Smart pixels with data reduction at source
Smart pixels with data reduction at source.
43 PARTICLE ACCELERATORS↗
SEARCH · Engineering Papers
Results for “SMART”
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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A Smart Alarm for the CEBAF Injector
We present initial results from a proof-of-concept ?smart alarm? for the CEBAF injector. Because of the injector's large number of parameters and possible fault scenarios, it is highly desirable to have an autonomous alarm system that can quickly identify and diagnose unusual machine states. Our approach leverages a trained neural network to not only identify an anomalous machine state, but also to identify the root-cause by pinpointing the specific element or region responsible. We developed an inverse model trained on data collected during normal operations. Using the inverse model, measurements from the machine are used to compute machine settings, which are then compared to EPICS setpoints. Instances when predictions differ from EPICS setpoints by a user-defined threshold are flagged as anomalies, and the user is alerted to the issue. We present the results of our data collection efforts, model training and performance, and initial performance metrics.
Tennant, C.↗
SMART Deliverable 6.1.2a: Application of the ORION tool to the IBDP Carbon Storage Site
Forecasting and managing potential induced seismic activity is one of the challenges facing commercialscale geologic carbon sequestration (GCS), as well as other geologic energy extraction and byproduct disposal technologies. Historically, the process to develop robust, science-based forecasts of induced seismicity has required an integrated effort from experts in seismology, geomechanics, and reservoir engineering to manage data, develop and evaluate models of subsurface processes, and to calibrate and interpret the results from a range of models to understand site behavior relative to prescribed standards and in the context of uncertainty in geologic characterization data, forecasting models, and operational scenario uncertainty. The Operational Forecasting of Induced Seismicity (ORION) toolkit is an open-source, observation-based forecasting toolkit that is being co-developed by two U.S. DOE-funded initiatives: the National Risk Assessment Partnership (NRAP) and the Scienceinformed Machine Learning for Accelerating Real Time Decisions in Subsurface Applications (SMART) Initiative. ORION is designed to provide functionality to support decision making about seismic hazard analysis and risk management for GCS stakeholders ranging from the public to site operators to expert seismologists. The tool, which is written as open-source code in the Python programming language, is composed of a desktop graphical user interface (GUI) and an underlying forecasting engine. The forecasting engine uses available reservoir properties, well and fluid injection scenario details, and observed seismic catalog data as inputs to produce a set of temporal and spatio-temporal seismic forecasts.
58 GEOSCIENCES↗
W-SMART Phase-I Pathway Analysis: Case Study - City of Boston, MA
The purpose of this study is to synthesize stakeholder and research learnings to date by exercising PNNL’s Waste - Sustainability Monitoring of Alternative Reuse Options over Time (W-SMART) sustainability protocol for the Greater Boston region. This report serves as a foundation for future discussion and project work to characterize the costs, risks, impacts, tradeoffs, and highest uses for major waste streams. This analysis differs from previous work by 1) incorporating results of a newly completed detailed resource assessment for the Greater Boston area; (2) providing a head-to-head pathway comparison without any policy supports (e.g., carbon or energy credits); and (3) focusing on locally relevant critical waste streams and reuse strategies, by assessing the cost-effectiveness of two complimentary pathways, including (a) expanded incineration of municipal solid waste (MSW) at existing treatment sites to produce baseload electricity, and (b) the conversion of blended municipal wastewater solids (i.e., sludge) and non-residential food waste to produce liquid transportation biofuels at a proposed hydrothermal liquefaction facility in Quincy, MA. The performance of each pathway is also compared to assumed business-as-usual waste management practices as a baseline.
09 BIOMASS FUELS↗
Optimizing Residential HVAC Systems: Evaluating How the Usage of Smart Diagnostic Tools for Quality Installation and Commissioning Impacts System Performance and HVAC Contractor Businesses
The adoption of digital quality installation and fault detection tools has the potential to transform the $14 billon residential heating, ventilating, and air conditioning (HVAC) service and installation industry. Increased market penetration can be accelerated by providing an increased understanding of the energy and economic value proposition of the usage of these tools. In tandem with energy and HVAC system performance impact research and analysis, the Southface Team investigated the economic business implications for HVAC service and installation contractors adopting the use of measureQuick (mQ), a smart diagnostic app that aids in quality installation and fault detection and works agnostically with Bluetooth-enabled HVAC technician tools.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
Comparison of ML-Based Proxy Modeling Strategies: Lessons Learned from the SMART Initiative
Teams of researchers on Task 5 of the SMART project have developed a variety of modeling architectures to predict subsurface behavior during carbon injection and post-injection periods. One important part of this task was to compare the candidate approaches in terms of accuracy, reliability, speed, and memory use, all using a common set of metrics and visualizations for an “apples to apples” comparison. Dr. Jared Schuetter will share the details of this task, the results that were obtained, and the lessons learned.
Schuetter, Jared↗
Smart CO2 Transport-Route Planning Tool: Providing Data and Insights for Accelerating Carbon Transport & Storage Deployment
Overview presentation given at the 2024 FECM / NETL Carbon Management Research Project Review Meeting on NETL's Bipartisan Infrastructure Law-funded Smart CO2 Transport-Route Planning Tool and associated geodatabase. This machine learning informed, data-driven public resource was designed to inform regulators, industry, and researchers plan and develop safe and efficient transport routes across the country.
Romeo, Lucy↗
Enabling the Next Generation of Smart Sensors in Coal Fired Power Plants using Cellular 5G Technology
An important need for coal fired power plants is the ability to monitor multiple systems with ease and accuracy. Common implementations of these monitoring systems come with drawbacks due to the nature of coal fired power plants. Harsh environments, High Temperatures, and lots of RF (Radio Frequency) noise can create issues for accurately recording and transmitting data across wireless signals. In addition, as renewable energy sources come online, existing fossil fueled plants will need to operate more flexibly with their maintenance schedules outside of standard conditions. Therefore, additional sensing and control mechanisms need placed in existing plants to provide operators with more information such that maintenance decisions can be made well in advance of failures. A solution to this problem is the Next Generation of Smart Sensors, which leverages the power of 5G cellular signals and machine learning to overcome the myriad of problems with current implementations
20 FOSSIL-FUELED POWER PLANTS↗
Complementing the CCS Class VI Well Permit Process with DOE-NETL's SMART Initiative Tools and Workflows
This is a presentation on model explorer developed under SMART initiative Task 2. Our team will present the current progress of the model explorer in using machine learning models to accelerate CCS project at GWPC meeting. Model explorer bring new capabilities, (fast, Realtime, and accurate) that can help CCS stakeholders including regulatory agencies, public and site operators make faster decisions and process information and data.
Hosseini, Seyyed↗
Residential HVAC Fault Detection: Field Data Analysis and Interviews with Smart Thermostat Manufacturers
This report presents an analysis of cooling-season field data evaluating how refrigerant undercharge and overcharge faults affect building indoor conditions and HVAC system operation. The report also includes feedback from interviews with six representatives from four smart-thermostat manufacturers.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
Rapid Design and Engineering of Smart and Secure Microbiological Systems (Final Report)
The design and application of successfully engineered biosystems requires an understanding of how engineered microbes will interact with other organisms – either as one-on-one competitors or in the context of microbial consortia. Engineering microorganisms from first principles for non-laboratory, environmental applications is inherently challenging because: (1) engineered systems tend to quickly revert back to their wild-type behaviors; and (2) these systems typically pay a price in reduced fitness, making them uncompetitive against invasive contaminating species (i.e., metabolic burden). For this project, we used a synthetic biology-based strategy to investigate the organization, control, stabilization, and destabilization of natural and engineered microbes. This approach enabled development of (1) single-strain systems capable of detecting and responding to target organisms in the environment; (2) a pipeline for refining and engineering biological constructs in new, non-model host organisms; and (3) improved systems for rapidly designing, engineering, and assaying new biological modules. This coupled approach to safeguard system design is predictable and portable across bacterial species and is focused on microbes that are part of the beneficial plant microbiome. A long-term goal beyond the proposed research is to enable the rational engineering of microbial communities based on first principles of biological design that mimic the smart performance of microorganisms observed in natural systems.
59 BASIC BIOLOGICAL SCIENCES↗
Fermilab Smart Logbook Update 2025
An update on the AD smart search for AD logbook
43 PARTICLE ACCELERATORS↗
Advancing Grid Resilience through Smart Charge Management: Findings from Maryland’s Pilot
This report presents research findings from a four-year Smart Charge Management (SCM) pilot program conducted by Maryland’s largest electric utilities—Baltimore Gas and Electric (BGE), Potomac Electric Power Company (Pepco), and Delmarva Power & Light (DPL)—to evaluate strategies for optimizing electric vehicle (EV) charging loads and enhancing grid stability. Supported by the U.S. Department of Energy (DOE), Argonne National Laboratory collaborated with all project partners and examined the effectiveness of Time-of-Use (TOU) and Load Balancing (LB) strategies in managing peak demand, deferring costly infrastructure upgrades, and reducing grid constraints at the feeder level.
24 POWER TRANSMISSION AND DISTRIBUTION↗
Real-Time Testbed for Smart Grid Recloser Controller
The growing need for a low voltage recloser has become apparent due to the rise in requirements for a smart grid. This includes more detailed management of power flow forward (towards load) and backward (towards generation), source synchronization in real time, more indepth fault responses, and the use of green energy. The SEL-651R-2 relay is a device that can manage these needs, especially in fault response and synchronization, and is commonly used in systems called microgrids. Microgrids are distribution level systems that are able to operate separated from the main grid, are typically installed much closer to the load(s), and are fed by distributed energy resources (DERs), such as wind, solar or diesel generators. The SEL-651R-2 is normally used in the field with presets operative settings, but the Western Michigan University (WMU) Center for Interdisciplinary Research on Secure, Efficient and Sustainable Energy Technology (WMU InterEnergy Center) wished to test this device in its range of capabilities for microgrid application. A Hardware-In-the-Loop (HIL) testbed was implemented and used through the Real Time Digital Simulator (RTDS) using the RSCAD software to test the SEL-651R-2's use cases and functions. The testbed includes a microgrid with interconnection to a larger main grid, and the relay is meant to control the recloser at the point of common coupling (PCC) between the main grid and microgrid. The testbed shows how basic protections, reclosing, and synchronization checks function when handling faults that affect both the microgrid and the main grid.
24 POWER TRANSMISSION AND DISTRIBUTION↗
The Implications of Advanced Manufacturing in a Connected Economy Moving Towards a Smart, Sustainable, and Productive Economy
This report is intended to provide a comprehensive overview of information and communications technologies [ICT], including ICT infrastructure, electronics manufacturing, and smart manufacturing.
42 ENGINEERING↗
Smart Contracts for Power Grid Applications Using the Advanced DLT Cyber Grid Guard Testbed
In this study is presented two power system applications with distributed ledger technology (DLT) and smart contracts (SC) that were assessed in a Cyber-Grid-Guard System (CGGS) advanced testbed, with protective relays, power meters, communication devices, DLT devices, synchronized time source, clock displays and real time simulator. This CGGS testbed was set in the Advanced Protection Lab, 252 lab space of the Grid Research Integration and Deployment Center (GRID- C), at Oak Ridge National Laboratory. In power grids, customer-owned distributed energy resources (DERs) are more frequent than in the past, and the numbers of points of interconnection (POI) with customer-owned DERs have increased. Disruptive operation from DERs presents a risk to grid operations, and protective relays located at the POI are used to isolate out-of-tolerance or poorly behaving of DERs. Ensuring the integrity of data from the relays at the POI, and DLT could enhance the security of the power grids. The first application is a SC to define and control the allowable total power factor (TPF) of the DER (wind farm) output, and the terms of the SC are implemented using DLT with a CGGS for a customer-owned DER. The TPF SC was implemented by the CGGS using DLT. The experimental model was performed with a real-time simulator using a CGGS and relay in-the-loop. The data collected from the CGGS were used to execute the TPF SC. The TPF limits were between +0.9 and +1.0, and the breakers’ operation in the POI was controlled by the relay using the SC. The events were collected from the real-time simulator, CGGS, and SEL 700GT relay to validate a successful application of the TPF SC using DLT. The second application is a SC to measure and control the allowable voltage service limits (VSL) by the CGGS using DLT. The tests were performed by using a real-time simulator, CGGS and relay in-the-loop. The data was collected from the CGGS that executed the SC. The main constraints were defined based on ANSI C84.1 service voltage limits, and the operation of the breakers in the POI. The events were collected from the CGGS, and SEL 700GT relay to assess a successful operation of the VSL SC using DLT.
24 POWER TRANSMISSION AND DISTRIBUTION↗
Wireless High-Temperature Sensor Network for smart boiler systems
This final project report describes the research data and findings. This project aims to develop a new wireless high-temperature sensor network for real-time continuous boiler condition monitoring in harsh environments. Such a wireless high-temperature sensor network enables network-based automatic temperature sensing and data collection, which combined with artificial intelligent (AI) algorithms allow the construction of smart boiler systems with boiling condition management and optimization for significant energy-saving and reliability improvement
42 ENGINEERING↗