Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Performance optimization”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 613 records · Page 34

Addition of Chloroform in a Solvent-in-Salt Electrolyte: Outcomes in the Microscopic Dynamics in Bulk and Confinement

Solvent-in-salt electrolytes (SISEs) are a promising alternative to the electrolytes currently used in commercial devices. Despite the SISEs’ advantages, their utilization is not yet realized due to the poor mobility of their chemical species. Here, we explore this problem by adding chloroform to a SISE formed by acetonitrile and a Li-salt. First, we performed illustrative cycling experiments to highlight the potential of this approach. Then, we focused on the description of the microscopic dynamics of the electrolytes and exposed the relevant aspects to be considered for their optimal performance. While the conductivity at low temperatures may be enhanced by the addition of chloroform, only subtle changes occur at room temperature. As revealed by molecular dynamics simulations and quasielastic neutron scattering (QENS) experiments, this effect is related to the preservation of the structure expected for a highly concentrated solution and promotion of the formation of ionic aggregates. These outcomes occur despite the increase in the overall mobility of the chemical species. The dynamics of the electrolytes in porous carbon was also investigated using QENS. In these circumstances, low concentrations of chloroform lead to diffusivities of the molecular species higher than those observed for the bulk electrolytes. As chloroform’s concentration increases, no further changes in the diffusivities are observed. Nonetheless, chloroform is mostly immobilized on the carbon surfaces and this behavior may be intensified at compositions closer to the eutectic mixture.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Conductor Specification and Validation for High-Luminosity LHC Quadrupole Magnets

The High Luminosity Upgrade of the Large Hadron Collider (HL-LHC) at CERN will replace the main ring inner triplet quadrupoles, identified by the acronym MQXF, adjacent to the main ring intersection regions. For the past decade, the U.S. LHC Accelerator R&D Program, LARP, has been evaluating conductors for the MQXFA prototypes, which are the outer magnets of the triplet. Recently, the requirements for MQXF magnets and cables have been published in P. Ferracin et al., IEEE Trans. Appl. Supercond., vol. 26, no. 4, 2016, Art. no.4000207, along with the final specification for Ti-alloyed Nb3Sn conductor determined jointly by CERN and LARP. This paper describes the rationale beneath the 0.85 mm diameter strand’s chief parameters, which are 108 or more sub-elements, a copper fraction not less than 52.4%, strand critical current at 4.22 K not less than 631 A at 12 T and 331 A at 15 T, and residual resistance ratio of not less than 150. This paper also compares the performance for ~100 km production lots of the five most recent LARP conductors to the first 163 km of strand made according to the HL-LHC specification. Two factors emerge as significant for optimizing performance and minimizing risk: a modest increase of the sub-element diameter from 50 to 55 μm, and a Nb:Sn molar ratio of 3.6 instead of 3.4. Furthermore, the statistics acquired so far give confidence that the present conductor can balance competing demands in production for the HL-LHC project.

43 PARTICLE ACCELERATORS↗

Consensus Control (Wind Farm Collective Yaw Control) [SWR-19-11]

Wind turbines in a wind farm typically operate individually to maximize their own performance and do not take into account information from nearby turbines. In an autonomous wind farm, enabling cooperation to achieve farm-level objectives, turbines will need to use information from nearby turbines to optimize performance, ensure resiliency when other sensors fail, and adapt to changing local conditions. A key element of achieving an autonomous wind farm is to develop algorithms that provide necessary information to ensure reliable, robust, and efficient operation of wind turbines in a wind plant using local sensor information that is already being collected, such as supervisory control and data acquisition (SCADA) data, local meteorological stations, and nearby radars/sodars/lidars. This code implements a framework for implementing an autonomous wind farm that incorporates information from local sensors in real time to better align turbines in a wind farm. Oftentimes, measurements made at an individual turbine are noisy and unreliable. By incorporating measurements from multiple nearby turbines, a more robust estimate of the wind direction can be obtained at an individual turbine. Results indicate that this estimate of the wind direction can be used to improve the turbine's knowledge of the wind direction and could decrease dynamic yaw misalignment, decrease the amount of time a turbine spends yawing due to a more robust input to the yaw controller, and increase resiliency to faulty wind-vane measurements.

King, Jennifer↗

Develop Wake Mitigation Strategy (CRADA CRD-17-00693 Final Report)

Wind turbines in a wind farm typically operate individually to maximize their own performance and do not take into account information from nearby turbines. In an autonomous wind farm, enabling cooperation to achieve farm-level objectives, turbines will need to use information from nearby turbines to optimize performance, ensure resiliency when other sensors fail, and adapt to changing local conditions. A key element of achieving an autonomous wind farm is to develop algorithms that provide necessary information to ensure reliable, robust, and efficient operation of wind turbines in a wind plant using local sensor information that is already being collected, such as supervisory control and data acquisition (SCADA) data, local meteorological stations, and nearby radars/sodars/lidars. In this work consensus control is applied in a hybrid analysis to data from an existing wind farm to demonstrate the benefit of consensus control.

17 WIND ENERGY↗

Revealing the Full Potential of Glycolated Mixed Ionic-Electronic Semiconductors – Symmetric Monomer Polymerization to Boost Electrochemical Transistor Performance

Organic electrochemical transistors (OECTs) enable the transduction of ionic signals into electronic outputs, positioning them as ideal candidates for next-generation sensing and (bio)signal processing applications. Recent years have witnessed the development of various OECT channel materials, affording insights into structural fine-tuning to achieve optimal performance and/or stability. However, homocouplings, commonly present in alternating conjugated polymers, have largely been overlooked. This study investigates the effect of homocoupling on OECT materials by employing two synthesis methods – standard Stille polymerization and an alternative symmetric approach – to create the p-type enhancement-mode benchmark polymer pgBTTT. The impact of homocoupling, and its absence, is studied by comparing the bulk properties of the two polymers and evaluating their respective OECT metrics. The new, homocoupling-free polymer exhibits a notably improved OECT performance ( μC *), mainly due to an average 3-fold increase in electronic mobility (μ).

defects↗

Optimal Control and Architecture Design Optimization for Hydraulic Drive Train of a Compact Track Loader

Hydrostatic transmission (HST) is a common hydraulic drive train transmission used in track loaders and other high power off-road vehicles. While reliable, traditional HST with fixed-displacement motors has relatively poor efficiencies. In this paper, alternative HST and series hybrid drive train architectures are proposed to replace the traditional HST to allow the implementation of optimal control and optimization methods for better vehicle fuel efficiency. Besides the optimal control methods applied to minimize fuel consumption, the proposed architectures are also optimized for the best configuration in terms of component sizing. Backward-facing (acausal) simulation models were developed to estimate the fuel efficiency of each architecture. Finally, each architecture is compared for optimized performance and fuel saving relative to the traditional HST as baseline.

33 ADVANCED PROPULSION SYSTEMS↗

Advancing Understanding of Fission Gas Behavior in Nuclear Fuel through Leadership Class Computing

This report describes the outcome of the pilot SciDAC project jointly funded by the DOE Office of Nuclear Energy and the DOE Office of Science, Advanced Scientific Computing Research to advance understanding of fission gas behavior in nuclear fuel. The computational approach involved utilizing both a bottom up and top down multiscale materials modeling to evaluate the processes of xenon fission gas diffusion, xenon clustering and precipitation and the mechanisms of fission gas resolution by energetic fission fragments in uranium dioxide nuclear fuel. The computer science and applied mathematics research activities were focused on optimizing the uranium – oxygen – xenon interatomic potential implementation in the LAMMPS molecular dynamics code for large-scale simulations of fission gas resolution, in addition to improvements in visualization of accelerated molecular dynamics simulations and performance optimization of the Xolotl continuum cluster dynamics with a new grouping scheme to reduce the computational cost of modeling very large fission gas bubbles containing more than 10,000 xenon atoms. The most impactful result from this project stems from a systematic series of atomistic molecular dynamics to evaluate fission gas resolution from xenon bubbles that, combined with the fission product yields and consideration of electron-phonon coupling, informed a first principles model that predicts the magnitude of fission gas resolution in good agreement with empirical estimates.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Structural and optical properties for typical solid mirror shapes

A method is developed to determine the weight, center of gravity, areal properties, and mass inertial properties for typical mirrors. A number of support conditions were considered to examine optical surface deflections, surface quality, and fundamental natural frequency for single- and double-arch mirror shapes. Structural performance estimates were made with the NASTRAN program, and optical performances were evaluated with the FRINGE program, using an SXA 40-in mirror. To show the behavior of element types from the NASTRAN program, finite element validity and sensitivity studies were performed in optical model applications. Material parameters, contoured back shapes, and support locations are shown to have significant effects on structural and optical performances. Optimal support locations and support points are given. Fundamental natural frequencies for some shapes are found with the closed-form solution. The plate models results may not be acceptable for determining real mirror optical performances.

Cho, Myung K.↗

Mixed and Doped Solid Sorbents for CO 2 Capture Applications

The objectives of this presentation are to capture CO2 we need materials with optimal performance and low costs; establish a theoretical procedure to identify most potential candidates of CO 2 solid sorbents from a large solid material databank; computational synthesis new materials to fit industrial needs; and explore the optimal working conditions for the promised CO 2 solid sorbents, especially from room to warm T ranges with optimal energy usage.

01 COAL, LIGNITE, AND PEAT↗

LSAFE: a Lightweight Static Analysis Framework for binary Executables

Static analysis is a widely used technique for analyzing various aspects of programs. However, as programs become more complex, static analysis tools require larger resources, such as CPU time and memory, to perform the same tasks. Moreover, the source code of programs may not always be accessible, requiring static analysis to be performed on the binary executable code directly. To overcome these challenges, we propose a lightweight static analysis framework called LSAFE, which constructs control flow graphs (CFGs) and data dependency graphs (DDGs) of target programs with optimized performance in terms of CPU and memory usage. We evaluated the proposed framework using both Spec benchmark programs and real-world industrial applications, and found that it outperformed Angr, an existing state-of-the-art static analysis tool. Additionally, we demonstrate a case study that utilizes the CFG generated by LSAFE to detect memory leaks.

Qu, Guangzhi↗

Irradiation Performance: High-Temperature Gas Reactor Fuels

The response of TRISO fuel under irradiation is complex and dictated by the integrated nature of all components which define the TRISO fuel architecture. Potential failure mechanisms have been well understood and iterative improvements to the TRISO fuel architecture have been made to ensure optimized performance for different reactor designs. Ultimately, modern TRISO fuel for HTGR applications has exceeded performance targets.

Gerczak, Tyler↗

A Goldilocks Approach to Water Management: Hydrochannel Porous Transport Layers for Unitized Reversible Fuel Cells

Abstract This work presents a novel porous transport layer (PTL), the hydrochannel PTL, that enables improved water management and record high round trip efficiency in unitized reversible fuel cells (URFCs). URFCs require rapid transport of O 2 and H 2 O to provide high performance in both fuel cell and water electrolyzer operation, but cell design is complicated by conflicting water management requirements: electrolyzers perform best with high liquid water saturation, whereas fuel cells perform best when liquid water saturation is as low as possible while still maintaining effective ionomer hydration. The hydrochannel PTL circumvents this obstacle by providing hydrophilic channels for water transport through an otherwise hydrophobic PTL, enabling optimal performance in both fuel cell and water electrolyzer modes. Neutron radiography measurements of water content in both operating modes confirm that the hydrochannel PTL enables high performance due to its improved water management capabilities.

25 ENERGY STORAGE↗

Electrochromic performance of nanocomposite nickel oxide counter electrodes containing lithium and zirconium

Nickel oxide materials are suitable for counter electrodes in complementary electrochromic devices. The state-of-the-art nickel oxide counter electrode materials are typically prepared with multiple additives to enhance peformance. Herein, nanocomposite nickel oxide counter electrodes were fabricated via RF magnetron co-sputtering from Ni-Zr alloy and Li2O ceramic targets. The as-deposited nanocomposite counter electrodes were characterized with inductively coupled plasma mass spectrometry (ICP-MS), scanning electron microscopy (SEM), high-resolution transmission electron microscopy (HRTEM), X-ray diffraction (XRD), and X-ray absorption spectroscopy (XAS). It was found that the stoichiometry, crystal structure and electronic structure of the nickel oxide-based materials could be readily tuned by varying the Li2O sputter deposition power level. Comprehensive electrochromic evaluation demonstrated that the performance of the nickel oxide-based materials was dependent on the overall Li stoichiometry. Overall, the nanocomposite nickel oxide counter electrode containing lithium and zirconium synthesized with a Li2O deposition power of 45 W exhibited the optimal performance with an optical modulation of 71% and coloration efficiency of 30 cm2/C at 670 nm in Li-ion electrolyte.

36 MATERIALS SCIENCE↗

ORCHA: A performance portability system for extreme heterogeneity

Heterogeneity is the prevalent trend in the rapidly evolving high-performance computing (HPC) landscape in both hardware and application software. The diversity in hardware platforms, currently comprising various accelerators and a future possibility of specializable chiplets, poses a significant challenge for scientific software developers aiming to harness optimal performance across different computing platforms while maintaining the quality of solutions when their applications are simultaneously growing more complex. Code synthesis and code generation can provide mechanisms to mitigate this challenge. We have developed a divide and conquer approach where different aspects of performance are handled by different stand-alone tools that are interfaced with the application through generated code. This portability system, ORCHA, enables users to configure and orchestrate their computations among available resources on a platform by specifying a high-level recipe, thereby permitting a many-to-many paradigm where each recipe results in a different variant of the application. The core design goal is to let users decide the application’s hardware mapping and orchestration by editing only the high-level recipe—without modifying the maintained source code or binding the application to a particular runtime system. Tools in ORCHA distribution are: CG-Kit for translating the recipe into an execution graph; Milhoja to execute the graph by orchestrating data and task movement among hardware resources; and Macroprocessor that enables users to define their own code-shorthand for higher composability and easier management of code variants. Additionally, the design of ORCHA permits tools to work in a plug-and-play mode where the application can build and run without CG-Kit and Milhoja, and either tool can be swapped out for other tools with similar capabilities by modifying the code generation portion of ORCHA. In this paper, we describe the design of ORCHA and the role that code-generation plays in isolating applications from tools. We demonstrate the breadth of configurations ORCHA enables with a case study in which an application configuration is realized on three distinct hardware mappings—a GPU-centric, a CPU/GPU balanced, and a CPU/GPU concurrent layouts by using different recipes.

Lee, Youngjun↗

Development of a Digital Twin for Hydrogen Dispersion and Safety Assessment in an Electrolyzer Based Hydrogen Production Facility

Digital twin models are virtual representations of physical systems that use real-time data to simulate and optimize performance. This study presents the development and initial implementation of a digital twin (DT) for the electrolyzer-based hydrogen production facility at NREL's Advanced Research on Integrated Energy Systems (ARIES), focused on enhancing safety and optimizing sensor placement through physics-based simulations and metadata integration. The DT incorporates detailed facility-specific information, including component layout, leak locations, and controlled release parameters, to model hydrogen dispersion under varying environmental conditions. Using steady-state computational fluid dynamics (CFD) simulations informed by real meteorological data, such as wind speed, direction, and vertical wind profiles, the DT enables visualization of hydrogen plume behavior and spatial concentration distributions. Comparative analysis between high and low wind speed scenarios illustrates the significant influence of wind dynamics on plume shape and extent, with horizontal momentum dominating dispersion at higher speeds, while buoyancy effects become more prominent under low wind conditions. These simulations generate a rich dataset embedded within the DT, allowing users to assess potential leak outcomes and identify optimal sensor locations based on concentration thresholds. The model supports scenario-based analysis to guide safety strategies and equipment deployment for open-area hydrogen infrastructure. The digital twin thus serves as a dynamic platform for virtual prototyping, providing predictive insight into hydrogen behavior and enhancing risk-informed decision-making. This initial phase establishes a validated foundation for future integration of transient, uncontrolled leak scenarios and real-time sensor feedback, positioning the DT as a critical tool for safety design, operational planning, and adaptive monitoring in hydrogen systems. Overall, the approach demonstrates the value of combining environmental data with digital simulations to inform safer and more efficient deployment of hydrogen technologies.

08 HYDROGEN↗

Defects go green: using defects in nanomaterials for renewable energy and environmental sustainability

Induction of point defects in nanomaterials can bestow upon them entirely new physics or augment their pre-existing physical properties, thereby expanding their potential use in green energy technology. Predicting structure-property relationships for defects a priori is challenging, and developing methods for precise control of defect type, density, or structural distribution during synthesis is an even more formidable task. Hence, tuning the defect structure to tailor nanomaterials for enhanced device performance remains an underutilized tool in materials design. We review here the state of nanomaterial design through the lens of computational prediction of defect properties for green energy technology, and synthesis methods to control defect formation for optimal performance. We illustrate the efficacy of defect-focused approaches for refining nanomaterial physics by describing several specific applications where these techniques hold potential. Most notably, we focus on quantum dots for reabsorption-free solar windows and net-zero emission buildings, oxide cathodes for high energy density lithium-ion batteries and electric vehicles, and transition metal dichalcogenides for electrocatalytic green hydrogen production and carbon-free fuels.

14 SOLAR ENERGY↗

Development and case study of the liquid desiccant system module in sorption system simulation program (SorpSim)

Liquid desiccant systems (LDS) have recently seen an increase in research interest as they can utilize low-grade heat resources and separate the sensible and latent cooling loads by efficiently removing moisture in the air without cooling it to the dew point. Yet, simulation and analysis of LDS had remained complex and demanding due to the limited resources of LDS simulation tools. This work presents the new LDS module developed in the Sorption system Simulation program (SorpSim), which is an open-source and flexible platform for steady-state simulation and analysis of various sorption systems. First, the new LDS module containing a finite-difference model and an effectiveness-NTU model for the heat and mass transfer in LDS dehumidifier/regenerator component was introduced. Then the simulation results of the new module were verified using data from the literature. Lastly, a case study was carried out in SorpSim where an LDS cycle was built and simulated using the new module. The impacts of design and operating parameters on the simulated LDS performance were investigated. The parametric study revealed that a high source temperature improved moisture removal rate (MRR) but reduced the system coefficient of performance (COP); the COP increased monotonically with the desiccant solution recirculation ratio, while the MRR peaked at a ratio of 85%; and an internal solution heat exchanger with UA of 800 W/K was found to be sufficient for optimal performance under high recirculation ratios. The case study demonstrated the LDS module’s capability to facilitate the analysis of LDS design and operation. The LDS module can be further coupled with other component models in SorpSim to simulate and analyze various liquid-desiccant-based systems.

42 ENGINEERING↗

Non-trivial symmetries in quantum landscapes and their resilience to quantum noise

Very little is known about the cost landscape for parametrized Quantum Circuits (PQCs). Nevertheless, PQCs are employed in Quantum Neural Networks and Variational Quantum Algorithms, which may allow for near-term quantum advantage. Such applications require good optimizers to train PQCs. Recent works have focused on quantum-aware optimizers specifically tailored for PQCs. However, ignorance of the cost landscape could hinder progress towards such optimizers. In this work, we analytically prove two results for PQCs: (1) We find an exponentially large symmetry in PQCs, yielding an exponentially large degeneracy of the minima in the cost landscape. Alternatively, this can be cast as an exponential reduction in the volume of relevant hyperparameter space. (2) We study the resilience of the symmetries under noise, and show that while it is conserved under unital noise, non-unital channels can break these symmetries and lift the degeneracy of minima, leading to multiple new local minima. Based on these results, we introduce an optimization method called Symmetry-based Minima Hopping (SYMH), which exploits the underlying symmetries in PQCs. Our numerical simulations show that SYMH improves the overall optimizer performance in the presence of non-unital noise at a level comparable to current hardware. Overall, this work derives large-scale circuit symmetries from local gate transformations, and uses them to construct a noise-aware optimization method.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗