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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.

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At least 379 records · Page 21
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DOE OSTI2024

VLM4Bio: A Benchmark Dataset to Evaluate Pretrained Vision-Language Models for Trait Discovery from Biological Images

Images are increasingly becoming the currency for documenting biodiversity on the planet, providing novel opportunities for accelerating scientific discoveries in the field of organismal biology, especially with the advent of large vision-language models (VLMs). We ask if pre-trained VLMs can aid scientists in answering a range of biologically relevant questions without any additional fine-tuning. In this paper, we evaluate the effectiveness of 12 state-of-the-art (SOTA) VLMs in the field of organismal biology using a novel dataset, VLM4Bio, consisting of 469K question8 answer pairs involving 30K images from three groups of organisms: fishes, birds, and butterflies, covering five biologically relevant tasks. We also explore the effects of applying prompting techniques and tests for reasoning hallucination on the performance of VLMs, shedding new light on the capabilities of current SOTA VLMs in answering biologically relevant questions using images

Maruf, M [Virginia Tech, Blacksburg]↗
DOE OSTI2024

(Doublon) Benchmarking of Different Inverse Point Kinetics Implementations for an Autocorrected Reactimeter Algorithm

In November 2017, the Transient Reactor Test Facility returned to operation. Since that time, many transient test series have been completed, such as the Transient Heatsink Overpower Response capsule (THOR), the Transient Water Irradiation System for TREAT (TWIST), and Sirius. Each has provided valuable data for materials performance and reactor safety that can be applied in future designs. During each experimental series, detector count rates provided important information on the core behavior during transients. However, a limitation of these data is that variations in the neutron distribution during experiments can cause errors when attempting to infer reactivity evolution from detector signals. Neutron physics codes can be used to compute the flux shape variations. However, this is a poor solution when the experimental data is used for code verification, validation and uncertainty quantification. Indeed, if the output of the code is used both as a reference and to correct what the reference is compared to, the circular dependency limits the quality of the verification, validation and uncertainty quantification approach. To overcome this problem, the autocorrected reactimeter algorithm (ACRA) has been developed. This approach infers a time-dependent reactivity evolution by testing different spatial corrections and selecting the one that minimizes reactivity variations when the core is in a frozen configuration (i.e., when there is no variation in parameters affecting reactivity). However, the scope of this method was limited to transients where there were negligible thermal feedback. Indeed, the core is never in a frozen configuration when the fuel temperature varies during the whole transient. This is our motivation for developing an improved version of the ACRA that does not require frozen configurations. To develop this new algorithm, we need a precise and unbiased implementation of the inverse point kinetic equations (IPKEs) as any error in the reactivity evaluation will be propagated into the choice of the optimal spatial correction. Indeed, the previous reactimeter algorithm would use approximations, such as a negligible flux amplitude derivative, to focus on rapidity. For the numerical validation of ACRA, we aim at absolute error under for reactivity derived from signals similar to the one of this study. In this summary, we test eight different IPKE implementations. Each will process a mockup signal built for this study, similar to those that the future ACRA will process. Each reactivity output will be compared to the reference reactivity that has been used to generate the mockup signal. The implementation minimizing the difference with the reference reactivity will be used in the development of a new ACRA formulation.

73 - NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Benchmarking MCNP models to support gamma irradiation experiments

Seismic isolators and damping devices have been used for 30+ years to reduce seismic forces and deployed in 10,000+ structures, including bridges, buildings, and mission-critical infrastructure. Studies have shown that seismic isolation of nuclear power plants can reduce the seismic risk by several orders of magnitude and substantially reduce the overnight capital cost. Advanced reactor developers are considering seismic isolation as an integral design feature in their reactor design. It can either be deployed at the building level, isolating the entire reactor building, or at the component level, isolating individual pieces of safety-class equipment, such as a reactor vessel or a steam generator. For equipment isolation, located close to the reactor vessel, the seismic isolators and/or damping devices may be exposed to gamma and neutron radiation, with a possible effect on their mechanical properties which would affect the response of the isolated equipment under earthquake shaking. The Department of Energy, as part of its Nuclear Energy University Program (NEUP), in collaboration with the Idaho National Laboratory (INL), is funding a project at the University at Buffalo (UB) to investigate the effect of gamma radiation on the mechanical properties of various seismic protective devices. (When isolating equipment, the seismic protective devices will be located outside the reactor vessel where the neutron exposure will be insignificant.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

GIF: VHTR Benchmark

Intern research presentation for C-120 Group meeting.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Beyond Point Estimates: Benchmarking Uncertainty Quantification Methods on the AION-1 Astronomical Foundation Model

Foundation models for astronomical surveys offer powerful learned representations that can be transferred to downstream regression tasks such as galaxy property estimation. However, point predictions alone are insufficient for scientific inference; reliable uncertainty quantification (UQ) is essential. We compare seven UQ methods on galaxy property regression using frozen AION-1 foundation-model embeddings, predicting redshift, stellar mass, stellar-population age, gas-phase metallicity, and specific star-formation rate, from Legacy Survey photometry/imaging and DESI spectra, with PROVABGS-derived labels. Distribution-free conformal methods achieve marginal coverage within $\sim$1 pp of the nominal 90% across all properties, while non-conformal baselines (Deep Ensembles, MC~Dropout) fail to calibrate reliably. Among conformal approaches, Conformalized Quantile Regression (CQR) delivers the best coverage in the bin with the poorest model predictions. More importantly, only the Locally Valid and Discriminative (LVD) framework -- particularly when operating on AION-1 embeddings -- also provides finite-sample \emph{local validity}, producing intervals that adapt to each galaxy's local prediction difficulty rather than relying on marginal guarantees alone. These results establish conformal prediction, and LVD in particular, as the preferred UQ framework for uncertainty-aware inference on foundation-model embeddings in astrophysics.

Tame-Narvaez, Karla [Fermilab] (ORCID:000000022249↗
DOE OSTI2026

The BRIAR Dataset: A Comprehensive Whole-Body Biometric Recognition Benchmark at Extreme Distances and Altitudes (Collections 1-6)

The Biometric Recognition and Identification at Altitude and Range (BRIAR) program aims to extend biometric capabilities into severe operational environments characterized by long ranges, atmospheric turbulence, and elevated viewpoints. This paper introduces the program’s two final government collections expanding activities, environments, viewpoints, distances, and modalities, and adding appearance and environmental stressors. We refine curation/evaluation and include sequestered subsets to support controlled assessments. These updates strengthen BRIAR as a comprehensive resource for whole-body, face, and gait recognition at altitude and range, while maintaining privacy-first practices.

Yoon, Rocky [ORNL] (ORCID:0009000491499165)↗
DOE OSTI2025

NEA HTTR LOFC Project Test#2 Benchmark Results

The High Temperature Engineering Test Reactor (HTTR) is a 30 MW prismatic high-temperature gas-cooled reactor (HTGR) owned and operated by the Japan Atomic Energy Agency (JAEA). Staring in 2010, HTTR was used in a series of three loss of forced cooling (LOFC) tests without SCRAM to demonstrate the inherent safety of HTGRs.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗