Search NASA⌕ Search

SEARCH · Search NASA

Results for “maintainability systems”

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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Same Data, Different Audiences: Using Personas to Scope a Supercomputing Job Queue Visualization

Domain-specific visualizations sometimes focus on narrow, albeit important, tasks for one group of users. This focus limits the utility of a visualization to other groups working with the same data. While tasks elicited from other groups can present a design pitfall if not disambiguated, they also present a design opportunity—namely, the development of visualizations that support multiple groups. This development choice presents a trade-off of broadening the scope but limiting support for the more narrow tasks of any one group, which in some cases can enhance the overall utility of the visualization. We investigate this scenario through a design study where we develop Guidepost, a notebook-embedded visualization of data that helps scientists assess compute wait times, machine learning researchers understand prediction accuracy, and system maintainers analyze usage trends. We adapt the use of personas for visualization design from existing literature in the HCI and design domains, applying them to categorize tasks based on their uniqueness across stakeholder personas. Under this model, tasks shared between all groups should be supported by interactive visualizations and tasks unique to each group can be deferred to scripting with notebook-embedded visualization design. We evaluate our visualization through real-world case studies and a task-focused evaluation with nine participants. We observe that together, Guidepost's visual encodings, interactions, and export capabilities support the tasks of our differing personas.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Bayesian Optimization of Non-Invariant Systems with Constraints Developed for Application to the ECR Ion Source VENUS

In this work, we consider the optimization of non-invariant systems with both safety and control constraints. We present a new approach based on Bayesian optimization for the dynamic, safe and controlled optimization of such systems. Although there are other possible use cases, we focus on the application to the electron cyclotron resonance ion source VENUS. From experimental data, we have observed that VENUS behaves to first order as a non-invariant dynamic system with moving areas of instability. Our novel approach aims at providing a tool that can maintain system optimization in a safe way. This is accomplished by making sure the objective function, the beam current in the case of VENUS, does not fall under an operational minimum, while simultaneously requiring the optimization to avoid areas where VENUS is unstable. We compare the result of our approach on synthetic data modeled to mimic the behavior of VENUS with two methods from the literature, a standard Bayesian optimizer and a safe Bayesian optimizer, both adapted to deal with dynamic systems. A cross Student T-test is conducted to show the significance of the improvement given by the new method we introduce here, regarding the two preexisting methods we compared to. The results of the tests conducted on synthetic data show that the proposed method succeeds at maintaining the system optimized and obeys the predefined constraints better than the literature methods explored.

Bayesian optimization↗
DOE OSTI2024

Statistical Performance of Forced Oscillation Detectors in the Presence of Missing Measurements

In bulk power systems, measurement-based monitoring for large oscillations can help maintain system reliability. One of the challenges encountered in a recent field demonstration was the unavailability of measurements due to underlying measurement quality or communication problems. During the demonstration, the oscillation detector ignored a measurement location if even 10 seconds of data was missing. To extend the detector's ability to operate in these conditions, this paper evaluates the impact of three methods for addressing missing data. The strengths and weaknesses of each approach are evaluated using theoretical expressions for the probability of detection along with results from simulated data and publicly available field measurements. Based on these results, a suitable approach is identified that can extend the oscillation detector's performance when large segments of data are missing.

Follum, James D.↗
DOE OSTI2026

New measurement techniques for gear-changing research using DESIREE

In this work we cover some of the newer techniques developed to measure the effects of a gear changing system maintained in DESIREE at Stockholm University. Gear-changing is a collider synchronization method where two rings with different harmonic numbers in them maintain collisions through different velocities, pathlengths or a combination of the two. This system has been demonstrated using the low energy ion collider DESIREE at Stockholm university. We have not only continued our previous methods of studying the beam using a repeating pattern technique where one bucket in each ring is intentionally left empty, but we now also use recently installed pickups outside of the merger region to study the beams separately while they collide.

Accelerator Physics↗
DOE OSTI2025

Implementation and Demonstration of the Digital Twin Certification System Remote Operations Framework

Microreactors are one promising advanced-reactor concept being pursued by the nuclear industry. They are distinguished by a relatively low power output of 20 MWth or less. These microreactors are intended for deployment in applications where conventional small-capacity power solutions, such as diesel generators, are either economically unfeasible or logistically challenging. Such applications include providing electric power and/or heat for remote communities, mining sites, defense installations, and humanitarian and disaster-relief missions. An important feature for the successful deployment of microreactors is their capability to be operated remotely. This capability can significantly reduce staffing costs by eliminating the need for licensed operators to be physically present at each reactor site. Instead, operators can be centralized in a single remote operations center placed in an economically advantageous location, thereby optimizing resources by consolidating expertise and enhancing operational efficiency. However, the implementation of a remote operation system for nuclear reactors raises new concerns regarding the security, reliability, and resilience of such a system. One way in which remote operations can be supported in a manner that maintains system security, reliability, and resilience is through the use of digital twins in a novel framework designed to verify and validate sensor data and commands communicated between the remote operations center and reactor. This framework, known as the Digital Twin Certification System (DTCS), has previously been proposed as an operations architecture that can bring security and resiliency levels of remote nuclear-reactor operations to a level acceptable for commercial deployment. This paper moves the proposed DTCS architecture from concept to reality by presenting the implementation and testing of the system. The rationale and implementation of the DTCS using tools such as DeepLynx and Apache Airflow, is covered in-depth. This is followed by a demonstration of the DTCS by applying the implemented system architecture to the Single Primary Heat Extraction and Removal Emulator, a small-scale non-nuclear test bed that emulates thermal behavior of a microreactor. The demonstration includes both normal and abnormal operating scenarios to highlight how the DTCS can increase the security, reliability, and resilience of a remote operations system.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Implementation and Demonstration of the Digital Twin Certification System Remote Operations Framework

Microreactors are one promising advanced-reactor concept being pursued by the nuclear industry. They are distinguished by a relatively low power output of 20 MWth or less. These microreactors are intended for deployment in applications where conventional small-capacity power solutions, such as diesel generators, are either economically unfeasible or logistically challenging. Such applications include providing electric power and/or heat for remote communities, mining sites, defense installations, and humanitarian and disaster-relief missions. An important feature for the successful deployment of microreactors is their capability to be operated remotely. This capability can significantly reduce staffing costs by eliminating the need for licensed operators to be physically present at each reactor site. Instead, operators can be centralized in a single remote operations center placed in an economically advantageous location, thereby optimizing resources by consolidating expertise and enhancing operational efficiency. However, the implementation of a remote operation system for nuclear reactors raises new concerns regarding the security, reliability, and resilience of such a system. One way in which remote operations can be supported in a manner that maintains system security, reliability, and resilience is through the use of digital twins in a novel framework designed to verify and validate sensor data and commands communicated between the remote operations center and reactor. This framework, known as the Digital Twin Certification System (DTCS), has previously been proposed as an operations architecture that can bring security and resiliency levels of remote nuclear-reactor operations to a level acceptable for commercial deployment. This paper moves the proposed DTCS architecture from concept to reality by presenting the implementation and testing of the system. The rationale and implementation of the DTCS using tools such as DeepLynx and Apache Airflow, is covered in-depth. This is followed by a demonstration of the DTCS by applying the implemented system architecture to the Single Primary Heat Extraction and Removal Emulator, a small-scale non-nuclear test bed that emulates thermal behavior of a microreactor. The demonstration includes both normal and abnormal operating scenarios to highlight how the DTCS can increase the security, reliability, and resilience of a remote operations system.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Trust-Based Detection and Mitigation of Cyber Attacks in Distributed Cooperative Control of Islanded AC Microgrids

In this study, we address the challenge of detecting and mitigating cyber attacks in the distributed cooperative control of islanded AC microgrids, with a particular focus on detecting False Data Injection Attacks (FDIAs), a significant threat to the Smart Grid (SG). The SG integrates traditional power systems with communication networks, creating a complex system with numerous vulnerable links, making it a prime target for cyber attacks. These attacks can lead to the disclosure of private data, control network failures, and even blackouts. Unlike machine learning-based approaches that require extensive datasets and mathematical models dependent on accurate system modeling, our method is free from such dependencies. To enhance the microgrid’s resilience against these threats, we propose a resilient control algorithm by introducing a novel trustworthiness parameter into the traditional cooperative control algorithm. Our method evaluates the trustworthiness of distributed energy resources (DERs) based on their voltage measurements and exchanged information, using Kullback-Leibler (KL) divergence to dynamically adjust control actions. We validated our approach through simulations on both the IEEE-34 bus feeder system with eight DERs and a larger microgrid with twenty-two DERs. The results demonstrated a detection accuracy of around 100%, with millisecond range mitigation time, ensuring rapid system recovery. Additionally, our method improved system stability by up to almost 100% under attack scenarios, showcasing its effectiveness in promptly detecting attacks and maintaining system resilience. These findings highlight the potential of our approach to enhance the security and stability of microgrid systems in the face of cyber threats.

Computer Science↗
DOE OSTI2025

Early Research in Load-Following Management for HPC-Nuclear Integration

With the rising demand for high performance computing (HPC) and artificial intelligence (AI) systems, maintaining a stable and efficient power supply is increasingly critical. The HPC team at Idaho National Laboratory is spearheading efforts to seamlessly integrate HPC systems with nuclear reactors. This lightning talk explores one early strategy for managing power fluctuations using software-defined controls. To effectively harness nuclear reactors for power generation, control mechanisms are essential to address the slow load-following capabilities of reactors, which are typically around 5% per minute. While this rate is sufficient for many uses, large HPC systems can experience rapid power consumption changes by tens of megawatts when jobs start or stop running. A reactor could overproduce power and match the peak power rating for the HPC system, however when the system is not running a job or a job unexpectedly stops, the load-following of the system would be affected leading to power being wasted and the likelihood of power transient occurrences increases. Controlling the increase or decrease of power consumption on these systems at the same rate as the load-following of reactors is one piece of the puzzle to properly utilizing nuclear reactors as a power source for HPC systems.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Cooling Matters: Benchmarking Large Language Models and Vision-Language Models on Liquid-Cooled Versus Air-Cooled H100 GPU Systems

The unprecedented growth in artificial intelligence (AI) workloads, recently dominated by large language models (LLMs) and vision-language models (VLMs), has intensified power and cooling demands in data centers. This study benchmarks LLMs and VLMs on two HGX nodes, each with 8× NVIDIA H100 graphics processing units (GPUs), using liquid and air cooling. Leveraging GPU Burn, Weights & Biases, and IPMItool, we collect detailed thermal, power, and computation data. Results show that the liquid-cooled systems maintain GPU temperatures between 41-50$^\circ$C, while the air-cooled counterparts fluctuate between 54-72$^\circ$C under load. This thermal stability of liquid-cooled systems yields 17% higher performance (54 TFLOPs/ GPU vs. 46 TFLOPs/GPU), performance-per-watt, reduced energy overhead, and greater system efficiency than the air-cooled counterparts. These findings underscore the energy and sustainability benefits of liquid cooling, offering a compelling path forward for hyperscale data centers seeking to optimize AI infrastructure. https://github.com/iscaas/Cooling-Matters.

Latif, Imran↗
DOE OSTI2024

Grand challenges of wind energy science – meeting the needs and services of the power system

The share of wind power in power systems is increasing dramatically, and this is happening in parallel with increased penetration of solar photovoltaics, storage, other inverter-based technologies, and electrification of other sectors. Recognising the fundamental objective of power systems, maintaining supply–demand balance reliably at the lowest cost, and integrating all these technologies are significant research challenges that are driving radical changes to planning and operations of power systems globally. In this changing environment, wind power can maximise its long-term value to the power system by balancing the needs it imposes on the power system with its contribution to addressing these needs with services. A needs and services paradigm is adopted here to highlight these research challenges, which should also be guided by a balanced approach, concentrating on its advantages over competitors. The research challenges within the wind technology itself are many and varied, with control and coordination internally being a focal point in parallel with a strong recommendation for a holistic approach targeted at where wind has an advantage over its competitors and in coordination with research into other technologies such as storage, power electronics, and power systems.

17 WIND ENERGY↗
DOE OSTI2025

Ensuring electromagnetic compatibility in grid-connected power converters: Challenges, standards, and compliance strategies

In today's rapidly advancing world, electronic devices and systems are fundamental to a wide range of industries, including renewable energy and global telecommunications infrastructure. However, as these devices become more complex and widespread, the risk of electromagnetic interference (EMI) also increases, underscoring the importance of stringent Electromagnetic Compatibility (EMC) requirements for maintaining system integrity. This paper addresses the specific challenges associated with grid-connected power converters (GCPCs), which are critical in integrating renewable energy into existing power grids. It explores the complexities of EMI in the context of GCPCs, particularly given the recent emergence of tailored EMC standards for these systems. The paper also highlights the shortcomings of applying generic or unrelated standards to GCPCs, often leading to inadequate compliance and testing protocols. Through a detailed analysis of existing standards and recent advancements in product-specific EMC requirements, this paper provides a comprehensive overview of the current landscape, offering guidance to stakeholders on navigating the intricate EMC compliance landscape, with a focus on methodologies, testing procedures, and the evolving regulatory environment for GCPCs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Verification of Adaptive Protection in Hardware in the Loop for Coordination with Solar Variability

As inverter-based resources continue to be installed at all levels of the electric grid, the fixed protection schemes used at the distribution level will continue to be stressed until they no longer ensure the protection of the grid. Adaptive protection has been proposed as a solution with the ability to update the protection schemes in near real-time to ensure reliability and increase the resilience of the grid. However, weather variability poses a significant challenge to the ability of these methods to keep the selectivity and reliability of these schemes coordinated. If the ramp rates, due to solar variability, of the inverter-based resources change faster than the adaptive protection can issue new settings, the protection system could be uncoordinated, with the wrong device responding to a system fault. The proposed adaptive protection method ensures that due to solar variability, communication, and protection calculation latency, it can issu e coordinated protection settings promptly, in one minute or less. The hardware-in-the-loop results show the protection settings being issued and maintaining system coordination in under a minute.

Summers, Adam↗
DOE OSTI2026

Low-voltage syngas synthesis via BPM electrolysis of CO 2 capture and aldehyde solution

A bipolar membrane electrolyzer coupling bicarbonate electrolysis with formaldehyde oxidation directly produces syngas (H 2 : CO = 1) at 1.7 V and 200 mA cm −2 with 200% combined Faradaic efficiency. We demonstrate an electrochemical syngas production platform that couples bicarbonate electrolysis with formaldehyde oxidation in a bipolar membrane electrode assembly. This strategy doubles syngas (CO + H 2 ) throughput compared to conventional CO 2 electrolysis by generating CO at the cathode and H 2 at the anode. The system achieves a full-cell voltage of 1.7 V while operating at an industrially relevant current density of 200 mA cm −2 . The system maintained a combined Faradaic efficiency of 200% over 8 hours. The process produces syngas with a 1 : 1 H 2 : CO ratio, aligning with downstream requirements for Fischer–Tropsch synthesis. We further investigated how Cu anode active sites and electrolyte composition affect formaldehyde oxidation activity. Our integrated electrolytic system reduces levelized energy by 45–61% relative to conventional electrochemical syngas production platforms.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Small-Signal Stability Constrained Optimal Power Flow of Inverter-Dominated Power Systems with Flexible Operation Mode Selection

Given the intermittence and low inertia nature of inverter-based resources (IBRs), modern power systems with high penetration of IBRs challenge the conventional optimal power flow (OPF) analysis and the system may experience unexpected failures if stability constraints are not incorporated. This study proposes a small-signal stability-constrained OPF (SSSC-OPF) with flexible operation mode selection between grid-forming (GFM) and grid-following (GFL) modes for IBRs to address these challenges. The approach aims to maintain system stability with a sufficient stability margin while minimizing operation costs. The effectiveness of the proposed method is validated through extensive case studies on the IEEE 14-bus system. The results demonstrate that the proposed method is able to support system-level power flow analysis, reduce generation costs, and ensure stability under various disturbances.

grid-following↗
DOE OSTI2026

Intelligent Experiments through Real-Time AI: Fast Data Processing and Autonomous Detector Control for High-Energy Nuclear Experiments

The aim of this project is to develop software and hardware for fast real-time data processing and autonomous detector control and calibration for the sPHENIX and the future EIC experiments. Below summarizes Georgia Tech team efforts in the past year: 1. We developed a real-time clustering algorithm and FPGA-based pipeline architecture for processing fired pixel data from ALPIDE sensors in sPHENIX experiments. Our Columnar Clustering Co-Design introduces a hardware-aware, stream-friendly approach that segments pixel data by column pairs using a Column Pair Clustering (CPC) strategy, followed by Cluster Stitching to merge adjacent subclusters. Implemented in Vitis HLS, the pipeline comprises five stages—read-in, subclustering, stitching, analysis, and write-out—connected by tagged HLS streams with custom end-of-event signaling for robust synchronization. We designed a pipelined dataflow model optimized for throughput, low latency, and minimal buffering, enabling scalable clustering across events of arbitrary size. Our system maintains spatial precision via center-of-mass and shape key extraction and efficiently handles edge cases such as fragmented or nested clusters. Compared against DBSCAN in both software and hardware, our approach demonstrates competitive performance under FPGA constraints. 2. We also conducted a comprehensive algorithm-to-hardware co-design of connected component analysis tailored for sPHENIX experiments, focusing on real-time, low-latency processing using FPGAs and High-Level Synthesis (HLS). Starting from a Python-based particle tracking pipeline, the team translated the core logic—graph traversal via DFS and Union-Find—into an HLS-compatible C++ model, replacing dynamic memory and recursion with static arrays and pipelined control flow. The final design includes a fully streamed and dataflow-compatible Union-Find kernel optimized across five iterations, incorporating loop pipelining, array partitioning, AXI/FIFO interface tuning, and function flattening. Experimental results show up to 14.8× speedup over the CPU baseline, reducing per-graph latency to 1.58 μs and demonstrating strong resource efficiency with only ~7k LUTs and zero BRAM usage. The design maintains functional correctness against the Python reference using a Python-based C-simulation framework and Mean Squared Error metrics. This work validates the potential of HLS-driven FPGA designs for edge-level HEP data acquisition, laying a scalable foundation for future integration with real-time detector pipelines and multi-graph processing systems.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Secure and Privacy Aware Data Sharing Approach for Smart Electric Vehicles

The integration of smart electric vehicles (SEVs) into smart cities marks a significant step toward creating efficient, sustainable, and connected urban spaces. However, secure and private data sharing is a major challenge as SEVs connect with smart city systems. The interaction between SEVs and consumer electronic devices (CEDs) raises serious concerns about data security and privacy. Here, to address these challenges, this article presents how blockchain technology and federated learning (FL) can address these issues. The proposed approach provides a secure and privacy-aware framework for data exchange between SEVs and CEDs in smart cities. The experiment results demonstrate the effectiveness of the proposed framework for secure data sharing and maintaining system reliability in smart city environments. It also enables trust and promotes the widespread adoption of interconnected urban technologies.

Das, Debashis [Meharry Medical College, Nashville,↗
DOE OSTI2026

A State-Space Model for Stability Boundary Analysis of Grid-Following Voltage Source Converters Considering Grid Conditions

With the growing significance of renewable energy resources and energy storage systems, the number of grid-connected inverters has been rising at an increasingly rapid pace. Generally, these inverters are directly integrated with the distribution network by synchronizing with the grid voltage at the point of common coupling. However, the low grid strength and varying R/X ratios, as the common characteristics of most distribution networks or weak grids, can lead to dynamic interactions that comprise stability and limit the power transfer capacity of grid-connected inverters. To ensure stable operation of the inverters, researchers must determine the stability boundary, described as the maximum power transfer capacity of grid-connected inverters under the premise of maintaining system small-signal stability. For this purpose, we propose to formulate a state-space model of the system in the synchronously rotating dq-frame of reference and perform eigenvalue analysis to determine the stability boundary. With a detailed model of the control structure and parameters of the grid-connected inverters, the stability boundary is identified as a surface with respect to different grid strengths and R/X ratios. Case study results of proposed eigenvalue analysis are compared with those of admittance model-based stability analysis as well as time-domain simulation using a switching model in Matlab/Simulink, validating the effectiveness and accuracy of the proposed eigenvalue analysis for stability boundary identification.

grid-connected inverters↗
DOE OSTI2025

Reduced soil diazotroph diversity decreases nitrogen fixation rates, but depends on land management

Soil diazotrophs convert atmospheric nitrogen into plant-available ammonium through free-living nitrogen fixation (FLNF). This sustainable nitrogen source can reduce our dependence on synthetic fertilizer inputs in conventional agricultural systems. However, we know little about the effect of diazotroph diversity on FLNF, especially given that FLNF is intermediate within the broad-narrow functional spectrum. Here, we determined how management-mediated shifts in diazotroph diversity would impact their ecosystem function (FLNF) by quantifying diazotroph diversity across a long-term management gradient during and after the growing season. In addition to field observations, we leveraged the same management gradient to manipulate diversity in soil microcosms via chloroform fumigation exposure. In the field, diazotroph diversity was significantly higher after the growing season, and the biologically-based annual cropping system harbored the highest diazotroph diversity. However, perennial cropping systems maintained the highest FLNF despite lower diazotroph diversity, and both soil moisture and temperature were stronger predictors of FLNF. Based on these results, integrating diverse perennial crops into agricultural landscape could result in greater N from FLNF, particularly at the end of the growing season. When we reduced biodiversity in a manipulation experiment, the diversity-FLNF association was stronger than in the field experiment, suggesting that FLNF communities are not as functionally redundant as taxonomically ‘broad’ ecosystem functions. Here, the strength of diversity-FLNF correlation varied by previous land management. Diazotroph diversity better predicted FLNF in annual and forest soil microcosms, and microbial biomass carbon better predicted FLNF in perennial soil microcosms. Taken together, our results show that while diazotroph diversity influences FLNF, especially under extreme environmental disturbances, abiotic factors like soil moisture and temperature are stronger constraints on FLNF in the field.

60 APPLIED LIFE SCIENCES↗