report generator ARG. User engagement was initiated early in the development process eliciting concrete requirements and actionable feedback to assure that the integrated CompSim capability will have high user acceptance and impact. The current integrated capabilities have been demonstrated and are continually being tested by a set of exemplars ranging from training scenarios to computationally demanding uncertainty analyses. The integrated workflow platform has been deployed on both SRN (Sandia Restricted Network) and SCN (Sandia Classified Network). Computational platforms where the system has been demonstrated span from Windows (Creo the CAD platform chosen by Sandia) to Trinity HPC (Sierra and CTH solvers). Follow up work will focus on deployment at SNL and other sites in the nuclear enterprise (LLNL, KCNSC), training and consulting support to democratize the analysis agility, process health and knowledge management benefits the NGW platform provides.

97 MATHEMATICS AND COMPUTING↗

Formulation of an experimental substructure model using a Craig-Bampton based transmission simulator

An experimental–analytical substructuring is attractive when there is motivation to replace one or more system subcomponents with an experimental model. This experimentally derived substructure can then be coupled to finite element models of the rest of the structure to predict the system response. The transmission simulator method couples a fixture to the component of interest during a vibration test in order to improve the experimental model for the component. The transmission simulator is then subtracted from the tested system to produce the experimental component. This method reduces ill-conditioning by imposing a least squares fit of constraints between substructure modal coordinates to connect substructures, instead of directly connecting physical interface degrees of freedom. This paper presents an alternative means of deriving the experimental substructure model, in which a Craig–Bampton representation of the transmission simulator is created and subtracted from the experimental measurements. The corresponding modal basis of the transmission simulator is described by the fixed-interface modes, rather than free modes that were used in the original approach. Moreover, these modes do a better job of representing the shape of the transmission simulator as it responds within the experimental system, leading to more accurate results using fewer modes. The new approach is demonstrated using a simple finite element model based example with a redundant interface.

42 ENGINEERING↗

Residential Real-time Price Response Simulation

The electric industry is gaining experience with innovative price responsive demand pilots and limited roll-outs to customers. One of these pilots is investigating real-time pricing signals to engage end-use systems and local distributed generation and storage in a distributed optimization process. Attractive aspects about the approach include strong scalability characteristics, simplified interfaces between automation devices, and the adaptability to integrate a wide variety of devices and systems. Experience in this nascent field is revealing a rich array of for engineering decisions and the application of complexity theory. To test the decisions, computer simulations are used to reveal insights about design, demand elasticity, and the limits of response (including consumer fatigue). Agent-based approaches lend themselves well in the simulation to modeling the participation and interaction of each piece of equipment on a distribution feeder. This paper discusses rate design and simulation experiences at the distribution feeder level where consumers and their HVAC systems and water heaters on a feeder receive real-time pricing signals.

99 GENERAL AND MISCELLANEOUS↗

Energize: An Interactive Evaluation Tool for Engaging the General Public with Energy Decision Making - Final Report

The public has an ever-increasing interest in the economic, environmental, and social impacts of global energy production. To support informed decision making, the scientific community has a responsibility to communicate reliable and straight-forward information to the general public, in an engaging way, regarding energy systems and how choices made at different stages of an energy technology life cycle can impact the cost, amount of materials used, and waste produced. Our objective is to enhance public engagement via an interactive electrical energy game (Energ!ze) through which players interact with one another in their quest to develop an electrical energy portfolio that optimizes economic (e.g., company profit), environmental (e.g., reduced CO 2 emissions), and social (e.g., public opinion) impacts. The design and development of Energ!ze was an iterative process involving an interdisciplinary team of engineers, discipline-based scientists, computer scientists, and education experts. The development objectives were two-fold: (1) Accurate and quantifiable modeling of electrical energy systems and (2) Engaging and interactive user interface within the construct of the game narrative. The major game mechanics in the current playable Energ!ze version focus on economic metrics, and the database is scaffolded to add environmental and social metrics for future versions. This report details the outcome of the funding period (Section 2 and 3) and describes the development process, along with recommendations for future development (Section 4).

29 ENERGY PLANNING, POLICY, AND ECONOMY↗