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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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DOE OSTI2016

Pre-commercial Demonstration of Direct Non-iterative State Estimator for Operational Use of Synchrophasor Management Systems

The objective of this project was to demonstrate functionality and performance of a Direct Non-iterative State Estimator (DNSE) integrated with NYPA’s Energy Management System (EMS) and with enhanced Real Time Dynamics Monitoring System (RTDMS) synchrophasor platform from Electric Power Group (EPG). DNSE is designed to overcome a major obstacle to operational use of Synchro-Phasor Management Systems (SPMS) by providing to synchrophasor management systems (SPMS) applications a consistent and a complete synchrophasor data foundation in the same way that a traditional EMS State Estimator (SE) provides to EMS applications. Specifically, DNSE is designed to use synchrophasor measurements collected by a central PDC, Supervisory Control and Data Acquisition (SCADA) measurements, and Energy Management System (EMS) network model, to obtain the complete state of the utility’s operating model at rates that are close to the synchrophasor data rates. In this way, the system is comprehensive in that it does not only cover the part of the network that is “visible” via synchrophasors, but also the part that is only “visible” through the SCADA measurements. Visualization needs associated with the use of DNSE results are fulfilled through suitably enhanced Real Time Dynamics Monitoring System (RTDMS), with the enhancements implemented by EPG. This project had the following goals in mind: To advance the deployment of commercial grade DNSE software application that relies on synchrophasor and SCADA data ; Apply DNSE at other utilities, to address a generic and fundamental need for “clean” operational data for synchrophasor applications; Provide means for “live” estimated data access by control system operators; Enhance potential for situational awareness through full system operational model coverage; Sub-second execution rate of the Direct Non-iterative State Estimator, eventually at a near-phasor data rate execution speed, i.e. < 0.1 sec. Anticipated benefits from this projects are: Enhanced reliability and improvements in the economic efficiency of bulk power system planning and operations; Providing “clean” data to other synchrophasor applications; Enhancement of situational awareness by providing the full operational model updated at near synchrophasor rate; A production-grade software tool that incorporate synchrophasor and SCADA data; Provides a basis for development of next generation monitoring and control applications, based on both SCADA and PMU data. Quanta Technology (QT) team worked in collaboration with Electric Power Group (EPG) whose team has enhanced its commercial Real Time Dynamics Monitoring System (RTDMS) to accommodate the requirements posed by DNSE application. EPG also provided its ePDC and Model-less Data Conditioning (PDVC) software for integration with DNSE+. QT developed the system requirements for DNSE; developed system architecture and defined interfaces between internal DNSE components. The core DNSE algorithm with all surrounding interfaces was named DNSE+. Since the DNSE development was done in a simulated system environment, QT used its PMU simulator that was enhanced during this project for development and factory acceptance testing (FAT). SCADA data in this stage was simulated by commercial PSS/e software. The output of DNSE are estimates of System states in C37.118-2 format, sent to RTDMS for further processing and display. As the number of these states is large, it was necessary to expand the C37.111-2 standard to accommodate large data sets. This enhancement was implemented in RTDMS. The demonstration of pre-production DNSE technology was done at NYPA using streaming field data from NYPA PMUs and from its RTUs through their SCADA system. NYPA provided ICCP interface as well as Common Information Model (CIM). The relevance of the DNSE+ application is that it provides state estimation of the power system based on hybrid set of data, consisting of both available PMU data and SCADA measurements. As this is a direct, non-iterative method of calculation of the system states, if does not suffer from convergence issues which is potential problem for conventional state estimators. Also, it can take any available PMU measurements, so it does not need to have a high percentage of PMU coverage needed in the case of Linear State Estimator. As the DNSE calculates synchrophasors of the system states (both phase and absolute value) as sub-second rate, this application can provide a basis for development of next generation of applications based both on SCADA and PMU data.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Autonomous Grid Support Functionality in Variable-Speed Drive-Based End-Use Loads

High penetration of inverter-based resources into power systems causes lower inertia, and it becomes more challenging to maintain grid stability during contingency events. While conventional demand response and shedding at the load side suffer from slow response, impact by unavailability, and issues from communication, variable-speed drives (VSDs) are becoming strong candidates for fast frequency response (FFR) thanks to their fast response and reduced user impact from variable power adjustment capability. In this letter, we propose an autonomous frequency support control method for a residential refrigerator with a VSD, a promising target small end-use load for FFR. We analyze the effect of the proposed controller on grid stability, and we verify the performance through laboratory experiments with a commercially available refrigerator.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2014

Rapid evaluation and quality control of next generation sequencing data with FaQCs

Background: Next generation sequencing (NGS) technologies that parallelize the sequencing process and produce thousands to millions, or even hundreds of millions of sequences in a single sequencing run, have revolutionized genomic and genetic research. Because of the vagaries of any platform's sequencing chemistry, the experimental processing, machine failure, and so on, the quality of sequencing reads is never perfect, and often declines as the read is extended. These errors invariably affect downstream analysis/application and should therefore be identified early on to mitigate any unforeseen effects. Results: Here we present a novel FastQ Quality Control Software (FaQCs) that can rapidly process large volumes of data, and which improves upon previous solutions to monitor the quality and remove poor quality data from sequencing runs. Both the speed of processing and the memory footprint of storing all required information have been optimized via algorithmic and parallel processing solutions. The trimmed output compared side-by-side with the original data is part of the automated PDF output. We show how this tool can help data analysis by providing a few examples, including an increased percentage of reads recruited to references, improved single nucleotide polymorphism identification as well as de novo sequence assembly metrics. Conclusion: FaQCs combines several features of currently available applications into a single, user-friendly process, and includes additional unique capabilities such as filtering the PhiX control sequences, conversion of FASTQ formats, and multi-threading. The original data and trimmed summaries are reported within a variety of graphics and reports, providing a simple way to do data quality control and assurance.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2011

Observation Targeting for the Tehachapi Pass and Mid-Columbia Basin: WindSENSE Phase III Project Summary Report

The overall goal of this multi-phased research project known as WindSENSE is to develop an observation system deployment strategy that would improve wind power generation forecasts. The objective of the deployment strategy is to produce the maximum benefit for 1- to 6-hour ahead forecasts of wind speed at hub-height (~80 m). In Phase III of the project, the focus was on the Mid-Columbia Basin region which encompasses the Bonneville Power Administration (BPA) wind generation area shown in Figure 1 that includes Klondike, Stateline, and Hopkins Ridge wind plants. The typical hub height of a wind turbine is approximately 80-m above ground level (AGL). So it would seem that building meteorological towers in the region upwind of a wind generation facility would provide data necessary to improve the short-term forecasts for the 80-m AGL wind speed. However, this additional meteorological information typically does not significantly improve the accuracy of the 0- to 6-hour ahead wind power forecasts because processes controlling wind variability change from day-to-day and, at times, from hour-to-hour. It is also important to note that some processes causing significant changes in wind power production function principally in the vertical direction. These processes will not be detected by meteorological towers at off-site locations. For these reasons, it is quite challenging to determine the best type of sensors and deployment locations. To address the measurement deployment problem, Ensemble Sensitivity Analysis (ESA) was applied in the Phase I portion of the WindSENSE project. The ESA approach was initially designed to produce spatial fields that depict the sensitivity of a forecast metric to a set of prior state variables selected by the user. The best combination of variables and locations to improve the forecast was determined using the Multiple Observation Optimization Algorithm (MOOA) developed in Phase I. In Zack et al. (2010a), the ESA-MOOA approach was applied and evaluated for the wind plants in the Tehachapi Pass region for a period during the warm season. That research demonstrated that forecast sensitivity derived from the dataset was characterized by well-defined, localized patterns for a number of state variables such as the 80-m wind and the 25-m to 1-km temperature difference prior to the forecast time. The sensitivity patterns produced as part of the Tehachapi Pass study were coherent and consistent with the basic physical processes that drive wind patterns in the Tehachapi area. In Phase II of the WindSENSE project, the ESA-MOOA approach was extended and applied to the wind plants located in the Mid-Columbia Basin wind generation area of Washington-Oregon during the summer and to the Tehachapi Pass region during the winter. The objective of this study was to identify measurement locations and variables that have the greatest positive impact on the accuracy of wind forecasts in the 0- to 6-hour look-ahead periods for the two regions and to establish a higher level of confidence in ESA-MOOA for mesoscale applications. The detailed methodology and results are provided in separate technical reports listed in the publications section below. Ideally, the data assimilation scheme used in the Phase III experiments would have been based upon an ensemble Kalman filter (EnKF) that was similar to the ESA method used to diagnose the Mid-Columbia Basin sensitivity patterns in the previous studies. However, running an EnKF system at high resolution is impractical because of the very high computational cost. Thus, it was decided to use a three-dimensional variational (3DVAR) analysis scheme that is less computationally intensive. The objective of this task is to develop an observation system deployment strategy for the mid Columbia Basin (i.e. the BPA wind generation region) that is designed to produce the maximum benefit for 1- to 6-hour ahead forecasts of hub-height (~80 m) wind speed with a focus on periods of large changes in wind speed. There are two tasks in the current project effort designed to validate the ESA observational system deployment approach in order to move closer to the overall goal: (1) Perform an Observing System Experiment (OSE) using a data denial approach. (2) Conduct a set of Observing System Simulation Experiments (OSSE) for the Mid-Columbia basin region.

17 WIND ENERGY↗
DOE OSTI2013

MAGNETICALLY CONTROLLED CIRCULATION ON HOT EXTRASOLAR PLANETS

Through the process of thermal ionization, intense stellar irradiation renders hot Jupiter atmospheres electrically conductive. Simultaneously, lateral variability in the irradiation drives the global circulation with peak wind speeds of the order of ∼km s{sup –1}. In turn, the interactions between the atmospheric flows and the background magnetic field give rise to Lorentz forces that can act to perturb the flow away from its purely hydrodynamical counterpart. Using analytical theory and numerical simulations, we show here that significant deviations away from axisymmetric circulation are unstable in presence of a non-negligible axisymmetric magnetic field. Specifically, our results suggest that dayside-to-nightside flows, often obtained within the context of three-dimensional circulation models, only exist on objects with anomalously low magnetic fields, while the majority of highly irradiated exoplanetary atmospheres are entirely dominated by zonal jets.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Reinforcement Learning for Volt- Var Control: A Novel Two-stage Progressive Training Strategy

This paper develops a reinforcement learning (RL) approach to solve a cooperative, multi-agent Volt-Var Control (VVC) problem for high solar penetration distribution systems. The ingenuity of our RL method lies in a novel two-stage progressive training strategy that can effectively improve training speed and convergence of the machine learning algorithm. In Stage 1 (individual training), while holding all the other agents inactive, we separately train each agent to obtain its own optimal VVC actions in the action space: fconsume, generate, do-nothingg. In Stage 2 (cooperative training), all agents are trained again coordinatively to share VVC responsibility. Rewards and costs in our RL scheme include (i) a system-level reward (for taking an action), (ii) an agent-level reward (for doing-nothing), and (iii) an agent-level action cost function. This new framework allows rewards to be dynamically allocated to each agent based on their contribution while accounting for the trade-off between control effectiveness and action cost. The proposed methodology is tested and validated in a modified IEEE 123-bus system using realistic PV and load profiles. Simulation results confirm that the proposed approach is robust and computationally efficient; and it achieves desirable volt-var control performance under a wide range of operation conditions.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2015

Wind Turbine Wake-Redirection Control at the Fishermen's Atlantic City Windfarm: Preprint

In this paper, we will present our work towards designing a control strategy to mitigate wind turbine wake effects by redirecting the wakes, specifically applied to the Fishermen’s Atlantic City Windfarm (FACW), proposed for deployment off the shore of Atlantic City, New Jersey. As wind turbines extract energy from the air, they create low-speed wakes that extend behind them. Full wake recovery Full wake recovery to the undisturbed wind speed takes a significant distance. In a wind energy plant the wakes of upstream turbines may travel downstream to the next row of turbines, effectively subjecting them to lower wind speeds, meaning these waked turbines will produce less power.

17 WIND ENERGY↗
DOE OSTI2016

Local and transient nanoscale strain mapping during in situ deformation

The mobility of defects such as dislocations controls the mechanical properties of metals. This mobility is determined both by the characteristics of the defect and the material, as well as the local stress and strain applied to the defect. Therefore, the knowledge of the stress and strain during deformation at the scale of defects is important for understanding fundamental deformation mechanisms. In this paper, we demonstrate a method of measuring local stresses and strains during continuous in situ deformation with a resolution of a few nanometers using nanodiffraction strain mapping. Finally, our results demonstrate how large multidimensional data sets captured with high speed electron detectors can be analyzed in multiple ways after an in situ TEM experiment, opening the door for true multimodal analysis from a single electron scattering experiment.

36 MATERIALS SCIENCE↗
DOE OSTI2021

The case for digital twins in metal additive manufacturing

The digital twin (DT) is a relatively new concept that is finding increased acceptance in industry. A DT is generally considered as comprising a physical entity, its virtual replica, and two-way digital data communications in-between. Its primary purpose is to leverage the process intelligence captured within digital models—or usually their faster-solving surrogates—towards generating increased value from the physical entities. The surrogate models are created using machine learning based on data obtained from the field, experiments and digital models, which may be physics-based or statistics-based. Anomaly detection and correction, and diagnostic closed-loop process control are examples of how a process DT can be deployed. In the manufacturing industry, its use can achieve improvements in product quality and process productivity. Metal additive manufacturing (AM) stands to gain tremendously from the use of DTs. This is because the AM process is inherently chaotic, resulting in poor repeatability. However, a DT acting in a supervisory role can inject certainty into the process by actively keeping it within bounds through real-time control commands. Closed-loop feedforward control is achieved by observing the process through sensors that monitor critical parameters and, if there are any deviations from their respective optimal ranges, suitable corrective actions are triggered. The type of corrective action (e.g. a change in laser power or a modification to the scanning speed) and its magnitude are determined by interrogating the surrogate models. Because of their artificial intelligence (AI)-endowed predictive capabilities, which allow them to foresee a future state of the physical twin (e.g. the AM process), DTs proactively take context-sensitive preventative steps, whereas traditional closed-loop feedback control is usually reactive. Apart from assisting a build process in real-time, a DT can help with planning the build of a part by pinpointing the optimum processing window relevant to the desired outcome. Again, the surrogate models are consulted to obtain the required information. In this article, we explain how the application of DTs to the metal AM process can significantly widen its application space by making the process more repeatable (through quality assurance) and cheaper (by getting builds right the first time).

36 MATERIALS SCIENCE↗
DOE OSTI2017

Compressive Classification for TEM-EELS

Acquiring atomic-resolution images of beam sensitive materials or under dynamic conditions (e.g. operando STEM) is very difficult and requires precise dose fractioning to minimize the dose delivered to the sample and acquire the data more rapidly than dynamics present. Typical methods of low-dose STEM imaging include adjusting the beam current, dwell-time, and probe Scanning transmission electron microscopy (STEM) is used routinely to obtain atomic-resolution images of a small selection of radiation tolerant materials under stable conditions.size. All three of these determine the dose over a spatial area in STEM. Recently, compressive sensing [1] has been applied to electron microscopy. The computational imaging method of inpainting [2] has been proposed as a method to reduce dose and increase acquisition speed for STEM. Inpainting is a technique to recover missing pixels in an image. By skipping pixels (randomly) during acquisition, a fourth dose-control mechanism is realized [3]. A few implementations of randomly-subsampled STEM exist (e.g., [4]). To make the concepts of compressive sensing accessible to the microscopy community we begin with an example using atomic resolution images of a GaAs crystal (see Figure 1). Because the crystal is periodic it has a sparse representation in reciprocal space. In fact, a sparse representation is a key component of compressive sensing. If an image is sub-sampled randomly we find that the Fourier transform remains sparse, but becomes increasing noisy as less and less data is acquired. Yet, by finding the peaks in the reciprocal image and removing the noise it is possible to recover atomic resolution images with only 1% of the pixels. Figure 1 shows the reconstruction process for GaAs sub-sampled at 50%, 10%, 5%, and 1%. Periodic images form a special class for which the optimal sampling approach (according to CS theory) is a random selection of pixels. For non-periodic images, such as those arising in in-situ STEM, methods such as dictionary learning are necessary [2,5]. The data can be compressed in time for TEM [5] or pixels can be skipped randomly for STEM. There are several issues that arise in developing a random scan for STEM [4] and a coded aperture for TEM. The remainder of the talk will address these issues. References: [1] E Candes and M Wakin. Signal Processing Magazine, IEEE. 2(25) (2008), pp. 21. [2] A Stevens, Pu Y, Sun Y, et al. Artificial Intelligence & Statistics (AISTATS), 2017. [3] A Stevens, H Yang, L Carin et al. Microscopy 63(1), (2014), pp. 41. [4] L Kovarik, A Stevens, A Liyu et al. Appl. Phys. Lett. 109, 164102 (2016). [5] A Stevens, L Kovarik, P Abellan et al. Adv. Structural and Chemical Imaging 1(10), (2015), pp. 1. [6] Supported by the Chemical Imaging, Signature Discovery, and Analytics in Motion Initiatives at PNNL. PNNL is operated by Battelle Memorial Inst. for the US DOE; contract DE-AC05-76RL01830.

Hao, Weituo↗
DOE OSTI2023

Rapid Droplet Sampling Interface for Low-Volume, High-Throughput Mass Spectrometry Analysis

Here, we present a rapid droplet sampling interface (RDSI) electrospray ionization mass spectrometry (ESI-MS) system as a high-throughput, low-volume, noncontact, and minimal-carryover approach for characterization of liquids. Liquid characterization was achieved by combining droplet ejection with an open-face microflow capillary with a 2.5 μL/min continuous flow of carrier solvent. Through this implementation, single 0.3 nL droplets containing the analyte effectively mix with 4–8 nL of carrier solvent and create a combined electrospray plume. The carrier solvent continuously cleaned the system, eliminating carryover. A sampling rate of 5 Hz was achieved for droplets containing 1 μM propranolol or 5 μM leu-enkephalin with each droplet fully baseline-resolved (138 ± 32 ms baseline-to-baseline). Using a SCIEX API4000 mass spectrometer, a lower limit of quantification (LLOQ) of propranolol was 15 nM, corresponding to 1.16 fg of propranolol in the droplet, and was linear across 3 orders of magnitude. Further, quantitation could be achieved by adding an isotopically labeled internal standard, as done in conventional ESI. Signal transients were faster than the acquisition speed of the mass spectrometer, resulting in artificially high reproducibility of 15–30% RSD droplet-to-droplet. Analyte–solvent mixing ratios could be controlled by adjusting droplet positioning along the open-face capillary with an optimal position about 0.4 mm from the tip end. The range of analyte coverage was exemplified by measures of peptides and drugs in methanol, water, and buffer solutions. In a comparison to the Open Port Sampling Interface (OPSI) implemented on the same system, the RDSI had 78× greater sensitivity, 6× greater throughput and used significantly less carrier solvent.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2011

Quantum-state tomography of a single nuclear spin qubit of an optically manipulated ytterbium atom

A single Yb atom is loaded into a high-finesse optical cavity with a moving lattice, and its nuclear spin state is manipulated using a nuclear magnetic resonance technique. A highly reliable quantum state control with fidelity and purity greater than 0.98 and 0.96, respectively, is confirmed by the full quantum state tomography; a projective measurement with high speed (500 {mu}s) and high efficiency (0.98) is accomplished using the cavity QED technique. Because a hyperfine coupling is induced only when the projective measurement is operational, the long coherence times (T{sub 1}=0.49 s and T{sub 2}=0.10 s) are maintained.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Analysis of Integrated Vapor Transport Biases

Abstract High-fidelity analyses and forecasts of integrated vapor transport (VT) are central to the study of Earth’s hydrological cycle as well as high-impact phenomena such as monsoons and atmospheric rivers. The impact of the in-line analysis correction-based additive inflation (ACAI) on IVT biases and forecast errors is examined within the Navy Earth System Prediction Capability (Navy ESPC) global coupled system. The ACAI technique uses atmospheric analysis corrections from the data assimilation system to approximate model bias and as a representation of stochastic model error to simultaneously reduce systematic and random errors and improve ensemble performance. ACAI reduces the global average magnitude of the 7- and 14-day IVT bias by 16%–17% during Northern Hemisphere summer, reaching 70% reductions in some tropical regions. The global average IVT bias reduction is similar to the bias reduction for low-level wind speed bias and considerably smaller than the bias reduction in total precipitable water. The localized regions where ACAI increases IVT bias occur where the control IVT biases change sign and structure with increasing forecast lead time, such as the South Asian monsoon region. Substituting analyzed wind or moisture fields for the forecast fields when calculating the forecast IVT confirms that, on average, wind errors dominate the IVT error calculation in the tropics, although wind and moisture error contributions are comparable in the extratropics. The existence of regions where using either analyzed winds or analyzed moisture increases IVT bias or mean absolute error reveals areas with compensating errors.

Reynolds, Carolyn A.↗
DOE OSTI2014

HPC4Energy Final Report : GE Energy

Power System planning tools are being used today to simulate systems that are far larger and more complex than just a few years ago. Advances in renewable technologies and more pervasive control technology are driving planning engineers to analyze an increasing number of scenarios and system models with much more detailed network representations. Although the speed of individual CPU’s has increased roughly according to Moore’s Law, the requirements for advanced models, increased system sizes, and larger sensitivities have outstripped CPU performance. This computational dilemma has reached a critical point and the industry needs to develop the technology to accurately model the power system of the future. The hpc4energy incubator program provided a unique opportunity to leverage the HPC resources available to LLNL and the power systems domain expertise of GE Energy to enhance the GE Concorda PSLF software. Well over 500 users worldwide, including all of the major California electric utilities, rely on Concorda PSLF software for their power flow and dynamics. This pilot project demonstrated that the GE Concorda PSLF software can perform contingency analysis in a massively parallel environment to significantly reduce the time to results. An analysis with 4,127 contingencies that would take 24 days on a single core was reduced to 24 minutes when run on 4,217 cores. A secondary goal of this project was to develop and test modeling techniques that will expand the computational capability of PSLF to efficiently deal with systems sizes greater than 150,000 buses. Toward this goal the matrix reordering implementation time was sped up 9.5 times by optimizing the code and introducing threading.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Parallel Implicit Hydrodynamics with Material Strength for High Explosive Burn Calculations

High explosives are almost always evolving in some form of metal containment vessel. This fact requires that a materials model for the evolution of the metal containment vessel be part of any simulation of the HE. Since the actual form of the strength model to be used is an open question, we incorporate the material strength properties in a relatively agnostic fashion, which will accommodate many strength models. The only restriction is that the stress components be a function of density, specific internal energy and velocities. In addition, the timescales and rates of the chemical reactions in the HE vary between thousands of seconds and nanoseconds. A hydrodynamics capable of operating in anticipation of the eventual violent release of energy via these chemical reactions is a necessity. The central issue in creating a hydrodynamics capable of spanning these timescales is to forgo the use of a Courant time step control necessary in an explicit hydrodynamics. The Courant time-step arises because of characteristic velocities associated with the material, such as the sound speed or, in materials with strength, characteristic longitudinal and transverse speeds associated with compression and shear. The method used to circumvent the need for a Courant time-step limit is to develop an implicit calculation of the advanced particle pressure and shear modulus derived from the conservation laws of mass, momentum and specific internal energy. This process creates the implicit hydrodynamics needed for the HE calculations of interest to this study.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Distributed Rules-Based Deconfliction of ADMS Applications: Part 1: Requirements & Decomposition

This work introduces a rules-based deconfliction methodology for resolving conflicting device control commands issued by advanced power applications considering a range of technical, economic, environmental, and social objectives. The methodology is designed to serve as one of multiple alternative implementations (along with application cooperation and global optimization) for the numerical component of the Deconfliction Pipeline. Development of the methodology is divided into two parts. This first document introduces the requirements, context, and methods for decomposing the deconfliction problem using the Laminar Coordination Framework and Variable Grid Structures. The deconfliction problem is decomposed into a distributed optimization problem based on the concept of quasi-static grid segments, which form independent distributed areas for control and coordination. Selection of the optimal number of decompositions of the deconfliction problem should be made based on a tradeoff analysis between computational speed and global optimality. This second document will define an initial set of technical, economic, and environmental criteria, as well as thirty specific qualitative rules that are used as part of the deconfliction methodology to eliminate non-viable setpoint alternatives. The deconfliction optimization problem is converted into a ranking of individual discrete setpoints, which are scored by the extent to which they satisfy specific decision criteria. The ranking is determined through the concepts of deconfliction exclusivity, priority, and preference. Several multi-criteria decision-making frameworks are examined with the simple multi-attribute rating technique exploiting ranks (SMARTER) recommended as a simple implementation alternative that aligns with the steps of the rules-based deconfliction methodology.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Enhancing Plastic Recycling Through Nano-Scale Structure Analysis in Custom Block Copolymer Filaments (Rev.1)

As plastic production continues to increase, new methods to combat plastic waste are needed. This paper explores upcycling, a way to increase the utility or value of waste plastic. This can be done using block copolymers as compatibilizers. Block copolymers are made of two immiscible polymer blocks that phase separate on the nanoscale, forming small structures. The orientation of these nano-scale structures influences mechanical properties, and we show that orientation can be controlled by directional 3D (three dimensional) printing. Using small-angle X-ray scattering (SAXS), we analyze block copolymer filaments extruded at varying speeds. The SAXS data provide a baseline understanding of nano-scale structure in these unique filaments for future use in 3D printing experiments.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Performance Evaluation of LPBF Manufactured 316H Components

This work represents the continuation of a benchmark study that includes modeling, fabrication and characterization as demonstration to support industry’s adoption of advanced manufacturing processes in a variety of structures. This comprehensive study investigated the feasibility of using additive manufacturing (AM) technologies, specifically Laser Powder Direct Energy Deposition (LP-DED) and Laser Powder Bed Fusion (LPBF), to produce complex nuclear microreactor components using 316H stainless steel. The research focused on manufacturing an expanded elbow pipe component with transitioning sections, which are traditionally difficult and costly to produce through conventional manufacturing methods. The overall study’s primary objectives are therefore demonstrating AM viability for nuclear applications, optimizing process parameters, developing comprehensive material characterization protocols, validating computational modeling approaches, and establishing manufacturing guidelines for complex geometries. Although the initial work included the phased approach of cubical, upscaled cylindrical components, it is to enable to obtain more knowledge for the printing of the expanded elbow structure. The project achieved significant progress in process development by successfully optimizing LP-DED parameters to achieve 99.16-99.97% relative density in 316H stainless steel components. Through systematic evaluation of sixteen cube samples with varied laser powers (400-700W) and scan speeds (600-900 mm/min), optimal processing windows were identified at 500-550W with 600-700 mm/min or 650-700W with 650-900 mm/min scan speeds. The DED manufactured 316H demonstrated mechanical properties comparable or superior to wrought materials, with Young's modulus ranging from 153-208 GPa and controlled microstructural characteristics including greater than 95% face-centered cubic (FCC) phases and engineered cellular structures with sizes between 3.23-6.17 µm.

36 MATERIALS SCIENCE↗