Results for “contributions to safety” — Page 19

DOE OSTI2020

Design of Experiments Involving Molybdenum in SNL SPRF/CX Facility

This report is part of the collaboration with the Nuclear Criticality Safety Program and constitutes the “CED-2 report” of the experiments proposed in the SPRF/CX facility of SANDIA National Laboratories to contribute to the validation of Molybdenum in thermal energy spectrum. It supplements the study carried out in the CED-1 report by providing a more precise design of the proposed experiments and presents a complete evaluation of the experimental uncertainties. In the CED-1 report, corresponding to the preliminary design of the experiments, IRSN identified several promising configurations that could be implemented in the SPRF/CX facility of SNL. They use metallic molybdenum either in the form of foils between the UO 2 pellets inside BUCCX rods, or in the form of sleeves surrounding 7uPCX rods. In this CED-2 report, a new design using molybdenum sleeves surrounding BUCCX rods is also analyzed and the experimental uncertainties of all the proposed configurations are estimated. Given the constraints to carry out the experiments and the costs associated with the manufacturing of the foils, the experiments using molybdenum foils are discarded. Similarly, the design using molybdenum sleeves around BUCCX rods leads to significant manufacturing costs which could certainly be partially offset by use of existing grids but which would lead to slightly lower values of the integral sensitivities to the cross sections of molybdenum. Consequently, the design using molybdenum sleeves around 7uPCX rods is favored insofar as it presents higher $k_{eff}$ sensitivities to the molybdenum cross sections and that there is still possibility to reduce the number of sleeves to reduce the cost of experiments. Regarding feedback on nuclear data in support of criticality safety assessment, one of the advantages of the work described here is that the proposed experiments are not correlated with the MIRTE and FP experiments using molybdenum. In addition, they lead to higher sensitivity values in the thermal energy range than the existing experiments and partly “cover” the first resonance of the 95 Mo, which is a real advantage for improving knowledge on molybdenum cross sections.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2025

Complete Initial Studies in Microstructural Studies of Nuclear Graphite

Nuclear graphite is a critical material for the performance and safety of high-temperature reactors, making its study essential for the successful deployment of next-generation reactors in the United States. During the past year, Oak Ridge National Laboratory (ORNL) has contributed extensively to advancing the understanding of nuclear graphite’s properties, behavior, and applications; particular focus has been given to irradiation effects, oxidation mechanisms, thermal and mechanical performance, and long-term stability under reactor conditions. This report provides an update on the ongoing publications being prepared at ORNL. These studies are collectively intended to build a comprehensive knowledge base on nuclear graphite. The studies focus on key aspects such as microstructural characterization, oxidation behavior, advanced analytical techniques, molten salt infiltration, technique development, and billet-to-billet variability. By summarizing the progress of these publications, this report outlines ORNL’s contributions to the field, identifies knowledge gaps, and proposes future research directions. The findings presented in these studies will help enhance the understanding of nuclear graphite’s behavior, support the qualification of nuclear graphite materials, further the development of new techniques and guidelines for using microscopy techniques, and improve reactor safety and performance.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2023

The need for an integrated multi-OMICs approach in microbiome science in the food system

Microbiome science as an interdisciplinary research field has evolved rapidly over the past two decades, becoming a popular topic not only in the scientific community and among the general public, but also in the food industry due to the growing demand for microbiome-based technologies that provide added-value solutions. Microbiome research has expanded in the context of food systems, strongly driven by methodological advances in different -omics fields that leverage our understanding of microbial diversity and function. However, managing and integrating different complex -omics layers are still challenging. Within the Coordinated Support Action MicrobiomeSupport (https://www.microbiomesupport.eu/), a project supported by the European Commission, the workshop “Metagenomics, Metaproteomics and Metabolomics: the need for data integration in microbiome research” gathered 70 participants from different microbiome research fields relevant to food systems, to discuss challenges in microbiome research and to promote a switch from microbiome-based descriptive studies to functional studies, elucidating the biology and interactive roles of microbiomes in food systems. A combination of technologies is proposed. This will reduce the biases resulting from each individual technology and result in a more comprehensive view of the biological system as a whole. Although combinations of different datasets are still rare, advanced bioinformatics tools and artificial intelligence approaches can contribute to understanding, prediction, and management of the microbiome, thereby providing the basis for the improvement of food quality and safety.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2024

An Analysis of the Spatial Variations in the Relationship Between Built Environment and Severe Crashes

Traffic crashes significantly contribute to global fatalities, particularly in urban areas, highlighting the need to evaluate the relationship between urban environments and traffic safety. This study extends former spatial modeling frameworks by drawing paths between global models, including spatial lag (SLM), and spatial error (SEM), and local models, including geographically weighted regression (GWR), multi-scale geographically weighted regression (MGWR), and multi-scale geographically weighted regression with spatially lagged dependent variable (MGWRL). Utilizing the proposed framework, this study analyzes severe traffic crashes in relation to urban built environments using various spatial regression models within Leon County, Florida. According to the results, SLM outperforms OLS, SEM, and GWR models. Local models with lagged dependent variables outperform both the global and generic versions of the local models in all performance measures, whereas MGWR and MGWRL outperform GWR and GWRL. Local models performed better than global models, showing spatial non-stationarity; so, the relationship between the dependent and independent variables varies over space. The better performance of models with lagged dependent variables signifies that the spatial distribution of severe crashes is correlated. Finally, the better performance of multi-scale local models than classical local models indicates varying influences of independent variables with different bandwidths. According to the MGWRL model, census block groups close to the urban area with higher population, higher education level, and lower car ownership rates have lower crash rates. On the contrary, motor vehicle percentage for commuting is found to have a negative association with severe crash rate, which suggests the locality of the mentioned associations.

Alisan, Onur (ORCID:0000000193113984)↗

NASA NTRS2001

Evaluation of the National Throughput Benefits of the Civil Tilt Rotor

The air transportation system is a key part of the U.S. and global economic infrastructure. In recent years, this system, by any measure of usage - operations, enplanements, or revenue passenger miles (RPMs) - has grown rapidly. The rapid growth in demand has not been matched; however, by commensurate increases in the ability of airports and the airspace system to handle the additional traffic. As a result, the air transportation system is approaching capacity and airlines will face excessive delays or significant constraints on service unless capacity is expanded. To expand capacity, the air traffic management system must be improved. To improve the air traffic management system, the National Aeronautics and Space Administration (NASA) Aerospace Technology Enterprise developed the strategic goal of tripling air traffic throughput over the next 10 years, in all weather conditions, while at least maintaining current safety standards. As the first step in meeting that goal, the NASA Intercenter Systems Analysis Team (ISAT) is evaluating the contribution of existing programs to meet that goal. A major part of the study is an examination of the ability of the National Airspace System (NAS) to meet the predicted growth in travel demand and the potential benefits of technology infusion to expand NAS capacity. We previously analyzed the effects of the addition of two technology elements - Terminal Area Productivity (TAP) and Advanced Air Transportation Technologies (AATT). The next program we must analyze is not specific to airspace or aircraft technology. The program incorporates a fundamentally different vehicle to improve throughput: the civil tilt rotor (CTR). The CTR has the unique operating characteristic of being able to take off and land like a rotorcraft (vertical take off and landing, or VTOL, capability) but cruises like a traditional fixed-wing aircraft. The CTR also can operate in a short take off and landing (STOL) mode; generally, with a greater payload capacity (i.e., more passengers) than when operating in the VTOL mode. CTR could expand access to major airports without interfering with fixed-wing aircraft operating on congested runways and it could add service to new markets without the infrastructure support needed for fixed-wing aircraft. During FY 1999, we preliminarily assessed the feasibility of operating CTRs at two major U.S. airports as part of the annual review of NASA aerospace goals by the ISAT. This current study expands the analysis and concepts of that study to the complete NAS to quantify the national throughput effects of the CTR.

Johnson, Jesse↗

NASA NTRS1997

Identification of Error Patterns in Terminal-Area ATC Communications

Advancing air traffic management technologies have enabled a greater number of aircraft to use the same airspace more effectively. As aircraft separations are reduced and final approaches are more finely timed, there is less room for error. The present study examined 122 terminal-area, loss-of-separation and procedure violation incidents reported to the Aviation Safety Reporting System (ASRS) by air traffic controllers. Narrative description codes were used for the incidents for type of violation, contributing factors, recovery strategies, and consequences. Usually multiple errors occurred prior to the violation. Error sequences were analyzed and common patterns of errors were identified. In half of the incidents, errors were noticed in time to correct mistakes. Of these, almost 43% committed additional errors during the recovery attempt. This analysis shows that redundancies in the present air traffic control system may not be sufficient to support large increases in traffic density. Error prevention and design considerations for air traffic management systems are discussed.

Quinn, Cheryl↗

NASA NTRS2015

Explicate '78: Uncovering the Implicit Assurance Case in DO-178C

For about two decades, compliance with Software Considerations in Airborne Systems and Equipment Certification (DO-178B/ED-12B) has been the primary means for receiving regulatory approval for using software on commercial airplanes. A new edition of the standard, DO-178C/ED-12C, was published in December 2011, and recognized by regulatory bodies in 2013. The purpose remains unchanged: to provide guidance 'for the production of software for airborne systems and equipment that performs its intended function with a level of confidence in safety that complies with airworthiness requirements.' The text of the guidance does not directly explain how its collection of objectives contributes to achieving this purpose; thus, the assurance case for the document is implicit. This paper presents an explicit assurance case developed as part of research jointly sponsored by the Federal Aviation Administration and the National Aeronautics and Space Administration.

Holloway, C. Michael↗

NASA NTRS2022

SWOT and NISAR Boom Ground Deployment Test Challenges & Resolution

NASA’s Jet Propulsion Laboratory is developing two new spacecraft that use radar instruments to characterize temporal changes in the Earth’s surface with unprecedented precision (Figure 1). Both the Surface Water Ocean Topography (SWOT) and the NASA-ISRO Synthetic Aperture Radar (NISAR) spacecraft utilize large, precision flight deployable booms to properly position and support their instrument reflectors. The SWOT spacecraft includes two nearly identical reflector booms, each of which have similar flight deployable hinge designs. The NISAR spacecraft has a single reflector boom, with four unique hinge designs. These booms each undergo a multi-staged flight deployment sequence on orbit to transition from the launch stowed configuration to the science configuration within days of launch (Figure 2). The SWOT and NISAR Projects faced significant challenges relevant to requirement verification as well as hardware safety in their approach to ground testing these large flight deployables. This report summarizes flight deployable system design decisions that contributed to ground testing challenges. The report also summarizes the architecture trade study conducted for ground deployment testing. A summary of key issues encountered during flight deployable ground testing with the chosen common gravity offload system ensues, with discussion of the issues and mitigation measures implemented by both Projects that ultimately enabled successful flight subsystem-level full range of motion ground tests. Recommendations and lessons learned are offered to facilitate ground testability of future analogous large scale flight deployables.

Waters, Kyle C.↗

NASA NTRSDate not supplied

Overview of Lightning Science at NASA Marshall Space Flight Center

NASA Marshall Space Flight Center (MSFC) is a recognized world leader in the science of lightning. To date, MSFC has led three space-based global lightning observing missions and has helped lead multiple suborbital field campaigns involving lightning observations. Recently, the MSFC Lightning Team is closing out the recently completed International Space Station Lightning Imaging Sensor (ISS LIS) mission, including developing a nearly three-decade global climatology of lightning from space. This work also includes integrating lightning observations with data from NASA precipitation missions. The Team is also busy analyzing data from a recent airborne field campaign that observed dozens of terrestrial gamma-ray flashes (TGFs) from intense tropical thunderstorms. Lightning Team members are also leaders in validation of the Geostationary Lightning Mapper (GLM) operated by NOAA, and in developing lightning safety applications and studying the relationship between lightning and wildfires. The Lightning Team also studies chemical production by lightning and contributes to the National Climate Assessment (NCA). Finally, the Lightning Team is busy developing the next generation of spaceborne lightning sensors to broaden our understanding of the relationships between lightning, weather, climate, and atmospheric composition.

Timothy Lang↗

DOE OSTI2022

Estimating β eff from static, late-time Feynman neutron noise measurements

The effective delayed neutron fraction, β eff , is a kinematic parameter describing the contribution of delayed neutrons to the effective multiplication factor, $\kappa$ eff , and is of great interest to the nuclear criticality safety community and beyond. In fact, $\kappa$ eff presently must be inferred (as opposed to directly measured) since variables like β eff must be obtained from simulation, reference tables, or a dynamic or pulsed measurement where the assembly of fissile material is perturbed and not in steady state. Several recent works have proposed neutron noise techniques to estimate β eff from static measurements (such as benchmark experiments). This work experimentally investigates an approach based on looking at late-time (up to thousands of seconds) correlated neutrons in Feynman histograms. This work utilizes measurements of weapons grade plutonium and highly enriched uranium to construct late-time Feynman histograms and investigate a proposed methodology of estimating β eff from a fit of the distribution. Data is shown from both He-3 detectors and an organic scintillator array. This work is preliminary in nature, demonstrating some experimental feasibility and proposing improvements for future investigations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

NASA NTRS2023

Adaptive Independent Verification and Validation (IV&V) Reduces Risk of Software Impacting Safety in Artemis Missions

The National Aeronautics and Space Administration (NASA) is asking more of its human spaceflight programs than ever before through the collective Artemis Missions. The NASA Independent Verification and Validation (IV&V) Program contributes to NASA’s human spaceflight goals by providing IV&V services for NASA’s critical spacecraft and ground software. The IV&V Program is tasked with providing assurance from both individual and integrated mission software perspectives. The Artemis IV&V organization is actively supporting six distinct development efforts: Orion, the Space Launch System (SLS), Exploration Ground Systems (EGS), Mission Control Center (MCC), the Lunar Gateway, and the Human Landing System (HLS), representing a wide diversity of developer organizations, management structures, and development approaches. With much of this extremely complex flight and ground software being essential to human safety both on the ground and in space, Artemis IV&V is likewise challenged to provide more value-added assurance to future Artemis missions within a constrained budget. To meet this challenge, Artemis IV&V employs a variety of novel and evolving “Adaptive IV&V” approaches for planning and executing IV&V analysis to increase both the efficiency and effectiveness of the IV&V Program’s assurance activities, and to address the difficulties imposed by assuring software for a large, highly integrated, multi-mission enterprise managed and executed by physically and organizationally distinct programs. Instilling agile principles like iterative planning cycles, self-organizing teams, and regular retrospectives, into IV&V planning and execution has led to a more rapid turnaround of a minimum viable assurance product and allowed for increased alignment of assurance activities with development progress. Adopting an assurance case methodology has led to greater consistency and clearer communication of assurance design and provided a foundation for long-term maintenance of assurance plans, products, and results across missions. The IV&V-developed Assurance / Safety Case Analytical Network (A-SCAN) framework and tool has enabled the quantification and tracking of system/software risk and confidence. These confidence measures provide a means to repeatedly express the impact of planned and completed assurance work and the remaining residual risk. Applied as part of a “Follow-the-Risk” organizational ethos, this allows consistent rightsizing of analysis rigor and intensity commensurate with the perceived risk of defects, as well as appropriate targeting of the highest risk areas of the software to find safety issues before they can manifest. Finally, the development of the IV&V Advanced Risk Reduction Integrated Software Test and Operations Tri-program Lightweight Environment (ARRISTOTLE), an integrated software-only simulation of Orion, SLS, and EGS systems, has made it possible to independently test integrated pad and flight scenarios and inject faults to observe how the Artemis multi-program, mission software behaves in degraded modes and in response to hazards. These adaptive IV&V investments have enabled Artemis IV&V to become more efficient and effective in IV&V planning and execution and respond more readily to changes in the risk landscape, increasing the breadth and depth of risk reduction possible within the available resources. Residual risk tracking allows IV&V to communicate more effectively with stakeholders, both internal and external at all levels, and inform key decision-making personnel. This evolving assurance design approach provides IV&V surety that work is performed in the highest risk, most value-added areas of the software, to keep our astronauts and ground crews safe and ensure mission success.

Gerek A Whitman↗

NASA NTRS2023

Adaptive Independent Verification and Validation (IV&V) Reduces Risk of Software Impacting Safety in Artemis Missions

The National Aeronautics and Space Administration (NASA) is asking more of its human spaceflight programs than ever before through the collective Artemis Missions. The NASA Independent Verification and Validation (IV&V) Program contributes to NASA’s human spaceflight goals by providing IV&V services for NASA’s critical spacecraft and ground software. The IV&V Program is tasked with providing assurance from both individual and integrated mission software perspectives. The Artemis IV&V organization is actively supporting six distinct development efforts: Orion, the Space Launch System (SLS), Exploration Ground Systems (EGS), Mission Control Center (MCC), the Lunar Gateway, and the Human Landing System (HLS), representing a wide diversity of developer organizations, management structures, and development approaches. With much of this extremely complex flight and ground software being essential to human safety both on the ground and in space, Artemis IV&V is likewise challenged to provide more value-added assurance to future Artemis missions within a constrained budget. To meet this challenge, Artemis IV&V employs a variety of novel and evolving “Adaptive IV&V” approaches for planning and executing IV&V analysis to increase both the efficiency and effectiveness of the IV&V Program’s assurance activities, and to address the difficulties imposed by assuring software for a large, highly integrated, multi-mission enterprise managed and executed by physically and organizationally distinct programs. Instilling agile principles like iterative planning cycles, self-organizing teams, and regular retrospectives, into IV&V planning and execution has led to a more rapid turnaround of a minimum viable assurance product and allowed for increased alignment of assurance activities with development progress. Adopting an assurance case methodology has led to greater consistency and clearer communication of assurance design and provided a foundation for long-term maintenance of assurance plans, products, and results across missions. The IV&V-developed Assurance / Safety Case Analytical Network (A-SCAN) framework and tool has enabled the quantification and tracking of system/software risk and confidence. These confidence measures provide a means to repeatedly express the impact of planned and completed assurance work and the remaining residual risk. Applied as part of a “Follow-the-Risk” organizational ethos, this allows consistent rightsizing of analysis rigor and intensity commensurate with the perceived risk of defects, as well as appropriate targeting of the highest risk areas of the software to find safety issues before they can manifest. Finally, the development of the IV&V Advanced Risk Reduction Integrated Software Test and Operations Tri-program Lightweight Environment (ARRISTOTLE), an integrated software-only simulation of Orion, SLS, and EGS systems, has made it possible to independently test integrated pad and flight scenarios and inject faults to observe how the Artemis multi-program, mission software behaves in degraded modes and in response to hazards. These adaptive IV&V investments have enabled Artemis IV&V to become more efficient and effective in IV&V planning and execution and respond more readily to changes in the risk landscape, increasing the breadth and depth of risk reduction possible within the available resources. Residual risk tracking allows IV&V to communicate more effectively with stakeholders, both internal and external at all levels, and inform key decision-making personnel. This evolving assurance design approach provides IV&V surety that work is performed in the highest risk, most value-added areas of the software, to keep our astronauts and ground crews safe and ensure mission success.

Gerek Whitman↗

DOE OSTI2025

Exploring how urban form and demographics are linked with pedestrian and bicycle safety

With pedestrian and bicycle safety as the focus, this study investigates the role of urban form, burdened communities (BCs), and demographics at the national level. Urban form can contribute to segregation, limiting access to crucial resources such as safe infrastructure, essential services, and economic opportunities. Leveraging recent data, this research applies six key indicators to identify BCs based on various socioeconomic and environmental factors. Here, the study creates a unique database combining 10 years of pedestrian-bicycle-involved fatal crashes with data for the 71,729 census tracts with burden indicators and census data. The data are analyzed using descriptives and rigorous zero-hurdle negative binomial models, which account for excessive zeros observed in the data. The inference-based analysis results reveal a positive correlation between burden indicators and pedestrian-bicycle-involved fatal crash occurrences, alongside a heightened risk in areas with high-intensity development. Higher Black, American Indian, or Alaska Native populations are associated with more fatal crashes. The study offers novel insights into safety dynamics across different contexts characterized by urban forms, BCs, and demographics. The study underscores the importance of targeted interventions to enhance pedestrian and bicycle safety.

bicycle crashes↗

DOE OSTI2022

Human reliability analysis studies from simulator experiments using Bayesian inference

Probabilistic Safety Assessment (PSA) of complex facilities is performed to arrive at the risk posed by them. PSA also accounts for the contribution of the human errors towards the overall risk through Human Reliability Analysis (HRA) in terms of Human Error Probability (HEP). Human operators are part of the system and do not work in isolation. Their performance is influenced by the context in which the actions are performed. As a result, quantification of HEP requires operator performance data under the given context. Some good sources of operator performance data are plant‘s operation data, simulator data and expert judgement. The plant operation data pertaining to HRA is generally sparse. In this situation, a full scope plant simulator provides a good alternative for operator performance data generation. Many of the currently practiced HRA methods have been developed by combining the empirical evidence with expert judgement and contain a lot of uncertainty in their estimates. Bayesian inference is suitable for updating the prior HRA estimates with the simulator evidence to obtain the posterior HEP. Here, posterior HEP has been calculated for postulated accident scenarios in advanced reactor (first of its kind) at design stage, using plant simulator.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Developing an Automated Microscopic Traffic Simulation Scenario Generation Tool

Traffic simulation is an effective tool for urban planners, traffic engineers, and researchers to study traffic. In particular, microscopic traffic simulation, which simulates individual vehicles’ movements within a transportation network, has demonstrated its importance in analyzing and managing transportation systems. However, integrating data from various sources, generating traffic scenarios, and importing information into traffic simulators to conduct microscopic simulations have always been a challenge. This paper presents a solution to overcome this challenge: RealTwin, a comprehensive tool for automated scenario generation for microscopic traffic simulation. Following a streamlined scenario generation and calibration workflow, RealTwin effectively bridges gaps between traffic data from various sources and traffic simulators, making microscopic traffic simulation more accessible for researchers and engineers across various levels of expertise. Using RealTwin to generate a real-world traffic scenario in Simulation of Urban Mobility (SUMO), VISSIM, and AIMSUN, RealTwin’s ability is demonstrated in the construction of realistic and consistent traffic scenarios in different simulators. Furthermore, this paper introduces and illustrates RealTwin’s capability for technology (e.g., autonomous vehicle) scenario generation. This feature can contribute to more comprehensive microscopic simulations, facilitating the analysis of potential effects of various technological innovations on mobility, energy efficiency, and safety. Finally, RealTwin is used to calibrate a simulation in SUMO. In conclusion, the calibration module enhances RealTwin’s ability to generate consistent simulations across different platforms and more realistic simulations that reflect real-world traffic operations.

autonomous vehicle↗

DOE OSTI2023

Confidentiality-preserving machine learning algorithms for soft-failure detection in optical communication networks

Automated fault management is at the forefront of next-generation optical communication networks. The increase in complexity of modern networks has triggered the need for programmable and software-driven architectures to support the operation of agile and self-managed systems. In these scenarios, the European Telecommunications Standards Institute zero-touch network and service management approach is imperative. The need for machine learning algorithms to process the large volume of telemetry data brings safety concerns as distributed cloud-computing solutions become the preferred approach for deploying reliable communication network automation. This paper’s contribution is twofold. First, we propose a simple yet effective method to guarantee the confidentiality of the telemetry data based on feature scrambling. The method allows the operation of third-party computational services without direct access to the full content of the collected data. Additionally, the effectiveness of four unsupervised machine learning algorithms for soft-failure detection is evaluated when applied to the scrambled telemetry data. The methods are based on factor analysis, principal component analysis, nonlinear principal component analysis, and singular value decomposition. Most dimensionality reduction algorithms have the common property that they can maintain similar levels of fault classification performance while hiding the data structure from unauthorized access. Evaluations of the proposed algorithms demonstrate this capability.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

A Survey of Direct Heating Equipment Market Actors in California

Direct Heating Equipment (DHE) is a category of ductless space heating appliances that provide warm air directly to the space where they are installed. We investigate, from the perspective of the DHE supply chain in California, what types of DHE are marketed in the state, how they are sold and serviced, and whether any potential barriers to adoption of high-efficiency DHE exist. We find that the market for DHE in the state is almost exclusively a replacement market, with some additional repair and maintenance services. We also find that, even though manufacturers sell high-efficiency DHE models in California, most contractors report installing baseline models most of the time. Contractors say their customers do not see any value in high-efficiency units, and they (contractors) do not believe that high-efficiency DHE is worth the additional cost to their customers. In addition, the majority of contractors purchase DHE from distributors and, therefore, distributors are a key piece of the supply chain that can constrain DHE purchase choice. Distributors do not see a demand for high-efficiency DHE and, hence, do not keep stock of these units. They argue that, since the market is driven mostly by replacements and these replacements occur typically in an unplanned way, homeowners are unwilling to pay for any additional costs associated with a high-efficiency model. Rather, homeowners usually prefer to replace the failed unit with a new unit that can fit in the same location with no- or minimal additional replacement costs. Considering that most DHE purchases are made by contractors, on behalf of their customers, informing contractors (and homeowners) of the potential cost-effectiveness of efficient DHE could help mitigate some of the barriers to the adoption of high-efficiency DHE in the state. In addition, monetary incentives and more stringent building codes that apply to DHE replacements can contribute to increasing adoption of high-efficiency DHE in California. This will not only reduce energy costs, but also increase safety and comfort to DHE users.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2026

Statistical and Machine Learning Approaches to Analyzing Pipeline Incidents in the United States (2010–2024)

This study applies machine learning methods to analyze natural gas pipeline incidents in the United States using the Pipeline and Hazardous Materials Safety Administration (PHMSA) Gas Distribution Incident Dataset (2010–2024). The dataset includes over 600 variables describing incident characteristics, infrastructure attributes, and contributing factors associated with unintentional gas releases. The objective is to assess whether these features can reliably predict the underlying cause of pipeline failures. Multinomial logistic regression and Random Forest models were developed to classify incident causes, including excavation damage, corrosion, equipment failure, and natural forces. Results show that excavation damage is both the most frequent and most predictable cause, with models achieving strong performance for this category. However, when excavation damage is excluded, model accuracy declines significantly, with some models performing near random levels. Across all approaches, severe class imbalance and limited variability in key predictors constrain predictive performance. Pipeline age and diameter emerge as the most influential variables, but they provide insufficient discriminatory power to distinguish among less frequent failure types. These findings indicate that non-excavation-related incidents are rare, heterogeneous, and weakly represented in the dataset, limiting the effectiveness of machine learning classification. Overall, this study highlights the structural limitations of the PHMSA dataset for predictive modeling and underscores the need for improved data balance and feature enrichment. The results reinforce excavation damage prevention as the most impactful strategy for reducing pipeline incidents.

03 NATURAL GAS↗