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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Efficient Distributed Optimization of Wind Farms Using Proximal Primal-Dual Algorithms: Preprint

This paper presents a distributed approach to perform real-time optimization of large wind farms. Wind turbines in a wind farm typically operate individually to maximize their own performance regardless of the impact of aerodynamic interactions on neighboring turbines. This paper optimizes the overall power produced by a wind farm by formulating and solving a nonconvex optimization problem where the yaw angles are optimized to allow some turbines to operate in misaligned conditions and shape the aerodynamic interactions in a favorable way. The solution of the nonconvex smooth problem is tackled using a proximal primal-dual gradient method, which provably identifies a first-order stationary solution in a global sublinear manner. By adding auxiliary optimization variables for every pair of turbines that are coupled aerodynamically and properly adding consensus constraints into the underlying problem, a distributed algorithm with turbine-to-turbine message passing is obtained; this allows for turbines to be optimized in parallel using local information rather than information from the whole wind farm. This algorithm is computationally light, as it involves closed-form updates. This approach is demonstrated on a large wind farm with 60 turbines. The results indicate that similar performance can be achieved as with finite-difference gradient-based optimization at a fraction of the computational time and thus approach real-time control/optimization.

17 WIND ENERGY↗
DOE OSTI2022

Highly efficient small molecule multi-junction organic photovoltaic cells

A highly efficient multi junction photovoltaic device, such as a two, three, or four junction device, is disclosed. The multi-junction device may include a first subcell comprising a first photoactive region and a second subcell comprising a second photoactive region. The first and second photoactive regions are designed to minimize spectral overlap and maximize photocurrent across a broad absorption spectra, such as wavelengths ranging from 400 nm to 900 nm. The device may further include an inter-connecting layer, disposed between the first subcell and the second subcell, that is at least substantially transparent. By introducing a transparent interconnecting layer, a dual element (tandem) cell achieves a power conversion efficiency of 10.0±0.5%. By adding an additional (3rd) sub-cell that absorbs at the second order optical interference maximum within the stack. The triple junction cell significantly improves the quantum efficiency at shorter wavelengths, achieving a power conversion efficiency of 11.1±0.5%. Adding additional sub-cells has been shown to increase power conversion efficiency above 12%.

Che, Xiaozhou↗
DOE OSTI2020

Generation of reactive species in water film dielectric barrier discharges sustained in argon, helium, air, oxygen and nitrogen

Activation of liquids with atmospheric pressure plasmas is being investigated for environmental and biomedical applications. When activating the liquid using gas plasma produced species (as opposed to plasmas sustained in the liquid), a rate limiting step is transport of these species into the liquid. To first order, the efficiency of activating the liquid is improved by increasing the ratio of the surface area of the water in contact with the plasma compared to its volume—often called the surface-to-volume ratio (SVR). Maximizing the SVR then motivates the plasma treatment of thin films of liquids. In this paper, results are discussed from a computational investigation using a global model of atmospheric pressure plasma treatment of thin water films by a dielectric barrier discharge (DBD) sustained in different gases (Ar, He, air, N 2 , O 2 ). The densities of reactive species in the plasma activated water (PAW) are evaluated. The residence time of the water in contact with the plasma is increased by recirculating the PAW in plasma reactor. Longer lived species such as H 2 O 2aq and NO 3 - aq accumulate over time (aq denotes an aqueous species). DBDs sustained in Ar and He are the most efficient at producing H 2 O 2aq , DBDs sustained in argon produces the largest density of NO 3 - aq with the lowest pH, and discharges sustained in O 2 and air produce the highest densities of O 3aq . Finally, comparisons to experiments by others show agreement in the trends in densities in PAW including O 3aq , OH aq , H 2 O 2aq and NO 3 - aq , and highlight the importance of controlling desolvation of species from the activated water.

42 ENGINEERING↗
DOE OSTI2022

Multi-Pressure Rail System Design with Variable Pressure Control Strategy

This paper presents the design and the control method of a Multiple Pressure Rail system (MPR) with a variable pressure control logic that allows minimization of throttling loss, therefore, increasing the overall fluid power actuation efficiency. An MPR system allows controlling hydraulic actuators with a pressure control logic, as opposed to traditional flow control logics which are well established in mobile applications. A proper setting of the number of pressure rails and the pressure level in each rail permits optimizing the system efficiency of an MPR solution. MPR systems have been recently proposed with different purposes, but seldom adopt variable pressure control strategies to manage the pressure variations in the rails. Moreover, the related past work attempts to maximize the energy recovery during overrunning load conditions. This paper, instead, addresses the case of an MPR system that handles a multitude of hydraulic functions without significant overrunning loads, as it occurs in many mobile applications such as in agriculture. The paper first presents the design alternatives considered for the MPR system, including the supply, the control valves, and the controller. Second, a dedicated test rig is developed to support experimental activities and validations of a lumped parameter model developed within this research to develop the MPR control strategy. The results describe the operating features of the proposed MPR solution. By considering the case of a traditional LS system, the paper results also show how system efficiency can be highly improved, with energy savings in the order of 49%

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2012

Beyond the born approximation: Measuring the two-photon exchange effect at CLAS

Recent results from experiments at Jefferson Laboratory, Newport News VA, which measured the ratio of the electric to magnetic form factors of the proton, G{sub E}/G{sub M}, have forced us to reexamine the single photon exchange approximation in lepton-proton elastic scattering. Discrepancies between the ratio obtained via the time-tested Rosenbluth separation method and newer polarization transfer measurements, which differ by as much as a factor of three, may be resolved by considering the effect of two photon exchange (TPE) processes. The CLAS TPE experiment at Jefferson Laboratory, will determine the effect of two-photon exchange in elastic lepton-proton scattering by precisely measuring the ratio of positron-proton to electron-proton elastic cross sections over a large kinematic range (0.1 < {xi} < 0.96, 0.2 {ge} Q{sup 2} {le} 2.0 GeV{sup 2}). We accomplish this by directing the 5.5 GeV primary electron beam, provided by the Continuous Electron Beam Accelerator Facility (CEBAF), onto a set of radiators and converters to produce simultaneous and identical beams of electron and positrons which collide with our proton target. Acceptance and efficiency concerns are minimized by only considering the ratios of the elastic cross sections and by switching polarity of magnets in the beamline and the spectrometer. Guided by the results of a short 2006 test run and extensive GEANT based modeling, new shielding and beamline components were designed to maximize luminosity. We took data from November 2010 - February 2011. The unique experimental design and challenges of the TPE experiment and the current analysis status will be presented.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

ExtremeMETA: High-speed Lightweight Image Segmentation Model by Remodeling Multi-channel Metamaterial Imagers

Deep neural networks (DNNs) have heavily relied on traditional computational units, such as CPUs and GPUs. However, this conventional approach brings significant computational burden, latency issues, and high power consumption, limiting their effectiveness. This has sparked the need for lightweight networks such as ExtremeC3Net. Meanwhile, there have been notable advancements in optical computational units, particularly with metamaterials, offering the exciting prospect of energy-efficient neural networks operating at the speed of light. Yet, the digital design of metamaterial neural networks (MNNs) faces precision, noise, and bandwidth challenges, limiting their application to intuitive tasks and low-resolution images. In this study, we proposed a large kernel lightweight segmentation model, ExtremeMETA. Based on ExtremeC3Net, our proposed model, ExtremeMETA maximized the ability of the first convolution layer by exploring a larger convolution kernel and multiple processing paths. With the large kernel convolution model, we extended the optic neural network application boundary to the segmentation task. To further lighten the computation burden of the digital processing part, a set of model compression methods was applied to improve model efficiency in the inference stage. The experimental results on three publicly available datasets demonstrated that the optimized efficient design improved segmentation performance from 92.45 to 95.97 on mIoU while reducing computational FLOPs from 461.07 MMacs to 166.03 MMacs. The large kernel lightweight model ExtremeMETA showcased the hybrid design’s ability on complex tasks.

large convolution kernel↗
DOE OSTI2017

Implicit sampling combined with reduced order modeling for the inversion of vadose zone hydrological data

Bayesian inverse modeling techniques are computationally expensive because many forward simulations are needed when sampling the posterior distribution of the parameters. Here, in this paper, we combine the implicit sampling method and generalized polynomial chaos expansion (gPCE) to significantly reduce the computational cost of performing Bayesian inverse modeling. There are three steps in this approach: (1) find the maximizer of the likelihood function using deterministic approaches; (2) construct a gPCE-based surrogate model using the results from a limited number of forward simulations; and (3) efficiently sample the posterior distribution of the parameters using implicit sampling method. The cost of constructing the gPCE-based surrogate model is further decreased by using sparse Bayesian learning to reduce the number of gPCE coefficients that have to be determined. We demonstrate the approach for a synthetic ponded infiltration experiment simulated with TOUGH2. The surrogate model is highly accurate with mean relative error that is < 0.035% in predicting saturation and < 0.25% in predicting the likelihood function. The posterior distribution of the parameters obtained using our proposed technique is nearly indistinguishable from the results obtained from either an implicit sampling method or a Markov chain Monte Carlo method utilizing the full mode.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

A Computational Framework to design 3D stiffness gradient acoustic metamaterials for impedance matching

Acoustic waves play a crucial role in various applications, including medical imaging, non-destructive testing, and sonar systems. One of the significant challenges in these applications is impedance matching, which is essential for minimizing reflections and maximizing the transfer of acoustic energy between different media. Acoustic metamaterials offer a promising solution to this challenge. In addition to impedance control, gradient stiffness can enhance structural efficiency and enable spatial control of wave propagation, making it a valuable feature in acoustic metamaterial design. In this pa- per, we present our developed computational method to design 3D stiffness gradient acoustic metamaterials for impedance matching. The key steps in our approach include generating initial designs using a periodic covariance function to provide unit cells that are both periodic on the boundaries and randomly formed inside the unit cell. Furthermore, we integrated manufacturing constraints into the design process, ensuring that the structures are interconnected for fabrication. We propose two computational optimization algorithms: GenUnit, based on a non-dominated sorting genetic algorithm (NSGA-II), and MLMatch, which leverages differentiable machine learning. The two approaches are not separate contributions but complementary com- ponents of a unified framework. GenUnit requires no training data and directly interfaces with physics-based simulations, making it highly accurate but slower for large-scale exploration. In contrast, MLMatch is data-hungry during training but, once trained, enables near-instantaneous inference and broad design-space coverage. Together, they form a hybrid strategy: ML- Match rapidly explores the global design space, and GenUnit provides local refinement with high-fidelity accuracy. This balance between training cost, inference time, and precision is the motivation for including both methods in the same study. We applied this dual-algorithm framework to generate two metallic-based metamaterial designs that match the acoustic impedance of water while exhibiting a controlled gradient in stiffness (from stiff to soft). The stiffness gradient is particularly advantageous in applications where one side of the structure must interface with soft or sensitive surfaces, such as human tissue or delicate components. Here, this work paves the way for improved materials in various acoustic applications, particularly in ultrasound devices, by providing better impedance.

Metamaterial↗
DOE OSTI2019

Two-stage ignition behavior and octane sensitivity of toluene reference fuels as gasoline surrogate

Current approaches to improve the efficiency of Spark-Ignition (SI) gasoline engines have been focusing on turbocharging, increasing the compression ratio, and pursuing advanced low-temperature combustion concepts. In order to maximize these strategies, it is important to optimize the knock resistance of the fuel, and therefore knowledge of the sensitivity of the ignition process under a wide range of engine operating conditions is required. Octane sensitivity (OS), which is defined as the difference between Research Octane Number (RON) and Motored Octane Number (MON), has been introduced to represent how fuel's ignition reactivity changes relative to the primary reference fuels (n-heptane/iso-octane) within RON/MON conditions. Previous works have indicated that OS is intimately related to low temperature reactivity of the fuel, which can be revealed as two-stage heat release characteristics during an ignition event. Prompted by these findings, in this paper, we investigate the relationship between two-stage ignition behavior and OS, using chemical kinetic simulations of 24 Toluene Reference Fuels (TRFs)/ethanol blends. TRFs are ternary mixtures of n-heptane/iso-octane/toluene, which is capable of capturing aromatic content and positive values of OS of real gasoline fuels. Simulation results show that fuels with weak or no two-stage ignition behavior tend to have high OS, due to their lack of Negative Temperature Coefficient (NTC) effect and high sensitivity in ignition delay time. Leveraging such observations, we develop a correlation between two-stage behavior and OS as an OS prediction method. Two metrics that represent the strength of the two-stage ignition behavior are proposed and used as OS predictors, which are Low Temperature Heat Release percentage (LTHR%) and Heat Release Rate at the end of first stage (HRR inf ) calculated from a simple kinetic simulation. Regression analysis shows a clear trend between decreases in the proposed two-stage behavior metrics and increases in the value of OS of the fuel. We also test the new metric (LTHR%) using simulation results of 0-D reactors with imposed pressure time histories obtained from engine experiments, as well as using different TRF kinetic mechanisms. Here, the results demonstrate the effectiveness of the metric as a representation of the two-stage ignition behavior in practical combustion systems, highlighting the importance of the proposed relationship, and its potential as a simple and effective OS predictor.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2024

Assessment of the polygeneration approach in wastewater treatment plants for enhanced energy efficiency and green hydrogen/ammonia production

Wastewater treatment plants (WWTPs) offer opportunities to optimize resource utilization and enhance energy efficiency. Here, this study provides a comprehensive analysis of using the polygeneration approach in WWTPs to reduce grid energy dependence, optimize energy distribution, and utilize surplus energy for hydrogen (H 2 ) and ammonia (NH 3 ) production. Several models were employed, including photovoltaic (PV) cells, parabolic trough collectors (PTCs), steam methane reforming, and polymer electrolyte membranes, to assess the feasibility of this approach. Three scenarios were evaluated and compared: Scenario 1 (Baseline) represents the current situation, Scenario 2 maximizes the Net Present Value (NPV), and Scenario 3 minimizes NH 3 production costs. Real data from As-Samra WWTP in Jordan was used to accurately assess the feasibility of each scenario. The results show that Scenario 2 offers the highest profitability and efficiency, with a NPV of 87.48 million USD and an annual NH 3 production of 15,417 tons, reducing both grid dependency and biogas fuel consumption. Both Scenarios 2 and 3 demonstrate the ability to meet thermal demands efficiently while generating significant revenue from NH 3 production. Scenario 3, in particular, achieves competitive H 2 and NH 3 production costs. Environmentally, Scenario 2 significantly reduces annual greenhouse gas emissions by 12.66 kilotons of CO 2eq , with near-zero carbon intensity for thermal energy due to solar reliance. In conclusion, the polygeneration approach offers a promising pathway for WWTPs to achieve greater sustainability, economic gains, and reduced environmental impact, providing valuable insights for decision-makers.

42 ENGINEERING↗
DOE OSTI2024

Robust cooperative control strategy for a platoon of connected and autonomous vehicles against sensor errors and control errors simultaneously in a real-world driving environment

In a real-world driving environment, a platoon of connected and autonomous vehicles (CAVs) is subject to many internal and external disturbances, resulting in uncertain vehicle dynamics. In general, the disturbances can be categorized into two types: disturbances due to vehicle sensor errors (e.g., GPS error) and disturbances due to vehicle control errors (e.g., actuator delay). In the literature, many control strategies have been proposed to improve the robustness of the CAV platoon against uncertain vehicle dynamics induced by these disturbances. However, most of these strategies only consider one type of disturbance and cannot tackle both types of disturbances simultaneously. Furthermore, they are designed to maximize the benefits of each vehicle in the platoon independently, which can deteriorate the performance of the platoon. Here, to address these problems, this study proposes a robust cooperative control (RCC) strategy to maneuver the vehicles in the platoon cooperatively to counteract the impacts of both types of disturbances. The RCC strategy is developed based on a minimax problem, where the maximization subproblem seeks to find the worst inputs for the uncertainty terms in the vehicle dynamics equation to minimize the platoon performance, while the minimization subproblem seeks to find the optimal control decisions for all subsequent vehicles to maximize the platoon performance in the worst case. To solve the minimax problem, this study proposes a globally convergent solution algorithm. It can solve the minimax problem very efficiently to enable real time deployment of the RCC strategy. Numerical application indicates that compared to the existing methods, the RCC strategy can dramatically improve the robustness of the CAV platoon against the uncertain vehicle dynamics induced by both vehicle state detection errors and vehicle control errors. Therefore, it can maneuver the CAV platoon safely and efficiently in a real-world driving environment.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2014

Enhanced thermoelectric figure of merit in strained Tl-doped Bi{sub 2}Se{sub 3}

We explain recent experimental findings on Tl-doped Bi{sub 2}Se{sub 3} by determining the electronic and transport properties by first-principles calculations and semi-classical Boltzmann theory. Though Tl-doping introduces a momentum-dependent spin-orbit splitting, the effective mass of the carriers is essentially not modified, while the band gap is reduced. Tl is found to be exceptional in this respect as other dopants modify the dispersion, which compromises thermoelectricity. Moreover, we demonstrate that only after Tl-doping strain becomes an efficient tool for enhancing the thermoelectric performance. A high figure of merit of 0.86 is obtained for strong p-doping (7 × 10{sup 20} cm{sup −3}, maximal power factor) at 500 K under 2% tensile strain.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2018

Hydrogen Storage and Fuel Cells

Globe warming and future energy supply are two major challenges facing American public today. To overcome such challenges, it is imperative to maximize the existing fuel utilization with new conversion technologies while exploring alternative energy sources with minimal environmental impact. Hydrogen fuel cell represents a next-generation energy-efficient technology in transportation and stationary power productions. In this presentation, a brief overview of the current technology status of on-board hydrogen storage and polymer electrolyte membrane fuel cell in transportation will be provided. The directions of the future researches in these technologic fields, including a recent “big idea” of “H2@Scale” currently developed at U. S. Department of Energy, will also be discussed.

fuel cells, hydrogen storage↗
DOE OSTI2016

The Reverse Cuthill-McKee Algorithm in Distributed-Memory

Ordering vertices of a graph is key to minimize fill-in and data structure size in sparse direct solvers, maximize locality in iterative solvers, and improve performance in graph algorithms. Except for naturally parallelizable ordering methods such as nested dissection, many important ordering methods have not been efficiently mapped to distributed-memory architectures. In this paper, we present the first-ever distributed-memory implementation of the reverse Cuthill-McKee (RCM) algorithm for reducing the profile of a sparse matrix. Our parallelization uses a two-dimensional sparse matrix decomposition. We achieve high performance by decomposing the problem into a small number of primitives and utilizing optimized implementations of these primitives. Our implementation shows strong scaling up to 1024 cores for smaller matrices and up to 4096 cores for larger matrices.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

An Overview of Driver Feedback Systems for Efficiency and Safety

Driver feedback systems have the potential to improve driving safety and efficiency by providing instructions to drivers aimed at improving their driving style. There is already a rich body of available literature devoted to the derivation of energy efficient speed profiles to develop driver feedback or eco-driving systems. While most of them can be applied to any type of vehicle, their effectiveness will be maximized if their formulation involves the dynamics of the particular vehicle powertrain configuration. This paper summarizes the research trends in the development of these systems that have been reported in the literature to date classifying them according to the powertrain structure and the nature of the control strategy. The study concludes with a discussion on the remaining challenges and potential future research directions.

Rios Torres, Jackeline↗
DOE OSTI2021

Lab Home Testing of Residential Isolation Space Control to Minimize Infectious Disease Transmission in Existing Single-Family Homes

Existing evidence strongly suggests that viral infectious diseases can be transmitted via an airborne route across distances in indoor environments. Accordingly, the risk of airborne transmission within homes should be managed. The public health emergency associated with SARS-CoV-2 makes controlling airborne transmission of respired viruses in indoor environments critical, especially in poorly ventilated indoor environments. The effectiveness of engineering interventions requiring minor efforts that create a negative-pressure isolation zone (IZ) for a contagious person has yet to be tested for existing residential homes. To mitigate the risk of airborne virus transmission and maximize health protection for the population in existing single-family homes, the relative effectiveness of several control strategies are investigated in this report. While very high-efficiency MERV filtration, high ventilation rates, and other controls can help be effective, most occupants are not likely to have the time or means for advanced measures found in hospitals. This project focused on testing relatively simple efforts that utilize existing or easy to acquire materials and simple processes.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS2016

Performance Evaluation of the Approaches and Algorithms for Hamburg Airport Operations

The German Aerospace Center (DLR) and the National Aeronautics and Space Administration (NASA) have been independently developing and testing their own concepts and tools for airport surface traffic management. Although these concepts and tools have been tested individually for European and US airports, they have never been compared or analyzed side-by-side. This paper presents the collaborative research devoted to the evaluation and analysis of two different surface management concepts. Hamburg Airport was used as a common test bed airport for the study. First, two independent simulations using the same traffic scenario were conducted: one by the DLR team using the Controller Assistance for Departure Optimization (CADEO) and the Taxi Routing for Aircraft: Creation and Controlling (TRACC) in a real-time simulation environment, and one by the NASA team based on the Spot and Runway Departure Advisor (SARDA) in a fast-time simulation environment. A set of common performance metrics was defined. The simulation results showed that both approaches produced operational benefits in efficiency, such as reducing taxi times, while maintaining runway throughput. Both approaches generated the gate pushback schedule to meet the runway schedule, such that the runway utilization was maximized. The conflict-free taxi guidance by TRACC helped avoid taxi conflicts and reduced taxiing stops, but the taxi benefit needed be assessed together with runway throughput to analyze the overall performance objective.

air traffic management↗
NASA NTRS2016

Performance Evaluation of the Approaches and Algorithms using Hamburg Airport Operations

The German Aerospace Center (DLR) and the National Aeronautics and Space Administration (NASA) have been independently developing and testing their own concepts and tools for airport surface traffic management. Although these concepts and tools have been tested individually for European and US airports, they have never been compared or analyzed side-by-side. This paper presents the collaborative research devoted to the evaluation and analysis of two different surface management concepts. Hamburg Airport was used as a common test bed airport for the study. First, two independent simulations using the same traffic scenario were conducted: one by the DLR team using the Controller Assistance for Departure Optimization (CADEO) and the Taxi Routing for Aircraft58; Creation and Controlling (TRACC) in a real-time simulation environment, and one by the NASA team based on the Spot and Runway Departure Advisor (SARDA) in a fast-time simulation environment. A set of common performance metrics was defined. The simulation results showed that both approaches produced operational benefits in efficiency, such as reducing taxi times, while maintaining runway throughput. Both approaches generated the gate pushback schedule to meet the runway schedule, such that the runway utilization was maximized. The conflict-free taxi guidance by TRACC helped avoid taxi conflicts and reduced taxiing stops, but the taxi benefit needed be assessed together with runway throughput to analyze the overall performance objective.

Airport surface operations↗