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At least 523 records · Page 29

Rapid Quality Assessment in Additive Manufacturing: New Procedure Accelerates Build Quality Assessment. White paper

Accelerated growth of the additive manufacturing (AM) industry in recent years is accompanied by a rising need for methods to quickly assess quality at-scale. Current practices for quality inspection include nondestructive test methods and destructive testing of witness coupons, which are artifacts built alongside the actual part. However, these methods can be costly and time-consuming. Recognizing this need, the Additive Manufacturing Center of Excellence (AM CoE) initiated a project led by its partner, Auburn University, to develop rapid testing procedure using asbuilt samples tested in torsion to quantitatively assess build quality. The presented work developed a rapid testing procedure using as-built samples tested in torsion to quantify small variances for assessing build quality.

42 ENGINEERING↗

Artificial Intelligence Strategy and Implementation [Slides]

LANL strategic activities for AI center on this goal: accelerate development of AI-enabled capabilities for science and security, with focus on developing and applying mission-relevant core AI technologies, creating an AI workforce pipeline and training opportunities, and building AI partnerships and community.

42 ENGINEERING↗

Power Electronics and Electric Machines for Advanced Aircraft

Power electronics and electric machines are critical components of efficient, high-performance aircraft - from fixed-wing turbine to electric vertical takeoff and landing aircraft and beyond. Improvements to these components create enormous energy efficiencies, enable cost savings, and ensure fail-safe operations. National Renewable Energy Laboratory researchers are developing innovative power electronics, electric motors, integrated electric traction drives, and thermal management systems to build highly efficient, lightweight, ultrareliable powertrains for aircraft.

42 ENGINEERING↗

Texture evolution as a function of scan strategy and build height in electron beam melted Ti-6Al-4V

Metal additive manufacturing (AM) enables customizable, on-demand parts, allowing for new designs and improved engineering performance. Yet, the ability to control AM metal alloy microstructures (i.e., grain morphology, crystallographic texture, and phase content) is lacking. Furthermore, this work performs corroborative neutron diffraction and large-scale electron backscatter diffraction (EBSD) measurements to assess crystallographic texture in electron beam melted (EBM) Ti-6Al-4V as a function of scan strategy and build height. Texture components for one raster and two spot melt scan strategies were evaluated using a triclinic specimen symmetry to capture all possible texture components, which were found to be considerably different than previously reported values from studies employing orthotropic specimen symmetry. This finding highlights the importance of a standard method and best practice for assessing textures produced by AM.

36 MATERIALS SCIENCE↗

Impacts of the Additive Manufacturing Process on the Roughness of Engine Scale Vanes and Cooling Channels

Abstract By leveraging the additive manufacturing (AM) platform, development time and costs for turbine component testing can be reduced relative to traditional investment casting. Surface roughness is a key characteristic of the additive manufacturing process that can impact flow, heat transfer, and mechanical integrity of printed components. There are multiple design and build considerations that result in variability in surface roughness, especially when additively fabricating complicated three-dimensional vanes and internal cooling passages. This study characterizes the surface roughness of internal cooling passages, vanes, and flat external surface samples made using additive manufacturing, specifically the direct metal laser sintering process. The samples were manufactured with various wall thicknesses, layer thicknesses, build locations, build directions, and on different AM machines. A combination of computed tomography scanning and optical profilometry was used to evaluate surface roughness levels. The data indicate that the dominant factors in roughness for a given layer thickness are a function of wall thickness, build location, and build direction.

Engineering↗

Securing Grid-interactive Efficient Buildings (GEB) through Cyber Defense and Resilient System (CYDRES)

The DOE CYDRES project is driven by the urgent need to address critical research gaps in the domain of cyber-physical security of smart buildings, including Grid-interactive Efficient Buildings (GEBs). CYDRES, a real-time advanced building resilient platform, aims to enhance the cyber-attack-immune capabilities of buildings through multi-layered prevention, detection, and adaptation mechanisms. CYDRES consists of five key modules: a multi-layer network analyzer, an Automatic Fault Detection, Diagnosis, and Prognosis (AFDDP) framework, an intelligent mode selector, a cyber-resilient control framework, and a situation awareness platform. The Network Analyzer employs a data-driven framework that includes a protocol state learning tool and a CRF (Conditional Random Field) command validator. In Hardware-In-the-Loop (HIL) testbeds, it achieved 100% detection accuracy with a false alarm rate of 3%, validating its efficacy in identifying selected cyber-attacks. The AFDDP framework leverages pattern matching, PCA (Principal Component Analysis)-based strategies, and a DBN (Dynamic Bayesian Network)-based fault diagnosis approach to pinpoint the causes of physical system abnormalities using Building Automation System (BAS) data. In HIL experiments, the AFDDP module attained a detection accuracy of over 95% with a false alarm rate below 7%. Additionally, the fault detector utilized machine learning (Random Forest) and deep learning (Multi-Layer Perceptron) methods with acoustic sensor data to achieve a 100% fault detection accuracy in Heating, Ventilation, and Air-Conditioning (HVAC) equipment. The Mode Selector offered real-time impact analysis, allowing immediate actions to protect BASs in the face of emerging threats. The cyber-resilient control framework included an adaptive Model Predictive Control (MPC) and a measurement compensator, reducing temperature violations by up to 94% and improving the total demand flexibility by up to 70% in HIL experiments. Such HIL experiments covered a cyber-attack case and a physical fault case, showcasing CYDRES’ efficiency in maintaining operational continuity during threats. The situation awareness platform in Grafana enhanced real-time threat detection and response visualization, augmenting the operational awareness for building operators. CYDRES demonstrated high technical effectiveness in various test scenarios, particularly in HIL environments. The project's phased development approach ensured efficient use of resources, highlighting its practical feasibility and readiness for commercialization. By enhancing the security and resilience of building operations, CYDRES represents a significant advance in mitigating risks associated with cyber-physical systems, thereby enhancing public confidence in the safety of modern building infrastructure. Future directions for the project include expanding testing protocols, refining AFDDP methodologies, exploring more comprehensive resilient control strategies, and testing in real commercial buildings.

42 ENGINEERING↗

Production of β-ketoadipic acid from glucose in Pseudomonas putida KT2440 for use in performance-advantaged nylons

Biomass-derived chemicals can offer unique chemical functionality relative to petroleum-derived building blocks. To this end, here we report that β-ketoadipic acid (βKA), a C6 diacid with a β-ketone group, can be used as a performance-advantaged replacement for adipic acid in a nylon-6,6 analog. Building on our previous efforts to produce shikimate-derived products from carbohydrates, Pseudomonas putida KT2440 is engineered to produce βKA from glucose, achieving a 26 g/L titer. Following purification, βKA imparts an increase of 69 degrees C above the nylon-6,6 glass transition temperature and 20% reduced water permeability, equivalent to nylon-6,10. Molecular simulations predict that the enhanced thermal properties result from rigidity introduced by the β-ketone. Process analysis predicts that βKA can be produced for US$1.94/kg from sugars, requiring 63% less energy and emitting 43% less greenhouse gases than fossil-based adipic acid. Overall, this study illustrates the potential for βKA to serve as a useful building block for bio-based polymers.

09 BIOMASS FUELS↗

Incorporating two-dimensional conduction modeling techniques into an energy simulation program: The EnergyPlus radiant system example

Due to the inherent complexity of multi-dimensional solutions for transient conduction in a multilayered building element, most heat balance-based algorithms assume that conduction occurs only in one dimension—through the building element between the inside and outside environments. Usually, since the length and width of the elements are much greater than the thickness of the element, this is a valid assumption. However, there are some cases such as hydronic radiant slabs where this assumption may not lead to an accurate estimate of the energy consumption of the system. In a hydronic radiant slab, water tubes are embedded in a slab, and hot or chilled water is circulated to meet any heating or cooling loads. The energy consumption of such a system will depend highly on the temperature of the water being sent to the slab (i.e., produced by the boiler or chiller). The temperature of the water that must be sent to the slab will depend on the spacing of the tubes, the multilayer construction of the building element, and the boundary conditions to which the construction is exposed. Thus, to accurately predict the energy consumption of such a system, a transient two-dimensional heat conduction model must be integrated with a heat balance-based simulation. This paper demonstrates the potential loss of accuracy associated with the one-dimensional radiant system models by providing a comparison of one- and two-dimensional solutions using EnergyPlus.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

A quantum processor based on coherent transport of entangled atom arrays

The ability to engineer parallel, programmable operations between desired qubits within a quantum processor is key for building scalable quantum information systems. In most state-of-the-art approaches, qubits interact locally, constrained by the connectivity associated with their fixed spatial layout. Here we demonstrate a quantum processor with dynamic, non-local connectivity, in which entangled qubits are coherently transported in a highly parallel manner across two spatial dimensions, between layers of single- and two-qubit operations. Our approach makes use of neutral atom arrays trapped and transported by optical tweezers; hyperfine states are used for robust quantum information storage, and excitation into Rydberg states is used for entanglement generation. We use this architecture to realize programmable generation of entangled graph states, such as cluster states and a seven-qubit Steane code state. Furthermore, we shuttle entangled ancilla arrays to realize a surface code state with thirteen data and six ancillary qubits and a toric code state on a torus with sixteen data and eight ancillary qubits. Finally, we use this architecture to realize a hybrid analogue–digital evolution and use it for measuring entanglement entropy in quantum simulations, experimentally observing non-monotonic entanglement dynamics associated with quantum many-body scars. Realizing a long-standing goal, these results provide a route towards scalable quantum processing and enable applications ranging from simulation to metrology.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

The Untold Story of Building the First Megaton Thermonuclear Fusion Device: The Simple Element and IVY Mike

This report is a research and development engineer’s perspective on the fascinating story of the world’s first megaton-class thermonuclear device, IVY Mike (10.4 Mt). Few modern scientific endeavors have matched the complexity and breadth of scientific achievement in such a short amount of time as IVY Mike. This paper will take a look at the design, engineering, fielding, and execution of the world’s first megaton-class physics experiment by Los Alamos Scientific Laboratory and the birth of industrial liquid hydrogen use spawned by the Cold War effort. Although others have written on aspects of this technical history, they have not benefited from access to the original classified documents used by the present author. The present paper must necessarily omit some technical details that remain classified but represents the most comprehensive summary of the engineering and fabrication of the IVY Mike device in the open literature.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Mini‐synplastomes for plastid genetic engineering

Summary In the age of synthetic biology, plastid engineering requires a nimble platform to introduce novel synthetic circuits in plants. While effective for integrating relatively small constructs into the plastome, plastid engineering via homologous recombination of transgenes is over 30 years old. Here we show the design–build–test of a novel synthetic genome structure that does not disturb the native plastome: the ‘mini‐synplastome’. The mini‐synplastome was inspired by dinoflagellate plastome organization, which is comprised of numerous minicircles residing in the plastid instead of a single organellar genome molecule. The first mini‐synplastome in plants was developed in vitro to meet the following criteria: (i) episomal replication in plastids; (ii) facile cloning; (iii) predictable transgene expression in plastids; (iv) non‐integration of vector sequences into the endogenous plastome; and (v) autonomous persistence in the plant over generations in the absence of exogenous selection pressure. Mini‐synplastomes are anticipated to revolutionize chloroplast biotechnology, enable facile marker‐free plastid engineering, and provide an unparalleled platform for one‐step metabolic engineering in plants.

Occhialini, Alessandro↗

Towards Off-policy Evaluation as a Prerequisite for Real-world Reinforcement Learning in Building Control

We present an initial study of off-policy evaluation (OPE), a problem prerequisite to real-world reinforcement learning (RL), in the context of building control. OPE is the problem of estimating a policy's performance without running it on the actual system, using historical data from the existing controller. It enables the control engineers to ensure a new, pretrained policy satisfies the performance requirements and safety constraints of a real-world system, prior to interacting with it. While many methods have been developed for OPE, no study has evaluated which ones are suitable for building operational data, which are generated by deterministic policies and have limited coverage of the state-action space. After reviewing existing works and their assumptions, we adopted the approximate model (AM) method. Furthermore, we used bootstrapping to quantify uncertainty and correct for bias. In a simulation study, we evaluated the proposed approach on 10 policies pretrained with imitation learning. On average, the AM method estimated the energy and comfort costs with 1.84% and 14.1% error, respectively.

Chen, B↗

Challenges, Industry Practice, and Research Opportunities for Protection of IBR-Rich Systems

The objective of this technical report is to outline the challenges of protection design for power systems rich in inverter-based resources (IBRs), synthesize current industrial practices, review new approaches from recent literature, and explore future opportunities in protection. IBRs are experiencing widespread adoption across both transmission and distribution systems. When present in significant quantities, IBRs challenge the performance of many traditional protection functions. To address these issues, the industry has developed sophisticated protection schemes that involve advanced relaying techniques in highly engineered pilot projects. However, these schemes are expensive and time-consuming to develop, build, and test. Researchers have proposed a number of new approaches for protection in IBR-rich distribution systems. Despite their potential, these new approaches do not address some major shortcomings of industry approaches stemming from complexity, practical requirements, and reliability.

24 POWER TRANSMISSION AND DISTRIBUTION↗

AI-Ready Control System for the Fermilab Accelerator Complex

Reliable, high-intensity operation of the Fermilab Accelerator Complex is critical to the success of the Long-Baseline Neutrino Facility and Deep Underground Neutrino Experiment. We describe the requirements and infrastructure necessary to support routine use of artificial intelligence and machine learning (AI/ML) in the accelerator control system. Three capabilities are identified: a machine learning operations (MLOps) framework standardizing the lifecycle of AI/ML automation from data management through deployment and monitoring; a data quality framework defining and enforcing standards required to build trustworthy AI/ML applications; and workflow integration with large language models to assist physicists, engineers, and operators with information retrieval, code development, and routine analysis. Use cases spanning beam diagnostics, beam control, and support system automation illustrate the technical requirements across the complex.

43 PARTICLE ACCELERATORS↗

Grid Architecture Mapping to Understand Transformation (GAMUT): Methods and Framework Architecture

Grid architecture (GA) is a concept that was developed to address the need for a comprehensive view of power grid challenges. GA can be viewed as a relatively consistent and fixed high-level approach; however, for any instantiation of grid structures, a combinatorial explosion results from each lower-layer expansion. This constitutes the main challenge with GA—it is a grid architect’s view of the system, which might not be very informative at the implementation level. Grid Architecture Mapping to Understand Transformation (GAMUT project) seeks to bridge that gap by integrating subject matter expertise across GA structures, providing users who lack expertise in GA approaches with valuable insights and informational materials. GAMUT seeks to answer feasibility questions for the approach. System-level expectations are that a GA baseline needs to be established in order for GA to be the common framework to which any lower layer approach is tied. This report explores a potential information ingestion and documentation framework to support GAMUT. The main concepts that enable the solution domain of GAMUT are discussed, and examples are provided. The solution domain leverages already-existing technology and concepts related to GA, knowledge management, and other relevant areas. To assess GAMUT building blocks and the overall approach, a feasibility assessment is proposed, rooted in systems engineering and GA architecture evaluation concepts.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Coalition for Community-Supported Affordable Geothermal Energy Systems (C2SAGES)

The C2SAGES project evaluated the feasibility of a community geothermal system for the planned Windy Ridge affordable housing development in Hinesburg, Vermont. Led by GTI Energy with Vermont Gas Systems, LN Consulting, NREL, and Frontier Energy, the work assessed technical design, energy performance, costs, business models, community engagement, maintenance, workforce development, and permitting. The proposed system was designed to serve 100% of the development’s heating, cooling, and domestic hot water loads. Compared with a baseline using air-source heat pumps and natural gas water heating, the geothermal system was estimated to reduce HVAC and domestic hot water energy use by about 45% to 48%, lower operating and maintenance costs, and reduce 30-year life-cycle costs by 37% for Phase 1 and 10% for Phase 2. Technical testing and modeling indicated that the Windy Ridge site is suitable for a community-scale geothermal system. The project also developed borehole field layouts, piping concepts, pump house designs, controls, maintenance plans, and supporting engineering drawings. The business model analysis found that first cost, ownership structure, and customer affordability remain major deployment challenges. Utility-led maintenance and operation were viewed favorably, but traditional utility cost-recovery models may require subsidy or revised financing structures to be practical for affordable housing. Community engagement highlighted the need for clear public education, transparent financing, reliable long-term maintenance, trained technicians, and the potential to pair geothermal systems with weatherization. Overall, the report concludes that community geothermal is technically feasible and offers meaningful energy, emissions, and life-cycle cost benefits, but broader deployment will depend on workable financing models and workforce readiness.

15 GEOTHERMAL ENERGY↗

A KBase Case Study on Genome-wide Transcriptomics and Plant Primary Metabolism in Sorghum

A better understanding of the genetic and metabolic mechanisms that confer stress resistance and tolerance in plants is key to engineering new crops through advanced breeding technologies. This requires a systems biology approach that builds on a genome-wide understanding of the regulation of gene expression, plant metabolism, physiology and growth. In this study, we examine the response to drought stress in Sorghum, as we leverage the tools for transcriptomics and plant metabolic modeling we have implemented at the U.S. Department of Energy Systems Biology Knowledgebase (KBase). KBase enables researchers worldwide to collaborate and advance research by allowing them to upload private or public data into the KBase Narrative Interface, empowering them to analyze this data using a rich, extensible array of computational and data-analytics tools, and allows them to securely share scientific workflows and conclusions. We demonstrate how to use the current RNA-seq tools in KBase, applicable to both plants and microbes, to assemble and quantify long transcripts and identify differentially expressed genes effectively. More specifically, we demonstrate the utility of the platform by identifying key genes that are differentially expressed during drought-stress in Sorghum bicolor, which is an important sustainable production crop plant. We then show how to use KBase tools to predict the membership of genes in metabolic pathways and examine expression data in the context of metabolic subsystems. We demonstrate the power of the platform by making the data analysis and interpretation available to the biologists in the reproducible, re-usable, point-and-click format of a KBase Narrative thus promoting FAIR (Findable, Accessible, Interoperable and Reusable) guiding principles for scientific data management and stewardship.

59 BASIC BIOLOGICAL SCIENCES↗

Growth of Native Oxides of Niobium Thin Films for Superconducting Qubits with Etching Chemistry

Niobium thin films have been broadly applied in building superconducting qubits for quantum computing hardware. While improvements have been made by device engineering efforts, scaling the energy-sensitive quantum system requires materials study for further improvements. In this study, we performed XPS and ToF-SIMS analysis for Nb thin films across samples with different manufacturing techniques. By varying the air exposure time of the samples, this research comparatively investigates the chemical and depth profile of native oxides before and after the etching process. We observe a rapid logarithmic growth of oxide thickness across all samples and the dominant presence and growth of Niobium pentoxide in atomic percentage concentration on the surface. This comparative study provides insight into oxides mitigation strategies and correlation with qubits performance.

Lei, Zhicheng↗