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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 73 records · Page 4

Commercial Off-the-Shelf Flexible Contact Stress Sensor System: Design Thinking and Systems Engineering Assignment

NNSA has a need to measure the contact stress over long-term durations with minimal impact on the element of interest. The sensor and package should have a small footprint, thin, flexible, modular, and preferably commercially available. There exists an opportunity to leverage expertise within LLNL in sensor development to provide a minimally invasive contact stress sensing solution for NNSA and potentially external customers.

42 ENGINEERING↗

Packaging of an 8-kV Silicon Carbide Diode Module with Double-Side Cooling and Sintered-Silver Joints

Packaging innovations are needed for medium-voltage wide bandgap power semiconductor modules to enable their adaptation in grid applications. A unique challenge for packaging medium-voltage power modules is managing the trade-off between insulation demand and heat dissipation. The focus of this work was on developing a packaging innovation that improves the module heat dissipation and offers more flexibility to its insulation design. Two strategies were explored for the packaging of an 8-kV SiC diode rectifier module:(1) double-side cooling and (2) sintered-silver bonding. Double-side cooling was realized by using short metal posts rather than long and thin wire bonds for device interconnection, forming a low-profile package with devices sandwiched between two insulated metal substrates. Sintered-silver bonding enabled the devices to function reliably at over 250 °C. Simulations of the packaged module showed a low interconnect inductance of 2.67 nH and a 50% less heat transfer coefficient required to cool the chips. Prototypes of the module were fabricated, and preliminary electrical testing results validated the package design.

27 ARPA - Advanced Research Projects Agency-Energy↗

An Organic, Direct Bonded Copper, Multi-Layered, Ultra-Low Inductance Package for High-Power UWBG MOSFETs

The most common metalized substrates used in high-power switching packages consist of a ceramic layer such as Aluminum Nitride (AlN) sandwiched between two copper layers. Ceramic substrates are used because it has the key characteristic of having high dielectric strength while being thermally conductive. A large drawback to ceramic substrates is that they do not allow for a multi-layered circuit design. By replacing the traditional ceramic substrate with organic direct bonded copper (ODBC) we can open a wide range of possibilities when it comes to power module layout such as multi-layered circuits and double-sided cooling. Both benefits are critical while packaging high-performance Gallium Oxide (Ga2O3) MOSFETs. Because of Ga2O3's relatively poor thermal conductivity, a double-sided cooled package becomes necessary. Therefore, the use of ODBC provides the flexibility to fabricate copper traces carrying much higher currents, and by creating a multi-layered package, we can drastically reduce the parasitic inductance inside the power module. Achieving lower parasitic inductance is critical for an ultra-fast Ga2O3 package to avoid excessive voltage overshoot and ringing. Using ODBC, we have designed novel packages capable of handling the challenges presented by fast Ga2O3 switching. Using multi-physics modeling software, we can validate our design before building the prototype. Due to the simple process parameters needed to work with ODBC, we can rapidly create prototypes without using external vendors. This flexibility allows us to quickly design, build, and validate highly complex switching power modules to accommodate next generation, Ga2O3 switching devices.

ADVANCED PROPULSION SYSTEMS,ENGINEERING↗

Packaging Development for a 1200V SiC BiDFET Switch Using Highly Thermally Conductive Organic Epoxy Laminate

A novel 1.2 kV/10A, 4H-SiC monolithic, bidirectional switch has been developed for use in cycloconverter applications to facilitate high-frequency direct AC-to-AC power conversion and enables new power converter topologies. A new packaging solution, utilizing a 100 µm flexible polyimide organic laminate substrate is developed to mitigate thermo-mechanical stress during power cycling and enable smaller form factor and lower cost. Multiphysics simulations and static tests were conducted to show performance characterization of the module and compare it against metallic substrates. A new organic laminate epoxy resin composite dielectric (ERCD) is also evaluated for superior thermal performance and shows 63% reduction in junction to case resistance compared to DBC substrates.

Silicon Carbide, Bi-directional switch, BiDFET, MO↗

LIBlib v0.1.0

LIBlib is a Python 2 / Python 3 software package (library), built on top of the PyGDH package, for relatively simple and highly flexible implementation of macrohomogenous lithium ion battery models.

Higa, Kenneth↗

Development and verification of the pyIsoDep depletion package for nuclear thermal propulsion reactors

Nuclear thermal propulsion technology is currently being developed by the National Air and Space Administration for future manned Mars missions. There are multiple on-going activities to develop and enhance computational capabilities, single- and multi-physics, to advance the readiness level of this technology. The prediction of short-lived fission products is crucial to understand the reactivity penalty and the decay heat production during the different burnout stages of the vehicle. Generally, the solution entails coupled neutronic-depletion analysis. However, such simulations are somewhat expensive, especially if the duration of each engine burn is to be optimized. Therefore, there is a need to complement such high-fidelity techniques with time-efficient alternatives that do not require the sequential neutronic and depletion analysis. This paper details the methods and capabilities of pyIsoDep, an open-source code used for depletion analysis of nuclear thermal propulsion reactors. The package is general, in principle, and thus can be applied to any fission system, and can potentially be extended for fusion systems. The package was developed to provide a flexible and efficient alternative to pre-existing higher order depletion codes that could integrate well into mission and transient analysis of nuclear thermal propulsion reactors. Finally, this paper presents a validation and verification of pyIsoDep against analytical and Serpent-generated solutions. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Statistical Mechanics on Lattices (smol) v0.0.1

smol is a Python implementation of the Cluster Expansion Method and extensions of this methodology; which is used to fit applied lattice models from first principle calculations for subsequent use in Monte Carlo simulations for computing thermodynamic and statistical properties of atomic configuration. smol has a several notable advantages over other similar software packages. The first being its Python implementation which makes it easy to use even for users with little software and coding skills. Despite being implemented in Python, essential Monte Carlo routines are implemented in Cython such that performance is not compromised and is competitive even to similar software implemented in C/C++. Furthermore, the package has specific functionality for handling complex ionic materials (such as cathodes and electrolytes) that is not readily available in other packages. Lastly, the software has a flexible and modular design with the intention of making it fast and efficient to develop and extend the methodology.

Barroso-Luque, Luis↗

Matilda v1.0: An R package for probabilistic climate projections using a reduced complexity climate model

A primary advantage to using reduced complexity climate models (RCMs) has been their ability to quickly conduct probabilistic climate projections, a key component of uncertainty quantification in many impact studies and multisector systems. Providing frameworks for such analyses has been a target of several RCMs used in studies of the future co-evolution of the human and Earth systems. In this paper, we present Matilda, an open-science R software package that facilitates probabilistic climate projection analysis, implemented here using the Hector simple climate model in a seamless and easily applied framework. The primary goal of Matilda is to provide the user with a turn-key method to build parameter sets from literature-based prior distributions, run Hector iteratively to produce perturbed parameter ensembles (PPEs), weight ensembles for realism against observed historical climate data, and compute probabilistic projections for different climate variables. This workflow gives the user the ability to explore viable parameter space and propagate uncertainty to model ensembles with just a few lines of code. The package provides significant freedom to select different scoring criteria and algorithms to weight ensemble members, as well as the flexibility to implement custom criteria. Additionally, the architecture of the package simplifies the process of building and analyzing PPEs without requiring significant programming expertise, to accommodate diverse use cases. We present a case study that provides illustrative results of a probabilistic analysis of mean global surface temperature as an example of the software application.

54 ENVIRONMENTAL SCIENCES↗

PyGDH: Python Grid Discretization Helper

Mathematical models expressed in the form of discretized equations play an important role inmany scientific disciplines. In our experience, few domain scientists have sufficient backgroundin numerical computing (or the time required to acquire such a background) to use manyflexible and powerful but complex open source packages, such as FEniCS (Alnæs et al., 2015)and OpenFOAM (The OpenFOAM Foundation Ltd, n.d.). Many user-friendly open sourcepackages, such as FiPy (J. E. Guyer & Warren, 2009), and many commercial packages, suchas COMSOL Multiphysics (COMSOL AB, n.d.) and Simcenter STAR-CCM+ (Siemens DigitalIndustries Software, n.d.), provide limited flexibility in the equations that users can express.Additionally, the use of commercial packages, which by nature do not perform calculationstransparently, can hinder reproducibility, which is vital to the scientific process. PyGDH(“pigged”) is a Python 2 / Python 3 (Python Software Foundation, 1991–2020) package thatis meant to be accessible to scientists who might not be specialists in scientific computing,while approaching the level of flexibility associated with writing dedicated programs tailoredto solving specific problems. The PyGDH User’s Guide provides detailed instructions forcreating numerical models, including a brief introduction to necessary command line andPython (Python Software Foundation, 1991–2020) skills, and discussions of discretization andvalidation. Note that PyGDH emphasizes flexibility and simplicity over performance, and wasnot designed for high-performance applications or models describing complex spatial domains.

97 MATHEMATICS AND COMPUTING↗

The impact of energy-efficiency upgrades and other distributed energy resources on a residential neighborhood-scale electrification retrofit

We report ambitious targets for carbon emissions reductions are highlighting new challenges for electrification strategies, leading to an increased focus on building load flexibility and energy management to complement the variability inherent in renewable energy generation. Over the next decade millions of existing homes could undergo electrification retrofits, and there is an urgent need to understand the potential impacts of electrifying major residential loads such as water and space heating on community load characteristics, resident energy bills, and the utility's distribution system. Behind-the-meter distributed energy resources (DERs), including efficiency measures, photovoltaics (PV), battery storage, managed electric vehicle (EV) charging, and controls such as home energy management systems (HEMS), can significantly alter a neighborhood's load profile and provide benefits to both the residents and the grid. We present a novel approach to characterizing the impact of a hypothetical neighborhood-scale residential retrofit program on individual homes' energy use profiles, associated utility bills, and the local distribution system. We modeled a mixed-fuel community of 30 single-family homes in Denver, Colorado, and compared the effects of retrofit scenarios ranging from conventional energy-efficiency upgrades to full electrification with and without more advanced DER technologies. We analyzed which packages of DERs most reliably enable demand flexibility in response to a time-of-use (TOU) rate for this and similar neighborhoods. Our buildings-to-grid co-simulation framework includes a generic secondary distribution feeder model to capture voltage profiles, transformer loading, and other grid impacts in each case. We also calculated the carbon emissions associated with energy use in the community. The methodology developed here can be broadly applied to community-scale beneficial electrification studies in other regions, climates, utility infrastructures, and building typologies to make specific, targeted recommendations based on quantified projections of energy demand in any given community. Our findings indicate that residential electrification can be achieved without negatively impacting the monthly utility bill, and that a combination of conventional energy-efficiency measures, PV, battery, controls, and managed EV charging to maximize a community's demand flexibility is a promising strategy. Adding DERs (especially PV) as part of efficient electrification produces much bigger savings than efficient electrification without DERs. A key barrier is that upgrades require upfront costs, and modest utility bill savings result in long payback periods.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

TEQUILA: a platform for rapid development of quantum algorithms

Variational quantum algorithms are currently the most promising class of algorithms for deployment on near-term quantum computers. In contrast to classical algorithms, there are almost no standardized methods in quantum algorithmic development yet, and the field continues to evolve rapidly. As in classical computing, heuristics play a crucial role in the development of new quantum algorithms, resulting in a high demand for flexible and reliable ways to implement, test, and share new ideas. In this paper, inspired by this demand, we introduce TEQUILA, a development package for quantum algorithms in PYTHON, designed for fast and flexible implementation, prototyping and deployment of novel quantum algorithms in electronic structure and other fields. TEQUILA operates with abstract expectation values which can be combined, transformed, differentiated, and optimized. On evaluation, the abstract data structures are compiled to run on state of the art quantum simulators or interfaces.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Colorado Residential Retrofit Energy District (CoRRED) Phase I: Final Modeling Results

Electrification of buildings and transportation coupled with increased deployment of distributed energy resources (DERs) has been identified as a key step toward meeting emissions reduction goals across the U.S. Examples of pilot projects that feature innovative, 'smart' electric neighborhoods are largely focused on new construction projects, but there is a need to address the millions of existing homes so that they too may accommodate cleaner yet variable energy production in ways that benefit both the utility grid and the homes' residents. The Colorado Residential Retrofit Energy District (CoRRED) project used building and grid co-simulation tools to model an advanced energy district demonstration in an existing residential neighborhood in Denver, Colorado, and explored how existing building and utility infrastructures can be enhanced with combinations of traditional energy-efficiency retrofit measures and integration of solar panels and other DER technologies to provide better affordability and reliability. We analyzed which packages of DERs most reliably enable demand flexibility in response to a time-of-use (TOU) rate. Our results clearly indicate that incorporating DERs into efficient electrification produces much bigger utility bill savings on an annual basis than efficient electrification without DERs. While electrifying a neighborhood will increase the maximum load, batteries and solar panels can reduce load during peak hours so that the community can be a net producer during peak periods. A remaining challenge is to overcome first cost barriers to implementing energy-efficiency and DER technologies, as modest utility bill savings require long payback periods that are not practical for most homeowners.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

An Intelligent Adaptable Monitoring Package. Final Report

The “Intelligent Adaptable Monitoring Package” project was a four-year effort that demonstrated the feasibility of integrated sensing packages at tidal and wave energy sites. Such integration is generally required by the breadth of sensors required to understand environmental effects at marine energy sites and the operational difficulty of deploying, maintaining, and recovering such sensors. Over the course of the project, the Adaptable Monitoring Package (AMP) was deployed in multiple settings, each corresponding to a project budget period: - Budget Period 1: Demonstration of cabled deployment at Pacific Northwest National Laboratory’s Marine Science Laboratory. The deployment highlighted AMP hardware endurance over a 4-month deployment in a tidally-dominated environment and laid the groundwork for machine learning algorithms to detect and classify targets present in active sonar data. - Budget Period 2: Demonstration of an autonomous deployment at PacWave South off the coast of Newport, Oregon. The deployment highlighted the stability of AMP hardware and software, with the autonomous package collecting data on a duty cycle over a 1.5-month deployment. - Budget Period 3: Demonstration of an autonomous deployment powered by a wave energy converter at the U.S. Navy’s Wave Energy Test Site. The deployment highlighted the potential of wave energy to power ocean observatories and led to the development of machine learning algorithms to detect and classify targets in optical camera data. In aggregate, this project’s greatest success was demonstrating the AMP’s flexibility in a range of deployment scenarios. Each budget period represented a “first of a kind” demonstration of integrated instrumentation – cabled AMP, autonomous AMP, wave-energy powered AMP – and each deployment helped to identify and set goals for the next. Further, despite the exploratory nature of these deployments, each one achieved high system up-time and proved that flexible integration of multiple sensors in a single package represents a viable strategy for marine energy environmental monitoring. The key lessons learned from the project are: - Without continuous power, either from a shore cable or in situ source, many of the benefits of integration are lost (If continuous power is not available, the ability to detect rare events is lost, as is the ability to minimize the risk of behavioral changes through adaptive sensing. However, even on a duty cycle, there is still value in being able to acquire synchronous data from multiple sensors.); and - Observations from a moving platform present substantially greater data processing challenges than those from stationary platforms. Finally, these deployments also demonstrate an important truth: successful integration alone does not guarantee that relevant data are collected. To grow the knowledge base about environmental interactions with marine energy converters, integrated systems, like the AMP, need to include the right sensor mix and connect the data pipelines to effective processing algorithms. These deployments establish a strong foundation for future collaborations with the environmental research community: not only to understand the environmental effects of marine energy, but also to improve our general ability to study life in the sea.

16 TIDAL AND WAVE POWER↗

Recycling of a post-industrial printed multilayer plastic film containing polyurethane inks by solvent-targeted recovery and precipitation

The recently reported Solvent-Targeted Recovery And Precipitation (STRAP) strategy is used to deconstruct multilayer plastic packaging films into their constituent resins by selective polymer dissolution. To broaden the applicability of STRAP, we demonstrate the process with a flexible post-industrial printed multilayer plastic film used for food packaging. The material was a reverse printed film composed of polyethylene (PE), ethylene vinyl alcohol (EVOH), polyethylene terephthalate (PET), and polyurethane (PU)-based inks. Removal of all colors was observed with biomass-derived gamma-valerolactone (GVL) and the recovered polymers possessed comparable properties to the corresponding virgin resins. A technoeconomic analysis indicates that this STRAP process could be economically feasible at a processing capacity of 6,000 tons per year. Furthermore, the production of plastic films with materials recovered by this STRAP process can have a lower climate change impact than the production of films from virgin polymers.

54 ENVIRONMENTAL SCIENCES↗

The Blending ToolKit: A simulation framework for evaluation of galaxy detection and deblending

We present an open source Python library for simulating overlapping (i.e., blended) images of galaxies and performing self-consistent comparisons of detection and deblending algorithms based on a suite of metrics. The package, named Blending Toolkit (BTK), serves as a modular, flexible, easy-to-install, and simple-to-use interface for exploring and analyzing systematic effects related to blended galaxies in cosmological surveys such as the Vera Rubin Observatory Legacy Survey of Space and Time (LSST). BTK has three main components: (1) a set of modules that perform fast image simulations of blended galaxies, using the open source image simulation package GalSim; (2) a module that standardizes the inputs and outputs of existing deblending algorithms; (3) a library of deblending metrics commonly defined in the galaxy deblending literature. In combination, these modules allow researchers to explore the impacts of galaxy blending in cosmological surveys. Additionally, BTK provides researchers who are developing a new deblending algorithm a framework to evaluate algorithm performance and make principled comparisons with existing deblenders. BTK includes a suite of tutorials and comprehensive documentation. The source code is publicly available on GitHub at https://github.com/LSSTDESC/BlendingToolKit.

79 ASTRONOMY AND ASTROPHYSICS↗

Livermore tomography tools: Accurate, fast, and flexible software for tomographic science

Livermore Tomography Tools (LTT) is a customizable scientific software package that enables a broad range of research and development efforts into computed tomography (CT). Here, it was developed to process x-ray and neutron CT data accurately and rapidly from raw detector counts to reconstructed volumes with the flexibility to handle many special cases. LTT fulfills long-term CT software goals to provide quantitatively accurate results reported in physical units (e.g., mm -1 or cm -1 ) while exploiting all available computational advantages to maximize speed. Written in C/C++ with support for multiple CPUs and GPUs, LTT runs on many computing platforms (Linux/Unix, Windows, and Mac; laptops to supercomputers). As a result, LTT can:process data acquired from various custom-built and commercially available CT scanners, model and simulate x-ray and neutron interactions to encourage algorithm prototyping, and allow for rapid insertion of the latest algorithms.We describe LTT’s software architecture, user interfaces, and its 88 algorithms (as of this writing) for pre-processing, reconstruction, post-processing, and simulation that support many scanner geometries (parallel-, fan-, cone-beam, and custom). Several applications are presented that illustrate LTT’s accuracy, speed, and flexibility relative to other solutions.

36 MATERIALS SCIENCE↗

ftmsRanalysis: An R package for exploratory data analysis and interactive visualization of FT-MS data

The high-resolution and mass accuracy of Fourier transform mass spectrometry (FT-MS) has made it an increasingly popular technique for discerning the composition of soil, plant and aquatic samples containing complex mixtures of proteins, carbohydrates, lipids, lignins, hydrocarbons, phytochemicals and other compounds. Thus, there is a growing demand for informatics tools to analyze FT-MS data that will aid investigators seeking to understand the availability of carbon compounds to biotic and abiotic oxidation and to compare fundamental chemical properties of complex samples across groups. We present ftmsRanalysis, an R package which provides an extensive collection of data formatting and processing, filtering, visualization, and sample and group comparison functionalities. The package provides a suite of plotting methods and enables expedient, flexible and interactive visualization of complex datasets through functions which link to a powerful and interactive visualization user interface, Trelliscope. Example analysis using FT-MS data from a soil microbiology study demonstrates the core functionality of the package and highlights the capabilities for producing interactive visualizations.

97 MATHEMATICS AND COMPUTING↗