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At least 253 records · Page 14

Towards Predictive Plasma Science and Engineering through Revolutionary Multi-Scale Algorithms and Models (Final Report)

This report describes the high-level accomplishments from the Plasma Science and Engineering Grand Challenge LDRD at Sandia National Laboratories. The Laboratory has a need to demonstrate predictive capabilities to model plasma phenomena in order to rapidly accelerate engineering development in several mission areas. The purpose of this Grand Challenge LDRD was to advance the fundamental models, methods, and algorithms along with supporting electrode science foundation to enable a revolutionary shift towards predictive plasma engineering design principles. This project integrated the SNL knowledge base in computer science, plasma physics, materials science, applied mathematics, and relevant application engineering to establish new cross-laboratory collaborations on these topics. As an initial exemplar, this project focused efforts on improving multi-scale modeling capabilities that are utilized to predict the electrical power delivery on large-scale pulsed power accelerators. Specifically, this LDRD was structured into three primary research thrusts that, when integrated, enable complex simulations of these devices: (1) the exploration of multi-scale models describing the desorption of contaminants from pulsed power electrodes, (2) the development of improved algorithms and code technologies to treat the multi-physics phenomena required to predict device performance, and (3) the creation of a rigorous verification and validation infrastructure to evaluate the codes and models across a range of challenge problems. These components were integrated into initial demonstrations of the largest simulations of multi-level vacuum power flow completed to-date, executed on the leading HPC computing machines available in the NNSA complex today. These preliminary studies indicate relevant pulsed power engineering design simulations can now be completed in (of order) several days, a significant improvement over pre-LDRD levels of performance.

42 ENGINEERING↗

Transmission Planning Analysis Tool

Developed to solve specific problem: Assist transmission planning for regional transfers in interconnected power systems. This work was originated in a study for the U.S. Department of State, to recommend transmission reinforcements for the Central American regional system that interconnects 6 countries. Transmission planning analysis is currently performed by engineers with domain-specific and system-specific knowledge without a unique methodology. The software codes of this disclosure assists engineers by defining systematic analysis procedures to help identify weak points and make decisions on transmission planning of regional interconnected power systems. Transmission Planning Analysis Tool groups PSS/E results of multiple AC contingency analysis and voltage stability analysis and QV analysis of many scenarios of study and arrange them in a systematic way to aid power system planning engineers or transmission operators in effective decision-making process or in the offline study environment.

Vyakaranam, Bharat↗

FY24 LDRD Annual Report PDF

The Laboratory Directed Research and Development (LDRD) Program at Lawrence Livermore National Laboratory (LLNL) is the Lab's most significant resource for supporting internally directed research and development. It provides investments in cutting-edge science, technology, and engineering. This program expands the frontiers of knowledge, creates capabilities required by our evolving mission needs, and attracts and retains the world's most talented scientists and engineers. In this annual report, we describe the LDRD investment portfolio, provide information to demonstrate the program's value and impact to LLNL's science, technology and engineering capabilities, and showcase LDRD accomplishments across the Lab's mission space.

42 ENGINEERING↗

Attacking the IEC-61131 Logic Engine in Programmable Logic Controllers in Industrial Control Systems

In industrial control systems (ICS), programmable logic controllers (PLCs) directly monitor and control a physical process such as nuclear power plants, gas pipelines, and water treatment. They are equipped with a control logic written in IEC-61131 languages (e.g., ladder logic and structured text) that defines how a PLC should control a physical process. A PLC's control logic is a usual target of a cyberattack to sabotage a physical process. For instance, Stuxnet targets a control logic of a Siemens S7-300 PLC to damage a nuclear facility's centrifuges. The existing attacks in the literature generally focus only on injecting malicious control logic into a PLC. This paper presents a new dimension of control logic attacks that target the control logic engine (responsible for running a control logic) of a PLC. It demonstrates that a cyberattack can disable the control logic engine successfully by exploiting inherent PLC features such as program mode and starting/stopping engine. We develop two novel case studies on control logic engine attacks by employing the MITRE ATT\&CK knowledge base on the real-world PLCs used in industry settings, i.e., 1) Schweitzer Engineering Laboratory (SEL)'s Real-Time Automation Controller (SEL-3505 RTAC) equipped with security features such as encrypted traffic and device-level access control, and 2) traditional PLCs, i.e., Schneider Electric's Modicon M221, Allen-Bradley's MicroLogix 1400 and 1100 that do not have security features. The case studies present the internals of the logic engine attacks and facilitate the ICS research community and industry to understand the attack vectors on the control logic engine. We evaluate the effectiveness of the control engine attacks on a power substation, a 4-floor elevator, and a conveyor belt to demonstrate their real-world impact of halting a physical process.

Ali qasim, Syed↗

Improved Biofuel Production through Discovery and Engineering of Terpene Metabolism in Switchgrass

Project Objectives - Of the myriad specialized metabolites that plants deploy to adapt to environmental challenges, terpenes form the largest group. In many major crops, unique terpene blends serve as key stress defenses that directly impact plant fitness and yield. In addition, terpenes, such as bisabolene and pinene, are used for producing renewable biofuels. Essential to advancing a broader use of terpenes for biofuel feedstock engineering is a system-wide knowledge of the diverse biosynthetic machinery and defensive potential of often species-specific terpene blends. The proposed project would merge genome-wide enzyme discovery with comparative –omics, protein structural and plant microbiome studies to define the biosynthesis and stress-defensive functions of the switchgrass (Panicum virgatum) terpene network. These insights would be combined with developing and applying non-transgenic genome editing tools to design plants with desirable terpene blends for higher productivity and biofuel production on marginal lands. As a dedicated lignocellulosic feedstock for U.S. biofuel production with high net energy yield, stress tolerance, and available genome resources, switchgrass is well-suited for devising new avenues for biofuel production. Project Description – The diversity of plant terpene defenses is governed by species-specific families of terpene synthase (TPS) and cytochrome P450 monooxygenase (P450) enzymes. Mining of the switchgrass genome (genotype Alamo) identified ~100 TPS and P450 candidate genes, and combinatorial biochemical analysis of synthesized TPSs and P450s revealed more than a dozen enzymes with common and novel activities. In addition, several identified terpene metabolites and the corresponding transcripts were up-regulated in response to abiotic stressors. These findings demonstrate a unique switchgrass terpene network with probable importance to abiotic stress tolerance, thus providing a large chemical portfolio for optimizing crop resistance, yield, and biofuel composition. Leveraging these preliminary data, we propose to generate a genome-wide map of the switchgrass terpene metabolic network through multi-gene co-expression analyses that allow the efficient cross-validation of TPS and P450 functions. Key enzymes would further be applied to structure-function studies via X-ray protein crystallography, homology modeling and site-directed mutagenesis to gain mechanistic insight into the catalytic specificity of switchgrass terpene metabolism and provide gene and amino acid targets for genome editing. In tandem with terpene pathway discovery, system-wide metabolomics, transcriptomics and proteomics studies in switchgrass accessions of contrasting drought tolerance would define the role of switchgrass terpene metabolism in conferring abiotic stress resilience. Metabolic changes would be assessed in a combined approach of targeted (terpenes) and untargeted metabolite profiling using a high-resolution LC-MS/MS approach, differential gene expression analyses through multiplexed Illumina RNA sequencing, and quantitative analysis of high-priority pathway enzymes using multiple reaction monitoring (MRM). Drawing on these insights, knock-down/out mutants of stress-associated pathway nodes would be generated by optimizing transient virus-induced gene silencing (VIGS) and CRISPR/Cas9 systems under control of the Tobacco Rattle Virus (TRV). The resulting mutant lines would then be analyzed for stress susceptibility and the impact on the root microbiome to define gene functions in planta. Knowledge of terpene pathways, enzyme mechanisms and bioactivities would be applied to enhance switchgrass stress resilience and to tailor-make terpene blends for biofuel production. Here, TRV-enabled CRISPR/Cas9 genome editing, including allele-specific knock-out of redundant genes, engineering of enzyme specificity via structure-guided point mutations, and overexpression of terpene genes relevant to stress-protection or biofuel production, would be used to increase metabolic flux toward desired pathways. Broader Impacts - Integrating the system-wide discovery, mechanistic analysis and non-transgenic genome engineering of the switchgrass terpene network aligns the required steps to unlock the chemical potential of this important metabolite class to generate crops that are more resistant to stress and provide advanced biofuel production in light of rising climate pressures as foreseeable challenges for bioenergy crop cultivation. The proposed project would further offer interdisciplinary student training through active involvement in the project and integration of research concepts and outcomes into newly-developed graduate and undergraduate courses on Plant Biotechnology.

09 BIOMASS FUELS↗

LLMs for Mfg.—On the State of Large Language Models and Applications to Manufacturing

Additive Manufacturing (AM), referred to as 3D printing, has emerged as a key pillar of Industry 4.0 enabling layer-by-layer fabrication of intricate geometries from CAD models. In parallel, Large Language Models (LLMs), deep learning models for natural language generation trained on vast text corpora, have demonstrated unprecedented capabilities in understanding and generating human-like text. The convergence of these trends opens new opportunities at the intersection of AM and AI/ML, where LLMs can assist engineers and researchers in design, manufacture planning, and knowledge discovery. Recent academic work has begun to explore LLM applications in AM and adjacent fields, such as material science, mechanical engineering, and design for additive manufacturing. This exploration ranges from intelligent process planning to domain-specific knowledge retrieval. This survey provides a comprehensive review of current developments, focusing on peer-reviewed literature contributions that apply, adapt, and advance LLMs in general and domain-specific domains. We analyze state-of-the-art (SOTA) techniques, such as fine-tuning foundational models for specific domains, retrieval-augmented generation (RAG) pipelines, knowledge graph integration, and delve into the architectures and evaluation methods employed. The goal of this survey is to inform researchers and practitioners of the current capabilities and limitations of LLMs in general and in domain-specific applications, and to outline how these models are being tailored to meet the requirements of these applications.

36 MATERIALS SCIENCE↗

TeMoto 2.0: Source Agnostic Command-to-Task Architecture Enabling Increased Autonomy in Remote Systems - 18438

Tele-operated robots provide safe means for executing tasks in hazardous environments such as underground mines, space, disaster and legacy nuclear facility decommissioning sites, etc. The desire to use these systems in increasingly complex and dynamic environments presents a variety of technical and educational challenges including (i) insufficient field knowledge of system developers, (ii) restricted data bandwidth, and (iii) insufficient operator situational awareness. Lack of field knowledge is commonly addressed by actively educating robotics engineers in the perspective areas. The Nuclear Robotics Group (NRG) at the University of Texas at Austin trains students to have the necessary skill and knowledge in both the robotic and nuclear domains. To address the second two deficiencies, the NRG has developed TeMoto: a speech and hand gesture based supervisory teleoperation software. TeMoto addresses several chronic technical issues associated with most teleoperation systems including the operator's situational awareness, communication delays and interface intuitiveness. This paper reviews recent efforts to update and extend the TeMoto architecture (TeMoto 2.0) to support more complex semi-autonomous behaviors and eliminate the unnecessary and confining concept of a human interface as a separate component from the rest of the robot's sensors and actuators. This paper outlines the key architectural changes and demonstrations using a dual-arm mobile manipulator to complete semi-autonomous tasks. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Advanced characterization-informed machine learning framework and quantitative insight to irradiated annular U-10Zr metallic fuels

Abstract U-10Zr Metal fuel is a promising nuclear fuel candidate for next-generation sodium-cooled fast spectrum reactors. Since the Experimental Breeder Reactor-II in the late 1960s, researchers accumulated a considerable amount of experience and knowledge on fuel performance at the engineering scale. However, a mechanistic understanding of fuel microstructure evolution and property degradation during in-reactor irradiation is still missing due to a lack of appropriate tools for rapid fuel microstructure assessment and property prediction based on post irradiation examination. This paper proposed a machine learning enabled workflow, coupled with domain knowledge and large dataset collected from advanced post-irradiation examination microscopies, to provide rapid and quantified assessments of the microstructure in two reactor irradiated prototypical annular metal fuels. Specifically, this paper revealed the distribution of Zr-bearing secondary phases and constitutional redistribution across different radial locations. Additionally, the ratios of seven different microstructures at various locations along the temperature gradient were quantified. Moreover, the distributions of fission gas pores on two types of U-10Zr annular fuels were quantitatively compared.

36 MATERIALS SCIENCE↗

Practical Experience Integration into the Univ. of NV, Reno Nuclear Packaging Graduate Certificate - 18210

In 2015, the University of Nevada, Reno (UNR) Mechanical Engineering (ME) Department began offering a 9-credit, regionally accredited Graduate Certificate in Nuclear Packaging (GCNP). The certificate's program educational objectives are to provide the necessary applied knowledge and skills that mechanical, materials, or nuclear engineers require to be successful as nuclear packaging designers, analysts and users. This includes knowing how to apply required quality assurance methods, regulations, and design goals. It also includes gaining added depth in those required topics, and/or a breadth beyond those topics, to support the certificate holder to excel in the nuclear packaging industry. The GCNP courses draw heavily on nuclear packaging safety content that experts at Argonne, Laurence Livermore and Savannah River National Laboratories developed and taught over the past 20 years with support from the US Department of Energy (DOE) Packaging and Certification Program (PCP). The national laboratories continue to teach the GCNP required courses, which present the essential information, and several elective courses. UNR offers some elective courses. Oak Ridge and Sandia National Laboratories are currently developing new elective courses. This paper describes the development and requirements of a new 3-credit elective course UNR is developing, entitled Nuclear Packaging Internship (ME 699). The student learning outcome of that course is to provide project-based supervised practical training at a national laboratory or DOE site that contributes to the student's depth and breadth of nuclear packaging knowledge and skills. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Nuclear waste Educator's workshop: What and how do we teach about nuclear waste?

A workshop was held at the Massachusetts Institute of Technology (MIT) on July 25th and 26th, 2022. The objective was to develop a blueprint for educating next-generation engineers and scientists about nuclear waste management and disposal, which requires knowledge from diverse disciplines, including nuclear, chemical, civil, environmental, and geological science and engineering. The 49 participants included university professors, researchers, industry experts, and government officials from different areas. First, we have developed a list of key fundamental knowledge on waste management and disposal across the nuclear fuel cycle. In addition, we discussed strategies on how to teach students with diverse backgrounds through innovative teaching strategies as well as how to attract students into this area. Through the workshop, we identified the critical needs to (1) develop community resources for nuclear waste education; (2) synthesize historical perspectives, including past contamination and the management of general hazardous waste; (3) emphasize a complete life-cycle perspective, including proper waste management as the key component for energy sustainability; (4) teach students how to communicate about the key facts and risks to technical and non-technical audiences; and (5) accelerate the use of the state-of-art-technologies to attract and retain a young workforce. Furthermore, we aim to build a diverse, inclusive community that supports students in developing their own narratives about nuclear waste, particularly in recognizing that antagonistic views have been important to improving safety and protecting public health and the environment.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

High-Speed Multiplexed Spatiotemporally Resolved Measurements of Exhaust Gas Recirculation Dynamics in a Multi-Cylinder Engine Using Laser Absorption Spectroscopy

The need for more environmentally friendly and efficient energy conversion is of paramount importance in developing and designing next-generation internal combustion (IC) engines for transportation applications. One effective solution to reducing emissions of mono-nitrogen oxides (NO x ) is exhaust gas recirculation (EGR), which has been widely implemented in modern vehicles. However, cylinder-to-cylinder and cycle-to-cycle variations in the charge-gas uniformity can be a major barrier to optimum EGR implementation on multi-cylinder engines, and can limit performance, stability, and efficiency. Precise knowledge and fine control over the EGR system is thus crucial, particularly for optimizing advanced engine concepts such as reactivity controlled compression ignition (RCCI). An absorption-based laser diagnostic was developed to study spatiotemporal charge-gas distributions in an IC engine intake manifold in real-time. The laser was tuned to an absorption band of carbon dioxide (CO 2 ), a standard exhaust-gas marker, near 2.7 µm. The sensor was capable of probing four separate measurement locations simultaneously, and independently analyzing EGR fraction at speeds of 5 kHz (1.2 crank-angle degree (CAD) at 1 k RPM) or faster with high accuracy. Lastly, the probes were used to study spatiotemporal EGR non-uniformities in the intake manifold and ultimately promote the development of more efficient and higher performance engines.

33 ADVANCED PROPULSION SYSTEMS↗

Building Nuclear-Specific Cybersecurity Expertise in Higher Education

The rapid digitalization of nuclear power plants (NPPs) and the deployment of advanced and small modular reactors (A/SMRs) have expanded the cybersecurity attack surface within the nuclear sector. This evolution introduces unique challenges beyond those faced in general information technology (IT), operational technology (OT) and industrial control system (ICS) security, due to nuclear power’s regulatory rigor, safety-critical nature, and operational needs. A pressing workforce gap persists; cybersecurity graduates typically lack nuclear-specific context and retraining them for industry readiness requires 12–18 months, creating a significant burden. This paper addresses this gap by defining the domains of knowledge that nuclear cybersecurity specialists must master, spanning cybersecurity, nuclear engineering, OT/ICS security, and regulatory governance. We propose a curricular framework integrating technical, regulatory, and applied learning components to accelerate workforce readiness. Our approach builds on existing findings that current curricula inadequately integrate nuclear engineering and cybersecurity, shifting the discourse from why specialization is needed to what knowledge must be taught. The recommendations have implications for workforce development and long-term resilience of the nuclear energy sector.

99 - GENERAL AND MISCELLANEOUS↗

Predicting on-site environmental impacts of municipal engineering works

The research findings fill a gap in the body of knowledge by presenting an effective way to evaluate the significance of on-site environmental impacts of municipal engineering works prior to the construction stage. First, 42 on-site environmental impacts of municipal engineering works were identified by means of a process-oriented approach. Then, 46 indicators and their corresponding significance limits were determined on the basis of a statistical analysis of 25 new-build and remodelling municipal engineering projects. In order to ensure the objectivity of the assessment process, direct and indirect indicators were always based on quantitative data from the municipal engineering project documents. Finally, two case studies were analysed and found to illustrate the practical use of the proposed model. The model highlights the significant environmental impacts of a particular municipal engineering project prior to the construction stage. Consequently, preventive actions can be planned and implemented during on-site activities. The results of the model also allow a comparison of proposed municipal engineering projects and alternatives with respect to the overall on-site environmental impact and the absolute importance of a particular environmental aspect. These findings are useful within the framework of the environmental impact assessment process, as they help to improve the identification and evaluation of on-site environmental aspects of municipal engineering works. The findings may also be of use to construction companies that are willing to implement an environmental management system or simply wish to improve on-site environmental performance in municipal engineering projects. -- Highlights: • We present a model to predict the environmental impacts of municipal engineering works. • It highlights significant on-site environmental impacts prior to the construction stage. • Findings are useful within the environmental impact assessment process. • They also help contractors to implement environmental management systems.

54 ENVIRONMENTAL SCIENCES↗

Biofuels Refining Engineering

The goal of this project is the development of novel catalysts and knowledge of reaction pathways and mechanisms for conversion of biomass-based compounds to fuels that are compatible with oil-based fuels and with acceptable or superior fuel properties. The research scope included both catalysts to convert lignocellulosic biomass-based molecules (from pyrolysis) and vegetable oil-based molecules (i.e., triglycerides and fatty acid methyl esters). This project comprised five technical tasks. Each task is briefly introduced below, and major technical accomplishments summarized. Technical accomplishments were described in greater detail in the quarterly progress reports, and in even more detail in the >50 publications acknowledging this DoE project funding (list of publications and presentations included at the end of this report). The results of this research added greatly to the knowledge base necessary for upgrading of pyrolysis oil to hydrocarbon fuels and chemicals, and for conversion of vegetable oils to fungible diesel fuel. Numerous new catalysts and catalytic reaction systems were developed for upgrading particular compounds or compound families found in the biomass-based pyrolysis oils and vegetable oils. Methods to mitigate catalyst deactivation were investigated, including novel reaction/separation systems. Performance and emission characteristics of biofuels in flames and engines were measured. Importantly, the knowledge developed from this project became the basis for a subsequent collaborative proposal led by our research group, involving researchers from the University of Wisconsin, the University of Pittsburg, and the Idaho National Lab, for the DoE Carbon, Hydrogen and Separations Efficiency (CHASE) program, which was subsequently funded (one of only four projects awarded in the CHASE program). The CHASE project examined novel catalytic processes for lignocellulosic biomass conversion as well as technoeconomic analyses for process options for maximum carbon capture and hydrogen efficiency. Our research approach combined catalyst synthesis, measurements of catalyst activity and selectivity in different reactor systems and conditions, and detailed catalyst characterization to develop fundamental understanding of reaction pathways and the capability to predict product distributions. Nearly all of the candidate catalysts were prepared in-house via standard techniques such as impregnation, co-impregnation, or chemical vapor deposition. Supports were usually purchased, but in some cases coprecipitation was used to simultaneously create the support and active component, which can be advantageous for strong active component-support interactions and for achieving high active component dispersion. In-house synthesis also allowed for studies of the effects on catalyst activity and selectivity of such factors as support porosity, calcination temperature, and reduction/activation conditions. Depending on the physical characteristics of the molecule, catalyst activity measurements were carried out in tubular flow reactors (for vapor phase reactions) or stirred tank reactors (for liquid phase reactions) over a wide range of pressures and temperatures. Reactant and product concentrations were measured using gas chromatography (both on-line and off-line, with TCD, FID, and/or mass spectrometric detection). For promising catalysts, detailed physicochemical characterization was carried out using FTIR, Raman, XPS, and XRD spectroscopies (all available in our laboratories) and TEM spectroscopy (available at OU). Additional methods included temperature programmed techniques (TPD, TPO) and surface area measurements by nitrogen adsorption techniques.

01 COAL, LIGNITE, AND PEAT↗

Large language models for transportation research: Methodologies, state of the art, and future opportunities

The rapid rise of large language models (LLMs) is transforming transportation research, with significant advancements emerging between 2023 and 2025, a period marked by the inception and swift growth of adopting and adapting LLMs for various transportation applications. Despite these significant advancements, however, a systematic review and synthesis of the existing literature remains lacking. This paper aims to fill this gap by providing a comprehensive review of the methodologies and applications of LLMs in transportation. We explore key applications, including autonomous driving, travel behavior prediction, and general transportation-related queries, alongside LLM methodologies such as zero- or few-shot learning, prompt engineering, and fine-tuning. From the review, critical research gaps are identified. From the methodological perspective, many of the research limitations can be addressed by integrating LLMs with existing tools and refining LLM architectures. From the application perspective, research opportunities for LLMs to address various transportation challenges are also explored. By synthesizing these findings, this review not only presents the state-of-the-art LLM adoption and adaptation in transportation, but also proposes future research directions as well as insights and recommendations for policymakers and practitioners, paving the way for greater LLM-driven research innovations in transportation in the future.

42 ENGINEERING↗

Temperature-dependent 780-nm laser absorption by engineering grade aluminum, titanium, and steel alloy surfaces

When modeling laser interaction with metals for various applications it requires a knowledge of absorption coefficients for real, commercially available materials with engineering grade (unpolished, oxidized) surfaces. But, most currently available absorptivity data pertain to pure metals with polished surfaces or vacuum-deposited thin films in controlled atmospheres. A simple laboratory setup is developed for the direct calorimetric absorptivity measurements using a diode-array laser emitting at 780 nm. A scheme eliminating the effect of convective and radiative losses is implemented. Futhermore, the obtained absorptivity results differ considerably from existing data for polished pure metals and are essential for the development of predictive laser-material interaction models.

36 MATERIALS SCIENCE↗

Challenging Engineering Demographics and the READY Program - 18528

The mission of the Liquid Waste Organization at the Savannah River Site involves the safe storage of nuclear waste, closure of waste tanks, and immobilization of the waste into grout (low-level waste) or glass (high-level waste). With much of the mission left to complete and a significant percentage of the engineering organization eligible for retirement within the next 5 years, focus has been on recruiting and retaining new hires and early career engineers. Over the past two years, enhancements have been made to current programs and new programs have been created with the goal of improving the retention rate for engineering. These programs include the Reaching Engineers at the Development Years, the Early Career Professional Technology Exchange, the Shift Technical Engineer Pipeline, and Technical Staff Training. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗