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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,027 records · Page 57
All sourcesNASA NTRSDOE OSTI
DOE OSTI2012

Study of Morphological Changes in MgH2 Destabilized LiBH4 Systems Using Computed X-ray Microtomography

The objective of this study was to apply three-dimensional x-ray microtomographic imaging to understanding morphologies in the diphasic destabilized hydride system: MgH2 and LiBH4. Each of the single phase hydrides as well as two-phase mixtures at LiBH4:MgH2 ratios of 1:3, 1:1, and 2:1 were prepared by high energy ball milling for 5 minutes (with and without 4 mol % TiCl3 catalyst additions). Samples were imaged using computed microtomography in order to (i) establish measurement conditions leading to maximum absorption contrast between the two phases and (ii) determine interfacial volume. The optimal energy for measurement was determined to be 15 keV (having 18% transmission for the MgH2 phase and above 90% transmission for the LiBH4 phase). This work also focused on the determination of interfacial volume. Results showed that interfacial volume for each of the single phase systems, LiBH4 and MgH2, did not change much with catalysis using 4 mol % TiCl3. However, for the mixed composite system, interphase boundary volume was always higher in the catalyzed system; increasing from 15% to 33% in the 1:3 system, from 11% to 20% in the 1:1 system, and 2% to 14% in the 2:1 system. The parameters studied are expected to govern mass transport (i.e., diffusion) and ultimately lead to microstructure-based improvements on H2 desorption and uptake rates.

36 MATERIALS SCIENCE↗
DOE OSTI2016

In situ investigation of the formation and metastability of formamidinium lead tri-iodide perovskite solar cells

Organic–inorganic perovskites have emerged as an important class of next generation solar cells due to their remarkably low cost, band gap, and sub-900 nm absorption onset. Here, we show a series of in situ observations inside electron microscopes and X-ray diffractometers under device-relevant synthesis conditions focused on revealing the crystallization process of the formamidinium lead-triiodide perovskite at the optimum temperature of 175 °C. Direct in situ observations of the structure and chemistry over relevant spatial, temporal, and temperature scales enabled identification of key perovskite formation and degradation mechanisms related to grain evolution and interface chemistry. The lead composition was observed to fluctuate at grain boundaries, indicating a mobile lead-containing species, a process found to be partially reversible at a key temperature of 175 °C. Using low energy electron microscopy and valence electron energy loss spectroscopy, lead is found to be bonded in the grain interior with iodine in a tetrahedral configuration. At the grain boundaries, the binding energy associated with lead is consequently shifted by nearly 2 eV and a doublet peak is resolved due presumably to a greater degree of hybridization and the potential for several different bonding configurations. At the grain boundaries there is adsorption of hydrogen and OH¯ ions as a result of residual water vapor trapped as a non-crystalline material during formation. Lastly, insights into the relevant formation and decomposition reactions of formamidinium lead iodide at low to high temperatures, observed metastabilities, and relationship with the photovoltaic performance were obtained and used to optimize device processing resulting in conversion efficiencies of up to 17.09% within the stability period of the devices.

14 SOLAR ENERGY↗
DOE OSTI2014

Development and optimization of SPECT gated blood pool cluster analysis for the prediction of CRT outcome

Purpose: Phase analysis of single photon emission computed tomography (SPECT) radionuclide angiography (RNA) has been investigated for its potential to predict the outcome of cardiac resynchronization therapy (CRT). However, phase analysis may be limited in its potential at predicting CRT outcome as valuable information may be lost by assuming that time-activity curves (TAC) follow a simple sinusoidal shape. A new method, cluster analysis, is proposed which directly evaluates the TACs and may lead to a better understanding of dyssynchrony patterns and CRT outcome. Cluster analysis algorithms were developed and optimized to maximize their ability to predict CRT response. Methods: About 49 patients (N = 27 ischemic etiology) received a SPECT RNA scan as well as positron emission tomography (PET) perfusion and viability scans prior to undergoing CRT. A semiautomated algorithm sampled the left ventricle wall to produce 568 TACs from SPECT RNA data. The TACs were then subjected to two different cluster analysis techniques, K-means, and normal average, where several input metrics were also varied to determine the optimal settings for the prediction of CRT outcome. Each TAC was assigned to a cluster group based on the comparison criteria and global and segmental cluster size and scores were used as measures of dyssynchrony and used to predict response to CRT. A repeated random twofold cross-validation technique was used to train and validate the cluster algorithm. Receiver operating characteristic (ROC) analysis was used to calculate the area under the curve (AUC) and compare results to those obtained for SPECT RNA phase analysis and PET scar size analysis methods. Results: Using the normal average cluster analysis approach, the septal wall produced statistically significant results for predicting CRT results in the ischemic population (ROC AUC = 0.73;p < 0.05 vs. equal chance ROC AUC = 0.50) with an optimal operating point of 71% sensitivity and 60% specificity. Cluster analysis results were similar to SPECT RNA phase analysis (ROC AUC = 0.78, p = 0.73 vs cluster AUC; sensitivity/specificity = 59%/89%) and PET scar size analysis (ROC AUC = 0.73, p = 1.0 vs cluster AUC; sensitivity/specificity = 76%/67%). Conclusions: A SPECT RNA cluster analysis algorithm was developed for the prediction of CRT outcome. Cluster analysis results produced results equivalent to those obtained from Fourier and scar analysis.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Smart Building Start (SBS) (CRADA 480)

The idea of Smart Building Start (SBS) is to manage the on/off scheduling of HVAC equipment in buildings in an optimal way in order to achieve comfort conditions at the designated times with the minimal use of energy. This concept is also known as Optimal Start and it has typically been used in buildings to start up equipment based on predictions made for a representative (or average) zone in a building. This means that zones that could have waited longer to receive conditioned air are activated too early leading to unnecessary energy loss. The approach proposed in this project is to develop and implement a distributed version of optimal start that will consider the individual requirements of all treated zones. The developed control strategy will enable smart start of the central plant as well as further localized control over each individual zone by means of setpoint adjustment so that zones are not conditioned too early thereby reducing energy use compared to the current state of the art. This project is a collaboration between PNNL and Verdicity with the goal being to bring the research concept of SBS to commercialization. The SBS algorithm(s) will be implemented and hosted on the PNNL-developed open-platform VOLTTRON which will accelerate bringing the research to practice. It is anticipated that this project will lead to new IP surrounding the algorithm and its decentralized deployment. The project will also further demonstrate the success of VOLTRON as a flexible platform for implementation of innovative algorithms for improving energy efficiency in buildings. Previous studies on smart building start carried out by PNNL have indicated potential energy savings on the order of 10-15% for multi-zone buildings compared to conventional strategies. Verdicity currently has a number of customers who can benefit from the use of this technology. PNNL will work with Verdicity to identify any key gaps in the integrated software and jointly work to enhance and customize it for Verdicity and to integrate it with their existing products for use at their customers’ sites. The proposed work will help previously funded Federal research and development technology investments find their way into a viable commercial market.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2016

Toward the Validation of Maternal Embryonic Leucine Zipper Kinase: Discovery, Optimization of Highly Potent and Selective Inhibitors, and Preliminary Biology Insight

MELK kinase has been implicated in playing an important role in tumorigenesis. Our previous studies suggested that MELK is involved in the regulation of cell cycle and its genetic depletion leads to growth inhibition in a subset of high MELK-expressing basal-like breast cancer cell lines. Herein we describe the discovery and optimization of novel MELK inhibitors 8a and 8b that recapitulate the cellular effects observed by short hairpin ribonucleic acid (shRNA)-mediated MELK knockdown in cellular models. We also discovered a novel fluorine-induced hydrophobic collapse that locked the ligand in its bioactive conformation and led to a 20-fold gain in potency. Here, these novel pharmacological inhibitors achieved high exposure in vivo and were well tolerated, which may allow further in vivo evaluation.

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

An automated and portable method for selecting an optimal GPU frequency

Power consumption poses a significant challenge in current and emerging graphics processing unit (GPU) enabled high-performance computing systems. In modern GPUs, dynamic voltage frequency scaling (DVFS) appears to be a reliable control to regulate power consumption and performance. However, the DVFS design space is large - hence, brute-force approaches are infeasible to select the optimal frequency. Furthermore, no single frequency can be universally optimal for applications with varying computational intensities. Thus, the application's complexity and the availability of a wide range of frequency settings are a challenge in selecting the optimal frequency configuration for a given GPU workload. To that end, this paper proposes a systematic approach that consists of three steps. The feature characterization study identifies the fine-grain GPU utilization metrics that influence the power consumption and execution time of a given workload. To understand the performance, power, and energy consumption behaviors of a workload across GPU's DVFS design space, we derived analytical power and performance models using the identified fine-grain features. Here, it is shown that the same set of GPU utilization metrics can estimate both the power consumption and execution time while being agnostic of changes to frequency and input sizes. Applying a power control with the single objective of reducing power may cause performance degradation, leading to more energy consumption. A multi-objective approach is proposed to select the optimal GPU DVFS configuration for a workload that reduces power consumption with negligible degradation in performance. The evaluation was conducted using SPEC ACCEL benchmarks and three real applications - NAMD LAMMPS, and LSTM on NVIDIA GV100, GA100, and AMD MI210 GPUs. On average, real applications showed 29.6% energy savings with a performance loss of 5.2% on GA100 and 22.6% energy savings with a performance loss of 4.7% on GV100. Moreover, the proposed models are portable to real applications, GPU architectures, and vendors, and require metric collection at only the default frequency rather than all supported DVFS configurations. Additionally, we conducted a comparison between our models and the GPU assembly instructions (PTX)-based static models. The results revealed a significant reduction in the average error rates, with a decrease from 19.7% to 3.1% for power models and from 29.4% to 5.2% for performance models.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Dynamic Programming and Error Estimates for Stochastic Control Problems with Maximum Cost

This work is concerned with stochastic optimal control for a running maximum cost. A direct approach based on dynamic programming techniques is studied leading to the characterization of the value function as the unique viscosity solution of a second order Hamilton–Jacobi–Bellman (HJB) equation with an oblique derivative boundary condition. A general numerical scheme is proposed and a convergence result is provided. Error estimates are obtained for the semi-Lagrangian scheme. These results can apply to the case of lookback options in finance. Moreover, optimal control problems with maximum cost arise in the characterization of the reachable sets for a system of controlled stochastic differential equations. Some numerical simulations on examples of reachable analysis are included to illustrate our approach.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Centralized and Decentralized Optimal Control of Variable Speed Heat Pumps

Utility service providers are often challenged with the synchronization of thermostatically controlled loads. Load synchronization, as a result of naturally occurring and demand-response events, has the potential to damage power distribution equipment. Because thermostatically controlled loads constitute most of the power consumed by the grid at any given time, the proper control of such devices can lead to significant energy savings and improved grid stability. The contribution of this paper is the development of an optimal control algorithm for commonly used variable speed heat pumps. By means of selective peer-to-peer communication, our control architecture allows for the regulation of home temperatures while simultaneously minimizing aggregate power consumption, and aggregate load volatility. An optimal centralized controller is also explored and compared against its decentralized counterpart.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2025

Enhancement of PyARC for Westinghouse Electric Company’s Lead Fast Reactor Design and Modeling (Final TCF Report)

Westinghouse Electric Company is a nuclear reactor vendor headquartered in the U.S. that is developing advanced reactor technology for the U.S. and global markets. Westinghouse has been relying on the neutronics Argonne Reactor Codes (ARC) executed through the NEAMS Workbench and its PyARC module that are developed under the DOE-NE Nuclear Energy Advanced Modeling and Simulation (NEAMS) and Advanced Reactor Technology (ART) – Fast Reactor programs. Through this user experience, Westinghouse identified several enhancements that would benefit the ARC codes’ usability by the US industry and therefore its commercialization potential. The enhancements were proposed to deliver both improvements in workflow and analysis capabilities to better support effective fast reactor core design and analysis to the nuclear industry. The PyARC workflow was extended in this project by integrating non-neutronic ARC codes DASSH and NUBOW-3D. The Ducted Assembly Steady-State Heat equation (DASSH) code is developed at ANL to perform steady-state thermal hydraulic sub-channel analysis in liquid metal fast reactor assemblies to determine optimized coolant flow and temperature distributions, which in this project was updated and validated for lead fast reactor (LFR) applications. The interface between REBUS and NUBOW-3D were improved in this project to assess the impact of the core restraint design and thermal induced expansion effects on the reactivity of the core, and to model the deformations of the fuel assemblies induced by temperature and irradiation. Finally, the ARC models that were extensively verified and validated through various SFR-based modeling benchmarks are extended in this project through code-to-code comparison on relevant LFR-specific neutronics benchmarks against Monte-Carlo neutronic solutions. Overall, this work enables verification of the capability of the ARC codes for a wide range of Generation-IV reactor designs. The outcome of this project is the release of a comprehensive modeling toolkit of validated, robust and efficient codes, as well as their user interface, that enables industry to perform a wide range of fast reactor analyses for design and licensing of their concepts.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Technoeconomic Design Optimization for Fast Reactors. Part I: Workflow Development and Case Study for Small LFR District Energy Application

The nuclear industry is developing small reactor designs that can target a variety of deployment locations and energy products. Smaller nuclear designs have traditionally struggled to handle the steep trade-offs between size and cost that have historically incentivized large reactors. This motivates computational optimization of small reactors to minimize costs and quantify the trade-off between size and cost. In this paper, the cost/size trade-off for a small fast reactor is derived using a multi-objective genetic algorithm optimization, with steady-state, transient, and cost analysis of the fast reactor being performed. Specifically, the method is demonstrated on a small 10- to 120-MW(thermal) U-Pu-Zr–fueled lead-cooled fast reactor with a 10-year core life for district energy applications, which can have a thermal load compatible with this range. The results reinforced that fast reactor cores at the lower end of this power range suffer cost penalties due to critical mass considerations. It was found that high power density cores with strong reactivity swings and many control rods were favored over designing to minimize reactivity swing. Furthermore, this contrasts with some traditional configurations designed using engineering judgment and demonstrates that optimizers can find nontraditional but realistic solutions, along with demonstrating the value of incorporating cost functions into whole-reactor design optimization.

Fast reactor↗
DOE OSTI2018

Speed Trajectory Optimization for a Heavy-Duty Truck Traversing Multiple Signalized Intersections: A Dynamic Programming Study

This paper explores the fuel savings that can be achieved by optimizing the speed trajectory of a heavy-duty truck traversing a sequence of intersections, under the assumptions that the behavior of the leading traffic and the timing of the traffic lights is known. Specifically, we look at the impact of corridor topology (i.e. green cycle lengths, phase offsets) on the expected fuel savings of the optimized trajectories. This is an important area of research because vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) technology has the potential to allow autonomous vehicles to reduce fuel consumption, especially in urban and sub-urban driving scenarios. The literature tackles the problem of arterial corridor trajectory optimization, and shows the potential fuel saving benefits. However, previous research focuses primarily on passenger vehicles, and often limits its findings to specific case studies. The main contribution of this paper is to offer an estimate of the fuel saving potential - for heavy-duty trucks and under different corridor characteristics - of optimizing trajectories in an urban arterial with V2V and V21 capabilities.

42 ENGINEERING↗
DOE OSTI2016

A Slag Management Toolset for Determining Optimal Coal Gasification Temperatures

Abstract Gasifier operation is an intricate process because of the complex relationship between slag chemistry and temperature, limitations of feedstock materials, and operational preference. High gasification temperatures increase refractory degradation, while low gasification temperatures can lead to slag buildup on the gasifier sidewall or exit, either of which are problematic during operation. Maximizing refractory service life and gasifier performance require finding an optimized operating temperature range which is a function of the coal slag chemistry and viscosity. Gasifier operators typically use a slag’s viscosity-temperature relationship and/or ash-fusion fluid temperature to determine the gasification temperature range. NETL has built a slag management toolset to determine the optimal temperature range for gasification of a carbon feedstock. This toolset is based on a viscosity database containing experimental data, and a number of models used to predict slag viscosity as a function of composition and temperature. Gasifier users typically have no scientific basis for selecting an operational temperature range for gasification, instead using experience to select operational conditions. The use of the toolset presented in this paper provides a basis for estimating or modifying carbon feedstock slags generated from ash impurities in carbon feedstock.

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

Survey of Multifidelity Methods in Uncertainty Propagation, Inference, and Optimization

In many situations across computational science and engineering, multiple computational models are available that describe a system of interest. These different models have varying evaluation costs and varying fidelities. Typically, a computationally expensive high-fidelity model describes the system with the accuracy required by the current application at hand, while lower-fidelity models are less accurate but computationally cheaper than the high-fidelity model. Outer-loop applications, such as optimization, inference, and uncertainty quantification, require multiple model evaluations at many different inputs, which often leads to computational demands that exceed available resources if only the high-fidelity model is used. This work surveys multifidelity methods that accelerate the solution of outer-loop applications by combining high-fidelity and low-fidelity model evaluations, where the low-fidelity evaluations arise from an explicit low-fidelity model (e.g., a simplified physics approximation, a reduced model, a data-fit surrogate) that approximates the same output quantity as the high-fidelity model. The overall premise of these multifidelity methods is that low-fidelity models are leveraged for speedup while the high-fidelity model is kept in the loop to establish accuracy and/or convergence guarantees. We categorize multifidelity methods according to three classes of strategies: adaptation, fusion, and filtering. The paper reviews multifidelity methods in the outer-loop contexts of uncertainty propagation, inference, and optimization.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Particle Swarm Optimisation for group structure optimization for radiotherapy shielding

Neutron transport simulations are ubiquitous in nuclear engineering because they allow one to model experimental systems and render a model platform for easy perturbation of experimental designs. In addition, simulations allow one to gain experimental insight without actually having to go through the trouble of building a physical experiment. Neutron transport simulations can be stochastic or deterministic based. Stochastic neutron transport simulations are typically simulated using the Monte Carlo method and yield very accurate solutions but are computationally expensive, while deterministic methods are typically faster but can be less accurate. Here we focus on optimizing the accuracy of deterministic neutron transport simulations for radiotherapy simulations. Deterministic neutron transport requires discretization of angle, energy, and space to appropriately analyze the system one is trying to model. Discretization of energy is challenging because of the highly variable neutron flux at certain neutron energies. Improper discretization of energy in the transport model can lead to erroneous results and therefore inaccurate interpretations of the solution. In this study, we evaluate Particle Swarm Optimization (PSO) as a mechanism for selecting optimal group structures for radiotherapy shielding. We tested the particle swarm optimization algorithm on radiotherapy shielding problems using Los Alamos National Laboratory's (LANL) main deterministic transport code PARTISN. Results show that the optimized energy group structures generated from the optimization algorithm outperformed LANL's standard energy group structures, and therefore demonstrate utility in using PSO to expedite computation times due to the increased accuracy obtained with a smaller but optimized group structure. (authors)

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

A modified cosmic brane proposal for holographic Renyi entropy

We propose a new formula for computing holographic Renyi entropies in the presence of multiple extremal surfaces. Our proposal is based on computing the wave function in the basis of fixed-area states and assuming a diagonal approximation for the Renyi entropy. For Renyi index n ≥ 1, our proposal agrees with the existing cosmic brane proposal for holographic Renyi entropy. For n < 1, however, our proposal predicts a new phase with leading order (in Newton’s constant G) corrections to the cosmic brane proposal, even far from entanglement phase transitions and when bulk quantum corrections are unimportant. Recast in terms of optimization over fixed-area states, the difference between the two proposals can be understood to come from the order of optimization: for n < 1, the cosmic brane proposal is a minimax prescription whereas our proposal is a maximin prescription. We demonstrate the presence of such leading order corrections using illustrative examples. In particular, our proposal reproduces existing results in the literature for the PSSY model and high-energy eigenstates, providing a universal explanation for previously found leading order corrections to the n < 1 Renyi entropies.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2011

Insider Models with Finite Utility in Markets with Jumps

In this article we consider, under a Levy process model for the stock price, the utility optimization problem for an insider agent whose additional information is the final price of the stock blurred with an additional independent noise which vanishes as the final time approaches. Our main interest is establishing conditions under which the utility of the insider is finite. Mathematically, the problem entails the study of a 'progressive' enlargement of filtration with respect to random measures. We study the jump structure of the process which leads to the conclusion that in most cases the utility of the insider is finite and his optimal portfolio is bounded. This can be explained financially by the high risks involved in models with jumps.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Research Highlight - Dispatch Optimization, System Design and Cost Benefit Analysis of a Nuclear Reactor with Molten Salt Thermal Storage

We highlight our work from our previous publication titled "Dispatch Optimization, System Design, and Cost Benefit Analysis of a Nuclear Reactor with Molten Salt Thermal Storage" published in MDPI Energies 2022 (doi.org/10.3390/en15103599). Variable renewable energy availability has increased the volatility in energy prices in most markets. Nuclear power plants, with a large ratio of capital to variable costs, have historically operated as base load energy suppliers but the need for more flexible operation is increasing. We simulate the techno-economic performance of a 950 MWt nuclear power plant, based on the Westinghouse lead-cooled fast reactor, coupled with molten salt thermal storage as a method for flexible energy dispatch. We use the System Advisor Model to model the nuclear reactor thermal power input and power cycle operating modes. We combine this robust engineering model with a mixed-integer linear program model for optimized dispatch scheduling. We then simulate the coupled nuclear and thermal storage system under different market scenarios with varying price volatility. We find that the coupled plant outperforms the base plant under markets where energy price peaks fluctuate by a factor of two or more about the mean price. We show that a calculated power purchase agreement price for the plant improves by up to 10% when operating under California energy market conditions. Sensitivity analysis on the thermal storage cost shows that the optimal design remains unchanged even when doubling costs.

97 MATHEMATICS AND COMPUTING↗