Search NASA⌕ Search

SEARCH · Search NASA

Results for “analytic services”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 199 records · Page 11

Data for Resourceful and Economical Designing of Fermentation Medium for Lab and Commercial Strains of Yeast from Alternative Feedstock: Transgenic Oilcane

Sugarcane plant engineered to accumulate lipids in its vegetative tissue is being developed as a new bioenergy crop. The new crop would be a source of juice, oil, and cellulosic sugars. However, limited tolerance of industrially recognized yeasts towards inhibitors generated during the processing of lignocellulosic biomass to produce fermentable sugars is a major challenge in developing scalable processes for second-generation drop-in fuel production. To this end, hydrolysates generated from engineered sugarcane—‘oilcane’ bagasse contain added phenolics and fatty acids that further restrict the growth of fermenting microorganisms and necessitate nutrient supplementation and/or detoxification of hydrolysate which makes the fermentation process expensive. Herein, we propose a resourceful and economical approach for growing lab and commercial strains of S. cerevisiae on unrefined cellulosic sugars aerobically and fermentatively. An equal ratio of hydrolysate and juice was found optimum for growth and fermentation by lab and commercial strains of Saccharomyces cerevisiae engineered for xylose fermentation. The industrial strain grew and fermented efficiently under low aeration conditions having an ethanol titer, yield, specific and volumetric productivities of 46.96 ± 0.19 g/l, 0.51 ± 0.00 g/g, 0.27 ± 0.02 g/g.h and 1.95 ± 0.01 g/l.h, respectively, while the lab strain grew better under higher aeration conditions having the ethanol titer, yield, specific and volumetric productivities of 24.93 ± 0.09, 0.27 ± 0.00 g/g, 0.17 ± 0.00 g/g.h and 1.04 ± 0.00 g/l.h, respectively. Acclimation of cultures in a blended medium significantly improved the performance of the yeast strains. The addition of transgenic oilcane juice, which is inedible and rich in amino acids, to the hydrolysate averted the need for expensive nutrient supplementation and detoxification steps of hydrolysate. The approach provides an economical solution to reduce the cost of fermentation at an industrial scale for second-generation drop-in fuel production.

Biomass Analytics↗

Autonomous Intelligent Charging/Discharging of Electric Vehicles using Distributed Multi-Agent ADMM Framework for Grid Ancillary Services

The increasing popularity of Electric Vehicles (EVs) in the distribution grid along with technological advancement in EV electronics such as vehicle to grid (V2G) technique has enabled them to participate in grid ancillary services. To achieve this, the EVs need to establish a contract with third-party aggregators and connect to a charging unit, either residential or commercial. At any time they are connected, the EVs can decide to take part in the ancillary services program offered to them by the aggregators. If agreed, the aggregators will use the EVs as a power source capable of charging/discharging power according to the input signal, and in return, they will be compensated. This inter-temporal nature of charging/discharging is also transforming the traditional optimal power flow (OPF) problem into a dynamic OPF problem. This chapter aims at developing a multi-layer time-dependent optimization algorithm to utilize EV potential and provide ancillary services while maximizing its utilization function. Specifically, in the upper layer, an autonomous distributed ADMM algorithm is developed to optimize the cost for charging/discharging EVs while using them to regulate the voltage at each bus in the distribution grid. The distributed ADMM algorithm is also expanded to the lower layer where the individual EVs active and reactive power is controlled for voltage regulation while maintaining the desired state of the charge of the vehicle at the end of the charging period. Here, the effectiveness and performance improvement of the proposed multi-layer algorithm is illustrated through analytical analysis and simulation results.

Rahman, Towfiq↗

Securing the Modern Grid: Federal Investments, Digitization, and Supply Chain Strategy

Across the United States (U.S.) grid expansion and modernization is underway, paving the way for accelerated load growth and intelligent resource management. Digitization of the grid is supported by several state and federal programs, providing support for utilities installing advanced metering infrastructure (AMI), AI-powered analytics systems, battery energy storage systems (BESS), and distributed energy resource management systems (DERMS) to transform the grid from a one-way power delivery system into an intelligent, responsive network that will enable faster load growth and power expansion of data centers for advanced artificial intelligence (AI) applications. The digital transformation of America's grid presents opportunity for increased efficiency and resiliency but also introduces new digital risks that require careful management. Digital equipment often contains several vulnerabilities such as unencrypted communication protocols, and persistent remote access capabilities that could be exploited to manipulate device settings, coordinate service disruptions, or inject false data into grid operations. These digital risks become particularly important as the grid must rapidly scale to support AI-driven data centers, which the administration has identified as essential for maintaining U.S. technological leadership and economic competitiveness. These vulnerabilities are compounded by supply chain realities: Chinese manufacturers currently produce 70-90% of essential grid components including inverters, batteries, and control systems, with the U.S. lacking domestic manufacturing capacity for critical assets like extra-high voltage transformers. Recent federal legislation has established Foreign Entity of Concern (FEOC) restrictions to address these risks, requiring projects to achieve escalating thresholds of non-FEOC content to receive tax credits while utilities work to expand sourcing channels for their supply chains and strengthen security measures. These restrictions arrive precisely when utilities face unprecedented electricity demand growth driven by the rapid growth in data centers, creating a considerable challenge: rapidly expanding infrastructure while navigating complex compliance requirements while lacking viable alternatives for many critical components. Idaho National Laboratory (INL) and its partners have developed practical approaches to help utilities navigate these intersecting challenges as they leverage federal investment to strengthen and grow the grid. These solutions include Cyber-Informed Engineering (CIE) principles that build resilience directly into systems, the Cirrus tool for secure cloud migration, and enhanced procurement guidance that embeds security requirements throughout equipment lifecycles. Federal initiatives, such as the Technical Assistance for Digital Assurance (TADA) project, provide direct support to utilities implementing these approaches while facilitating knowledge sharing across the industry. While these tools and frameworks cannot eliminate all risks inherent in foreign supply chain dependencies, they offer pragmatic pathways for strengthening security posture without sacrificing the deployment momentum essential to meeting surging electricity demand. Ultimately, securing America's digital energy infrastructure demands dedicated coordination across multiple fronts: building domestic supply chains, implementing robust digital assurance practices, and maintaining the aggressive modernization timeline necessary for reliability, resilience, and energy independence.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Pumped Storage Hydro Model Evaluation Report Task 1: Tool Assessment

Pumped storage hydro (PSH) projects support various aspects of power system operations. However, determining the value of PSH projects and the many services and contributions to the system they provide can be a challenge. The PSH techno-economic studies being carried out by a 5-lab consortium are defining extensive modeling approaches for evaluating the economic benefits of PSH projects. To enhance the impact of the valuation approach and follow-on techno-economic studies, Pacific Northwest National Laboratory (PNNL) will be developing a set of online tools that industry could adopt and use to advance PSH projects in the US. The problem is that the research team is not entirely clear on the features of the tools that would offer the most significant impact to industry. Thus, year one of this effort is designed to first define the needs of industry before developing the PSH valuation tool. The first step in defining industry needs is to evaluate existing tool packages, including those created by DOE and those by industry groups, to both measure usage levels and define tool attributes that maximize industry impact. The second step in this process will be to hold a workshop designed to elicit direct industry input. Given the breadth and nature of the task, which is to define ideal model attributes, the research team did not constrain the assessment to storage valuation tools. Several tools were assessed, and their characteristics compared against a list of “ideal” attributes that included ease of use, generalizability of results, and analytical flexibility. Information regarding usage and impact were then compared to specific model attributes to define which attributes appear to drive success. The following key lessons and implications can be drawn from the analysis: Models with high ease of use were often the most adopted by industry, though they did not necessarily have high publication reference records, meaning a published article made direct reference to the tool. For example, REScheck TM and COMcheck TM , two tools which share a site, have seen a high amount of web traffic and usage. Similarly, Storage Value Estimate Tool (StorageVET®), an energy storage valuation model, has a large number of organizations using it despite a low publication reference record. A common feature between these models is that they are web-hosted, theoretically making them more easily accessible with graphic user interfaces (GUIs) that are more navigable; Models with higher usage statistics were typically free and/or open source. While it may be unsurprising that this attribute could be considered a draw for users, there is the potential for overestimating the tool's value based on popularity due to the fact that some users may have used the model simply because it was free and not because it is the best model; Models that offer more in-depth analysis and a wide coverage of applications (e.g. VOLTTRON™, GridLAB-D™, and Integrated Valuation of Ecosystem Services and Tradeoffs (InVest)) have shown a high number of publication references as well as showing a high number of downloads in the case of GridLAB-D™. It should be noted that the figure below does not include the model with the highest number of publication references (EnergyPlus™) as it has been removed to show clearer distinction between the remaining tools; The most popular model within the evaluation list was EnergyPlus™. This tool has the highest number of publication references (2,034) of all models considered and contains both a high ease of use level as well as broad application flexibility. Its high usage may be correlated, however, with the presumed wider audience conducting energy consumption modeling compared to the audiences for some of the other tools in this list; Models that were low in both general usage and publication reference generally did not exhibit characteristics considered ideal by the research team. Some of these models offered a narrower range of analytical applications or lower generalizability of results. This would automatically restrict the pool of potential users to those who fall within a narrow range of specific technologies or applications. This report also explores two model structures for the PSH tool: decision tree-based, which would guide the user through the valuation methods defined in the PSH techno-economic studies currently being carried out by DOE, and an all-inclusive comprehensive model. The strengths of each were explored and a hybrid approach was defined that would embed a price taker model into the decision tree approach. Such an approach would provide a comprehensive approach for modeling small-scale PSH while recognizing the challenges associated with implementing a price-maker approach in an all-inclusive model. Insight gained in this analysis of other models can aid in narrowing down the list of effective and sought-after attributes, and in defining model structure. Next steps toward developing a model for storage valuation will be to gain direct industry input through workshops.

13 HYDRO ENERGY↗

Ion Clusters Reveal the Sources, Impacts, and Drivers of Freshwater Salinization

Population growth, land use change, climate change, and natural resource extraction are driving the salinization of freshwater resources worldwide. Reversing these trends will require data-centric approaches that identify salt sources, environmental drivers, and ecosystem responses. In this study, we applied principal component analysis and hierarchical clustering to identify ion covariance patterns, or “ion clusters,” in Broad Run, an urban stream in the Mid-Atlantic United States. These clusters correspond to distinct hydrologic regimes and reveal specific salinization risks: (1) phosphorus pollution mobilized during summer storms (Cluster 1); (2) elevated concentrations of sulfate and bicarbonate during baseflow (Cluster 2), likely reflecting groundwater discharge; and (3) elevated specific conductance and sodium, chloride, and potassium ion concentrations during snowmelt and rain-on-snow events (Cluster 3), driven by deicer and anti-icer wash-off. These ion fingerprints offer a transferable framework for diagnosing salt sources, assessing ecological risk, and identifying management targets. Our findings underscore the need for next-generation stormwater infrastructure and smart growth policies to protect aquatic life in rapidly urbanizing watersheds.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Grid-Interactive Efficient Buildings Technical Report Series: Overview of Research Challenges and Gaps

These reports evaluate state-of-the-art and emerging building technologies that have significant potential to provide grid services. The reports also identify major research challenges and gaps facing the technologies as well as opportunities for technology-specific R&D. The GEB Technical Report Series will help inform and guide BTO's portfolio and serve as a foundational resource for the larger building research community. On-site behind-the-meter generation, battery storage, and electric vehicles are also an important part of the distributed energy resource (DER) optimization strategy for buildings. In general, the component technology reports do not focus on distributed generation or battery storage, but the Whole-Building Controls, Sensors, Modeling, and Analytics report discusses how a building can optimize across all DERs.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Mechanically robust and reprocessable imine exchange networks from modular polyester pre-polymers

Covalent adaptable networks (CANs) containing reversible cross-links impart recyclability to thermoset materials without sacrificing their desirable properties (e.g. high tensile strength and solvent resistance). In addition to thermal recycling, the sustainability of these materials may be further improved by incorporating bio-sourced monomers or by enabling alternate end-of-life fates, such as biodegradation or recovery of starting materials. The alternating ring-opening copolymerisation of epoxides and cyclic anhydrides permits the modular synthesis of polyester pre-polymers that can then be cross-linked to form dynamic imine-linked networks. In this work, we report the synthesis and characterisation of five imine exchange polyester CANs with varied cross-linking densities and pre-polymer architectures. While the materials exhibit characteristic thermoset properties at service temperatures, differences in pre-polymer architecture produce distinct dynamic mechanical effects at elevated temperatures. The networks may be thermally reprocessed with full recovery of their tensile strengths and cross-linking densities, dissociated to pre-polymer, or hydrolytically degraded.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Impact on Cycle Efficiency of Small CHP Plants from Increasing Firing Temperature Enabled by AM of Turbine Blades

Combined Heat and Power (CHP) systems are gaining popularity because of their potential for high overall thermodynamic efficiency and increased need for distributed power generation. Most CHP systems include a gas turbine for electricity generation and a heat recovery steam generator (HRSG) for steam generation. The steam can be used to power a steam turbine for additional electricity generation or to drive rotating equipment, for space heating, for absorption chillers, etc. A CHP cycle configuration is often driven by the ‘principal’ utility for the facility that it services; steam or electricity. In either case, performance improvements in the gas turbine have the potential to increase the steam and power output from the cycle, which is a direct result of improvements in the gas turbine efficiency and power output. One possible opportunity to improve an existing gas turbine’s performance is to increase the firing temperature with improved turbine cooling and increased compression ratio.<br>In this study, the impact on CHP cycle performance from increasing the turbine firing temperature by 100 °C and improving the turbine blade cooling for a 6-MW scale gas turbine is estimated using an analytical cooled gas turbine model and a steam cycle model. A sensitivity analysis was performed to understand the impact of increasing the internal cooling effectiveness, thermal barrier coating performance and blade material upgrades on gas turbine and CHP cycle efficiency. The impacts of turbine blade cooling improvements were studied for three common CHP cycle configurations identified from the literature. Various definitions for CHP cycle efficiency from the literature are used in the comparisons. The results showed that a 100 °C increase in firing temperature can increase the gas turbine efficiency by 1 percentage point without improving cooling effectiveness and add 2 additional percentage points in efficiency by using advanced turbine blades with higher internal cooling efficiency. Studied engine upgrades showed potential for increasing the CHP cycle efficiency by 3 percentage points while increasing the steam generation rate by 8%.<br>

Uysal, Selcuk Can↗

Atomistic investigation of calcium sulfonate and lithium complex grease tribofilms under severe sliding conditions

We report innovative grease chemistries and additives are continuously developed to meet challenging applications such as wind energy bearings and offshore/underwater applications. The non-equilibrium and transient structures within interfacial tribofilms play an influential role in the service life of a component. Atom probe tomography and transmission electron microscopy studies were performed to investigate the tribofilms formed by lithium complex and calcium sulfonate grease thickeners. The study reveals that morphology, amorphicity, nanostructure, and atomic layering play an influential role in the exceptional wear and corrosion performance of calcium sulfonate thickeners.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Research Priorities and Opportunities in United States Wholesale Electricity Markets

The power system is currently undergoing a number of changes, including a rapidly evolving resource mix, growth of distributed energy resources (DERs), more active consumer participation, increased deployment of energy storage and hybrid resources, and more advanced communication and control requirements. These changes in the power system present numerous technical, economic, implementation, and policy challenges and research opportunities for power system operators. To help address these challenges, a collaboration among five research institutions—Argonne National Laboratory, the National Renewable Energy Laboratory, Lawrence Berkeley National Laboratory, the Electric Power Research Institute, and Johns Hopkins University—has been established to provide technical assistance to the seven U.S. Independent System Operators (ISOs) and Regional Transmission Organizations (RTOs). The 3-year project aims to leverage the advanced methods, tools, datasets, and resources of the collaborators to provide robust analytical support to address the high-priority market challenges that will be faced in the 2- to 10-year time horizon.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Correlative STEM-APT characterization of radiation-induced segregation and precipitation of in-service BWR 304 stainless steel

In this study, radiation induced segregation and precipitation phenomena in an in-service boiling water reactor 304 stainless steel component were investigated using directly correlated 3D-atom probe tomography and scanning transmission electron microscopy. Significant quantitative differences in measured segregation at grain boundaries were found between the atom probe and energy dispersive spectroscopy measurements of the exact same locations. In particular, a much stronger Si segregation (~10 atomic% via atom probe versus ~4 atomic% via electron microscopy) and different Cr profile shapes were detected that are critical to models of radiation induced segregation and stress corrosion cracking behavior. These quantitative differences highlight the need for comparative microscopy and critical evaluation of limitations in each analytical method. Elemental segregation to dislocations and conjoined-clusters were also highlighted by atom probe; confirming and expanding upon what has been observed in test reactor neutron and accelerator-based ion irradiations.

36 MATERIALS SCIENCE↗

ICE Calculator 2.0: Final Report for Phase 1 of the National Initiative to Update the Interruption Cost Estimate (ICE) Calculator

In 2021, Berkeley Lab and Resource Innovations, Inc. launched the “ICE 2.0 Initiative” – a national study to refresh the underlying data and enhance the functionality of the ICE Calculator. The Initiative involves Berkeley Lab contracting with sponsoring utilities to administer identical, updated and comprehensive interruption cost surveys to statistically representative samples of each utility’s customers. Berkeley Lab and Resource Innovations then pool the survey results across the utilities and use them to update the analytical engines that drive the ICE Calculator. The ICE 2.0 Initiative is being conducted in phases. Each phase involves the administration of interruption cost surveys to the customers of sponsoring utilities, followed by an update to the ICE Calculator based on analysis of the pooled survey results. This report describes the activities and findings from Phase 1 of the ICE 2.0 Initiative. Phase 1 was sponsored by eight utilities: American Electric Power, Commonwealth Edison, Dominion Energy, Duke Energy, DTE Electric, Exelon, National Grid, and Puget Sound Energy. Phase 1 involved 11 customer interruption cost survey activities representing a total of 24 electricity distribution service territories, 23 of them located in the Eastern and Midwestern regions of the U.S. and one located in the Pacific Northwest. ICE 2.0 vs. 1.0 Comparison This memorandum compares customer power interruption costs estimated using the recently updated Interruption Cost Estimate (ICE) Calculator (“ICE 2.0”) to the original ICE Calculator (“ICE 1.0”). ICE 1.0 was developed in 2009 based on 15 independent power interruption cost surveys conducted by 10 electric utilities between 1989 and 2012. ICE 2.0 was developed in 2025 through a national initiative based on a consistent set of power interruption cost surveys and 11 surveying efforts conducted across 24 electric utility service territories between 2022 and 2024.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Long-Term Stability of PVD/Sputtered Au Electrical Contacts to Thermoelectric Bi 2 Te 2 : Re-evaluation of SAND2015-7203

The fabrication of long-lived electrical contacts to thermoelectric Bi 2 Te 3 -based modules is a challenging problem due to chemical incompatibilities and rapid diffusion rates. Previously, technical guidance from SAND report 2015-7203 selected electroplated Au as the preferred method for fabrication of long-lived contacts because of concerns that the grain structure of sputtered/physical vapor deposited (PVD) Au contacts can evolve during aging. We have re- evaluated PVD Au contacts and show that they are appropriate for long-life service. We measure grain size and morphology at different aging times under accelerated temperature gradient conditions, and we show that the PVD Au contacts are stable and remain relatively unchanged. The PVD Au fabricated here is not subject to the deterioration observed in the previous report.

36 MATERIALS SCIENCE↗

Developing a Decision Support Engine to Enable Irrigation Modernization - Poster

Irrigation systems in the United States are some of the oldest continually utilized infrastructure in existence today, with some systems exceeding 100 years in age. They are operated to meet farming demands but are managed through a balance of varying influence: policies limiting water usage, stakeholder interests, and environmental impacts. Irrigation modernization is defined as a set of activities that update and improve existing irrigation systems, including, but not limited to improving water quantity, development of distributed energy resources for surrounding communities, ecosystem services, and improved agricultural yields. Modernizing an existing irrigation system can enable stakeholders to combat changing environmental and population demands but is difficult because the complexity involved in determining the potential benefits and consequences of irrigation modernization is high. We are combining a large amount of various geospatial, tabular, and temporal data with subject matter expertise into a decision support engine that will enable stakeholders to determine the benefits and consequences of irrigation modernization in their irrigation systems. A web-based GIS will allow the user to construct the modifications out of a palette of modernization options, which will be sent to the analytics engine for computations, and back to the web client for a graphical display and comparison of relevant metrics. Our development process involves four phases: 1) identify mechanisms of modernization, 2) identify data requirements, data streams, first principles and applicable algorithms necessary to quantify modernization mechanisms, 3) create ‘modules’ for each modernization mechanism, these modules will form the decision support engine, each capable of performing independently but can also inform other modules when needed, 4) Merge the decision support engine with a user interface, capable of ingesting user inputs and returning insights into the impacts of a modernization project as they relate to economic, environmental, monetary, and energy generation. Once complete, it is our intention that this tool will be fundamental in irrigation modernization projects, providing a strong analytical basis from which stakeholders can quickly make informed decisions regarding project development.

13 HYDRO ENERGY↗

Edge ML for CAN bus intrusion detection in AVs

Autonomous Vehicles (AVs) are revolutionizing transportation, but their reliance on interconnected cyber-physical systems exposes them to unprecedented cybersecurity risks. This study addresses the critical challenge of detecting real-time cyber intrusions in self-driving vehicles by leveraging a dataset from the Udacity self-driving car project. We simulate four high-impact attack vectors, Denial of Service (DoS), spoofing, replay, and fuzzy attacks, by injecting noise into spatial features (e.g., bounding box coordinates) to replicate adversarial scenarios. We develop and evaluate two lightweight neural network architectures (NN-1 and NN-2) alongside a logistic regression baseline (LG-1) for intrusion detection. The models achieve exceptional performance, with NN-2 attaining an AUC score of 93.15% and 93.15% accuracy, demonstrating their suitability for edge deployment in AV environments. Through explainable AI techniques, we uncover unique forensic fingerprints of each attack type, such as spatial corruption in fuzzy attacks and temporal anomalies in replay attacks, offering actionable insights for feature engineering and proactive defense. Visual analytics, including confusion matrices, ROC curves, and feature importance plots, validate the models' robustness and interpretability. This research sets a new benchmark for AV cybersecurity, delivering a scalable, field-ready toolkit for Original Equipment Manufacturers (OEMs) and policymakers. By aligning intrusion fingerprints with SAE J3061 automotive security standards, we provide a pathway for integrating machine learning into safety-critical AV systems. Our findings underscore the urgent need for security-by-design AI, ensuring that AVs not only drive autonomously but also defend autonomously. This work bridges the gap between theoretical cybersecurity and life-preserving engineering, offering a leap toward safer, more secure autonomous transportation.

97 MATHEMATICS AND COMPUTING↗

Analysis of Respirator Cartridge Performance Testing on the 702-AZ Primary Exhauster for the Hanford AY/AZ Tank Farms

Washington River Protection Solutions (WRPS) conducted tests on two types of chemical cartridges for use in air purifying respirators to determine the period of time that the cartridges would provide adequate performance to protect workers when exposed to a mixture of Chemicals of Potential Concern (COPC) from vapors exiting the 702-AZ primary exhauster for the Hanford AY/AZ tank farms. The Occupational Safety and Health Administration (OSHA) identifies cartridge testing as a valid approach for establishing cartridge change schedules. Testing is commonly applied in situations where mixtures of COPCs exist, and where other approaches, such as manufacturer recommendations and modeling, are less reliable. The tests were designed and conducted to assure measurement and/or control of the key variables OSHA identified as important to estimate cartridge service life, including temperature, humidity, COPC concentration, breathing rate, and cartridge adsorption capacity. Testing was conducted from August 26–28, 2016, on a slipstream from the 702-AZ exhauster, under static conditions fed to a respirator cartridge test stand developed by WRPS in collaboration with HiLine Engineering (Richland, Washington). Multipurpose respirator cartridges, SCOTT 7422-SD1 and SCOTT 7422-SC1(SCOTT Safety, Monroe, North Carolina) were assessed on separate days. Sample media (sorbent tubes) were used to collect samples of the vapor stream entering and exiting the respirator cartridge, and were subsequently analyzed for COPC concentrations. Pacific Northwest National Laboratory was tasked with conducting an independent analysis of the analytical results and making recommendations based on the results for respiratory cartridge performance and change-out frequency.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Bridging Cloud and Edge Computing at NREL Using CONNECT: Cloud Optimized Networking for Next-Gen Edge Computing Technologies [Slides]

CONNECT is an innovative on-premise hardware and software solution that integrates edge and cloud computing infrastructure at NREL. Built on the AWS Greengrass middleware and leveraging the MQTT protocol, CONNECT enables real-time data streaming from IoT devices and gateways to both cloud and local services, empowering researchers to rapidly capture, analyze, and act upon edge-generated data while leveraging cloud capabilities. The platform addresses research infrastructure challenges by providing a pre-approved platform which is already configured with the correct networking and cybersecurity baselines thus eliminating procurement delays and enabling on-demand availability. CONNECT's hybrid architecture efficiently manages burstable workloads, allowing research teams to dynamically scale computational capacity, handle peak data loads, and reduce operational bottlenecks. Advanced capabilities include built-in GPU support for executing machine learning models which enables low-latency inference at the edge from models trained in the cloud. This architecture supports real-time analytics and filtering, providing a mechanism to allow only transmitting and processing high-value data. Cloud-based configuration management permits engineers to manage on-premise systems remotely, optimizing operational efficiency. By bridging edge and cloud computing, CONNECT provides NREL researchers with a flexible, scalable platform that accelerates scientific discovery while maintaining robust security and performance standards.

97 MATHEMATICS AND COMPUTING↗

Solar PV on U.S. Houses of Worship: Overview of Market Activity and Trends [Slides]

Rooftop solar photovoltaic systems on houses of worship can provide unique community benefits and can raise local awareness and acceptance of solar energy. Recognizing that potential, a stakeholder team selected under DOE’s Solar Energy Innovation Network is working to develop a scalable model for recruiting and installing solar PV on houses of worship in underserved communities. Berkeley Lab is providing analytical support to this stakeholder team through several work products, including this report, which provides a data-oriented overview of market activity and trends related to solar PV installations on U.S. houses of worship (HoW). Drawing on Berkeley Lab’s project-level dataset of U.S. solar PV installations, the report describes: -market size and growth trends for PV on HoW -demographic characteristics of the communities in which HoW with PV are located, including income, race and ethnicity, and educational levels -key characteristics of the PV systems installed on HoW, including system size, installed costs, prevalence of third-party ownership, and pairing with storage -characteristics of the installer network servicing PV installations on HoW The purpose of the market overview is to inform business development and policy-making efforts aimed at supporting solar adoption by HoW.

14 SOLAR ENERGY↗