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Technical Assistance for RingIR Aerosol Penetration Study with RingIR

Sikora, Joel S.

Sandia provided technical assistance to RingIR to test and evaluate of the RingIR molecular detector. The detector can identify gas phase species using molecular fingerprinting and has potential application for SARS-CoV-2 detection in near real time. As part of the development process Sandia will utilize the biological aerosol test bed deployed at the Aerosol Complex to evaluate the penetration of MS2 bacteriophage aerosol through the RingIR system. The objective of this project is to provide experimentally derived measurements of the RingIR molecular detector penetration efficiency, including external exhaust filter for mitigation of exhaust aerosol and operation using MS2 bacteriophage as a biological surrogate to the SARS-CoV-2 virus.

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TYPE Other Report YEAR 2021
DOIOSTI

CY2020 Report for PECOS Activities

Geissel, Matthias G.

All experiments involving the Pecos target chamber in calendar year (CY) 2020 were dedicated to Pre-Heat studies in the context of Magnetized Liner Inertial Fusion (MagLIF). Activities at the target area included actual laser shots but also diagnostic and maintenance, and preparatory work for experiments with cryogenically cooled targets. The latter took up a large part of CY2020’s shot availability, and consequently there were fewer shots performed than in previous years. Since the Z-Beamlet and Z-Petawatt lasers support multiple campaigns, we can only anticipate laser and laser-operator time for one out of three shot windows in a day, and typically not on every day of the week. For that reason, many of our non-shot activities need to be traded against shots as well.

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TYPE Other Report YEAR 2021
DOIOSTI

Secure LoRa firmware update with adaptive data rate techniques

Sensors

Heeger, Derek S.; Garigan, Maeve; Plusquellic, Jim; Tsiropoulou, Eirini E.

Internet of Things (IoT) devices rely upon remote firmware updates to fix bugs, update embedded algorithms, and make security enhancements. Remote firmware updates are a significant burden to wireless IoT devices that operate using low-power wide-area network (LPWAN) technologies due to slow data rates. One LPWAN technology, Long Range (LoRa), has the ability to increase the data rate at the expense of range and noise immunity. The optimization of communications for maximum speed is known as adaptive data rate (ADR) techniques, which can be applied to accelerate the firmware update process for any LoRa-enabled IoT device. In this paper, we investigate ADR techniques in an application that provides remote monitoring of cattle using small, battery-powered devices that transmit data on cattle location and health using LoRa. In addition to issues related to firmware update speed, there are significant concerns regarding reliability and security when updating firmware on mobile, energy-constrained devices. A malicious actor could attempt to steal the firmware to gain access to embedded algorithms or enable faulty behavior by injecting their own code into the device. A firmware update could be subverted due to cattle moving out of the LPWAN range or the device battery not being sufficiently charged to complete the update process. To address these concerns, we propose a secure and reliable firmware update process using ADR techniques that is applicable to any mobile or energy-constrained LoRa device. The proposed system is simulated and then implemented to evaluate its performance and security properties.

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TYPE Journal Article YEAR 2021
DOIOSTIScopus

An overview of magneto-inertial fusion on the Z Machine at Sandia National Laboratories

Yager-Elorriaga, David A.; Gomez, Matthew R.; Ruiz, Daniel E.; Slutz, Stephen A.; Harvey-Thompson, Adam J.; Jennings, Christopher A.; Weis, Matthew R.; Awe, Thomas J.; Chandler, Gordon A.; Myers, Clayton E.; Fein, Jeffrey R.; Geissel, Matthias G.; Glinsky, Michael E.; Hansen, Stephanie B.; Harding, Eric H.; Lamppa, Derek C.; Laros, James H.; Robertson, Grafton K.; Savage, Mark E.; Ampleford, David A.; Beckwith, Kristian B.; Peterson, Kyle J.; Porter, John L.; Rochau, G.A.

Abstract not provided.

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TYPE Conference Paper YEAR 2021
OSTI

An overview of magneto-inertial fusion on the Z Machine at Sandia National Laboratories

Yager-Elorriaga, David A.; Gomez, Matthew R.; Ruiz, Daniel E.; Slutz, Stephen A.; Harvey-Thompson, Adam J.; Jennings, Christopher A.; Knapp, Patrick K.; Schmit, Paul S.; Weis, Matthew R.; Awe, Thomas J.; Chandler, Gordon A.; Mangan, Michael M.; Myers, Clayton E.; Fein, Jeffrey R.; Geissel, Matthias G.; Glinsky, Michael E.; Hansen, Stephanie B.; Harding, Eric H.; Lamppa, Derek C.; Webster, Evelyn L.; Rambo, Patrick K.; Robertson, Grafton K.; Savage, Mark E.; Smith, Ian C.; Ampleford, David A.; Beckwith, Kristian B.; Peterson, Kara J.; Porter, John L.; Rochau, G.A.; Sinars, Daniel S.

Abstract not provided.

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TYPE Conference Poster YEAR 2021
DOIOSTI

Tamper-Indicating Enclosures with Visually Obvious Tamper Response (Final Project Report)

Smartt, Heidi A.; Benin, Annabelle L.; Corbin, William C.; Feng, Patrick L.; Jones, Amanda; Myllenbeck, Nicholas M.; Livesay, Jason D.; Pickett, Chris A.

Sandia National Laboratories is developing a new method for detecting penetration of tamper - indicating enclosures (TIEs). This method incorporates the use of "bleeding" materials (analogous to visually obvious, colorful bruised skin that doesn't heal) into the design of TIEs. As designed, it will allow inspectors to use simple visual observation to detect attempts to penetrate the external surfaces of a TIE, without providing adversaries the ability to repair damage. A material of this type can enhance tamper indication of current TIEs used to support treaty verification regimes. Current TIE inspections are time - consuming and rely on subjective visual assessment by an inspector, equipment such as eddy current or camera devices, or involve approaches that may be limited due to application environment. The complexities and requirements that volumetric sealing methods (or TIEs) must address are: (1) enclosures that are non - standard in size/shape; (2) enclosures that may be inspectorate - or facility - owned; (3) finding tamper attempts that are difficult and time consuming for an inspector to locate; (4) enclosures that are reliable and durable enough to survive the conditions that exist in the operating environment (including facility handling); and (5) methods that prevent adversaries from repairing penetrations. Early project R&D [1] focused on encapsulated transition metals. Due to the challenges associated with the transition metal - based approach, a mitigation approach was investigated resulting in two separate research paths — one that involves fabricating custom TIE molds that meet the specific (size and shape) needs of safeguards equipment a nd one that can be deployed as a sprayed on or painted coating to an existing TIE or surface. The "custom mold" approach is based on creating thin layers of materials that , when penetrated, expose an inner material to O2 which causes an irreversible color change. The "in-situ coating" approach is based on applying a sensor solution containing color changing microcapsules that bleed when the microcapsule is ruptured. The anticipated benefits of this work are passive, flexible, scalable, robust , cost-effective TIEs with visually obvious responses to tamper attempts. This provides more efficient and effective monitoring , as inspectors will require little or no additional equipment and will be able to detect tamper without extensive time - consuming visual examination. Applications include custom TIEs (cabinets , equipment enclosures or seal bodies ), or spray-coating/painting onto facility-owned items, walls or structures, or circuit boards. The paper describes research and testing completed to-date on the method and integration of select system components.

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TYPE SAND Report YEAR 2021
DOIOSTI

ExaWind: Exascale Predictive Wind Plant Flow Physics Modeling

Sprague, Michael; Ananthan, Shreyas; Binyahib, Roba; Brazell, Michael; De Frahan, Marc H.; King, Ryan A.; Mullowney, Paul; Rood, Jon; Sharma, Ashesh; Thomas, Stephen A.; Vijayakumar, Ganesh; Crozier, Paul C.; Berger-Vergiat, Luc B.; Cheung, Lawrence C.; Dement, David C.; deVelder, Nathaniel d.; Glaze, D.J.; Hu, Jonathan J.; Knaus, Robert C.; Lee, Dong H.; Matula, Neil M.; Okusanya, Tolulope O.; Overfelt, James R.; Rajamanickam, Sivasankaran R.; Sakievich, Philip S.; Smith, Timothy A.; Vo, Johnathan V.; Williams, Alan B.; Yamazaki, Ichitaro Y.; Turner, William J.; Prokopenko, Andrey; Wilson, Robert V.; Moser, Robert; Melvin, Jeremy; Sitaraman, Jay

Abstract not provided.

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TYPE Conference Poster YEAR 2021
DOIOSTI

Safeguards-Informed Hybrid Imagery Dataset [Poster]

Rutkowski, Joshua E.; Gastelum, Zoe N.; Shead, Timothy M.; Rushdi, Ahmad R.; Bolles, Jason C.; Mattes, Arielle

Deep Learning computer vision models require many thousands of properly labelled images for training, which is especially challenging for safeguards and nonproliferation, given that safeguards-relevant images are typically rare due to the sensitivity and limited availability of the technologies. Creating relevant images through real-world staging is costly and limiting in scope. Expert-labeling is expensive, time consuming, and error prone. We aim to develop a data set of both realworld and synthetic images that are relevant to the nuclear safeguards domain that can be used to support multiple data science research questions. In the process of developing this data, we aim to develop a novel workflow to validate synthetic images using machine learning explainability methods, testing among multiple computer vision algorithms, and iterative synthetic data rendering. We will deliver one million images – both real-world and synthetically rendered – of two types uranium storage and transportation containers with labelled ground truth and associated adversarial examples.

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TYPE Conference Poster YEAR 2021
DOIOSTI

Designing New Materials for Photovoltaics: Opportunities for Lowering Cost and Increasing Performance through Advanced Material Innovations

Oreski, Gernot; Stein, Joshua S.; Eder, Gabriele; Berger, Karl; Bruckman, Laura S.; Vedde, Jan; Weiss, Karl-Anders; Tanahashi, Tadanori; French, Roger H.; Ranta, Samuli

Within the framework of IEA PVPS, Task 13 aims to provide support to market actors working to improve the operation, the reliability and the quality of PV components and systems. Operational data from PV systems in different climate zones compiled within the project will help provide the basis for estimates of the current situation regarding PV reliability and performance. The general setting of Task 13 provides a common platform to summarize and report on technical aspects affecting the quality, performance, reliability and lifetime of PV systems in a wide variety of environments and applications. By working together across national boundaries we can all take advantage of research and experience from each member country and combine and integrate this knowledge into valuable summaries of best practices and methods for ensuring PV systems perform at their optimum and continue to provide competitive return on investment. Task 13 has so far managed to create the right framework for the calculations of various parameters that can give an indication of the quality of PV components and systems. The framework is now there and can be used by the industry who has expressed appreciation towards the results included in the high-quality reports. The IEA PVPS countries participating in Task 13 are Australia, Austria, Belgium, Canada, Chile, China, Denmark, Finland, France, Germany, Israel, Italy, Japan, the Netherlands, Norway, Spain, Sweden, Switzerland, Thailand, and the United States of America.

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TYPE Other Report YEAR 2021
DOIOSTI

Using Bayesian Methodology to Estimate Liquefied Natural Gas Leak Frequencies

Mulcahy, Garrett W.; Brooks, Dusty M.; Ehrhart, Brian D.

This analysis provides estimates on the leak frequencies of nine components found in liquefied natural gas (LNG) facilities. Data was taken from a variety of sources, with 25 different data sets included in the analysis. A hierarchical Bayesian model was used that assumes that the log leak frequency follows a normal distribution and the logarithm of the mean of this normal distribution is a linear function of the logarithm of the fractional leak area. This type of model uses uninformed prior distributions that are updated with applicable data. Separate models are fit for each component listed. Five order-of-magnitude fractional leak areas are considered, based on the flow area of the component. Three types of supporting analyses were performed: sensitivity of the model to the data set used, sensitivity of the leak frequency estimates to differences in the model structure or prior distributions, and sufficiency of sample sized used for convergence. Recommended leak frequency distributions for all component types and leak sizes are given. These leak frequency predictions can be used for quantitative risk assessments in the future.

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TYPE SAND Report YEAR 2021
DOIOSTI
Results 11001–11200 of 96,771
Results 11001–11200 of 96,771