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Assessment of ProgPy - An Open-Source Condition Monitoring and Diagnostics Tool

Traditional maintenance programs, such as corrective and preventive strategies, may lead to high costs and operational inefficiencies. Condition Monitoring and Diagnostics (CM&D) aims to improve these maintenance strategies by enabling timely insights into equipment health and performance. However, implementation of CM&D can be challenging without a robust framework that manages data efficiently, supports interoperability and simplifies integration. To address these challenges ProgPy, an open-source Python-based prognostics tool developed by NASA Ames Research Center, offers a structured solution for broader Prognostics and Health Management (PHM) applications. Ongoing research is assessing the feasibility of implementing ProgPy as a Condition Monitoring and Diagnostics (CM&D) solution by comparing its framework to the guidelines for open CM&D systems recommended in the ISO 13374-2 standard. This evaluation aims to highlight ProgPy’s strengths and identify opportunities for improvement, thereby, contributing to its advancement as an effective tool for Prognostics and Health Management (PHM). This paper presents the results of an initial assessment of the ProgPy toolbox through a gearbox case study using open-source datasets.

Condition-Monitoring, Diagnostics, Failure, Gearbo↗

Integration of Data Analytics with Plant System Health Program

This report summarizes the R&D activities of the Plant Health Management (PHM) project during fiscal year 2020 (FY20). This project focuses on the development of methods that integrate component health data and propagate such information at the system level to evaluate system sources of risk. This project development lives in cooperation with the Risk Informed Asset Management (RIAM) project. The RIAM project, in fact, uses the reliability models and data generated by the PHM project to optimize plant operations (e.g., maintenance/replacement schedule, optimal maintenance posture). This year’s activities for the PHM project focused mainly on the development of two classes of models. The first one includes a series of component reliability models which include aging, testing and maintenance. The second class includes a series of system reliability models which focus on the secondary side of exiting U.S. reactors. These models are based on fault tree logic structures such that they can be used by existing plant PRA software. We also started to focus on the management of health data and we tackled this issue in two directions. The first one focuses on the integration of monitor data with simulation models to assess component health. This approach is moving from a classical data based to a model+data based approach with the goal of improving higher component health information. The second direction focuses on linking equipment reliability data (e.g., maintenance/failure reports, component monitoring data) directly to system reliability models using a safety margin based language rather than a probability based language. The main advantage of a safety margin based language is that it can provide to system engineers more tangible information on system/component health and how it propagates to the system level.

97 MATHEMATICS AND COMPUTING↗

Environmental and cost benefits of multi‐purpose buffers in an agricultural watershed for biomass production

Abstract The cost‐benefit of riparian buffers to landowners has not been fully understood despite its ecosystem benefits. This study investigates the environmental and economic value of multi‐purpose buffers for biomass production under alternative land‐management scenarios at the watershed scale. The work incorporates the Soil and Water Assessment Tool with a field‐scale tool, the Agriculture Conservation Practice Framework, and cost‐benefit analysis. Our work took place in the agriculturally dominant Raccoon River watershed (RRW) in Iowa. The cost analysis includes implementing and harvesting the switchgrass buffers, the value of nitrogen and phosphorus fertilizer, and the forgone income of cropland to determine the net return under 12 alternative feedstock scenarios. We estimated that 14 603 Mg of nitrogen and 2563 Mg of phosphorus runoffs can be intercepted by riparian buffers in the RRW, representing a nutrient loss reduction of 11% of nitrogen and 26% of phosphorus. These nutrients are valued at $1.31 million (M) for phosphorus and $1.24 M for nitrogen as fertilizers. The trapped nutrients account for 12% of the riparian buffers’ total cost. We found that net economic returns increase with biomass market price, increase with maintenance fertilizer application, and decrease with the cropland areas that are converted to buffers. Under current land management, a biomass market price at $60 per dry ton of biomass would be economically viable at the sub‐basin level when maintenance fertilizers are applied. At $80 per dry ton, all 108 sub‐basins in the RRW would be profitable up to $517 a year. The results highlight the trade‐offs between water quality and profitability. Published 2021. This article is a U.S. Government work and is inthe public domain in the USA. Biofuels, Bioproducts and Biorefining published by Society of Industrial Chemistry and John Wiley & Sons Ltd.

09 BIOMASS FUELS↗

Whole plant traits of coastal dune vegetation and implications for interactions with dune dynamics

Abstract Coastal dunes are important protective features against sea level rise and coastal storms. Interactions between dune plant aboveground structures and sediment trapping that allow for dune building and maintenance are well established. More recently, studies documenting belowground biomass for promoting erosion resistance in dominant dune species have been conducted, yet a knowledge gap remains regarding species‐specific characterization of whole plants, specifically with respect to roots, rhizomes, and belowground stems. Our objective was to quantify above‐ and belowground traits of four dominant dune grasses to document the potential for species‐specific effects on dune growth, maintenance, and erosion resistance. We examined above‐ and belowground traits among four prominent dune grasses of the Atlantic and Gulf Coasts of North America: Ammophila breviligulata , Panicum amarum , Spartina patens , and Uniola paniculata . Whole plant samples of each species were collected from the foredune at the US Army Engineer Research and Development Center's Field Research Facility in Duck, North Carolina, USA, and quantified for several above‐ and belowground traits (e.g., stem height, rhizome number and length, root surface area by diameter class, root tensile strength, and mycorrhizal percent infection). Belowground factors known to impact important dune processes, such as rhizome length, mycorrhizal percent infection, and root traits, differed substantially among species. When visualized in multivariate space, all species significantly differed in suites of above‐ and belowground traits. When considering belowground only, Ammophila and Spartina were similar, despite differences in biomass allocation. Species separated along axes related to mycorrhizal association, biomass allocation, and root construction. The four co‐occurring dune grass species were dissimilar in suites of plant traits. Belowground trait differences were driven by those describing root construction, biomass allocation, and mycorrhizal infection. Dissimilarity in above‐ and belowground suites of traits may demonstrate different approaches for surviving the dune environment. Incorporating belowground traits into modeling will enhance predictions of dune response to climate change through interactions between vegetation and dune dynamics that facilitate coastal resistance and resilience.

54 ENVIRONMENTAL SCIENCES↗

PV Field Reliability Status--Analysis of 100,000 Solar Systems

In this paper, we analyzed annual production data from 100 000 photovoltaic systems as well as comments relating to their performance and maintenance. Our analysis revealed that 80% to 90% of all systems performed within 10% of the predicted production or better. Also, 56% of the systems were still performing above P50 or the median at 5 years. However, a small but significant tail of about 7000 systems perform below P90 expectations. In general, residential systems have a lower rate of failure than utility or commercial systems. Despite higher rates of component failures, utility systems lose less power than residential or commercial systems. This outcome is likely due to closer monitoring and better operations and maintenance practices. Inverters are still the components that reportedly fail most often (4%-6%), but other failures such as unspecified repair and meters cause more production loss. Reported module failures are relatively rare (0.2%) and are within the range of historical values. Installation quality affects performance and safety as indicated by data showing connector, wiring, breaker, and fuse failures due to undersizing, electrical design, and improper connection. Lastly, early detection of degradation and proactive response resulted in less impact on production than reactive, unplanned repairs.

14 SOLAR ENERGY↗

Risk assessment of engineering diseases of embankment–bridge transition section for railway in permafrost regions

Abstract The embankment–bridge transition section (EBTS) is one of the zones where railway diseases occur frequently in permafrost regions. Disease risk assessment of EBTSs can provide guidance for maintenance. In this study, considering the engineering geological conditions, climate characteristics, and embankment structure types along the Qinghai–Tibet Railway (QTR) as well as based on the disease inventory of the QTR from 2010 to 2019, the logistic regression (LR), support vector machine (SVM), and combination‐weight‐based gay relation analysis (GRA) were used for disease risk assessment of the EBTSs along the QTR in permafrost regions. The results indicate that the LR and SVM models have a better capability for EBTS disease prediction than the GRA model, and the SVM model can select more disease samples in relatively larger regions than the LR model. Based on the SVM and LR models, the risk level of EBTSs is divided into four classes: low‐ (29.9%), moderate‐ (39.6%), high‐ (22.1%), and very high (8.4%) risk. Finally, we selected 272 EBTSs in high‐ and very‐high‐risk classes for key observation during the maintenance of the QTR in permafrost regions. This study provides a reference for the risk assessment of railways built in permafrost regions using data‐driven methods.

Zhang, Saize↗

Catalyst Revised: Rethinking the ParaView in Situ Analysis and Visualization API

As in situ analysis goes mainstream, ease of development, deployment, and maintenance becomes essential, perhaps more so than raw capabilities. In this paper, we present the design and implementation of Catalyst, an API for in situ analysis using ParaView, which we refactored with these objectives in mind. Furthermore, our implementation combines design ideas from in situ frameworks and HPC tools like Ascent and MPICH.

97 MATHEMATICS AND COMPUTING↗

Digital Twins for Nuclear Power Plants and Facilities

The nuclear digital twin (DT) is the virtual representation of a nuclear energy system across its lifecycle. The nuclear DT uses real-time information and other data sources to improve the process of design, licensing, construction, security, O&M, decommissioning, and waste disposal. By leveraging the knowledge base and experience from the past 40 years of LWR operation, the nuclear DT is helping to accelerate the development and deployment of advanced nuclear technology in areas of passive safety, new fuel forms, instrumentation, and reactor control. For the currently operating nuclear fleet, DTs are reducing the operational risks, increasing plant availability, increasing energy capability, and reducing electricity production costs. For advanced fission and fusion reactors, DTs are being used to design for passive safety and built-in security-by-design. Rapidly deployable small modular reactor (SMR) and microreactor designs compatible with modular construction techniques and advanced manufacturing will be the new normal, reducing the need for large capital expenditures and compressing construction schedules. In addition, lower operational and maintenance costs will be realized by reducing the complexity of operations, staffing needs, and maintenance-related activities.

Kropaczek, Dave↗

Root lateral interactions drive water uptake patterns under water limitation

The plasticity of root water uptake determines the maintenance of transpiration during periods of water limitation and drought. However, the mechanistic basis of plant water uptake, as well as the implications of water uptake strategies at the individual and ecosystem scale remain elusive. We model three-dimensional root water uptake under variably saturated conditions for a one-hectare temperate forest plot for a growing season with a pronounced mid-season dry period. Variations in root architecture, hydraulic properties, and degree of lateral interaction between root systems produce divergent local responses to water limitation and provide insights on individual and community response to meteorological conditions. Results demonstrate the plasticity of ecosystem-scale responses to surface drying, where interacting roots shift regions of active uptake to deeper soil layers with less abundant root biomass. These shifts, a product of both root system and soil hydraulic properties, illustrate intimate links between root and soil hydraulics in determining plant water sourcing. Furthermore, we demonstrate that root lateral interactions are beneficial at the ecosystem-scale, even when trees compete for water. Specifically, a more spatially extensive root system facilitates access to a larger soil water reservoir, often ameliorating water limitation and reducing sharp water potential gradients. While the reduction of water stress is a benefit, it can be offset by increased root construction and maintenance costs associated with the larger rooting system. A plausible “viability” region of root communal co-existence is therefore implied where competitive pressures and root production costs are balanced by a potential water benefit.

54 ENVIRONMENTAL SCIENCES↗

High-burnup boiling water reactor steady-state operating conditions and fuel performance analysis

The primary operational costs for existing nuclear reactors are plant operation costs, maintenance costs, and fuel costs, all of which are influenced by the materials used and the design of the reactor core. Optimizing core design parameters—including burnup limits and enrichment levels—can lengthen cycles, reduce outages, reduce reload batch fractions and spent fuel storage requirements, and lower maintenance and operating expenses, thereby enhancing economic viability. Furthermore, developing higher-fidelity tools to simulate these parameters enables better identification of the available margin, improves overall plant safety, and improves the understanding a given plant’s responses to accident scenarios. Here, in the US, much of the research and development focus has traditionally been on pressurized water reactors (PWRs), but boiling water reactors (BWRs) comprise approximately one-third of the US reactor fleet. Modeling and simulation advances for BWRs and PWRs—particularly those achieved through the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program—are crucial to the long-term viability of the light–water reactor industry. A key research area of the high burnup and increased enriched fuel initiative is focused on addressing issues related to postulated loss-of-coolant accident (LOCA) scenarios. NEAMS has dedicated significant effort to enhancing tools to better support BWRs. A current focus is showcasing the BWR framework for high-burnup LOCA analysis. This high-fidelity steady-state analysis is a first step toward demonstrating a best-estimate, pin-by-pin high-burnup BWR LOCA analysis to assess full-core cladding rupture behavior for a representative BWR. The objective of this effort is to provide a modeling capability that will help elucidate and provide a best-estimate evaluation for cladding rupture susceptibility in BWRs. This modeling capability could then be used to prevent and/or mitigate cladding ruptures in postulated accident scenarios without penalizing operational parameters. Additionally, the results of this work will help identify strategies for finding additional margins or potentially limiting cladding ruptures through core design optimizations to enable more efficient core designs.

Capps, Nathan [Oak Ridge National Laboratory (ORNL↗

Reliability of emergency and standby diesel generators: Impact on energy resiliency solutions

Emergency diesel generators are the most common form of backup power for critical loads when the grid fails and are most often deployed as stand-alone generators (<2000 kW) tied to individual buildings for hospitals, emergency services, military bases, ports, airports, industries, and commercial facilities. Understanding the finite reliability of emergency diesel generators during continuous operation is critical for energy planners, managers, and end-users. A new analysis of two large non-public emergency diesel generator operational data sets shows that commonly used reliability metrics are inadequate to predict the performance during a grid outage. Additional metrics addressing the likelihood of an emergency diesel generator to be available at the time an outage starts, successfully start and carry load, and constantly run for the duration of the outage are needed to predict the continuous run-time reliability of emergency diesel generators during a grid outage. This is the first analysis of the reliability of modern generators that follow standard maintenance protocols commonly used for backup power and these new metrics are shown to be dependent on the level of emergency diesel generator maintenance with values that can vary by more than an order of magnitude. Even using the new metrics for well-maintained emergency diesel generators, the analysis shows that the single emergency diesel generators configurations are only 80% likely to provide power for the duration of a two-week grid outage.

ENERGY PLANNING, POLICY, AND ECONOMY,POWER TRANSMI↗

Air quality impacts from the development of unconventional oil and gas well pads: Air toxics and other volatile organic compounds

Unconventional oil and natural gas development (UOGD) has expanded rapidly across the United States in recent decades and raised concerns about associated air quality impacts. While significant effort has been made to quantify methane emissions, relatively few observations have been made of Volatile Organic Compounds (VOCs), especially during drilling and completion of new wells. Extensive air monitoring during development of several large, multi-well pads in Broomfield, Colorado, in the Denver-Julesburg Basin, provides a novel opportunity to examine changes in local air toxics and other VOC concentrations during well drilling and completions and production. These operations offer an especially useful case to study as several management practices were implemented to reduce emissions (e.g., electrified, grid-powered drill rigs and closed loop fluid handling systems to reduce truck traffic and limit fluid handling on the pad). With simultaneous measurements of methane and 50 VOCs from October 2018 to December 2022 at as many as 19 sites near well pads, in adjacent neighborhoods, and at a more distant reference location, we identify impacts from each phase of well development and production. Use of weekly, time-integrated canisters, a Proton Transfer Reaction Mass Spectrometer (PTR-MS), continuous photoionization detectors (PID) to trigger canister collection upon detection of VOC-rich plumes, and an instrumented vehicle, provided a powerful suite of measurements to characterize both transient plumes and longer-term changes in air quality. Prior to the start of well development, VOC gradients were small across Broomfield. Once drilling commenced, concentrations of oil and gas (O&G) related VOCs, including alkanes and aromatics, increased around active well pads. Concentration increases were clearly apparent during certain operations, including drilling, coil tubing/millout operations, and production tubing installation. Emissions of C 8 –C 10 n-alkanes during drilling operations highlighted the importance of VOC emissions from synthetic drilling mud chosen to reduce odor impacts. More than 90 samples were collected of transient plumes. Using composition measurements, meteorological data, and information about well pad activities, these plumes were connected with specific UOGD operations including drilling, flowback, and production equipment maintenance. The chemical signatures of these plumes differed by operation type (e.g., C 8 –C 10 n-alkanes constituted a larger fraction of measured VOCs in drilling-related plumes). Concentrations of individual, oil and gas-related VOCs in these plumes were often several orders of magnitude higher than in background air, with maximum ethane and benzene concentrations of 79,600 and 819 ppbv, respectively. Because these plumes typically impact a monitoring site for just several minutes, they are easily missed by slower-responding instruments. Study measurements highlight future emission mitigation opportunities during UOGD operations, including better control of emissions from shakers that separate drill cuttings from drilling mud, production separator maintenance operations, and periodic emptying of sand cans during flowback operations.

54 ENVIRONMENTAL SCIENCES↗

Robotics for HVAC applications: A critical review and future perspectives

Recent advances in artificial intelligence (AI), enhanced computational capabilities, and innovations in sensors and hardware have driven the increasing development and application of robots in heating, ventilation, and air conditioning (HVAC) systems. We selected and reviewed 101 studies published between 2005 and 2025, sourced from IEEE Xplore, Scopus, Web of Science, and the ACM Digital Library. To analyze these works, we developed a five-dimensional analytical framework (morphology, sensing, navigation, task execution, and system integration), inspired by the Springer Handbook of Robotics and tailored specifically for robotic applications in HVAC. Based on the reviewed studies, six distinct tasks spanning the entire HVAC lifecycle have been identified. Among the six tasks, inspection and maintenance dominate (59 %), followed by indoor monitoring and auditing (21 %), whereas leakage detection, comfort support, and installation/retrofit remain less explored. To address the identified gaps, this review proposes future research directions including investigating robot-aware HVAC design principles, developing multimodal HVAC sensing and data fusion techniques, enhancing robot training and hardware capabilities, and expanding robotic applications beyond Maintenance and Operations (M&O). The findings from this review inform future robotics research for HVAC applications and ultimately enhance system affordability, energy efficiency, resilience or reliability, and occupant environmental comfort. Moreover, it seeks to inspire researchers to explore the intersections of robotics, computer science, building science, and HVAC engineering fostering advancements in this multidisciplinary field.

AI↗

Ten questions concerning Large Language Models (LLMs) for building applications

Large Language Models (LLMs) are emerging as powerful AI tools capable of transforming how building information is collected, processed, analyzed, and applied across diverse research areas. Their capabilities can help building operators, facility managers and other stakeholders such as designers, architects and engineers by providing actionable insights for decision-making across planning, construction, operations, and maintenance of buildings and facilities. This paper explores ten key questions concerning the role of LLMs in shaping sustainable, intelligent, and human-centric buildings. From fundamental definitions to advanced applications, we examine how LLMs facilitate decision-making across the life cycle of buildings and energy systems. LLMs can enhance life cycle assessments (LCA), building energy simulations, and real-time data integration, empowering more efficient and adaptive human-AI environments. They can also contribute to streamlining regulatory compliance, improving post-occupancy evaluations, and fostering more inclusive and participatory design processes. Additionally, this paper addresses the ethical challenges posed by LLMs, such as bias, data privacy, and environmental impacts, and explores their potentials in advancing intelligent digital twins (DT) for ongoing building operations and maintenance. Built upon our applied research using LLMs and the review of tools, datasets, and research gaps, we provide a forward-looking perspective on how LLMs can drive innovation, collaboration, and productivity in the built environment while supporting ethical and effective implementation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Modeling of crystallization fouling on a horizontal-tube falling-film evaporator for thermal desalination

Scale formation within horizontal-tube falling-film evaporators is an important issue for thermal desalination, because of the deterioration of heat transfer performance and added maintenance costs. Predicting the fouling process is crucial for desalination plant design, operation, and maintenance. In this paper, a model is developed to predict the crystallization fouling process during seawater falling-film flow over a horizontal tube bundle. The scaling is estimated based on deposition theory, with couple heat transfer including the in-tube steam condensation, conduction through the tube wall and the scale layer, and falling-film evaporation. The spatial and temporal variations of temperature, heat transfer coefficient, and scale thickness are predicted, and the effects of variations in process parameters of steam, feed seawater, and tube properties on the scale thickness, evaporation rate, and heat transfer coefficient for falling-film evaporation are analyzed. Comparisons to existing experimental data show the scaling layer thickness falls in the general range of reported measurements, with a slight overestimation due to neglecting the delay of scaling onset under real conditions. The scale layer thickness increases dramatically as the in-tube steam pressure is increased or the seawater flow rate is decreased. In general, the scaling layer becomes thicker on the lower tubes in the tube bundle, due to the heat and mass transfer of the falling film. The effect of tube material on scaling appears mainly dependent on thermal conductivity; thus, using polymer rather than a stainless steel tube decreases scaling and evaporation rate 96% and 88%, respectively. Finally, this work has potential to guide thermal desalination plant design, material selection, and operating parameter optimization.

42 ENGINEERING↗

The cold high-pressure approach to hydrogen delivery

In view of the very expensive and wasteful nature of today's approaches to H 2 delivery, in this work we explore the possibility of transporting cold (200 K) high pressure (875 bar) H 2 in thermally insulated trailers and dispensing H 2 directly from the trailer, with the potential to eliminate station compressor, cascade, and refrigerator, leading to major reductions in station complexity, maintenance, electricity consumption, and cost, while improving functionality by enabling essentially unlimited back to back refuels, and improving safety due to reduced H 2 expansion energy at low temperature. Detailed techno-economic analysis shows promise for substantial delivery cost reductions through cold high pressure H 2 dispensed directly from the trailer. Results indicate that: (1) Terminal operations for cold high pressure H 2 delivery are $\$$0.32/kg H 2 more expensive than for 350 bar compressed gas delivery (today's lowest cost H 2 delivery technology) due to higher level of pressurization (to 1000 bar) and chilling needs (to 165 K). (2) Trailer cost drops slightly ($\$$0.73 vs. $\$$0.81/kg H 2 for a 350 bar trailer) due to increased capacity (1035 kg H 2 delivered vs. 700 kg) compensating for increased capital cost ($\$$906,900 for cold high pressure H 2 vs. $\$$634,000 for 350 bar trailer). (3) Cold hydrogen delivery presents major advantages in fueling station cost, reduced from $\$$1.27 to $\$$0.46/kg H 2 due to elimination of major system components: compressor, cascade, and chiller. (4) Total compression cost (terminal + station) drops from $\$$0.92/kg H 2 ($\$$0.32 terminal and $\$$0.60 station) for 350 bar trailers to $\$$0.55/kg H 2 (all at the terminal) for cold high pressure H 2 . (5) Elimination of small-scale station compressors is the main contributor to reduced delivery cost due to their inefficiency, capital expense, and maintenance needs. In summary, total delivery cost reduction vs. 350 bar trailer equals $\$$0.58/kg H 2 (from $\$$2.96 to 2.38/kg H 2 ), equivalent to 24% of the total delivery cost. This large cost advantage will improve the economics of H 2 vehicles facilitating the transition to a future of zero emission transportation.

08 HYDROGEN↗

Design and requirements of a hydrogen component reliability database (HyCReD)

Hydrogen technologies are expected to play a key role in the decarbonization of several sectors including energy storage and transportation. Rigorous investigation and quantification of the risk and reliability issues associated with hydrogen technologies will be critical to ensuring both their wider adoption and safe, economical operations. Quantitative risk assessment (QRA) is an important tool that has been used to enable the safe deployment of many engineering systems, including hydrogen fueling stations and hydrogen storage systems. However, QRA studies require reliability data which is currently lacking for expanding applications of hydrogen systems. Here, to address this gap, we present a new structure for a hydrogen component reliability database (HyCReD) that can be used to generate reliability data to be used in QRA, reliability, safety studies, maintenance planning, and more. Building on our previous work examining four major hydrogen safety data collection tools (West et al., 2022) [1], our approach in this work was to consult scientific literature on reliability data collection as well as a number of existing reliability engineering databases in the oil & gas, chemical processing, and nuclear power plant sectors. The evaluation of these databases led to identifying best practices to be implemented in a data collection framework for a hydrogen component reliability database. Based on these best practices, a set of 24 requirements for the proposed database are presented, covering its characteristics and the types of data to be collected. We define the structure of the HyCReD database and 25 data elements to be collected, spanning system description, failure, shutdown, or near-miss events, and maintenance events. The data elements are then defined according to international standards used in the safety and reliability practice and potential choice lists are provided for each field. Since this database is being piloted for hydrogen fueling stations, a generic station component hierarchy developed by West (2021) [2] is used to standardize system data. Finally, we demonstrate populating the database with information extracted from five narrative reports on hydrogen fueling station incidents.

08 HYDROGEN↗