Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Reliability”

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 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Reliability comparisons between additively manufactured and conventional SiC–Si ceramic composites

Abstract An additively manufactured reaction‐bonded silicon carbide ceramic composite is fabricated using a bimodal powder feedstock and the binder‐jetting printing technique. On fabricating, the ceramic is investigated to report its composition, mechanical, and thermal properties at room temperature and high temperatures (up to 750). The ceramic has a density of 2.76 g/cc, and shows a hardness of 21.74 GPa, and a flexure strength of 207.5 MPa at room temperature. The mechanical property of flexure strength is used to estimate its failure probability under applied stress, using a Weibull distribution. The mechanical properties and failure probabilities are compared with those of conventionally fabricated reaction‐bonded silicon carbide ceramics reported in the literature. These ceramics were fabricated using methods such as slip‐casting, compacting, and tape‐casting. The comparison is used to elucidate the advantages and areas of improvement of the present additive manufacturing technique for reaction‐bonded ceramics.

14 SOLAR ENERGY↗
DOE OSTI2020

Development and evaluation of a Novel RT‐PCR system for reliable and rapid SARS‐CoV ‐2 screening of blood donations

Abstract Background The ongoing outbreak of severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) has caused great global concerns. In contrast to SARS, some SARS‐CoV‐2–infected people can be asymptomatic or have only mild nonspecific symptoms. Furthermore, there is evidence that SARS‐CoV‐2 may be infectious during an asymptomatic incubation period. With the discovery that SARS‐CoV‐2 can be detected in plasma or serum, blood safety is worthy of consideration. Study Design and Methods We developed a nucleic acid test (NAT) screening system for SARS‐CoV‐2 targeting nucleocapsid protein (N) and open reading frame 1ab (ORF 1ab) gene that could screen 5076 samples every 24 hours. The 2019 novel coronavirus RNA standard was used to evaluate linearity of standard curves. Diagnostic sensitivity and reproducibility were evaluated using artificial SARS‐CoV‐2. Specificity was evaluated with 61 other respiratory pathogens. Diagnostic performance was evaluated by testing two sputum and nine oropharyngeal swab specimens. The reverse transcription polymerase chain reaction (RT‐PCR) assay was used to screen SARS‐CoV‐2 RNA in blood donor specimens collected during the outbreak of SARS‐CoV‐2 in Chengdu. Results Limits of detection of the SARS‐CoV‐2 RT‐PCR assay for N and ORF 1ab gene were 12.5 and 27.58 copies/mL, respectively. Intra‐assay and interassay for the SARS‐CoV‐2 RT‐PCR assay based on cycle threshold were acceptably low. No cross‐reactivity was observed with other respiratory virus and bacterial isolates. The overall agreement value between the SARS‐CoV‐2 RT‐PCR assay and clinical diagnostic results was 100%. A total of 16 287 blood specimens collected from blood donors during SARS‐CoV‐2 surveillance were tested negative. Conclusions A high‐throughput NAT screening system was developed for SARS‐CoV‐2 screening of blood donations during the outbreak of SARS‐CoV‐2.

Li, Meng↗
DOE OSTI2020

System-Level Thermal Management and Reliability of Automotive Electronics: Goals and Opportunities Using Phase-Change Materials

Abstract Electronic packaging for automotive applications are at particular risk of thermomechanical failure due to the naturally harsh conditions it is exposed to. With the rise of electric and hybrid electric vehicles (EVs and HEVs), combined with a desire to miniaturize, the challenge of removing enough heat from electronic devices in automotive vehicles is evolving. This paper closely examines the new challenges in thermal management in various driving environments and aims to classify each existing cooling method in terms of performance. Particular focus is placed upon emerging solutions regarded to hold great potential, such as phase-change materials (PCMs). PCMs have been regarded for some time as a means of transferring heat quickly away from the region with the electronic components and are widely regarded as a possible means of carrying out cooling in large scale from small areas, because of their high latent heat of fusion, high specific heat, temperature stability, and small volume change during phase change, etc. They have already been utilized as a method of passive cooling in electronics in various ways, but their adoption in automotive power electronics, such as in traction inverters, has yet to be fulfilled. A brief discussion is made on some of the potential areas of application and challenges relating to more widespread adoption of PCMs, with reference to a case study using computational model of a commercially available power module used in automotive applications.

Engineering↗
DOE OSTI2021

Performance and reliability of β-Ga 2 O 3 Schottky barrier diodes at high temperature

Beta-gallium oxide (ß-Ga 2 O 3 ) is an ultrawide bandgap semiconductor that has potential for power electronic applications and devices operating at high temperatures. Particularly important for these applications are its 4.9 eV bandgap, facile electron doping, and the ability to grow ß-Ga 2 O 3 crystals from the melt. In this work, vertical ß-Ga 2 O 3 Schottky barrier diodes were fabricated using Pt Schottky and Ti-based Ohmic contacts and Au contact pads on unintentionally doped n-type, (2¯01)-oriented single crystal substrates. The diode’s temperature-dependent electrical properties up to 400°C were investigated, and the Pt/Ga 2 O 3 Schottky barrier height was determined to be close to 1.2 eV. The degradation of the contacts over multiple cycles up to 400°C was observed, resulting in a significant increase in series resistance of the diodes by 1000× at ambient temperature after they were cycled. According to electron microscopy measurements, this degradation is likely due in part to the migration and oxidation of Ti at the top surface of the Au contact pads. This degradation highlights the need for further research and development to ensure stable Ohmic and Schottky contacts to Ga 2 O 3 at temperatures above 400°C.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Grid Reliability Statistics [SWR-25-45]

This codebase houses a suite of statistical and descriptive analyses of NERC GADS data of interest to grid modelers and planners. This repository is envisioned to house a collection of statistical and descriptive summaries of NERC GADS data, particularly summaries that on their own might be insufficient to warrant publication. In addition, it is intended to disseminate results rather than to enable reproduction as GADS is non-public.

Murphy, Sinnott [National Renewable Energy Laborat↗
DOE OSTI2023

First-Order Individual Gas Sensors as Next Generation Reliable Analytical Instruments

It is conventionally expected that the performance of existing gas sensors may degrade in the field compared to laboratory conditions because (i) a sensor may lose its accuracy in the presence of chemical interferences and (ii) variations of ambient conditions over time may induce sensor-response fluctuations (i.e., drift). Breaking this status quo in poor sensor performance requires understanding the origins of design principles of existing sensors and bringing new principles to sensor designs. Existing gas sensors are single-output (e.g., resistance, electrical current, light intensity, etc.) sensors, also known as zero-order sensors (Karl Booksh and Bruce R. Kowalski, Analytical Chemistry, DOI: 10.1021/ac00087a718). Any zero-order sensor is undesirably affected by variable chemical background and sensor drift that cannot be distinguished from the response to an analyte. To address these limitations, we are developing multivariable gas sensors with independent responses, which are first-order analytical instruments. Here, we demonstrate self-correction against drift in two types of first-order gas sensors that operate in different portions of the electromagnetic spectrum. Our radiofrequency sensors utilize dielectric excitation of semiconducting metal oxide materials on the shoulder of their dielectric relaxation peak and achieve self-correction of the baseline drift by operation at several frequencies. Our photonic sensors utilize nanostructured sensing materials inspired by Morpho butterflies and achieve self-correction of the baseline drift by operation at several wavelengths. These principles of self-correction for drift effects in first-order sensors open opportunities for diverse emerging monitoring applications that cannot afford frequent periodic maintenance that is typical of traditional analytical instruments.

Potyrailo, Radislav A.↗
DOE OSTI2026

Dataset for Top Model Decision Tree: Selecting Segmentation Models for Reliable Quantitative Analysis in Low- and Ultralow-Dose CryoEM

Motivation Multiple deep learning model architectures can be used to segment bacterial membranes in cryoEM images. However, an AI-based tool advancement is often presented with only a single segmentation model for broad use, and this single model may show inconsistent results across datasets from different users. Here, we present the Top Model Decision Tree, a model screening framework to screen for the best model to generate bacterial inner and outer membrane masks based on user priorities. We use pre-trained segmentation models from YOLOv11, YOLO26, U-Net, Detectron2 and SAM3 fine-tuned on bacterial inner and outer membranes imaged with cryoEM. Run the Framework This notebook must be opened in Google Colab. Mount Google Drive and run with a GPU-based runtime. Open the notebook and follow steps to git clone in folders and files within this repository. There will be a repeating top_model_decision_tree.ipynb (notebook clone) that will not be used. Save your .png binary mask files and .csv table outputs within your Google Drive or download before closing the notebook. The models and all analysis/training scripts are available at [GitHub: https://github.com/Lynnicia/CryoEM_membranes_top_model_decision_tree and https://github.com/Sireesiru/Semantic-Segmentation-of-bacterial-cell-envelope-using-U-Nets.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Digital risk analysis in nuclear engineering projects: Designing for safety, performance, reliability, and security

Cyber-informed engineering and security-by-design frameworks are important in promoting the need to identify cybersecurity concerns early in the systems engineering lifecycle so risks from adversarial cyber-attacks can be eliminated or reduced through engineering design practices. In addition to adversarial risk, risk in operational technology systems also includes non-adversarial and unintentional risk from other factors such as human performance errors, environmental conditions, design flaws, and device degradation or failure. This paper introduces a new concept for characterizing digital risk, both adversarial and non-adversarial, and provides the basis for initial research into a novel digital risk analysis approach focused on incorporating attack difficulty into a multi-attribute analysis technique using robust decision-making. This digital risk characterization is also used to frame a discussion on the challenges of competing objectives and competing stakeholder requirements in an integrated energy system project that incorporates a small modular reactor and industrial facility.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Spot-Checking for Reliable Quantum Communications

We demonstrate a spot-checking approach for real-time drift estimation and mitigation in continuously operating quantum links. Using polarization-entangled photon pairs, we achieve stable 16-hour operation, validating efficient, minimally invasive monitoring of quantum-network performance.

Zhang, Yanbao [ORNL] (ORCID:0000000245530561)↗
DOE OSTI2020

Integration of phage and yeast display platforms: A reliable and cost effective approach for binning of peptides as displayed on-phage

Hundreds of target specific peptides are routinely discovered by peptide display platforms. However, due to the high cost of peptide synthesis only a limited number of peptides are chemically made for further analysis. Here we describe an accurate and cost effective method to bin peptides on-phage based on binding region(s), without any requirement for peptide or protein synthesis. This approach, which integrates phage and yeast display platforms, requires display of target and its alanine variants on yeast. Flow cytometry was used to detect binding of peptides on-phage to the target on yeast. Once hits were identified, they were synthesized to confirm their binding region(s) by HDX (Hydrogen deuterium exchange) and crystallography. Moreover, we have successfully shown that this approach can be implemented as part of a panning process to deplete non-functional peptides. This technique can be applied to any target that can be successfully displayed on yeast; it narrows down the number of peptides requiring synthesis; and its utilization during selection results in enrichment of peptide population against defined binding regions on the target.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Accelerating Control Systems with GitOps: A Path to Automation and Reliability

GitOps is a foundational approach for modernizing infrastructure by leveraging Git as the single source of truth for declarative configurations. The poster explores how GitOps transforms traditional control system infrastructure, services and applications by enabling fully automated, auditable, and version-controlled infrastructure management. Cloud-native and containerized environments are shifting the ecosystem not only in the IT industry but also within the computational science field, as is the case of CERN and Diamond Light Source among other Accelerator/Science facilities which are slowly shifting towards modern software and infrastructure paradigms. The ACORN project, which aims to modernize Fermilab’s control system infrastructure and software is implementing proven best-practices and cutting-edge technology standards including GitOps, containerization, infrastructure as code and modern data pipelines for control system data acquisition and the inclusion of AI/ML in our accelerator complex.

Gonzalez, M. [Fermilab]↗
DOE OSTI2022

Challenges to Reliable Production Nitrogen Doping of Nb for SRF Accelerating Cavities

Over the last several years, alloying of the surface layer of niobium SRF cavities has been demonstrated to beneficially lower the superconducting RF surface resistance. Nitrogen, titanium, and oxygen have all been demonstrated as effective alloying agents, occupying interstitial sites in the niobium lattice within the RF penetration depth and even deeper, when allowed to thermally diffuse into the surface at appropriate temperatures. The use of nitrogen for this function has been often termed ’nitrogen doping’ and is being applied in the LCLS-II and LCLS-II HE projects. We report characterization studies of the distribution of nitrogen into the exposed niobium surface and how such distribution is affected by the quality of the vacuum furnace environment in which the doping takes place, and the complexity of nitride crystal growth on different grain orientations of surface niobium. Using state-of-the-art quantification methods by dynamic secondary ion mass spectrometry (SIMS) depth profiling in niobium, we identify several phenomena involving furnace-sourced contamination. We also highlight a potential issue with N₂ flow constraints from the flange ’caps’ used during heat treatments.

Reece, Charles↗
DOE OSTI2020

Developing Flexible, Networked Lighting Control Systems That Reliably Save Energy in California Buildings

An important strategy to meet California's ambitious energy efficiency goals is to use innovative wireless communications, embedded sensors, data analytics and controls to significantly reduce lighting energy use in commercial buildings. This project developed a suite of networked lighting solutions to further this goal. The technologies include a platform for low-cost sensing, distributed intelligence and communications, the “PermaMote,” which is a self-powered sensor and controller for lighting applications. The project team also developed a task ambient daylighting system that integrates sensors with data-driven daylighting control using an open communication interface, called the “Readings-At-Desk” (RAD) system. To address the problem of building occupants being confused about how to operate traditional lighting control systems, the research team created content that could be the basis for a user interface standard for lighting controls. Finally, to address the difficulty of ensuring that advanced lighting control systems actually deliver their promised energy savings, the project team developed a new method for evaluating and specifying lighting systems’ performance. The research team validated these technologies in the laboratory, showing significant lighting energy savings, up to 73% for the PermaMote sensor system from occupancy control and daylight dimming features, compared to the same light source (LED replacement lamps) operated via simple on/off scheduling. The project team also developed a proposed standard lighting data model and user interface elements, which were contributed to the ANSI Lighting Systems Committee (C137) for standardization. Existing data models are incomplete and inconsistent, whereas the lighting-specific data model developed here is clear and comprehensive, to serve as a starting point for creating common, universally agreed upon semantic definitions of key lighting parameters, to promote interoperability. For the task on verifiable performance of lighting systems, the project team developed a more effective metric for capturing the actual energy impact of a lighting system over time — the energy usage intensity (kWh/ft2/year). Three commercial lighting systems were tested in FLEXLAB® using this new metric, and the tests show a wide range in the accuracy of the self-reported energy-use metric, from 0.5% to 28% error compared to direct measurement of lighting energy using dedicated submeters. Overall, the project team estimates that these advanced technologies can reduce California office lighting energy use by 20% (above and beyond normal advanced lighting controls mandated by Title 24), resulting in about 1,600 GWh/year in savings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Multi-Gas Sensors for Enhanced Reliability of SOFC Operation

GE Research, in partnership with SUNY Polytechnic Institute (SUNY Poly), designed, built, and tested gas sensors for in situ monitoring of H 2 and CO anode tail gases produced with on-site steam reforming in solid oxide fuel cell (SOFC) systems. The knowledge of the H 2 /CO ratio of these anode tail gases should allow accurate determination and control of the efficiency of the reforming process in the SOFC system and should deliver a lower operating cost for SOFC customers. The project objectives were to achieve multi-gas monitoring capability with a single multivariable sensor, and to sustain this performance in the presence of gaseous interferences and a potential poison for the sensor. The duration of the project was 24 months with the project structure that included three technical tasks such as (1) development of design rules of photonic nanostructures for H 2 and CO gas detection, (2) laboratory validation of photonic nanostructures for selective H 2 and CO gas detection, and (3) validation of photonic nanostructures for initial stability and poison-resistance against H 2 S. To build multivariable sensors for selective H 2 and CO gas detection in the presence of interferences, we expanded our earlier knowledge of multi-gas sensors into new fabrication and functionalization methodologies as well as into new methodologies for the spectral data analysis of multi-gas responses. We have advanced our design rules of the three-dimensional (3D) photonic nanostructures that allowed detection of H 2 and CO at high temperatures as individual gases and as their mixtures and rejection of interferences such as CO 2 , H 2 O, CH 4 , and other hydrocarbons for SOFC applications. Our advanced design rules should be attractive for building the new generation of cost-effective industrial sensors. Stability and poison resistance of our 3D photonic nanostructures was tested in the laboratory conditions. While initially we utilized conventional machine learning data analysis tools, we have found that they were unable to correct for the sensor drift. Thus, we have implemented new methods of machine learning for the analysis of our spectral data. These learnings pave the way to move the future studies into advanced testing of effects of interferences, aging and field tests. In future, our work will continue to advance our sensing designs to operate in conditions with known and unknown interferences by implementing nanostructures with enhanced spectral diversity of responses to gaseous species of interest and interferences. Our systematic reduction of technical risks in this completed project and in future studies will ensure transition of this sensing technology to commercialization.

03 NATURAL GAS↗