LLNL researchers have developed a TDLAS-based, standalone, real-time gas analyzer in a small form-factor for continuous or single-point monitoring. The system can analyze multiple gases with ultra-high sensitivity (ppm detection levels) in harsh conditions when utilizing wavelength-modulation spectroscopy (WMS).
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![Diffuse discharge circuit breaker with latching switch](/sites/default/files/styles/scale_exact_400x400_/public/2024-02/Diffuse%20discharge%20circuit%20breaker.png?itok=qWpciEtY)
A thyristor will stay conducting until the current through the device is zero (“current zero”) or perhaps slightly negative. LLNL’s approach is to use the opticondistor (“OTV”) to force this current zero in order to force the device into an “off” state. By combining a light-activated thyristor with an OTV, a noise-immune, high efficiency, high-power switching device can be constructed. The…
![LLNL energy grid protection device](/sites/default/files/styles/scale_exact_400x400_/public/2023-10/LLNL%20energy%20grid%20protection%20device_0.png?itok=vpqzRY_R)
The approach is to leverage the fact that a momentary “load” equal to the power transmission line impedance, (Z0), during the transient can suppress its propagation. Z(0) is typically a fixed impedance of several hundred ohms based on the geometry of most single wire transmission lines.
So, an isolated self-powered opticondistor (OTV) system may provide an ultrafast method of…
![AI Innovation Incubator](/sites/default/files/styles/scale_exact_400x400_/public/2022-01/AI%20Innovation%20Incubator.jpg?itok=B8jcKPOy)
Lawrence Livermore National Laboratory (LLNL) is offering the opportunity to collaborate in accelerating artificial intelligence (AI) for applied science, including research in key areas such as advanced material design, 3D printing, predictive biology, energy systems, “self-driving” lasers and fusion energy research.
![Plasma wind](/sites/default/files/styles/scale_exact_400x400_/public/2022-08/Plasma%20wind%20.png?itok=RB5iLhMv)
![Catalyst HPC cluster](/sites/default/files/styles/scale_exact_400x400_/public/2022-06/Catalyst%20HPC%20cluster.jpg?itok=k9uYS5xL)
Clinical images have a wealth of data that are currently untapped by physicians and machine learning (ML) methods alike. Most ML methods require more data than is available to sufficiently train them. In order to obtain all data contained in a clinical image, it is imperative to be able to utilize multimodal, or various types of, data such as tags or identifications, especially where spatial…
![medical_x-rays_x-ray_tech](/sites/default/files/styles/scale_exact_400x400_/public/2022-06/medical_x-rays_x-ray_tech_1.jpg?itok=kn0J-DkH)
Some COVID-19 diagnoses are utilizing computed tomography (CT)-scans for triage. CT-scans produce immediate results with high sensitivity. The digital images produced by a CT-scan require physicians to identify objects within the image to determine the presence of disease. Object identification can be done using machine learning (ML) techniques such as deep learning (DL) to improve speed and…
![MimicGAN data set example](/sites/default/files/styles/scale_exact_400x400_/public/2020-05/mimicgan_robustness_to_rotation.png?itok=yacM18ra)
MimicGAN represents a new generation of methods that can “self-correct” for unseen corruptions in the data out in the field. This is particularly useful for systems that need to be deployed autonomously without needing constant intervention such as Automated Driver Assistance Systems. MimicGAN achieves this by treating every test sample as “corrupt” by default. The goal is to determine (a) the…
![multichannel_pyrometer.jpg multichannel_pyrometer](/sites/default/files/styles/scale_exact_400x400_/public/2019-08/multichannel_pyrometer.jpg?itok=x0sCe_BN)
LLNL researchers have designed and tested performance characteristics for a multichannel pyrometer that works in the NIR from 1200 to 2000 nm. A single datapoint without averaging can be acquired in 14 microseconds (sampling rate of 70,000/s). In conjunction with a diamond anvil cell, the system still works down to about 830K.
![Intrinsic Use Control](/sites/default/files/styles/scale_exact_400x400_/public/2022-06/Intrinsic%20Use%20Control.jpg?itok=plVEiBwC)
LLNL's method of equivalent time sampling incorporates an embedded system that generates the pulses used to trigger the external circuit and the data acquisition (DAQ). This removes the external reference clock, allowing the overall system clock rate to change based on the ability of the embedded system. The time delays needed to create the time stepping for equivalent time sampling is done by…
![Toy model demonstration of a Napier Deltic Engine. Thermo-structural analysis in Diablo with piston pressure. Simrev software-twin is seven python modules; pistons, crank-arms, gears, etc.; and a main program. Total 600 lines of code.](/sites/default/files/styles/scale_exact_400x400_/public/2019-10/toy_model_demonstration.png?itok=f08Z-smu)
Simrev is a python library imported into a user-generated program. As the program grows in capability and complexity, the engineered product matures. The "software twin" handles all changes to product configuration and is the portal to running supercomputing analysis and managing workflow for engineering simulation codes. Assemblies become program modules; parts, materials, boundary conditions…
![medical_x-rays_x-ray_tech](/sites/default/files/styles/scale_exact_400x400_/public/2022-06/medical_x-rays_x-ray_tech_1.jpg?itok=kn0J-DkH)
LLNL has developed a new system, called the Segmentation Ensembles System, that provides a simple and general way to fuse high-level and low-level information and leads to a substantial increase in overall performance of digital image analysis. LLNL researchers have demonstrated the effectiveness of the approach on applications ranging from automatic threat detection for airport security, to…
![Marine helmet](/sites/default/files/styles/scale_exact_400x400_/public/2022-06/Marine%20helmet-inside.jpg?itok=8W_dqpgI)
LLNL's high fidelity hydrocode is capable of predicting blast loads and directly coupling those loads to structures to predict a mechanical response. By combining this code and our expertise in modeling blast-structure interaction and damage, along with our access to experimental data and testing facilities, we can contribute to the design of protective equipment that can better mitigate the…