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At least 955 records · Page 53

Cyberinfrastructure for the democratization of smart manufacturing

“Smart Manufacturing” is the transformation of U.S. manufacturing that results from disrupting traditional business, organizational, operating, and market structures with a radical increase in the availability and use of real-time operations data to produce value in previously inconceivable ways—a transformation process known as “manufacturing digitalization” or “manufacturing digital transformation.” There are significant economic and investment opportunities with substantially increased supply chain productivity and far better product design with process and machine precision and performance for highervalue products manufactured better, faster, cheaper with less energy and material.

Advanced sensor controls platforms and modeling↗

Computationally Aided Design of a Small-Scale Waste-Glass Melter - 20452

To provide mission support to the WTP for the vitrification of legacy nuclear tank waste at the Hanford site, a reduced-scale vitrification pilot system is being designed to process simulated and actual radioactive tank wastes. The waste stored in underground tanks will be separated into HLW and LAW fractions, where the majority is LAW by mass (approximately 90%) and HLW by activity (greater than 95%). The first tank waste to be processed at the WTP will be LAW. Because Hanford tank waste and the resultant melter feed compositions are known to vary widely, pilot-scale operations are essential to identify potential problems, provide needed data, confirm assumptions, and determine impacts to full-scale melters and off-gas systems from these different feeds. In addition, the reduced-scale melter system must be capable of quickly providing results to operations without the typically high cost of full-scale radioactive operations and to provide an engineering platform in close proximity to local operations staff. The objectives of this computational modeling effort are to produce process conditions like those encountered in the WTP LAW melters and to minimize the volume of radioactive waste necessary for the evaluations. To this end, melter design features are being explored to increase production without significantly increasing surface area or melter-glass volumes or compromising data quality. In support of these objectives, a set of computational fluid dynamic models was developed to provide insight into the flow patterns within these small melters and evaluate design features to increase production without significantly increasing glass inventory. Computed velocities were evaluated at the interface between the cold cap and the molten-glass pool and within the bulk-glass pool. Since melt rate correlates with the velocity underneath the cold cap, this information can be used to select design features that produce the highest gains. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Statistical Analysis in Support of Control Fuel Temperature for the Advanced Gas Reactor Experiments

There are four completed tests among a series of Advanced Gas Reactor (AGR) irradiation experiments that are being conducted within the Advanced Reactor Technologies (ART) Fuel Development and Qualification Program. The main objectives of the fuel experimental campaigns are to provide the necessary data on fuel performance to support fuel process development, qualify a fuel design and fabrication process for normal operation and hypothetical accident conditions, and support development and validation of fuel performance and fission product transport models and codes.1 Since this tristructural isotropic fuel is qualified to be used in high temperature gas-cooled reactors (HTGRs), it is essential that the testing conditions of fuel irradiations are designed to mimic those in the conceptual gas reactors. As a result, temperatures of the AGR test fuel have to be maintained within a specified range that is typical of the HTGRs. In each AGR capsule, the test fuel temperature is controlled independently using a variable fraction neon and helium gas mixture that fills the gap volume for each capsule. The temperature as measured by a thermocouple (TC) terminated in the graphite holder (which houses fuel compacts) is used as a feedback for the gas flow controllers. Direct temperature measurement for fuel compacts is not possible because contact between a TC head and fuel particle could lead to undesirable failures. Therefore, an ABAQUS based finite element thermal model was created to predict the daily average fuel temperatures during the entire irradiation period.2,3 It is well-known that extended exposure to neutron irradiation and high temperatures leads to changes in geometries of fuel compacts and graphite holder, which result in changes of the gas gap leading to a change in the relationship between TC and fuel temperatures. In addition, TCs are also expected to drift and sometimes fail under irradiation conditions. These facts make maintaining test fuel temperature within a specified range challenging. This paper describes how the regression analysis methods are used in conjunction of calculated fuel temperatures from early irradiation periods (when irradiation effect is relatively small) to effectively control fuel temperature for the remaining irradiation, when irradiation effect became profound. This is particularly important in the event of all TCs in a capsule fail.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Statistical Analysis in Support of Fuel Temperature Control in the Advanced Gas Reactor Experiments

There are four completed tests among a series of Advanced Gas Reactor (AGR) irradiation experiments that are being conducted within the Advanced Reactor Technologies (ART) Fuel Development and Qualification Program. The main objectives of the fuel experimental campaigns are to provide the necessary data on fuel performance to support fuel process development, qualify a fuel design and fabrication process for normal operation and hypothetical accident conditions, and support development and validation of fuel performance and fission product transport models and codes. Since this tri-structural isotropic fuel is qualified to be used in high temperature gas-cooled reactors (HTGRs), it is essential that the testing conditions of fuel irradiations are designed to mimic those in the conceptual gas reactors. As a result, temperatures of the AGR test fuel have to be maintained within a specified range that is typical of the HTGRs. In each AGR capsule, the test fuel temperature is controlled independently using a variable fraction neon and helium gas mixture that fills the gap volume for each capsule. The temperature as measured by a thermocouple (TC) terminated in the graphite holder (which houses fuel compacts) is used as a feedback for the gas flow controllers. Direct temperature measurement for fuel compacts is not possible because contact between a TC head and fuel particle could lead to undesirable failures. Therefore, an ABAQUS-based finite element thermal model was created to predict the daily average fuel temperatures during the entire irradiation period. It is well-known that extended exposure to neutron irradiation and high temperatures leads to changes in geometries of fuel compacts and graphite holder, which results in changes of the gas gap, leading to a change in the relationship between TC and fuel temperatures. In addition, TCs are expected to drift and sometimes fail under irradiation conditions. These facts make maintaining test fuel temperature within a specified range challenging. This paper describes how the regression analysis methods are used in conjunction with calculated fuel temperatures from early irradiation periods (when the irradiation effect is relatively small) to effectively control fuel temperature for the remaining irradiation (when the irradiation effect became profound). This is particularly important in the event when all TCs in a capsule fail.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Advances in Experimental Design, Optimal Control, and Learning for Uncertain Complex Systems (Final Report for AEOLUS)

The AEOLUS Center is dedicated to developing a unified optimization-under-uncertainty framework for: (1) learning predictive models from data; and (2) optimizing experiments, processes, and designs governed by these models, all driven by complex, uncertain energy systems. AEOLUS addresses the critical need for principled, rigorous, scalable, and structure-exploiting capabilities for exploring parameter and decision spaces of complex forward simulation models. This report summarizes the key highlights of our research during the period of performance.

97 MATHEMATICS AND COMPUTING↗

DIVA/DeviceEditor (DIVA) v6.0.0

The DIVA software interfaces a process in which researchers design their DNA with a web-based graphical user interface (DeviceEditor), submit their designs to a central queue, and a few weeks later receive their sequence-verified clonal constructs. Each researcher independently designs the DNA to be constructed with a web-based BioCAD tool, and presses a button to submit their designs to a central queue. Researchers have web-based access to their DNA design queues, and can track the progress of their submitted designs as they progress from "evaluation", to "waiting for reagents", to "in progress", to "complete". Researchers access their completed constructs through the central DNA repository. Along the way, all DNA construction success/failure rates are captured in a central database. Once a design has been submitted to the queue, a small number of dedicated staff evaluate the design for feasibility and provide feedback to the responsible researcher if the design is either unreasonable (e.g., encompasses a combinatorial library of a billion constructs) or small design changes could significantly facilitate the downstream implementation process. The dedicated staff then use DNA assembly design automation software to optimize the DNA construction process for the design, leveraging existing parts from the DNA repository where possible and ordering synthetic DNA where necessary. Once all requisite process inputs are available, the design progresses from "waiting for reagents" to "in progress" in the design queue. Human-readable and machine-parseable DNA construction protocols output by the DNA assembly design automation software are then executed by the dedicated staff exploiting lab automation devices wherever possible. Since the all employed DNA construction methods are sequence-agnostic, standardized (utilize the same enzymatic master mixes and reaction conditions), completely independent DNA construction tasks can be aggregated into the same multi-well plates and pursued in parallel. The resulting sets of cloned constructs can then be screened by high-throughput next-gen sequencing platforms for sequence correctness. A combination of long read-length (e.g., PacBio) and paired-end read platforms (e.g., Illumina) would be exploited depending the particular task at hand (e.g., PacBio might be sufficient to screen a set of pooled constructs with significant gene divergence). Post sequence verification, designs for which at least one correct clone was identified will progress to a "complete" status, while designs for which no correct clones were identified will progress to a "failure" status. Depending on the failure mode (e.g., no transformants), and how many prior attempts/variations of assembly protocol have been already made for a given design, subsequent attempts may be made or the design can progress to a "permanent failure" state. All success and failure rate information will be captured during the process, including at which stage a given clonal construction procedure failed (e.g., no PCR product) and what the exact failure was (e.g. assembly piece 2 missing). This success/failure rate data can be leveraged to refine the DNA assembly design process.

Plahar, Hector↗

Dynamic metrics of natural ventilation cooling effectiveness for interactive modeling

The evaluation of natural ventilation potential for cooling indoor spaces during the early design phases is of great interest to researchers and practitioners. Among various definitions and usages for natural ventilation potential (NVP) in early design evaluation, this paper reviews and identifies the key performance indicators, and proposes two new dynamic metrics—natural ventilation cooling effectiveness (NVCE) and climate potential utilization ratio (CPUR). The metrics are dynamically responsive to various design options, in both steady and transient states, allowing consideration of thermal mass. Assisting in design development processes, the metrics quantify how well indoor spaces make use of natural ventilation’s cooling capacity. Case studies are presented to demonstrate how NVCE and CPUR enable designers to evaluate the predicted performance and how to apply the information to improve building design. Finally, the results of the design iterations showed that the relationship among various design parameters should be dynamically understood in order to evaluate the performance of natural ventilation, confirming that “the more the airflow, the greater the potential,” and “the heavier the thermal mass, the greater the energy saving” were not always true.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Computationally-Aided Design of a Small-Scale Radioactive Waste Glass Melter

To provide mission support to the Hanford Waste Immobilization and Treatment Plant for the vitrification of legacy nuclear tank waste, a reduced-scale vitrification pilot system is being designed to process simulated and actual radioactive tank wastes. The tank waste will be separated into high-level waste (HLW) and low-activity waste (LAW) fractions, where the majority by mass (~90%) is LAW and by activity (>95%) is HLW. The first tank waste to be processed at the WTP will be LAW. Since Hanford tank waste and the resultant melter feed compositions are known to vary widely, pilot-scale operations are essential to identify potential problems, provide needed data, confirm assumptions, and determine impacts to full-scale melters and off-gas systems from these different feeds. In addition, the reduced-scale melter system must be capable of quickly providing results to operations without the typically high costs of radioactive operations and provide an engineering platform in close proximity to local operations staff. The objective is to produce similar process conditions to those encountered in the full-scale LAW melters and minimize the volume of radioactive waste necessary for the evaluations. To this end, melter design features are being explored to increase production without significantly increasing surface area, melter glass volumes or compromising data quality. In support of these objectives, a set of computational fluid dynamic models have been developed to provide insight into the flow patterns within these small melters and evaluate design features to increase production without significantly increasing glass inventory. Computed velocities were evaluated at the interface between the cold cap and the molten glass pool and within the bulk glass pool. A method was developed to correlate results to an estimated melt rate and down-select design features that produce the highest gains.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Computationally-Aided Design of a Small-Scale Radioactive Waste Glass Melter

To provide mission support to the Hanford Waste Immobilization and Treatment Plant for the vitrification of legacy nuclear tank waste, a reduced-scale vitrification pilot system is being designed to process simulated and actual radioactive tank wastes. The tank waste will be separated into high-level waste (HLW) and low-activity waste (LAW) fractions, where the majority by mass (~90%) is LAW and by activity (>95%) is HLW. The first tank waste to be processed at the WTP will be LAW. Since Hanford tank waste and the resultant melter feed compositions are known to vary widely, pilot-scale operations are essential to identify potential problems, provide needed data, confirm assumptions, and determine impacts to full-scale melters and off-gas systems from these different feeds. In addition, the reduced-scale melter system must be capable of quickly providing results to operations without the typically high costs of radioactive operations and provide an engineering platform in close proximity to local operations staff. The objective is to produce similar process conditions to those encountered in the full-scale LAW melters and minimize the volume of radioactive waste necessary for the evaluations. To this end, melter design features are being explored to increase production without significantly increasing surface area, melter glass volumes or compromising data quality. In support of these objectives, a set of computational fluid dynamic models have been developed to provide insight into the flow patterns within these small melters and evaluate design features to increase production without significantly increasing glass inventory. Computed velocities were evaluated at the interface between the cold cap and the molten glass pool and within the bulk glass pool. A method was developed to correlate results to an estimated melt rate and down-select design features that produce the highest gains.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Characterizing 5,000 Properties to Determine which Require Radiological Remediation - 19152

The Port Hope Area Initiative (PHAI) is a federal environmental clean-up program. Its mandate is the remediation and local, long-term, safe management of approximately 1.7 million cubic metres of historic low-level radioactive waste (hLLRW) in the adjacent communities of Port Hope and Port Granby in Southern Ontario, Canada. The PHAI is being undertaken by Canadian Nuclear Laboratories (CNL), on behalf of Atomic Energy of Canada Limited, a federal Crown corporation. It is currently one of the largest environmental remediation projects in Canada. Conducting work safely, while delivering the PHAI on time and within budget, is CNL's number one priority. The PHAI is being carried out as two projects - the Port Hope Project and the Port Granby Project. The Port Hope Project is the larger of the two and includes the cleanup of approximately 1.7 million cubic metres of hLLRW from various locations within the community. The Port Hope Project includes a unique and important component - the Property Radiological Survey. This survey involves the interior and exterior investigation of approximately 4,800 small-scale sites (SSS) - primarily residential - in the Municipality of Port Hope for the presence or absence of hLLRW. This paper provides an overview of the characterization, delineation and design for remediation of historic LLRW for the SSS, a grouping of sites within the municipality comprised of residential properties, municipal properties including municipal road allowances, private road allowances and temporary storage sites. Comprising over 4,800 parcels of land, a robust remedial process was designed to identify, characterize, delineate and remediate interior and exterior hLLRW contamination found in soils and building materials. The process adheres to the framework of the Port Hope Project Waste Nuclear Substance Licence (License) and its associated governance frameworks and regulatory requirements [1]. The overall goal is for CNL to be able to issue the owner of each parcel of land a Compliance Letter stating that the site meets the PHAI Clean-up Criteria, either after completion of characterization (if no hLLRW is identified) or after completion of remediation and verification. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Community Planning for Solar: Toolkit Overview

UMass Clean Energy Extension (CEE) and its partners have designed the Community Planning for Solar Toolkit to help municipalities in Massachusetts and throughout the Northeast proactively plan for solar PV development in their communities. The tools and processes are designed with rural and suburban communities in mind, though some of the tools may also apply to urban settings. Community Planning for Solar empowers community residents and officials to take the lead in solar development by providing communities with the resources that can help them to: (1) Identify and prioritize locations in the community for solar development; (2) Evaluate various solar financing options and provide guidance on community benefits that best match community goals and needs; (3) Assess their community's unique resources, solar development options, goals, and preferences regarding solar development; (4)Develop a Community Solar Action Plan.

14 SOLAR ENERGY↗

Science of Scale-Up: Accelerating chemical manufacturing technology development workshop report

The Science of Scale-Up: Accelerating chemical manufacturing technology development workshop report outlines key insights and actionable recommendations for accelerating the scale-up of disruptive chemical manufacturing technologies. Convened in October 2024, the workshop brought together approximately fifty experts from academia, industry, national laboratories, and government agencies to address the barriers and solutions for maturing technologies from proof-of-concept to commercialization. The report identifies seven critical themes for enabling faster scale-up. These themes were explored through general discussions and breakout sessions focused on three specific chemical manufacturing technologies—electrochemical, thermochemical, and biological conversion processes. The findings emphasize the importance of interdisciplinary collaboration, robust funding mechanisms, and shared resources to overcome technical barriers and accelerate technology deployment. The report also highlights technology-specific challenges and opportunities, including the need for advanced materials, scalable manufacturing processes, and integrated testing environments. For electrochemical manufacturing processes, durability and material optimization are key priorities, while thermochemical processes require novel reactor designs and better supply chain integration. Biological conversion processes face hurdles in strain engineering, reactor design, and process integration. Across all technologies, the workshop emphasized the importance of leveraging computational tools, standardized protocols, and collaborative networks to address knowledge gaps and technical barriers. By acting on these insights, stakeholders can reduce the timeline for scaling up critical chemical manufacturing technologies, ensuring their timely impact on manufacturing competitiveness, and environmental sustainability.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

ML-GA

ML-GA is a software that can be used to expedite design optimization process combining machine learning and genetic algorithm approaches. It employs a machine learning (ML) model (any ML algorithm can be incorporated) to predict the quality (merit) of a design from the input parameters. Then, a stochastic global optimization genetic algorithm (GA) is used, with the machine learning model as the objective function, to optimize the input parameters based on the merit function. ML-GA is scalable to higher computational platforms like supercomputers and clusters enabling optimization to be performed in significantly short time frames (e.g., in a day).

PAL, PINAKI↗

Denoising diffusion algorithm for inverse design of microstructures with fine-tuned nonlinear material properties

Here we introduce a denoising diffusion algorithm to discover microstructures with nonlinear fine-tuned properties. Denoising diffusion probabilistic models are generative models that use diffusion-based dynamics to gradually denoise images and generate realistic synthetic samples. By learning the reverse of a Markov diffusion process, we design an artificial intelligence to efficiently manipulate the topology of microstructures to generate a massive number of prototypes that exhibit constitutive responses sufficiently close to designated nonlinear constitutive behaviors. To identify the subset of microcstructures with sufficiently precise fine-tuned properties, a convolutional neural network surrogate is trained to replace high-fidelity finite element simulations to filter out prototypes outside the admissible range. Results of this study indicate that the denoising diffusion process is capable of creating microstructures of fine-tuned nonlinear material properties within the latent space of the training data. More importantly, this denoising diffusion algorithm can be easily extended to incorporate additional topological and geometric modifications by introducing high-dimensional structures embedded in the latent space. Numerical experiments are conducted on the open-source mechanical MNIST data set (Lejeune, 2020). Consequently, this algorithm is not only capable of performing inverse design of nonlinear effective media, but also learns the nonlinear structure–property map to quantitatively understand the multiscale interplay among the geometry, topology, and their effective macroscopic properties.

42 ENGINEERING↗

Design of the 650 MHz High Beta Prototype Cryomodule for PIP-II at Fermilab

The Proton Improvement Plan II (PIP-II) is the first U.S. accelerator project that will have significant contributions from international partners. The prototype High Beta 650 MHz cryomodule (pHB650 CM) is designed by an integrated design team, consisting of Fermilab (USA), CEA (France), UKRI-STFC (UK), and RRCAT (India). The manufacturing & assembly of this prototype cryomodule will be done at Fermilab, whereas the production cryomodules will be manufactured and/or assembled by UKRI-STFC, RRCAT, or Fermilab. Similar to the prototype Single Spoke Resonator 1 cryomodule (pSSR1 CM), this cryomodule is based on a strong-back at room temperature supporting the coldmass. The pSSR1 CM led to significant lessons being learnt on the design, procurement, and assembly processes. These lessons were incorporated into the design and processes for the pHB650 CM. Amongst many challenges faced, the main challenges of the pHB650 CM design were to make the cryomodule compatible to overseas transportation and to design components that can be procured in USA, Europe, and India.

43 PARTICLE ACCELERATORS↗

Spatially resolved x-ray detection with photonic crystal scintillators

We study the self-collimation phenomenon in photonic crystals (PhC) of wide bandgap materials for ultra-fast and high spatial resolution x-ray detection. We work on various heavy inorganic scintillators: BaF 2 , GaN, ZnO, CsI:Tl, NaI:Tl, LYSO, WO 4 compounds, and plastic scintillators. Conventional scintillator detectors do not rely on a direct detection mechanism; hence, they require intricate design and fabrication processes. We offer a PhC design to observe self-collimation phenomena and overcome the ongoing spatial resolution challenges with these types of materials. We investigate the photonic band diagrams and iso-frequency contours. Fourier transforms based on finite-difference time-domain and frequency domain simulations are done for verifying and analyzing the self-collimation with the selected material. Light extraction efficiency at the PhC–air interface, depending on the truncation distance from the excitation point, is measured. Beam divergence values are calculated at 1 mm propagation distance. The vertical field profiles are obtained to observe the confinement. For the spatial resolution analysis, cross-sectional beam profiles have been examined. Furthermore, Gaussian envelopes are fitted to beam profiles for a consistent data analysis, and full-width-at-half-maximum values are considered. As a result, we theoretically prove and demonstrate the spatially resolved x-ray detection at the sub-micrometer level for a wide range of scintillator materials.

36 MATERIALS SCIENCE↗

DEVELOPMENT OF A PROTOTYPE 197 MHz CRAB CAVITY FOR THE ELECTRON-ION COLLIDER AT JLAB

Thomas Jefferson National Accelerator Facility (JLab) is currently developing a prototype 197MHz Radio-Frequency Dipole (RFD) crab cavity as part of the Electron-Ion Collider (EIC) to be built at Brookhaven National Laboratory (BNL). Cryomodules containing these cavities will be part of the Hadron Storage Ring (HSR) of the EIC. The prototype cavity is constructed primarily of formed niobium sheets of thickness 4.17mm, with machined niobium parts used as interfaces where tight tolerancing is required. The cavity?s large size and complex features present sever-al challenges in fabrication, tuning, and RF testing. Structural and forming analyses have been carried out to optimize the design and fabrication processes. An overview of the design phase and the current state of fabrication are presented in this paper.

Huque, Naeem↗

Catalysis Driven by Confined Hot Carriers at the Liquid/Metal/Zeolite Interface

In chemical industry controlling the activity and selectivity of a chemical conversion process is of immense importance. Traditionally, dissipation of thermal energy drives transformation of reactants, which may lead to formation of a variety of products; it remains a key challenge to design a process that dissociation and formation of specific chemical bonds can be triggered to form certain desirable products with very high selectivity, preferably at low temperatures. Introduction of light-sensitive solid materials into catalysis provides a powerful, alternate strategy for this purpose.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗