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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 703 records · Page 39
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

A Trapping-Micro-LC-FAIMS/dCV-MS Strategy for Ultrasensitive and Robust Targeted Quantification of Protein Drugs and Biomarkers

The sensitivity of LC-MS in quantifying target proteins in plasma/tissues is significantly hindered by co-eluted matrix interferences. While antibody-based immuno-enrichment effectively reduces interferences, developing and optimizing antibodies are often time-consuming and costly. Here, in this study, by leveraging the orthogonal separation capability of Field Asymmetric Ion Mobility Spectrometry (FAIMS), we developed a FAIMS/differential-compensation-voltage (FAIMS/dCV) method for antibody-free, robust, and ultra-sensitive quantification of target proteins directly from plasma/tissue digests. By comparing the intensity-CV profiles of the target vs. co-eluted endogenous interferences, the FAIMS/dCV approach identifies the optimal CV for quantification of each target protein, thus maximizing the signal-to-noise ratio (S/N). Compared to quantification without FAIMS, this technique dramatically reduces endogenous interferences, showing a median improvement of the S/N by 14.8-fold for the quantification of 17 representative protein drugs and biomarkers in plasma or tissues and a 5.2-fold median increase in S/N over conventional FAIMS approach, which uses the peak CV of each target. We also discovered that the established CV parameters remain consistent over months and are matrix-independent, affirming the robustness of the developed FAIMS/dCV method and the transferability of the method across matrices. The developed method was successfully demonstrated in three applications: the quantification of monoclonal antibodies with sub-ng/mL LOQ in plasma, an investigation of the time courses of evolocumab and its target PCSK9 in a preclinical setting, and a clinical investigation of low abundance obesity-related biomarkers. This innovative and easy-to-use method has extensive potential in clinical and pharmaceutical research, particularly where sensitive and high-throughput quantification of protein drugs and biomarkers is required.

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

Ex situ metrology and data processing techniques developed at the ALS for optimization of beamline performance of bendable x-ray mirrors

We discuss experimental, analytical, and numerical methods recently developed at the Advanced Light Source (ALS) X?Ray Optics Laboratory (XROL) for calibration and precision shaping of bendable x-ray mirrors. The methods are based on ex situ measurements with the mirrors using surface slope profilers available at the ALS XROL. The first realization of methods and dedicated software has allowed the optimization of the beamline performance of bendable mirrors by adjustment of the mirror shape to minimize the root-mean-square variation of residual (after subtraction of the ideal desired shape) slope deviations from ideal (specified) surface figure. Here, we further develop the methods that in application to elliptically bent mirrors adapt as a figure of merit the minimum of the rms size of the focused beam. The efficacy of the developed methods is demonstrated with examples of optimal tuning of an elliptically bendable cylindrical mirror designed for the ALS beamline 10.3.2.

Yashchuk, VV↗
DOE OSTI2020

A Comparison of DER Voltage Regulation Technologies Using Real-Time Simulations

Grid operators are now considering using distributed energy resources (DERs) to provide distribution voltage regulation rather than installing costly voltage regulation hardware. DER devices include multiple adjustable reactive power control functions, so grid operators have the difficult decision of selecting the best operating mode and settings for the DER. In this work, we develop a novel state estimation-based particle swarm optimization (PSO) for distribution voltage regulation using DER-reactive power setpoints and establish a methodology to validate and compare it against alternative DER control technologies (volt–VAR (VV), extremum seeking control (ESC)) in increasingly higher fidelity environments. Distribution system real-time simulations with virtualized and power hardware-in-the-loop (PHIL)-interfaced DER equipment were run to evaluate the implementations and select the best voltage regulation technique. Each method improved the distribution system voltage profile; VV did not reach the global optimum but the PSO and ESC methods optimized the reactive power contributions of multiple DER devices to approach the optimal solution.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Machine learning-driven predictive resource management in complex science workflows

Here, the collaborative efforts of large communities in science experiments, often comprising thousands of global members, reflect a monumental commitment to exploration and discovery. Recently, advanced and complex data processing has gained increasing importance in science experiments. Data processing workflows typically consist of multiple intricate steps, and the precise specification of resource requirements is crucial for each step to allocate optimal resources for effective processing. Estimating resource requirements in advance is challenging due to a wide range of analysis scenarios, varying skill levels among community members, and the continuously increasing spectrum of computing options. One practical approach to mitigate these challenges involves initially processing a subset of each step to measure precise resource utilization from actual processing profiles before completing the entire step. While this two-staged approach enables processing on optimal resources for most of the workflow, it has drawbacks such as initial inaccuracies leading to potential failures and suboptimal resource usage, along with overhead from waiting for initial processing completion, which is critical for fast-turnaround analyses. In this context, our study introduces a novel pipeline of machine learning models within a comprehensive workflow management system, the Production and Distributed Analysis (PanDA) system. These models employ advanced machine learning techniques to predict key resource requirements, overcoming challenges posed by limited upfront knowledge of characteristics at each step. Accurate forecasts of resource requirements enable informed and proactive decision-making in workflow management, enhancing the efficiency of handling diverse, complex workflows across heterogeneous resources.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Optimal Strategies for Hybrid Battery‐Storage Systems Design

As stationary hybrid energy‐storage systems (HESS) for power systems applications have recently drawn interest due to their enhanced performance and decreasing cost, developing systematic approaches for HESS design while considering controls is gaining traction. Herein, a method is presented to optimally design hybrid battery storage by proposing a mathematical modeling framework, formulated as a mixed integer linear programming model. The optimization is capable of handling multiple subsystems of batteries, considering their economic and technological performance. Decisions involve sizing of the batteries, optimal temporal and strategic dispatch to end uses, and energy sources for charging each battery. The applicability of the model is tested on four case studies for three battery chemistries representing distinct objectives: high‐power, high‐energy, and second life. Compared to traditionally designed battery storage with a homogeneous battery, optimally designed hybrid systems can save 12%–26% of system costs, depending on the nature of the dispatch profile. Findings point to design preference toward the second life battery supplemented with some high‐power or high‐energy battery capacity, or both. With the utilized electricity price structure, customers can experience approximately 10%–35% reduction in their bills.

Koleva, Mariya↗
NASA NTRS1993

A CFD-based aerodynamic design procedure for hypersonic wind-tunnel nozzles

A new procedure which unifies the best of current classical design practices, computational fluid dynamics (CFD), and optimization procedures is demonstrated for designing the aerodynamic lines of hypersonic wind-tunnel nozzles. The new procedure can be used to design hypersonic wind tunnel nozzles with thick boundary layers where the classical design procedure has been shown to break down. An efficient CFD code, which solves the parabolized Navier-Stokes (PNS) equations using an explicit upwind algorithm, is coupled to a least-squares (LS) optimization procedure. A LS problem is formulated to minimize the difference between the computed flow field and the objective function, consisting of the centerline Mach number distribution and the exit Mach number and flow angle profiles. The aerodynamic lines of the nozzle are defined using a cubic spline, the slopes of which are optimized with the design procedure. The advantages of the new procedure are that it allows full use of powerful CFD codes in the design process, solves an optimization problem to determine the new contour, can be used to design new nozzles or improve sections of existing nozzles, and automatically compensates the nozzle contour for viscous effects as part of the unified design procedure. The new procedure is demonstrated by designing two Mach 15, a Mach 12, and a Mach 18 helium nozzles. The flexibility of the procedure is demonstrated by designing the two Mach 15 nozzles using different constraints, the first nozzle for a fixed length and exit diameter and the second nozzle for a fixed length and throat diameter. The computed flow field for the Mach 15 least squares parabolized Navier-Stokes (LS/PNS) designed nozzle is compared with the classically designed nozzle and demonstrates a significant improvement in the flow expansion process and uniform core region.

Korte, John J.↗
NASA NTRS1986

Toward a systematic design theory for silicon solar cells using optimization techniques

This work is a first detailed attempt to systematize the design of silicon solar cells. Design principles follow from three theorems. Although the results hold only under low injection conditions in base and emitter regions, they hold for arbitrary doping profiles and include the effects of drift fields, high/low junctions and heavy doping concentrations of donor or acceptor atoms. Several optimal designs are derived from the theorems, one of which involves a three-dimensional morphology in the emitter region. The theorems are derived from a nonlinear differential equation of the Riccati form, the dependent variable of which is a normalized recombination particle current.

Misiakos, K.↗
DOE OSTI2021

Optimized Dispatch of Distributed Energy Resources for Resiliency and Power Quality Improvements at the Grid-Edge

Distributed Energy Resources (DERs) installed on low-voltage distribution systems, both utility-owned and nonutility owned may be employed to make improvements to system resiliency and power quality, in addition to simply serving load demand. By selectively dispatching active and reactive power from these existing DERs, improvements in voltage profiles and service availability during adverse events may be achieved. Further benefits can be gained by optimally choosing which DERs to dispatch power from, and the distribution of power from those DERs. For a given operating condition, using Linear Programming methods, optimal power dispatch values for individual DERs can be determined, while considering variables such as voltage gains, losses in the lines and the DERs, and DER reserve capacities. One such optimization technique is developed in this paper, and results from a real-time simulation study on a modified IEEE 13-bus distribution system with three DERs, are being presented. The operation of the optimized DER selection and dispatch algorithm is shown during normal operation of the transmission system when the DERs operate in grid-connected mode. Similar analyses can drive decision making during transmission system failure when the DERs operate in grid-forming or islanded mode.

Chowdhury, Prithwiraj Roy↗
DOE OSTI2019

Parallel Computing for Module-Based Computational Experiment

Large-scale scientific code plays an important role in scientific researches. In order to facilitate module and element evaluation in scientific applications, we introduce a unit testing framework and describe the demand for module-based experiment customization. We then develop a parallel version of the unit testing framework to handle long-term simulations with a large amount of data. Specifically, we apply message passing based parallelization and I/O behavior optimization to improve the performance of the unit testing framework and use profiling result to guide the parallel process implementation. Finally, we present a case study on litter decomposition experiment using a standalone module from a large-scale Earth System Model. This case study is also a good demonstration on the scalability, portability, and high-efficiency of the framework.

Yao, Zhuo↗
DOE OSTI2019

Synthesis and in silico and in vitro evaluation of trimethoxy-benzamides designed as anti-prion derivatives

Transmissible spongiform encephalopathies (TSEs), also known as prion diseases, are neurodegenerative disorders which affect mammals, including the human species, and arise after the conversion of the monomeric cellular prion protein (PrP{sup C}) into the aggregated scrapie form (PrP{sup Sc}). There is no therapy to treat TSEs and the identification of compounds that bind PrP{sup C}, preventing its conversion into PrP{sup Sc}, is a viable therapeutic strategy. We designed and synthesized six novel trimethoxy-benzamide compounds as anti-prion drug candidates. Molecular docking analyses predicted that all the derivatives bind to a hotspot region located in the PrP globular domain with very similar spatial orientation and interaction mode. Although none of the analogs inhibited in vitro-aggregation of recombinant PrP (rPrP) in a cell-free conversion assay, the RT-QuIC, compound 8a accelerated rPrP conversion into PrP{sup Sc}-like species. STD-NMR and ITC analyses indicated that both 8a and 8b bind to rPrP{sup 90–231}. These analogs were toxic to PrP{sup Sc}-infected cell lines, hence we could not assess their anti-prion activity by using this cellular approach, although this toxicity was cell line-dependent. These results point out that the 4-amino-quinoline trimethoxy-benzamide scaffold described herein represents a novel chemical pattern useful as a starting point for future structural optimization in the design of PrP ligands with improved affinity and safety profiles.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

The MPI_T events interface: An early evaluation and overview of the interface

Understanding the behavior of parallel applications that use the Message Passing Interface (MPI) is critical for optimizing communication performance. Performance tools for MPI currently rely on the PMPI Profiling Interface or the MPI Tool Information Interface, MPI_T, for portably collecting information for performance measurement and analysis. While tools using these interfaces have proven to be extremely valuable for performance tuning, these interfaces only provide synchronous information, i.e., when an MPI or an MPI_T function is called. There is currently no option for collecting information about asynchronous events from within the MPI library. Here, we propose a callback-driven interface for event notification from MPI implementations. Our approach is integrated in the existing MPI_T interface and provides a portable API for tools to discover and register for events of interest. We implement our MPI_T Events interface in Open MPI and demonstrate its functionality and usability with a small logging tool (MEL) as well as an early integration into the comprehensive measurement infrastructure Score-P.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

An Optimization-Based State Estimation Framework for Large-Scale Natural Gas Networks

We propose an optimization-based state estimation framework to track internal spacetime flow and pressure profiles of natural gas networks during dynamic transients. We find that the estimation problem is ill-posed (because of the infinite-dimensional nature of the states) and that this leads to instability of the estimator when short estimation horizons are used. To circumvent this issue, we propose moving horizon strategies that incorporate prior information. In particular, we propose a strategy that initializes the prior using steady-state information and compare its performance against a strategy that does not initialize the prior. We find that both strategies are capable of tracking the state profiles but we also find that superior performance is obtained with steady-state prior initialization. We also find that, under the proposed framework, pressure sensor information at junctions is sufficient to track the state profiles. We also derive approximate transport models and show that some of these can be used to achieve significant computational speed-ups without sacrificing estimation performance. We show that the estimator can be easily implemented in the graph-based modeling framework Plasmo.jl and use a multipipeline network study to demonstrate the developments.

Jalving, Jordan↗
DOE OSTI2022

Multi-objective goal-directed optimization of de novo stable organic radicals for aqueous redox flow batteries

Abstract Advances in the field of goal-directed molecular optimization offer the promise of finding feasible candidates for even the most challenging molecular design applications. One example of a fundamental design challenge is the search for novel stable radical scaffolds for an aqueous redox flow battery that simultaneously satisfy redox requirements at the anode and cathode, as relatively few stable organic radicals are known to exist. To meet this challenge, we develop a new open-source molecular optimization framework based on AlphaZero coupled with a fast, machine-learning-derived surrogate objective trained with nearly 100,000 quantum chemistry simulations. The objective function comprises two graph neural networks: one that predicts adiabatic oxidation and reduction potentials and a second that predicts electron density and local three-dimensional environment, previously shown to be correlated with radical persistence and stability. With no hard-coded knowledge of organic chemistry, the reinforcement learning agent finds molecule candidates that satisfy a precise combination of redox, stability and synthesizability requirements defined at the quantum chemistry level, many of which have reasonable predicted retrosynthetic pathways. The optimized molecules show that alternative stable radical scaffolds may offer a unique profile of stability and redox potentials to enable low-cost symmetric aqueous redox flow batteries.

25 ENERGY STORAGE↗
DOE OSTI2022

Optimization of quasi-symmetric stellarators with self-consistent bootstrap current and energetic particle confinement

Quasi-symmetry can greatly improve the confinement of energetic particles and thermal plasma in a stellarator. The magnetic field of a quasi-symmetric stellarator at high plasma pressure is significantly affected by the bootstrap current, but the computational cost of accurate stellarator bootstrap calculations has precluded use inside optimization. Here, a new efficient method is demonstrated for optimization of quasi-symmetric stellarator configurations such that the bootstrap current profile is consistent with the geometry. The approach is based on the fact that all neoclassical phenomena in quasi-symmetry are isomorphic to those in axisymmetry. Therefore, accurate formulas for the bootstrap current in tokamaks, which can be evaluated rapidly, can be applied also in stellarators. The deviation between this predicted parallel current and the actual parallel current in the magnetohydrodynamic equilibrium is penalized in the objective function, and the current profile of the equilibrium is included in the parameter space. Quasi-symmetric configurations with significant pressure are thereby obtained with self-consistent bootstrap current and excellent confinement. In a comparison of fusion-produced alpha particle confinement across many stellarators, the new configurations have significantly lower alpha energy losses than many previous designs.

Landreman, M. (ORCID:000000027233577X)↗
DOE OSTI2018

Electron-cyclotron-resonance heating in Wendelstein 7-X: A versatile heating and current-drive method and a tool for in-depth physics studies

For stellarators, which need no or only small amounts of current drive, electron-cyclotron-resonance heating (ECRH) is a promising heating method even for the envisaged application in a fusion power plant. Wendelstein 7-X (W7-X) is equipped with a steady-state capable ECRH system, operating at 140 GHz, which corresponds to the 2nd cyclotron harmonic of the electrons at a magnetic field of 2.5 T. Ten gyrotrons are operational and already delivered 7 MW to W7-X plasmas. Combined with pellet injection, the highest triple product (0.68 × 10 20 keV m –3 s), observed up to now in stellarators, was achieved. For the first time, W7-X plasmas were sustained by 2nd harmonic O-mode heating, approaching the collisionality regime for which W7-X was optimized. Power deposition scans did not show any indication of electron temperature profile resilience. In low-density, low-power plasmas a compensation of the bootstrap current with electron-cyclotron current drive (ECCD) was demonstrated. Furthermore, sufficiently strong ECCD close to the plasma centre produced periodic internal plasma-crash events, which coincide with the appearance of low order rationals of the rotational transform.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Variable-spectrum mode control of high poloidal beta discharges

DIII-D experiments demonstrate that high pressure, broad current profile equilibria can be accessed in the high poloidal beta regime by optimizing the MHD mode control poloidal spectrum. A novel, variable spectrum (VS) magnetic feedback scheme implemented using the DIII-D internal non-axisymmetric coils (I-coils) facilitated access to reduced internal inductance $l$ i operation above the no-wall beta limit compared with both no feedback and fixed spectrum feedback. In addition, the VS feedback helped avoid beta collapses caused by marginally unstable resistive wall mode activity. The lower and upper I-coil rows were configured in two independent feedback loops, allowing the feedback field's poloidal spectrum to vary and track changes in the plasma mode structure as the edge safety factor q 95 varied from 11 to 6 during the discharges. The q 95 dependence of the measured phase difference between the lower and upper I-coil rows during VS feedback is qualitatively compatible with ideal MHD simulations of the least-stable plasma kink mode and with plasma response simulations that included kinetic modifications to ideal MHD. The VS feedback approach is a straightforward way to improve resilience to variations in mode structure that occur as plasma parameters change. The demonstrated expansion of the operating space to lower $l$ i is expected to improve the coupling of the plasma kink mode to external fields and beneficial wall eddy currents, and is compatible with high bootstrap fraction operation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗