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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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At least 1,099 records · Page 61
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Creating a Simulation Platform for Research and Development of Advanced Control Methods

Advanced nuclear reactors are essential to meet the changing energy requirements throughout both the United States and the rest of world. In addition to other features, they are designed to enable deployment in remote locations and operate in a fully (or near-fully) autonomous manner, which will require a new control paradigm. To realize autonomously operating reactors, the U.S. Department of Energy’s Nuclear Energy Enabling Technologies Advanced Sensors and Instrumentation (NEET ASI) program conducts research and development into the enabling technologies and methods needed, including digital twins, machine learning, and risk modeling, in addition to various types of control methods. These technologies and methods are the key foundations needed to achieve fully autonomous systems. To develop and evaluate the technologies and methods necessary for achieving autonomous operations, it is critical to identify a software tool capable of integrating all the required elements. In surveying the available solutions, no software platforms were identified that could accomplish what was needed without introducing drawbacks. This challenge was the motivation for the current effort: to develop a software platform that can seamlessly integrate autonomouscontrol-enabling technologies and methods, allowing for accelerated research and development and transfer of ideas. The resulting platform, known as the Control and Optimization Modular Modeling Application for Nuclear Deployment (COMMAND), is Python-based, and leverages open-source tools to provide flexibility and facilitate building upon prior research. It is designed to enable advanced reactor developers to deploy and test advanced control technologies and methods coupled with their own models, solutions, and hardware. Given the substantial undertaking of developing such a platform, the current effort focused on laying down scalable, flexible software foundations and infrastructure, then demonstrating the platform via a use case. These foundations included developing generic modules, which contain the base variable and system blocks (the information and functional building blocks, respectively, that can be used to design a simulation) and the data handling and storage blocks needed to exchange information between the various blocks; as well as enablingtechnology-specific modules. This platform was evaluated via a use case, which was to simulate and control a process for the Microreactor Automated Control System (MACS) test bed. While MACS is not currently directly coupled to any specific microreactor physics, it was initially developed in concert with the Microreactor Applications Research Validation and Evaluation (MARVEL) microreactor, and so the MARVEL physics are used here. As part of this use case, several enabling-technology-specific blocks within COMMAND were integrated, including a proportional integral derivative (PID) control block, a Reactor Excursion and Leak Analysis Program (RELAP5-3D) block, and an anomaly detection block. The COMMAND software platform was successfully demonstrated to achieve the scalability and flexibility objectives of this effort and will be leveraged by the program’s research efforts to advance state of the art control methodologies towards autonomous operations of advanced reactors. As new use cases are created and implemented, it is anticipated that COMMAND will continue to grow and evolve to meet new requirements.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Pathways to commercial building plug and process load efficiency and control

Abstract To accomplish net-zero carbon emissions in the built environment by 2050, we must equitably decarbonize commercial buildings, including reducing plug and process loads (PPLs). PPLs are plug-in or hardwired electric and gas loads that are not associated with major building end uses like lighting and HVAC. Research shows PPL energy reduction strategies and control technologies have the potential to save energy. But even when implemented, these savings have rarely been achieved and there has not been widespread uptake in U.S. commercial buildings. We investigate why these technologies and strategies have not seen widespread adoption and identify behavior and technology pathways to increase PPL reduction in U.S. commercial buildings. We examined behaviors of commercial building stakeholders through 44 interviews and cross-referenced qualitative analysis findings with in-depth technical knowledge of existing PPL control technologies and reduction strategies. PPL control implementation must be paired with management strategies, such as occupant engagement and training, to achieve optimal savings, and best practices should be disseminated across the industry. We found that increasing access to cost and energy savings data will promote uptake of PPL control technologies and allow designers to better incorporate PPLs into building design. Improving access to funding for PPL energy efficiency projects and addressing the split-incentive problem will increase adoption of PPL efficiency and control. Code bodies should continue to include PPL monitoring and reduction measures in energy codes. Key building stakeholders, including cybersecurity and information technology teams, should be involved in PPL monitoring and reduction strategy processes for successful implementation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Sensing and control of additive manufacturing processes

Systems, devices, and methods for additive manufacturing are provided that allow for components being manufactured to be assessed during the printing process. As a result, changes to a print plan can be considered, made, and implemented during the printing process. More particularly, in exemplary embodiments, a spectrometer is operated while a component is being printed to measure one or more parameters associated with one or more layers of the component being printed. The measured parameter(s) are then relied upon to determine if any changes are needed to the way printing is occurring, and if such changes are desirable, the system is able to implement such changes during the printing process. By way of non-limiting examples, printed material in one or more layers may be reheated to alter the printed component, such as to remove defects identified by the spectrometer data. A variety of systems, devices, and methods for performing real-time sensing and control of an additive manufacturing process are also provided.

Penny, Ryan Wade↗
DOE OSTI2021

Investigating the Evolution of Ice Particle Distributions in Mixed-Phase Clouds

The goal of this project is to conduct modeling studies that focus on the processes that control the macrophysical and microphysical properties of mixed phase clouds, such as the partitioning of water phase and the processes that promote precipitation and govern cloud evolution. The process specific to this project is the collection of vapor-grown non-spherical ice crystals and snow hydrometeors through aggregation, as uncertainty remains in the evolution of particle properties as they aggregate. To aid in the understanding of ice particle evolution from pristine monomers to aggregates, the aggregation process is depicted using an offline simulator for ice crystal collection, namely the Ice Particle and Aggregate Simulator (IPAS). Of particular interest in the context of this work is the influence of monomer habit on aggregation and subsequently on cloud microphysical structure. This overarching goal has been completed by conducting modeling studies using the Adaptive Habit Model (AHM) in mixed-phase cloud systems, which predicts and evolves ice shape. While the AHM is designed with physical detail in mind, those details may be lost on larger spatial or temporal scales. Hence, how the contributions of particle growth and collection control the evolution of ice particle size distributions (PSDs) and redistribute mass within the cloud and at the surface has been investigated. Analyses include microphysical sensitivity investigations that inform on future improvement capabilities of microphysical parameterizations in larger scale models. Further, improvements of processes within ice clouds have resulted from this work as the environmental processes controlling ice crystal growth, microphysical processes, and precipitation are inherently integrated within this investigation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Luminescent microporous metal–organic framework with functional Lewis basic sites on the pore surface: Quantifiable evaluation of luminescent sensing mechanisms towards Fe{sup 3+}

A systematic study has been conducted on a novel luminescent metal-organic framework, ([Zn(bpyp)(L-OH)]·DMF·2H{sub 2}O){sub n} (1), to explore its sensing mechanisms to Fe{sup 3+}. Structure analyses show that compound 1 exist pyridine N atoms and -OH groups on the pore surface for specific sensing of metal ions via Lewis acid-base interactions. On this consideration, the quenching mechanisms are studied and the processes are controlled by multiple mechanisms in which dynamic and static mechanisms are calculated, achieving the quantification evaluation of the quenching process. This work not only achieves the quantitative evaluation of the luminescence quenching but also provides certain insights into the quenching process, and the possible mechanisms explored in this work may inspire future research and design of target luminescent metal-organic frameworks (LMOFs) with specific functions. - Graphical abstract: A systematic study has been conducted on a novel luminescent metal-organic framework to explore its sensing mechanisms to Fe{sup 3+}. The quenching mechanisms are studied and the processes are controlled by multiple mechanisms in which dynamic and static mechanisms are calculated, achieving the quantification evaluation of the quenching process. - Highlights: • A novel porous luminescent MOF containing uncoordinated groups in interlayer channels was successfully synthesized. • The compound 1 can exhibit significant luminescent sensitivity to Fe{sup 3+}, which make its good candidate as luminescent sensor. • The corresponding dynamic and static quenching constants are calculated, achieving the quantification evaluation of the quenching process.

36 MATERIALS SCIENCE↗
DOE OSTI2012

Control Improvement for Jump-Diffusion Processes with Applications to Finance

We consider stochastic control problems with jump-diffusion processes and formulate an algorithm which produces, starting from a given admissible control {pi}, a new control with a better value. If no improvement is possible, then {pi} is optimal. Such an algorithm is well-known for discrete-time Markov Decision Problems under the name Howard's policy improvement algorithm. The idea can be traced back to Bellman. Here we show with the help of martingale techniques that such an algorithm can also be formulated for stochastic control problems with jump-diffusion processes. As an application we derive some interesting results in financial portfolio optimization.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Model predictive control of KSTAR equilibrium parameters enabled by TRANSP

Due to the complex behavior of tokamak plasmas and the importance of optimizing performance while avoiding instabilities and machine limits, plasma control algorithms are becoming increasingly dependent on sophisticated model-based control approaches. It is anticipated that the use of integrated modeling codes in the model-based control design process will reduce the amount of experimental time needed to implement new control algorithms by facilitating development of control-oriented models and enabling higher-fidelity closed-loop simulations. In this work, a reduced model is developed from a series of TRANSP simulations and is used to develop a model predictive control (MPC) algorithm for controlling important equilibrium parameters in KSTAR [1] discharges. The control algorithm uses the KSTAR neutral beam injection system and the target plasma current and plasma boundary as actuators, and optimizes the plasma stored energy, loop voltage, and internal inductance while avoiding constraints that could lead to disruptions. Higher fidelity testing of the control algorithm is performed using a flexible framework for enabling external processes to actively control plasma parameters in TRANSP simulations. Furthermore, closed-loop simulations demonstrate the ability of the control algorithm to respond to disturbances in density and confinement, handle actuator failures, and move the discharge to high non-inductive fraction conditions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2014

Significant Quantum Effects in Hydrogen Activation

Dissociation of molecular hydrogen is an important step in a wide variety of chemical, biological, and physical processes. Due to the light mass of hydrogen, it is recognized that quantum effects are often important to its reactivity. However, understanding how quantum effects impact the reactivity of hydrogen is still in its infancy. Here, we examine this issue using a well-defined Pd/Cu(111) alloy that allows the activation of hydrogen and deuterium molecules to be examined at individual Pd atom surface sites over a wide range of temperatures. Experiments comparing the uptake of hydrogen and deuterium as a function of temperature reveal completely different behavior of the two species. The rate of hydrogen activation increases at lower sample temperature, whereas deuterium activation slows as the temperature is lowered. Density functional theory simulations in which quantum nuclear effects are accounted for reveal that tunneling through the dissociation barrier is prevalent for H 2 up to ~190 K and for D 2 up to ~140 K. Kinetic Monte Carlo simulations indicate that the effective barrier to H 2 dissociation is so low that hydrogen uptake on the surface is limited merely by thermodynamics, whereas the D 2 dissociation process is controlled by kinetics. These data illustrate the complexity and inherent quantum nature of this ubiquitous and seemingly simple chemical process. Here, examining these effects in other systems with a similar range of approaches may uncover temperature regimes where quantum effects can be harnessed, yielding greater control of bond-breaking processes at surfaces and uncovering useful chemistries such as selective bond activation or isotope separation.

08 HYDROGEN↗
DOE OSTI2023

Model-based data center cooling controls comparative co-design

This article presents a comparative simulation-based control logic design process. It uses the Control Description Language (CDL) and the ASHRAE Guideline 36 high-performing building control sequences with the Modelica Buildings Library (MBL) to demonstrate a comparative analysis of two control designs for a data center chilled water plant. Details include a description of the closed-loop plant and control design methodology, including sizing and parameterization, base and alternative (Guideline 36) control logic with software implementation structure, and outline of the simulation experimentation process. The selected control designs are paired with comparable chilled water plant configurations. The models include a chiller, a water-side economizer, and an evaporative cooling tower. The plant provides cooling at 27ºC zone supply air temperature to a data center in Sacramento, CA. The comparative simulation results examined the impacts of a selected control logic detail, and present an example model-based design application. Overall, the simulation results showed a 25% annual and a 18% summer energy use reduction for alternative controls. This shows that simulation-based control logic design performance evaluation can improve energy efficiency and resilience aspects of system controls at large.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2012

Plasma process optimization for N-type doping applications

Plasma doping (PLAD) has been adopted across the implant technology space and into high volume production for both conventional DRAM and NAND doping applications. PLAD has established itself as an alternative to traditional ion implantation by beamline implantation. The push for high doping concentration, shallow doping depth, and conformal doping capability expand the need for a PLAD solution to meet such requirements. The unique doping profile and doping characteristics at high dose rates allow for PLAD to deliver a high throughput, differentiated solution to meet the demand of evolving transistor technology. In the PLAD process, ions are accelerated to the wafer as with a negative wafer bias applied to the wafer. Competing mechanisms, such as deposition, sputtering, and etching inherent in plasma doping require unique control and process optimization. In this work, we look at the distinctive process tool control and characterization features which enable an optimized doping process using n-type (PH{sub 3} or AsH{sub 3}) chemistries. The data in this paper will draw the relationship between process optimization through plasma chemistry study to the wafer level result.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Deep reinforcement learning for optimal control of induction welding process

Optimizing induction welding (IW) process parameters for the application of joining thermoplastic composites is challenging as it requires achieving complex spatiotemporal thermal characteristics along the weld-line to obtain desired weld quality. We formulate an optimal control problem which captures these requirements and seeks to optimize the IW coil speed using a fast-acting dynamic IW process model. We develop a novel Deep Reinforcement Learning (DRL) framework to solve this computationally challenging control problem and demonstrate via simulation study that the learned DRL feedback control policy results in better spatiotemporal thermal characteristics as compared to the current state-of-the-art.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Method and system for controlling a gasification or partial oxidation process

A method and system for controlling a fuel gasification system includes optimizing a conversion of solid components in the fuel to gaseous fuel components, controlling the flux of solids entrained in the product gas through equipment downstream of the gasifier, and maximizing the overall efficiencies of processes utilizing gasification. A combination of models, when utilized together, can be integrated with existing plant control systems and operating procedures and employed to develop new control systems and operating procedures. Such an approach is further applicable to gasification systems that utilize both dry feed and slurry feed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

DOE Hanford Tank Side Cesium Removal System (TSCR) Update: Fabrication and Factory Acceptance Testing - 20300

The Tank Side Cesium Removal (TSCR) System is a modular, quickly-deployable, and passively safe system for efficiently removing solids and cesium from alkaline liquid waste raffinate created by fuel processing on the Hanford site. This paper provides an overview of the project with particular emphasis on completion of fabrication and factory acceptance testing (FAT). All TSCR System components are inside three enclosures known as the Process Enclosure, Ancillary Enclosure, and Control Enclosure. The Process Enclosure is seismic design category II (SDC-II) and built to withstand the rigors of transportation and lifting, high winds, volcanic ash fall, and heavy precipitation (snow) over a temperature range of -25 to 115 deg. F. The Process Enclosure and Control Enclosure were fabricated in AVANTech's Columbia, SC facility, while the Ancillary Enclosure was fabricated in AVANTech's Richland, WA facility. The design and preliminary documented safety analysis were completed in December 2019, with all work being performed in accordance with ASME NQA-1 quality assurance requirements. The Process Enclosure, Ion Exchange Columns (IXCs), and several other TSCR components have a nuclear safety function and are designated as safety significant structures, systems, and components (SS-SSCs). The NQA-1 Commercial Grade Dedication (CGD) process was used to identify critical characteristics in order to accept materials and items used for fabrication of several safety significant TSCR components. This paper also addresses unique aspects and challenges of implementing CGD in DOE facilities and systems. After fabrication and preliminary testing, the Process and Control Enclosures were shipped to AVANTech's Richland facility where the complete TSCR System was setup and connected in a represented layout and configuration that will be used on the Hanford site. Test tanks and pumps were put in place and connected to the TSCR Process Enclosure in a manner that mimicked interfacing Double Shell Tanks in the 241-AP Tank Farm. The TSCR System was then tested/operated under conditions equivalent to those planned for onsite operation. Testing was separated into five separate phases as defined below: - Phase 1: Confirmation of TSCR System readiness for the FAT; - Phase 2: Verification of TSCR System operation under standard conditions; - Phase 3: Demonstration of TSCR System operation under non-standard conditions; - Phase 4: Demonstration of ion exchange media removal from an IXC; and - Phase 5: Completion of TSCR System lift plans and site mobilization. The Hanford Tank Operations Contractor, Washington River Protection Solutions (WRPS), participated in all phases of testing. Testing at AVANTech's Richland Facility allowed WRPS personnel to familiarize themselves with TSCR operations in a radiologically clean facility prior to onsite mobilization. Engineering and operations personnel gained valuable experience that allowed them to better refine onsite operational protocols and procedures - including handling and movement of IXCs with a forklift. This paper describes the technologies used by the TSCR System as well as how these technologies are deployed and operated to advance the Hanford mission of safely, efficiently, and effectively treating tank waste. It also provides detailed information on fabrication and FAT, including operational data from simulated tank waste runs. A project schedule for WRPS' planned construction acceptance testing, operational acceptance testing, and actual tank waste treatment is provided. This presentation should be of great interest to parties responsible for the design, testing, and mobilization of modular NQA-1 technologies for the treatment of raffinate and similar liquid wastes containing high concentrations of radioactive cesium. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Electronic control of redox reactions inside Escherichia coli using a genetic module

Microorganisms regulate the redox state of different biomolecules to precisely control biological processes. These processes can be modulated by electrochemically coupling intracellular biomolecules to an external electrode, but current approaches afford only limited control and specificity. Here we describe specific electrochemical control of the reduction of intracellular biomolecules in Escherichia coli through introduction of a heterologous electron transfer pathway. E . coli expressing cymAmtrCAB from Shewanella oneidensis MR-1 consumed electrons directly from a cathode when fumarate or nitrate, both intracellular electron acceptors, were present. The fumarate-triggered current consumption occurred only when fumarate reductase was present, indicating all the electrons passed through this enzyme. Moreover, CymAMtrCAB-expressing E . coli used current to stoichiometrically reduce nitrate. Thus, our work introduces a modular genetic tool to reduce a specific intracellular redox molecule with an electrode, opening the possibility of electronically controlling biological processes such as biosynthesis and growth in any microorganism.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Intelligent experiments through real-time AI: Fast Data Processing and Autonomous Detector Control for sPHENIX and future EIC detectors

This R&D project, initiated by the DOE Nuclear Physics AI-Machine Learning initiative in 2022, leverages AI to address data processing challenges in high-energy nuclear experiments (RHIC, LHC, and future EIC). Our focus is on developing a demonstrator for real-time processing of high-rate data streams from sPHENIX experiment tracking detectors. The limitations of a 15 kHz maximum trigger rate imposed by the calorimeters can be negated by intelligent use of streaming technology in the tracking system. The approach efficiently identifies low momentum rare heavy flavor events in high-rate p+p collisions (3MHz), using Graph Neural Network (GNN) and High Level Synthesis for Machine Learning (hls4ml). Success at sPHENIX promises immediate benefits, minimizing resources and accelerating the heavy-flavor measurements. The approach is transferable to other fields. For the EIC, we develop a DIS-electron tagger using Artificial Intelligence - Machine Learning (AI-ML) algorithms for real-time identification, showcasing the transformative potential of AI and FPGA technologies in high-energy nuclear and particle experiments real-time data processing pipelines.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2012

Spectral Induced Polarization Signatures of Hydroxide Adsorption and Mineral Precipitation in Porous Media

The spectral induced polarization (SIP) technique is a promising approach for delineating subsurface physical and chemical property changes in a minimally invasive manner. To facilitate the understanding of position and chemical properties of reaction fronts that involve mineral precipitation in porous media, we investigated spatiotemporal variations in complex conductivity during evolution of urea hydrolysis and calcite precipitation reaction fronts within a silica gel column. The real and imaginary parts of complex conductivity were shown to be sensitive to changes in both solution chemistry and calcium carbonate precipitation. Distinct changes in imaginary conductivity coincided with increased hydroxide ion concentration during urea hydrolysis. In a separate experiment focused on the effect of hydroxide concentration on interfacial polarization of silica gel and well-sorted sand, we found a significant dependence of the polarization response on pH changes of the solution. We propose a conceptual model describing hydroxide ion adsorption behavior in silica gel and its control on interfacial polarizability. Our results demonstrate the utility of SIP for noninvasive monitoring of reaction fronts, and indicate its potential for quantifying geochemical processes that control the polarization responses of porous media at larger spatial scales in the natural environment.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Toward more realistic projections of soil carbon dynamics by Earth system models

Soil carbon (C) is a critical component of Earth system models (ESMs), and its diverse representations are a major source of the large spread across models in the terrestrial C sink from the third to fifth assessment reports of the Intergovernmental Panel on Climate Change (IPCC). Improving soil C projections is of a high priority for Earth system modeling in the future IPCC and other assessments. To achieve this goal, we suggest that (1) model structures should reflect real-world processes, (2) parameters should be calibrated to match model outputs with observations, and (3) external forcing variables should accurately prescribe the environmental conditions that soils experience. First, most soil C cycle models simulate C input from litter production and C release through decomposition. The latter process has traditionally been represented by first-order decay functions, regulated primarily by temperature, moisture, litter quality, and soil texture. While this formulation well captures macroscopic soil organic C (SOC) dynamics, better understanding is needed of their underlying mechanisms as related to microbial processes, depth-dependent environmental controls, and other processes that strongly affect soil C dynamics. Second, incomplete use of observations in model parameterization is a major cause of bias in soil C projections from ESMs. Optimal parameter calibration with both pool-and flux-based data sets through data assimilation is among the highest priorities for near-term research to reduce biases among ESMs. Third, external variables are represented inconsistently among ESMs, leading to differences in modeled soil C dynamics. Furthermore, we recommend the implementation of traceability analyses to identify how external variables and model parameterizations influence SOC dynamics in different ESMs. Overall, projections of the terrestrial C sink can be substantially improved when reliable data sets are available to select the most representative model structure, constrain parameters, and prescribe forcing fields.

54 ENVIRONMENTAL SCIENCES↗