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Results for “Efficiency maximization”

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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Maximizing the efficiency of plasma-based lepton accelerators

The next generation of particle accelerators will likely rely on compact accelerating structures to achieve very high gradients; one such candidate is accelerators using plasmas for the accelerating structures. Because of the small length scales of these structures, they can also be prone to the beam break-up instability, which would spoil the quality of the beam and leave it unsuitable for many applications. The goal of this project is to develop a framework for understanding the instabilities in plasma accelerators using language from conventional linear accelerator instabilities, such as wake fields and wake functions. During the course of this Phase I, we benchmarked a pseudo-spectral particle-in-cell code to determine its suitability for computing wake functions, and developed a procedure for extracting wake functions from a sequence of simulations using this code.

43 PARTICLE ACCELERATORS↗
NASA NTRS1978

Active controls technology to maximize structural efficiency

The implication of the dependence on active controls technology during the design phase of transport structures is considered. Critical loading conditions are discussed along with probable ways of alleviating these loads. Why fatigue requirements may be critical and can only be partially alleviated is explained. The significance of certain flutter suppression system criteria is examined.

Hoy, J. M.↗
DOE OSTI2017

Nonlinear Dynamic Model-Based Multiobjective Sensor Network Design Algorithm for a Plant with an Estimator-Based Control System

Here, a novel sensor network design (SND) algorithm is developed for maximizing process efficiency while minimizing sensor network cost for a nonlinear dynamic process with an estimator-based control system. The multiobjective optimization problem is solved following a lexicographic approach where the process efficiency is maximized first followed by minimization of the sensor network cost. The partial net present value, which combines the capital cost due to the sensor network and the operating cost due to deviation from the optimal efficiency, is proposed as an alternative objective. The unscented Kalman filter is considered as the nonlinear estimator. The large-scale combinatorial optimization problem is solved using a genetic algorithm. The developed SND algorithm is applied to an acid gas removal (AGR) unit as part of an integrated gasification combined cycle (IGCC) power plant with CO 2 capture. Due to the computational expense, a reduced order nonlinear model of the AGR process is identified and parallel computation is performed during implementation.

Lexicographic optimization↗
DOE OSTI2018

Experimental demonstration of voltage-matched two-terminal tandem minimodules

Mechanically stacked tandem solar cells are a potential near-term solution for increasing the efficiency of photovoltaic modules. Practical implementation requires an interconnection approach that maximizes efficiency and minimizes complexity and cost. Connecting the top and bottom cells in a voltage-matched configuration allows two-terminal modules to be fabricated without altering the cell design or processing methods. Here, we experimentally demonstrate two-terminal voltage-matched GaInP 2 / Si minimodules. The two-terminal minimodules performed just as well as four terminal configurations when voltage-matching requirements were met. The magnitude of the efficiency loss experienced by the voltage-matched minimodule when voltage-matched conditions were not met depends on whether the voltage was constrained by the GaInP 2 or Si cells. Monte Carlo simulations also indicate that the two-terminal voltage-matched tandems respond to small cell-to-cell parameter variations in a similar manner as four terminal tandems.

14 SOLAR ENERGY↗
DOE OSTI2016

A matrix-algebraic formulation of distributed-memory maximal cardinality matching algorithms in bipartite graphs

We describe parallel algorithms for computing maximal cardinality matching in a bipartite graph on distributed-memory systems. Unlike traditional algorithms that match one vertex at a time, our algorithms process many unmatched vertices simultaneously using a matrix-algebraic formulation of maximal matching. This generic matrix-algebraic framework is used to develop three efficient maximal matching algorithms with minimal changes. The newly developed algorithms have two benefits over existing graph-based algorithms. First, unlike existing parallel algorithms, cardinality of matching obtained by the new algorithms stays constant with increasing processor counts, which is important for predictable and reproducible performance. Second, relying on bulk-synchronous matrix operations, these algorithms expose a higher degree of parallelism on distributed-memory platforms than existing graph-based algorithms. We report high-performance implementations of three maximal matching algorithms using hybrid OpenMP-MPI and evaluate the performance of these algorithm using more than 35 real and randomly generated graphs. On real instances, our algorithms achieve up to 200 × speedup on 2048 cores of a Cray XC30 supercomputer. Even higher speedups are obtained on larger synthetically generated graphs where our algorithms show good scaling on up to 16,384 cores.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1993

Fabricating binary optics: An overview of binary optics process technology

A review of binary optics processing technology is presented. Pattern replication techniques have been optimized to generate high-quality efficient microoptics in visible and infrared materials. High resolution optical photolithography and precision alignment is used to fabricate maximally efficient fused silica diffractive microlenses at lambda = 633 nm. The degradation in optical efficiency of four-phase-level fused silica microlenses resulting from an intentional 0.35 micron translational error has been systematically measured as a function of lens speed (F/2 - F/60). Novel processes necessary for high sag refractive IR microoptics arrays, including deep anisotropic Si-etching, planarization of deep topography and multilayer resist techniques, are described. Initial results are presented for monolithic integration of photonic and microoptic systems.

Stern, Margaret B.↗
DOE OSTI2024

Improving Efficiency of Off-Road Vehicles by Novel Integration of Electric Machines and Advanced Combustion Engines

Modern off-road equipment will increasingly rely on electrified implements that will deliver precision control with a smaller footprint than hydraulics. The primary energy converter, however, will be an onboard reciprocating internal combustion engine because of the power density of hydrocarbon fuels in comparison to electrical energy storage and the remote locations where much of this equipment is deployed. Adding energy storage and electric machines creates opportunities to improve efficiency while reducing emissions. This program investigated approaches to take advantage of the extra flexibility that an enhanced electrical system to enable high-efficiency, low-emissions combustion technologies. The current program evaluated hybridization of both the torque application and air-handling systems to maximize efficiency while minimizing cost. This program designed, analyzed and tested a hybrid off-road vehicle consisting of a series electric powertrain with energy storage, an electrified air system, and a 33% downsized diesel engine. Detailed comparisons were made between the base powertrain and the developed powertrain using powertrain simulations, engine testing, and vehicle testing. The key results of the study are: • The resulting vehicle reduces fuel consumption by 5% to 15% at equal productivity. The primary improvements were due to recovery of regenerative braking losses for cycles where large transients are encountered. • The electrified air system was an enabler to allow engine downsizing. This was most important for duty-cycles where the engine primarily operated at moderate loads and had few low speed high torque conditions. • Engine level improvements showed re-optimization of the powertrain is possible when electrified air handing is available. Increased exhaust gas recirculation and advanced injection timing allowed up to a 15% reduction in brake specific fuel consumption at equal NOx and transient response. Compared to the larger engine, the downsized engine achieves up to an 18% reduction in brake specific fuel consumption over the non-road transient cycle. • The life cycle analysis and total cost of ownership study showed that the hybrid powertrain has the potential to reduce 5-year CO2 and total cost of ownership by ~6% over the baseline vehicle. The results also indicated that a pure battery electric vehicle is not feasible in this application and is likely to increase the CO2 emissions due to the CO2 from battery production. A hybrid powertrain with low carbon fuels shows the potential to substantially reduce CO2 and total cost of ownership.

02 PETROLEUM↗
NASA NTRS1982

An efficient low- and moderate-resolution spectrograph for the Hale telescope

A new low-to-moderate resolution spectrograph has been designed and built for the Cassegrain focus of the Hale 5.08-meter telescope. To maximize efficiency, resolution, and wavelength coverage the light is divided into two spectra regions by a dichroic filter behind the entrance slit, after which there are two completely separate spectrographs. The blue spectrograph operates from 3200 A to 5200 A while the red one goes from 5200 A to 10,000 A. The red detector is an 800 x 800 TI CCD while the blue detector is a 320 x 512 RCA CCD or a Shectrograph image pulse-counting system. A Boksenberg IPCS can also be mounted on the blue camera. The overall efficiency of the Cassegrain telescope, spectrographs, and CCD's combined, ranges from 5 percent to 13 percent between 3600 A and 8200 A. The spectrograph is usable from 3200 A to 10,400 A.

Oke, J. B.↗
DOE OSTI2025

A GPU Accelerated Mixed‐Precision Finite Difference Informed Random Walker (FDiRW) Solver for Strongly Inhomogeneous Diffusion Problems

In nature, many complex multi‐physics coupling problems exhibit significant diffusivity inhomogeneity, where one process occurs several orders of magnitude faster than others temporally. Simulating rapid diffusion alongside slower processes demands intensive computational resources due to the necessity for small time steps. To address these computational challenges, we have developed an efficient numerical solver named Finite Difference informed Random Walker (FDiRW). In this study, we propose a GPU‐accelerated, mixed‐precision configuration for the FDiRW solver to maximize efficiency through GPU multi‐threaded parallel computation and lower precision computation. Numerical evaluation results reveal that the proposed GPU‐accelerated mixed‐precision FDiRW solver can achieve a 117× speedup over the CPU baseline, while an additional 1.75× speedup is achieved by employing lower precision GPU computation. Notably, for large model sizes, the GPU‐accelerated mixed‐precision FDiRW solver demonstrates strong scaling with the number of nodes used in simulation. When simulating radionuclide absorption processes by porous wasteform particles with a medium‐sized model of 192 × 192 × 192, this approach reduces the total computational time to 10 min, enabling the simulation of larger systems with strongly inhomogeneous diffusivity.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Interwell carrier transport in InGaN/(In)GaN multiple quantum wells

Uniform carrier distribution between quantum wells (QWs) of multiple QW light emitting diodes (LEDs) and laser diodes is important for the efficiency of device operation. In lasers, the uniform distribution ensures that all the QWs contribute to lasing; in LEDs, it enables high power operation with minimal Auger losses and a maximal efficiency. The carrier distribution between the QWs takes place via interwell (IW) transport. In polar GaN-based structures, the transport might be hindered by the strong carrier confinement and the internal electric fields. In this work, we study the IW transport in InGaN/(In)GaN multiple QW structures typical for ultraviolet-emitting devices with different well and barrier parameters. Experiments have been performed by means of time-resolved photoluminescence. We find that the IW transport rate is limited by the hole thermionic emission, which for InGaN/GaN QWs produces long transport times, ~1 ns per well, and a nonuniform IW carrier distribution. However, adding 5% In to the barriers completely changes the situation with the transport time decreasing by a factor of four and the hole thermionic emission energy from 200 meV to 70 meV. Finally, this study shows that using InGaN barriers is a promising pathway toward efficient high power InGaN LEDs.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1992

A low-power, high-efficiency Ka-band TWTA

NASA has developed a new class of Ka-band TWT amplifiers (TWTAs) which achieve their high efficiency/low power performance goals by means of an advanced dynamic velocity taper (DVT). The DVT is characterized by a continuous, nonlinear reduction in helix pitch from its initial synchronous value in the output section of the TWT to near the end of the helix. Another efficiency-maximizing feature is the inclusion of a multistage depressed collector employing oxygen-free, high-conductivity Cu electrodes treated for secondary electron emission suppression by means of ion bombardment. An efficiency of 43 percent is expected to be reached.

Curren, Arthur N.↗
DOE OSTI2025

Electric Vehicle and Charging Infrastructure Assessment in Cold-Weather Climates: A Case Study of Fairbanks, Alaska

The purpose of this report is to determine the effects that extreme cold temperatures have on electric vehicles (EVs) and electric vehicle supply equipment (EVSE). The adoption of EVs in extreme cold weather presents challenges that require careful analysis of efficiency and charging infrastructure. This report, "Electric Vehicle and Charging Infrastructure Assessment in Cold-Weather Climates: A Case Study of Fairbanks, Alaska," explores how EVs and EVSE perform in temperatures as low as -40 degrees C (-40 degrees F), focusing on real-world data from Teslas in Alaskan winter conditions. The findings indicate that EVs can successfully function in extreme cold, though efficiency is significantly affected. Vehicles stored in heated environments outperformed those stored outdoors, with efficiency dropping by up to 69% for outdoor storage. Despite these challenges, none of the vehicles experienced failures that prevented travel. Storing EVs indoors led to benefits such as faster preconditioning and improved efficiency, while charging in extreme cold, though slower, remained functional. Ultimately, the report concludes that with proper precautions and best practices, EVs are viable transportation solutions in cold climates. Investing in enclosed, heated storage is recommended to maximize efficiency and minimize battery strain. As advancements in battery chemistry and thermal management progress, EV adoption in extreme climates is expected to become even more feasible.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2019

Solution-Based Adaptivity as a Paradigm for Computational Fluid Dynamics

This is the final report for the DOE Early Career award. Through innovation in error estimation and solution-based adaptation methods we strive to dramatically improve the efficiency and robustness of computational science and engineering simulations. By solution-based error estimation and adaptation we refer to techniques for estimating numerical error and efficiently reducing it through targeted discretization changes. In such a setting, high-order methods play a key role, though they are just one mechanism for efficient accuracy improvement. Other mechanisms include well known mesh size and stretching optimization, as well as less-practiced mesh motion and basis optimization. With additional work on the latter, we are integrating these techniques into one adaptive suite that maximizes efficiency and robustness of Computational Fluid Dynamics (CFD) calculations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1999

Streamlining Software Aspects of Certification: Report on the SSAC Survey

The aviation system now depends on information technology more than ever before to ensure safety and efficiency. To address concerns about the efficacy of software aspects of the certification process, the Federal Aviation Administration (FAA) began the Streamlining Software Aspects of Certification (SSAC) program. The SSAC technical team was commissioned to gather data, analyze results, and propose recommendations to maximize efficiency and minimize cost and delay, without compromising safety. The technical team conducted two public workshops to identify and prioritize software approval issues, and conducted a survey to validate the most urgent of those issues. The SSAC survey, containing over two hundred questions about the FAA's software approval process, reached over four hundred industry software developers, aircraft manufacturers, and FAA designated engineering representatives. Three hundred people responded. This report presents the SSAC program rationale, survey process, preliminary findings, and recommendations.

Hayhurst, Kelly J.↗
DOE OSTI2023

Data Center Facility Monitoring with Physics Aware Approach

U.S. Department of Energy's National Renewable Energy Laboratory (NREL) hosts one of the world's most energy-efficient HPC data centers; this system uses component-level warm-water liquid cooling to efficiently remove heat from the data center and capture it for reuse in the building or rejection to the atmosphere. Given the complexity of this system, building data-driven tools for holistically monitoring and operating the entire data center is a priority for ensuring maximal efficiency and resiliency. In this advanced smart facility, over one million metrics are recorded per minute using state-of-the-art streaming data architecture and software to capture and process the state of the system in real time. Here we detail two efforts to effectively analyze, visualize, and interpret this large volume streaming data. We have developed a novel, flexible system for identifying and visualizing individual metric anomalies and component performance across the data center through automatic metadata extraction and physically-motivated visualization for quick interpretation. Additionally, to directly connect system maintenance to data stream processing we explore a physics informed multi-metric drift and anomaly detection application to detect scale-build up in heat exchangers.

anomaly detection↗
NASA NTRS1977

An algorithm for constrained maximization of the trace of a matrix

The 'trace' of a rectangular matrix is defined as the trace of a square matrix obtained by appending null rows (or columns) at the bottom (or right) end. The problem of maximizing the trace of a matrix, by permutations and mergers of rows and columns with constraints on the resulting size of the matrix, is of interest in comparison of maps and image-change detection. This correspondence presents an algorithm based on dynamic programming for efficient maximization of trace.

Ramapriyan, H. K.↗
DOE OSTI2022

Deep reinforcement learning based optimization for a tightly coupled nuclear renewable integrated energy system

New ways to integrate energy systems to maximize efficiency are being sought to meet carbon emissions goals. Nuclear-renewable integrated energy system (NR-IES) concepts are a leading solution that couples a nuclear power plant with renewable energy, hydrogen generation plants, and energy storage systems, such that thermal and electrical power are dispatchable to fulfill grid-flexibility requirements while also producing hydrogen and maximizing revenue. Here, this paper introduces a deep reinforcement learning (DRL)-based framework to address the complex decision-making tasks for NR-IES. The objective is to maximize revenue by generating and selling hydrogen and electricity simultaneously according to their time-varying prices while keeping the energy flow in the subsystems in balance. A Python-based simulator for a NR-IES concept has been developed to integrate with OpenAI Gym and Ray/RLlib to enable an efficient and flexible computational framework for DRL research and development. Three state-of-the-art DRL algorithms have been investigated, including two-delayed deep deterministic policy gradient (TD3), soft-actor critic (SAC), proximal policy optimization (PPO), to illustrate DRL’s superiority for controlling NR-IES by comparing it with a conventional control approach, particle swarm optimization (PSO). In this effort, PPO has shown more-stable performance and also better generalization capability than SAC and TD3. Comparisons with PSO have demonstrated that, on average, PPO can achieve 13.9% more mean episode returns from the training process and 29.4% more mean episode returns from the testing process when different hydrogen-production targets are applied.

08 HYDROGEN↗