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At least 163 records · Page 9

Y-12 Lean Six Sigma Marketing Plan 2018

The Lean Six Sigma (LSS) organization at Y-12 sponsors the deployment of Performance Enterprise System (PES) and provides continuous improvement facilitation and training for the Y-12 site. The Lean Six Sigma organization is comprised of Subject Matter Experts (SME) who are passionate about continuous improvement and helping organizations improve their processes. The LSS group includes Support Leads, who perform various PES deployment activities, and Black Belts who use Lean, Six Sigma, and other leadership and project management tools to scope, analyze, and expertly facilitate teams on multifaceted improvement projects to meet safety, security, quality, timeliness, and/or cost savings goals. LSS is a group of change agents who help initiate continuous improvement throughout the Y-12 site. The ultimate goal of this marketing plan is to build a consistent, positive, and influential brand throughout Y-12. This brand will provide employees with information about the Lean Six Sigma organization, generate desire for employees to take the Performance Enterprise System training course, and to improve continuously.

99 GENERAL AND MISCELLANEOUS↗

On the Path to SunShot. Advancing Concentrating Solar Power Technology, Performance, and Dispatchability

This report examines the remaining challenges to achieving the competitive concentrating solar power (CSP) costs and large-scale deployment envisioned under the U.S. Department of Energy's SunShot Initiative. Although CSP costs continue to decline toward SunShot targets, CSP acceptance and deployment have been hindered by inexpensive photovoltaics (PV). However, a recent analysis found that thermal energy storage (TES) could increase CSP's value--based on combined operational and capacity benefits--by up to 6 cents/kWh compared to variable-generation PV, under a 40% renewable portfolio standard in California. Thus, the high grid value of CSP-TES must be considered when evaluating renewable energy options. An assessment of net system cost accounts for the difference between the costs of adding new generation and the avoided cost from displacing other resources providing the same level of energy and reliability. The net system costs of several CSP configurations are compared with the net system costs of conventional natural-gas-fired combustion-turbine (CT) and combined-cycle plants. At today's low natural gas prices and carbon emission costs, the economics suggest a peaking configuration for CSP. However, with high natural gas prices and emission costs, each of the CSP configurations compares favorably against the conventional alternatives, and systems with intermediate to high capacity factors become the preferred alternatives. Another analysis compares net system costs for three configurations of CSP versus PV with batteries and PV with CTs. Under current technology costs, the least-expensive option is a combination of PV and CTs. However, under future cost assumptions, the optimal configuration of CSP becomes the most cost-effective option.

14 SOLAR ENERGY↗

Integrating vehicle trajectory planning and arterial traffic management to facilitate eco-approach and departure deployment

Eco-approach and departure (EAD) enable continuous vehicle motion in urban signalized corridors. Since such a motion can extend to the EAD vehicles’ followers, it makes EAD a promising technology to benefit the traffic flow where automated vehicles and conventional vehicles coexist. Most existing EAD studies envision an ideal setting that neglects real-world operational conditions such as lane changes, multi-movement intersection configuration, partially automated fleet, and/or limited traffic state awareness. This study aims to fill the gap by designing an EAD algorithm considering real-world traffic operation constraints. The proposed algorithm uses a model predictive controller to minimize vehicle speed reduction and variation based on the real-time traffic signal control plan and measured queues at the intersection. The required inputs are readily available at many modern intersections. We observed that the proposed controller’s performance might degrade because of lane-changing maneuvers and lead-left turn traffic signals. These observations motivated our development of a lane change management strategy and a signal control implementation strategy to facilitate the EAD implementation. The lane change management strategies separate the EAD operations and lane-changing maneuvers in time and space. The signal control implementation strategy applies lag-left turn signals to enable EAD operation for both the through and left-turn vehicles. Compared to the non-EAD case, our EAD approach produces 2.5% to 7.8% energy savings while keeping similar intersection mobility. Notably, this approach brings about 2.5% to 3.6% energy savings in a 2% CAV case. This result demonstrates the feasibility of deploying EAD at low connected automated vehicle penetration rates.

Arterial corridor management↗

Summertime Aerosol across the North Slope of Alaska Field Campaign Report

The Summertime Aerosol across the North Slope of Alaska U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility field campaign, a collaborative effort between the University of Michigan and Baylor University, was focused on chemically characterizing sources of summertime aerosol impacting the Utqiagvik (Barrow, NSA) and the Oliktok Point (AMF3) ARM sites. This campaign was co-funded by a grant from the National Oceanic and Atmospheric Administration (NOAA, PI: Kerri Pratt, Co-I: Rebecca Sheesley) titled “Assessment of Atmospheric Aerosols Resulting from Oil and Gas Extraction Activities near the North Slope of Alaska”. The ARM field campaign took place on the North Slope of Alaska (NSA) from August 21 to September 30, 2015 and August 12 to September 20, 2016, with filter sampling occurring both years at both the NSA Barrow and AMF3 Oliktok Point sites. Online intensive measurements occurred at Barrow in 2015 and at Oliktok Point in 2016, coordinated with the arrival of the ARM Aerosol Observing System (AOS) in August 2016 at Oliktok Point. During 2015, the University of Michigan deployed the newly constructed aerosol time-of-flight mass spectrometer (ATOFMS), as well as a microanalysis particle sampler (MPS) to collect particles for offline analysis by computer-controlled scanning electron microscopy with energy-dispersive x-ray spectroscopy (CCSEM-EDX). Unfortunately, an issue with the time-of-flight mass spectrometer on the ATOFMS limited the number of particles that produced mass spectra during the 2015 study. This issue was subsequently fixed for the 2016 deployment. During 2016, the ATOFMS was deployed to the AMF3 at the Oliktok Point field site, in addition to a micro-orifice uniform deposition impactor (MOUDI) to collect particles for offline analysis by CCSEM-EDX. Notably, these measurements, to our knowledge, represent the first real-time, single-particle chemical characterization (aerosol mixing state) measurements at Utqiagvik and Oliktok Point. Online aerosol measurements also included: PM2.5 (particulate matter <2.5 μm) black carbon mass concentrations (aethalometer; Baylor) and size-resolved (0.013-20 μm) number concentrations (scanning mobility particle sizer, SMPS, and aerodynamic particle sizer, APS; Michigan). Baylor conducted filter sampling at both the Utqiagvik and Oliktok Point locations during both intensive operational periods (IOPs). Baylor deployed a total suspended particulate matter (TSP) sampler to Oliktok Point, and continuous one-week samples were collected in 2015 for a total of seven samples; during 2016, continuous 3-7 day samples were collected, for a total of 13 filters. Baylor deployed a TSP sampler and a PM1.0 sampler at Utqiagvik, Alaska; continuous 4-7 day filter samples were collected in 2015 for a total of eight samples. To supplement this campaign, PI Sheesley had a simultaneous DOE ARM field campaign at Utqiagvik and Oliktok Point (https://www.arm.gov/research/ campaigns/amf2016bbc), the goal of which was to collected continuous one-week TSP samples at both sites from June 2016 to September 2017. These results provide better context in terms of annual trends and for year-to-year variability and a final report with data was already submitted by PI Sheesley for that project. Analysis by Baylor focuses on TSP samples because of the extremely low PM loading on the PM1.0 sampler. Michigan deployed a three-stage impactor (0.07-5 μm PM collection) at Utqiagvik and a 10-stage impactor (0.056-10 μm PM collection) at Oliktok Point, during the 2015 and 2016 campaigns, respectively.

Arctic processes, North Slope of Alaska, Barrow, O↗

Expedited desalination permitting enables adaptive planning and water system cost reduction

Seawater desalination is a drought-proof water supply for coastal cities, but widespread development of desalination plants in the U.S. has been limited by both cost and the complexity of permitting processes designed to minimize environmental impact . This work estimates the value of accelerating the permitting timeline without changing environmental or social standards. On average, faster permitting reduces the frequency of desalination plant construction and operation, the overall costs of robust water system operation, the environmental impacts of drought-tolerant water supplies due to shorter duration of plant operation. Expedited permitting allows fundamental changes in how water infrastructure is deployed, facilitating a transition from anticipatory construction and continuous operation of seawater desalination capacity as a redundant drought buffer to just-in-time (i.e. adaptive) deployment of seawater desalination capacity when critical drought thresholds are crossed. We demonstrate the value of expedited desalination permitting in enabling adaptive planning and reducing water system costs using a simple case study in Santa Barbara, CA. We discuss additional forms of adaptive water infrastructure planning as enabled by faster permitting and address their challenges and opportunities. Lastly, we identify synergies between innovation in adaptive planning, innovation in expedited permitting practices, and innovation in water technology.

adaptive planning↗

A National Infrastructure for Artificial Intelligence on the Grid (NI4AI) (Final Scientific/Technical Report)

Electric utilities have traditionally taken a very pragmatic yet myopic approach with grid sensors and the resulting collected data. Sensors are purchased and deployed to solve a specific, known problem that has risen to sufficient awareness as to justify the effort of deploying sensors and the needed capital investment. This sensor data flows into proprietary software packages with limited functionality intended only to address the initial problem. This approach aligns with the financial incentives of the utility to deploy capital into fixed hardware assets for which the corporations earn a rate of return. This mentality stands in stark contrast to the big data revolution that started nearly 25 years ago with the rise of Google. In this worldview, data is a fundamental business asset; successful organizations collect, store, explore, merge, and exploit as much data as possible to not only solve problems well understood today but also to tackle new problems that will inevitably rise tomorrow. The ARPA-E Open Innovation 2018 project entitled A National Infrastructure for Artificial Intelligence on the Grid or NI4AI for short was designed to demonstrate this alternative paradigm for using data. To do this, the project was composed of three key thrust areas. The first major component deployed a variety of high-frequency grid sensors and captured terabytes of both wide-scale and localized grid measurements, generating high-value datasets for grid research and algorithm development. The second aspect made available PingThings’ PredictiveGridTM, a horizontally scalable, cloud-based data management and AI platform built for time series data to explore and exploit the collected data. Finally, the project fostered a diverse and open research community composed of experts from numerous fields through focused educational content, code sharing, and data science competitions. Shifting away from “single use” sensors and closed data silos within electric utilities is a major benefit to the public at large. This legacy approach to data is incredibly (1) capital intensive (new sensors must be deployed for each new problem and problems tend to arise continuously) and (2) painfully slow (new problems must be identified first and then new sensors must be deployed to collect data to begin to address the issue). The transition to a carbon neutral grid requires a massive transformation of the existing grid infrastructure and will continue to challenge the legacy grid in unforeseen ways. The only way to make the energy transition cost effective is for utilities to abandon this dated data paradigm and adopt more contemporary approaches. NI4AI has shown that it is technically possible and economically feasible to ingest, explore, and exploit grid data collected from even very high frequency sensing, such as continuous point on wave sensors collecting measurements 10,000 times a second. In fact, the PredictiveGrid platform used is commercially available and deployed at several utilities in the United States. Project accomplishments were numerous and included (1) making available a state of the art time series platform to the community, (2) collecting over 520 streams of time series data from grid sensors totaling over 1 trillion grid measurements, and (3) developing and nurturing a community within the industry focused on the use of data to create value for utilities and, ultimately, end consumers.

97 MATHEMATICS AND COMPUTING↗

Mechanically induced thermal runaway severity analysis of Li-ion batteries and continuous energy release monitoring

The large-scale deployment of Li-ion batteries in stationary energy storage and electrical vehicle applications demands a strong focus on safety, particularly on the thermal runaway risk and severity evaluation. A standardized single-side mechanical indentation test protocol was developed to induce an internal short-circuit (ISC) and evaluate cells' thermal runaway severity at different state of charge (SOC). The observed hazard severity (OHS in five categories) and evaluated scores in this work have a comprehensive consideration of each cell's capacity, initial voltage, SOC, temperature and voltage change, allowing a better evaluation of the cells' thermal runaway potential. This method was applied to about 200 Li-ion batteries in order to build an extensive thermal runaway database covering various SOCs, capacities and chemistries. In this study, we monitored the transitions of stored electrochemical energy and applied mechanical energy into both thermal energy and acoustic emissions (AE). The surface temperature and mechanical failures were monitored by infrared imaging and AE to capture critical events within battery cells throughout the mechanical indentation tests. Furthermore, the initial temperature maps can predict two types of follow-up events: thermal runaway or gradual heat release via conduction. Analyzing each cell's severity, AEs, and leveraging the evolving database offer insights into predicting occurrences of thermal runaway. The test method, thermal runaway severity evaluation and prediction, and the corresponding database provide battery designers, manufacturers, and end-users a clear overview of Li-ion batteries' thermal runaway potential under mechanical abuse, advancing the safety design of Li-ion batteries.

Acoustic emission↗

CORRTEX Diagnostic Deployment for the SPE-III experiment, 24 July 2012: Fielding Report and Preliminary Data Analysis

The Continuous Reflectometry for Radius vs Time Experiments (CORRTEX) diagnostic system was deployed for the third explosives test in the Source Physics Experiment (SPE) sequence to monitor and verify several conditions of the experiment including the detonation velocity of the explosive package and functioning of explosive initiators. Six distance-marked coaxial cables were installed on the SPE-III explosives canister, and key locations documented through along-cable length measurements and photography. CORRTEX uses electrical-pulse time-domain reflectometry to continuously record the two-way transit time (TWTT) of the cables. As the shock front of the detonation advances, the coaxial cable is shorted or destroyed, and the resulting TWTT also decreases. Interpretation of these changes as a function of TWTT can be converted to positional measurements using known parameters of the cables.

47 OTHER INSTRUMENTATION↗

FRONT-END ELECTRONICS FOR UNATTENDED SAFEGUARDS SYSTEMS: TESTING OF A CANDIDATE DEVICE

The International Atomic Energy Agency (IAEA) deploys unattended monitoring systems to provide continuous monitoring of nuclear material within safeguarded facilities around the world. As the number of unattended monitoring instruments increases, the IAEA is challenged to become more efficient in the implementation of those systems. In 2010, the IAEA initiated the Front-End Electronics for Unattended Measurement (FEUM) project with the goals of greater flexibility in the interfaces to various sensors and data acquisition systems, and improved capabilities for remotely located sensors (e.g., where sensor and front-end electronics might be separated by tens of meters). In consultation with the IAEA, a technical evaluation of a candidate FEUM device produced by a commercial vendor is being performed. This evaluation is assessing the device against the IAEA’s original technical specifications and a broad range of important parameters that included sensor types, cable types, and industrial electromagnetic noise that can degrade signals from remotely located detectors. Testing has been performed in a laboratory and also in environments representative of IAEA deployments. The results are expected to inform the IAEA about where and how FEUM devices might be implemented in the field. Data and preliminary findings from the testing performed to date are presented.

Smith, Leon E.↗

Geomechanical modeling of distributed fiber-optic sensor measurements

Fiber-optic-based distributed acoustic sensors (DAS) are a new technology that can be deployed in a well and are continuously interrogated during operations. These sensors calculate the strain (or strain rate) at all points along the fiber and have been used extensively to monitor hydraulic stimulations. The data from these sensors indicate that they are sensitive to high-frequency signals associated with microseismicity and low-frequency signals associated with fracture growth. We have developed a set of idealized models to simulate these signals and to identify interpretation methods that may be used to estimate fracture location, geometry, and extent. We use a multiphysics code that includes rock physics, fluid flow, and elastic-wave propagation to generate synthetic DAS measurements from a set of simple models that mimic hydraulic fracturing. We then relate the signals observed in the synthetic DAS to specific features in the model such as fracture height, width, and aperture. Our results demonstrate that the synthetic DAS measurements may be used to determine field DAS measurements and to optimize the design of future sensor deployments for sensitivity to fracture attributes.

03 NATURAL GAS↗

Crossing the Barriers: An Analysis of Land Access Barriers to Geothermal Development and Potential Improvement Scenarios

Developers have identified many non-technical barriers to geothermal power development, including access to land. Activities required for accessing land, such as environmental review and private and public leasing can take a considerable amount of time and can delay or prevent project development. This paper discusses the impacts to available geothermal resources and deployment caused by land access challenges, including tribal and cultural resources, environmentally sensitive areas, biological resources, land ownership, federal and state lease queues, and proximity to military installations. In this analysis, we identified challenges that have the potential to prevent development of identified and undiscovered hydrothermal geothermal resources. We found that an estimated 400 MW of identified geothermal resource potential and 4,000 MW of undiscovered geothermal resource potential were either unallowed for development or contained one or more significant barriers that could prevent development at the site. Potential improvement scenarios that could be employed to overcome these barriers include (1) providing continuous funding to the U.S. Forest Service (USFS) for processing geothermal leases and permit applications and (2) the creation of advanced environmental mitigation measures. The model results forecast that continuous funding to the USFS could result in deployment of an additional 80 MW of geothermal capacity by 2030 and 124 MW of geothermal capacity by 2050 when compared to the business-as-usual scenario. The creation of advanced environmental mitigation measures coupled with continuous funding to the USFS could result in deployment of an additional 97 MW of geothermal capacity by 2030 and 152 MW of geothermal capacity by 2050 when compared to the business-as-usual scenario. The small impact on potential deployment in these improvement scenarios suggests that these 4,400 MW have other barriers to development in addition to land access. In other words, simply making more resources available for development does not increase deployment; however, impacts to deployment could increase when coupled with other improvements (e.g., permitting, market and/or technology improvements).

15 GEOTHERMAL ENERGY↗

Development of an automated high-temperature valveless injection system for online gas chromatography

A reliable method of sample introduction is presented for online gas chromatography with a special application to in situ field portable atmospheric sampling instruments. A traditional multi-port valve is replaced with a valveless sample introduction interface that offers the advantage of long-term reliability and stable sample transfer efficiency. An engineering design model is presented and tested that allows customizing this pressure-switching-based device for other applications. Flow model accuracy is within measurement accuracy (1%) when parameters are tuned for an ambient-pressure detector and 15% accurate when applied to a vacuum-based detector. Laboratory comparisons made between the two methods of sample introduction using a thermal desorption aerosol gas chromatograph (TAG) show that the new interface has approximately 3 times greater reproducibility maintained over the equivalent of a week of continuous sampling. Field performance results for two versions of the valveless interface used in the in situ instrument demonstrate typically less than 2% week -1 response trending and a zero failure rate during field deployments ranging up to 4 weeks of continuous sampling. Extension of the valveless interface to dual collection cells is presented with less than 3% cell-to-cell carryover.

Kreisberg, N. M.↗

Deployment Readiness Framework for Marine Energy

As electricity prices continue to rise and extreme weather events related to climate change become more frequent, many island and remote coastal communities are prioritizing their energy future. Isolated locations and coastal environments pose challenges for energy costs and grid resilience, but the ocean can be a key solution. Marine energy could provide these communities with clean, affordable, and reliable power. The U.S. Department of Energy's (DOE) National Renewable Energy Laboratory and Pacific Northwest National Laboratory are developing the Deployment Readiness Framework (DRF) to support remote, coastal, and island community-driven energy transitions. This framework can be used to better understand the readiness of communities for marine energy technology demonstration projects and their operation. The DRF builds on the Energy Transitions Initiative Partnership Project (ETIPP) supported in part by DOE's Water Power Technologies Office.

community readiness↗

Average and Marginal Capacity Credit Values of Renewable Energy and Battery Storage in the United States Power System

As deployment of renewable resources and storage continue to significantly grow in the coming decades, these technologies will play increasingly important roles in maintaining power systems' resource adequacy. Few analyses so far offer comprehensive comparisons of forward-looking average and marginal capacity credits of variable renewable energy and storage in the U.S. interconnections across a wide range of possible futures. To fill this research gap, we quantify the average and marginal capacity credits of solar PV, onshore and offshore wind, and batteries between 2026 and 2050 across the U.S power systems to examine the temporal trends, spatial patterns, and trade-offs between these two capacity accreditation approaches. Across technologies, capacity credits of solar PV most clearly follow downward trends over time, reflecting the significant rise in solar PV generation share as the grid decarbonizes. While battery storages' generation shares also rise significantly over time, their capacity credits always remain stably high due to their capabilities to be dispatched strategically during critical periods to maintain reliability. On the other hand, capacity credits of wind technologies in general follow slight upward trends as their generation shares level off. There are strong spatial variabilities of both average and marginal capacity credits across technologies, but capacity credits of solar PV displaying the most obvious spatial patterns with high capacity credits concentrating in wind-rich, solar-poor regions in SPP, PJM, and MISO, suggesting potential reliability benefits of interconnection-wide planning for renewable energy deployments. Additionally, except for offshore wind, average capacity credits of all other renewable technologies tend to be higher than their marginal capacity credits, indicating that existing renewable resources tend to be accredited higher than new resources at almost any time.

25 ENERGY STORAGE↗

Cross-domain digital twin architecture for predictive maintenance via machine learning and Large Language Models

This research introduces a comprehensive framework for creating and deploying a digital twin platform for continuous monitoring and predictive maintenance within industrial settings. Through utilizing advanced technologies, including Unreal Engine 5, Unity 3D, the Message Queue Telemetry Transport protocol, Random Forest machine learning algorithms, and Large Language Models (LLMs), we establish a platform that digitally reproduces physical equipment and translates digital controls into real-world actions. This facilitates preventive maintenance approaches and improves operational effectiveness. The digital twin platform gathers sensor data from operational equipment, analyzes it using machine learning, and delivers practical insights to prevent potential malfunctions and enhance equipment performance. Furthermore, the incorporation of a web portal enables efficient monitoring and access to historical data, educational materials, and equipment status information. Preliminary findings indicate that digital twins can transform industrial equipment management and maintenance methodologies.

97 MATHEMATICS AND COMPUTING↗

Tethys: Developing a Commons for Understanding Environmental Effects of Ocean Renewable Energy

A lack of consistent widespread information on potential environmental effects, monitoring outcomes, and mitigation strategies continues to hinder the development and deployment of marine energy systems around the world. To address this need, member nations of the Ocean Energy Systems (OES) formed Annex IV, a three-year collaborative effort (2010-2013) to increase knowledge sharing, research collaborations, and efficient regulatory decision-making associated with investigating and evaluating the potential impacts of wave and tidal energy. In parallel, the US Department of Energy began development of a publically-available, searchable online database of environmental information (called Tethys), housing scientific literature pertaining to the environmental effects of marine energy and offshore wind systems, as well as metadata on international ocean energy projects and research studies collected under Annex IV. In addition to providing broad access to information on environmental effects of marine energy and offshore wind developments, Tethys can act as a commons for bringing together researchers, device and project developers, regulators, and stakeholders, to explore shared interests and information needs for the emerging marine energy industry. This paper will demonstrate the development, existing functionality, and content of Tethys, as well as discuss the future of Annex IV including information updates, improvements, and additional outreach efforts over the next several years.

marine energy, offhore wind, environmental effects↗

Development and testing of a continuous maritime monitor for radionuclide aerosols

Monitoring airborne concentrations of radionuclide activity may provide a timely warning to sea-based assets to avoid contamination from a radioactive plume. The development and testing of an automated aerosol monitoring system that can capture and detect radioactive particulate from marine air is presented. A custom electrostatic precipitator (ESP) was designed to capture particulate onto a reusable collection media. The collection efficiency of the ESP system for radon progeny was determined to be ~23%. A conservative calculation of the minimum detectable concentration of 214 Bi was estimated as 0.3-8 Bq/m 3 . The system was demonstrated in continuous operation, without consumables and limited maintenance, in a marine environment at the PNNL campus in Sequim, Washington. In conclusion, a successful 2-month deployment indicates the feasibility of the approach for continuous maritime monitoring for radionuclide aerosols.

Moore, Michael E. [Pacific Northwest National Labo↗

Iron Redox Chemistry and Its Environmental Impact: A Virtual Special Issue

Special Editorial Issue. Iron (Fe) is the most abundant redox-active element at the Earth’s surface. It occurs in diverse host rock lithologies, sediments, and soils as accessory oxide and oxyhydroxide minerals and nanoparticles that can dominate the reactive mineral/water interfacial area. Furthermore, designer Fe oxide nanoparticles produced to exploit the catalytic properties of specific mineral surfaces continue to undergo rapid development and deployment for a variety of purposes, including environmental remediation. The structure, charge, and chemical dynamics at these interfaces with aqueous solutions strongly impacts their interaction with other elements, organics, and contaminants. The influence of important environmental factors, especially oxygen concentration, natural organic matter, microbes, etc. remain poorly understood. Key interfacial processes can be driven by both biotic and abiotic mechanisms.

Iron redox, special issue, mechanisms, biogeochemi↗