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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Data-Driven Robust M-LS-SVR-Based NARX Modeling for Estimation and Control of Molten Iron Quality Indices in Blast Furnace Ironmaking

Optimal operation of an industrial blast furnace (BF) ironmaking process largely depends on a reliable measurement of molten iron quality (MIQ), which is not feasible using the conventional sensors. This paper proposes a novel data-driven robust modeling method for online estimation and control of MIQ indices. First, to completely capture the nonlinear dynamics of the BF process, the nonlinear autoregressive exogenous (NARX) model is constructed for the MIQ indices. Then, considering that the standard least-squares support vector regression (LS-SVR) cannot directly cope with the multi-output problem, the multi- task transfer learning is proposed to design a novel multi-output LS-SVR (M-LS-SVR) for learning of the NARX model. Furthermore, a novel M-estimator is proposed to reduce the interference of outliers and improve the robustness of the M-LS- SVR model. Since the weights of different outlier data are properly given by the weight function, their corresponding contributions on modeling can be properly distinguished, thus a robust modeling result can be achieved. Finally, a novel multi- objective evaluation index on modeling performance is developed by comprehensively considering the root mean square error of modeling and the correlation coefficient on trend fitting, based on which the NSGA-II algorithm is used to globally optimize the model parameters. Both experiments using industrial data and industrial applications illustrate that the proposed method can eliminate the adverse effect caused by the fluctuation of data in BF process efficiently, which indicates its stronger robustness and higher accuracy. Moreover, control testing shows that the developed model can be well applied to realize data-driven control of the BF process.

blast cavities, Control↗
DOE OSTI2020

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

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

Chen, B↗
DOE OSTI2022

Potential Heating Energy and Cost Savings of Dual Fuel Heat Pump Controls as a Residential Building Equipment Retrofit in the U.S.

This study investigated the energy and cost savings potential by modeling a dual fuel heat pump system with its control for a residential building in (5A) cold climate in U.S. The simulation analysis showed that the application of the DFHP system and its control to the target building can save the heating energy by 42% over a gas furnace system (baseline system). Although the HP-only system can save more heating energy (i.e., 53%) over the baseline system than DFHP system does, the DFHP with its control demonstrated the higher cost savings when a time of use electricity rate was considered.

Yoon, Yeobeom↗
DOE OSTI2023

Fault isolation and fault-tolerant control for nonlinear stochastic distribution control systems with multiplicative faults

Here, in this paper, a fault isolation, diagnosis and fault tolerant control algorithm is proposed for nonlinear multiple multiplicative faults stochastic distribution control systems employing Takagi–Sugeno fuzzy system. To obtain the detailed fault information, a fault detection algorithm is introduced to discover the fault occurrence time. Then a fault isolation observer is built to produce the residual, and the error system is separated to subsystems affected only by disturbance and multiplicative faults. Moreover, a fault estimation scheme is presented to obtain the fault magnitude information. When faults occur, the system output probability density function will deviate from the desired distribution. So the model predictive control fault tolerant control scheme is needed to minimize the impact of faults as much as possible to make sure that the post fault output probability density function track the desired probability density function. The validity of the designed algorithm is demonstrated through a simulation example, where the fault tolerant control algorithm ensures that the system output probability density function still track the given output probability density function despite the complex case of multiple multiplicative faults occurring simultaneously.

42 ENGINEERING↗
DOE OSTI2020

Modeling and Control Using Stochastic Distribution Control Theory for Intersection Traffic Flow

In this work, we investigated stochastic distribution control theory-based traffic signal optimization to achieve a smooth and uniform flow of vehicles through signalized intersections. In this context, the static and linear dynamic stochastic distribution models were developed to express the relationship between the signal timing and the traffic queue length together with its probability density function. Two stochastic distribution control algorithms were designed to control the signal timing at intersections such that the probability density function of the traffic queue of each intersection road segment is made as narrow and as small as possible. Also, a recursive input-output traffic queue estimation model was proposed, which is data-driven and dynamic in nature, to calculate real-time traffic queue length using traffic signal timings and loop-detector data. The control algorithms were evaluated for a one-signal corridor, two-signal corridor, and 2 x 2 network of signalized intersections. MATLAB simulation examples are provided to demonstrate the use of the proposed algorithms and comparison to the existing widely-used semi-actuated control has been made. Desired results were obtained.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

A Distributed Control System Prototyping Environment to Support Control Room Modernization

Operators of critical processes, such as nuclear power production, must contend with highly complex systems, procedures, and regulations. Developing human-machine interfaces (HMIs) that better support operators is a high priority for ensuring the safe and reliable operation of critical processes. Human factors engineering (HFE) provides a rich and mature set of tools for evaluating the performance of HMIs, however the set of tools for developing and designing HMIs is still in its infancy. Here we propose a rapid prototyping approach for integrating proposed HMIs into their native environments before a design is finalized. This approach allows researchers and developers to test design ideas and eliminate design flaws prior to fully developing the new system. We illustrate this approach with four prototype designs developed using Microsoft’s Windows Presentation Foundation (WPF). One example is integrated into a microworld environment to test the functionality of the design and identify the optimal level of automation for a new system in a nuclear power plant. The other three examples are integrated into a full-scale, glasstop digital simulator of a nuclear power plant. One example demonstrates the capabilities of next generation control concepts; another aims to expand the current state of the art; lastly, an HMI prototype was developed as a test platform for a new control system currently in development at U.S. nuclear power plants. WPF possesses several characteristics that make it well suited to HMI design. It provides a tremendous amount of flexibility, agility, robustness, and extensibility. Distributed control system (DCS) specific environments tend to focus on the safety and reliability requirements for real-world interfaces and consequently have less emphasis on providing functionality to support novel interaction paradigms. Because of WPF’s large user-base, Microsoft can provide an extremely mature tool. Within process control applications,WPF is platform independent and can communicate with popular full-scope process control simulator vendor plant models and DCS platforms.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2018

Micronutrient metal speciation is controlled by competitive organic chelation in grassland soils

Many elements are scarcely soluble in aqueous conditions found in high pH environments, such as calcareous grassland soils, unless complexed to strong binding organic ligands. To overcome this limitation, some plants and microbes produce chelators that solubilize micronutrient metals such as Fe, Ni, Cu, and Zn from mineral phases. These complexes are taken up by organisms via specific membrane receptors, thereby differentially impacting the bioavailability of these metals to the plant and microbial community. Although the importance of these chelation strategies for individual organisms has been well established, little is known about which pathways coexist within rhizosphere microbiomes or how they interact and compete for metal binding. Identifying these metallo-organic species within natural ecosystems has remained a formidable analytical challenge due to the vast diversity of compounds and poorly defined metabolic processes in complex soil matrix. Herein, we employed recently developed liquid chromatography (LC) mass spectrometry (MS) methods to characterize the speciation of water-soluble dissolved trace elements (Fe, Ni, Cu, and Zn) from Kansas Prairie soil. Both plant and fungal chelators were identified, revealing compound-specific patterns of chelation to biologically essential metals. Numerous metabolites typically implicated in plant iron acquisition and homeostasis, including mugineic acids, deoxymugineic acid, nicotianamine, and hydroxynicotianamine, dominated the speciation of divalent metals such as Ni, Cu, and Zn (2-57 pmol / g soil). In contrast, the fungal siderophore ferricrocine bound comparatively more trivalent Fe (9pmol / g soil). These results define biochemical pathways that underpin the regulation of metals in the grassland rhizosphere. They also raise new questions about the competition of these compounds for metal binding and their bioavailability to different members of the rhizosphere population. Even small structural differences result in significant differences in their environmental metal speciation, and likely impact metal uptake within the rhizosphere of calcareous soils.

Boiteau, Rene M.↗
DOE OSTI2018

Size and Morphology Controlled Synthesis of Boehmite Nanoplates and Crystal Growth Mechanisms

The aluminum oxyhydroxide boehmite is an important crystalline phase in nature and industry. We report development of a flexible additive-free hydrothermal synthesis method to prepare high quality boehmite nanoplates with sizes ranging from under 20 nm to 5 um via using hydrated alumina gels and amorphous powders as precursors. The size and morphology of the boehmite nanoplates was systematically varied between hexagonal and rhombic by adjusting precursor concentrations, pH, and the synthesis temperature, due to face-specific effects. The transformation mechanism is consistent with dissolution and reprecipitation, and involves transitory initial appearance of metastable gibbsite that is later consumed upon nucleation of boehmite. Detailed X-ray pair distribution characterization of the solids over time showed similarities in short-range order that suggest linkages in local chemistry and bonding topology between the precursors and product boehmite, yet also that precursor-specific differences in long-range order appear to manifest subtle changes in resulting boehmite characteristics, suggesting that the rate and extent of water release or differences in the resulting solubilized aluminate speciation leads to slightly different polymerization and condensation pathways. The findings suggest that during dissolution of the precursor that precursor-specific dehydration or solution speciation could be important aspects of the transformation impacting the molecular level details of boehmite nucleation and growth.

36 MATERIALS SCIENCE↗