TPS Research at Sandia National Laboratories
Overview of TPS work at Sandia
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Overview of TPS work at Sandia
Vertical-axis wind turbines (VAWTs) have been the subject of research and development for nearly a century. However, this turbine architecture has fallen in and out of favor on multiple occasions. Beginning in the late 1970s, the U.S. Department of Energy sponsored an extensive experimental program through Sandia National Laboratories which produced a mass of experimental data from several highly instrumented turbines. Turbines designed, built, and tested include the 2 meter, 5 meter, 17 meter, and 34 meter and their respective configurations. This program kicked off a commercial collaboration and resulted in the FloWind turbines. The FloWind turbines had several notable design changes from the experimental turbines that, in conjunction with a general lack of understanding regarding predicting fatigue at the time, led to the majority of the turbines failing prematurely during the late 80s.
In recent years, the procurement of essential materials such as Stainless Steels, Ni-Alloys, and Kovar has become increasingly challenging. Lead times for these materials have extended to over 24 months, placing significant stress on the reliability of attaining these alloys. This situation is exacerbated by the supplier’s minimum purchase requirement of excessively large quantities to meet unique purchase order (PO) requirements which is usually above the maximum requirements of Sandia National Laboratories (SNL). Additionally, the reluctance of foundries to engage in small lot development for SNL specific needs further complicates the procurement process. This white paper explores the reconstitution of SNL’ Melt Laboratory as a strategic solution to mitigate these challenges.
Brief overview of Hypersonics with emphasis on fluid mechanics at Sandia
We describe an approach to predict failure in a complex, additively-manufactured stainless steel part as defined by the third Sandia Fracture Challenge. A viscoplastic internal state variable constitutive model was calibrated to fit experimental tension curves in order to capture plasticity, necking, and damage evolution leading to failure. Defects such as gas porosity and lack of fusion voids were represented by overlaying a synthetic porosity distribution onto the finite element mesh and computing the elementwise ratio between pore volume and element volume to initialize the damage internal state variables. These void volume fraction values were then used in a damage formulation accounting for growth of these existing voids, while new voids were allowed to nucleate based on a nucleation rule. Blind predictions of failure are compared to experimental results. The comparisons indicate that crack initiation and propagation were correctly predicted, and that an initial porosity field superimposed as higher initial damage may provide a path forward for capturing material strength uncertainty. Here, the latter conclusion was supported by predicted crack face tortuosity beyond the usual mesh sensitivity and variability in predicted strain to failure; however, it bears further inquiry and a more conclusive result is pending compressive testing of challenge-built coupons to de-convolute materials behavior from the geometric influence of significant porosity.
Typical Meteorological Years (TMYs) are essential for the efficient evaluation of energy system performance. Ideally, 30 years of weather data are required to generate TMYs, but significantly fewer years are typically available due to practical limitations. To address this issue, an update to the Sandia method was developed, referred to as the Argonne method, to create TMYs from a limited number of years. Furthermore, this method enhances candidate diversity by systematically shifting original candidate months forward or backward by specific days, creating an expanded pool of candidates. The effectiveness of the Argonne method was validated through statistical testing, comparison of monthly average weather parameters, and numerical simulations. The results demonstrate a high probability of identifying at least one shifted month whose cumulative distribution functions of weather parameters closely align with long-term distributions. In 67 % of all comparisons, the monthly average weather parameters in TMYs generated using the Argonne method exhibit better agreement with long-term averages than TMY3. Moreover, in 74 % of the 318 building simulation cases, the Argonne method outperforms TMY3 in estimating long-term average building heating and cooling demands. Therefore, the Argonne method effectively diversifies the candidate pool and produces typical years that provide more accurate estimations of long-term averages compared to TMY3 when only a limited pool of calendar years (10 years or fewer) is available.
Distributed generations (DGs) for grid-connected applications require an accurate and reliable islanding detection methodology (IDM) for secure system operation. This paper presents an IDM for grid-connected inverter-based DGs. The proposed method is a combination of passive and active islanding detection techniques for aggregation of their advantages and elimination/minimisation of the drawbacks. In the proposed IDM, the passive method utilises critical system attributes extracted from local voltage measurements at target DG locations as well as employs decision tree-based classifiers for characterisation and detection of islanding events. The active method is based on Sandia frequency shift technique and is initiated only when the passive method is unable to differentiate islanding events from other system events. Thus, the power quality degradation introduced into the system by active islanding detection techniques can be minimised. Furthermore, a combination of active and passive techniques allows detection of islanding events under low power mismatch scenarios eliminating the disadvantage associated with the use of passive techniques alone. Finally, detailed case study results demonstrate the effectiveness of the proposed method in detection of islanding events under various power mismatch scenarios, load quality factors and in the presence of single or multiple grid-connected inverter-based DG units.
At Sandia National Laboratories, the x-ray generator Manson source model 5 was upgraded from 10 to 25 kV. The purpose of the upgrade is to drive higher characteristics photon energies with higher throughput. In this work we present characterization studies for the source size and the x-ray intensity when varying the source voltage for a series of K-, L-, and M-shell lines emitted from Al, Y, and Au elements composing the anode. We used a 2-pinhole camera to measure the source size and an energy dispersive detector to monitor the spectral content and intensity of the x-ray source. As the voltage increases, the source size is significantly reduced and line intensity is increased for the three materials. We can take advantage of the smaller source size and higher source throughput to effectively calibrate the suite of Z Pulsed Power Facility crystal spectrometers.
This document describes the personal nuclear accident dosimeter (PNAD) used by Sandia National Laboratories (SNL) and presents PNAD dosimetry results obtained during the Nuclear Accident Dosimeter Intercomparison Study held 20-23 September, 2010, at CEA Valduc, France. SNL PNADs were exposed in two separate irradiations from the CALIBAN reactor. Biases for reported neutron doses ranged from -15% to +0.4% with an average bias of -7.7%. PNADs were also exposed on the back side of phantoms to assess orientation effects.
This document describes the implementation level changes in the source code and input files of Sandia National Laboratories Environmental Fluid Dynamics Code (SNL-EFDC) that are necessary for including pH effects into algae-growth dynamics. The document also gives a brief introduction to how pH effects are modeled into the algae-growth model. The document assumes that the reader is aware of the existing algae-growth model in SNL-EFDC. The existing model is described by James, Jarardhanam and more theoretical considerations behind modeling pH effects are presented therein. This document should be used in conjunction with the original EFDC manual and the original water-quality manual.
An updated algorithm for the EXTRAD 4100S extremity dosimeter has been derived. This algorithm optimizes the binning of dosimeter element ratios and uses a quadratic function to determine the response factors for low response ratios. This results in lower systematic bias across all test categories and eliminates the need for the 'red strap' algorithm that was used for high energy beta/gamma emitting radionuclides. The Radiation Protection Dosimetry Program (RPDP) at Sandia National Laboratories uses the Thermo Fisher EXTRAD 4100S extremity dosimeter, shown in Fig 1.1 to determine shallow dose to the extremities of potentially exposed individuals. This dosimeter consists of two LiF TLD elements or 'chipstrates', one of TLD-700 ({sup 7}Li) and one of TLD-100 (natural Li) separated by a tin filter. Following readout and background subtraction, the ratio of the responses of the two elements is determined defining the penetrability of the incident radiation. While this penetrability approximates the incident energy of the radiation, X-rays and beta particles exist in energy distributions that make determination of dose conversion factors less straightforward in their determination.
This report provides a summary of the radionuclide releases from the United States (U.S.) Department of Energy (DOE) National Nuclear Security Administration facilities at Sandia National Laboratories, New Mexico (SNL/NM) during Calendar Year (CY) 2015, including the data, calculations, and supporting documentation for demonstrating compliance with 40 Code of Federal Regulation (CFR) 61.
The presentation was intended for the Accord Technical Exchange Meeting (ATEM), September 3, 2020. Multiple lines of evidence were evaluated in the Use Attainability Analysis for Upper Sandia Canyon.
The Burrowing Owl Survey Report for Sandia National Laboratories: 2024 provides data and analysis on occupancy surveys that were conducted during the 2024 survey season. The surveys were conducted in partnership with Kirtland Air Force Base’s Natural Resource Program to maintain and expand on the long-term dataset on burrowing owls on base.
The Burrowing Owl Survey Report for Sandia National Laboratories: 2025 provides data and analysis on occupancy surveys that were conducted during the 2025 survey season. The surveys were conducted in partnership with Kirtland Air Force Base’s Natural Resource Program and the United States Fish and Wildlife Service to maintain and expand on the long-term dataset on burrowing owls on base. Ecology Program biologists conducted roadside census surveys at survey areas previously identified by Kirtland Air Force Base along with several additional survey areas deemed suitable for occupancy. Remote sensor camera monitoring was also conducted on three nest burrows. In total, 12 breeding pairs of burrowing owls were confirmed in 2025. Several owls were confirmed to have leg bands, indicating previous captures and recurrence of these specific individuals on base. Occupancy surveys on burrowing owls continue to provide valuable information on ecosystem health and can serve to inform future management direction and decisions.
The Hawaiian Hoary Bat Report for Sandia National Laboratories, Kauai Test Facility (SNL/KTF) provides data and analysis of Hawaiian hoary bat occupancy of the SNL/KTF site. The monitoring period was from 2023-2025 and used passive acoustic detection at three locations to determine whether the Hawaiian hoary bat occurs at the site and if they roost and pup in the vegetation of the site. Bats were detected at all three locations, however, given the vegetation type at SNL/KTF, it is very unlikely
This is a presentation discussing some of the recent activities of the Sandia Access Delay department
Partnering with Los Alamos National Laboratory, an Albuquerque-based company is seeking to transform the way protein and peptide analysis is conducted around the world. Sandia Biotech is using a biological technology licensed from Los Alamos called split green fluorescent protein (sGFP), as a detecting and tracking tool for the protein and peptide industry, valuable in the fields of Alzheimer's research, drug development and other biotechnology fields using protein folding to understand protein expression and mechanisms of action. http://www.lanl.gov/news/stories/glowing-future-for-los-alamos-and-sandia-b iotech-partnership.html