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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 883 records · Page 49
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Experimental validation of a co-simulation architecture for modeling whole-building and detailed electrical distribution performance

This article presents an experimental validation of a co-simulation architecture for simultaneously modeling whole-building energy performance and detailed building electrical distribution system performance. The co-simulation architecture consists of a whole-building energy model (EnergyPlus®) embedded within a Modelica-based building electrical distribution system library called the Building Electrical Efficiency Analysis Model (BEEAM) using the Functional Mock-up Interface standard. We validate the model using experimental data collected at a full-scale test cell within Lawrence Berkeley National Laboratory’s FLEXLAB® facility. In conclusion, we show that the co-simulation model accurately predicts the electrical, mechanical, and thermal performance of the test cell for typical loads with both an AC and a DC electrical distribution topology.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Improving energy performance metrics to maximize the benefits of disruptive technologies

Advances in appliance and equipment systems' technologies also cause changes in their technical characteristics that can affect energy consumption and associated greenhouse gas emissions. Energy performance evaluation methods that use testing and metrics can evolve to account for energy consumption contributed from new technological characteristics. However, there is no systematic effort to enable the advancement of test procedures and performance metrics to maximize the energy, climate, and financial benefits of disruptive technologies. Therefore, it is important for countries to regularly update their energy-efficiency policy programs, such as standards and labels, by improving test procedures and metrics to reflect the innovation in emerging technologies as well as to mitigate the risk of deploying obsolete technology. This paper shows how energy performance metrics have been improving in selected appliances and equipment and provides insights to design a systematic effort to improve metrics and test procedures at the speed of ongoing changes in technologies and markets.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Effects of short-term over-discharge cycling on the performance of commercial 21,700 lithium-ion cells and the identification of degradation modes

In this paper, short-term over-discharge cycling was performed on commercially available 21,700 lithium-ion cells to investigate its effects on cell performance; the degradation modes were also identified and analyzed in detail using both in-situ and ex-situ methods. Results show that observable capacity loss occurs when the cell is over-discharged to 112.5% depth of discharge. Moreover, the negative impact of the depth of discharge on cell performance (or cell aging) is more serious than the number of cycles, and continuous over-discharge cycling will accumulate such impact. The loss of Li inventory related to the decomposition and reformation of solid electrolyte interphase film is an important cause of the irreversible capacity loss/degradation of Li-ion cells during over-discharge cycling testing. Furthermore, the dissolution of copper current collector can greatly reduce the mechanical stability of the anode, and further, the deposition of Cu, the exfoliation and the cracking of active material particles can influence the transfer of ions and lead to the loss of Li inventory and the loss of active material within Li-ion cells. Additionally, when the depth of discharge exceeds 108.3%, deposition of Cu is observed on the ceramic-covered side of separators.

25 ENERGY STORAGE↗
DOE OSTI2020

End-to-end online performance data capture and analysis for scientific workflows

With the increased prevalence of employing workflows for scientific computing and a push towards exascale computing, it has become paramount that we are able to analyze characteristics of scientific applications to better understand their impact on the underlying infrastructure and vice-versa. Such analysis can help drive the design, development, and optimization of these next generation systems and solutions. Here, we present the architecture, integrated with existing well-established and newly developed tools, to collect online performance statistics of workflow executions from various, heterogeneous sources and publish them in a distributed database (Elasticsearch). Using this architecture, we are able to correlate online workflow performance data, with data from the underlying infrastructure, and present them in a useful and intuitive way via an online dashboard. We have validated our approach by executing two classes of real-world workflows, both under normal and anomalous conditions. The first is an I/O-intensive genome analysis workflow; the second, a CPU- and memory-intensive material science workflow. Based on the data collected in Elasticsearch, we are able to demonstrate that we can correctly identify anomalies that we injected. The resulting end-to-end data collection of workflow performance data is an important resource of training data for automated machine learning analysis.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Value of abstraction in performance assessment – When is a higher level of detail necessary?

In this study, different approaches in performance assessment (PA) of the long-term safety of a repository for radioactive waste were examined. This investigation was carried out as part of the DECOVALEX-2023 project, an international collaborative effort for research and model comparison. One specific task of the DECOVALEX-2023 project was the Salt Performance Assessment Modelling task (Salt PA), which aimed at comparing various models and methods employed in the performance assessment of deep geological repositories in salt. In the context of the Salt PA task, three distinct teams from SNL (United States), Quintessa Ltd (United Kingdom), and GRS (Germany) examined the consequences of employing different levels of abstractions when modelling the repository's geometry and implementing various features and processes, using the example of a simple hypothetical repository structure in domal salt. Each team applied their own tools: PFLOTRAN (SNL), QPAC (Quintessa) and LOPOS (GRS). These differ essentially regarding numerical concept and degree of detail in the representation of the underlying physical processes. The discussion focused on when simplifications can be appropriately applied and what consequences result from them. Furthermore, it was explored when and if a higher level of fidelity in geometry or physical processes is required.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

High-performance and cost-effective membrane electrode assemblies for advanced proton exchange membrane water electrolyzers: Long-term durability assessment

In this work, improved activity and durability performance of a two-cell (86 cm 2 ) proton exchange membrane water electrolyzer (PEMWE) stack is reported for the first time. Both membrane electrode assemblies (MEAs) contain one order of magnitude lower platinum group metal (PGM) loadings compared to the state-of-the-art PEMWEs and incorporate novel Pt recombination layers. The high-performance and cost-effective MEAs are fabricated by the unique reactive spray deposition technology (RSDT). This advanced methodology allows for one-step fabrication of MEAs and ensures precise control and distribution of the catalyst composition and loading. The RSDT-fabricated MEAs contain only 0.2 and 0.3 mg PGM cm –2 loading in the cathode and anode electrodes, respectively, and demonstrate excellent activity and durability for over 3000 h of operation at industrially-relevant operating conditions without showing significant loss in performance. This novel work shows that a significant cost reduction for PEMWEs is achieved while maintaining excellent durability, high catalysts activities, and low hydrogen cross-over.

Proton exchange membrane water electrolyzer↗
DOE OSTI2022

Multiphysics modeling of SOFC performance degradation caused by interface delamination and active layer cracking

In solid oxide device operation, delamination and cracking cause more catastrophic damage to cell life than other degradation mechanisms, leading to more rapid cell failure. The electrochemical performance degradation caused by electrode/electrolyte interface delamination and active layer cracking were investigated through in-house developed three-dimensional multiphysics simulations. Here the multiphysics simulations, fully calibrated against experimental datasets for button cells in a previous study, were extended to quantitatively investigate the effects of electrode/electrolyte interface delamination and active layer cracking. The simulated polarization curves and impedance behavior with various levels of delamination and cracking provided insights of the performance degradation. Furthermore, the local current distributions within the cell were analyzed for three different operating modes: constant voltage, constant current, and constant power. Finally, a practical strategy was proposed to mitigate the performance degradation in the realistic cell operations, extending overall cell lifetime.

08 HYDROGEN↗
DOE OSTI2020

Performance of U 3 Si 2 in an LWR following a cladding breach during normal operation

High-density fuels have been proposed as a possible replacement for uranium-dioxide as a fuel for light water reactors (LWRs) due to their increased loading of fissionable material. The objectives of this proposal are (1) to increase reactor cycle length and reactor power, and (2) to offset any neutronic penalty associated with advanced cladding systems. Of the high-density fuels under consideration, there is particular interest in triuranium disilicide (U 3 Si 2 ) due to its increased metal density and favorable thermal properties as compared to UO 2 . However, there are concerns regarding the chemical compatibility of U 3 Si 2 with water and steam as used for LWR coolant.This paper summarizes research on fuel-coolant chemical compatibility for UO 2 LWR fuel during a cladding breach and highlights that generally, because of its chemical inertness, UO 2 -coolant reactions are of little consequence to reactor operation. However, the volumetric expansion associated with the reaction of UO 2 and oxygen is a concern for possible conditions encountered during air ingress of dry storage. These same concerns arise for U 3 Si 2 , which exhibits greater volumetric expansion than UO 2 when exposed to water or steam. These reactions ultimately result in increased fuel volume that the cladding must accommodate, as well as additional heat generated as the fuel reacts.The BISON fuel performance code was used to perform a comparative analysis on the behavior of UO 2 and U 3 Si 2 under normal operation. Silicide fuel simulations were then extended to demonstrate how varying thermodynamic and chemical kinetics influence fuel expansion and subsequent cladding performance during a cladding breach. These simulations were further extended to a 3D subsection of a fuel rod to demonstrate the characteristics of the resulting cladding crack.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Impact of cycling conditions on lithium-ion battery performance for electric vertical takeoff and landing applications

The development of better electrochemical energy storage systems has sparked significant interest in using Li-ion batteries for electric vertical takeoff and landing (eVTOL) applications. To ensure the optimal performance and safety of onboard batteries, their behavior under different charging/discharging protocols and environmental conditions must be understood. Here, this paper presents a comprehensive evaluation of commercial Li-ion batteries for eVTOL applications, focusing on their responses to varying charging/discharging strategies and mechanical vibrations experienced during flight. Through controlled experiments, the effects of rapid cycling on battery performance were investigated, including effects on lifespan, capacity, and internal resistance. Additionally, the impact of mechanical vibrations on battery behavior was assessed to identify potential challenges for onboard batteries. The results of this study revealed intriguing insights into the interplay between temperature, vibration, and battery performance. This work contributes to the broader adoption of electric aerial transportation, promising a greener and safer future for urban mobility.

18650 cells↗
DOE OSTI2025

Establishing a process-structure-property-performance framework for SLS additive manufacturing through integrated multiscale modeling

This study presents a comprehensive suite of high-fidelity computational models that integrate multiscale and multiphysics simulations to capture the full Selective Laser Sintering (SLS) additive manufacturing process—from initial melting and solidification to mechanical response under external loads. Process simulations are linked with mechanical analysis through Representative Volume Elements (RVEs), establishing a process-structure–property-performance framework. The interaction between laser light and polyamide 12 (PA12) powder is modeled, accounting for laser characteristics and the optical, thermal, and geometrical properties of the powder. The heat source is incorporated into a heat transfer model, coupled with crystallization kinetics and densification models to predict material density and crystallinity. The porosity distribution from the densification model and crystallinity interpolated from experimental data are used to construct the RVEs. A multi-mechanism constitutive model is then calibrated using mechanical tests to predict the stress–strain response. Simulation results show good agreement with experimental data in terms of porosity, crystallinity, and mechanical performance when sufficient laser power (62 W or higher) is used. This research supports the inverse design of 3D-printed structures by introducing a high-fidelity framework that combines multiscale and multiphysics modeling with experimental calibration for predictive and performance-driven additive manufacturing.

SLS↗
DOE OSTI2021

Understanding how single-atom site density drives the performance and durability of PGM-free Fe–N–C cathodes in anion exchange membrane fuel cells

One of the most important needs for the future of low-cost fuel cells is the development of highly active platinum group metal (PGM)-free catalysts. For the oxygen reduction reaction, Fe–N–C materials have been widely studied in both acid and alkaline media. However, reported catalysts in the literature show quite different intrinsic activity and in-cell performance, despite similar synthesis routes and precursors. Here, two types of Fe–N–C are prepared from the same precursor and procedure – the main difference is how the precursor was handled prior to use. It is shown that in one case Fe overwhelmingly existed as highly active single-metal atoms in FeN4 coordination (preferred), while in the other case large Fe particles coexisting with few single metal atoms were obtained. As a result, there were drastic differences in the catalyst structure, activity, and especially in their performance in an operating anion exchange membrane fuel cell (AEMFC). Additionally, it is shown that catalyst layers created from single-atom-dominated Fe–N–C can have excellent performance and durability in an AEMFC using H 2 /O 2 reacting gases, achieving a peak power density of 1.8 W cm -2 – comparable to similar AEMFCs with a Pt/C cathode – and being able to operate stably for more than 100 h. Finally, the Fe–N–C cathode was paired with a low-loading PtRu/C anode electrode to create AEMFCs (on H 2 /O 2 ) with a total PGM loading of only 0.135 mg cm -2 (0.090 mg Pt cm -2 ) that was able to achieve a very high specific power of 8.4 W mg PGM -1 (12.6 W mg Pt< sup>-1 ).

36 MATERIALS SCIENCE↗
DOE OSTI2021

Benchmarking the Performance of Neuromorphic and Spiking Neural Network Simulators

Software simulators play a critical role in the development of new algorithms and system architectures in any field of engineering. Neuromorphic computing, which has shown potential in building brain-inspired energy-efficient hardware, suffers a slow-down in the development cycle due to a lack of flexible and easy-to-use simulators of either neuromorphic hardware itself or of spiking neural networks (SNNs), the type of neural network computation executed on most neuromorphic systems. While there are several openly available neuromorphic or SNN simulation packages developed by a variety of research groups, they have mostly targeted computational neuroscience simulations, and only a few have targeted small-scale machine learning tasks with SNNs. Evaluations or comparisons of these simulators have often targeted computational neuroscience-style workloads. In this work, we seek to evaluate the performance of several publicly available SNN simulators with respect to non-computational neuroscience workloads, in terms of speed, flexibility, and scalability. We evaluate the performance of the NEST, Brian2, Brian2GeNN, BindsNET and Nengo packages under a common front-end neuromorphic framework. Our evaluation tasks include a variety of different network architectures and workload types to mimic the computation common in different algorithms, including feed-forward network inference, genetic algorithms, and reservoir computing. We also study the scalability of each of these simulators when running on different computing hardware, from single core CPU workstations to multi-node supercomputers. Our results show that the BindsNET simulator has the best speed and scalability for most of the SNN workloads (sparse, dense, and layered SNN architectures) on a single core CPU. However, when comparing the simulators leveraging the GPU capabilities, Brian2GeNN outperforms the others for these workloads in terms of scalability. NEST performs the best for small sparse networks and is also the most flexible simulator in terms of reconfiguration capability NEST shows a speedup of at least 2x compared to the other packages when running evolutionary algorithms for SNNs. The multi-node and multi-thread capabilities of NEST show at least 2x speedup compared to the rest of the simulators (single core CPU or GPU based simulators) for large and sparse networks. We conclude our work by providing a set of recommendations on the suitability of employing these simulators for different tasks and scales of operations. We also present the characteristics for a future generic ideal SNN simulator for different neuromorphic computing workloads.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Characterizing the performance of node-aware strategies for irregular point-to-point communication on heterogeneous architectures

Supercomputer architectures are trending toward higher computational throughput due to the inclusion of heterogeneous compute nodes. These multi-GPU nodes increase on-node computational efficiency, while also increasing the amount of data to be communicated and the number of potential data flow paths. In this work, we characterize the performance of irregular point-to-point communication with MPI on heterogeneous compute environments through performance modeling, demonstrating the limitations of standard communication strategies for both device-aware and staging-through-host communication techniques. Presented models suggest staging communicated data through host processes then using node-aware communication strategies for high inter-node message counts. Notably, the models also predict that node-aware communication utilizing all available CPU cores to communicate inter-node data leads to the most performant strategy when communicating with a high number of nodes. Furthermore, model validation is provided via a case study of irregular point-to-point communication patterns in distributed sparse matrix–vector products. Importantly, we include a discussion on the implications model predictions have on communication strategy design for emerging supercomputer architectures.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Performance and wake flow characterization of a 1:8.7-scale reference USDOE MHKF1 hydrokinetic turbine to establish a verification and validation test database

As hydrokinetic turbine technologies continue to advance towards commercialization, public datasets on the performance characteristics for these devices and their flow field effects are invaluable to advance our understanding of these technologies and to validate analytical and numerical models. The Applied Research Laboratory at The Pennsylvania State University (ARL Penn State) collaborated with Sandia National Laboratories and the University of California at Davis to design, fabricate (at a 1:8.7 scale), and experimentally test a novel hydrokinetic turbine rotor design to provide an open platform and dataset for further study and development. The water tunnel test of this three-bladed, horizontal-axis rotor recorded power production, blade loading, the near-wake flow, cavitation effects, and noise generation. These state-of-the-art measurements demonstrate much of the complex physics associated with the flow through an unducted, horizontal-axis turbine, and they elucidate the performance characteristics and flow field effects at an unprecedented fidelity, accuracy and resolution. Measurements of powering coefficients (power, torque and thrust) as a function of tip-speed-ratio were performed. The dataset also includes unsteady measurements of driveshaft loading, blade strain, tower pressures, and radiated noise. Detailed flow mapping using laser Doppler velocimetry, and planar and stereo particle image velocimetry includes measurements of mean velocity and Reynolds stresses. Although the wake measurements are limited to less than half a diameter, they reveal the complex flow patterns in the near-wake structure of the rotor. The full database, available at the United States Department of Energy’s marine and hydrokinetic data repository, includes tunnel and model Computer Aided Design geometry files and inflow data sufficient for a “Model-the-Test” computational Verification and Validation study.

13 HYDRO ENERGY↗
DOE OSTI2025

Empirical thermophotovoltaic performance predictions and limits

Significant progress has been made in the field of thermophotovoltaics, with efficiency recently rising to over 40% due to improvements in cell design and material quality, higher emitter temperatures, and better spectral management. However, inconsistencies in trends for efficiency with semiconductor bandgap energy across various temperatures pose challenges in predicting optimal bandgaps or expected performance for different applications. To address these issues, here we present realistic performance predictions for various types of single-junction cells over a broad range of emitter temperatures using an empirical model based on past cell measurements. Our model is validated using data from different authors with various bandgaps and emitter temperatures, and an excellent agreement is seen between the model and the experimental data. Using our model, we show that in addition to spectral losses, it is important to consider practical electrical losses associated with series resistance and cell quality to avoid overestimation of system efficiency. Here, we also show the effect of modifying various system parameters such as bandgap, above and below-bandgap reflectance, saturation current, and series resistance on the efficiency and power density of thermophotovoltaics at different temperatures. Finally, we predict the bandgap energies for best performance over a range of emitter temperatures for different cell material qualities.

14 SOLAR ENERGY↗
DOE OSTI2022

Understanding the Role of SEI Layer in Low-Temperature Performance of Lithium-Ion Batteries

Low-temperature electrolytes (LTEs) have been considered as one of the most challenging aspects for the wide adoption of lithium-ion batteries (LIBs) since the SOA electrolytes cannot sufficiently support the redox reactions at LT resulting in dramatic performance degradation. Although many attempts have been taken by employing various noncarbonate solvent electrolytes, there was a lack of fundamental understanding of the limiting factors for low-temperature operations (e.g., -20 to -40 degrees C). Here, the crucial role of the solid-electrolyte-interface (SEI) in LIB performance at low temperature using a butyronitrile (BN)-based electrolyte was demonstrated. These results suggested that an additive formed SEI with low resistance and low charge transfer dictates the LT performance in terms of capacity and cycle life, presenting a useful guideline in designing new electrolytes to address the LT issue.

25 ENERGY STORAGE↗
DOE OSTI2025

Algae Asphalt to Enhance Pavement Sustainability and Performance at Subzero Temperatures

This paper evaluates the potential of algae-derived biobinders as sustainable alternatives for pavement construction. It specifically examines the physicochemical and rheological properties of biomodified binders and their potential to offset carbon emissions when used as partial replacements for conventional petroleum-based asphalt binders. Biosequestration of CO 2 using microalgal cell factories is a promising way of recycling CO 2 into biomass via photosynthesis. Our study demonstrates that incorporating algae-derived binders into asphalt can significantly reduce carbon emissions. Each 1% increase in algae-based biobinder leads to an approximate 4.5% decrease in net carbon emissions. This indicates that a blend containing about 22% biobinder has the potential to achieve carbon neutrality. Blends with higher proportions may even result in net-negative emissions, highlighting a promising strategy for environmentally responsible road construction. In terms of performance, the study shows that certain algae-derived biobinders significantly enhance the cracking resistance of asphalt, particularly under subzero temperatures, by improving its stress-relief capacity. A key contribution of this work is the introduction of polarizability as a novel molecular-level parameter for assessing the compatibility of algae-derived bio-oils with asphalt. By capturing the electronic responsiveness of bio-oil molecules, polarizability serves as a predictive indicator of their interaction potential with asphalt components, providing a new dimension for evaluating the binder performance at the molecular scale. Among the tested materials, the biobinder derived from Haematococcus pluvialis demonstrated particularly strong improvements in resistance to permanent deformation under repeated loading conditions analogous to traffic-induced stress, as well as enhanced resistance to moisture-induced damage. In conclusion, these findings advance the chemistry-driven design of biomass-based binders and highlight a promising pathway toward the development of low-carbon, high-performance, and sustainable infrastructure materials.

Algae↗
DOE OSTI2021

Bio-Based Polymers with Performance-Advantaged Properties

Bio-based compounds with unique chemical functionality can be obtained through selective transformations of plant and other non-fossil, biogenic feedstocks for the development of new polymers to displace those produced from fossil carbon feedstocks. Although substantial efforts have been invested to produce bio-based polymers that are chemically identical to and directly replace those from petroleum, a long-pursued goal is to synthesize new, sustainable, bio-based polymers that either functionally replace or exhibit performance advantages relative to incumbent polymers. Owing to anthropogenic climate change and the environmental consequences of global plastics pollution, the need to realize a bio-based materials economy at scale is critical. To that end, in this Review we describe the concept of performance-advantaged, bio-based polymers (PBPs), highlighting examples wherein superior performance is facilitated by the inherent chemical functionality of bio-based feedstocks. We focus on PBPs with C–O and C–N inter-unit chemical bonds, as these are often readily accessible from bio-based feedstocks, which are heteroatom-rich relative to petroleum-derived feedstocks. Finally, we outline guiding principles and challenges to aid progress in the development of PBPs.

bio-based feedstock↗