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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 OSTI2023

Targeted Particle Fractionation Technologies: Proof of Concept

Most methods of particle-size analysis involve particle fractionation which, is often done by filtration or the use of screens. This paper provides proof of concept testing for new in-pipe particle fractionation technologies that can be used at laboratory to industrial scales. These technologies are extensions of recent advancements in bump arrays as well as testing of new inline angled-to-the-flow slats, and advanced boycott-based Avalanche separation technologies. Experiments were conducted for three targeted particle fractionation technologies to evaluate the in-pipe removal of oversized sands in Newtonian slurries prior to the introduction of bump arrays. The mesofluidic system uses an array of staggered posts as configured in a bump array for Newtonian slurry conditions. The methods and results of these experiments are described in this paper. This information could be applied in most industrial and laboratory systems to rapidly remove oversized particles from a flowing slurry.

slurry, solids removal, particle fractionation, bu↗
DOE OSTI2023

Cyber-Informed Engineering Principles: What’s in it for me?

CIE is an emerging method to integrate cybersecurity considerations into the conception, design, development, and operation of any physical system that has digital connectivity, monitoring, or control. CIE complements—but does not replace—the application of cybersecurity standards or practices currently in place within an organization. Rather, it expands cybersecurity decisions into the engineering space, not by asking engineers to become cyber experts, but by calling on engineers to apply engineering tools and make engineering decisions that improve cybersecurity outcomes. CIE examines the engineering consequences that a sophisticated cyber attacker could achieve, and drives engineering changes that may provide deterministic mitigations to limit or eliminate those consequences. Engineers and technicians that design critical energy infrastructure installations can integrate the 12 principles of CIE into each phase of the engineering lifecycle, from concept to retirement. These principles are aimed at system or design engineers, operators, and technicians, rather than software engineers or operational cybersecurity practitioners, because the engineers who design, build, operate, and maintain the physical infrastructure are best positioned to leverage a system’s engineering design to diminish the severity of cyber attacks or digital technology failures. This approach creates new opportunities for engineering teams—and not just cybersecurity teams—to secure the system using the physics and mechanics of engineering controls—not just digital monitoring and controls.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2018

An Ensemble Optimization Framework for Coupled Design of Hydropower Contracts and Real-Time Reservoir Operating Rules

Often, revenues from hydropower generation depend on the operator's ability to provide firm power in the presence of uncertain inflows. The primary options available for optimizing revenue are negotiation of a firm power contract before operations begin and adjustment of the reservoir release during operations. Contract and release strategy optimization are closely coupled and most appropriately analyzed with stochastic real-time control methods. Here we use an ensemble-based approach to stochastic optimization that provides a convenient way to construct nonparametric revenue probability distributions to explore the implications of uncertainty. The firm power contract is a simplified bilateral fixed price agreement that partially insulates operator and buyer from price fluctuations. The release control laws and firm energy target are jointly optimized to maximize the operator's expected revenue. Revenue probability distributions and related spill performance statistics indicate that predictive operating strategies such as stochastic dynamic programming and model predictive control can give significantly better performance than standard deterministic operating rules. The performance obtained from batch optimization with perfect inflow information establishes a convenient upper bound on potential revenue and provides a baseline for assessing the significance of differences between real-time operating strategies. Sensitivity analysis indicates that the benefits of predictive operational strategies are greatest for reservoirs with medium nondimensional residence times and less important for reservoirs with large residence times. Overall, probabilistic analysis of the coupled hydropower contract-operations problem provides a realistic way to assess revenue and risk for reservoirs that must provide firm power when inflows are uncertain.

13 HYDRO ENERGY↗
DOE OSTI2019

Stochastic Molecular Dynamics

I can not pass up the opportunity to honor Graeme Bird, a true gentleman and a real scholar, if there ever was one. When we first met at a rarefied gas dynamics conference, it was instant mutual admiration. Furthermore, we met rarely thereafter at subsequent rarefied gas meetings since I attended them infrequently as a physicist interested in hydrodynamics, where often even a rarefied gas without deterministic collisions can serve as a simple fluid model but Graeme attended them regularly. In that rst meeting I became aware of DSMC, read Graeme paper and found to my astonishment that the only reference in that paper was to my molecular dynamics work2. Indeed DSMC is computationally faster competitor to molecular dynamics and it is this feature that I would like to emphasize in this brief note. It is for this reason that I entitled this contribution \stochastic molecular dynamics". I once told Graeme that that would have been a more descriptive name to his method than DSMC. DSMC is also a good demonstration that an algorithm developed for an entirely different purposes can also be very useful for other applications.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2025

A Novel LDPP-MADDPG Approach for Distributed Power Allocation in mmWave Cellular Networks

This paper considers the problem of distributed beam scheduling and power allocation problem in millimeter- Wave (mmWave) cellular networks, in which multiple Base Stations (BSs) operate as individual operators over a shared spectrum. We propose a novel learning-aided approach that integrates the Lyapunov Drift-Plus-Penalty (LDPP) framework and Multi-agent Deep Deterministic Policy Gradient (MADDPG) reinforcement learning algorithms. This offers a powerful approach to learning stable and constraint-aware policies, reaping the joint benefit of both LDPP and MADDPG, in complex multiagent environments. The major challenge for this approach is to integrate these two approaches in a meaningful and effective manner. The key idea to solve this problem is to introduce a novel feature of local observation that incorporates potential negative value of the reward function due to the stochastic constraints introduced by the LDPP framework. Empirical results demonstrate that our proposed scheme outperforms the baseline methods under various conditions.

99 - GENERAL AND MISCELLANEOUS↗
DOE OSTI2022

GANISP: A GAN-Assisted Importance Splitting Probability Estimator: Preprint

To reduce the variance of rare event probability estimator, genealogical importance splitting marches towards a rare event by iteratively selecting and replicating realizations that are headed towards a rare event. The replication step is made difficult when applied to deterministic systems as the initial conditions of the offspring realizations need to be modified. Typically, a random perturbation is applied to the offspring to differentiate their trajectory from the parent realization. It is shown that a random perturbation strategy may be effective for some systems but may also fail for others, thereby preventing variance reduction in the probability estimate. To address this limitation, it is proposed to use a generative model such as a Generative Adversarial Network (GAN) to generate perturbations that are consistent with the attractor of the dynamical system. The GAN-assisted Importance SPlitting method (GANISP) improves the variance reduction for the system targeted. An implementation of the method is available in a companion repository (https://github.com/NREL/GANISP).

generative adversarial network↗
DOE OSTI2020

A signal compensation based cascaded PI control for an industrial heat exchange system

Since the characteristics of the industrial heat exchange system (HES) are drastically affected by variations of the steam pressure, ambient temperature and water quality, it is difficult for the classical cascade PI control system to meet the desirable control objectives. Therefore, in this paper, a deterministic linear model with unmodeled dynamics is used to describe the dynamic characteristics of the HES. It should be noted that the unmodeled dynamics at the previously sampled instant can be calculated using actual measurements and that the tracking error, which includes effects of the rate of changes of unmodeled dynamics on the controlled model, can be accurately determined. An additional compensating signal is obtained with the feedforward control together with a one-step optimal control law. Consequently, the cascade PI control strategy with the signal compensation is established. Furthermore, the simulation and industrial application show that the proposed method can effectively improve the performance of the cascade PI control system, especially when the unmodeled dynamics is subjected to unknown variations.

42 ENGINEERING↗
DOE OSTI2025

Laser-Modulation-Driven X-Ray Pulse Shaping in Regenerative Amplifier Free-Electron Lasers

In this Letter, we present a robust method for generating custom-shaped, coherent hard x-ray pulses in regenerative amplifier free-electron lasers (RAFELs) using laser-induced energy modulation of the electron beam. A temporally shaped optical modulation imprints an optical-wavelength energy pattern on the beam, which interacts with the recirculated seed in the x-ray cavity to generate spectral sidebands. These sidebands lie outside the Bragg reflection bandwidth and are extracted as out-coupled radiation, while the seed is retained for continued amplification, enabling a novel mechanism for both output coupling and pulse shaping. Furthermore, this approach allows deterministic control over the spectral and temporal properties of the emitted x-rays, including multicolor generation, twin-pulse structures, pulse duration tuning, and complex temporal waveforms. Importantly, it does not require modification of the RAFEL cavity or optics and is fully compatible with high-repetition-rate operation, offering a practical pathway to deliver coherent, shaped, and on-demand x-ray pulses for advanced time-resolved and nonlinear x-ray science.

Free-electron lasers↗
DOE OSTI2022

Adaptive Generation of Training Data for ML Reduced Model Creation

Machine learning proxy models are often used to speed up or completely replace complex computational models. The greatly reduced and deterministic computational costs enable new use cases such as digital twin control systems and global optimization. The challenge of building these proxy models is generating the training data. A naive uniform sampling of the input space can result in a non-uniform sampling of the output space of a model. This can cause gaps in the training data coverage that can miss finer scale details resulting in poor accuracy. While larger and larger data sets could eventually fill in these gaps, the computational burden of full-scale simulation codes can make this prohibitive. In this paper, we present an adaptive data generation method that utilizes uncertainty estimation to identify regions where training data should be augmented. By targeting data generation to areas of need, representative data sets can be generated efficiently. The effectiveness of this method will be demonstrated on a simple one-dimensional function and a complex multidimensional physics model.

Cianciosa, Mark↗
DOE OSTI2023

A Gridded Solar Irradiance Ensemble Prediction System Based on WRF-Solar EPS and the Analog Ensemble

The WRF-Solar Ensemble Prediction System (WRF-Solar EPS) and a calibration method, the analog ensemble (AnEn), are used to generate calibrated gridded ensemble forecasts of solar irradiance over the contiguous United States (CONUS). Global horizontal irradiance (GHI) and direct normal irradiance (DNI) retrievals, based on geostationary satellites from the National Solar Radiation Database (NSRDB) are used for both calibrating and verifying the day-ahead GHI and DNI predictions (GDIP). A 10-member ensemble of WRF-Solar EPS is run in a re-forecast mode to generate day-ahead GDIP for three years. The AnEn is used to calibrate GDIP at each grid point independently using the NSRDB as the “ground truth”. Performance evaluations of deterministic and probabilistic attributes are carried out over the whole CONUS. The results demonstrate that using the AnEn calibrated ensemble forecast from WRF-Solar EPS contributes to improving the overall quality of the GHI predictions with respect to an AnEn calibrated system based only on the deterministic run of WRF-Solar. In fact, the calibrated WRF-Solar EPS’s mean exhibits a lower bias and RMSE than the calibrated deterministic WRF-Solar. Moreover, using the ensemble mean and spread as predictors for the AnEn allows a more effective calibration than using variables only from the deterministic runs. Finally, it has been shown that the recently introduced algorithm of correction for rare events is of paramount importance to obtain the lowest values of GHI from the calibrated ensemble (WRF-Solar EPS AnEn), qualitatively consistent with those observed from the NSRDB.

14 SOLAR ENERGY↗
DOE OSTI2025

High‐Temperature Single‐Photon Emission From Covalently Functionalized van der Waals Heterostructures

Two-dimensional (2D) transition metal dichalcogenides (TMDs) such as tungsten diselenide (WSe 2 ) are attractive nanomaterials for quantum information applications due to single-photon emission (SPE) from intrinsic atomic defects. Defect and strain engineering techniques have been developed to produce high purity, deterministically placed SPE in WSe 2 . However, a major challenge in the application of these techniques is the low temperature required to observe defect-bound TMD exciton emission, typically limiting SPE to T < 30 K. SPE at higher temperatures either loses purity or requires integration into complex devices such as optical cavities. Here, 2D heterostructure engineering and molecular functionalization are combined to achieve high purity (>90%) SPE in strained WSe 2 persisting to over T = 90 K. Covalent diazonium functionalization of graphite in layered WSe 2 /graphite heterostructures maintains high purity up to T = 90 K and single-photon source integrity up to T = 115 K. This method preserves the best qualities of SPE from WSe 2 while increasing working temperature to more than three times the typical range. This work demonstrates the versatility of surface functionalization and heterostructure design to synergistically improve the properties of quantum emission and offers new insights into the phenomenon of SPE from 2D materials.

2D materials↗
DOE OSTI2019

Demonstration of Comprehensive Ex-Vessel Fluence Capability

Several recent developments in the Consortium for Advanced Simulation of Light Water Reactors’ (CASL) Virtual Environment for Reactor Applications (VERA) were tested to highlight its capability to perform ex-vessel fluence and reaction rate calculations. VERA offers unique capabilities for integrating the deterministic neutronics code, MPACT, with Shift, a Monte Carlo code, to perform high-fidelity in-core and ex-core radiation transport. Applications such as pressure vessel fluence, ex-core detector response, and coupon irradiation analyses take advantage of this coupling. For these applications, MPACT performs the in-core radiation transport with temperature feedback and isotopic depletion through the direct coupling with the CTF subchannel thermal-hydraulics code. Then, MPACT provides the fission source to Shift for a follow-on fixed source radiation transport calculation that tallies all the ex-core responses of interest for each time-dependent statepoint. The variance reduction method, CADIS, which is implemented in Shift, allows for efficient performance of ex-core transport for calculation of ex-core quantities of interest. This milestone report identifies limitations to the current methodology in place and showcases VERA’s current capability to model ex-core quantities of interest.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

Deep Reinforcement Scheduling of Energy Storage Systems for Real-time Voltage Regulation in Unbalanced LV Networks with High PV Penetration

The ever-growing higher penetration of distributed energy resources (DERs) in low-voltage (LV) distribution systems brings both opportunities and challenges to voltage support and regulation. This paper proposes a deep reinforcement learning (DRL)-based scheduling scheme of energy storage systems (ESSs) to mitigate system voltage deviations in unbalanced LV distribution networks. The ESS-based voltage regulation problem is formulated as a multi-stage quadratic stochastic program, with the objective of minimizing the expected total daily voltage regulation cost while satisfying operational constraints. While existing voltage regulation methods are mostly focused on onetime- step control, this paper explores a day-horizon systemwide voltage regulation problem. In other words, the size of action and state spaces are extremely high-dimensional and need to be delicately handled. Furthermore, in order to overcome the difficulty of modeling uncertainties and develop a realtime solution, a learn-to-schedule feedback control framework is proposed by adapting the problem to a model-free DRL setting. The proposed algorithm is tested on a customized 6-bus system and a modified IEEE 34-bus system. Simulation results validate the effectiveness and near-optimality of voltage regulation by ESS in comparison with a deterministic quadratic program solution.

Wang, Shengyi↗
DOE OSTI2021

Sensitivity Analysis of Particle-In-Cell Modeling Parameters in Settling Bed, Bubbling Fluidized Bed and Circulating Fluidized Bed

The objective of the work presented is to perform a preliminary sensitivity analysis of particle-in-cell (PIC) model parameters when applied to settling bed, bubbling fluidized bed, and circulating fluidized bed simulations. These examples correspond to widely different flow conditions commonly seen in chemical engineering applications. Simulations were performed using the PIC method in the open-source software Multiphase Flow with Interphase eXchanges (MFiX) developed by the National Energy Technology Laboratory (NETL). As part of the non-intrusive uncertainty quantification (UQ) analysis, simulation campaigns were generated using Nodeworks. Sampling locations or settings for PIC model parameters were determined using the Latin Hypercube method. Response surfaces were created using radial basis functions (RBF), and Sobol’ indices were estimated to quantify the influence of model parameters on the quantities of interest (QoI). This study marks a first step towards systematically determining optimal ranges for model parameters used in MFiX-PIC. Based on limited experience, it is expected that these values would depend strongly on flow conditions. Given the complexity of the multiphase flow systems under analysis, a non-intrusive UQ based approach is used to identify the most influential parameters in each case. This prior knowledge will help in proposing an effective design of experiments (DoE) and determine optimal parameters through techniques such as deterministic or Bayesian calibration, which will be pursued in the future.

42 ENGINEERING↗
DOE OSTI2019

Diffusion tensor imaging of the kidney in healthy controls and in children and young adults with autosomal recessive polycystic kidney disease

Objective: To compare diffusion tensor imaging (DTI) of the kidneys and its derived parameters in children with autosomal recessive polycystic kidney disease (ARPKD) versus healthy controls. Methods: In a prospective IRB-approved study, we evaluated the use of DTI to compare kidney parenchyma FA values in healthy controls (age-matched children with no history of renal disease) versus patients with ARPKD. A 20-direction DTI with b-values of b = 0 s/mm{sup 2} and b = 400 s/mm{sup 2} was used to acquire data in coronal direction using a fat-suppressed spin-echo echo-planar sequence. Diffusion Toolkit and TrackVis were used for analysis and segmentation. TrackVis was used to draw regions of interest (ROIs) covering the entire volume of the renal parenchyma, excluding the collecting system. Fibers were reconstructed using a deterministic fiber tracking algorithm. The FA values based on the ROI data, mean length, and volume of the tracks based on the fiber tracking data were recorded. Results: Eight healthy controls (mean age = 12.9 years ± 4.0; 1/8 males) and six ARPKD participants (mean age = 13.8 years ± 8.5; 5/6 males) were included in the study. Compared to healthy controls, patients with ARPKD had significantly lower FA values (0.33 ± 0.03 vs. 0.25 ± 0.02, p = 0.002) and mean track length (16.73 ± 3.43 vs. 11.61 ± 1.29 mm, p = 0.005). Conclusion: DTI of the kidneys shows significantly lower FA values and mean track length in children and young adults with ARPKD compared to normal subjects. DTI of the kidney offers a novel approach for characterizing renal disease based on changes in diffusion anisotropy and kidney structure.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2022

DECOVALEX-2023, Task F Specification, Revision 8

This report is the revised (Revision 8) Task F specification for DECOVALEX-2023. Task F is a comparison of the models and methods used in deep geologic repository performance assessment. The task proposes to develop a reference case for a mined repository in a fractured crystalline host rock and a reference case for a mined repository in a salt formation. Teams may choose to participate in the comparison for either or both of the reference cases. For each reference case, a common set of conceptual models and parameters describing features, events, and processes that impact performance will be given, and teams will be responsible for determining how best to implement and couple the models. The comparison will be conducted in stages, beginning with a comparison of key outputs of individual process models, followed by a comparison of a single deterministic simulation of the full reference case, and moving on to uncertainty propagation and uncertainty and sensitivity analysis. This report provides background information, a summary of the proposed reference cases, and a staged plan for the analysis.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

DECOVALEX-2023 Task F Specification (Rev. 9)

This report is the revised (Revision 9) Task F specification for DECOVALEX-2023. Task F is a comparison of the models and methods used in deep geologic repository performance assessment. The task proposes to develop a reference case for a mined repository in a fractured crystalline host rock (Task F1) and a reference case for a mined repository in a salt formation (Task F2). Teams may choose to participate in the comparison for either or both reference cases. For each reference case, a common set of conceptual models and parameters describing features, events, and processes that impact performance will be given, and teams will be responsible for determining how best to implement and couple the models. The comparison will be conducted in stages, beginning with a comparison of key outputs of individual process models, followed by a comparison of a single deterministic simulation of the full reference case, and moving on to uncertainty propagation and uncertainty and sensitivity analysis. This report provides background information, a summary of the proposed reference cases, and a staged plan for the analysis.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

DECOVALEX-2023: Task F Specification (Revision 10)

This report is the revised (Revision 10) Task F specification for DECOVALEX-2023. Task F is a comparison of the models and methods used in deep geologic repository performance assessment. The task proposes to develop a reference case for a mined repository in a fractured crystalline host rock (Task F1) and a reference case for a mined repository in a salt formation (Task F2). Teams may choose to participate in the comparison for either or both reference cases. For each reference case, a common set of conceptual models and parameters describing features, events, and processes that impact performance will be given, and teams will be responsible for determining how best to implement and couple the models. The comparison will be conducted in stages, beginning with a comparison of key outputs of individual process models, followed by a comparison of a single deterministic simulation of the full reference case, and moving on to uncertainty propagation and uncertainty and sensitivity analysis. This report provides background information, a summary of the proposed reference cases, and a staged plan for the analysis.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗