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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 1,243 records · Page 69

HYPPO: A Surrogate-Based Multi-Level Parallelism Tool for Hyperparameter Optimization

We present a new software, HYPPO, that enables the automatic tuning of hyperparameters of various deep learning (DL) models. Unlike other hyperparameter optimization (HPO) methods, HYPPO uses adaptive surrogate models and directly accounts for uncertainty in model predictions to find accurate and reliable models that make robust predictions. Using asynchronous nested parallelism, we are able to significantly alleviate the computational burden of training complex architectures and quantifying the uncertainty. HYPPO is implemented in Python and can be used with both TensorFlow and PyTorch libraries. We demonstrate various software features on time-series prediction and image classification problems as well as a scientific application in computed tomography image reconstruction. Finally, we show that (1) we can reduce by an order of magnitude the number of evaluations necessary to find the most optimal region in the hyperparameter space and (2) we can reduce by two orders of magnitude the throughput for such HPO process to complete.

adaptation models↗

Assessing Machine Learning as a Tool to Explain Variance in Deployed Photovoltaic (PV) System Degradation

Degradation remains a large uncertainty in forecasting production for PV plants, creating significant risk for developers and financiers. This study aims to quantify the distribution and drivers of degradation across 10,000 PV systems deployed for distributed or utility generation by training a machine learning model to predict year-over-year degradation rates from metadata characteristics. A combination of K-Means clustering and random forest regressor were found to associate multiple metadata features as potential drivers of degradation, including module characteristics, system design, and climate features. From this, it is inferred that if machine learning is able to find complex patterns between metadata features and system performance loss, such methods can be employed to help developers and financiers make data-informed decisions when estimating long-term energy production forecasts in financial models.

Dunn, Jimmy C.↗

Varistors: A Useful Tool for Superconducting Magnet Quench Protection

A perfect varistor is a constant voltage resistor as a function of current through the resistor. A perfect varistor can't exist, because its resistance would be infinite at zero current. In electronic devices, varistors are often used as surge protectors. A varistor can be used in place of an ordinary resistor as the discharge resistance across superconducting coil sections. When used this way, the integral of I 2 dt during the discharge can be reduced by almost one third. When a varistor is used for quench protection of coils that are coupled to shorted secondary circuits the integral of I 2 dt can be reduced much more. Furthermore, this can be a key factor when coil current densities and stored energies are high as in many potential HTS magnet systems. This paper discusses the types of varistors that are commercially available and their characteristics.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Stray-Capacitance As a Simple Tool for Monitoring and Locating Heat Generation Demonstrated in Three Superconducting Magnets

Real-time monitoring of heat loads in cryogenic systems is critical for many applications, particularly high field magnets. In this work, we demonstrated that by monitoring changes in the capacitance of local probes consisting of thin metal strips with a porous glass fiber dielectric, boiling helium from as little as 0.1 J of deposited heat can be located by an analysis of the response speed and amplitude in nearby probes. We further implemented stray-capacitance monitoring of a magnet's metal support structures, a more global probe of the magnet volumes, in three high temperature superconducting Bi-2212 magnet types. Global structural stray-capacitance monitoring was evaluated for a single racetrack coil, a common coil dipole, and a canted cosine theta winding, showing a quench response comparable to voltage signals without inductive effects. The response of the local and global probes was compared in the single racetrack coil with well-known quench properties. Monitoring the cool-down of the common coil dipole demonstrated the added benefit of the global stray-capacitance as a liquid level monitor. This simple method of monitoring the capacitance has proven to be a versatile and robust technique for monitoring and locating heat.

43 PARTICLE ACCELERATORS↗

Melt Blending: A Tool to Simplify Plastic Scintillator Synthesis

Plastic scintillators are widely used as radiation detection media in homeland security and nuclear physics applications. Their attributes include low cost, scalability to large detector volumes, and additive compounding to enable additional material and detection features, such as pulse shape discrimination (PSD), gamma-ray spectroscopy, aging resistance, and coincidence timing. However, traditional chemically cured plastic scintillators (CCS) require long reaction times, and hazardous wet chemical procedures performed by specially trained personnel, and can leave residual monomer, resulting in deleterious optical and material properties. Here, we synthesize melt blended scintillators (MBSs) in 2.5 days using easily accessible solid-state compounding of commercially-available poly(styrene) with 30–60 wt% fluorene-based compound “P2” to create monolithic detectors with < 100 ppm residual monomer, in several form factors. Further, the best scintillation performance was recorded for 60 wt% P2 in Styron 665, including gamma-ray light yield 139% of EJ- 200 commercial scintillator and PSD figure of merit (FOM) value of 2.65 at 478 keVee, approaching P2 organic glass scintillator (OGS). The capability of MBS to generate fog-resistant scintillators and poly(methyl methacrylate) (PMMA)-based scintillators for use in challenging environments is also demonstrated.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

Novel genetic tools improve Penicillium expansum patulin synthase production in Aspergillus niger

Since the first CRISPR (clustered regularly interspaced short palindromic repeats)‐Cas (CRISPR‐associated) system was developed for creating double‐stranded DNA breaks, it has been adapted and improved for different biotechnological applications. In this issue of The FEBS Journal , Arentshorst et al . developed a novel approach to enhance transgene expression of a specific protein, patulin synthase (PatE) from Penicillium expansum , in the important industrial filamentous fungus Aspergillus niger . Their technique involved the disruption of selected genes with counter‐effects on targeted protein production and simultaneous integration of glucoamylase landing sites into the disrupted gene locus such as protease regulator ( prtT ) in an ATP‐dependent DNA helicase II subunit 1 ( kusA or ku70 ) ‐ deletion strain. Multiple copies of the PatE transgene expression cassette were introduced by CRISPR‐Cas9‐mediated insertion. The purified PatE was further used for structural and functional studies, and the technique laid the foundation for elevating the overall production of various proteins or chemicals in those industrially important fungi.

59 BASIC BIOLOGICAL SCIENCES↗

Proximal remote sensing: an essential tool for bridging the gap between high‐resolution ecosystem monitoring and global ecology

Summary A new proliferation of optical instruments that can be attached to towers over or within ecosystems, or ‘proximal’ remote sensing, enables a comprehensive characterization of terrestrial ecosystem structure, function, and fluxes of energy, water, and carbon. Proximal remote sensing can bridge the gap between individual plants, site‐level eddy‐covariance fluxes, and airborne and spaceborne remote sensing by providing continuous data at a high‐spatiotemporal resolution. Here, we review recent advances in proximal remote sensing for improving our mechanistic understanding of plant and ecosystem processes, model development, and validation of current and upcoming satellite missions. We provide current best practices for data availability and metadata for proximal remote sensing: spectral reflectance, solar‐induced fluorescence, thermal infrared radiation, microwave backscatter, and LiDAR. Our paper outlines the steps necessary for making these data streams more widespread, accessible, interoperable, and information‐rich, enabling us to address key ecological questions unanswerable from space‐based observations alone and, ultimately, to demonstrate the feasibility of these technologies to address critical questions in local and global ecology.

Plant Sciences↗

Using block-copolymer nanolithography as a tool to sensitively evaluate variation in chemical dry etching rates of semiconductor materials with sub-5 nm resolution

Ion implantation is a robust and established method to customize the electronic properties of Si. However, fabricating doped, ultrafine semiconductor nanostructures can be challenging. Ion implantation has well-established effects on the dry etch rates of Si, which becomes increasingly consequential as the target dimension shrinks below a few tens of nanometers. While dry etching arrays of block copolymer-templated nanoscale holes (pitch = 37.5 nm, diameter ~25 nm) into p-type, n-type, and undoped Si, we observed that the lateral etch rate was notably larger for the n-type regions than p-type or undoped regions. By doing image analyses on high resolution electron micrographs of the nanostructured hole arrays, we were able to extract the porosity and average radii of the holes with subnanometer sensitivity and compare the relative etch rates between different doping conditions. We found that degenerately doped n-type silicon consistently etches between approximately 17% and 27% faster in the lateral direction than p-type Si, resulting in significantly larger porosity and, consequently, less mechanical stability. Here, we demonstrate that top-down dimensional analysis of a densely packed porous nanostructure is a robust method for assessing extremely small differences in the lateral, chemical etch rate of doped Si to a degree of sensitivity that was previously unachievable. The minute, dense-packed nature of block copolymer self-assembled nanostructures is shown to be ideal for this application. This proposed method could be useful for designing fabrication processes for heterogeneous nanostructures, as slight dry etch rate variations that may be within process tolerance at the micrometer-scale appear to have nontrivial consequences at the nanometer scale.

42 ENGINEERING↗

Using AI tools to analyze periodic phenomena

Here, in this report, we describe how students can use natural language to prompt ChatGPT to conduct the analysis of complex periodic acceleration data collected using their smartphones. Students may use this approach to characterize human physiological tremor frequency. Students can choose to use their own data, or, for privacy purposes, use an anonymized set of data provided to them.

Klay, Jennifer L. [California Polytechnic State Un↗