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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 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

On the Impact of Execution Models: A Case Study in Computational Chemistry

Efficient utilization of high-performance computing (HPC) platforms is an important and complex problem. Execution models, abstract descriptions of the dynamic runtime behavior of the execution stack, have significant impact on the utilization of HPC systems. Using a computational chemistry kernel as a case study and a wide variety of execution models combined with load balancing techniques, we explore the impact of execution models on the utilization of an HPC system. We demonstrate a 50 percent improvement in performance by using work stealing relative to a more traditional static scheduling approach. We also use a novel semi-matching technique for load balancing that has comparable performance to a traditional hypergraph-based partitioning implementation, which is computationally expensive. Using this study, we found that execution model design choices and assumptions can limit critical optimizations such as global, dynamic load balancing and finding the correct balance between available work units and different system and runtime overheads. With the emergence of multi- and many-core architectures and the consequent growth in the complexity of HPC platforms, we believe that these lessons will be beneficial to researchers tuning diverse applications on modern HPC platforms, especially on emerging dynamic platforms with energy-induced performance variability.

Execution models, computational chemistry, MPI and↗
DOE OSTI2024

Forte: An Interactive Visual Analytic Tool for Trust-Augmented Net-Load Forecasting

Accurate net-load forecasting is vital for energy planning, aiding decisions on trade and load distribution. However, assessing the performance of forecasting models across diverse input variables, like temperature and humidity, remains challenging, particularly for eliciting a high degree of trust in the model outcomes. In this context, there is a growing need for data-driven technological interventions to aid scientists in comprehending how models react to both noisy and clean input variables, thus shedding light on complex behaviors and fostering confidence in the outcomes. In this paper, we present Forte, a visual analytics-based application to explore deep probabilistic net-load forecasting models across various input variables and understand the error rates for different scenarios. With carefully designed visual interventions, this web-based interface empowers scientists to derive insights about model performance by simulating diverse scenarios, facilitating an informed decision-making process. We discuss observations made using Forte and demonstrate the effectiveness of visualization techniques to provide valuable insights into the correlation between weather inputs and net-load forecasts, ultimately advancing grid capabilities by improving trust in forecasting models.

Bhattacharjee, Kaustav↗
DOE OSTI2019

A Cooperative Multi-Agent Deep Reinforcement Learning Framework for Real-Time Residential Load Scheduling

Internet-of-Things (IoT) enabled monitoring and control capabilities are enabling increasing numbers of household users with controllable loads to actively participate in smart grid energy management. Realizing an efficient real-time energy management system that takes advantage of these developments requires novel techniques for managing the increased complexity of the control action space in resolving multiple challenges such as the uncertainty in energy prices and renewable energy output along with the need to satisy physical grid constraints such as transformer capacity. Addressing these challenges, we develop a multi-household energy management framework for residential units connected to the same transformer and containing DERs such as PV, ESS and controllable loads. The goal of our framework is to schedule controllable household appliances and ESS such that the cost of procuring electricity from the utility over a horizon is minimized while physical grid constraints are satisfied at each scheduling step. Traditional energy management frameworks either perform global optimization to satisfy grid constraints but suffer from high computational complexity (for example Integer Program, Mixed Integer Programming frameworks and centralized reinforcement learning) or perform decentralized real-time energy management without satisfying global grid constraints (for example multi-agent reinforcement learning with no cooperation). In contrast, we propose a cooperative multiagent reinforcement learning (MARL) framework that i) operates in real-time, and ii) performs explicit collaboration to satisfy global grid constraints. The novelty in our framework is two fold. Firstly, our framework trains multiple independent learners (IL) for each household in parallel using historical data and performs real-time inferencing of control actions using the most recent system state. Secondly, our framework contains a low complexity knapsack based cooperation agent which combines the outputs of ILs to minimize cost while satisfying grid constraints. Simulation results show that our cooperative MARL approach achieves significant cost improvement over centralized reinforcement learning and day-ahead planning baselines. Moreover, our approach strictly satisfies physical constraints with no apriori knowledge of system dynamics while the baseline approaches have occasional violations. We also measure the training and inference time by ranging the number of households from 1 to 25. Results show that our cooperative MARL approach scales best among various approaches.

14 SOLAR ENERGY↗
DOE OSTI2017

Structural and biochemical analyses of the DEAD-box ATPase Sub2 in association with THO or Yra1

mRNA is cotranscrptionally processed and packaged into messenger ribonucleoprotein particles (mRNPs) in the nucleus. Prior to export through the nuclear pore, mRNPs undergo several obligatory remodeling reactions. In yeast, one of these reactions involves loading of the mRNA-binding protein Yra1 by the DEAD-box ATPase Sub2 as assisted by the hetero-pentameric THO complex. To obtain molecular insights into reaction mechanisms, we determined crystal structures of two relevant complexes: a THO hetero-pentamer bound to Sub2 at 6.0 Å resolution; and Sub2 associated with an ATP analogue, RNA, and a C-terminal fragment of Yra1 (Yra1-C) at 2.6 Å resolution. We found that the 25 nm long THO clamps Sub2 in a half-open configuration; in contrast, when bound to the ATP analogue, RNA and Yra1-C, Sub2 assumes a closed conformation. Both THO and Yra1-C stimulated Sub2’s intrinsic ATPase activity. We propose that THO surveys common landmarks in each nuclear mRNP to localize Sub2 for targeted loading of Yra1.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Kinetics of temperature response of PEO-b-PNIPAM-b-PAA triblock terpolymer aggregates and of their complexes with lysozyme

We present the kinetics of temperature response of a PEO-b-PNIPAM-b-PAA triblock terpolymer and of its complexes with lysozyme in aqueous solution. It is found that during the coil-to-globule transition of PNIPAM new bonds within the polymer aggregates are created, making the transition of the aggregates partially irreversible. This effect is also found for the protein loaded PEO-b-PNIPAM-b-PAA aggregates whereas in this case protein globules appear to enhance the formation of bonds, making the transition totally irreversible. The internal dynamics of both aggregates and complexes are “frozen” once the temperature is increased upon PINIPAM's LCST in water and remain so even when the temperature drops below LCST. As a result, we investigate the complexation kinetics of lysozyme and PEO-b-PNIPAM-b-PAA and observe that it occurs in two stages, one where protein globules adsorb on single pre-formed aggregates and one where protein globules cause inter-aggregate clustering.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Inversion Reduction Method for Real and Complex Distribution Feeder Models

We report the proliferation of distributed generation on distribution feeders triggers a large number of integration and planning studies. Further, the complexity of distribution feeder models, short simulation time steps, and long simulation horizons rapidly render studies computational burdensome. To mend this issue, we propose a methodology for reducing the number of nodes, loads, generators, line, and transformers of p-phase distribution feeders with unbalanced loads and generation, non-symmetric wire impedance, mutual coupling, shunt capacitance, and changes in voltage and phase. The methodology is derived on a constant power load assumption and employs a Gaussian elimination inversion technique to design the reduced feeder. Compared to previous work by the authors, the inversion reduction takes half the time and voltage errors after reduction are reduced by an order of magnitude. Using a snapshot simulation the reduction is tested on six additional publicly available feeders with a maximum voltage error 0.0075 p.u. regardless of feeder size or complexity, and typical errors on the order of 1 × 10 -4 p.u. Lastly, for a day long quasi-static time series simulation on the UCSD A feeder, errors are shown to increase with changes in loading when a large number of buses removed, but shows less variation for less than 85% of buses removed.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

A Nonlinear Regression Method for Composite Protection Modeling of Induction Motor Loads

Protection equipment are used to prevent damages to induction motor loads by isolating those from the power network in the event of severe faults. Modeling the response of induction motor loads and their protection is vital for power system planning and operation, especially in understanding system's response moments after a fault has occurred. This article proposes an optimization based framework to generate composite protection models for commercial building motor loads. Introducing a mathematical abstraction, the task of finding a suitable (simplified) model of the composite protection scheme is formulated as a nonlinear regression problem. Numerical examples are provided to illustrate the application of the framework.

Kundu, Soumya↗
DOE OSTI2025

Techno-Economic Analysis for the Addition of a Thermal Energy Storage System to a Central Plant

Increasing energy demand and rising peak loads present significant challenges for energy management in commercial and institutional settings. As climate change drives greater cooling needs, central plants must navigate the complex tradeoffs between operational efficiency, cost control, and grid stability. Thermal energy storage (TES) systems offer a viable solution by shifting energy consumption from peak to off-peak periods, thereby reducing peak demand, lowering utility expenses, and improving grid resilience. However, the success of TES implementation hinges on appropriate system sizing, effective control strategies, and alignment with local utility rate structures. This article presents a techno-economic analysis of integrating a chilled water TES system into the central plant at California State University, Dominguez Hills. Drawing on historical load profiles and utility tariffs, we assess three TES sizing approaches and their corresponding control strategies from both energy and economic perspectives. This article utilizes a model-based approach to assess the impact of TES sizing and control strategies on the techno-economic feasibility of integrating TES into an existing central plant. The models employed for this analysis were calibrated using 4 years of historical data. Here, the results demonstrated that utility tariffs and the campus's operational profiles dictate the most feasible sizing and control methods. The findings offer valuable insights for institutions and commercial building managers exploring sustainable energy solutions. By demonstrating how optimized TES strategies can improve operational efficiency while achieving financial savings, this study highlights the potential for TES to align performance with cost effectiveness in real-world applications.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Achieving high hydrogen productivities of 20 L/L-day via microbial electrolysis of corn stover fermentation products

Microbial electrolysis cells have the potential to generate renewable hydrogen from underused waste streams, however current devices have not reached very large productivity targets using real waste products at any scale. This study used a waste from fermented corn stover known as corn stover fermentation product to reach performance metrics that could be commercialized, if adequately scaled. Average current densities in MECs with mature biofilms reached 17.9 +/- 1.6 A/m 2 at an organic loading rate of 30 grams of chemical oxygen demand per liter of anode volume per day (g/L-day), reaching a maximum current density of 27.2 +/- 2.9 A/m 2 . Hydrogen productivities reached 20.2 +/- 2.0 L of H 2 per L anode volume per day (L/L-day). These represent the highest current densities and highest hydrogen productivities using a complex feedstock in a microbial electrolysis cell. Organic acids and sugars present in untreated substrate were converted at high percentages in MECs, with most above 90% conversion, at organic loading rates of 10, 20, and 30 g/L-day. The effect of periodic high liquid flow rates through the anode on performance was assessed. These tests, called pulsing, showed that hydrogen productivities and current densities increased most dramatically as flow was pulsed every hour at a baseline flow rate of 0.3 mL/min. These productivities show promise for high performance systems, if adequate scale up can be achieved.

09 BIOMASS FUELS↗
DOE OSTI2017

A code-independent generalized actuator line model for wind farm aerodynamics over simple and complex terrain

Actuator line model representations of wind turbines reduce the simulation cost of wind farm aerodynamics relative to blade geometry resolving simulations. However, most implementations are code specific and may not have proper load balancing when run in parallel. Here, a generalized actuator line model (GALM) is developed to overcome this implementation drawback of existing approaches. The GALM can be coupled to any existing microscale solver with minimal or no modifications. The coupling of our GALM model with the open-source microscale code CgWind is used to demonstrate both its ease of use and fidelity. The results obtained from the coupled-model simulations are validated for both isolated turbine in wind tunnel experiments and measurements in offshore wind farm. Finally, an operational wind farm over complex terrain is demonstrated. The simulations show that wake meandering and power production are strongly influenced by terrain impacts. Access information for obtaining the code is provided.

17 WIND ENERGY↗
DOE OSTI2017

Anthropogenic pollution elevates the peak height of new particle formation from planetary boundary layer to lower free troposphere

New particle formation (NPF) and subsequent growth are primary sources of atmospheric aerosol particles and cloud condensation nuclei. Previous studies have been conducted in relatively clean environments; investigation of NPF events over highly polluted megacities is still lacking. Here in this paper we show, based on a recent yearlong aircraft campaign conducted over Beijing, China, from April 2011 to June 2012, that NPF occurrence peaks in the lower free troposphere (LT), instead of planetary boundary layer (PBL), as most previous studies have found and that the distance of NPF peak to PBL top increases with increasing aerosol loading. Further analysis reveals that increased aerosols suppress NPF in PBL, but enhance NPF in LT due to a complex chain of aerosol-radiation-photochemistry interactions that affect both NPF sources and sinks. These findings shed new light on our understanding of NPF occurrence, NPF vertical distribution, and thus their effects on atmospheric photochemistry, clouds, and climate.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Thermal Stability of Schottky Contacts and Rearrangement of Defects in β ‐Ga 2 O 3 Crystals

Abstract The thermal stability of different Schottky contacts (Au, Pt, and Ni) on (100) β ‐Ga 2 O 3 single crystals grown by the Czochralski method is investigated. Besides the examination of the Schottky barrier parameters, contact‐dependent defect levels are investigated by deep‐level transient spectroscopy (DLTS) in a 100–650 K (ramp‐up) and 650–100 K (ramp‐down) temperature cycle. Several defect levels are detected below the conduction band minimum at 0.41, 0.60, 0.77, 0.96, and 1.17 eV. In the temperature ramp‐down DLTS, the 1.17 eV level disappears, and the 0.60 eV level appears for all Schottky contacts. DFT calculations suggest that rearrangement and dissociation of a single hydrogen from a doubly‐hydrogenated Ga─O divacancy complex occurs during the temperature sweep under bias. The trap level at 0.96 eV only appears after the thermal load for the Ni contact, in contrast to Au and Pt, where it is present without a thermal budget. Temperature‐dependent leakage current (at −4 V) measurements indicate oxidation of Ni, and further thermodynamic analysis suggests alloying of Au‐Ga atoms at the Au/ β ‐Ga 2 O 3 interface. These studies provide insight into the behavior induced by these common Schottky contacts and the alteration associated with temperature cycling.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Equilibria and Rate Phenomena from Atomistic to Mesoscale: Simulation Studies of Magnetite

Batteries are complex devices composed of multiple components that operate far from equilibrium and may operate under extreme stress and varying loads. Research of isolated battery components are valuable to the fundamental understanding of the physical processes occurring within each constituent element. When the components are integrated into a full device and operated under realistic conditions, it can be difficult to decouple the physical processes that occur across multiple interfaces and multiple length scales. Thus, the physical processes studied in isolated components may change in a full battery setup or may be irrelevant to performance. Simulation studies on many length scales play a key role in the analysis of experiments and in the elucidation of the relevant physical processes impacting performance. In this Account, we aim to highlight the use of modeling on multiple length scales to identify rate limiting phenomena in lithium-ion batteries. To illustrate the utility of modeling, we examine lithium-ion batteries with nanostructured magnetite, Fe 3 O 4 , as the positive electrode active material against a solid Li 0 negative electrode. Due to continuous operation away from equilibrium, batteries exhibit highly nonideal behavior, and a model that aims to reproduce behavior under realistic operating conditions must be able to capture the physics occurring on the length scales relevant to the performance of the system. It is our experience that limiting behavior in lithium-ion batteries can be observed on the atomic scale and up through the electrode scale and thus, predictive models must be capable of integrating and communicating physics across multiple length scales. Magnetite is studied as an electrode material for lithium-ion batteries, but it is found to suffer from slow solid-state transport of lithium, slow reaction kinetics, and poor cycling. Magnetite (Fe 3 O 4 ) is a material capable of undergoing multiple electron transfers (MET), and can accept up to eight lithium per formula unit (Li 8 Fe 3 O 4 ). Magnetite, (Fe 8a 3+ )[Fe 3+ Fe 2+ ] 16d O 4,32e 2– , has a close-packed inverse spinel structure and undergoes intercalation, structural rearrangement, and conversion reactions upon full lithiation. To overcome solid-state transport resistances, magnetite can be nanostructured to decrease Li + diffusion lengths, and this has been shown to increase capacity. Additionally, unique architectures incorporating both carbon and Fe 3 O 4 have shown to alleviate transport and cycling issues in the material. Here, we solely address traditional composite electrodes, in which Fe 3 O 4 is synthesized as nanoparticles and combined with additives to fabricate the electrode. In the case of nanoparticulate magnetite, it has been found that the electrode fabrication process results in the formation of micrometer-sized agglomerates of the Fe 3 O 4 nanoparticles, introducing a secondary structural motif. The agglomerates may form in one or more fabrication processes, and their elimination may not be straightforward or warranted. Here, we highlight the impact of these secondary formations on the performance of the Fe 3 O 4 lithium-ion battery. We illustrate how simulations can be used to design experiments, prioritize research efforts, and predict performance.

25 ENERGY STORAGE↗
DOE OSTI2015

Organic Matter Remineralization Predominates Phosphorus Cycling in the Mid-Bay Sediments in the Chesapeake Bay

The Chesapeake Bay, the largest and most productive estuary in the US, suffers from varying degrees of water quality issues fueled by both point and non–point source nutrient sources. Restoration of the bay is complicated by the multitude of nutrient sources, their variable inputs and hydrological conditions, and complex interacting factors including climate forcing. These complexities not only restrict formulation of effective restoration plans but also open up debates on accountability issues with nutrient loading. A detailed understanding of sediment phosphorus (P) dynamics enables one to identify the exchange of dissolved constituents across the sediment- water interface and aid to better constrain mechanisms and processes controlling the coupling between the sediments and the overlying waters. Here we used phosphate oxygen isotope ratios (δ18Op) in concert with sediment chemistry, XRD, and Mössbauer spectroscopy on the sediment retrieved from an organic rich, sulfidic site in the meso-haline portion of the mid-bay to identify sources and pathway of sedimentary P cycling and to infer potential feedback effect on bottom water hypoxia and surface water eutrophication. Isotope data indicate that the regeneration of inorganic P from organic matter degradation (remineralization) is the predominant, if not sole, pathway for authigenic P precipitation in the mid-bay sediments. We interpret that the excess inorganic P generated by remineralization should have overwhelmed any bottom-water and/or pore-water P derived from other sources or biogeochemical processes and exceeded saturation with respect to authigenic P precipitation. It is the first research that identifies the predominance of remineralization pathway against remobilization (coupled Fe-P cycling) pathway in the Chesapeake Bay. Therefore, these results are expected to have significant implications for the current understanding of P cycling and benthic-pelagic coupling in the bay, particularly on the source and pathway of P that sustains hypoxia and supports phytoplankton growth in the surface water.

Environmental Molecular Sciences Laboratory↗
DOE OSTI2021

Low coordination number copper catalysts for electrochemical CO 2 methanation in a membrane electrode assembly

The electrochemical conversion of CO 2 to methane provides a means to store intermittent renewable electricity in the form of a carbon-neutral hydrocarbon fuel that benefits from an established global distribution network. The stability and selectivity of reported approaches reside below technoeconomic-related requirements. Membrane electrode assembly-based reactors offer a known path to stability; however, highly alkaline conditions on the cathode favour C-C coupling and multi-carbon products. In computational studies herein, we find that copper in a low coordination number favours methane even under highly alkaline conditions. Experimentally, we develop a carbon nanoparticle moderator strategy that confines a copper-complex catalyst when employed in a membrane electrode assembly. In-situ XAS measurements confirm that increased carbon nanoparticle loadings can reduce the metallic copper coordination number. At a copper coordination number of 4.2 we demonstrate a CO 2 -to-methane selectivity of 62%, a methane partial current density of 136 mA cm –2 , and > 110 hours of stable operation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Computational Fluid Dynamics Study of a Cross-Flow Marine Hydrokinetic Turbine and the Combined Influence of Struts and Helical Blades

A computational fluid dynamics study was performed for a cross-flow marine hydrokinetic turbine. The analysis was done in three dimensions and used the unsteady Reynolds-averaged Navier-Stokes solver in the commercial code STAR-CCM+. The base turbine configuration is the RivGen(R) Turbine, designed by the Ocean Renewable Power Company. A convergence and uncertainty analysis was performed for both the spatial and temporal discretization; this was done using the base configuration, which features support struts and helical foils. Both struts and helical blades introduce three-dimensional flow effects, influencing the complex flow phenomenon of dynamic stall. The study compares the relative impact of struts on power performance and blade loading for both helical and straight blades, and found that for this turbine the relative loss in power from struts was lower with helical blades.

CFD↗
DOE OSTI2020

Design and Analysis of a Double Wall, Water Cooled Window for Accelerator Based Mo-99 Production

The electron accelerator based Mo-99 production technique requires the use of Rhodotrons to generate 38 MeV, 6.32 mA pulsed electron beams. The introduction of the pulsed beam structure has introduced fatigue concerns in the vacuum-helium windows that did not exist previously for electron beam production via linear accelerators. Previous analysis has shown that temperature fluctuations of approximately 100°C above and below the steady state operating temperature of ~500°C will occur within the windows. A water cooled window will eliminate this concern by reducing the primary mechanical stress due to the 300-psig helium pressure load as well as the secondary thermally induced stress. Although a water cooled window was considered years ago, the complexities of adding an additional water line was unattractive until now. A double wall, water cooled window has been designed and analyzed for this reason. The water cooled window design is shown to decrease the helium-side window temperature to as low as 125°C, while the vacuum-side window is maintained at 161°C at a water flow rate of 3.2 GPM. These low steady state temperatures reduce the thermal stress of the helium-side window significantly. Also, the primary mechanical stress has been reduced by roughly 50% due to the reduced pressure gradient across the helium-side window (150-psig water and 300-psig helium). Considering a Mo-99 production loss of roughly 1%, the water cooled window is a drastic improvement over the previous helium cooled designs and should be greatly considered for future upgrades and redesign.

43 PARTICLE ACCELERATORS↗
DOE OSTI2021

In Situ High Energy X-ray Diffraction Characterization of Phase Transformations and Mechanical Behaviors in Rapidly Solidified Titanium and Stainless Steel Alloys [Thesis]

Advanced manufacturing techniques like additive manufacturing (AM) have poised themselves to revolutionize metal manufacturing. A wide range of AM techniques are capable of manufacturing metal components with unique, complex geometries and hastening the scientific-engineering-development cycle. Metal AM relies on a layer-by-layer rapid manufacturing process to build components from the substrate up. Rapid solidification is a large departure from traditional metal manufacturing due to its complex physics. Characterization of rapid solidification is difficult, stemming from the small volumes used in AM and the fast dynamics of the process. High energy X-ray diffraction (HEXRD) is a solution to the characterization problems of rapidly solidified alloys and AM. HEXRD can probe small volumes at fast rates and provides a wide range of thermomechanical and kinetic information. This thesis presents the application of HEXRD to rapidly solidified titanium and stainless steel alloys through a series of case studies. In the first two studies, HEXRD is applied to rapidly solidified titanium and stainless steel welds. The materials are characterized for their temperature history, phase changes, kinetics, and microstructural evolution. In the next case study, HEXRD is applied to characterize phase changes in elastocaloric NiTi shape memory alloys (SMAs) under thermomechanical load. HEXRD, in conjunction with other tools, is used to explain the superior performance of the additively manufactured SMAs. In the final two case studies, HEXRD is used to measure the mechanical response of AM parts with complex geometries; namely, the octet truss lattice. Diffraction reveals a wide range of materials information about the AM microstructure including unexpected phases, texture, and mechanical response to loading. The mechanical results from HEXRD and then compared with theoretical predictions about the performance of octet truss lattices. Summarily, HEXRD is a diverse tool that is poised to address the complex characterization problems of many aspects of the additive manufacturing process.

36 MATERIALS SCIENCE↗