Search NASA⌕ Search

SEARCH · Search NASA

Results for “well integrity”

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 649 records · Page 36
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

High-Resolution Southeast Asia Wind Resource Data Set

Well informed decision-making is a key part of integrating variable renewable energy into the global energy marketplace. USAID and NREL, through the Advanced Energy Partnership for Asia, are expanding access to critical resource data by providing free, high-fidelity time-series wind resource data for Southeast Asia through the RE Data Explorer platform. This brief highlights the development of the Southeast Asia wind resource data set and discusses the impacts of this data.

Advanced Energy Partnership for Asia↗
DOE OSTI2023

Supporting Nuclear Energy Research with MLOps

Artificial intelligence (AI) and machine learning (ML) have been shown to be increasingly helpful tools in a growing number of use-cases relevant to scientific research, despite significant software-related obstacles. There exist large technical costs to setting up, using, and maintaining AI/ML models in production. This often prevents researchers from utilizing these models in their work. The growing field of machine learning operations (MLOps) aims to automate much of the AI/ML life cycle while increasing access to these models. This paper presents our initial work in creating a nuclear energy MLOps platform for use by researchers at Idaho National Laboratory (INL) and aims to reduce the barriers of using AI/ML in scientific research. We hope to promote the integration of the latest AI/ML technologies into researchers' workflows and create more opportunity for scientific innovation. In this paper we discuss how our MLOps efforts aim to increase usage and the impact of AI/ML models created by engineers. We also present several use-cases that are currently integrated. Finally, we evaluate the maturity of our project as well as our plans for future functionality.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Development of a Regulatory Strategy for Post Operational Clean Out Activities at Sellafield Limited Nuclear Licensed Site - 20273

The Thermal Oxide Reprocessing Plant (THORP) at the Sellafield nuclear licensed site carried out its final commercial shear of spent nuclear fuel in November 2018, since when the facility has undergone rundown prior to cessation of operations. The Magnox Reprocessing Facility (MRF) is also due to cease operating, around the end of 2020. Following the cessation of spent fuel reprocessing, the facilities and supporting infrastructure will transition into Post Operational Clean Out (POCO), which will become an increasingly significant portion of Sellafield Limited's (SL) activities. POCO is defined as the set of activities undertaken directly after a nuclear facility comes to the end of its operational life, in order to place the plant in a suitable state for the subsequent decommissioning steps. The decommissioning strategy at SL is for deferred dismantling of these facilities, which will be subject to a period of Surveillance and Maintenance (S and M) following completion of POCO. This paper outlines the development and implementation of a regulatory strategy for POCO activities at the Sellafield site by the Office for Nuclear Regulation (ONR), the independent nuclear safety, transport and security regulator in the United Kingdom. The paper also describes how this regulatory strategy is applied to nuclear installations undergoing transition into POCO and subsequent decommissioning. ONR works jointly with the Environment Agency, as the environmental regulators in England, to ensure that matters relevant to them have been duly considered. In developing a regulatory strategy, ONR has taken a site-wide approach, moving away from regulation on a facility-by-facility basis, to promote consistency, as well as maximising efficiency and effectiveness. The aim of this integrated approach was to prevent complications during future decommissioning and dismantling that have been experienced previously at similar facilities in France. The strategy recognised that once reprocessing operations are concluded, the hazard present will be reduced significantly, which provides the opportunity for ONR to consider how best to deliver a proportionate approach to regulatory interventions. Once POCO has been completed and the facility has transitioned into a period of S and M, the scale and frequency of ONR's interventions will reduce, commensurate with the safety case covering the remaining hazard and activities associated with maintaining the facility prior to final decommissioning. This approach allows ONR to consider risks holistically, considering the full life cycle of the facility and by taking due account of the interdependencies between facilities across the site. The strategy also aligns with existing regulation of high hazard and risk reduction activities, which remain ONR's top priority. As SL progresses with POCO activities in THORP and across the rest of the site, ONR will review its regulatory strategy to ensure that the intended safety benefits are realised. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Real-time Anomaly Detection at the L1 Trigger of CMS Experiment

We present the preparation, deployment, and testing of an autoencoder trained for unbiased detection of new physics signatures in the CMS experiment Global Trigger (GT) test crate FPGAs during LHC Run 3. The GT makes the final decision whether to readout or discard the data from each LHC collision, which occur at a rate of 40 MHz, within a 50 ns latency. The Neural Network makes a prediction for each event within these constraints, which can be used to select anomalous events for further analysis. The GT test crate is a copy of the main GT system, receiving the same input data, but whose output is not used to trigger the readout of CMS, providing a platform for thorough testing of new trigger algorithms on live data, but without interrupting data taking. We describe the methodology to achieve ultra low latency anomaly detection, and present the integration of the DNN into the GT test crate, as well as the monitoring, testing, and validation of the algorithm during proton collisions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Evaluation of Maximum Allowable Working Pressure and Svensson Burst Pressure Recommended in API 579-1 2021 Edition

ABSTRACT API 579-1/ASME FFS-1 2021 Edition provides the minimum wall thickness, the maximum allowable working pressure (MAWP), and the membrane stress equations for thin and thick-walled cylindrical shells subject to internal pressure in Section 2C.3.3.1 of Appendix 2C – Thickness, MAWP, and Stress Equations for an FFS Assessment. The minimum wall thickness and MAWP are determined using the hoop stress and the Tresca yield criterion. Section 2C.7 – Estimation of Burst Pressure newly added the Svensson method for calculating burst pressure of cylindrical shells under internal pressure, where the plastic yielding is characterized by the von Mises yield criterion. For thin-walled cylinders, the von Mises flow solution of burst pressure in Equation (2C.179) was recommended. For thick-walled cylinders, an implicit burst pressure solution in an integral equation (2C.176) was recommended. But this integral equation is inconvenient to use in practice. It is well known that the classic plasticity theory includes the Tresca and von Mises yield criteria, with the Tresca criterion predicting a lower bound solution and the von Mises criteria predicting an upper bound solution. In addition, the present author developed an average shear stress yield criterion that can determine more accurate limit and burst pressures for thin and thick-walled cylinders. This work uses these three yield criteria to evaluate the minimum required wall thickness, MAWP and Svensson burst pressure recommended in the API 579 code.

burst pressure↗
DOE OSTI2025

COR-0011 Rev 6 MARVEL Project Code of Record

This Code of Record identifies the codes, standards, and procedures necessary to design, develop, construct, and startup the Microreactor Applications Research Validation and Evaluation (MARVEL) Project at the Materials and Fuel Complex (MFC) Transient Reactor Test (TREAT) Facility and the Idaho National Laboratory (INL). The MARVEL Project is an INL test microreactor funded by the United States Department of Energy (DOE) via the Microreactor Program (MRP). The goal of the project is to establish an operational nuclear applications test bed that can generate combined heat and power to enable integration and R&D with end-user technologies, as well as allow microreactor technologists to test next-generation control systems. The microreactor is a thermal reactor utilizing Uranium Zirconium Hydride (UZrH) fuel with review and authorization by the Department of Energy Idaho Operations Office (DOE-ID) for National Environmental Policy Act (NEPA) compliance, safety review, and supplemental readiness assessments for startup and operation. To enable rapid deployment, the MARVEL reactor will reside in the Transient Reactor Test (TREAT) Facility and utilize the existing operating Category B reactor facility, approved facility safety basis, operating crews, and recent re-start experience.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗
DOE OSTI2025

Toward Drilling the Perfect Geothermal Well: An International Research Coordination Network for Geothermal Drilling Optimization Supported by Deep Machine Learning and Cloud Based Data Aggregation

The EDGE project, supported by the U.S. Department of Energy Geothermal Technologies Office under award DE-EE0008793, established a data-driven framework for improving the efficiency, cost-effectiveness, and reliability of geothermal well drilling. The project focused on developing scalable data infrastructure, advanced machine learning and probabilistic models, and integrated analytics tools to support continuous drilling optimization. A central objective was to reduce geothermal drilling costs by up to seventy percent while minimizing the risk of well failure through predictive diagnostics and adaptive planning. Over the project period, a comprehensive data repository was designed and deployed, incorporating records from over one hundred geothermal wells across varied geological settings. This repository supported both structured and unstructured data and adhered to FAIR data principles, enabling provenance tracking, quality control, and standardized metadata. The project introduced automated ingestion pipelines and a cloud-hosted platform that facilitated access to raw, processed, and derived datasets. This infrastructure served as the foundation for model development and analysis. Machine learning workflows were developed to predict key drilling metrics including rate of penetration, non-productive time, and total drilling costs. Self-organizing maps and dimensionality reduction methods were used to uncover operational patterns and outliers, while supervised learning algorithms such as random forests and deep neural networks were applied to forecast performance outcomes. The models were validated on heterogeneous datasets from both U.S. and Icelandic fields, demonstrating variable but significant predictive accuracy. The results indicated that finer temporal resolution, inclusion of lithological data, and consistency in operational annotations could substantially improve model performance. The project also implemented process mining techniques to reconstruct state-transition models from drilling event logs. These models enabled the identification of deviations from optimal workflows and provided insights into recurring failure modes. Analysis of non-productive time highlighted the impact of equipment failures, geological challenges, and human factors, offering opportunities for targeted mitigation strategies. The EDGE Dashboard was developed as a web-based expert system integrating data visualization, model outputs, and user-driven queries. It provided an accessible interface for operators to explore historical data, evaluate predicted outcomes, and compare drilling scenarios. Initial feedback from project partners suggested that the dashboard could serve as a foundation for more advanced advisory and optimization tools. Overall, the EDGE project demonstrated the feasibility and value of applying modern data science techniques to geothermal drilling. It delivered a set of interoperable tools and models that can support more efficient, lower-risk well development. The findings point toward a viable path for transitioning from advisory analytics to semi-autonomous drilling systems, contingent on continued collaboration, expanded datasets, and field validation. The project results have immediate relevance for drilling operations, data management practices, and future geothermal R&D efforts aimed at achieving reliable, cost-competitive geothermal energy at scale.

15 GEOTHERMAL ENERGY↗
DOE OSTI2021

Bringing discrete-time Langevin splitting methods into agreement with thermodynamics

In light of the recently published complete set of statistically correct Grønbech–Jensen (GJ) methods for discrete-time thermodynamics, we revise a differential operator splitting method for the Langevin equation in order to comply with the basic GJ thermodynamic sampling features, namely, the Boltzmann distribution and Einstein diffusion, in linear systems. This revision, which is based on the introduction of time scaling along with flexibility of a discrete-time velocity attenuation parameter, provides a direct link between the ABO splitting formalism and the GJ methods. This link brings about the conclusion that any GJ method has at least weak second order accuracy in the applied time step. It further helps identify a novel half-step velocity, which simultaneously produces both correct kinetic statistics and correct transport measures for any of the statistically sound GJ methods. Explicit algorithmic expressions are given for the integration of the new half-step velocity into the GJ set of methods. Finally, numerical simulations, including quantum-based molecular dynamics (QMD) using the QMD suite Los Alamos Transferable Tight-Binding for Energetics, highlight the discussed properties of the algorithms as well as exhibit the direct application of robust, time-step-independent stochastic integrators to QMD.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

FEW questions, many answers: using machine learning to assess how students connect food–energy–water (FEW) concepts

There is growing support and interest in postsecondary interdisciplinary environmental education which integrate concepts and disciplines in addition to providing varied perspectives. There is a need to assess student learning in these programs as well as rigorous evaluation of educational practices, especially of complex synthesis concepts. This work tests a text classification machine learning model as a tool to assess student systems thinking capabilities using two questions anchored by the Food-Energy-Water (FEW) Nexus phenomena by answering two questions (1) Can machine learning models be used to identify instructor-determined important concepts in student responses? (2) What do college students know about the interconnections between food, energy and water, and how have students assimilated systems thinking into their constructed responses about FEW? Reported here are a broad range of model performances across 26 text classification models associated with two different assessment items, with model accuracy ranging from 0.755 to 0.992. Expert-like responses were infrequent in our dataset compared to responses providing simpler, incomplete explanations of the systems presented in the question. For those students moving from describing individual effects to multiple effects, their reasoning about the mechanism behind the system indicates advanced systems thinking ability. Specifically, students exhibit higher expertise for explaining changing water usage than discussing tradeoffs for such changing usage. This research represents one of the first attempts to assess the links between foundational, discipline-specific concepts and systems thinking ability. These text classification approaches to scoring student FEW Nexus Constructed Responses (CR) indicate how these approaches can be used, in addition to several future research priorities for interdisciplinary, practice-based education research. Development of further complex question items using machine learning would allow evaluation of the relationship between foundational concept understanding and integration of those concepts as well as more nuanced understanding of student comprehension of complex interdisciplinary concepts.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2025

High-Throughput Microfluidic Electroporation (HTME): A Scalable, 384-Well Platform for Multiplexed Cell Engineering

Electroporation-mediated gene delivery is a cornerstone of synthetic biology, offering several advantages over other methods: higher efficiencies, broader applicability, and simpler sample preparation. Yet, electroporation protocols are often challenging to integrate into highly multiplexed workflows, owing to limitations in their scalability and tunability. These challenges ultimately increase the time and cost per transformation. As a result, rapidly screening genetic libraries, exploring combinatorial designs, or optimizing electroporation parameters requires extensive iterations, consuming large quantities of expensive custom-made DNA and cell lines or primary cells. To address these limitations, we have developed a High-Throughput Microfluidic Electroporation (HTME) platform that includes a 384-well electroporation plate (E-Plate) and control electronics capable of rapidly electroporating all wells in under a minute with individual control of each well. Fabricated using scalable and cost-effective printed-circuit-board (PCB) technology, the E-Plate significantly reduces consumable costs and reagent consumption by operating on nano to microliter volumes. Furthermore, individually addressable wells facilitate rapid exploration of large sets of experimental conditions to optimize electroporation for different cell types and plasmid concentrations/types. Use of the standard 384-well footprint makes the platform easily integrable into automated workflows, thereby enabling end-to-end automation. We demonstrate transformation of E. coli with pUC19 to validate the HTME's core functionality, achieving at least a single colony forming unit in more than 99% of wells and confirming the platform's ability to rapidly perform hundreds of electroporations with customizable conditions. This work highlights the HTME's potential to significantly accelerate synthetic biology Design-Build-Test-Learn (DBTL) cycles by mitigating the transformation/transfection bottleneck.

Gaillard, William R↗
DOE OSTI2025

Background-field Method and QCD Factorization

One method for deriving a factorization for QCD processes is to use successive integration over fields in the functional integral. In this approach, we separate the fields into two categories: dynamical fields with momenta above a relevant cutoff, and background fields with momenta below the cutoff. The dynamical fields are then integrated out in the background of the low-momentum background fields. This strategy works well at tree level, allowing us to quickly derive QCD factorization formulas at leading order. However, to extend the approach to higher loops, it is necessary to rigorously define the functional integral over dynamical fields in an arbitrary background field. This framework was carefully developed for the calculation of the effective action in a background field at the two-loop level in the classic paper by Abbott «The Background Field Method Beyond One Loop», Nucl. Phys. B 185 , 189 (1981). Building on this work, I specify the renormalized background-field Lagrangian and define the notion of the quantum average of an operator in a background field, consistent with the “separation of scales” scheme mentioned earlier. As examples, I discuss the evolution of the twist-2 gluon light-ray operator and the one-loop gluon propagator in a background field near the light cone.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Engineering integration in elementary science classrooms: Effects of disciplinary language scaffolds on English learners' content learning and engineering identity

Abstract Background Limited research examines the effects of integrated science and engineering (SE) instruction emphasizing disciplinary literacy and language activities on engineering identity and content understanding. Far fewer studies target English learners (ELs). Purpose The impact of an SE intervention on the development of science, engineering, and technology knowledge as well as engineering identity was examined. To address ELs' learning needs, the curricular design was built on a validated SE model by integrating (1) developmental, (2) language scaffolds, and (3) culturally based accommodations. Design/Method Separate analysis of variance examined the effects of the intervention on science, engineering, and technology knowledge as well as engineering identity. The relationship among engineering identity and content outcomes was also examined. ELs from kindergarten to second grade classrooms were randomly assigned to the integrated SE group or control group. Results Integrated SE instruction significantly increased ELs' science, engineering, and technology knowledge as well as a substantially developed engineering identity. Overall, ELs' engineering identity is associated with an increase in science, engineering, and technology content knowledge. However, second grade girls' identity development was not associated with learning measures. These correlations suggest the context of the engineering activity may have reinforced gendered stereotypes and reduced the effects for girls' engineering attitudes. Conclusions Integrated SE instruction emphasizing disciplinary literacy and cultural accommodations increases early elementary ELs' learning and engineering identity. Future studies should examine the unique effects of language scaffolds and cultural modifications on student learning and the impact of gender stereotypes on girls' engineering attitudes.

Aguirre‐Muñoz, Zenaida↗
DOE OSTI2024

Sustainable urban transformations based on integrated microgrid designs

The impacts of natural hazards on infrastructure, enhanced by climate change, are increasingly more severe emphasizing the necessity of resilient energy grids. Microgrids, tailored energy systems for specific neighbourhoods and districts, play a pivotal role in sustaining energy supply during main grid outages. These solutions not only mitigate economic losses and well-being disruptions against escalating hazards but also enhance city resilience in alignment with Sustainable Development Goal (SDG) 11. However, disregarding socioeconomic factors in defining microgrid boundaries risks perpetuating inequalities and impeding progress towards other SDG 11 targets, including fair democratic participation. Our approach integrates social and technical indicators to bolster urban microgrid planning. Through a case study in a US county, we illustrate how integrated microgrid planning effectively intertwines urban resilience, well-being and equity while promoting sustainable development. This study underscores the importance of integrated microgrid planning for sustainable and resilient urban transformation amid environmental and societal challenges.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

An integrated methane dehydroaromatization and chemical looping process

Most of the natural gas co-produced in oil wells is flared due to the high transportation costs of bringing it to market. Onsite upgrading of natural gas to liquid products could address this issue but there are few processes for effective direct conversion of natural gas to liquid products. Methane dehydroaromatization (DHA) over Mo/HZSM- 5 offers a potential route to a value-added liquid product, however, DHA conversion is severely limited by thermodynamics at most industrially relevant temperatures. Here we propose an integrated process coupling methane DHA, chemical looping for selective hydrogen oxidation, and subsequent water removal to achieve higher yields of aromatic products limited by the thermodynamics in one-pass systems. Here, we validate this process via the construction and operation of a one-of-a-kind multibed recirculating reactor, and achieve a combined aromatics yield of 42%. Detailed technoeconomic analysis of the process for mobile applications show that such a process could be economically viable under certain circumstances.

03 NATURAL GAS↗
DOE OSTI2021

Mesocrystallizing Nanograins for Enhanced Li + Storage

Morphology and crystallinity of electrode materials have a major effect on their charge carrier storage properties when applied in rechargeable batteries. While nanosizing electrode particles (with larger surface area) and maintaining electrode integrity are both good for performance enhancement, they seem to contradict each other and can be hardly well-balanced. Herein, we designed electrode particles consisting of numerous nanograins with uniform crystalline orientation to guarantee both high surface area and high structural integrity, allowing the significant improvement of Li + storage kinetics and performance. Applying this “mesocrystallizing” strategy to a NiCo 2 O 4 -based anode, resulting in various degrees of pseudocapacitance response, the long-term cyclability and rate performance of this material have been largely enhanced. Impressively, the mesocrystalline NiCo 2 O 4 electrode exhibits a high reversible capacity of 1403 mAh g -1 after 200 cycles at 1.6 A g -1 (a rate of 1.8 C). The growth mechanism of mesocrystalline materials with different morphologies is identified to be a topotactic strctural transition process featuring a gradual edge-to-core corrasion process. This work presents an important synthetic clue to balance the morpholgy and crystallinity of battery electrode materials for their perforamnce optimization and is expected to inspire future structural design for battery materials beyond the one prototyped here.

25 ENERGY STORAGE↗
DOE OSTI2020

Accobeam - Acoustic Collimated Beam

Researchers at Los Alamos have developed a collimated acoustic imaging technology for non-destructive characterization of highly attenuating media, such as concrete, rocks, mud, and metal casings. The technology is used to investigate structural defects that could compromise important assets such as well boreholes, building structures and sensitive materials like explosives. Current acoustic methods are often unable to penetrate such materials deeply for more informative analysis, which limits what can be learned about asset structural integrity, crucial information companies require to make investment decisions such as fixing or replacing structures well before assets are completely compromised. ACCObeam provides requisite penetration and high-resolution acoustic imaging with applications in borehole imaging, explosives threat evaluation, and structural health evaluation. This technology will potentially save companies significant money by producing accurate and useful visual analyses to better understand the actual condition of assets in the field and respond accordingly. Los Alamos is searching for a collaboration partner to develop this technology for commercial applications that will lead to licensing opportunities for broad industry deployment.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Optimal interconnection of three-terminal tandem solar cells

Three-terminal (3T) tandem solar cells require an adapted module integration scheme in order to explore their full efficiency potential. The three terminals allow to extract the power of the top and bottom cell separately. In a cell string, the wide bandgap top cells are interconnected in parallel to multiple bottom cells resulting in a parallel/series interconnection. This interconnection scheme affects the operation of the subcells, the resulting current path between the subcells, the layout of the cell interconnects, and the system level. Here, we analyze by simulations and experiments the aspects of the module integration of series- and reverse-connected 3T cells with their practical impact on module processes and performance as well as the effect of varying voltage ratios on the string-end losses. If the subcells are connected in series, the module integration requires insulation layers and significantly longer interconnects compared to devices with reverse-connected subcells. Tandem devices with a reverse connection and a voltage ratio between top and bottom cell of 2:1 allow a lean interconnection design and low integration losses. Here, we present an approach for the integration of bypass diodes for the protection against shading effects that allow to minimize string-end and shading losses for a system of modules featuring 3T cells.

14 SOLAR ENERGY↗
DOE OSTI2021

Fast digital lossy compression for X-ray ptychographic data

Increases in X-ray brightness from synchrotron light sources lead to a requirement for higher frame rates from hybrid pixel array detectors (HPADs), while also favoring charge integration over photon counting. However, transfer of the full uncompressed data will begin to constrain detector design, as well as limit the achievable continuous frame rate. Here a data compression scheme that is easy to implement in a HPAD's application-specific integrated circuit (ASIC) is described, and how different degrees of compression affect image quality in ptychography, a commonly employed coherent imaging method, is examined. Using adaptive encoding quantization, it is shown in simulations that one can digitize signals up to 16383 photons per pixel (corresponding to 14 bits of information) using only 8 or 9 bits for data transfer, with negligible effect on the reconstructed image.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗