SEARCH · Engineering Papers

Results for “engine operability”

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.

SourceResearch connectionFrom yearThrough year

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

At least 901 records · Page 50

All sources NASA NTRS DOE OSTI

DOE OSTI2026

Hybrid Fuel Cell Systems for Heavy-Duty Trucks: Configuration, Heat Rejection, and Performance

Low-temperature polymer electrolyte membrane fuel cell systems can achieve higher efficiency than diesel engines, but heat rejection remains a major challenge in class-8 heavy-duty fuel cell trucks. For the same rated power, the radiator heat load is greater than that in a diesel engine, while the allowable operating temperatures are lower. This work proposes and evaluates 400 kWe fuel cell–battery hybrid (FCH) platforms and operating strategies that manage heat rejection without enlarging the radiator frontal area. Three FCH platforms are identified, each varying in fuel cell system (FCS) rated power, battery energy storage system (ESS) capacity, and maximum stack coolant exit temperature (T h1 ). All three satisfy key system and vehicle requirements, including 175 kWe FCS power at top sustained speed, 400 kWe FCH power on a 6% grade climb, a target stack power density (PD) of 750 mW e /cm 2 , and heat rejection constraints. The first FCH has the smallest FCS, the largest ESS, and a T h1 of 90 °C. The second achieves the highest PD of 840 mW e /cm 2 at a T h1 of 95 °C. The third has the largest FCS, the smallest ESS, and a T h1 of 102 °C. At a Th1 of 115 °C, the platform can be configured as a stand-alone 400 kWe(net) FCS without hybridization, but the achievable PD drops to 460 mW e /cm 2 .

25 ENERGY STORAGE↗

DOE OSTI2023

Code for BALDR Study 07.05 v.1.0.0

SAND2024-01293O The Code for BALDR Study 07.05 software reproduces results from the BALDR study concerning "A Semi-Supervised Learning Method to Produce Explainable Radioisotope Proportion Estimates for NaI-based Synthetic and Measured Gamma Spectra." The code for BALDR Study 07.05 can reproduce a scientific study following the step numbers within the file names. Using synthetic and measured data to find the best model for the radioisotope proportion estimation task of interest, the study generated results for inclusion in a paper. The high-level methods involved are neural networks, semi-supervised learning, and out-of-distribution detection. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Morrow, Tyler↗

DOE OSTI2024

pCubit

SAND2025-01894O pCubit is a software tool that can easily place particles or pores into a given geometry using desired statistics and the Poisson point process. It reduces the need for users to manually create complex geometry creation and placement. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Buche, Michael↗

DOE OSTI2022

statMechCrack

SAND2022-12599 O statMechCrack is a Python package providing an API to run calculations based on certain statistical mechanical models for cracks and crack growth. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Grutzik, Scott [Sandia National Lab. (SNL-CA), Liv↗

DOE OSTI2022

Polymer Modeling Library

SAND2022-12598 O The Polymer Modeling Library is a software package for modeling polymer chains, networks, and materials by applying existing theories and methods. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Buche, Michael [Sandia National Lab. (SNL-CA), Liv↗

DOE OSTI2021

System Modeling of the HTTR and Economic Dispatch Model of the Secondary System

High Temperature Gas-cooled Reactors (HTGRs) can be used for the generation of electricity and their process heat can be used to improve the efficiency of chemical processes such as hydrogen production. The JAEA-operated High-Temperature engineering Test Reactor (HTTR-GT/H2) is exploring using the reactor for electricity and hydrogen production. A RELAP5-3D model of the HTTR-GT/H2 secondary system has been developed using design information. The various components and heat exchangers in the secondary system were modeled and results were compared to the design conditions. The results for the sole-power generation mode were shown to fit the design conditions very well. The largest temperature difference was on the order of 7 K, and the largest pressure difference was on the order of 0.05 MPa. The results for the hydrogen cogeneration mode did not match the design conditions nearly as well. The largest temperature difference was about 39 K and the largest pressure difference was about 0.27 MPa at the compressor outlet. The larger differences for the hydrogen cogeneration mode are attributed to the various complex components and the flow being split in the secondary loop. A transient reduction in heat removal capability of the secondary system was investigated. Reactor temperatures are anticipated to rise as a result. The core reactivity response due to this increase in temperature is investigated and is expected to add negative reactivity to the reactor. An economic dispatch model was developed for a nuclear-driven iodine-sulfur cycle system to determine hydrogen sale prices that would make such a system profitable. The study focuses on the development of the economic model and the role that input data plays on final calculated values. It was found that the input electricity prices, whether using historical data or a host of synthetic time histories, produce significantly different breakeven hydrogen sale prices. As such, great care should be used in these economic dispatch analyses to select reasonable input assumptions.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2023

Thermal Analysis of Thermal Shield for PIP-II SSR1 Cryomodule

Fermilab's PIP-II project plans to enhance the onsite accelerator into the world's most intense neutrino beam, bringing Fermilab into the next generation of particle accelerators. The five different types of cryomodules are vital parts of the PIP-II project and each requires numerous engineering analyses to prove operation. For example, the thermal shield of the Single Spoke Resonator-1 (SSR1) cryomodule required a thermal analysis to ensure the design was operating as intended before fabrication commenced. The thermal shield is cooled by the supercritical helium inside of the extrusion and must remain between 45 and 80 Kelvin. The main purpose of the thermal shield is to intercept different high heat loads and thermal radiation and prevent them from reaching the more sensitive internal components. Finite Element Analysis (FEM) was used to determine temperature estimates of the thermal shield based on the location of a variety of heat sources. Results determined temperatures exceeding the design limit around the crucial component of the current leads. Due to superconducting properties, the areas around the current leads cannot surpass 68 Kelvin. Different solutions to the critical high-temperature areas will be proposed. These solutions range from changing the properties of the helium flow to designing an attachment for the thermal shield. Each proposition works as a viable solution, however, each proposition also has its own set of advantages and disadvantages that are described for further design consideration.

43 PARTICLE ACCELERATORS↗

DOE OSTI2025

Bridging the Gap Between Modern UX Design and Particle Accelerator Control Room Interfaces

Accelerator control systems often represent relatively complex and safety-sensitive human-machine interfaces within process control industries. These systems are technically robust and reflect the cumulative integration of solutions built and adapted across decades. One of the regular, unfortunate casualties of provisional accelerator control system updates is their human-system interfaces (HSIs) which often lag behind modern usability and design standards. An additional challenge is that although there is a multitude of established human factors (HF), and user experience (UX) principles for everyday digital applications, there are very few (if any) established principles for complex and safety-critical applications for an accelerator. This paper argues for the importance of established HF and UX principles (herein referred to as human-centered design principles) into the development of accelerator HSIs, emphasizing the need for clarity, consistency, responsiveness, and cognitive accessibility. Drawing from HF/UX best practices and human-centered design, this paper discusses how these approaches can enhance operator performance, reduce human error, and improve accelerator personnel collaboration. Case studies from Accelerator Control Operations Research Network (ACORN) at Fermilab are explored to demonstrate how interfaces built with human-centered design principles can scale with system complexity while remaining intuitive and efficient for diverse user roles including operators, machine experts, and engineers. By bridging the gap between traditional control system design and modern human-centered design methods, this paper provides a roadmap for evolving accelerator HSIs into more usable, maintainable, and effective tools.

Hill, Rachael [Idaho Natl. Lab.]↗

DOE OSTI2025

Risk-informed Graded Approach for Reliability and Performance Assessment of Machine Learning and Artificial Intelligence for Advanced Condition Monitoring Techniques

With the shift away from time-based maintenance and toward condition-based maintenance, and to reduce overall maintenance costs, there has been an upsurge in the usage and development of advanced condition monitoring (ACM) techniques for real-time monitoring of nuclear power plant (NPP) components. ACM is particularly useful in the development of digital twins, which are designed to predict the failure or degradation of plant components. Successful implementation of ACM requires an assessment to inform the development of a risk-informed approach to evaluate the use of ACM to meet Nuclear Regulatory Committee (NRC) regulations for in-service testing (IST) programs. This includes the monitoring and diagnostics of reactor components and systems in current, new, and advanced reactors. A key component in ACM is the usage of machine learning (ML) and artificial intelligence (AI) algorithms that can employ real-time data from instrumentation and sensors to detect and predict reactor component degradations. Such predictive capabilities enable early detection of component degradation so as to help plant personnel plan and execute necessary maintenance. For successful implementation of ML/AI in ACM such that regulatory requirements are met, a risk-informed graded approach is needed to assess the reliability and performance of ML/AI for ACM. The American Society for Mechanical Engineers (ASME) developed their Operations and Maintenance (O&M) Code to provide guidance on safe, reliable O&M of NPPs. The IST section of the O&M Code specifically establishes requirements for IST and examination to gauge operational readiness of components in water-cooled NPPs. This paper presents a state-of-the-art review of how reliability and risk assessment can be integrated with ACM to assess component performance by non-nuclear industries. This is followed by different methodologies and approaches for conducting performance and reliability assessments so as to meet IST requirements for NPP components.

97 - MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Risk-informed Graded Approach for Reliability and Performance Assessment for Advanced Condition Monitoring Techniques

99 - GENERAL AND MISCELLANEOUS↗

DOE OSTI2023

Proactive Intrusion Detection and Mitigation System

SAND2023-05661O The proactive intrusion detection and mitigation system (PIDMS) provides grid-edge situational awareness for cybersecurity defense by capturing real-time distributed energy resource (DER) network traffic and performance data with a novel approach that improves the detection and prevention of cyber-physical attacks. The PIDMS addresses the grid-edge security gap with real-time analysis of both network traffic and photovoltaic performance data to deliver a novel, cyber-physical intrusion detection system (IDS) approach that increases the accuracy and effectiveness of detection and mitigation. This hybrid IDS analysis enables dual monitoring that increases the workload of the adversary; both cyber and physical data would have to be simultaneously spoofed to evade detection. Furthermore, monitoring and analyzing cyber data are insufficient in some cases. For example, in an insider threat aimed at disrupting inverter grid-support functions where proper credentials and authentication are achieved, only the altered PV performance would indicate abnormal behavior. All in all, the PIDMS provides novel capabilities for: • Distributed, real-time cyber-physical detection and mitigation analysis • Cybersecurity defense for grid-edge systems • Analysis framework that can provide situational awareness across the transmission, distribution, and DER systems The PIDMS sensor is designed to collect cyber-physical data, process the data using machine-learning algorithms, detect abnormal events, and deploy mitigations. With these goals, the main functional PIDMS objectives are: • Capability to collect cyber-physical data • Onboard storage of cyber-physical data • Peer-to-peer communication • Computationally efficient machine-learning algorithms • Online cyber-physical data analysis • Alerting/visualization capabilities • Mitigation deployment capability with bump-in-the-wire (BITW) implementation Each of these functional objectives enable PIDMS to perform effective cyber-physical intrusion detection and mitigation. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Jones, Christian↗

DOE OSTI2022

GSAS Tools

SAND2023-06684O GSAS Tools is a web application that manages user access to modeling and simulation tools and promotional material. This software, which is a spiking neural network (SNN) simulator, represents an SNN as a graph of stochastic differential equations and simulates the time-evolution of these equations. It has the capability of reading inputs from file and writing outputs to file, and generally supports experimentation, analysis, and algorithm development using SNNs. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Noel, Todd↗

DOE OSTI2022

NIRP Core Software Suite v.5.1

SAND2023-06610O The Nuclear Incident Response Program (NIRP) Core Software Suite is a set of code that supports multiple applications. It includes miscellaneous base code for data objects, mathematic equations, and user interface components that are used for developing large applications, including those used for data management. Among the types of applications: • Analyst Manager is used for managing contact information, which is also often included in reports and identifies the owners of calculations. • Radionuclide Viewer provides access to the Dose Coefficient File Package (DCFPAK) radiological data, and it complements the Mixture Manager tool. • Mixture Manager creates and manages radionuclides mixtures that are commonly used in other applications. • High Explosive Manager manages explosives and properties. • Chart Viewer is used for data charts such as meteorology charts and other charts specific to data needs. • Unit Converter converts numeric values to/from different units. This package includes object-oriented base code such as data objects describing the date, time, and location of an event; weather conditions; data types that support predefined ranges of values; a unit library, and others. The package also includes mathematic equations such as determining the distance between two points; erf functions; factorial functions; incidence fractions of probit curves; and others. Other features are customized user interface components for text fields; unit selectors (combo boxes); menus; panels; bug-tracking; and automated checks for software updates. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Collins, Ian↗

DOE OSTI2023

Counter Unmanned Aircraft System Metrics Tool

SAND2023-05387O The Counter Unmanned Aircraft System (CUAS) Metrics Tool consists of three applications: • The Data Collection Tool is designed to be used during testing and captures details that can be imported into the Figure Creator application. • The Unmanned Aircraft System (UAS) Log Converter converts different UAS logs into a standardized hierarchical data format with a timeline of geospatial data. • The Figure Creator develops relevant images for the test event. The application includes logic to ingest and correlate data from the Data Collection Tool and the UAS Log Converter to produce the chosen figures. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Mayle, Ashley↗

DOE OSTI2023

Videoshare

SAND2023-05132O Videoshare is an application that allows users to communicate in a variety of ways, including voice, video, and text, over a local network without having to use a central server or an internet connection. The software features: • Screen-sharing and connecting to external IP cameras. • Ability to hold group calls on computers running the same software and network. • Ability to connect to other computers running the same software. • Curating potential connections and manually adding IP addresses to available connections. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

McIlraith, Aiden↗

DOE OSTI2023

Searchlight Source Code

SAND2024-01982O The Searchlight Source Code is software for creating, managing, and dismantling experiments. It also is a simple web server that mimics an online training module with scripts to automate a client. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Robinson, Matthew↗

DOE OSTI2023

FastACE

SAND2024-01893O The Fast Adaptive Cosine Estimator (FastACE) algorithm modifies the well-known Adaptive Cosine Estimator for target detection in hyperspectral imagery. Specifically, FastACE modifies the computation of the background precision matrix (C_b^-1) under a Vecchia approximation. That is, each spectral band, conditioned on a local neighborhood of bands around that band, is independent of the other spectral bands. The FastACE algorithm leverages a parameterizable, auto-regressive neighborhood for the conditional independence assumption. The underlying math used for computing detection scores is equivalent to ACE, but it is implemented within FastACE. The software implements a target detection algorithm and associated utilities for target detection in hyperspectral imagery. Provided with a hyperspectral image and corresponding target signature, it produces relevant background statistics and the corresponding detection scores for the target signature in the image. The software is designed to integrate into other end-user applications or processing. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

VanderLaan, John↗

DOE OSTI2023

Orca2

SAND2024-03236O Orca2 is a trajectory design and optimization code for constructing and solving problems numerically defined on homogeneous manifolds. Orca2 solves numerical trajectory design and optimization problems defined on Lie-type domains and operates primarily as a library requiring a user to write additional C++ code to leverage it. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Sparapany, Michael↗