Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Reliability assessment”

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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Integrated Approach to Ancillary PV Component Reliability Assessment (Final Report)

In this project, we have established a nondestructive, generalized methodology that (1) fuses rich field data with advanced ML for proactive reliability forecasting, (2) dramatically reduces experimental iterations via synthetic dataset generation, and (3) achieves unprecedented regression precision in both anomaly detection and component-level degradation assessment—paving the way for truly predictive maintenance of grid-tied PV inverters under diverse outdoor conditions.

14 SOLAR ENERGY↗
NASA NTRS2024

NASA Methodology for Physics of Failure-Based Reliability Assessments Handbook

At the intersection of mission, technology, and place is NASA’s need to modernize for a digital-forward future. Therefore, NASA’s Reliability & Maintainability (R&M) Enterprise Data Sharing team is working to leverage both Digitization and Digital Transformation to develop and share best practices and methodologies across NASA. One such cutting edge methodology is Physics of Failure. Therefore NASA OSMA's R&M office is developing a Reliability Physics of Failure Handbook in order to keep our engineers current and on the cutting edge of analysis methodologies to help ensure NASA’s optimize and achieve continued success.

Reliability Engineering↗
DOE OSTI2026

Incorporating Local Extreme Weather Events into Reliability Assessments

Presentation discussing modeling extreme weather effects on the Bulk power system. Using a Production cost model to analyze weather related demand increases, generator outages, transmission outages, and fuel supply constraints. These results can be analyzed to inform on system reliability effects of extreme weather. This presentation was developed for the 2026 NERC Probabilistic Assessment Forum at EPRI in Charlotte NC.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Assessing the Reliability Benefits of Energy Storage as a Transmission Asset

Utilizing energy storage solutions to reduce the need for traditional transmission investments has been recognized by system planners and supported by federal policies in recent years. This work demonstrates the need for detailed reliability assessment for quantitative comparison of the reliability benefits of energy storage and traditional transmission investments. First, a mixed-integer linear programming expansion planning model considering candidate transmission lines and storage technologies is solved to find the least-cost investment decisions. Next, operations under the resulting system configuration are simulated in a probabilistic reliability assessment which accounts for weather-dependent forced outages. The outcome of this work, when applied to TPPs, is to further equalize the consideration of energy storage compared to traditional transmission assets by capturing the value of storage for system reliability.

co-optimization↗
DOE OSTI2025

Computational materials reliability assessment of hydrogen fueled gas turbine power generation engines

The use of blended fuel sources in land based gas turbine engines drives variations in the resulting operational profile (temperatures and pressures) which can impact engine reliability. Furthermore, variability in the manufacture of components affects the resulting microstructure which directly impacts material performance and reliability. Currently, data-driven models are typically used for maintaining and inspecting fleets of engines. Without explicitly capturing material and operational sources of variability conservatism must be used in developing component-level reliability models. Therefore, there exists an opportunity to use information from materials-scale physics models to better inform reliability modeling and reduce conservatism; the impact is more cost-efficient operation and maintenance of current and future fleets. Specifically, this work establishes a computational framework for evaluating the probabilistic high temperature creep performance of hot-section Ni-based superalloys where uncertainty comes from both microstructural and operational variability. A novel high-fidelity physics model which phenomenologically captures grain-boundary sensitive phenomena has been established. A probabilistic calibration procedure was used to calibrate the model and capture uncertainty in the parameterized model coefficients. A design of experiments methodology was established for identifying informative microstructural digital representations for suitable for forward model evaluation. Results show that training a machine-learning surrogate using this design criteria outperforms random selection of microstructural representations. Finally, two surrogate models were developed: (1) a deterministic surrogate model which predicts the local field response given microstructure, constitutive model parameters, and operating conditions (stress, temperature) and (2) a probabilistic model, where uncertainty comes from constitutive law uncertainty, built using denoising diffusion probabilistic models which samples responses given (1) microstructure and (2) operating conditions. These surrogate models enable partner Siemens Energy to rapidly perform UQ analysis specific to creep deformation across a range of microstructures and operating conditions. The impact is that these ML and physics codes can be used to establish more advanced reliability models for the inspection, servicing, and maintenance of land based gas turbine engines.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Uncertainty quantification and reliability assessment for intermodal freight transportation

Intermodal freight optimization models support cost-effective, low-emission, and timely goods movement by coordinating trucks, rail, and barges. These models determine optimal flows, routing, and modal switches while respecting infrastructure and operational constraints. However, their real-world utility is often undermined by pervasive uncertainties-such as fluctuating transportation costs and emissions, variable terminal capacities, and uncertain freight demand-that distort key performance outcomes, including total system cost, carbon footprint, and transit time reliability. This study presents a structured framework for quantifying uncertainty in intermodal freight transportation (IFT) optimization. The framework evaluates how input uncertainty affects system performance and reliability, a critical need for ensuring that model-based decisions remain robust under real-world variability, especially amid volatile fuel prices, shifting demand, and growing disruptions. It integrates three complementary methods: (1) Sobol-based global sensitivity analysis to identify influential parameters affecting cost, emissions, and transit time, (2) Monte Carlo-based capacity perturbation analysis to assess robustness under probabilistic facility disruptions, and (3) Monte Carlo filtering with Bayesian inference to detect threshold-based performance vulnerabilities. The results highlight diesel truck unit cost as the dominant driver of variability. To improve system resilience, planners should prioritize uncertainty in fuel-related parameters when designing intermodal strategies.

Intermodal freight transportation↗
DOE OSTI2021

Data-Driven Reliability Assessment for Marine Renewable Energy Enabled Island Power Systems

Marine renewable energy (MRE) resources are highly predictable and persistent sources of energy, when compared to other renewable sources like wind and solar. These lend them favorably for potential grid applications, particularly for coastal/island power systems where their generation potential is high. Island power systems, on the other hand, are either supported by onsite generation or by transported energy from the mainland grid. Therefore, robustness of grid operations depend heavily on the diversity of onsite generation resources and the reliability of the power transportation medium. Issues relating to either of these two factors may lead to impediments in smooth and reliable operation of the power system. Analyzing and quantifying operational risks for such island power systems with diverse non-conventional generation portfolios through conventional techniques can also prove to be cumbersome, often requiring multiple different inputs. Therefore, in this paper, we firstly present a novel, purely data-driven formulation which quantifies the operational reliability of such island power systems through minimal input data. Specifically, our proposed methodology only relies on historical knowledge of typical hourly load and generation profiles to quantify associated operational risks. Subsequently, we use our proposed formulation to evaluate the effectiveness of MRE resources (over other renewable resources like wind and solar) in providing resilience benefits to island power systems. The proposed formulation is demonstrated with a case study for an island power system in Nantucket, MA.

Chalishazar, Vishvas H.↗
NASA NTRS2008

Qualification Testing of Engineering Camera and Platinum Resistance Thermometer (PRT) Sensors for Mars Science Laboratory (MSL) Project under Extreme Temperatures to Assess Reliability and to Enhance Mission Assurance

Package Qualification and Verification (PQV) of advanced electronic packaging and interconnect technologies and various other types of qualification hardware for the Mars Exploration Rover/Mars Science Laboratory flight projects has been performed to enhance the mission assurance. The qualification of hardware (Engineering Camera and Platinum Resistance Thermometer, PRT) under extreme cold temperatures has been performed with reference to various project requirements. The flight-like packages, sensors, and subassemblies have been selected for the study to survive three times (3x) the total number of expected temperature cycles resulting from all environmental and operational exposures occurring over the life of the flight hardware including all relevant manufacturing, ground operations and mission phases. Qualification has been performed by subjecting above flight-like qual hardware to the environmental temperature extremes and assessing any structural failures or degradation in electrical performance due to either overstress or thermal cycle fatigue. Experiments of flight like hardware qualification test results have been described in this paper.

package reliability↗
NASA NTRS2008

Reliability Assessment of Graphite Specimens under Multiaxial Stresses

An investigation was conducted to predict the failure strength response of IG-100 nuclear grade graphite exposed to multiaxial stresses. As part of this effort, a review of failure criteria accounting for the stochastic strength response is provided. The experimental work was performed in the early 1990s at the Oak Ridge National Laboratory (ORNL) on hollow graphite tubes under the action of axial tensile loading and internal pressurization. As part of the investigation, finite-element analysis (FEA) was performed and compared with results of FEA from the original ORNL report. The new analysis generally compared well with the original analysis, although some discrepancies in the location of peak stresses was noted. The Ceramics Analysis and Reliability Evaluation of Structures Life prediction code (CARES/Life) was used with the FEA results to predict the quadrants I (tensile-tensile) and quadrant IV (compression-tension) strength response of the graphite tubes for the principle of independent action (PIA), the Weibull normal stress averaging (NSA), and the Batdorf multiaxial failure theories. The CARES/Life reliability analysis showed that all three failure theories gave similar results in quadrant I but that in quadrant IV, the PIA and Weibull normal stress-averaging theories were not conservative, whereas the Batdorf theory was able to correlate well with experimental results. The conclusion of the study was that the Batdorf theory should generally be used to predict the reliability response of graphite and brittle materials in multiaxial loading situations.

Sookdeo, Steven↗
NASA NTRS2005

Reliability Assessment Of Conceptual Launch Vehicles

Planning is underway for new NASA missions to the moon and to MARS. These missions carry a great deal of risk, as the Challenger and Columbia accidents demonstrate. In order to minimize the risks to the crew and the mission, risk reduction must be done at every stage, not only in quality manufacturing, but also in design. It is necessary, therefore, to be able to compare the risks posed in different launch vehicle designs. Further, these designs have not yet been implemented, so it is necessary to compare these risks without being able to test the vehicles themselves. This paper will discuss some of the issues involved in this type of comparison. It will start with a general discussion of reliability estimation. It will continue with a short look at some software designed to make this estimation easier and faster. It will conclude with a few recommendations for future tools.

Bloomer, Lisa A.↗
DOE OSTI2021

Wind Turbine Drivetrain Reliability Assessment and Remaining Useful Life Prediction

This presentation describes a methodology for predicting probability of failure of wind turbine gearbox bearings failed by axial cracking. This methodology was applied to a commercial MW size wind plant and generated results were correlated with actual failures. This work is partnered with WindESCo and funded through DOE's Technology Commercialization Fund.

49 EE - Wind and Water Power Program - Wind (EE-4W↗