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DOE OSTI2021

Controlled Single-Electron Transfer via Metal–Ligand Cooperativity Drives Divergent Nickel-Electrocatalyzed Radical Pathways

Electrocatalysis enables the construction of C-C bonds under mild conditions via controlled formation of carbon-centered radicals. For sequences initiated by alkyl halide reduction, coordinatively unsaturated Ni complexes commonly serve as single-electron transfer agents, giving rise to the foundational question of whether outer- or inner-sphere electron transfer oxidative addition prevails in redox mediation. Indeed, rational design of electrochemical processes requires the discrimination of these two electron transfer pathways, as they can have outsized effects on the rate of substrate bond activation and thus impact radical generation rates and downstream product selectivities. We present results from combined synthetic, electroanalytical, and computational studies that examine the mechanistic differences of single electron transfer to alkyl halides imparted by Ni metal-ligand cooperativity. Electrogenerated reduced Ni species, stabilized by delocalized spin density onto a redox-active tpyPY2Me polypyridyl ligand, activates alkyl iodides via outer-sphere electron transfer, allowing for the selective activation of alkyl iodide substrates over halogen atom donors and the controlled generation and sequestration of electrogenerated radicals. In contrast, the Ni complex possessing a redox-innocent pentapyridine congener activates the substrates in an inner-sphere fashion owning to a purely metal-localized spin, thereby activating both substrates and halogen atom donors in an indiscriminate fashion, generating a high concentration of radicals and leading to unproductive dimerization. Overall, our data establish that controlled electron transfer via Ni-ligand cooperativity can be used to limit undesired radical recombination products and promote selective radical processes in electrochemical environments, providing a generalizable framework for designing redox mediators with distinct rate and potential requirements.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2016

Aerodynamic optimization of supersonic compressor cascade using differential evolution on GPU

Differential Evolution (DE) is a powerful stochastic optimization method. Compared to gradient-based algorithms, DE is able to avoid local minima but requires at the same time more function evaluations. In turbomachinery applications, function evaluations are performed with time-consuming CFD simulation, which results in a long, non affordable, design cycle. Modern High Performance Computing systems, especially Graphic Processing Units (GPUs), are able to alleviate this inconvenience by accelerating the design evaluation itself. In this work we present a validated CFD Solver running on GPUs, able to accelerate the design evaluation and thus the entire design process. An achieved speedup of 20x to 30x enabled the DE algorithm to run on a high-end computer instead of a costly large cluster. The GPU-enhanced DE was used to optimize the aerodynamics of a supersonic compressor cascade, achieving an aerodynamic loss minimization of 20%.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Idaho National Laboratory Data Acquisition And Processing System

The INLDAS data acquisition and processing system is designed to develop prototype measurements and real-time processing techniques. The INLDAS hardware and firmware currently consists of National Instruments • NI-DAQmx 14.1 • cDAQ-9184 • 9205 • 9211 INLDAS can perform of standard data acquisition functions as well as novel functions and real-time processing algorithms. There are 3 acquisition modes to choose from: • Continuous mode runs when the user hits start, processing data and logging it to file • SWTrigger mode waits for one or more predefined triggers before acquiring data. It will buffer data as well, so it can record data that happened shortly before the trigger • Wakeup mode waits on predefined timers. When a time goes off, it acquires a preset amount of data There are also 3 Data Processing Modes • Normal mode does no processing besides the rolling average • FFT Mode Performs an FFT on incoming data every time the time window has elapsed • STFFT mode

Smith, JamesA↗

DOE OSTI2019

PFLOTRAN: Reactive Flow & Transport Code for Use on Laptops to Leadership-Class Supercomputers. In: Groundwater Reactive Transport Models

PFLOTRAN, a next-generation reactive flow and transport code for modeling subsurface processes, has been designed from the ground up to run efficiently on machines ranging from leadership-class supercomputers to laptops. Based on an object-oriented design, the code is easily extensible to incorporate additional processes. It can interface seamlessly with Fortran 9X, C and C++ codes. Domain decomposition parallelism is employed, with the PETSc parallel framework used to manage parallel solvers, data structures and communication. Features of the code include a modular input file, implementation of high-performance I/O using parallel HDF5, ability to perform multiple realization simulations with multiple processors per realization in a seamless manner, and multiple modes for multiphase flow and multicomponent geochemical transport. Chemical reactions currently implemented in the code include homogeneous aqueous complexing reactions and heterogeneous mineral precipitation/dissolution, ion exchange, surface complexation and a multirate kinetic sorption model. PFLOTRAN has demonstrated petascale performance using 217 processor cores on problems composed of over 2 billion degrees of freedom. The code is currently being applied to simulate uranium transport at the Hanford 300 Area and CO2 sequestration in deep geologic formations.

carbon sequestration↗

DOE OSTI2017

Human factors engineering process to support human-system interface design in control room modernization - 351

The primary objective of the United States (U.S.) Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) program is to sustain operation of the existing commercial nuclear power plants (NPPs) through a multi-pathway approach in conducting research and development (R and D). The Advanced Instrumentation, Information, and Control (II and C) System Technologies pathway conducts targeted R and D to address aging and reliability concerns with legacy instrumentation and control (I and C) and other information systems in existing U.S. NPPs. Control room modernization is an important part following this pathway, and human factors experts at Idaho National Laboratory (INL) have been involved in conducting R and D to support migration of new digital main control room (MCR) technologies from legacy analog and legacy digital I and C. This paper describes a human factors engineering (HFE) process that supports human-system interface (HSI) design in MCR modernization activities, particularly with migration of old digital to new digital I and C. The process described in this work is an expansion from the LWRS Report INL/EXT-16-38576, and is a requirements-driven approach that aligns with NUREG-0711 requirements. The work described builds upon the existing literature by adding more detail around key tasks and decisions to make when transitioning from HSI Design into Verification and Validation (V and V). The overall objective of this process is to inform HSI design and elicit specific, measurable, and achievable human factors criteria for new digital technologies. Upon following this process, utilities should have greater confidence with transitioning from HSI design into V and V. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2023

Novel Transformational Membranes and Process for CO 2 Capture from Flue Gas (FE0031731)

The objectives of this project are to develop a cost-effective design and fabrication process for a novel transformational membrane and its membrane modules that capture CO 2 from flue gas. Optimization of the novel transformational membrane, scale-up of the membrane to a prototype size of about 20" wide in continuous roll-to-roll fabrication, and construction and testing of a skid for the integrated membrane process will be performed. For the design of this membrane, we use a cost-effective polymer support and coat a thin top layer of the membrane. The simplicity of this membrane design offers a low cost for the membrane element in commercial spiral-wound (SW) configuration (<$2.00/ft 2 or $21.5/m 2 ). The prototype membrane will be used to fabricate 6 pilot-size membrane modules (each about 20" length, 3 modules each at the commercial-size diameter of 8 inches with 35 m 2 membrane area for Stage 1 and 3 modules each at 5-inch diameter with 12 m 2 membrane area for Stage 2) for testing with simulated flue gas at OSU and with actual flue gas at the National Carbon Capture Center, Wilsonville, AL using the skid to capture the CO 2 (at 60 – 90%) with at least 95% CO 2 purity. The prototype membrane modules will be in commercial SW configuration with a minimal pressure drop (<0.103 bar/meter (1.5 psi/meter)). These objectives have been achieved successfully.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2018

Electrically-Assisted Tubing Processes for Enhancing Manufacturability of Oxide Dispersion Strengthened Structural Materials for Nuclear Reactor Applications

The overall goal of this project is to enhance the formability of Nanostructured Ferritic Alloys (NFAs) such that high-strength thin-walled claddings can be successfully and economically manufactured for use in future nuclear reactors. Specifically, four objectives were identified: Objective #1 – to achieve a good understanding of the mechanical behavior and resulting microstructure of 14YWT made from the powder form subjected to various Electrically- Assisted (EA) loading conditions. Objective #2 – to conduct EA-flat rolling of 14YWT completed and the prioritization/selection of two alternative designs of EA tube rolling processes. Objective #3 – to design and assemble a new EA tube rolling machine. Objective #4 – to conduct rolling using the new EA rolling machine. The above objectives were achieved and the findings can be further applied to establish other innovative fabrication processes. Specifically, the major accomplishments are summarized as: The use of an EA forming process was investigated to reduce the forming force of ODS ferritic steels. The effect of a continuous electric current on 14YWT during plastic deformation was evaluated. EA uniaxial tension tests show that the electric current is able to reduce the flow stress of 14YWT. 14YWT exhibits a ductility minimum at a current density of 34.5 A/mm2 which is consistent with fractography results. Hardness measurements and TEM results indicate that oxide particles are stable during the EA process. By following the tests, microstructure analysis was performed on the sample in its as-received state and after current treatment. The microstructures are stable when subjected to high current density. The related thermal model was developed to predict the Joule heating temperatures. The temperatures were compared with the experimental results. At last, a temperature-dependent hardening model was used to explore the mechanisms acting during EA deformation. Since the model can accurately predict the yield strength of 14YWT under EA conditions without the incorporation of non-thermal effects, it can be concluded that the reduction in yield strength is due to the Joule heating generated under continuous current loading conditions. An oven-heated pure thermal tension test was conducted to confirm this conclusion. The new EA tube rolling machine has been completely developed. The related work includes: (1) forming process design; (2) analysis of the effect of roll-tube contact geometry on rolling force; (3) analysis of machine performance under mechanical loading; (4) design of machine electrical setting path and insulation; (5) multi-pass process analysis; (6) design of power transmission system (axial/radial/torque feeding mechanisms), roll bearing system, cooling system, workpiece feeding mechanism, and other related mechanical connection support components; (7) design and optimization of roll profiles/dimensions; (8) analysis and simulation of the rolling process; (9) development of engineering drawings and fabrication; (10) assembly and calibration of the EA tube rolling machine; (11) design and integration of the electrical control system; (12) hardware integration for high power supply electrically-assisted rolling process; (13) induction heating system integration; (14) experimental tests for the new rolling process. Through the process from conceptual design to final machine calibration and experimental tests, there are many technical and physical works that have been implemented and improved for the best performance of the innovative prototype.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2019

Design standardization of unit operations for reducing the capital intensity and cost of small‐scale chemical processes

Abstract A methodology is proposed to reduce the cost and capital intensity of small‐scale chemical processes by creating new opportunities for economies of numbers through standardizing the equipment designs across multiple processes. We depart from asynchronous design of single‐processes and adopt a common‐functionality based simultaneous design of multiple processes that use similar unit operations. A generalized cost function is used to appropriately balance the trade‐offs between economies of scale and economies of numbers. An optimization‐based framework for design standardization is developed and illustrated using two case studies. The first involves the simultaneous synthesis of methanol and ammonia processes, and the second addresses the optimal synthesis of multi‐column natural gas liquid (NGL) fractionation processes for different natural gas sources. We observe that considerable reduction in capital intensity of small‐scale processes is possible through equipment standardization.

Arora, Akhil↗

DOE OSTI2023

Robust Parameter Design on Dual Stochastic Response Models With Constrained Bayesian Optimization

In engineering system design, minimizing the variations of the quality measurements while guaranteeing their overall quality up to certain levels, namely the robust parameter design (RPD), is crucial. Recent works have dealt with the design of a system whose response-control variables relationship is a deterministic function with a complex shape and function evaluation is expensive. In this work, we propose a Bayesian optimization method for the RPD of stochastic functions. Dual stochastic response models are carefully designed for stochastic functions. The heterogeneous variance of the sample mean is addressed by the predictive mean of the log variance surrogate model in a two-step approach. We establish an acquisition function that favors exploration across the feasible and optimality-improvable regions to effectively and efficiently solve the stochastic constrained optimization problem. Further, the performance of our proposed method is demonstrated by the extensive numerical and case studies. Note to Practitioners-Many manufacturing processes involve undesirable variations, which create variations in the final products. For example, many emerging manufacturing processes, such as nanomanufacturing, involve complex physical and chemical dynamics and transformation, creating variations in the manufacturing output. In such processes, it is crucial to design the manufacturing processes or products so that they have minimum variations in their quality. Meanwhile, it is also important to maintain the overall quality of the designed processes or products. Furthermore, acquiring data from many advanced manufacturing processes is often very costly, especially in the designing stage. In this work, we propose a data-driven method that automatically finds the best setting of manufacturing processes or products with the minimum variations of quality and a given constraint on the average quality satisfied. Our proposed method is used before conducting every experiment; It analyzes the historical data from previous experiments and provides a setting to be used in the next experiment. Our proposed method efficiently utilizes the historical data, and thus finds the best robust setting by conducting only a small number of experiments.

42 ENGINEERING↗

DOE OSTI2024

High-Throughput Computing: Case Study of Medical Image Processing Applications

HPC is designed for large-scale simulations using monolithic codes of tightly coupled processes highly optimized to deliver decreased time to solution. Medical image processing is not a traditional field of HPC. Similar to AI applications, medical image processing parses large datasets, typically multiple times, to support a variety of studies for classification, diagnosis or monitoring purposes. The convergence of AI, HPC and Big Data encouraged more fields using image processing to transition to HPC. However, not all applications benefit from the same optimizations. In this paper we focus on high throughput medical image processing applications that analyze a huge dataset of small MRI images and that require HPC systems to decrease the time of parsing the entire dataset and not individual MRIs. We show in this research the performance of running SLANT, an image processing application for a whole brain segmentation, on large-scale systems and highlight performance limitations. We present optimizations prioritizing throughput that exhibit a 3.5x speed-up on the Summit Supercomputer that can be used as a baseline for building a high-throughput execution framework for other HPC systems.

Predescu, Maria↗

DOE OSTI2015

A Statistical Perspective on Highly Accelerated Testing

Highly accelerated life testing has been heavily promoted at Sandia (and elsewhere) as a means to rapidly identify product weaknesses caused by flaws in the product's design or manufacturing process. During product development, a small number of units are forced to fail at high stress. The failed units are then examined to determine the root causes of failure. The identification of the root causes of product failures exposed by highly accelerated life testing can instigate changes to the product's design and/or manufacturing process that result in a product with increased reliability. It is widely viewed that this qualitative use of highly accelerated life testing (often associated with the acronym HALT) can be useful. However, highly accelerated life testing has also been proposed as a quantitative means for "demonstrating" the reliability of a product where unreliability is associated with loss of margin via an identified and dominating failure mechanism. It is assumed that the dominant failure mechanism can be accelerated by changing the level of a stress factor that is assumed to be related to the dominant failure mode. In extreme cases, a minimal number of units (often from a pre-production lot) are subjected to a single highly accelerated stress relative to normal use. If no (or, sufficiently few) units fail at this high stress level, some might claim that a certain level of reliability has been demonstrated (relative to normal use conditions). Underlying this claim are assumptions regarding the level of knowledge associated with the relationship between the stress level and the probability of failure. The primary purpose of this document is to discuss (from a statistical perspective) the efficacy of using accelerated life testing protocols (and, in particular, "highly accelerated" protocols) to make quantitative inferences concerning the performance of a product (e.g., reliability) when in fact there is lack-of-knowledge and uncertainty concerning the assumed relationship between the stress level and performance. In addition, this document contains recommendations for conducting more informative accelerated tests.

42 ENGINEERING↗

DOE OSTI2019

Life-Cycle Approaches in Computerized Vehicle Design and Additive Technology

Computer engineering permits the creation of models closely matching actual processes and vehicle designs. Production costs may be significantly reduced, while additive technologies permit customized production, with minimal expenditure of time and materials in development and prototyping. Such technologies may expediently be used in digital design of vehicles, taking account of the complete product life cycle.

42 ENGINEERING↗

DOE OSTI2023

Understanding structure-processing relationships in metal additive manufacturing via featurization of microstructural images

Understanding and predicting accurate property-structure-processing relationships for additively manufactured components is important for both forward and inverse design of robust, reliable parts and assemblies. While direct mapping of process parameters to properties is sometimes plausible, it is often rendered difficult due to poor microstructural control. Exploring the direct relationship between processing conditions and microstructural features can thus provide significant physical insights and aid the overall design process. Here, in this study, we develop an automated high-throughput framework to simulate an uncertainty-aware additive manufacturing (AM) process, characterize microstructural images, and extract meaningful features/descriptors. A kinetic Monte Carlo (KMC) based model of the AM process is used to simulate microstructural evolution for a diverse set of experimentally relevant processing conditions. We perform a parametric study to explore the relationship between microstructural features and processing conditions. Our results indicate that a many-to-one mapping can exist between processing conditions and typical descriptors; therefore, multiple descriptors are thus necessary to unambiguously represent microstructural images. Our work provides crucial quantitative and qualitative in-formation that would aid in the selection of features for microstructural images. Featurized microstructures could then be utilized to build data-driven models for predictive control of microstructures and thereby properties of additively manufactured components.

36 MATERIALS SCIENCE↗

DOE OSTI2017

Neutron residual stress measurement and numerical modeling in a curved thin-walled structure by laser powder bed fusion additive manufacturing

Severe residual stresses in metal parts made by laser powder bed fusion additive manufacturing processes (LPBFAM) can cause both distortion and cracking during the fabrication processes. Limited data is currently available for both iterating through process conditions and design, and in particular, for validating numerical models to accelerate process certification. In this work, residual stresses of a curved thin-walled structure, made of Ni-based superalloy Inconel 625™ and fabricated by LPBFAM, were resolved by neutron diffraction without measuring the stress-free lattices along both the build and the transverse directions. The stresses of the entire part during fabrication and after cooling down were predicted by a simplified layer-by-layer finite element based numerical model. The simulated and measured stresses were found in good quantitative agreement. The validated simplified simulation methodology will allow to assess residual stresses in more complex structures and to significantly reduce manufacturing cycle time.

36 MATERIALS SCIENCE↗

DOE OSTI2017

An environmentally friendly ball milling process for recovery of valuable metals from e-waste scraps

Highlights: • A new ball milling process was successfully developed for recovery of metals from e-waste. • The process produce soluble metallic compound with dry ball milling and benefits the leaching process. • Precious metals were successfully separated from base metals during the process. • Mechanism of the mechanochemical reactions was proposed. - Abstract: The present study reports a mechanochemical (MC) process for effective recovery of copper (Cu) and precious metals (i.e. Pd and Ag) from e-waste scraps. Results indicated that the mixture of K{sub 2}S{sub 2}O{sub 8} and NaCl (abbreviated as K{sub 2}S{sub 2}O{sub 8}/NaCl hereafter) was the most effective co-milling reagents in terms of high recovery rate. After co-milling with K{sub 2}S{sub 2}O{sub 8}/NaCl, soluble metallic compounds were produced and consequently benefit the subsequent leaching process. 99.9% of Cu and 95.5% of Pd in the e-waste particles could be recovered in 0.5 mol/L diluted HCl in 15 min. Ag was concentrated in the leaching residue as AgCl and then recovered in 1 mol/L NH{sub 3} solution. XRD and XPS analysis indicated that elemental metals in the raw materials were transformed into their corresponding oxidation state during ball milling process at low temperature, implying that solid–solid phase reactions is the reaction mechanism. Based on the results and thermodynamic parameters of the probable reactions, possible reaction pathways during ball milling were proposed. Suggestion on category of e-waste for ball milling process was put forward according to the experiment results. The designed metal recovery process of this study has the advantages of highly recovery rate and quick leaching speed. Thus, this study offers a promising and environmentally friendly method for recovering valuable metals from e-waste.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2016

Test results of the LARP Nb$_3$Sn quadrupole HQ03a

The US LHC Accelerator Research Program (LARP) has been developing $Nb_3Sn$ quadrupoles of progressively increasing performance for the high luminosity upgrade of the Large Hadron Collider. The 120 mm aperture High-field Quadrupole (HQ) models are the last step in the R&D phase supporting the development of the new IR Quadrupoles (MQXF). Three series of HQ coils were fabricated and assembled in a shell-based support structure, progressively optimizing the design and fabrication process. The final set of coils consistently applied the optimized design solutions, and was assembled in the HQ03a model. Furthermore, this paper reports a summary of the HQ03a test results, including training, mechanical performance, field quality and quench studies.

43 PARTICLE ACCELERATORS↗

DOE OSTI2015

Nitrogen mass transfer models for plasma-based low-energy ion implantation

The nitrogen mass transfer process in plasma-based low-energy ion implantation (PBLEII) is theoretically and experimentally studied in order to explore the process mechanism of PBLEII and therefore to optimize the apparatus design and the process conditions. An electron cyclotron resonance (ECR) microwave discharge generates the nitrogen plasma with a high density of 10{sup 11}–10{sup 12} ions/cm{sup 3}, which diffuses downstream to the process chamber along the divergent magnetic field. The nitrogen ions in the plasma implant into the surface and transport to the matrix of an austenitic stainless steel under the low negative pulsed bias of −2 kV at a process temperature of 400 °C. A global plasma model is used to simulate the ECR microwave plasma discharge for a range of working pressures and microwave powers. The fluid models are adopted to calculate the plasma downstream diffusion, the sheath expansion and the low-energy ion implantation on the surface. A nonlinear kinetic discrete model is established to describe the nitrogen transport in the austenitic stainless steel and the results are compared with the experimental measurements. Under an average implantation current density of 0.3–0.6 mA/cm{sup 2}, the surface nitrogen concentration in the range from 18.5 to 29 at. % is a critical factor for the nitrogen transport in the AISI 304 austenitic stainless steel by PBLEII, which accelerates the implanted nitrogen diffusion inward up to 6–12 μm during a nitriding time of 4 h.

36 MATERIALS SCIENCE↗

DOE OSTI2016

Implementation of flowsheet change to minimize hydrogen and ammonia generation during chemical processing of high level waste in the Defense Waste Processing Facility

Testing was completed to develop a chemical processing flowsheet for the Defense Waste Processing Facility (DWPF), designed to vitrify and stabilize high level radioactive waste. DWPF processing uses a reducing acid (formic acid) and an oxidizing acid (nitric acid) to rheologically thin the slurry and complete the necessary acid base and reduction reactions (primarily mercury and manganese). Formic acid reduces mercuric oxide to elemental mercury, allowing the mercury to be removed during the boiling phase of processing through steam stripping. In runs with active catalysts, formic acid can decompose to hydrogen and nitrate can be reduced to ammonia, both flammable gases, due to rhodium and ruthenium catalysis. Replacement of formic acid with glycolic acid eliminates the generation of rhodium- and ruthenium-catalyzed hydrogen and ammonia. In addition, mercury reduction is still effective with glycolic acid. Hydrogen, ammonia and mercury are discussed in the body of the report. Ten abbreviated tests were completed to develop the operating window for implementation of the flowsheet and determine the impact of changes in acid stoichiometry and the blend of nitric and glycolic acid as it impacts various processing variables over a wide processing region. Three full-length 4-L lab-scale simulations demonstrated the viability of the flowsheet under planned operating conditions. The flowsheet is planned for implementation in early 2017.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗