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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

High-temperature analysis of optical coupling using AlGaAs/GaAs LEDs for high-density integrated power modules

A low-temperature co-fired ceramic (LTCC)-based optocoupler design is demonstrated as a possible solution for optical isolation in high-density integrated power modules. The design and fabrication of LTCC based package are discussed. Commercially available aluminum gallium arsenide/gallium arsenide (AlGaAs/GaAs) double heterostructure is used both as emitter and photodetector in the proposed optocoupler. A detailed study on the electroluminescence and spectral response of the AlGaAs/GaAs structure is conducted at elevated temperatures. The material figure of merit parameter, D*, is calculated in the temperature range 77–800 K. The fabricated optocoupler is tested at elevated temperatures, and the results are presented.

42 ENGINEERING↗
DOE OSTI2020

Sensor Placement Optimization Software Applied to Site-Scale Methane-Emissions Monitoring

Advances in sensor technology have increased our ability to monitor a wide range of environments. However, even as the cost of sensors decline, only a limited number of sensors can be installed at any given site. The physical placement of sensors, along with the sensor technology and operating conditions, can have a large impact on our ability to adequately monitor environmental change. This paper introduces a new open-source Python package, called Chama, that determines optimal sensor placement and technology to improve a sensor network’s detection capabilities. Additionally, the methods are demonstrated using site-specific methane emission scenarios that capture uncertainty in wind conditions and emission characteristics. Mixed-integer linear programming formulations are used to determine sensor locations and detection thresholds that maximize detection of the emission scenarios. The optimized sensor networks consistently increase the ability to detect leaks, as compared to sensors placed near each potential emission source or along the perimeter of the site.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

An adaptive masking method for beam halo measurement by a digital micro mirror device

We report that in high intensity particle beams, irregularities in cathode emission, scattering effects, dark current and space charge forces can lead to a common phenomenon termed beam halo with associated emittance growth, beam loss and overall beam quality degradation. It is of fundamental interest and practical importance to precisely monitor such beam halo, which could offer valuable insights into the experimental strategy for the suppression of this undesired feature. A Digital Micro mirror Device (DMD) is a computer-controlled micro-electrical-mechanical system that contains a compact array of physically independent reflective mirrors. Using a standard DMD, we come up with an adaptive masking method for halo measurement, which demonstrates superior robustness and efficiency comparing to the conventional approaches as confirmed by simulation and experimental results. Our development includes an integrated package of hardware, software and a graphic user interface (GUI) that is robust and portable and can be applied as a beam halo diagnostic for electron guns or radiating charged particle beams in general.

43 PARTICLE ACCELERATORS↗
DOE OSTI2021

ORT: a workflow linking genome-scale metabolic models with reactive transport codes

Abstract Motivation Nutrient and contaminant behavior in the subsurface are governed by multiple coupled hydrobiogeochemical processes which occur across different temporal and spatial scales. Accurate description of macroscopic system behavior requires accounting for the effects of microscopic and especially microbial processes. Microbial processes mediate precipitation and dissolution and change aqueous geochemistry, all of which impacts macroscopic system behavior. As ‘omics data describing microbial processes is increasingly affordable and available, novel methods for using this data quickly and effectively for improved ecosystem models are needed. Results We propose a workflow (‘Omics to Reactive Transport—ORT) for utilizing metagenomic and environmental data to describe the effect of microbiological processes in macroscopic reactive transport models. This workflow utilizes and couples two open-source software packages: KBase (a software platform for systems biology) and PFLOTRAN (a reactive transport modeling code). We describe the architecture of ORT and demonstrate an implementation using metagenomic and geochemical data from a river system. Our demonstration uses microbiological drivers of nitrification and denitrification to predict nitrogen cycling patterns which agree with those provided with generalized stoichiometries. While our example uses data from a single measurement, our workflow can be applied to spatiotemporal metagenomic datasets to allow for iterative coupling between KBase and PFLOTRAN. Availability and implementation Interactive models available at https://pflotranmodeling.paf.subsurfaceinsights.com/pflotran-simple-model/. Microbiological data available at NCBI via BioProject ID PRJNA576070. ORT Python code available at https://github.com/subsurfaceinsights/ort-kbase-to-pflotran. KBase narrative available at https://narrative.kbase.us/narrative/71260 or static narrative (no login required) at https://kbase.us/n/71260/258. Supplementary information Supplementary data are available at Bioinformatics online.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

A High-Power Density Segmented Traction Drive Inverter

High power density is one of the requirements for traction drive inverters for meeting increasing demand for higher power and performance electrical vehicles (EV). This paper presents design and preliminary experimental results for a 100 kW high-power density inverter for EV traction drive applications. The inverter design was based on the segmented inverter topology that can significantly reduce the inverter DC filter capacitor and employs low-profile planar double-sided cooled SiC MOSFET-based power modules, compact mini-channel heat sinks with fin-profile optimized using genetic-algorithms, and high-ripple current capacitors. The design produced a compact inverter package with a total volume less than 1 litter, exceeding the power density goal of 100 kW/L. Experimental results are included to demonstrate the cooling and electrical performance.

Su, Gui-Jia↗
DOE OSTI2021

Omics-to-Reactive-Transport (ORT): A workflow linking genome-scale metabolic models with reactive transport codes

Motivation: Nutrient and contaminant behavior in the subsurface are governed by multiple coupled hydrobiogeochemical processes which occur across different temporal and spatial scales. Accurate description of macroscopic system behavior requires accounting for the effects of microscopic and especially microbial processes. Microbial processes mediate precipitation and dissolution and change aqueous geochemistry, all of which impacts macroscopic system behavior. As `omics data describing microbial processes is increasingly affordable and available, novel methods for using this data quickly and effectively for improved ecosystem models are needed. Results: We propose a workflow (`Omics to Reactive Transport – ORT) for utilizing metagenomic and environmental data to describe the effect of microbiological processes in macroscopic reactive transport models. This workflow utilizes and couples two open-source software packages: KBase (a software platform for systems biology) and PFLOTRAN (a reactive transport modeling code). We describe the architecture of ORT and demonstrate an implementation using metagenomic and geochemical data from a river system. Our demonstration uses microbiological drivers of nitrification and denitrification to predict nitrogen cycling patterns which agree with those provided with generalized stoichiometries. While our example uses data from a single measurement, our workflow can be applied to spatiotemporal metagenomic datasets to allow for iterative coupling between KBASE and PFLOTRAN. Live, interactive models, which incorporate the results from this narrative into a PFLOTRAN simulation, are available (without login) at https://pflotranmodeling.paf.subsurfaceinsights.com/pflotran-simple-model/.

Rubinstein, Rebecca L↗
DOE OSTI2020

High performance Nb/TiNi nanocomposites produced by packaged accumulative roll bonding

Taking full advantage of intrinsic high strength of nano-reinforcements has been proven difficult in a composite until the concept of strain matching was experimental verified in a nanowire Nb/TiNi in-situ composite, which was obtained via solidifying eutectic Nb/TiNi and subsequent severe wire drawing. However, the volume fraction of the nano-reinforcement was dictated by eutectic reaction, which severely limited the development of high-performance composites. Here, the martensitic transformation nanocomposites were successfully acquired with increased volume fraction and changeable morphology of the nano-reinforcement through hot packaged ARB (PARB) and subsequent wire drawing. The nano-reinforcement with lamellar configuration in the composite could exhibit a large lattice strain of similar to 3.8%, which demonstrated the applicability and effectiveness of the strain matching principle in nano-lamellar composite. The obtained composites show a yield strength over 2.0 GPa and a quasi-linear elastic strain as larger as similar to 6.5% with adjustable apparent elastic modulus from 30 to 50 GPa.

42 ENGINEERING↗
DOE OSTI2023

Engineering-Scale Integrated Energy System Data Projection Demonstration via the Dynamic Energy Transport and Integration Laboratory

The objective of this study is to demonstrate and validate the Dynamic Energy Transport and Integration Laboratory (DETAIL) preliminary scaling analysis using Modelica language system-code Dymola. The DETAIL preliminary scaling analysis includes a multisystem integral scaling package between thermal-storage and hydrogen-electrolysis systems. To construct the system of scaled equations, dynamical system scaling (DSS) was applied to all governing laws and closure relations associated with the selected integral system. The existing Dymola thermal-energy distribution system (TEDS) facility and high-temperature steam electrolysis (HTSE) facility models in the Idaho National Laboratory HYBRID repository were used to simulate a test case and a corresponding scaled case for integrated system HYBRID demonstration and validation. The DSS projected data based on the test-case simulations and determined scaling ratios were generated and compared with scaled case simulations. The preliminary scaling analysis performance was evaluated, and scaling distortions were investigated based on data magnitude, sequence, and similarity. The results indicated a necessity to change the normalization method for thermal storage generating optimal operating conditions of 261 kW power and mass flow rate of 6.42 kg/s and the possibility of reselecting governing laws for hydrogen electrolysis to improve scaling predictive properties. To enhance system-scaling similarity for TEDS and HTSE, the requirement for scaling validation via physical-facility demonstration was identified.

08 HYDROGEN↗
DOE OSTI2025

Blending Compostable Plastics for Packaging Applications

Non-sustainable packaging materials (polymers) are a large portion of the increasing amount of plastic waste that become environmental pollutants. While many biodegradable or compostable polymers have been developed in recent years, most fail to compete with the non-sustainable polymers dominating the market, due to lack of certain desired properties, such as thermal (high melt temperature) and mechanical (high ductility) performance. For example, the popular compostable polymer polylactic acid (PLLA) has a high melt temperature but is very brittle. Another polymer, poly(d-valerolactone) (PVL) demonstrates great ductility but has a very low melt temperature. By blending PLLA and PVL, there is an opportunity to create a new biodegradable material with synergistic desired properties for packaging applications. In this study, we produce several (9) physical blends of PVL and PLLA with varying compositions of the two polymers while applying three different materials to make them more compatible (compatibilizers). We test the success of compatibilization by scanning electron microscopy (SEM), mechanic testing (strain at break) and differential scanning calorimetry (melting temperature). Overall, we highlight several promising materials with high compatibility and desired thermomechanical properties for sustainable packaging. Ideally, these materials could help mitigate future plastic pollution in Colorado and beyond.

blending↗
DOE OSTI2020

Improving Heat Conduction of Insulated Metal Substrate with Thermal Pyrolytic Graphite Core for SiC Power Module Packaging

TPG-core IMS concept was jointly explored in this study. Integrating high thermally conductive TPG graphite core into IMS is expected to simultaneously achieve high thermal conductivity from TPG and electrical functionalities from IMS. Nearly 2x thermal conductivity and 30% weight saving was demonstrated on TPG-core IMS compared to conventional Cu-core IMS. Significant junction temperature reduction (11°C) in steady state and power cycling was revealed by the thermal analysis as the result of improved thermal spreading in plane and through the thickness. The study also proved the manufacturability and compatibility of this TPG-core IMS structure to the existing IMS production and power module assembling. Finally, the integration of TPG and IMS paves a new packaging route to increase heat load, improve reliability, simplify module design and reduce assembling cost and number of steps.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Simultaneous optimal system and controller design for multibody systems with joint friction using direct sensitivities

Abstract Real-world multibody systems are often subject to phenomena like friction, joint clearances, and external events. These phenomena can significantly impact the optimal design of the system and its controller. This work addresses the gradient-based optimization methodology for multibody dynamic systems with joint friction using a direct sensitivity approach. The Brown–McPhee model has been used to characterize the joint friction in the system. This model is suitable for the study due to its accuracy for dynamic simulation and its compatibility with sensitivity analysis. This novel methodology supports codesign of the multibody system and its controller, which is especially relevant for applications like robotics and servo-mechanical systems, where the actuation and design are highly dependent on each other. Numerical results are obtained using a software package written in Julia with state-of-the-art libraries for automatic differentiation and differential equations. Three case studies are provided to demonstrate the attractive properties of simultaneous optimal design and control approach for certain applications.

Verulkar, Adwait↗
DOE OSTI2020

Electron transport in gaseous detectors with a Python-based Monte Carlo simulation code

Understanding electron drift and diffusion in gases and gas mixtures is a topic of central importance for the development of modern particle detection instrumentation. The industry-standard MagBoltz code has become an invaluable tool during its 20 years of development, providing capability to solve for electron transport (‘swarm’) properties based on a growing encyclopedia of built-in collision cross sections. We have made a refactorization of this code from FORTRAN into Cython, and studied a range of gas mixtures of interest in high energy and nuclear physics. The results from the new open source PyBoltz package match the outputs from the original MagBoltz code, with comparable simulation speed. An extension to the capabilities of the original code is demonstrated, in implementation of a new Modified Effective Range Theory interface. We hope that the versatility afforded by the new Python code-base will encourage continued use and development of the MagBoltz tools by the particle physics community.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Deep learning for NLTE spectral opacities

Computer simulations of high energy density science experiments are computationally challenging, consisting of multiple physics calculations including radiation transport, hydrodynamics, atomic physics, nuclear reactions, laser–plasma interactions, and more. To simulate inertial confinement fusion (ICF) experiments at high fidelity, each of these physics calculations should be as detailed as possible. However, this quickly becomes too computationally expensive even for modern supercomputers, and thus many simplifying assumptions are made to reduce the required computational time. Much of the research has focused on acceleration techniques for the various packages in multiphysics codes. In this work, we explore a novel method for accelerating physics packages via machine learning. The non-local thermodynamic equilibrium (NLTE) package is one of the most expensive calculations in the simulations of indirect drive inertial confinement fusion, taking several tens of percent of the total wall clock time. We explore the use of machine learning to accelerate this package, by essentially replacing the physics calculation with a deep neural network that has been trained to emulate the physics code. Overall, we demonstrate the feasibility of this approach on a simple problem and perform a side-by-side comparison of the physics calculation and the neural network inline in an ICF Hohlraum simulation. We show that the neural network achieves a 10× speed up in NLTE computational time while achieving good agreement with the physics code for several quantities of interest.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Numerical methods and hypoexponential approximations for gamma distributed delay differential equations

Abstract Gamma distributed delay differential equations (DDEs) arise naturally in many modelling applications. However, appropriate numerical methods for generic gamma distributed DDEs have not previously been implemented. Modellers have therefore resorted to approximating the gamma distribution with an Erlang distribution and using the linear chain technique to derive an equivalent system of ordinary differential equations (ODEs). In this work, we address the lack of appropriate numerical tools for gamma distributed DDEs in two ways. First, we develop a functional continuous Runge–Kutta (FCRK) method to numerically integrate the gamma distributed DDE without resorting to Erlang approximation. We prove the fourth-order convergence of the FCRK method and perform numerical tests to demonstrate the accuracy of the new numerical method. Nevertheless, FCRK methods for infinite delay DDEs are not widely available in existing scientific software packages. As an alternative approach to solving gamma distributed DDEs, we also derive a hypoexponential approximation of the gamma distributed DDE. This hypoexponential approach is a more accurate approximation of the true gamma distributed DDE than the common Erlang approximation but, like the Erlang approximation, can be formulated as a system of ODEs and solved numerically using standard ODE software. Using our FCRK method to provide reference solutions, we show that the common Erlang approximation may produce solutions that are qualitatively different from the underlying gamma distributed DDE. However, the proposed hypoexponential approximations do not have this limitation. Finally, we apply our hypoexponential approximations to perform statistical inference on synthetic epidemiological data to illustrate the utility of the hypoexponential approximation.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Materials Learning Algorithms (MALA): Scalable machine learning for electronic structure calculations in large-scale atomistic simulations

We present the Materials Learning Algorithms (MALA) package, a scalable machine learning framework designed to accelerate density functional theory (DFT) calculations suitable for large-scale atomistic simulations. Using local descriptors of the atomic environment, MALA models efficiently predict key electronic observables, including local density of states, electronic density, density of states, and total energy. The package integrates data sampling, model training and scalable inference into a unified library, while ensuring compatibility with standard DFT and molecular dynamics codes. We demonstrate MALA's capabilities with examples including boron clusters, aluminum across its solid-liquid phase boundary, and predicting the electronic structure of a stacking fault in a large beryllium slab. Scaling analyses reveal MALA's computational efficiency and identify bottlenecks for future optimization. With its ability to model electronic structures at scales far beyond standard DFT, MALA is well suited for modeling complex material systems, making it a versatile tool for advanced materials research.

Density functional theory↗
DOE OSTI2022

Foot-and-Mouth Disease Virus Interserotypic Recombination in Superinfected Carrier Cattle

Viral recombination contributes to the emergence of novel strains with the potential for altered host range, transmissibility, virulence, and immune evasion. For foot-and-mouth disease virus (FMDV), cell culture experiments and phylogenetic analyses of field samples have demonstrated the occurrence of recombination. However, the frequency of recombination and associated virus–host interactions within an infected host have not been determined. We have previously reported the detection of interserotypic recombinant FMDVs in oropharyngeal fluid (OPF) samples of 42% (5/12) of heterologously superinfected FMDV carrier cattle. The present investigation consists of a detailed analysis of the virus populations in these samples including identification and characterization of additional interserotypic minority recombinants. In every animal in which recombination was detected, recombinant viruses were identified in the OPF at the earliest sampling point after superinfection. Some recombinants remained dominant until the end of the experiment, whereas others were outcompeted by parental strains. Genomic analysis of detected recombinants suggests host immune pressure as a major driver of recombinant emergence as all recombinants had capsid-coding regions derived from the superinfecting virus to which the animals did not have detectable antibodies at the time of infection. In vitro analysis of a plaque-purified recombinant virus demonstrated a growth rate comparable to its parental precursors, and measurement of its specific infectivity suggested that the recombinant virus incurred no penalty in packaging its new chimeric genome. These findings have important implications for the potential role of persistently infected carriers in FMDV ecology and the emergence of novel strains.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Recent Developments at the U.S. Navy Wave Energy Test Site.

The U.S. Navy’s Wave Energy Test Site (WETS) in Hawaii has hosted two wave energy conversion (WEC) devices since its June 2015 commissioning – the Fred. Olsen BOLT Lifesaver and the Northwest Energy Innovations (NWEI) Azura – each for two deployments. Several additional devices will be tested in the coming years, beginning with the Ocean Energy device in summer 2019. The Hawaii Natural Energy Institute (HNEI) provides research and logistics support to WETS. We will provide an overview of three major activities that we have recently undertaken in this capacity. First, we will discuss results from a project in which modifications were made to the hull and float of the Azura, aimed at improving power performance for a second WETS deployment. Second, HNEI undertook a redeployment of Lifesaver beginning in October 2018, with the dual intent of achieving improvements in reliability and power performance, while also conducting an important demonstration of the use of wave power for non-grid applications. HNEI partnered with the University of Washington to integrate their Adaptable Monitoring Package (AMP) into the hull of BOLT Lifesaver. Included for this deployment was a subsea inductive charging capability from WiBotic, Inc.. These systems are powered entirely by electricity generated by the Lifesaver itself. Finally, HNEI has undertaken design improvements for the deeper berth moorings at WETS, with principal engineering guidance from DNV GL. This has included extensive numerical analysis of strength and fatigue aimed at establishing moorings that can persist for as long as possible. The resulting design will be discussed.

Wave energy conversion devices, Alternative market↗
DOE OSTI2025

Thermal Optimization and Experimental Demonstration of a Silicon Carbide, Half-Bridge Power Module

This paper describes modeling and experimental work to design and demonstrate a silicon carbide (SiC), single-side-cooled power module. Two SiC metal-oxide-semiconductor field-effect transistors (MOSFET) were used for each switch position and packaged on a metalized ceramic substrate. Thermal modeling was first conducted to optimize the module packaging to minimize junction-to-fluid thermal resistance and device temperature variations. This procedure identified the optimal device placement and baseplate thickness to maximize thermal performance. A heat exchanger - incorporating impinging jets of water-ethylene glycol - was designed to cool the module's baseplate to minimize thermal resistance and pumping power. The heat exchanger used relatively low fluid velocities (<1.5 m/s) to minimize erosion-corrosion effects and relatively large fluid channel sizes (>=1 mm) to prevent clogging. The power module concept was fabricated, and experiments were conducted to measure its thermal performance. Direct current was used to power the module devices, and junction temperatures were measured via device temperature-sensitive parameters. The experimental results were found to be in good agreement with model predictions (within 2%) and yielded junction-to-fluid thermal resistance values as low as about 15 mm2 K/W at relatively low pumping power values. The results demonstrate the improved performance associated with jet impingement cooling and represent an improvement over existing channel-flow-type cold plates, which can enable improvements to power density and reliability.

36 MATERIALS SCIENCE↗