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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 OSTI2020

Biologically Diverse Genetic Engineering Platform

This project focused on methods to genetically edit arbitrary prokaryotes to convert non-agricultural biomass to industrially relevant chemicals at scale and at a price point that would be competitive with petroleum. Our target chemical for this demonstration was succinic acid, a polymer precursor that could theoretically be produced at scale from biomass. We demonstrated genetic control over a selected bacterial type strain: we can make permanent and directed changes to its genome. After thoroughly characterizing its behavior, and the circumstances under which it produced the most succinic acid, the researchers found a wild-type isolate that produces at least eight times more succinic acid than the type strain.

09 BIOMASS FUELS↗
DOE OSTI2022

Automated Production of Optimization-Based Control Logics for Dynamic Facade Systems, with Experimental Application to Two-Zone External Venetian Blinds

The primary goal of this research is to devise a system that produces controllers for complex fenestration systems that perform nearly as well as Model Predictive Control but at a level of cost and implementation complexity that rivals simple heuristic controls. To this end, a cloud-based automated controller production system has been set up for a motorized external Venetian blind device, with a simple web interface that can be used by non-experts. The computation cost per controller is in the range of a few dollars, and the control logic is simple enough to be implemented on small and cheap distributed controllers. The web interface allows the user to specify some details of their particular building and window configuration, including orientation, latitude, interior geometries, and lighting and HVAC system parameters. Upon submittal, a cloud-based system configures the necessary files and commands, and then runs thousands of optimizations with them. Once the calculations are finished, the system produces a lookup table and interpolation-based controller scripts that can be used on a simple and cheap distributed controller. This paper describes the underlying models and optimization processes. It also describes the resulting control logics for two cases tested at Lawrence Berkeley National Laboratory’s Advanced Windows Testbed Facility: illuminance maximization subject to glare constraints; and lighting + HVAC energy minimization. The performance of the model-based controllers produced by the automated web-based system are compared to a heuristic ‘block beam’ controller in physical experiments at the Testbed. The experimental results are supplemented by simulation experiments with the same configuration as the Testbed. The results show the illuminance maximizing controller significantly outperforms the heuristic controller in terms of glare avoidance, and also outperforms it in terms of hours of daylight autonomy. The energy minimizing controller also outperforms the heuristic controller. This paper also discusses how the web-based system may be extended to consider other configurations, such as electrochromic windows and thermally massive HVAC systems. Potential roles for this type of system within the building design and construction industry are discussed.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Real-time optimization of multi-cell industrial evaporative cooling towers using machine learning and particle swarm optimization

Existing electrical generating stations must operate with greater flexibility due to increasing renewable energy penetration on the electrical grid, and many coal-fired power stations have transitioned away from baseload operation to load-following operation to aid in grid stability. In cases where multiple independently controlled cooling tower cells are used in parallel for the cooling purposes of such stations, there is an opportunity to increase plant efficiency through data-driven optimization across their full load ranges. This work presents a novel application of real-time optimization using machine learning and particle swarm optimization on a multi-cell induced-draft cooling tower servicing a coal-fired power station under variable load. This is the first work to demonstrate simultaneous optimization of a multi-cell cooling tower, in addition to using machine learning for closed-loop control on a cooling tower. A novel control configuration is presented that ensures original control logic is not adversely affected and that the overall plant process is not disrupted using only existing hardware and operational data. To verify this methodology, the 12 independent cooling tower cells are simulated in parallel using historic operating data to demonstrate the effectiveness of real-time optimization compared to current practice. An artificial neural network is trained to predict overall cooling tower power consumption using only operational data and ambient conditions with an R2 value of greater than 0.96. The real-time optimization using particle swarm yields 6.7% annual energy usage savings compared to current practices, although the extent of the real-time savings varies greatly with both plant load and environmental conditions. This is particularly significant for a variable load situation because frequent ramping typically results in reduced overall efficiency. Furthermore, this proposed AI-based solution presents an opportunity to improve the overall heat rate of a load-following coal-fired power plant without the need to perform extensive first-principles modeling or add additional hardware to the cooling tower, resulting in more resources conserved and less overall emissions per unit of electricity generated.

42 ENGINEERING↗
DOE OSTI2024

Hydrogen Detection Strategies to Support H2@SCALE - The NREL Sensor Laboratory

Hydrogen represents a major pathway to decarbonize and stabilize the national and international energy industry and select manufacturing markets. To facilitate the development of hydrogen markets, the US Department of Energy initiated H2@Scale to bring together stakeholders to advance affordable hydrogen production, transport, storage, and utilization to increase revenue opportunities in multiple energy sectors. One major impediment to hydrogen implementation is cost. To expedite the use of hydrogen in energy and other markets, the United States announced in 2021 the Hydrogen Shot, which seeks to reduce the cost of clean hydrogen by 80% to $1 per 1 kilogram in 1 decade ("1 1 1"). As the cost of hydrogen drops, new applications will emerge that will require unique configurations of existing equipment and infrastructure, and eventually lead to advances in the generation and utilization of hydrogen. As the hydrogen economy expands, sensors and detection methods will need to adapt to changing infrastructure demands to address the primary targets of health & safety, emissions monitoring, and process control. The NREL Sensor Laboratory is playing a pivotal role in advancing the use of hydrogen sensors and detection methodologies in each of these categories to support DOE's mission for safe and efficient utilization in emerging markets. Health & safety monitors are required to ensure that operators and facilities can react to unintended hydrogen releases, either as GH2, LH2, or as a constituent of blends (e.g., natural gas or ammonia). Current detection methodologies focus on safety applications to detect near its lower flammable limit (4 vol %), and typically include point sensors in applications such as fixed or mobile detectors (e.g., personal gas monitors). Methodologies amenable for area detection include acoustic, emerging optical imaging methods, and flame detectors. Comparable detection strategies can be utilized for emissions monitoring and quantization, however few methods can simultaneously cover both low (emissions) and high (health & safety) levels. Deployment of emission level detectors will be required to 1) reduce product loss through small but potentially significant leaks from an environmental or cost perspective, 2) reduce downtime of high demand systems by early identification of eminent system failures (leaks through pump or compressor seals indicative of impending failure), and 3) address potential emission monitoring requirements that may be set by regulating bodies. The first two points should be adopted by industry to reduce the cost-of-goods-sold. The third main category for hydrogen detection relates to process control and may be advantageous for many existing applications. Two main applications are emerging. For example, the purity requirements for hydrogen that is dispensed from refueling systems for hydrogen fuel cell electric vehicles (FCEV) is rigorously regulated by the Standard SAE J2719, which prescribes maximum allowable levels of multiple impurities in the hydrogen fuel and must be verified by a regulatory body. Hydrogen contaminant detectors (HCD) integrated to the fueling station can assure this compliance. HCDs must be able operate in 100% H2 backgrounds and be able to distinguish between multiple contaminants at low ppm to low ppb levels. Secondly, as a strategy to decarbonize the natural gas grid, there are proposals to blend hydrogen with natural gas. This blending will affect transport applications (pipeline infrastructure), stationary combustion systems (turbines), and consumer and commercial appliances. In the short-term, hydrogen levels up to 20% are proposed. Variations in the hydrogen level can have dramatic impact on the combustion process and on the potential response of safety sensors. These mixtures may be regulated so that the concentration at a delivery point must be monitored with high precision. However, routine maintenance may introduce background gases such as ambient air (with water) or maintenance gases (introduced with welding processes or adhesive outgassing.) Therefore, the detection methodology must be robust enough to recover or respond to various contaminants. Several reviews can be found in literature addressing sensing and detection technologies, including their limitations and applications. However, for most applications, limitations can be alleviated by combining various detection techniques either through system integration or implementation of machine learning methods (artificial intelligence). In this presentation, we will discuss several applications, highlight their current approach for hydrogen detection, and suggest detection strategies to supplement their limitations.

ENERGY STORAGE,HYDROGEN↗
DOE OSTI2023

Reaction pathways and Sb(III) minerals formation during the reduction of Sb(V) by Rhodoferax ferrireducens strain YZ-1

Antimony (Sb), a non-essential metalloid, can be released into the environment through various industrial ac-tivities. Sb(III) is considered more toxic than Sb(V), but Sb(III) can be immobilized through the precipitation of insoluble Sb 2 S 3 or Sb 2 O 3 . In the subsurface, Sb redox chemistry is largely controlled by microorganisms; how-ever, the exact mechanisms of Sb(V) reduction to Sb(III) are still unclear. Here, in this study, a new strain of Sb(V)-reducing bacterium, designated as strain YZ-1, that can respire Sb(V) as a terminal electron acceptor was iso-lated from Sb-contaminated soils. 16S-rRNA gene sequencing of YZ-1 revealed high similarity to a known Fe(III)-reducer, Rhodoferax ferrireducens. XRD and XAFS analyses revealed that bioreduction of Sb(V) to Sb(III) proceed through a transition from amorphous valentinite to crystalline senarmontite (allotropes of Sb 2 O 3 ). Genomic DNA sequencing found that YZ-1 possesses arsenic (As) metabolism genes, including As(V) reductase arsC. The qPCR analysis showed that arsC was highly expressed during Sb(V)-reduction by YZ-1, and thus is proposed as the potential Sb(V) reductase in YZ-1. This study provides new insight into the pathways and products of microbial Sb(V) reduction and demonstrates the potential of a newly isolated bacterium for Sb bioremediation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Novosphingobium aromaticivorans LigR coordinates transcription of genes involved in metabolism of multiple types of aromatics

Aromatic compounds are a ubiquitous and diverse family of chemicals with functions as biomolecules, natural products, industrial chemicals, and pollutants. Novosphingobium aromaticivorans DSM 12444 uses multiple inducible pathways to catabolize H-, G-, and S-type aromatics that contain zero, one, or two methoxy groups, respectively. Here, we obtain a systems-level view of the transcriptional control of its aromatic metabolic pathways. Several in vitro analyses found that a N. aromaticivorans homolog of the Sphingobium lignivorans SYK-6 transcription factor LigR bound genomic DNA upstream of genes involved in metabolism of multiple aromatic types. We found that a ΔLigR mutant had growth defects on all three types of aromatics as sole carbon sources. Transcriptomic analysis revealed that LigR was required to increase expression of gene products that function in metabolism of all three aromatic types. We also found that, in media containing both glucose and an aromatic carbon source, the ΔLigR mutant directed intermediates through alternative aromatic metabolic pathways. Protein-DNA binding assays showed that N. aromaticivorans LigR binds immediately upstream of promoters of genes involved in aromatic metabolism. We found that N. aromaticivorans LigR coordinates the expression of enzymes that function in the catabolism of H-, G-, and S-type aromatics, and that there are differences in the role of LigR in N. aromaticivorans and S. lignivorans. A comparative genomic analysis predicted that LigR homologs and the aromatic-metabolizing genes that it directly regulates are often co-localized in the genomes of Sphingomonadales, but often not found in this arrangement in many other known aromatic metabolizing bacteria.

Aromatic Compound Degradation↗
DOE OSTI2022

Investigation of Ga 2 O 3 as a new transparent conductive oxide for photovoltaics applications

This small innovation project intended to leverage recent activity and advances in ultrawide-bandgap oxide power electronics toward the investigation of Ga 2 O 3 as a transparent conductive oxide (TCO) for use in photovoltaics (PV). Ga 2 O 3 ’s theoretical advantage over incumbent TCOs is its very large bandgap of 4.8 eV, ensuring optical transparency of photons with λ ≥ 260 nm, effectively the full terrestrial solar spectrum. At the time of proposal writing, literature on Ga 2 O 3 as a TCO/optical material was relatively sparse — what little existed was focused on for UV sensors and/or emitters, with none related to PV. As such, this project was intended to help determine the potential of Ga 2 O 3 as a PV-oriented TCO by investigating its deposition using tools common to the PV and electronics industries — atomic layer deposition (ALD) and RF sputtering (RS), both of which are already used in PV manufacturing — and its resultant optical and electronic properties. Final project goals were to test its application to Si and III-V solar cells. Controllable film thickness and excellent uniformity was established for both methods deposition methods, with ALD providing higher precision for thinner films and RS more effective for growing thicker films. The as-deposited films were found to be amorphous in nature. Spectroscopic ellipsometry (SE) confirmed bandgaps of at least 4.8 eV and non-parasitic absorption across both AM0 and AM1.5G spectra; a refractive index approaching the expected value of 1.8 was also observed, with some degree of tunability based on process parameters. Using this initial optical data, a transfer matrix model, which interfaces with in-house EQE and LIV models, was developed to simulate Ga 2 O 3 optical effects on various solar cells, included potential in antireflection coatings (ARCs). Despite promising optical properties, the resultant resistivity / conductivity metrics did not meet expectations, regardless of deposition process. Although thick RS-deposited films, using both undoped and 1 at% Ge (n-type) doped sintered targets — demonstrated high net carrier concentrations (via C-V), and low specific resistance Ohmic contacts were demonstrated, transmission line measurements (TLM) showed very high resistivity. Further analysis indicated high vertical film conductivity, but very low lateral conductivity. Deeper characterization revealed a relatively high density of nano/microcrystalline inclusions that were ostensibly the source of the vertical conductivity, with the amorphous matrix serving as an effective insulator (likely due to high concentrations of electronic trap states). Despite extensive work to increase film polycrystallinity — demonstrated via high temperature annealing — sufficient lateral conductivity for TCO use was not achieved. The final phase of the project shifted focus toward investigation of ALD-deposited Ga 2 O 3 ’s potential as a passivant and/or passivating contact for both Si and III-V solar cells, with expectation of performance similar to Al 2 O 3 . However, initial rounds of testing using our baseline ALD process yielded minimal (but not quite zero) passivation of both GaInP and Si surfaces. Dielectric passivation is well-known to be highly process sensitive; given the unoptimized nature of the process used, this work was deemed inconclusive. The final outlook with respect to feasibility of Ga 2 O 3 as a PV-oriented TCO is, ultimately, still uncertain. The work performed in this project confirmed the optical properties and deposition methods, but the achieved electrical properties do not meet technological needs; literature reports in recent years are somewhat inconsistent and potentially untrustworthy, but generally appear to be in line with our results. At the very least it is clear that, should Ga 2 O 3 still be under consideration for PV TCO and/or selective contact applications, a significant amount of optimization and study is still needed.

14 SOLAR ENERGY↗
DOE OSTI2024

Hot Springs and Geysers: Exploring Historical and Modern Impacts of Geothermal Energy Production on Associated Natural Surface Systems and Standardizing Management Practices

Surface thermal features, most notably hot springs and geysers are increasingly being recognized for their importance to ecosystems, indigenous cultures, and in some cases agriculture, recreation, and tourism. Geothermal project development poses a potential risk to these natural features but current regulatory requirements for assessing and managing these risks during exploration, permitting and monitoring are somewhat inconsistent and unpredictable across different geothermal fields. This has resulted in uncertainty and increases in exploration risk for geothermal energy developers that have led to costly project delays, cancellations, or hesitation to commit. Varying regulatory requirements may also influence public perception, fostering confusion, distrust and ultimately opposition to geothermal projects, further contributing to project delays or cancellations. At a time when there is an increasing urgency for reliable baseload clean energy, geothermal is a net-zero, renewable solution that additionally provides access to more equitable and environmentally just clean power. Continued integration of geothermal energy into the national energy roadmap can be facilitated through consistent and predictable permitting, providing regulators the framework they need, developers a clear path forward, and transparency that the public deserves. This project, currently in its beginning phases, seeks to address this important issue by providing a technical basis from which to build a preliminary protocol for assessing and managing potential impacts from new or existing geothermal energy projects to surface thermal features and their associated ecosystems. Development of this preliminary protocol will be informed by (1) a literature review of well-documented case studies in the western U.S. and New Zealand to understand the range of conditions that exemplify geothermal-surface thermal systems; (2) development of generic illustrative conceptual-numerical models to quantify, understand, and predict the first-order controls (e.g., pressure and permeability) on surface flows; and (3) additional independent and scientifically rigorous evaluations of geothermal-surface thermal system case studies from the Basin and Range Province that incorporate publicly available data as well as data provided by industry through data-sharing agreements. Learning from the successes of the process used to develop the Induced Seismicity Management Protocol (ISMP), we ultimately aim to use these initial efforts as a springboard for establishing a surface thermal feature management working group that will work collaboratively to finalize the protocol as well as co-create recommended best practices for implementation. We envision that the working group will primarily be composed of representatives from regulatory entities, government agencies, Tribes, academia, national laboratories, and industry, and will include early and regular engagement with community organizations and environmental groups. This will help ensure broad acceptance and implementation of the protocol, which will facilitate a more consistent, predictable, and standardized regulatory process, and help to ensure that geothermal energy continues to provide a reliable source of clean energy, and a pathway to achieving greater energy equity in the U.S.

Best Practices↗
DOE OSTI2023

Safety-Related Instrumentation and Control Upgrade Pilot Project: NUREG- 0711 Process Development, Planning and Analysis Activities, and Lessons Learned

Constellation Energy and the United States Department of Energy (DOE) have established a public/private partnership to implement a pilot digital upgrade to replace legacy analog, safety-related reactor protection and emergency safety feature actuation systems (RPS/ESFAS) with modern digital systems. This effort is occurring at Constellation’s Limerick Generating Station. This project is being performed in accordance with industry processes that have been adapted to better support digital upgrades. These processes include IP-ENG-001, Standard Design Process, NISP-EN-04, Standard Digital Engineering Process and Electric Power Research Institute Report 3002011816, Digital Engineering Guide. The Light Water Reactor Sustainability (LWRS) Program at the Idaho National Laboratory (INL) has been supporting this effort. Latest INL HFE efforts in support of this project have focused on definition and implementation of the Human Factors Engineering (HFE) Program in support of Constellation design and related licensing efforts. This paper presents the development execution of the HFE Program through completion of the Planning and Analysis Phase as defined by NUREG-0711 as well as HFE lessons learned.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2020

Integrating Energy Efficiency Strategies with Industrialized Construction for Our Clean Energy Future: Preprint

NREL’s Industrialized Construction Innovation Team has developed an ambitious plan to accelerate the integration of energy efficiency (EE) strategies with Industrialized Construction (IC). The United States (U.S.) construction industry is beginning to use IC methods to build multifamily apartment buildings to address affordability and labor shortages. Apart from reducing cost of construction and delivery times, the IC method of permanent modular construction has the potential to facilitate the integration of a wide range of EE strategies and advanced controls into such buildings. While there may be unintended EE benefits to IC such as a tighter envelope due to higher construction quality, the process has not been leveraged specifically to enhance EE. NREL aims to claim this missed opportunity and integrate IC benefits with EE as well as advanced controls, distributed energy resources, and grid-friendly design strategies. The paper proposes an ‘IC Assessment Framework’ to achieve affordable zero-energy modular multifamily buildings. Through the selection criteria of Design for Manufacturing and Assembly, the framework aims to distill a broad range of proven EE strategies for site-built into a set of strategies that qualify as easy to integrate for off-site. The output is a Factory Information Model (FIM) that represents a process-based digital twin to enable advanced time-and-motion study, plugs into open source building energy modeling platform (EnergyPlus), and serves as a vital tool facilitating wider adoption of EE integration. Conclusively, the paper delineates next steps for upcoming pilots with NREL’s IC partners towards developing a transformational pathway for our Clean Energy Future.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2022

Demonstration and Evaluation of the Human-Technology Integration Guidance for Plant Modernization

The significance of nuclear power in its role producing carbon-free electricity to the U.S. cannot be overstated. However, with changes in the energy market coupled with changes in incentives given to certain resources like solar and wind, the operating and maintenance costs for these sources have seen a significant reduction, which has consequently negatively impacted the economic viability of the existing U.S. nuclear power plant fleet. Digital instrumentation and control (I&C) and control room modernization is a major critical work domain to reduce operating and maintenance costs. Existing nuclear power plants are commonly configured with mostly legacy analog I&C as well as isolated pockets of digital I&C (a plant process computer, digital recorders, etc.). One challenge with this analog I&C is that replacement parts are becoming prohibitively more expensive and difficult to obtain. Moreover, a significant challenge with the existing analog I&C is that the way in which plants are currently operated and maintained is no longer competitive with other electricity generating sources, like natural gas, where advanced digital I&C technologies are commonplace. This gap between the waynuclear power plants are operated compared to other electricity generating sources significantly challenges the economic viability of the nuclear industry. Indeed, digital I&C systems can fundamentally change the way the plant is operated (i.e., the concept of operation). The introduction of digital I&C technologies offers a wealth of benefits to the nuclear industry. However, it is important to emphasize that, to realize these benefits, a careful understanding of how to integrate technology in a collaborative way that leverages the capabilities of people and technologies is necessary. Human-technology integration applies human factors engineering methods and tools to ensure the safe and reliable use of these technologies while ensuring that the inherent features of the technologies that provide economic value are not missed. The scope of this work documents the demonstration of the recently developed human and technology integration methodology, as applied to developing a new vision and concept of operations for a major U.S. nuclear power plant fleet. This report focuses on the methodological aspects of developing a vision and concept of operations. This report shares the tools, activities, and lessons learned during a modernization currently underway for industry as a whole to consider when planning any significant digital modification and developing a new vision and concept of operations.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Portable and Cost-Effective Device for Reliable Detection of Counterfeit and Non-compliant Refrigerants in Diverse Applications

Counterfeit refrigerants pose significant challenges to safety, system reliability, and operational effectiveness due to their harmful contaminants or incompatible chemical compositions. Utilizing these noncompliant products can lead to reduced efficiency, equipment failures, and expensive repairs. Additionally, heightened demand for alternative refrigerants during the industry's transition has created supply gaps, enabling counterfeit products to proliferate. Accurate detection and analysis tools are therefore essential to verify refrigerant authenticity and ensure system integrity in diverse applications. This paper presents the development of a portable device designed for reliable identification and detailed analysis of refrigerant composition. By integrating precision gas sampling, controlled pressure regulation, and automated sensor technology, the device not only detects deviations from standard refrigerant properties but also provides a comprehensive composition breakdown. Pre-calibrated sensors measure the refrigerant gas to identify specific concentrations and contaminants, with an intuitive LED-based indicator system ensuring quick interpretation of results. The user-friendly interface enables operators to select refrigerant types for targeted testing, further enhancing accuracy and usability for field technicians. Comprehensive testing was conducted on mildly flammable A2L refrigerants, showcasing the device’s robustness and adaptability in analyzing composition and detecting discrepancies. The device demonstrated consistent accuracy across a range of refrigerant samples, affirming its reliability in diverse operational environments. Its design minimizes contamination risks during sampling and provides detailed composition results within 90 seconds, ensuring efficient and precise analysis. With a projected price point under $150, the proposed solution delivers affordability alongside its lightweight portability and straightforward operation. Unlike complex and costly alternatives, such as gas chromatography systems, this device provides an accessible option for technicians, customs personnel, and industry operators in need of quick and effective refrigerant verification. Compatible with both current formulations and emerging refrigerant technologies, the device addresses critical counterfeit detection needs across a range of applications. By delivering accurate composition analysis and counterfeit identification, this innovation enhances system performance, safety, and operational reliability in crucial industries.

Cheekatamarla, Praveen [ORNL] (ORCID:0000000248827↗
DOE OSTI2024

Measuring Impact: Evaluating Thermal Zoning Simplification on Energy Efficiency Measures Analysis

Building Energy Modeling (BEM) is a versatile tool for designing, retrofitting, ensuring code compliance, obtaining certifications, qualifying for incentives, and enabling real-time building control. However, capturing all the details of building geometry for thermal zoning can be time-consuming, costly, and sometimes computationally challenging. As a result, modelers have been applying zoning simplification based on factors such as space functions and internal loads, as well as relying on their experience and judgment while adhering to zoning rules outlined in industry standards. Despite the prevalence of this common practice, a notable gap exists in the literature regarding studies quantifying the influence of simplified thermal zoning on the evaluation of Energy Efficiency Measures (EEMs). Recognizing this gap, this paper seeks to contribute to the field by enhancing the understanding of how the simplification of thermal zoning influences the evaluation of EEMs against a baseline design. The study utilized a medium office prototype model with a detailed floor plan featuring over 20 zones per floor covering diverse functional spaces with varying internal loads and occupancy schedules. A standard thermal zoning strategy outlined in ASHRAE Standard 90.1 Appendix G was employed as the simplified zoning method. This strategy condenses the zoning into a core zone and four perimeter zones per floor. It was compared with the detailed zoning approach, which involves one zone per space. Common Energy EEMs, such as enhanced envelope, high-efficiency appliances and equipment, and HVAC controls, were individually implemented and evaluated. The results indicate that the performance comparison between the two zoning methods varies depending on the type of measures considered. Basic measures, such as adding wall insulation, demonstrate similar energy impacts, while advanced HVAC control measures, such as static pressure reset, exhibit a more substantial difference that cannot be overlooked.

Xie, Jiarong↗
DOE OSTI2021

Combustion Performance and Emissions Optimization through Integration of Miniaturized High Temperature Multi Process Monitoring System

The main objective of this research program is to design, manufacture, and demonstrate a miniaturized, multi-process, monitoring system (mMPMS) for boiler condition management and easy system deployment to obtain a higher spatial resolution. This system will facilitate a Condition-Based Maintenance (CBM) philosophy that actively monitors the health of assets to predict and prevent failures and maximize availability and generating capacity at a reduced cost. CBM systems can provide boiler data that the advanced process control (APC) system can utilize for plant performance optimization, which is increasingly relevant as coal power plants shift from predominantly base-load operation to predominantly transient operation involving large load swings. The mMPMS is based on an electrochemical sensor that provides a real-time indication of the risk of damage to key locations in the radiant or convective section of a coal-fired boiler such as metal loss rates, heat flux, metal surface temperature, and deposit thickness. These indications can be utilized to optimize boiler performance as well as improve boiler availability in conjunction with corresponding operating conditions. This monitoring system was developed and tested in the high-temperature regions of coal-fired utility boilers in this project but can be applied to many other industries and applications as well. The new sensor design, leveraging the existing electrochemical noise-based monitoring system, is small enough to be installed through the webbing of the waterwalls without the need for long shut-downs to bend tubes and to make it feasible to obtain high spatial resolution in the boiler. Data can be transferred to the plant distributed control system (DCS) and any other control system. The sensor body that houses the sensor assembly was designed to ensure good conductive contact with boiler tubes to ensure the sensor is held at an identical temperature to the tube surface temperature. The data acquisition and signal conditioning modules were redesigned into a small footprint with optimized cooling of the module. System software was developed specifically for the new signal conditioning module and is compatible with plant PLCs. After the preliminary testing at a pilot-scale facility, five mMPMS were installed at a full-scale pulverized coal-fired plant, Basin Electric Power Cooperative’s Leland Olds Unit 1. The systems were demonstrated over a 6-week period during typical operation. Sensor measurements of deposit thickness were validated during the demonstration and subsequently leveraged to determine sensor-based boiler cleaning strategies. These strategies have the benefit of reduced thermal stresses on boiler tubes from over-cleaning and improved boiler water management. At the end of the project, continued development of the sensor technology was carried out at PacifiCorp’s Hunter Station. REI leveraged the permanent installation of the mMPMS in Unit 3 made possible by DOE funding on a separate program. The work at Hunter Plant focused on application of machine learning and artificial intelligence-based models for integration of sensor signals into control and optimization of Hunter Unit 3 processes.

Advanced Sensors, Corrosion, Ash Deposition, Optim↗
DOE OSTI2022

Combustion Performance and Emissions Optimization Through Integration of a Miniaturized High-Temperature Multi Process Monitoring System

The main objective of this research program is to design, manufacture, and demonstrate a miniaturized, multi-process, monitoring system (mMPMS) for boiler condition management and easy system deployment to obtain a higher spatial resolution. This system will facilitate a Condition-Based Maintenance (CBM) philosophy that actively monitors the health of assets to predict and prevent failures and maximize availability and generating capacity at a reduced cost. CBM systems can provide boiler data that the advanced process control (APC) system can utilize for plant performance optimization, which is increasingly relevant as coal power plants shift from predominantly base-load operation to predominantly transient operation involving large load swings. The mMPMS is based on an electrochemical sensor that provides a real-time indication of the risk of damage to key locations in the radiant or convective section of a coal-fired boiler such as metal loss rates, heat flux, metal surface temperature, and deposit thickness. These indications can be utilized to optimize boiler performance as well as improve boiler availability in conjunction with corresponding operating conditions. This monitoring system was developed and tested in the high-temperature regions of coal-fired utility boilers in this project but can be applied to many other industries and applications as well. The new sensor design, leveraging the existing electrochemical noise-based monitoring system, is small enough to be installed through the webbing of the waterwalls without the need for long shut-downs to bend tubes and to make it feasible to obtain high spatial resolution in the boiler. Data can be transferred to the plant distributed control system (DCS) and any other control system. The sensor body that houses the sensor assembly was designed to ensure good conductive contact with boiler tubes to ensure the sensor is held at an identical temperature to the tube surface temperature. The data acquisition and signal conditioning modules were redesigned into a small footprint with optimized cooling of the module. System software was developed specifically for the new signal conditioning module and is compatible with plant PLCs. After the preliminary testing at a pilot-scale facility, five mMPMS were installed at a full-scale pulverized coal-fired plant, Basin Electric Power Cooperative’s Leland Olds Unit 1. The systems were demonstrated over a 6-week period during typical operation. Sensor measurements of deposit thickness were validated during the demonstration and subsequently leveraged to determine sensor-based boiler cleaning strategies. These strategies have the benefit of reduced thermal stresses on boiler tubes from over-cleaning and improved boiler water management. At the end of the project, continued development of the sensor technology was carried out at PacifiCorp’s Hunter Station. REI leveraged the permanent installation of the mMPMS in Unit 3 made possible by DOE funding on a separate program. The work at Hunter Plant focused on application of machine learning and artificial intelligence-based models for integration of sensor signals into control and optimization of Hunter Unit 3 processes.

Advanced Sensors, Corrosion, Ash Deposition, Optim↗
DOE OSTI2022

Assessing effective radiative forcing from aerosol–cloud interactions over the global ocean

How clouds respond to anthropogenic sulfate aerosols is one of the largest sources of uncertainty in the radiative forcing of climate over the industrial era. This uncertainty limits our ability to predict equilibrium climate sensitivity (ECS)—the equilibrium global warming following a doubling of atmospheric CO 2 . Here, we use satellite observations to quantify relationships between sulfate aerosols and low-level clouds while carefully controlling for meteorology. We then combine the relationships with estimates of the change in sulfate concentration since about 1850 to constrain the associated radiative forcing. We estimate that the cloud-mediated radiative forcing from anthropogenic sulfate aerosols is − 1.11 ± 0.43 W m −2 over the global ocean (95% confidence). This constraint implies that ECS is likely between 2.9 and 4.5 K (66% confidence). Our results indicate that aerosol forcing is less uncertain and ECS is probably larger than the ranges proposed by recent climate assessments.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

A comparison of ceramic and carbon-based reductants for vitrification of low-activity waste

Sucrose is the current baseline additive at the Hanford Waste Treatment and Immobilization Plant in Washington, USA to control foaming during waste feed to glass transitions and the redox state of the glass melt. Alternative reductants are being investigated to alleviate strain on effluent treatment from toxic acetonitrile production from incomplete combustion of sucrose. This study evaluates ceramic additive options including B4C, B6Si, SiC and VB2 in simulated low-activity waste feed, as well as coke dust, probing the feed volume expansion during melting as well as the gas evolution. All alternative reductant options examined significantly reduced acetonitrile production, however there was variability in their effectiveness as foam-reducing agents. VB2 and coke at the appropriate ratios were similarly effective as sucrose in controlling both foam volume and glass redox state, but with considerably less acetonitrile production. B4C, B6Si and SiC showed more promising foam control and very little acetonitrile production, however all of the final glasses were over reduced, i.e., Fe2+/FeT = 0.5. These alternative reductant studies provide operational flexibility to the operation of the vitrification plant, as well as options for alternative raw materials in industrial glass melting.

Rigby, Jessica C. (ORCID:0000000235719977)↗