Search NASA⌕ Search

SEARCH · Search NASA

Results for “risk assessments”

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 253 records · Page 14

Characterization of Extreme Wave Conditions for Wave Energy Converter Design and Project Risk Assessment

Best practices and international standards for determining n-year return period extreme wave (sea states) conditions allow wave energy converter designers and project developers the option to apply simple univariate or more complex bivariate extreme value analysis methods. The present study compares extreme sea state estimates derived from univariate and bivariate methods and investigates the performance of spectral wave models for predicting extreme sea states at buoy locations within several regional wave climates along the US East and West Coasts. Two common third-generation spectral wave models are evaluated, a WAVEWATCH III® model with a grid resolution of 4 arc-minutes (6–7 km), and a Simulating WAves Nearshore model, with a coastal resolution of 200–300 m. Both models are used to generate multi-year hindcasts, from which extreme sea state statistics used for wave conditions characterization can be derived and compared to those based on in-situ observations at National Data Buoy Center stations. Comparison of results using different univariate and bivariate methods from the same data source indicates reasonable agreement on average. Discrepancies are predominantly random. Large discrepancies are common and increase with return period. There is a systematic underbias for extreme significant wave heights derived from model hindcasts compared to those derived from buoy measurements. This underbias is dependent on model spatial resolution. However, simple linear corrections can effectively compensate for this bias. A similar approach is not possible for correcting model-derived environmental contours, but other methods, e.g., machine learning, should be explored.

16 TIDAL AND WAVE POWER↗

Battery Fire Risk Assessment

Explore the source record for details and available documents.

Energy - Conversion, Energy - Storage, Chemistry -↗

Risk Assessment of Hydrogen Production Coupled to Nuclear Power Plants

Presentation slides curated from previous public INL reports & other open references: - Slide 1 from INL homepage www.inl.gov - Slide 2 from MIT report and NEI report (both are publicly available) - Slide 3 from LWRS portal www.lwrs.inl.gov - Slide 4 from H2@Scale portal https://www.energy.gov/eere/fuelcells/h2scale - Slide 6-8 from INL reports: INL/EXT-20-60104, INL/EXT-20-60104 Rev 1, INL/RPT-23-74319 - Slide 9 from an open journal paper - Slide 10-30 from INL open reports INL/RPT-23-74319 and INL/RPT-22-68155

08 HYDROGEN↗